GENETIC NETWORKS of PLANT DEVELOPMENT
and NUTRIENT-TREATED ROOT HAIRS
by
Christophe Liseron-Monfils
A Thesis
presented to
The University of Guelph
In partial fulfilment of the requirements
for the degree of
Doctor of Philosophy
in
Plant Agriculture
Guelph, Ontario, Canada
© Christophe Liseron-Monfils, January, 2012
ABSTRACT
GENETIC NETWORKS of PLANT DEVELOPMENT
and NUTRIENT-TREATED ROOT HAIRS
Christophe V. Liseron-Monfils
Advisor:
University of Guelph, 2012
Associate Professor Manish N. Raizada
Nitrogen and water limit global crop production. Root hairs comprise the major surface
area of plant roots for nitrogen and water absorption. Despite this, no studies have reported how
added nutrients or water alter global gene expression in root hairs in any plant species.
I demonstrate that within 3 h of added nitrate, >876 genes in maize root hairs switch up
or down. These genes overlapped with relevant maize QTLs. I also demonstrate that within 3 h
of adding water to drought-stressed roots, 1831 genes show altered expression in root hairs.
These results demonstrate that root hairs are rapid sensors of the soil environment.
Following root uptake of nitrate, it is assimilated into amino acids for transport to the
shoot; a process that involves families of genes. Understanding where and when these genes
switch on/off may facilitate improved use of nitrogen. Here, the expression of 65 nitrogen uptake
and assimilation probes was analyzed in 50 maize tissues, from germination to seed
development. The results demonstrate that subsets of nitrogen-related genes are selectively
expressed in specific organs at specific stages of development. This result identifies a higher
network level of control over nitrogen-related gene expression in maize.
An important clue to identify the master regulators responsible for such coordinated changes in
gene expression can come from identifying their promoter targets. No software program has been
adapted to serve this purpose in maize. I have created an online software tool for the maize
community, called Promzea that is able to retrieve DNA motifs over-represented in the
promoters of co-expressed genes, will be described. Using Promzea, over-represented motifs
were identified associated with co-expressed genes in root hairs, diverse maize organs and
different developmental phases. These results should aid in the design of synthetic promoters for
targeted maize gene expression. As such genetic transformation will involve improving in vitro
regeneration in maize, in my last study, I describe the transcriptome effects of two QTLs that
improve in vitro plant regeneration, using a model system
Acknowledgements
First I would like to express gratitude to my advisor Manish Raizada for giving me this
great opportunity. I would like to thank him for his support and his kindness. Thank you for
giving me direction and to have believed in me. Thank you for your great scientific vision that
has made me raise the bar in science considerably. You have been and will remain an example of
dedication and caring about others for me.
Thank you to my Advisory Committee composed of Lewis Lukens, Joseph Colasanti and
Daniel Ashlock for their guidance and helpful advice.
I am grateful to François Fauteux, Gregory Downs, Lewis Lukens and Martina Strömvik
for guiding me in the computer programming learning process, and for helping to solve my first
computer problems. I am also grateful to them to have allowed me to use their server during the
first years. I am also grateful to Paul McNicholas for his advice and for kindly giving me access
to his server during the Promzea testing. I would like to express gratitude to the internet Perl
community for their help during the production of Promzea and during the initial difficulties
involving microarray analysis.
I am also very grateful to Steven Rothstein and Mei Bi for their help, good advice and
support during these years. You have been examples for me during these years. This experience
would not have been the same without the exceptional sharing and support of my lab mates:
Steve, Mike, Blair, Sameh, Amélie, David, Hannan and Vijay. Their presence has enriched me
exceptionally for the rest of my life. Thank you also to the summer students who helped during
this project: Adrienne, Sarah, Bridget, and all the others for their enthusiasm and their great
work.
iv
I would like to thank my fiancée, Eve. I would never have enough words to describe her
support and love through these years. Thank you for encouraging me to continue with graduate
school when my only will was to give up on this part of my life. I am also very grateful to my
family for their unconditional support and love, my parents, my sisters and my brother. You
have taught me and encouraged me to never give up and never allow me to compromise on what
I want to become in life.
v
Abbreviations
AddN:
Added Nitrate media
AMT:
ammonium transporter
BioP:
BioProspector
BLAST:
basic local alignment search tool
bp:
base pair(s)
cM:
CentiMorgan
DIMBOA:
2,4-dihydroxy-7-methoxy-2H-1,4-benzoxazin-3(4H)-one
Gln:
glutamine synthetase 1-encoding gene
GOGAT:
glutamate synthase.
GS:
glutamine synthetase
Ler:
Landsberg Arabidopsis ecotype
MaintN:
Maintenance Nitrate media
MAL:
Maize Adult Leaf motif
MAR:
Maize Adult Root motif
Mbp:
Mega base pairs
MEME:
Multiple Em for Motif Elicitation
miRNA:
micro ribonucleic acid
MJL:
Maize Juvenile Leaf motif
MJR:
Maize Juvenile Root motif
MNR:
Maize Nodal Root motif
MNR:
Maize Nodal Root motif
MORSL:
Maize Old Reproductive Stage Leaf motif
vi
MORSR:
Maize Old Reproductive Stage Root motif.
MSR:
Maize Seminal Root motif
MSR:
Maize Seminal Root motif
MV1R:
Maize V1-stage Root motif
MV2L:
Maize V2-stage Leaf motif
MV2R:
Maize V2-stage Root motif
MVeL:
Maize Ve-stage Leaf motif
MVeR:
Maize Ve-stage Root motif
MYLL1:
Maize Young Lower Leaf motif
N:
nitrogen
NAR2:
nitrate transporter 2 complex accessory protein
NiR:
nitrite reductase
NiRT:
nitrite transporter
NIL:
near isogenic line
NO:
Nitric oxide
Nos:
Nossen Arabidopsis ecotype
NR:
nitrate reductase
NRE:
nitrate responsive element
NRT:
nitrate transporter
PLACE:
plant cis-acting regulatory DNA elements database
qPCR:
quantitative polymerase chain reaction
QTL:
quantitative trait loci
RH:
root hair
vii
RHM:
root hair media
ROS:
reactive oxygen species
RxDAP:
reproductive stage, x days after pollination
Vx:
vegetative stage
viii
List of Tables
Chapter 2
Table 2.1: Position weight matrix example.
Chapter 3
Table 3.1: Software programs used in Promzea.
Table 3.2: Combination of motif discovery programs based on measures of True Positive
and False Positive nucleotides.
Table 3.3: Effectiveness of combining different motif discovery programs based on
nucleotide sensitivity scores.
Table 3.4: The effect of MNCP score cut-offs to the motif prediction from the Sandve’s
benchmark.
Table 3.5: List of input cDNAs from the maize anthocyanin pathway used for Promzea
searches.
Chapter 4
Table 4.1: Detailed description of developmental stages and tissues sampled.
Table 4.2: Tissue/stage-specific interesting genes.
Table 4.3: GO terms of the photosynthetic genes up-regulated in seminal roots compared
to nodal roots.
Chapter 5
Table 5.1: Over-represented motifs associated with vegetative phase change.
Table 5.2: Probe sets differentially expressed in leaf and root tissues
Chapter 6
Table 6.1: Detailed description of developmental stages and tissues sampled.
ix
Table 6.2: Promoter cis-acting motifs over-represented in the nitrogen-related genes
expressed during maize development at different stages/tissues.
Table 6.3: NRE/Acore motifs detected in nitrogen-related promoters from gene
expression Cluster 1.
Chapter 7
Table 7.1: Real time qRT-PCR primers used to determine the RH/root expression ratio of
N-related genes.
Table 7.2: Relative expression of nitrate and ammonium transporters in root hair cells.
Table 7.3: Ammonium transporters retrieved from the maize genome, and orthologs
from rice and Arabidopsis.
Table 7.4: Categories of differentially expressed genes in the root hair response to nitrate
addition.
Table 7.5: Hormone-related genes that are differentially expressed in root hairs at 0.3
mM versus 3 mM nitrate at 30 min and 3 h following addition of liquid root hair media
(RHM).
Chapter 8
Table 8.1: Relative expression of genes related to root hair growth and development
following rehydration in root hair.
Table 8.2: Hypergeometric test p-values corresponding to the over-represented gene
categories shown in Figure 7.5.
Table 8.3: Relative expression of hormone-related genes that were differentially
expressed in maize root hairs following rehydration.
x
Table 8.4: Relative expression of other signalling and vesicle-trafficking related genes
that were differentially expressed in maize root hairs following rehydration.
Table 8.5: Relative expression of genes encoding transcription factor and regulons
related to water stress that were differentially expressed in maize root hairs following
rehydration.
Table 8.6: Relative expression of osmoprotectant and osmotic solute related genes that
were differentially expressed in maize root hairs following rehydration.
Table 8.7: Relative expression of other drought-related genes that were differentially
expressed in maize root hairs following rehydration.
Chapter 9
Table 9.1. Evidence of the Nossen QTLs action on shoot regeneration.
Table 9.2. Hormone and root-related genes found to be differentially expressed
xi
List of Figures
Chapter 2
Figure 2.1: Maize early development.
Figure 2.2: Maize root anatomy.
Figure 2.3: Genetic pathway of RH initiation in Arabidopsis thaliana.
Figure 2.4: Vesicle trafficking during RH elongation.
Figure 2.5: Sensing of nitrogen availability in maize.
Figure 2.6: Affymetrix probe synthesis.
Figure 2.7: The Affymetrix RNA labeling and hybridization process.
Chapter 3
Figure 3.1: Flow chart of the Promzea motif discovery pipeline.
Figure 3.2: Comparison of standalone motif discovery programs.
Figure 3.3: Optimization of motif filtering for each standalone motif discovery program.
Figure 3.4: Effectiveness of combining different motif discovery programs.
Figure 3.5: Effectiveness of combining different motif discovery programs.
Figure 3.6: Genes in the maize anthocyanin and phlobaphene biosynthesis pathways
regulated by transcription factors C1 and P.
Figure 3.7: Motifs predicted by Promzea for genes encoding the maize anthocyanin
biosynthesis pathway.
Figure 3.8: Motifs predicted by Promzea compared to experimentally defined motifs in
the literature using Dialign and Matalign.
Figure 3.9: Example of the Promzea output for anthocyanin pathway Motif5.
xii
Figure 3.10: The presence of Promzea-predicted motifs upstream of genes encoding
anthocyanin and phlobaphene biosynthesis enzymes and encoding their known
transcription factors.
Chapter 4
Figure 4.1: Juvenile leaf stage-selective array expression and associated over-represented
promoter motifs.
Figure 4.2: Juvenile root stage-selective probe expression and associated overrepresented promoter motifs.
Figure 4.3: GO annotation summary of corresponding genes selectively up-regulated in
seminal roots compared to nodal roots.
Figure 4.4: Relative expression of array probes corresponding to photosynthesis related
genes in roots compared to leaves.
Chapter 5
Figure 5.1: Gene expression comparison between juvenile and adult vegetative
tissues.
Figure 5.2: GO annotation summary of genes showing differential regulation before
versus after the juvenile to adult transition.
Figure 5.3: Gene expression comparison between pre-flowering, growing leaves and
post-flowering, mature leaves.
Figure 5.4: Gene expression comparison between pre-flowering and post-flowering
roots.
Chapter 6
Figure 6.1: Heatmap showing relative expression of nitrogen-related genes in root and
leaf tissues at different developmental stages.
xiii
Figure 6.2: Relative expression of nitrogen-related genes across vegetative and
reproductive tissues.
Chapter 7
Figure 7.1: The custom growth system for root hair growth.
Figure 7.2: Determination of the nitrate concentrations needed for this experiment.
Figure 7.3: Experimental flow chart.
Figure 7.4: Genes differentially expressed in root hairs at 30 min versus 3 h in response
to added nitrate.
Figure 7.5: Relative expression summary heatmap.
Figure 7.6: Genes differentially expressed in root hairs in response to nitrate classified
by gene annotation category.
Figure 7.7: Validation of N-related gene expression stability between in root and root
hairs.
Figure 7.8: Fold difference in expression of nitrate uptake and assimilation genes in roots
versus root hairs.
Figure 7.9: Over-represented cis-acting elements present in the promoters of the
differentially expressed root hair genes.
Figure 7.10: Physical map overlap of differentially expressed root hair genes and Nrelated QTLs.
Figure 7.11: Summary model of the early root hair transcriptome response to nitrate.
Chapter 8
Figure 8.1: Custom growth system.
Figure 8.2: Experimental flow chart.
xiv
Figure 8.3: Sample clustering.
Figure 8.4: Venn diagrams summarizing differentially expressed genes in root hairs in a
time course following rehydration.
Figure 8.5: Over-represented protein categories in the root hair response to rehydration.
Figure 8.6: Hypothetical jasmonate synthesis pathway and regulation
Figure 8.7: Cis-acting elements found in the promoters of genes differentially expressed
in root hairs following rehydration.
Figure 8.8: Summary of root hairs gene expression during early rehydration.
Chapter 9
Figure 9.1: Natural variation screen for ecotypes that can bypass the high auxin/low
cytokinin (CIM) pre-treatment normally required for efficient shoot regeneration.
Figure 9.2: Developmental time course showing ecotype specific responses to pretreatments with or without high auxin/low cytokinin.
Figure 9.3: Ecotype-specific differences in shoot regeneration in response to auxin
and cytokinin.
Figure 9.4: The effect of two QTLs from Nossen-0, introgressed into Ler-0, on shoot
regeneration frequency in the absence of a high auxin/low cytokinin (CIM) pretreatment.
Figure 9.5: Effect of the Chromosome 5 Major QTL from No-0 on the sensitivity of
intact Ler-0 seedlings to auxin and cytokinin.
Figure 9.6: Example of array probe set hybridizations.
Figure 9.7: Heatmap of hormone-related genes that are differentially expressed in
response to alleles present at the Chromosome 4 and 5 QTLs.
xv
Figure 9.8: Summary for how hormone-related genes are affected by the Major
Chromosome 4 and Chromosome 5 QTLs from No-0.
xvi
Table of Contents
Table of Contents ................................................................................................................... xvii
1. Thesis overview .....................................................................................................................1
2. Literature review ....................................................................................................................4
2.1
Importance of maize as a crop ....................................................................................4
2.2
Maize Development and Anatomy .............................................................................5
2.2.1 Maize body plan .................................................................................................. 5
2.2.2 Maize root formation, morphology and anatomy................................................ 8
2.2.3 Root anatomy .................................................................................................... 11
2.3
Genetics of Maize Root Development .....................................................................12
2.3.1 Introduction ....................................................................................................... 12
2.3.2 Maize root QTL analysis ................................................................................... 12
2.3.3 Root mutants ..................................................................................................... 13
2.4
Detailed Review of Angiosperm Root Hair Development .......................................14
2.4.1 Overview ........................................................................................................... 14
2.4.2 Root hair initiation: Arabidopsis thaliana ......................................................... 14
2.4.3 Root hair (RH) elongation ................................................................................. 17
2.4.4 Environmental sensing versus root hair elongation .......................................... 20
2.5
Nitrate Absorption and Nitrogen Effects on Root Growth.......................................21
2.5.1 Nitrogen demand ............................................................................................... 21
2.5.2 Nitrate availability and uptake .......................................................................... 23
2.5.3 Nitrate assimilation ........................................................................................... 24
xvii
2.5.4 Nitrate effects on root growth ........................................................................... 26
2.5.5 Localization of nitrogen transporters ................................................................ 27
2.5.6 Promoter elements associated with nitrogen induction of gene expression ...... 27
2.5.7 Improving early season nitrogen uptake at the juvenile stage .......................... 28
2.5.8 Effects of water stress on plants and root hairs ................................................. 28
2.6
Microarray Techniques and Data Analysis ..............................................................29
2.6.1 Background ....................................................................................................... 29
2.6.2 Affymetrix genechip platform ........................................................................... 31
2.6.3 Quality control of the data ................................................................................. 35
2.6.4 Normalization and choice of normalization ...................................................... 35
2.6.5 Statistical analysis and production of a list of differentially-expressed genes .. 36
2.6.6 Validation of the results .................................................................................... 37
2.7
Examples of Published Maize Transcriptome Studies .............................................38
2.7.1 Introduction to maize transcriptome studies ..................................................... 38
2.7.2 Maize leaf transcriptome studies ....................................................................... 38
2.7.3 Maize root transcriptome analysis ..................................................................... 39
2.7.4 Maize whole plant transcriptome studies .......................................................... 40
2.8
Gene expression regulatory elements in plants ........................................................41
2.8.1 Definition of cis-acting elements ...................................................................... 41
2.8.2 Plant cis-element databases and the search for known promoter motifs........... 42
2.8.3 Promoter-Enhancer Motif Prediction ................................................................ 43
2.8.4 Transcription factors and promoters in plants ................................................... 44
2.8.5 Approaches to discover and study candidate master gene regulators ............... 46
xviii
2.9
Plant transformation with genes of interest and the limits of plant regeneration .....46
2.10 Need for stage-, organ- and cell type-specific promoters in maize ..........................47
2.11 Hypotheses and Objectives ......................................................................................49
3. Promzea: A pipeline for discovery of regulatory motifs in maize (Zea mays L.)................51
3.1
Abstract ....................................................................................................................52
3.2
Introduction ..............................................................................................................52
3.3
Materials and Methods .............................................................................................55
3.3.1 Software programs used in this study ............................................................... 55
3.3.2 Comparisons of current motif discovery tools .................................................. 58
3.3.3 Filters for each standalone program .................................................................. 59
3.3.4 Combining multiple programs .......................................................................... 61
3.3.5 Construction of Promzea: Overview ................................................................. 61
3.3.6 Construction of upstream and first-intron sequence databases from maize ...... 63
3.3.7 Extraction of promoter and first-intron sequences from user inputs ................. 63
3.3.8 Motif discovery, filtering, ranking and graphical output in Promzea ............... 64
3.3.9 Understanding motif function in Promzea using functional gene annotation ... 65
3.3.10 Validation of Promzea predictions using experimentally defined motifs ......... 66
3.4
Results ......................................................................................................................66
3.4.1 Comparisons of current motif discovery programs using benchmark data sets 66
3.4.2 Defining filters for each standalone program using benchmark data sets......... 69
3.4.3 Effect of combining motif discovery programs using benchmark data sets ..... 72
3.4.4 Promzea: a pipeline for motif discovery in maize............................................. 78
xix
3.4.5 Validation of Promzea using experimentally defined transcriptional
binding sites .................................................................................................................. 81
3.4.6 Novel candidate motifs in the anthocyanin pathway ........................................ 86
3.4.7 Other genes containing the same motifs as the anthocyanin promoters ........... 90
3.5
Discussion ................................................................................................................94
3.6
Conclusion ................................................................................................................97
4. Association of cis-acting elements with juvenile stage-selective gene expression in maize (Zea
mays L.) ....................................................................................................................................98
4.1
Abstract ....................................................................................................................99
4.2
Introduction ............................................................................................................100
4.3
Materials and Methods ...........................................................................................102
4.3.1 Plant growth and tissue harvest. ...................................................................... 102
4.3.2 Microarray analysis and normalization ........................................................... 102
4.3.3 Statistical analysis of tissue-specific gene expression .................................... 102
4.3.4 Statistical analysis of seminal versus nodal roots ........................................... 103
4.3.5 Gene Ontology detection ................................................................................. 103
4.3.6 Promoter motif discovery ................................................................................ 104
4.4
Results and Discussion ...........................................................................................104
4.4.1 Overview ......................................................................................................... 104
4.4.2 Stage-selective leaf expression........................................................................ 109
4.4.3 Stage-selective root expression ....................................................................... 113
4.4.4 Comparison of the transcriptomes of seminal versus nodal root organs ......... 117
xx
4.5
Study Limitations and Significance .......................................................................124
5. Promoter motifs associated with leaf and root gene expression at the juvenile, adult and
reproductive phases of maize (Zea mays L.) development.....................................................126
5.1
Abstract ..................................................................................................................127
5.2
Introduction ............................................................................................................128
5.3
Materials and Methods ...........................................................................................131
5.3.1 Plant growing conditions and tissues sampled. ............................................... 131
5.3.2 Affymetrix array hybridization and normalization procedure ........................ 131
5.3.3 Statistical analysis of phase change ................................................................ 131
5.3.4 Gene Ontology (GO) analysis ......................................................................... 131
5.3.5 Discovery of over-represented promoter motifs ............................................. 131
5.4
Results and Discussion ...........................................................................................133
5.4.1 Overview of transcriptome results .................................................................. 133
5.4.2 Juvenile to adult transition .............................................................................. 133
5.4.3 Pre-flowering versus post-flowering ............................................................... 145
5.5
Study limitations, significance and summary.........................................................151
6. Spatio-temporal gene expression and cis-acting promoter motifs associated with nitrogen
transporter and assimilation genes in maize (Zea mays L.) ....................................................153
6.1
Abstract ..................................................................................................................154
6.2
Introduction ............................................................................................................155
6.3
Materials and Methods ...........................................................................................157
6.3.1 Plant growth and tissue harvest ....................................................................... 157
xxi
6.3.1 Microarray analysis ......................................................................................... 158
6.3.2 Annotation and clustering of nitrogen related genes ....................................... 158
6.3.3 Promoter motif discovery ................................................................................ 159
6.4
Results ....................................................................................................................160
6.4.1 Tissue and developmental stage selective expression ..................................... 160
Over-represented cis-acting promoter motifs.............................................................. 169
6.5
Discussion ..............................................................................................................173
6.5.1 Global analysis of nitrogen-related genes during maize development. .......... 173
6.5.2 Promoter motifs underlying stage-selective gene expression. ........................ 174
6.5.3 Nitrite transporter expression. ......................................................................... 177
6.5.4 Significance ..................................................................................................... 178
7. Early Reprogramming of the Maize Root Hair Transcriptome in Response to Nitrate .....179
7.1
Abstract ..................................................................................................................180
7.2
Background ............................................................................................................182
7.3
Methods ..................................................................................................................185
7.3.1 Biological material .......................................................................................... 185
7.3.2 Growth system overview ................................................................................. 185
7.3.3 Growth and nitrate treatments ......................................................................... 188
7.3.4 Root hair RNA extraction ............................................................................... 188
7.3.5 Microarray hybridization, analysis and clustering .......................................... 190
7.3.6 Real time quantitative RT-PCR....................................................................... 191
7.3.7 Promoter motif prediction ............................................................................... 193
xxii
7.3.8 Physical mapping of QTLs .............................................................................. 193
7.4
Results and Discussion ...........................................................................................194
7.4.1 Root hair RNA yield ....................................................................................... 194
7.4.2 Determination of nitrate concentrations .......................................................... 194
7.4.3 Expression summary ....................................................................................... 197
7.4.4 Annotation summary ....................................................................................... 201
7.4.5 Genes Affecting Plant Nutrition ...................................................................... 203
7.4.6 Nutrition: Light, carbon and energy metabolism ............................................ 219
7.4.7 Putative Genes Involved in Root Hair Growth ............................................... 226
7.4.8 Other Genes of Interest ................................................................................... 245
7.4.9 Caviats in interpreting transcriptome results ................................................... 248
7.4.10 Prediction of cis-acting promoter motifs ......................................................... 250
7.4.11 Coincidence of differentially expressed genes with QTLs ............................. 251
7.5
Conclusions ............................................................................................................260
8. The Early Transcriptome Response to Rehydration by Maize Root Hairs (Zea mays L.) 262
8.1
Abstract ..................................................................................................................263
8.2
Introduction ............................................................................................................264
8.3
Methods ..................................................................................................................267
8.3.1 Biological material .......................................................................................... 267
8.3.2 Growth system overview ................................................................................. 267
8.3.3 Growth and rehydration treatments ................................................................. 268
8.3.4 Root hair RNA extraction ............................................................................... 270
xxiii
8.3.5 Microarray hybridization, analysis and clustering .......................................... 270
8.3.6 Promoter motif prediction ............................................................................... 271
8.4
Results and Discussion ...........................................................................................272
8.4.1 Overview ......................................................................................................... 272
8.4.2 Over-represented pathways ............................................................................. 276
8.4.3 Genes involved in root hair (RH) growth and development ........................... 281
8.4.4 Hormone pathways .......................................................................................... 283
8.4.5 Transcription factors ....................................................................................... 298
8.4.6 Downstream tolerance responses .................................................................... 307
8.4.7 Interpreting transcriptome results.................................................................... 322
8.4.8 Prediction of cis-acting promoter motifs ......................................................... 323
8.5
Conclusions ............................................................................................................328
9. Two QTLs Act Cooperatively to Bypass the Requirement for Callus Induction Media (CIM)
During in vitro Shoot Regeneration in Arabidopsis thaliana (L.) ...........................................330
9.1
Abstract ..................................................................................................................331
9.2
Introduction ............................................................................................................332
9.3
Methods ..................................................................................................................334
9.3.1 Plant Material and Growth Conditions............................................................ 334
9.3.2 Cotyledon Regeneration Assay and Analysis ................................................. 334
9.3.3 Time Course of Regeneration ......................................................................... 335
9.3.4 Genetic Mapping ............................................................................................. 335
9.3.5 Seedling Hormone Assays .............................................................................. 336
xxiv
9.3.6 RNA Isolation for Microarray Experiments .................................................... 337
9.3.7 Microarray Hybridizations and Data Analysis ................................................ 337
9.3.8 Semi-quantitative RT-PCR ............................................................................. 338
9.4
Results ....................................................................................................................339
9.4.1 Natural variation screen .................................................................................. 339
9.4.2 Explants of Nossen-0 are less sensitive to changes in exogenous auxin and
cytokinin compared to other ecotypes ........................................................................ 341
9.4.3 Two chromosome segments from ecotype No-0 confer CIM-independent shoot
regeneration ability to ecotype Ler-0 .......................................................................... 346
9.4.4 The Chromosome 4 and Chromosome 5 segments from No-0 act synergistically in
a dosage-dependent manner to promote shoot regeneration ....................................... 351
9.4.5 The Chromosome 5 segment from No-0 reduces sensitivity to exogenous auxin
and cytokinin in intact seedlings ................................................................................. 353
9.4.6 Using microarray to analyze gene expression from a Landsberg genotype (Ler)
containing introgressed chromosome segments from a Nossen-0 genotype (No-0)... 354
9.4.8 The Chromosome 5 segment from No-0 has a greater impact on global gene
expression in cotyledon explants on SIM than the Chromosome 4 segment .............. 359
9.4.9 Auxin-related gene expression dependent of No-0 chromosome segments ... 361
9.4.10 Cytokinin-related gene expression dependent of No-0
chromosome segments ................................................................................................ 366
9.4.11 Ethylene-related gene expression dependent of No-0
chromosome segments ................................................................................................ 367
xxv
9.4.12 Root growth- and development-related gene expression dependent of No-0
chromosome segments ................................................................................................ 368
9.5
10.
Discussion ..............................................................................................................369
General Discussion and Future Experiments ..............................................................375
10.1 Summary of results .................................................................................................375
10.1.1 Objective 1 ...................................................................................................... 375
10.1.2 Objective 2 ...................................................................................................... 376
10.1.3 Objective 3 ...................................................................................................... 377
10.1.4 Objective 4 ...................................................................................................... 377
10.1.5 Objective 5 ...................................................................................................... 378
10.1.6 Objective 6 ...................................................................................................... 379
10.1.7 Objective 7 ...................................................................................................... 381
10.2 Overall Significance ...............................................................................................381
11.
References ...................................................................................................................383
12.
Appendices ..................................................................................................................479
xxvi
1.
Thesis overview
The overall objective of this thesis was to use bioinformatic tools to identify important
co-expressed genes and associated promoter motifs underlying plant development and plant
responses to nutrients, with a special focus on the maize root hair.
In Chapter 2, a general literature review is provided as a background for the biological
problems addressed in the data chapters, in particular nitrogen, as well as the technologies
utilized, in particular, microarrays. This literature review was used to generate the thesis
Hypotheses and Objectives to test these hypotheses, which are presented at the end of this
chapter.
In Chapter 3, an online software tool created for the maize research community called
Promzea that retrieves DNA motifs that are over-represented in the promoters of co-expressed
genes is described. To illustrate the need for improvements in motif discovery, I first compare
the results of using current motif-discovery tools against a benchmark dataset of promoters with
known motifs. Promzea was validated for its ability to retrieve experimentally defined binding
sites of transcription factors C1 and P, regulators of the anthocyanin and phlobaphene
biosynthetic pathways in maize. Promzea is used in subsequent chapters.
In Chapter 4, microarray data from 50 maize tissues across maize development were
analyzed to identify leaf and root cis-acting promoter motifs associated with the three distinct
developmental phases of maize (Zea mays L.): juvenile, adult and reproductive. In particular, the
focus was on genes and promoter motifs shared by both roots and leaves at each phase to shed
light on the whole plant coordination of developmental phase change in maize. It is described
how genes involved in epicuticular wax biosynthesis, a well-known marker for the juvenile
phase in maize leaves, are also up-regulated in juvenile roots, further demonstrating whole plant
1
coordination of plant development.
In Chapter 5, the focus was put on the juvenile (seedling) phase of maize development
and I ask whether this phase can be divided into sub-stages based on global gene expression
clusters and associated promoter motifs. The results demonstrate precise transcriptional control
of gene expression during juvenile maize development, and this chapter identifies landmark
genes for each sub-stage including genes involved in nutrient uptake/transport. For example, I
demonstrate that biosynthetic enzymes for the anti-pathogenic metabolite DIMBOA are
selectively up-regulated in emergence stage coleoptiles.
In Chapter 6, the expression of 65 nitrogen uptake and assimilation probes was analyzed
in 50 maize tissues from seedling emergence to 31 days after pollination. Such global analysis
of nitrogen related genes has not previously been reported in maize, and only a limited study was
conducted in Arabidopsis. Four nitrogen-related gene expression clusters were identified in roots
and shoots corresponding to, or overlapping, juvenile, adult and reproductive phases of
development. Promzea was used to screen promoters corresponding to each gene expression
cluster for over-represented cis-acting elements. An 8 bp core motif within a recently identified
43 bp nitrogen response element (NRE) from dicot nitrite reductase gene promoters was detected
as being over-represented in the promoters of maize genes encoding nitrate and ammonium
transporters, suggesting this core motif is critical across angiosperms.
In Chapter 7, I focus further on the maize root hair and report the results of the first
study ever conducted on the transcriptome response by root hairs of any species to nitrogen (or
any other nutrient). First, protocols were created or optimized for maize root hair growth,
harvesting and isolation of root hair-specific RNA, to facilitate microarray analysis. I then
demonstrate that > 876 genes show significant changes in gene expression within 3 hours of
2
added nitrate in maize root hairs. Of these genes, 92% were down-regulated at 30 min after
nitrate addition while 77% were up-regulated at 3 hours, suggestive of an early reprogramming
of the maize root hair transcriptome in response to nitrate. The root hair responsive genes were
physically overlapped with previously identified quantitative trait loci (QTLs) underlying
nitrogen and yield responses in maize to facilitate future candidate gene discovery efforts.
Promzea was also used to identify over-represented promoter motifs associated with different
root hair nitrate-response expression clusters.
Chapter 8 is a parallel to Chapter 7 maize root hair study, in which the first ever analysis
of the effects of water availability on the transcriptome of plant root hairs was conducted.
Specifically, the early rehydration response of maize root hairs following an extended mild
drought stress was analyzed. At least 1831 annotated genes were differentially expressed in
maize root hairs during the first 3 hours of rehydration after drought. Promzea was used to
identify promoter motifs associated with different root hair expression clusters that respond to
changes in water status.
Both Chapter 8 and Chapter 9 illustrate that the root hair is a rapid and sensitive sensor of
the soil environment and a model system to study abiotic stress responses in plants.
Chapter 9 reports the results of a side-project in which Arabidopsis was used as a model
system for maize to identify candidate genes responsible for improved shoot regeneration from
callus, as shoot regeneration is primarily limited to one genotype in maize (A188) which
significantly limits maize transformation. Specifically, I conducted microarray experiments to
understand the effects of two QTLs that bypass the need for auxin during shoot regeneration.
Finally, in Chapter 10, the results from all chapters are summarized and I conclude
whether these results support or refute the initial hypotheses presented in Chapter 2.
3
2. Literature review
2.1 Importance of maize as a crop
Maize (synonymous with corn) is a member of the Poaceae, a family that includes the
grasses and cereal plants. On the research side, maize has been an organism of choice for the
study of genetics during the past 100 years for multiple reasons: its economic importance; the
ease by which genetic crossing is possible; because of the rapid visualization of hundreds of
offspring on one ear for segregation analysis; and because of the existence of visual genetic
markers (such as anthocyanin pigments) for chromosome mapping (Coe, 1994). A large
collection of developmental mutants is available in maize (Sheridan, 1988); but in spite of this
only limited knowledge exists about maize growth and development at the molecular level. An
international consortium has recently sequenced the maize genome, inbred B73 (Schnable et al.,
2009) which is large (2.5 Giga bases), similar in size to the human genome (Bevan and Waugh,
2007). Such international genomics efforts are making new resources available for basic maize
research which aids in answering fundamental questions regarding maize growth and
development at the molecular level.
In terms of agriculture, maize along with rice and wheat, represents 50% of the human
calorie intake globally (Media-Office, 2006), consumed either directly by humans or indirectly
as livestock feed. Corn is also an important source of biomass for industrial products. Recently,
this crop has taken on a new dimension as a feedstock for increasing production of bio-ethanol in
the United States. Due to increasing human population and increased industrial usage, the
demand for corn is growing worldwide (Dyson, 1999; Pingali, 2001; Wisner and Baumel, 2004).
In Canada, corn yields have doubled from 1970-1990. Subsequently, the yield has increased
4
more slowly than the demand worrying some that limitations in breeding selection have been
reached (FAOSTAT, 2008; OCPA, 2008). Consequently researchers are looking for alternative
methods to accelerate the improvement of maize yields including the use of transgenes. High
maize yields require significant inputs of organic nitrogen fertilizer (nitrate, ammonium, urea)
and globally, nitrogen limits maize production (Gallais and Hirel, 2004; Okamoto and Okada,
2004). As fertilizer costs continue to increase due to rising energy costs, a more effective use of
nitrogen-based fertilizers will be required just to maintain current levels of maize production
globally.
2.2 Maize Development and Anatomy
2.2.1 Maize body plan
Maize development has been described extensively (Poethig, 1982; Coe, 1994; Feldman,
1994; Kiesselbach, 1999). Germination occurs in warm, moist soil at which time the seed
absorbs 30% of its weight in water. At germination, maize embryos have several pre-formed root
and shoot organs, including the radicle (embryonic primary and seminal roots) as well as 4-6
embryonic leaves. The rest of the body plan develops post-embryonically. The radicle grows by
the activity of the primary root meristem, producing the primary root. Simultaneously, the
coleoptile, a shoot structure which protects the first 4-6 embryonic leaves from soil damage,
starts to elongate in the opposite direction. Finally, the seminal roots are the last organs to
emerge from the kernel.
5
Figure 2.1: Maize development
6
The mesocotyl, a stem-like organ between the kernel and the coleoptile, pushes the latter
structure out of the soil by rapid elongation. This first phase is called the emergence phase, or
Ve, in the early development of corn. At this time the growth of the mesocotyl stops and the
coleoptile opens up.
All true leaves derive from a population of stem cells at the apex of the stem, the shoot
apical meristem (SAM). Stem growth from the SAM occurs with the appearance of the first preformed leaves and the first visible node or collar. The appearance of this first node is referred to
as the V1 stage. Each of the vegetative stages of corn development is thereafter referred to as V1,
V2 until V12-V16, as a function of the number of nodes (Figure 2.1). Subsequent leaves initiate
180˚C from one another, with one leaf and one axial meristem per node (Kiesselbach, 1999). The
vegetative phase of leaf initiation continues for four or five weeks after germination, after which
the SAM converts to a reproductive tassel meristem. However, at stage V5 all the leaf primordia
are formed and the initiation of a micro-tassel can be observed upon dissection. The SAM is
responsible for all the above ground structures (Sheridan, 1988). In addition to the leaf
primordia, an axial meristem is formed at the base of each leaf except the five uppermost leaves.
These new meristems are part of the reproductive system and they subsequently give rise to the
ear shoots. Only one or two of these axial shoots will produce mature ears in modern corn
cultivars.
In the vegetative phases of development, roots, main stems and leaves are developed. In
the reproductive phase, the axillary shoots and the tassel internodes grow to differentiate the ears
and the tassel respectively. Ears differentiate by the appearance of lateral shoot-like
protuberances. Ears are protected by modified leaves called husk leaves. Inside the husk,
reproductive organ growth begins with the development of miniature branches along the main
7
stem. Each branch divides itself in subsequent branches. Ramifications are denser in the lower
part to give a cone-like structure of the immature ear. All the branches or sub-branches of the ear
of normal corn remain short and differentiate into spikelet initials. Each spikelet undergoes an
unequal division. Usually, the larger and upper division of the spikelet develops a fertile flower;
the flower formation aborts in the smaller, lower division. Flower differentiation starts by the
formation of empty glumes. Subsequently, male and female organs, anthers and pistils
respectively, grow in the glume (Bonnett, 1948). In the pistil, the ovary is extended by the silk,
followed by hairs. Hairs elongate out of the husk in order to catch the pollen. Pollen sticks to the
exposed hairs of the silk. Pollen tubes grow inside the silk and eventually reach the ovule but
only one pollen grain fertilizes the embryo sac. Two sperm are released from the pollen
(Kiesselbach, 1999). One sperm fuses with the egg nucleus to form the zygote. The other sperm
fuses with one of the polar nuclei to form the triploid endosperm. The cells of the zygote and
endosperm are enclosed in the former carpel tissue, the pericarp. After cell division and
differentiation, these tissues will form the mature kernel that contains a pre-formed seedling
embryo (Bonnett, 1948).
The male inflorescence (flower-bearing structure) or tassel is at the top of the stem. The
tassel is formed by reproductive branches, spike bears spikelets producing flowers. At the time of
initiation, tassel flowers contain both male and female organs but the female organs degenerate.
Only the male organs, the stamens, survive to produce pollen (Kiesselbach, 1999).
2.2.2 Maize root formation, morphology and anatomy
2.2.2.1 Root morphology
The root system is the product of several meristems: the embryonic root meristems are
responsible for the growth of the seminal and primary roots (see Figure 2.2). The latter will stop
8
growing at the ~V3 stage. Then, adventitious roots or crown roots begin to grow from 8 to 10
nodes at the base of the shoot. The adventitious roots first grow horizontally and then vertically;
in warmer soil, the horizontal growth decreases, suggesting that their orientation is temperaturedependent (Kiesselbach, 1999). By the V5 stage, the crown roots outgrow the seminal roots and
are eventually responsible for most of the nutrient and water absorption. Some authors have
observed the death of the primary root after the formation of the crown roots (Hochholdinger et
al., 2004). All these root types produce branches to increase the surface area for uptake of water
and nutrients but the most notable increase in surface area is due to the root hairs. Each root hair
is unicellular, an extension of a root epidermal cell. Root hairs first emerge very close to the
growing tips. Later, as lateral roots develop from main roots (crown, seminal and primary) they
also initiate root hairs.
These different root structures eventually create a network that is 6 miles in length
(Poethig, 1982), spreading across a diameter of 6-8 feet of the parent stem with the dominant
root organs being the crown roots (Poethig, 1982; Kiesselbach, 1999).
9
Figure 2.2: Maize root anatomy
10
2.2.3 Root anatomy
Unlike the underlying genetics, the anatomy of the root is well characterized in maize.
All the root types have a similar anatomy, in term of the radial arrangement of cell types and
tissue layers starting with the epidermis in the outer layer, followed by the cortex, and then the
stele that includes the vascular tissues: xylem and phloem.
The root tip is a major site of cell divisions. Subsequently the cells generated undergo
elongation and differentiation in order to form the different root tissues and cell types. All root
cells are derived from a small population of slow-dividing cells in each root apical meristem
(RAM), the Quiescent Center (QC) (Hochholdinger and Zimmermann, 2007). QC-derived
daughter cells establish three layers within the RAM. The outermost meristem or protoderm
produces the epidermis including root hairs that increase the surface area for water and nutrient
absorption; the middle layer or ground meristem produces the starch-storing cortex cells and
water-proofing endodermis layer (due to its secretion of a suberized layer known as the
Casparian Strip which prevents water and nutrient seepage); and the innermost meristem, the
procambium, produces the vascular cylinder or stele. The vascular cylinder consists of waterconducting, non-living xylem cells and photosynthate-conducting live phloem cells which are
surrounded on the outside by a specialized layer, the pericycle, which persists as a meristem to
produce lateral roots later in development in response to environmental conditions. Unlike dicot
roots, the center of the vascular cylinder also contains spongy parenchyma pith cells which act as
storage (Hochholdinger and Zimmermann, 2007).
Below the root meristem lies the root cap which is composed of a “loose network” of
cells; these cells are embedded in a mucilage rich in carbohydrates. The function of the root cap
is to protect the root meristem behind it as the root pushes into the soil.
11
After division, cells at the root tip undergo elongation which seems to be under the
control of two hormone types, gibberelins and auxins. The extensin proteins also act in the
process (Bassani et al., 2004). Cell elongation occurs via loosening of the cell walls, a rigid
polymer network. Finally the cells differentiate to produce the tissues and cell types of the
mature root (Kiesselbach, 1999).
2.3 Genetics of Maize Root Development
2.3.1 Introduction
The genetic improvement of corn inbred lines has mostly ignored root genetics because
of the complexity and the difficulties of visualizing this organ system. Whereas above-ground
traits have been improved, including leaf size, angle and senescence as well as kernel size and
number, studies involving the root system have primarily focused on defense against pathogens
and less often for its contribution to yield.
2.3.2 Maize root QTL analysis
The two major roles of the roots are to anchor the plant and to acquire nutrients for its
growth. A major problem faced by plants is that nutrients are heterogeneously distributed in the
soil, and the development of the root thus has important implications for the exploitation of these
resources. In maize, interestingly, several root size and architecture QTLs have been shown to
overlap with QTLs important for grain yield, suggesting a direct relationship between grain
filling and root size/architecture (de Dorlodot et al., 2007; Coque et al., 2008). This interaction
has also been shown for yield stability during drought and salt stresses (Tuberosa et al., 2002; de
Dorlodot et al., 2007).
12
2.3.3 Root mutants
In Arabidopsis, some genes have been shown to be indispensable to lateral root
development; this includes genes of the auxin signaling pathway including SOLITARY
ROOT/IAA14 (Vanneste et al., 2005). Low auxin levels promote the blockage of mitosis in the
pericycle and subsequent local increases of auxin level stimulate the elongation of lateral root
primordia (Dembinsky et al., 2007).
Unlike in Arabidopsis, however, only a limited number of published root mutants exist in
maize and other cereals. The most studied maize root mutants are defective in root branching and
root hair development, resulting in the absence or reduction of crown roots, lateral roots and root
hairs. The mutant rt1 has a reduced number of upper node crown roots (Hochholdinger et al.,
2004). In the rtcs mutant only the primary root is formed and all the others types are missing
(Hochholdinger et al., 2004). Control of cell division may lie at the heart of these mutant
phenotypes, because key cyclin genes are not expressed compared to normal branch points.
Mutants defective in maize lateral root formation have also been found. Ltr1 and rum1
mutants are affected in the initiation of the lateral roots (Hochholdinger et al., 2004; Dembinsky
et al., 2007). In addition, slr1 and slr2 mutants are affected at the subsequent elongation step
(Hochholdinger et al., 2001). Regarding root hairs mutants, two types of mutants have been
found in maize: roothairless 1 (rth1) and roothairless 3 (rth3) affect root hair initiation, whereas
rth2 affects root hair elongation (Hochholdinger et al., 2004; Wen et al., 2005; Kwasniewski and
Szarejko, 2006). Plants affected by rth2 and rth3 mutations manage to grow normally, but rh1
mutant have dramatically reduced nutrient uptake (Hochholdinger et al., 2004). Therefore, from
the mutant analysis, two different genetic steps can be identified: initiation and elongation.
13
2.4 Detailed Review of Angiosperm Root Hair Development
2.4.1 Overview
The root hair (RH) is a specialized single epidermal cell projection resulting from tip
growth. RHs are present in higher plant species, and they are derived from a cell type called the
trichoblast (Schiefelbein et al., 1997; Guimil and Dunand, 2006; Kwasniewski and Szarejko,
2006; Fischer et al., 2007). In higher plants, roots hairs are grouped in three main types (Dolan
and Roberts, 1995). In the first group, characterized by many dicots, RHs initiate “randomly”
from the epidermis. In the second group, primarily within the monocots, including maize, RHs
originate from an asymmetric division of an epidermal cell; the cytoplasmically-dense smaller
cell becomes the hair by subsequent elongation, whereas the larger undergoes further division
and becomes the hairless cell (atrichoblast). This mode of cell division results in a highly
asymmetric RH pattern on the epidermis. In the third group, which includes Arabidopsis, the
RHs are organized in a file of cells; along particular columns of cells, every cell develops a RH.
Possibly linked with their absorption role, the RHs have a higher density of plasmodesmata than
other epidermal cells (Vakhmistrov, 1981).
During the early development stage of maize, RHs appear first on the seminal roots, but
by the V5 stage, almost none of these hairs remain. Instead at this stage the crown roots become
the more dominant root organ, and they develop RHs. The loss of RHs on the seminal roots
coincides with that organ no longer being able to absorb nutrients.
2.4.2 Root hair initiation: Arabidopsis thaliana
As very little molecular information is available concerning RH development in
monocots, in this section and the next section, I review literature from Arabidopsis thaliana, a
dicot. It has been observed in Arabidopsis that during the RH differentiation process, the cell fate
14
of a root epidermal cell is determined by its location with respect to underlying cortical cells.
Cells located above an intercellular space give rise to roots hairs whereas cells located directly
above cortical cells remain as non-RH cells (Schiefelbein, 2000; Pesch and Hulskamp, 2004).
Consequently, the pattern of RHs along the epidermis reflects the underlying pattern of cortical
cells.
Hormones, primarily auxin and ethylene, are known to be involved in RH initiation
(Fischer et al., 2007). It is hypothesized that these hormones serve as sensors of the environment
in order to modulate the pattern of gene expression during RH initiation (Fischer et al., 2007).
The elongation point of the RH within the trichoblast cell has a basal-apical polarity with respect
to the epidermal layer. In Arabidopsis, auxin influx is required for proper positioning of the RH
elongation point within the trichoblast cell (Fischer et al., 2007). A mutation in the AUX1 gene,
a component of the auxin transport machinery, was shown to reduce basal polarity. In contrast,
an increase in endogenous auxin resulted in enhanced basal polarity (Fischer et al., 2007). In
Arabidopsis, reduced ethylene production blocked RH differentiation (Dolan and Roberts, 1995).
In Arabidopsis, several informative mutants have been isolated which affect RH
initiation, and these have helped to define a genetic pathway as shown in Figure 2.3 below:
15
Figure 2.3: Genetic pathway of RH initiation in Arabidopsis thaliana. The N-position refers to a
non-RH epidermal cell while the H-position is a RH-forming cell; Summary from Libault
(Libault 2010).
16
In Arabidopsis, the mutant scm exhibits random RH formation (Guimil, 2006). SCM
encodes a Leucine-Rich Repeat Receptor-like Kinase and it appears to be a receptor of the RH
positioning signal. A mutation in another gene, TRANSPARENT TESTA GLABRA 1 (TTG1),
results in hair initiating on all root epidermal cells (Pesch and Hulskamp, 2004). In fact, TTG1
has been shown to interact with two other proteins: WEREWOLF (WER), a MYB-type
transcription factor and what was initially identified as a basic helix-loop- helix transcription
factor (bHLH) (Schiefelbein et al., 1997; Schiefelbein, 2000; Pesch and Hulskamp, 2004). WER
may be a component of the hair fate pathway of SCM because wer mutants exhibit random RH
localization (Pesch and Hulskamp, 2004). The putative SCM/WER complex subsequently
activates the expression of GLABRA2 (GL2) and represses cell division (Birnbaum and Benfey,
2004). GL2 is a transcription factor (Rerie et al., 1994) which has been shown to act as a
repressor of RH development. TTG and bHLH have also been shown to interact with CAPRICE
(CPC) (Wada et al., 1997) to promote RH initiation. More recently, bHLH has been identified as
being encoded by two different bHLH-encoding genes, GLABRA 3 (GL3) and ENHANCER OF
GLABRA 3 or EGL3 (Birnbaum and Benfey, 2004; Pesch and Hulskamp, 2004). EGL3 and
GL3 are involved in RHs as well as non-RH cells. Two other proteins have been identified as
interacting with CPC in Arabidopsis RH initiation: TRIPTYCHON (TRY) and ENHANCER OF
TRIPTYCHON also named TRY and ETC respectively (Guimil and Dunand, 2006). As noted in
an earlier section, unlike in Arabidopsis, almost none of the components of the RH initiation
pathway in monocots have been identified.
2.4.3 Root hair (RH) elongation
The Rho of Plant (ROP) GTPases influence RH elongation by regulating the actin
cytoskeleton mainly Actin 2, 7 and 8 as well as the polarization of reactive oxygen species
17
(ROS) (Libault et al., 2010; Bloch et al., 2011). ROP GTPases, under the regulation of auxin, act
both on RH elongation an initiation (Payne and Grierson, 2009).
ROS participates in the modification of the cell wall to promote RH elongation (Libault
et al., 2010). ROS accumulates at the very tip of the RH during elongation; they are produced by
NADPH oxidases located on the plasma membrane (Carol and Dolan, 2006), notably the NADH
oxidase RHD2; rhd2 mutations cause defects in RH growth. Calcium ions, potassium and proton
polarization are also observed during RH elongation toward the tip; these cause vesicle
trafficking along these molecular gradients (Campanoni and Blatt, 2007). In addition, RH
elongation is auto-activated by a loop between calcium polarization and ROS. Calcium
polarization provokes the release of external ATP (eATP) at the RH tip. This eATP subsequently
triggers ROS production (Kim et al., 2006).
In general, vesicle trafficking is normally associated with SNARE proteins which interact
with the cytoskeleton to direct vesicles to their membrane target(s) (Uemura et al., 2004). No
SNARE proteins have thus far been definitively implicated in RH elongation, however
(Campanoni and Blatt, 2007); this remains a gap in our understanding of RH dynamics. Vesicle
trafficking during RH elongation is shown in Figure 2.4.
18
Figure 2.4: Vesicle trafficking during root hair elongation. This figure is adapted from Figure 2
in Kost’s review (Kost, 2008).
19
2.4.4 Environmental sensing versus root hair elongation
In Arabidopsis and cereals, studies on wild-type plants and mutants have revealed how
RH elongation is regulated. For example, under conditions of limiting nutrients, such as iron and
phosphate, Arabidopsis forms longer hairs to increase the surface area for absorption (Guimil
and Dunand, 2006) and even initiates RHs from atrichoblast cells. The underlying mechanism
seems to be that under stress conditions, GL2 proteins can be down-regulated in atrichoblasts
thus changing their cell fate (Schiefelbein, 2000). Here it is interesting to note that RHs form the
interface (rhizosheath) between soil microorganisms and the plant. For example, nitrogen-fixing
bacteria have been isolated at this interface (Kwasniewski and Szarejko, 2006), suggesting the
existence of important environmental sensory systems on the RH that may subsequently affect its
own growth. During nitrate uptake it was observed that proton anti-porter activity could act as a
signal for nitrogen uptake (Meharg and Blatt, 1995). This signal could be the beginning of a
signalling cascade that includes ROP GTPases, possibly leading to RH elongation in response to
nitrogen treatment (Bloch et al., 2011).
Additional mutants have revealed aspects of the machinery of RH elongation. The
Arabidopsis roothairless mutant rhd2-1 (Jones et al., 2006) has normal RH initiation but
subsequently has no tip growth. The RDH2 gene was identified as encoding a NADPH oxidase
homologue of NOX (Foreman et al., 2003). NOX proteins produce extracellular superoxide
forms, and are involved in both RH growth and the pathogen response. For transcriptome
analysis, RNA was isolated from the RH differentiation zone (RHDZ), the segment above the
root tip as well as the elongation zone. The microarray experiments showed altered expression of
genes associated with the cell wall and membranes as might be predicted for a RH elongation
trait.
20
In barley, Kwasniewski et al. (2006) used cDNA Representational Difference Analysis to
show that rhl1, a mutant of RH elongation, was defective for a β-expansin protein. Expansins are
believed to play a role in the extension of the cell wall by weakening the links between different
compounds, specifically glucans. Expansin proteins are known to be involved in other processes,
including root elongation. There are two different families of expansins, A and B; in maize (and
most the monocots) the dominant form is expansin B. The growing zone of the root expresses
only a small proportion of expansin genes (Cosgrove et al., 2002).
Finally, in maize, the rth1 mutant has normal RH initiation but is defective in elongation.
The predicted RTH1 protein has 93% of homology with SEC3, part of a protein complex in
mammals that is required for proper exocytosis, a process by which a cell directs secretory
vesicles out of the cell membrane to facilitate membrane expansion. Plant RH elongation may
therefore be dependent on a process similar to the exocytosis phenomenon of yeast and mammals
(Wen et al., 2005). In spite of this progress, there remain many unknowns concerning the
relationship between nutrient (environmental) sensing and RH elongation, especially in
monocots such as maize.
2.5 Nitrate Absorption and Nitrogen Effects on Root Growth
2.5.1 Nitrogen demand
As long as 14 days after germination, maize plants are still utilizing nutrient reserves in
the kernel, but nutrient absorption from the soil becomes increasingly important after this stage
(Hochholdinger et al., 2004). During early maize development, nitrogen uptake is important for
the establishment of the plant; 15 - 35% of the plant nitrogen demand is to produce ribulose-1,5P2 carboxylase/oxygenase (RuBisCo) for carbon fixation (Hirel and Gallais, 2006). Under
optimal growth conditions (temperature, day length) phosphoenolpyruvate carboxylase (PEPC),
21
pyruvate orthophosphate dikinase (PPD), and RuBisCo promote carbon assimilation in the “dark
phase” of corn photosynthesis. The soluble protein concentration of these three enzymes is
promoted by increased nitrogen availability (Sugiyama et al., 1984), showing a clear relationship
between nitrogen availability and carbon assimilation. Of these enzymes, PEPC is the most
affected by nitrogen deficiency (Sugiharto et al., 1990). This is noteworthy because, under
conditions of limiting carbon assimilation, a decline is plant protein synthesis is observed, which
has been partially attributed to decreased levels of PEPC (Sugiharto et al., 1990). In fact, PEPC
appears to be one of the target genes of the cytokinin hormone zeatin. Nitrogen availability also
has a significant impact at later development stages, including on kernel yield (Gallais and Hirel,
2004). Maize kernels require a significant amount of carbohydrate (80%) compared to nitrogen
(1.5%) (Swank et al., 1982); however nitrogen has a great impact on grain yield, because of the
interactions between carbon assimilation and nitrogen availability (Swank et al., 1982; Hirel and
Gallais, 2006).
Nitrogen can be stored in cell vacuoles during the vegetative growth stage, and the plant
can later remobilize stored nitrogen from leaves to developing ears during grain fill (Gallais and
Hirel, 2004). In addition to its photosynthetic role, RuBisCo is an important source of nitrogen
storage in corn. Senescence of old leaves during ear development allows for the remobilization
of nitrogen, notably from RuBisCo, in yellowing varieties (that undergo leaf senescence during
the grain filling process); consequently 50%-60% of the grain nitrogen comes from this
remobilization and not from external sources during the grain filling period (Ping et al., 2004;
Hirel and Gallais, 2006).
22
2.5.2 Nitrate availability and uptake
Most of the inorganic nitrogen in the soil is produced by the decomposition of organic
nitrogen by soil microorganisms, a process referred to as mineralization. The two primary forms
of inorganic nitrogen in the soil for uptake by maize are nitrate (NO3-) and ammonium (NH4+)
ions (Okamoto and Okada, 2004). The source of nitrogen can differ according to the soil
condition (e.g. pH and temperature). Nitrate is the primary uptake form, mediated by three types
of membrane transporters, which sense and uptake different concentrations of exogenous nitrate
(Espen et al., 2004): the high affinity inducible transporters (IHATS), constitutive high affinity
transporters (CHATS), and a low affinity transport system (LATS). In Arabidopsis, the nitrate
transporters are generally classified into two gene families, NTR1 and NTR2, originally
discovered as low affinity and high affinity transporters, respectively. It is also noteworthy that
nitrogen uptake has been observed to influence the absorption of others critical nutrients such as
potassium (K+) (Okamoto and Okada, 2004).
Recently, NRT1.1 has been described not only as a nitrate transporter but also as a nitrate
sensor (Krouk et al., 2010). AtNRT1.1 seems to be an auxin transporter in the root epidermis. A
low concentration of nitrate appeared to activate auxin transport through NRT1.1. This transport
prevents the auxin accumulation necessary for lateral roots initiation. Consequently, NRT1.1
could inhibit lateral root branching in low nitrate conditions. Furthermore, though NRT1.1 has
only been considered as a low affinity transporter, it could switch to a high affinity transporter
depending on nitrogen concentrations and other conditions, thus having dual affinity to nitrate
(Gojon et al., 2011).
23
2.5.3 Nitrate assimilation
Following uptake, nitrate is used in numerous pathways including the production of
amino acids. In order to be assimilated into these pathways, nitrate is converted to nitrite by
cytoplasmic Nitrate Reductase (NR). Nitrite is then reduced to ammonium by Nitrite Reductase
(NiR) in the plastids. Nitrite is toxic to the plant and therefore the rate at which it is reduced is
very important. Microarray experiments have shown that the genes involved in nitrite reduction
are activated ~20 minutes after the soil is treated with nitrate (Wang et al., 2003). Although most
of the nitrate is converted in the leaf, this study shows that the expression of more genes is
affected in the root and these changes precede those in the shoot. A rapid response to available
nitrate and activation of these pathways is regulated by two types of signaling: first, nitrate itself
induces dramatic changes in gene expression, but further systematic effects can also be brought
about by hormones (Takei et al., 2001; Takei et al., 2002); cytokinins, primarily zeatin, seems to
be particularly important in mediating the plant response to available nitrate. In addition, it has
been shown that under N or Phosphate (P) limitation, the concentration of zeatin decreases
compared to normal conditions of N or P (de Groot et al., 2003). These pathways are
summarized in Figure 2.5 below:
24
Figure 2.5: Sensing of nitrogen availability in maize.
25
Although most of the plants are able to use nitrate and ammonium as nitrogen sources, it appears
that ammonium as the sole source could be toxic for maize cell metabolism, whereas rice can
utilize both forms without apparent toxicity (Kosegarten et al., 1997). Rice could have a more
efficient GS/GOGAT system to absorb excess ammonium compared to maize.
2.5.4 Nitrate effects on root growth
Whereas low levels of available nitrate result in very poor kernel yield, a high
concentration of nitrate results in the inhibition of root growth. The effects of nutrition and the
environment on maize root development have been widely studied, particularly their effects on
lateral root growth (Tian et al., 2007). In this article, the authors confirmed that a low
concentration of nitrate in the soil has no effect on root growth, whereas concentrations > 5 mM
reduce the elongation of the cells of the roots. A high concentration of nitrate in the plant is
correlated with a decreased level of auxin in the root, and auxins are known to normally trigger
growth of the root system (Tian et al., 2007). Auxins are synthesized in the young leaves and
transported to the root. In contrast, cytokinins are synthesized in the root and can be transported
to the shoot, where they can act as auxin antagonists; interestingly, cytokinins help to mediate
the sensing of nitrogen availability Therefore, a high concentration of nitrate in the soil, via
cytokinin, leads to decreased auxin transport from the shoot to the root, resulting in decreased
overall root growth. In contrast, however, the local presence of nitrate in the soil may stimulate
localized root branching including promoting lateral root growth to permit more efficient
nitrogen uptake. Under a local high concentration of nitrate, auxin transport from the shoot to
roots promotes the elongation of lateral roots (Guo et al., 2005); the number of lateral roots (root
initiation), however, is not affected. Therefore local nitrate stimulates root branching by
26
promoting cell elongation, whereas global nitrate reduces growth by reducing root cell
elongation.
2.5.5 Localization of nitrogen transporters
Some nitrogen transporters have been shown to be tissue localized. For example, an
ammonium transporter (LeAMT1) and a nitrate transporter (LeNTR1-2) were selectively
expressed in the RHs of tomato seedlings (Lauter et al., 1996). Interestingly, LeNRT1-1 was
preferentially expressed in the root following ammonium exposure, and mainly expressed in the
RH after nitrate treatment (Lauter et al., 1996). Furthermore, LeAMT1-1 was strongly expressed
in RH during nitrogen starvation, whereas LeAMT1-2 was expressed after ammonium resupply
(Von Wirén et al., 2000).The compartmentalization of nitrate transporter expression has also
been detected in rice: the OsNRT2.2 high affinity transporter was selectively expressed in the
root and OsNRT2.4 was specific to leaves and the base of lateral root primordia (Feng et al.,
2011).
2.5.6 Promoter elements associated with nitrogen induction of gene expression
Upon exposure to nitrate or ammonium, approximately 10% of the plant genome shows
changes in gene expression (Konishi and Yanagisawa, 2010). Induction of nitrogen related genes
is in part due to transcriptional regulation by cis-acting promoter elements. Recently, a nitrogen
response element (NRE) cis-acting motif, 5’-tGACcCTT-N(10)-AAG-3’, was discovered in the
promoter sequences of nitrite reductase (NiR1) from different dicot species (Konishi and
Yanagisawa, 2010).
In the nitrate reductase (NIA1) gene of Arabidopsis, nitrate was unable to induce the
promoter; surprisingly, it was the downstream sequence that was responsive to nitrate.
Interestingly, the downstream sequence of NIA1 contained the same NRE site (5’-tGACcCTT-
27
N(10)-AAG-3’) as NiR1 (Konishi and Yanagisawa, 2011), though experiments have not yet
confirmed that this NRE is functional.
2.5.7 Improving early season nitrogen uptake at the juvenile stage
As noted earlier, it is estimated that <50% of nitrogen fertilizer added to a maize field is
actually taken up by plants. Fertilizer is typically added by farmers before seed germination (preemergent fertilizer) or in the initial weeks after germination (plant juvenile stage of
development). Studies have suggested that increasing nitrogen uptake will require increasing the
shoot demand for nitrogen (Peng et al., 2010). If true, then increasing early shoot growth and/or
root growth may allow for improved early-season nitrogen uptake. In addition, there is a need to
understand which nitrogen uptake, transport and assimilation genes are expressed during juvenile
development, and subsequently to correlate changes in expression between genotypes to
improved early-season nitrogen uptake.
There has already been interest in accelerating early plant development (Brookes and
Barfoot, 2006), but in part as a weed tolerance strategy. In the early part of the growth season,
maize is highly susceptible to weed competition. Herbicide tolerant transgenic lines have been
engineered (Johnson and McCuddin, 2009), but this technology has either met with resistance by
some nations (e.g. in Europe) or is unaffordable (e.g. in Sub-Saharan Africa). One proposed
solution would be to outcompete weeds by accelerated maize crop. Both of these objectives will
require a better understanding of maize juvenile development.
2.5.8 Effects of water stress on plants and root hairs
In addition to nitrogen, water limitation affects maize globally (Iglesias et al., 1996;
Rosenzweig et al., 2001). Conserved responses to drought at the whole plant or organ level
include altered root architecture for improved water uptake, changes in the cell wall to prevent
28
water loss, reduced stomatal conductance to minimize transpiration, and production of
osmoprotectants which act to balance the osmotic pressure inside the cell (Yamaguchi-Shinozaki
and Shinozaki, 2005). The plant hormone abscisic acid (ABA) has been shown to coordinate
many responses to drought (Umezawa et al., 2010). Drought signalling involving ABA involves
a complex signal transduction cascade (Umezawa et al., 2010).
Surprisingly, no studies have reported the impact of water stress on the root hair
transcriptome, even though root hairs and the root epidermis are the cells in direct contact with
soil moisture. Transcriptome studies involving water stress have however been conducted using
intact organs or whole plants (Oono et al., 2003; Rabbani et al., 2003; Lee et al., 2009; Marino et
al., 2009; Rodriguez et al., 2010; Zheng et al., 2010; Wang et al., 2011). These studies
demonstrate the central importance of the transcription factor family DREB/CBF (dehydration
response element binding protein/C-repeat binding factors) (Yamaguchi-Shinozaki and
Shinozaki, 2005; Agarwal and Jha, 2010), numerous other transcription factors (YamaguchiShinozaki and Shinozaki, 2005; Agarwal and Jha, 2010) and additional hormones including
jasmonates in particular (Oono et al., 2003; Young et al., 2004; Walia et al., 2007; Rodriguez et
al., 2010; Wang et al., 2011). It remains unknown whether root hairs respond to water
availability similarly to intact roots and shoots at the molecular level.
2.6 Microarray Techniques and Data Analysis
2.6.1 Background
Microarray analysis represents an effective approach to characterizing global gene
expression. A genechip or microarray consists of a small glass surface upon which tens of
thousands of DNA sequences or probes can be covalently attached (Rensink and Buell, 2005).
The sequences can represent every gene in the genome of a species. The sequences can be
29
assembled directly on the slide (Affymetrix arrays) or cDNAs can later be attached to the slide
by a robotic spotter (Amersham arrays). Each of the spots contains millions of copies of the same
DNA sequence.
Subsequently, RNA samples from the selected tissue, called target RNA, are hybridized
onto these spots. Before hybridization, the target RNAs are first reverse-transcribed into cDNA.
The cDNA is then amplified and labeled with a florescent molecule to allow for the amount of
target RNA that hybridizes to each spot (probe) to be quantified. Probes (attached DNA
population) are in excess compared to the possible target RNA, and consequently the DNA probe
spot will never in theory, be saturated.
There are three major types of microarrays: cDNA microarrays, genomic sequence tag
microarrays (GST) and Affymetrix oligonucleotide microarrays (Rensink and Buell, 2005). The
cDNA microarray uses cDNA sequences covalently attached to a glass slide. This cDNA usually
comes from an EST (Expressed Sequence Tag) gene bank. The cDNA chip is the easiest to set
up in a laboratory but the long length of the cDNA decreases the reliability of the result because
of the lack of hybridization specificity it permits. Genomic sequence tag (GST) microarrays are
oligonucleotide arrays (e.g. Agilent). They have spotted oligonucleotides of 70-80 bases,
representing the whole or a part of a genome. This technology is intermediate between the
Affymetrix array (consisting of 25 nucleotide oligos; described in detail below) and the longer
cDNA microarrays. cDNA and GST genechips that can be hybridized by two target samples (e.g.
from two different treatments or tissues) are called two colour microarrays.
The advantage of the shorter Affymetrix oligonucleotide array is enhanced specificity for
the target sequence when compared with the cDNA array. However, in this case, only one
sample is hybridized to the chip, and therefore two chips are needed to compare two samples.
30
2.6.2 Affymetrix genechip platform
2.6.2.1 Construction of the Affymetrix chip
Affymetrix arrays can represent an entire genome: examples include the Arabidopsis
ATH1 chip and the human HG-95Av2 chip. The production of these genechips is special
because the oligonucleotide probes are synthesized directly onto the slide by a combination of
photolithography and combinatorial chemistry (DalmaWeiszhausz et al., 2006) as summarized in
Figure 2.6 below. The oligonucleotides are synthesized in a succession of chemical reactions that
covalently link individual nucleotides, using a process that is triggered by ultraviolet light. In
order to create the desired sequence, a mask is first applied to the slide. The mask protects all the
positions on the chip except those sequences that require addition of a specific nucleotide (A, C,
G or T) for that particular cycle. Then the remaining free nucleotides are washed away and the
mask is changed before another cycle of nucleotide addition starts. These cycles continue until
each probe receives their specific 25 nucleotides according to the chip design.
31
Figure 2.6: Affymetrix probe synthesis. (A) Schematic of the mask process that attaches specific
nucleotides to growing oligonucleotide chains in response to ultraviolet light. (B) Schematic of
the oligonucleotide chemical synthesis process (DalmaWeiszhausz et al., 2006).
32
The Affymetrix chip consists of two types of covalently attached oligonucleotide probes:
the perfect match (PM) probe and the mismatch probe (MM) (DalmaWeiszhausz et al., 2006).
Each gene on the chip is represented by 11-20 PMs and 11-20 MMs. Whereas PM probes are
specific to the desired target RNA, the MM probes are less specific and serve to measure the
noise corresponding to all the non-specific hybridizations that can occur to PM gene probes. In a
later section, I will further explain how the PM and MM probe data are analyzed.
2.6.2.2 The hybridization procedure and image acquisition of the array
The procedure is summarized in Figure 2.7 below. The mRNAs reflect levels of
transcription and RNA stability. After extraction, mRNAs are reverse-transcribed into doublestranded cDNAs, which then serve as stable templates for transcription and amplification of an
RNA copy (cRNA) by T7 RNA Polymerase. Subsets of the ribonucleotides included in the
reaction are biotin-labeled UTP and CTP. Each cRNA is shredded into small fragments of 20200 bases, all of which are hybridized onto the genechip. Then, the chip is exposed to
streptavidin-phycoerythrin, a fluorescent complex that binds to biotin. The fluorescence signal
can be amplified by using an anti-Streptavidin antibody (goat) and biotinylated goat IgG
antibody. Phycoerythrin is a red-orange fluorescent molecule that is excited at 488 nm and emits
at 578 nm. Streptavidin provides the connection between biotin and phycoerythrin. After a series
of washes, the chip is scanned with a confocal laser. The fluorescent signal of each spot on the
array is recorded. The array signals are transferred in relative intensity numbers into data tables,
which serve as the basis for the expression data analysis.
33
Figure 2.7: The Affymetrix RNA labeling, hybridization process. This figure was adapted from
previous publications (Lockhart and Winzeler, 2000; DalmaWeiszhausz et al., 2006).
34
2.6.3 Quality control of the data
Data quality controls are used to check the range of intensities on the microarray as well
as the experimental raw data. The aim is to check whether all the slides can be compared to one
another and to determine which inter-slide normalization steps are required to do so. Slide-toslide comparisons can only be made if two criteria are met: (1) more than 50% of the genes have
a similar expression level under two compared conditions (e.g. A, B); and (2) the frequency
graph of the expression ratio (A/B) has a normal distribution (Quackenbush, 2002; Bolstad et al.,
2005; Bolstad et al., 2005; Rayner et al., 2006). These conditions can be represented graphically
using a box plot or an intensity frequency plot. Quality control visually identifies an outlier set of
data, and in this case, identifies chips that should be eliminated from the analysis.
2.6.4 Normalization and choice of normalization
The large density of data generated by microarrays can create unwanted biases that can
change the results if suitable controls are not applied (Quackenbush, 2002; Bolstad et al., 2005).
Normalization methods have the goal of managing these variations and they help to determine
the real biological pattern of the data. The source of variation can be between different chips or
within the same slide. Therefore two levels of normalization are possible: intra- and inter-slide
normalization. Usually the hypothesis used to normalize microarray data is that a majority of the
genes have no differential expression under a range of conditions. Thus, there are two major
methods to normalize between Affymetrix slides: (1) use a constant factor of normalization (the
median); or (2) use an adaptive factor of normalization like the lowess or quantile normalization
(Quackenbush, 2002; Irizarry et al., 2003; Bolstad et al., 2005; Boes and Neuhäuser, 2005 ). An
adaptive factor uses 70% - 90% of the data. After the data are cut in frame, a median
35
normalization is applied to this frame. A specific factor of normalization is then applied to each
frame and all frames are regrouped.
In order to visualize the effect of the normalization on the data, a scatter plot with a logscale is used. Data is first transformed to a log-scale before the normalization. Since non-specific
hybridization would result in signal noise or background, as noted earlier, each gene is
represented on the array by both perfectly matched oligonucleotide probes (PMs) as well as
oligos containing mismatches (MMs) to detect the signal noise. Hence, the subtraction step, PM
minus MM, should remove the noise during normalization. The first attempt to then normalize
the data involves median normalization, in which the data are artificially centered on a gene
expression ratio of one where there is no change between two compared conditions; the data are
transformed on a logarithmic scale to facilitate the visualization. However in reality MM probes
sometimes produce an intensity superior to the PM probes, and in this case different methods are
used based only on the PM intensities. The most popular of these methods is the Robust Multichip Average method, RMA (Irizarry et al., 2003). RMA performs a background correction
based on all the intensities, a form of quantile normalization, that uses local regression
adjustments to center the ratio of gene expression data around one according to the normalization
hypothesis that a majority of genes have the same expression level in two compared conditions
or two Affymetrix genechips (so have a differential expression of one); RMA also standardizes
the intensities at a multi-chip experiment level.
2.6.5 Statistical analysis and production of a list of differentially-expressed genes
The large quantity of data generated by microarrays increases the possibility of making
an error that a particular gene is differentially expressed between two conditions when it is in
fact not (error type II), or the possibility of considering a gene as not differentially expressed
36
when it is in reality (error type I) . For a gene to be classified as having differential expression,
the null hypothesis must be rejected; this hypothesis states that all genes have similar expression
under two or more conditions unless otherwise shown (Dudoit et al., 2003). A reasonable
statistical test that might be used to test this hypothesis has the probability of generating Type II
error that can lead to a rate of false positives in a gene list (Dudoit et al., 2003). Therefore, in
rejecting the null hypothesis, a balance must be achieved between generating a reliable gene list
(high stringency), while maximizing the number of true gene candidates (large screen). To
generate tissue-specific or nitrate-responsive gene candidates, use of an ANOVA coupled with
an FDR multiple testing correction (type II error) and a Tukey’s post-hoc test to compare all the
treatments, should be effective. The post-hoc test minimizes the error rate, and permits pair wise
comparisons while taking into account the range of data generated by all treatments.
2.6.6 Validation of the results
Microarray analysis is a powerful tool to generate a list of candidate genes that have a
high probability of differing in expression intensity under two different treatments or
developmental stages. Because false positives may be a problem, however, independent methods
are needed to confirm the differential expression of the candidate genes. In order to confirm that
a gene has altered expression under two conditions, a house-keeping gene (e.g. actin) is used for
comparison as its expression should remain constant under different conditions. Another internal
control used is to quantify and normalize for levels of ribosomal RNA from both samples.
Finally, after microarray analysis, candidate gene expression is typically validated, such as using
semi-quantitative Reverse-Transcription Polymerase Chain Reaction (sqRT-PCR). In sqRTPCR, total RNAs are reverse-transcribed into cDNAs which are then are amplified by PCR using
gene-specific primers. In this method (Joyce, 2002; Choquer et al., 2003; Wang et al., 2003), the
37
final PCR product reflects the amount of target RNA in the initial sample. Quantitative RT-PCR
is 100-fold more sensitive than the microarray method (Varshney et al., 2005), but as this is a
single-gene methodology, it is extraordinarily difficult to analyze an entire genome using qRTPCR. Therefore, only a subset of the candidate genes is tested using this method.
2.7 Examples of Published Maize Transcriptome Studies
2.7.1 Introduction to maize transcriptome studies
Agriculture will be challenged by climate change, and crop breeding will have to meet
this challenge (Kim et al., 2006). Accordingly, cereal transcriptome research papers have largely
focused on environmental stresses. For example, the greenhouse gas effect, particularly the effect
of increased carbon dioxide, has been monitored in maize (Kim et al., 2006). Other stresses that
have been studied in maize at the transcriptome level have included UV light stress (Casati and
Walbot, 2003, 2004), and salt stress (Wang et al., 2003; Chao et al., 2005; Ueda et al., 2006). In
addition to the stress response, given the economic importance of corn kernels, microarray
analysis has also focused on maize reproductive tissues of different maize lines (inbreds and
hybrids). For example, during the grain fill stage, 2403 mRNAs (EST sequences) were shown to
be specifically expressed in the endosperm of maize kernels (Verza et al., 2005). In maize
kernels, the transition between maternal and embryo expression has also been studied using
microarray profiling (Grimanelli et al., 2005).
2.7.2 Maize leaf transcriptome studies
Several microarray experiments have been conducted on maize leaf tissues. For example,
laser capture micro-dissection (LCM)-based profiling has demonstrated that the leaf epidermis
expresses high levels of mRNAs encoding defense proteins and secondary metabolite enzyme
(Nakazono et al., 2003). Below the epidermis, the bundle sheath and mesophyll cells are
38
responsible for photosynthesis and carbon assimilation respectively in maize; transcriptome
analysis has recently demonstrated the specialization of these two cell types, as 18% of the
transcriptome differs between the bundle sheath and mesophyll (Sawers et al., 2007). In the leaf
vascular tissue, the predominance of lignin-related gene expression has also been confirmed by
large scale expression analysis (Nakazono et al., 2003). Surprisingly, retrotransposon and antisense RNA have been shown to be expressed at high levels in the maize shoot apical meristem
(Jiong, 2006; Ohtsu et al., 2007). The reason for this phenomenon still needs to be elucidated. In
addition, the importance of anti-sense RNAs as regulators of gene expression has been suggested
by their expression in juvenile leaves (as well as in anthers) (Ramon et al., 2007). An additional
study examined gene expression in maize leaves during the transition from juvenile to adult
stages, and showed that the largest subset of expressed genes in juvenile leaves were related to
photosynthesis (Strable et al., 2008). Recent transcriptome studies have focused on gene
expression over a 24 hour period in juvenile maize leaves, to show the effect of day/night cycles
on gene expression (Jończyk et al., 2011). Another recent study described gene expression along
a tip-base gradient within a juvenile maize leaf (Li et al., 2010). This latter study showed that the
growth zone of the leaf (base) involved expression of genes involved in respiration, cell
elongation and the production of chlorophyll precursors including heme-binding proteins;
whereas genes that were selectively expressed at the tip were involved in photosynthesis, sugar
storage and export .
2.7.3 Maize root transcriptome analysis
The most careful and precise examination of global gene expression in the root has been
conducted not in maize, but in Arabidopsis, by Dr. Phil Benfey’s laboratory at Duke University
(Birnbaum et al., 2003; Birnbaum and Benfey, 2004). Similarities do exist in root development
39
between cereals and Arabidopsis, but cereal roots also differ in some aspects including having a
predominance of adventitious roots (Hochholdinger and Zimmermann, 2007).
Few studies have been published on gene expression during the early stages of root
development (seedling roots) in cereals. Root transcriptome analysis has determined that 22000
genes are expressed in maize roots (Poroyko et al., 2005). Dembinsky et al. (2007) examined cell
type-specific gene expression in maize inbred B73 in the formation of lateral roots from the
pericycle. They concluded that 32 non-characterized genes were preferentially expressed in the
pericycle (Dembinsky et al., 2007). Cell type-specific root transcriptome analysis was also
conducted in the maize root apical meristem and the surrounding quiescent center and root cap
(Jiang et al., 2006). Critically, no studies have been conducted on the maize root hair, including
responses to nutrients.
2.7.4 Maize whole plant transcriptome studies
A detailed analysis was conducted to compare the transcriptomes of development maize
roots (2-, 8- and 14 day-old), leaves (blade and sheath), husks, silks, the ear and embryos (Cho et
al. 2002). This analysis was conducted using a small array consisting of 5376 unique ESTs.
Surprisingly, this experiment suggested that husks, the modified leaves that surround the ears,
have a transcription pattern closer to reproductive organs than to other leaves. More recently, a
comprehensive study compared gene expression in different organs across different stages of
maize development; these authors subsequently focused on genes encoding lignin biosynthetic
enzymes (Sekhon et al., 2011).
40
2.8
Gene expression regulatory elements in plants
2.8.1 Definition of cis-acting elements
Among the transcriptome analysis methods, microarrays and next-generation sequencing
facilitate the identification of co-expressed genes. Transcriptional co-expression is primarily
caused by shared cis-acting promoter elements, which are recognition sites of transcription factor
(TF) complexes. During transcriptional activation, a TF complex forms on the DNA promoter
sequence and recruits RNA polymerase to initiate transcription. The affinity of a TF for its DNA
target can be modulated by nucleotide substitutions within the cis-element. A motif that permits
sequence polymorphisms is called a degenerative motif.
A practical method was needed to define degenerative motifs, and this led to the creation
of the position weight matrix (PWM). The PWM defines a motif based on the frequency of each
nucleotide being present at each position within the motif, after the cis-elements are aligned
(Stormo, 1990). The PWM is composed of four rows representing the DNA alphabet A, C, G and
T. Each column represents one nucleotide position in the motif, so a motif of 6 bases would have
6 columns in its PWM. Each row-column combination corresponds to a number which shows the
occurrence of the base (row) at the motif position, as shown in Table 2.1 (Stormo, 1990).
The PWM can be transformed into a probability matrix depending of the occurrence of
each base in the genome. The consensus sequence is generally used to describe a motif.
However, another way to represent a motif is to use a sequence logo (Stormo, 2000). In a
sequence logo, the height of each base at a particular position represents the probability of
occurrence of that nucleotide compared to the background (Stormo, 2000; Crooks et al., 2004).
41
Table 2.1: Position weight matrix example
DNA base
A
C
G
T
Consensus sequence
1
1
3
2
10
Nucleotide position
2
3
4
15
1
9
0
2
1
0
2
1
1
11
5
5
12
1
1
2
T
A
A
T
A
Following microarray clustering and alignment of the corresponding upstream regions, a motif
can be identified from available databases and online tools to predict specific enhancer motifs.
2.8.2 Plant cis-element databases and the search for known promoter motifs
Databases for promoter identification and characterization were developed first for
animal eukaryote genomes, an example being TRANSFAC (Biobase). At least five
comprehensive enhancer motif databases exist for plants. One of the most popular databases is
the Arabidopsis Gene Regulatory Information Server (AGRIS), which is dedicated to
Arabidopsis cis-elements characterized from molecular and genetic experiments (Yilmaz et al.,
2011). AGRIS includes ~100 cis-elements. This website also has a list of 1770 transcription
factors discovered in Arabidopsis. AGRIS authors are currently trying to connect all
transcription factors with their potential DNA promoter targets through a new database called
AtRegNet (At Regulatory Networks) that contains ~11,000 cis-element-transcription factor
interactions (Palaniswamy et al., 2006).
Second, Athamap is a cis-element database containing 115 transcription factors and gives
the user the option to retrieve this motif in promoter sequences (Bülow et al., 2010). Athamap is
also based on Arabidopsis promoter motifs.
42
The Plant Promoter Database (PPDB) is one of the most comprehensive databases
available to find promoter cis-elements in plants, but at this time, it is limited to rice (Oryza
sativa) and Arabidopsis thaliana (Yamamoto and Obokata, 2008). Sequences are found using
gene names or keyword searches. Results are correlated with regulatory sequences from the
PLACE database (described below).
PLACE (Higo et al., 1999) is an enhancer motif database that covers all plant species,
including maize. Plant cis regulatory elements are registered and updated from published articles.
However, to use this database, the Genbank accession number or Pubmed ID is necessary to find
gene promoter sequences and motifs.
PlantCARE (Lescot et al., 2002) is complementary to PPDB and PLACE, as it is a tool to
find motifs in unknown promoter sequences. To use this tool, FASTA format promoter
sequences from EMBL, TRANSFAC or MEDLINE must first be imported. Cis-acting elements
are then predicted in silico. However, PlantCare is not regularly maintained and can contain
outdated data.
2.8.3 Promoter-Enhancer Motif Prediction
Three main methods exist to find de-novo motifs from a list of promoters from coexpressed genes or from inter-species orthologs (D'Haeseleer, 2006):
The first motif discovery method utilizes enumerative algorithms that search the overrepresented word sequences with a size ranging from 6 to 12 bp. The occurrence of each possible
motif word is pre-calculated for different organisms in order to calculate the statistical
significance of these over-represented motif words compared to the relevant background.
Weeder (Pavesi et al., 2007) and Seeder (Fauteux et al., 2008) are among the enumerative
algorithms that are adapted for plants. Weeder allows only one or two substitutions in the motif
43
word. Based on the different substitutions allowed, a consensus sequence can be established. The
disadvantage of these approaches is the difficulty in finding more degenerative motifs. Seeder
has tried to partly solve this problem.
The second motif discovery method, the deterministic algorithm, finds de-novo motifs
based on the Expectation-Maximisation method (Bailey and Elkan, 1994). This method divides
sequences into subsegments, and all subsegments are systematically processed as a possible
motif. The expectation step consists of a probability calculation as to whether each subsegment
sequence occurs non-randomly within the input promoters based on its PWM. The maximisation
step then refines the PWM based on the new probability of occurrence in the subsegments
defined early during the expectation phase. The subsegments with the highest probability after
EM are chosen and modified by reiterating the EM algorithm until a candidate motif cannot be
improved (Bailey and Elkan, 1994).
The third motif discovery method is a complete probabilistic method such as Gibbs
sampling (Lawrence et al., 1993). This method is similar to expectation-randomization, except
that it defines the length of subsequences that are randomly picked. The algorithm reiteratively
searches within input promoters until a high probability match is found, defined as having PWM
significantly different from the expected background sequences at the same position. During the
process, the motifs that did not reach the model expectations are eliminated from the subsequent
reiteration.
2.8.4 Transcription factors and promoters in plants
The promoter region is organized into five regulatory regions: the core promoter (-30 +1),
the proximal promoter (-100 -45), the distal promoter up to 2 kb upstream of the transcription
starting site (+1), and any downstream promoter elements after the transcriptional start site
44
(Gurley et al., 2007). The core promoter is the site of binding of the general transcription factors
that constitute the basal transcription machinery (Gurley et al., 2007). The proximal and
downstream promoters contain binding sites for proteins that participate in RNA polymerase
complex formation. The regulatory elements are found in the proximal region but mainly in the
distal promoter; the cis-acting element binding sites for the transcription factors (TFs) are located
in these latter promoter regions. However it is also possible to find regulatory elements in an
intron and/or downstream of the gene (Gidekel et al., 1996; Dorsett, 1999; Konishi and
Yanagisawa, 2011).
Transcription factors (TFs) are proteins translated in the cytosol, which subsequently
enter into the nucleus, a process mediated by nuclear localization amino acid sequences that
interact with nuclear pore complexes, or by TFs interacting with helper proteins such as
importins (Ye et al., 2011). The TF phosphorylation state can also be important in this process::
the phosphorylation status can affect binding site recognition by the TF or affect its ability to
localize to the nucleus (Kirchler et al.; Poon and Jans, 2005). As a result, TF localization to the
nucleus is now considered to be the first step in the regulation of gene expression, as it represents
a rapid means to respond to external or cellular stimuli.
TFs represent ~7% of the Arabidopsis genome with 1770 TFs identified to date (Yilmaz
et al., 2011). These TFs are grouped into at least 42 TF families (Riechmann, 2007) that are
categorized based on their DNA binding domains or biological activity. In rice and Arabidopsis
combined, the predominant TF categories are MYB, bHLH, AP2/ERF (ethylene responsive
factor), MADS, NAC, WRKY, Homeodomain and bZIP families (Riechmann, 2007). Grotewold
and Gray (2009) have hypothesised that maize could have ~4000 transcription factors given the
complexity of its genome (Grotewold and Gray, 2009).
45
2.8.5 Approaches to discover and study candidate master gene regulators
Yeast one-hybrid constitutes the most popular method to capture proteins that bind to a
known promoter of interest (Luo et al., 1996). Chromatin immuno-precipitation (ChIP) is used to
find promoter targets of a known DNA binding protein in vivo. To accelerate the discovery of all
DNA binding sites of a TF, ChIP can be combined with a tiling array that has probes from the
complete target genome including intergenic regions. This method is called ChIP on chip (Ren et
al., 2000). Short nucleotide high throughput sequencing has simplified this process with the
ChIP-Seq method (Robertson et al., 2007; Schmid and Bucher, 2007).
Once the interaction with its DNA binding site has been experimentally characterized, a
TF of agronomic interest can be used for further experiments, including the construction of
transgenic plants (e.g. over-expression or RNAi). Natural sequence variants of the TF can also be
screened and a desirable allele introgressed into agronomically superior genotypes. Agronomic
improvement by these methods is challenging, however, as other factors such as interacting
proteins, small RNAs or modifiers of chromatin conformation, can all affect gene expression
(Zhu, 2007).
2.9 Plant transformation with genes of interest and the limits of plant
regeneration
Following identification of a useful gene, such as one encoding a beneficial regulatory
protein for nitrogen use efficiency, drought tolerance or early seedling growth, a significant
challenge is introgressing this gene into an agronomic line of interest. Apart from traditional
breeding which requires the parent of the gene donor to be from the same or related species, gene
introduction requires in vitro transformation using recombinant DNA followed by shoot and root
regeneration of the transformed cell(s). In general, de novo shoot organogenesis (shoot
46
regeneration) in tissue culture occurs in two steps: a cell “dedifferentiation” step followed by
shoot organogenesis (Christianson and Warnick, 1983). The first step requires a high level of
auxin hormone and a low level of cytokinin, whereas the second step requires high cytokinin and
low auxin.
Unfortunately, in maize and many other crops, gene transformation is significantly
limited by the inability of most genotypes to regenerate shoots from explants or callus (Johnson
and McCuddin, 2009). For example, primarily only one inbred in maize, A188, is known to
regenerate shoots at high frequencies from callus. Five QTLs are responsible for this high
frequency of shoot regeneration; these have recently been introgressed into the more
agronomically relevant inbreds B73 and Mo17 (Green and Phillips; Johnson and McCuddin,
2009). However, neither the genes nor mechanism underlying the A188 high regeneration trait,
have been reported. Discovery of these genes and/or associated physiological traits could
dramatically accelerate basic research and biotechnological applications of agronomically useful
genes.
2.10 Need for stage-, organ- and cell type-specific promoters in maize
To enable transgenic approaches for improved nitrogen use efficiency, there is a need for
promoters that are specific to a developmental stage, organ or cell type. In general, the most
widely used promoters in maize are all constitutive, including the CaMV35S promoter, the rice
actin promoter and the maize ubiquitin promoter. Overexpressing a regulatory factor or nitrogen
transporter in the incorrect organ or stage of development could lead to yield loss rather than
improvement as shown by numerous transgenic studies in Arabidopsis. In particular, there is
interest in discovering promoters that are specific to root hair cells as these constitute the primary
surface area for nitrogen absorption. A second type of promoter of interest in maize would be
47
specific for the juvenile stage of development (seedlings) for targeting accelerated growth and/or
direct nitrogen uptake when fertilizer applications are in excess of plant demand. A third type of
promoter of interest would be post-flowering promoters as this is the stage of peak nitrogen
demand in maize (Peng et al., 2010). Post flowering root promoters could be used to increase
nitrogen uptake, whereas post-flowering leaf promoters could be used to improve nutrient
scavenging from senescing leaves and direct them to growing kernels. Any of these promoters
could also be used for basic research applications in maize.
48
2.11 Hypotheses and Objectives
Hypothesis 1: Compiled results of software tools will increase promoter motif discovery in
maize to enable future targeted interventions in nitrogen improvement.
Objective 1: To create an ensemble software program for the maize research community that
retrieves and analyzes co-expressed promoters and then applies an ensemble algorithm to enable
de novo promoter motif discovery in maize.
Hypothesis 2: Microarray analysis of different stages of juvenile maize development will assist
in the identification of juvenile stage-selective promoters.
Objective 2: To apply motif discovery software to juvenile stage-specific microarray data to
identify promoter motifs that are selective for different stages of juvenile maize development.
Hypothesis 3: Microarray analysis during different phases of maize development will assist in
the identification of phase-selective promoters in maize.
Objective 3: To apply motif discovery software to microarray data collected before and after the
juvenile-adult and floral transitions in maize to identify phase-selective promoter motifs.
Hypothesis 4: Nitrogen related genes in maize show spatio-temporal expression.
Objective 4: To analyze microarray expression data of genes related to nitrogen, based on
expression data from different tissues and developmental stages in maize.
49
Hypothesis 5: The plant root hair transcriptome responds to a change in the external nitrate
concentration.
Objective 5: To optimize a system for growing maize root hairs and harvesting root hair-specific
RNA, then use this RNA to undertake microarray analysis of RH in response to added nitrate.
Hypothesis 6: The plant root hair transcriptome responds to a change in water availability.
Objective 6: To optimize a system for growing maize root hairs and harvesting root hair-specific
RNA, then use this RNA to undertake microarray analysis of RH in response to added water
following an extended period of drought.
Hypothesis 7: Important shoot regeneration genes that may assist long-term efforts to improve
maize transformation, can be identified by analyzing transcriptome changes associated with
QTLs that promote shoot regeneration in Arabidopsis.
Objective 7: To conduct transcriptome analysis of the effects of QTLs that promote shoot
regeneration in Arabidopsis in the absence of auxin.
50
3. Promzea: A pipeline for discovery of regulatory motifs in maize
(Zea mays L.)
Author contributions: Christophe Liseron-Monfils conducted all Bioinformatics analyses and
script programs.
51
3.1 Abstract
The discovery of genetic networks and cis-acting DNA motifs underlying their regulation
is a major objective of transcriptome studies. The recent release of the maize genome (Zea mays
L.) has facilitated in silico searches for regulatory motifs. Several algorithms exist to predict cisacting element, but none have been adapted for maize. A benchmark data set was used to
evaluate the accuracy of three motif discovery programs: BioProspector, Weeder and MEME.
Analysis showed that each motif discovery tool had limited accuracy and appeared to retrieve a
distinct set of motifs. Using the benchmark, statistical filters were optimized to reduce the false
discovery rate. Retained motifs from all programs were subsequently combined to improve motif
prediction. These principles were integrated into a user-friendly pipeline for motif discovery in
maize called Promzea. A user enters cDNA sequences or gene IDs; corresponding upstream or
first-intron sequences are retrieved from the maize genome. Predicted motifs are filtered,
combined and ranked. Promzea searches the maize genome for genes containing each motif,
providing the user with the gene list and annotation. Promzea was validated by its ability to
retrieve the experimentally defined binding sites of transcription factors C1 and P, regulators of
the maize anthocyanin and phlobaphene biosynthetic pathways, respectively. Promzea also
retrieved motifs not previously defined. Genome-wide motif searches by Promzea predicted that
transcription factors (C1, R, P, and PAC1) and additional anthocyanin biosynthetic enzymes
share the known and novel regulatory motifs potentially identifying a broader network of coregulated genes. Promzea is a publicly available tool for the maize community.
3.2 Introduction
One of the key objectives of global gene expression studies is the identification of
transcription factors and their DNA binding sites responsible for co-expression of genes. DNA
52
binding sites can be predicted in silico by searching regulatory regions of co-expressed genes for
overrepresented motifs (MacLean et al., 2008; Vandepoele et al., 2009). Recently, the genome
sequence of maize (Zea mays L.) was released (Schnable et al., 2009), facilitating searches for
cis-acting motifs in one of the world’s most important crops. Useful motif discovery tools
already exist for maize including Grassius (Yilmaz et al., 2009) and PlantPAN (Chang et al.,
2008), but they retrieve only known, experimentally defined motifs from databases such as
PLACE (Higo et al., 1999) or PlantTFDB (Zhang et al., 2011). There remains a need for
software that predicts de novo motifs from co-expressed genes in maize.
In general, two major types of algorithms exist to search co-regulated genes for de novo
motifs. The first approach, consensus searching, consists of searching sets of genes for similar
sequences. This method searches motifs up to 12 bases in length and allows for a few
substitutions. Weeder (Pavesi et al., 2007) is a widely used program that uses consensus-based
sampling. The second type of search algorithm is probabilistic and uses a position weight matrix
(PWM) to define a motif (Stormo, 1990). In the PWM, the probability of occurrence of each of
the four possible nucleotides is calculated for every position within a predicted motif. Motif
PWMs are first identified by scanning regulatory sequences for similar motifs. Predicted motifs
are reported if the probability of the motif occurrence is statistically non-random compared to the
background. Widely used software programs that use a probabilistic algorithm are BioProspector
(Liu et al., 2001) and MEME (Multiple Expectation-maximization for Motif Elicitation) (Bailey
and Elkan, 1995). These programs use different statistical approaches. BioProspector uses Gibbs
sampling (Lawrence et al., 1993), which randomly picks subsequences of a defined length and
reiteratively searches within input promoters until a high probability match is found, defined as
having PWM values that are significantly different from the input background sequences. By
53
contrast, MEME divides sequences into subsegments, and all subsegments are systematically
processed as a possible motif. The probability that each subsegment occurs non-randomly within
input promoters is calculated based on its PWM values (Expectation, E) which is then refined
based on the probability of occurrence of each nucleotide at each position within the subsegment
(Maximization, M). The subsegment with the highest probability after EM is chosen and
modified by reiterating the EM algorithm until a candidate motif cannot be improved (Bailey and
Elkan, 1995).
The various motif discovery programs have significant limitations. For example, one
limit of Gibbs sampling and hence BioProspector (Liu et al., 2001), is that different motifs are
often obtained at each run. In contrast, MEME predictions are more consistent (Bailey and
Elkan, 1995). The main problem with all the current motif discovery programs is their low
accuracy. The best motif discovery program thus far was shown to be only 17.4% accurate, in
E.coli, with many known motifs being missed (Hu et al., 2006). In order to overcome the
problem of low prediction accuracy, motif discovery programs have been combined to increase
their effectiveness, creating what has been termed an ensemble algorithm (Hu et al., 2006).
However, most ensemble algorithms are conservative because they report only motifs that are
retrieved by more than one of the motif discovery programs (Wijaya et al., 2008). To help
researchers evaluate motif discovery programs objectively, benchmark data sets have been
created, in which known motifs are embedded into diverse sequences (Sandve et al., 2007). Each
motif discovery program can then be compared based on the rate of true and false predictions.
Ideally, a motif discovery program for maize should be validated by its ability to retrieve
transcription factor binding sites that have been experimentally validated. Some of the best
studied transcription factor targets in maize are those of C1 and P, transcription factors which up-
54
regulate the biosynthetic enzymes responsible for production of the red-purple pigments,
anthocyanin and phlobaphene, respectively (Dooner et al., 1991; Grotewold et al., 1994; Tuerck
and Fromm, 1994; Lesnick and Chandler, 1998). C1 and P are homologous proteins belonging to
the R2R3 Myb family of regulators (Grotewold et al., 2000), and they have been shown to
interact with identical cis-acting motifs in the A1 promoter (Grotewold et al., 1994; Sainz et al.,
1997).
In this study, first, a benchmark data set was used to compare and evaluate the accuracy
of the three most used motif discovery programs, Weeder, BioProspector and MEME.
Improvements were then created to reduce the limitations of each program. These improvements
were incorporated into a comprehensive motif discovery pipeline customized for maize called
Promzea. Promzea was then validated by asking whether it could retrieve known binding sites of
maize C1 and P transcription factors (Grotewold et al., 1994; Tuerck and Fromm, 1994; Sainz et
al., 1997; Lesnick and Chandler, 1998). Promzea accurately identified these binding sites using
only a small number of input genes from these pathways. Interestingly, in a genome-wide scan,
Promzea retrieved these binding sites in important anthocyanin pathway-related genes not
previously thought be regulated by C1 and P, including genes of historic interest to maize
geneticists.
3.3 Materials and Methods
3.3.1 Software programs used in this study
A list of the software programs used in this study is shown in Table 3.1. Three motif
discovery tools were used: MEME, BioProspector and Weeder. With respect to the parameters
used, MEME was set to search for three motifs with a maximum length of 20 nucleotides on both
DNA strands. BioProspector was set to search for 10-nucleotide long motifs and retain only the
55
first three motifs found. Weeder was set to search for motifs ranging in length from 4-10
nucleotides (medium option). In addition, FIMO (Grant et al., 2011), PSCAN (Zambelli et al.,
2009) and Clover (Frith et al., 2004) were used to retrieve motifs from the maize genome.
56
Table 3.1: Software programs used in Promzea
Tool
Description and download site
MEME
Multiple EM (Expectation Maximization) for Motif Elicitation is a probabilistic de
novo motif finding algorithm. It divides sequences into substrings and calculates
the probability of each substring being a motif compared to the background.
Each motif probability is recalculated during re-running using an expectationmaximisation algorithm http://meme.nbcr.net/downloads/meme_4.6.0.tar.gz
BioProspector
Gibb sampling algorithm. Motif width is user-defined. The sequences are
randomly searched to find similar motifs. Newly discovered PWM motifs are
scored relative to the background. The operation is repeated until conversion of
the results. Results are different at each run.
(http://motif.stanford.edu/distributions/bioprospector)
Weeder
Consensus enumeration program; finds similar consensus sequences in data
allowing 1 to 3 mismatches. The search is extended to the adjacent bases of
the word to define the final motif. (http://159.149.109.9/modtools)
PSCAN
Determines the probability that a defined PWM motif exists in each database
sequence relative to its best score. (http://159.149.109.9/modtools)
FIMO
Finds occurrence of defined PWM in a sequence database using p-value
calculation relative to the Markov background.
(http://meme.nbcr.net/downloads/meme_4.6.0.tar.gz )
Clover
Finds occurrence of defined PWM in a sequence database using PWM best
scores compared to the background. (http://zlab.bu.edu/clover)
57
3.3.2 Comparisons of current motif discovery tools
In order to determine whether existing motif discovery programs give equivalent results,
Weeder, MEME and BioProspector programs were compared. Each program was used to
discover 213 known TRANSFAC® motifs (Matys et al., 2006) embedded in 125 promoter data
sets known as the benchmark data set, previously generated to help researchers make direct
comparisons of the effectiveness of different motif discovery tools (Sandve et al., 2007). The
data sets are grouped into three types: synthetic (Algorithm Markov, AM), semi-synthetic
(Algorithm Real, AR), and real biological promoters (Model Real, MR). The success rate of each
motif discovery program for each benchmark data set was measured using the following
statistical outputs either generated by the benchmark web application or calculated:

the nucleotide level sensitivity (nSn):

the nucleotide False Discovery Rate (nFDR):

the nucleotide level correlation coefficient (nCC):
√(
)(
)(
)(
)
Where: nTP is the number of true positive motif nucleotides found; nTN, the number of true
negative motif nucleotides found; nFP, the number of false positive motif nucleotides found;
nFN, the number of false negative motif nucleotides found. nCC is a measure of the correlation
between the known nucleotide positions and the predicted nucleotide positions (Tompa et al.,
2005).
58
For each benchmark data set, the nucleotide level correlation coefficient score (nCC) of
motif prediction was compared between pairs of motif discovery programs. The results of all
data sets were plotted and compared using the Spearman correlation coefficient (Prism 5,
GraphPad Software, USA).
3.3.3 Filters for each standalone program
As each program generates different sets of false-positives, a custom filter was designed
for each motif discovery tool to reduce the nFDR while preserving nTPs. In order to optimize the
filter parameters, candidate filters were applied to the Sandve et al. (2007) benchmark data set
described above and the best filters were chosen based on comparisons of nFDR and nCC (see
above) using the Friedman test (non-parametric repeated measures ANOVA; Prism 5, GraphPad
Software, USA).
Each filter was based on limiting the probability (p) that the frequency of the candidate
motif in the user data set (with sample size N) could occur randomly if a genome was repeatedly
sampled using sample size N. Two sampling algorithms were tested. The first one was the motif
“enrichment”, without replacement of the subject (promoter sequences) that uses the
hypergeometric distribution (Harbison et al., 2004; Sinha et al., 2006; Linhart et al., 2008). The
second was with replacement of the sample subject following the binomial distribution (Van
Helden et al., 1998; Linhart et al., 2008).
For MEME, the significance level (
) based on the hypergeometric distribution was
used for the motif filtering and was calculated as follows:
(
∑
)
( )(
)
( )
59
Where n is the number of benchmark data set sequences containing the predicted motif out of the
total number of sequences (N) belonging to that data set; G is the number of random sequences
from the organism that is the most overrepresented in the data set (G was set at 300); g is the
number of random sequences containing the predicted motif; n is the size of the motif in base
pairs; and i is the position within the motif. To retrieve predicted motifs in both the benchmark
and random data sets, FIMO was used (Grant et al., 2011); the FIMO e-value threshold was set at
1e-4. Predicted motifs were filtered out when
and
was > 0.05. These threshold levels (FIMO value
) were chosen based on optimization runs using the benchmark data sets that increased the
nSn but decreased nFDR.
For Weeder, there were two filters applied. The first filter removed predicted motifs with
low complexity DNA stretches (> 75% of the same nucleotide). The second filter was based on
the binomial distribution (
) based on previous works (Van Helden et al., 1998; Linhart et al.,
2008), which gives an estimate of the probability that a motif is non-random, calculated as
follows:
( )
(
)
Where n is the number of benchmark data set sequences containing the predicted motif out of the
total number of sequences (N) belonging to that data set; and P is the ratio of the number of
random sequences containing the predicted motif compared to the total number of random
promoter sequences (set at 300). To retrieve predicted motifs in both the benchmark and random
data sets, Pscan was used (Zambelli et al., 2009); the Pscan score threshold was set at 0.97.
Predicted motifs were filtered out when
was > 0.3. Pscan and
significance levels were
also selected after optimization runs using the benchmark data sets that increased the nSn and
decreased nFDR.
60
For BioProspector, the same binomial probability (
) used for Weeder was applied,
except that the Pscan score threshold was set at 0.90, and predicted motifs were filtered out when
was >0.7. The significance levels were selected using the same method as Weeder.
To test each potential filter threshold, the average of three run results was used; for each
run, a new set of random promoter sequences was generated. This multiple-run method also
helped to buffer against the fact that BioProspector uses a stochastic algorithm, each run
generating a different prediction.
3.3.4 Combining multiple programs
As each standalone program appeared to predict different but overlapping sets of motifs,
the effect of combining all three filtered motif discovery programs was tested using the Sandve
et al. (2007) benchmark data set. The performance of the filtered combination against each
standalone program was compared using the nSn, nCC and nFDR scores (see above) with the
Friedman test, a non-parametric repeated measures ANOVA (Prism 5, GraphPad Software,
USA).
3.3.5 Construction of Promzea: Overview
An overview of the pipeline, called Promzea, used to discover maize promoter motifs is
shown (Figure 3.1). A user friendly interface was created using Perl CGI. Using this interface,
the user first submits a list of co-expressed cDNA FASTA sequence files, a microarray probe-set
ID or ID list from MaizeSequence.org. These sequences are BLAST searched against the maize
genome to retrieve a list of corresponding promoters. The promoter data set is then searched in
parallel by each of the three motif discovery programs. The motif results are filtered and then
displayed for the user.
61
Figure 3.1. Flow chart of the Promzea motif discovery pipeline. Abbreviations: HG,
hypergeometric distribution; MNCP, Mean Normalized Conditional Probability score.
62
3.3.6 Construction of upstream and first-intron sequence databases from maize
Flat files of putative maize promoter and first-intron sequences were created using
custom Perl script programs. For the promoter database, the 5’ end of each predicted immature
mRNA from the maize genome was used to define the transcriptional start site (+1) of each gene.
For each gene, 1 kb of upstream sequence was extracted and used to create a flat file of predicted
maize promoters. Whenever a sequence gap was identified, only the relevant downstream
sequence was extracted. Upstream sequences <40 bp were discarded. Three upstream sequence
databases were created, each representing different sequence lengths (1000 bp, 500 bp, 200 bp).
For the database of first-intron sequences, a Perl script was written to recognize and retrieve
predicted intron 1 sequences (based on lower case annotation). The sequences used to generate
both databases were extracted from MaizeSequence.org, release 4a.53 Working Set,
(http://ftp.maizesequence.org). The sequence data originated from the Genome Sequencing
Center at the Washington University School of Medicine, St. Louis, USA (Schnable et al., 2009).
3.3.7 Extraction of promoter and first-intron sequences from user inputs
The Perl script was written to allow each user to generate a list of promoters and firstintron sequences corresponding to only those genes of interest (e.g. promoters of co-expressed
genes or genes in the same biochemical pathway). The program accepts the following inputs:
cDNA FASTA sequence files, microarray probe-set ID or Gramene maize ID list (Figure 3.1).
The GeneChip Maize Genome Array (Affymetrix) is currently supported by Promzea. In the case
of the cDNA FASTA files, the Perl script matches each input cDNA to its corresponding
MaizeSequence.org cDNA using standalone BLAST (NCBI, version 2.2.23). The selected
cDNAs from MaizeSequence.org are then used to retrieve the corresponding upstream or first
63
intron sequences. For microarray/Gramene ID inputs, the Perl script generates a list of the
corresponding upstream or intron 1 sequences directly.
3.3.8 Motif discovery, filtering, ranking and graphical output in Promzea
The user lists of promoters and first intron sequences generated above were used by our
Perl script as inputs into three complimentary motif discovery programs shown to retrieve
different types of motifs: MEME (Bailey and Elkan, 1994), BioProspector (Liu et al., 2001) and
Weeder (Pavesi et al., 2007). Predicted motifs from each standalone program were filtered using
the parameters described above. All the filtered results are regrouped.
In order to rank predicted remaining motifs, Promzea incorporates a published metric, the
Mean Normalized Conditional Probability or MNCP (Clarke and Granek, 2003). Biologically, a
promoter/first intron containing multiple occurrences of a given motif potentially increases the
chance that the motif is non-random. The MNCP score allows one to determine if the mean
occurrence of any given motif mx in the data set (where the motif has been defined) is higher
than its mean occurrence in a random set of promoters/first introns (e.g. whole genome). A motif
with a higher MNCP score has a lower probability of being false. The occurrence of motif mx is
determined in each of the promoters/first introns of the regulated user data set u belonging to the
regulated promoter/first intron population Nu. Each promoter/first intron within the regulated
data set is ranked according to the occurrence of motif mx: promoter(s)/first intron(s) with the
highest motif occurrence are given the 1st rank. In parallel, the occurrence of motif mx is also
determined in the random promoter/first intron data set r (regulated and non-regulated) belonging
to the random promoter/first intron population Nr. If the motif mx is a regulator of the user data
set Nu, its occurrences should be higher than in the random data set Nr. Each promoter/first intron
64
(px) in the regulated data set has a rank
( ) and another rank in the random data set
( )A
normalized ratio of the two ranks (C) for each promoter/first intron px is hence:
( )
( )⁄
( )⁄
C is calculated for each promoter/first introns containing motif mx in the user data set. MNCP is
the mean of all the C values. If MNCP for motif mx is greater than 1, that motif is more
represented in the regulated data set compared to the random data set. In Promzea, each motif is
ranked according to its relative MNCP score. Clover software is used to retrieve the motif and
estimate its occurrence in the user and random data sets from the maize genome.
The final filtered set of motifs is represented for the user as consensus sequence logos
using Weblogo Software (Crooks et al., 2004). The frequency of motif occurrence at each
position, as defined by each motif discovery program, is shown as a graphic using the
Chart::Clicker Perl module (Watson, 2010).
3.3.9 Understanding motif function in Promzea using functional gene annotation
Gene annotations (e.g. anthocyanin pathway) can be used to help users understand the
biological function of a motif. The annotation can also be used by the user as a second form of
motif validation as the annotation-defined trait should relate to the user experiment. A flat file of
well-described gene annotations was first created using the “Functional-Annotations” files from
MaizesSequence.org. Clover (Frith et al., 2004) is used to search the maize promoter/first-intron
flat file for each predicted motif which is then matched to its corresponding gene annotation
(Figure 3.1). The iGA Perl program (Breitling et al., 2004) is used to calculate if an annotation is
overrepresented for a given motif. The annotations are represented as a pie chart for the user
using Chart:Clicker where each slice is - log (annotation p-value). For a p-value equal to zero, -
65
log(p-value) is equal to infinite which cannot be represented on a pie-chart. To circumvent this
problem, the choice has been made to replace zero p-values with p-values equal to 10-8.
3.3.10 Validation of Promzea predictions using experimentally defined motifs
Promzea was further validated by searching a data set of promoters regulated by
transcription factors C1 and P which activate the maize anthocyanin and phlobaphene
biosynthetic pathways, respectively (Dooner et al., 1991). To generate the input for Promzea, all
cDNAs from Genbank that were annotated as corresponding to the co-regulated genes were
gathered in a FASTA file; a promoter sequence list was generated as described above. The 200
base promoter option was used for Promzea analysis, as the literature shows that motifs
important for the expression of anthocyanin biosynthetic enzymes are within the first 200 bases
of the promoter (Bodeau and Walbot, 1996).
3.4 Results
3.4.1 Comparisons of current motif discovery programs using benchmark data sets
The first objective was to evaluate whether each standalone motif discovery program
predicted the known motif nucleotides in each data set to a similar extent. For this analysis, a
previously generated benchmark data set was used consisting of 213 known motifs embedded
into sets of promoter sequences (Sandve et al., 2007). For each data set, the nCC score was
calculated, a measure of the correlation between the known motif nucleotide positions and the
predicted motif nucleotide positions (Tompa et al., 2005). When software predicted nucleotides
that exactly matched with the known binding sites (true positives, nTP), the nCC score was +1,
whereas an nCC score of ≤0 indicated a random prediction. For every paired program
comparison, Spearman correlations (r) of the benchmark nCC scores ranged from 0.14 to 0.36
(Figure 3.2). In a large subset of benchmark data sets, Weeder predicted known motifs
66
effectively (nCC>0), whereas BioProspector and MEME did not (nCC ≤0) (Figure 3.2 B, C).
These results suggest that each motif discovery program retrieves a distinct set of motifs.
67
Figure 3.2. Comparison of standalone motif discovery programs. Different motif discovery
programs predicted motifs embedded in 125 sets of sequences belonging to the Sandve et al
(2007) benchmark dataset. The benchmark software calculated the nucleotide Correlation
Coefficient scores (nCC scores), a measure of the correlation between the known nucleotide
positions and the predicted nucleotide positions. The nCC scores are compared for (A)
68
BioProspector and MEME, (B) Weeder and MEME, and (C) Weeder and BioProspector. The
Spearman correlation (r) between the sets of nCC scores is indicated.
3.4.2 Defining filters for each standalone program using benchmark data sets
A custom filter was designed for each motif discovery program to reduce the false
discovery rate (nFDR) while preserving the true positives as indicated by the nCC score. To
optimize the filter parameters, candidate filters were applied to the benchmark data set (Sandve
et al., 2007) based on limiting the probability (pB) that a motif prediction could occur randomly;
the best filters were chosen based on their impact on the nFDR and nCC scores. For
BioProspector, pB thresholds at 0.3, 0.5 and 0.7 significantly reduced the average nFDR score
(from 0.92 with unfiltered motif discovery data to 0.82, 0.86 and 0.86, respectively, Friedman’s
test p-value <0.01; Figure 3.3 A). Though the average nCC scores between the filtered data were
not significantly different from one another, the
= 0.7 filter was chosen for BioProspector as it
caused the least absolute reduction in the nCC score average compared to the unfiltered data
(from 0.097 to 0.084; Figure 3.3 A). For MEME, a significance level of 0.05 was chosen as it
achieved the best balance between a significant reduction in the nFDR average (from 0.96 to
0.85, Friedman’s test p-value<0.05) and a significant increase in the nCC average (from 0.065 to
0.073, p-value < 0.01; Figure 3.3 B). For Weeder, a significance level of 0.3 was selected as it
similarly achieved the best balance between a significant reduction in the average nFDR score
(from 0.97 to 0.95, p-value < 0.001) and the largest absolute increase in the average nCC score
(from 0.054 to 0.071, p-value<0.001; Figure 3.3 C).
69
A
B
C
70
Figure 3.3. Optimization of motif filtering for each standalone motif discovery program. The
performance of each motif discovery program, applied to the Sandve et al. (2007) benchmark
dataset, was measured using the nucleotide Correlation Coefficient score mean (nCC, grey bar)
and the nucleotide False Discovery Rate mean (nFDR, black line). Shown is the performance of
each original program (unfiltered) and after motif filtering at three probability cut-offs (p) for:
(A) BioProspector, using the binomial distribution; (B) MEME using the hypergeometric
distribution; and (C) Weeder using the binomial distribution. FDR and nCC error bars indicate
the mean confidence intervals.
71
3.4.3 Effect of combining motif discovery programs using benchmark data sets
When BioProspector (unfiltered) was applied to all three types of Sandve et al. (2007)
benchmark data sets, the average number of true positive motifs (nTPs) predicted was 1191
while the number of false positives (nFPs) was 10785 (Figure 3.4 A-C, Table 3.2). Unfiltered
MEME predicted an average of 1145 nTPs correctly, but 29982 nFPs. By contrast, unfiltered
Weeder predicted two-fold more nTPs (2083 on average) but a very high average number of
nFPs (99561; Table 3.2). Given the earlier results which suggested that the three standalone
programs appear to identify different sets of motifs (Figure 3.2), it was hypothesized that
combining the programs into an ensemble-type algorithm would increase the total number of true
positives. In fact, combining the programs increased the number of nTPs to 3185, a >50%
increase compared to the best standalone program, Weeder, under the software parameters
chosen (Figure 3.4 A-C, Table 3.2). However, combining the programs also increased the
number of nFPs compared to each standalone program. Filtering each motif discovery program
separately before combining the results reduced the average nFPs by 25.7% compared to the
combined unfiltered data while reducing nTPs by only 8.7% (Figure 3.4 A-C, Table 3.2). The
nCC score after combining all three filtered programs was not significantly different compared to
each standalone program, likely because nTPs and nFPs both increased (Figure 3.5).
72
73
Figure 3.4. Effectiveness of combining different motif discovery programs. (A-C) The
performance of each motif discovery program, applied to the Sandve et al. (2007) benchmark
dataset, was measured using the total number of true positive nucleotides (nTP, grey bars) and
the total number of false positive nucleotides (nFP, black lines). Shown are scores for the three
types of datasets that comprise the Sandve dataset: (A) synthetic (Algorithm Markov), (B) semisynthetic (Algorithm Real), and (C) real promoters (Model Real). Shown are the scores of each
standalone unfiltered program, as well as the scores after combining the outputs of the three
programs without filtering (combined) or with filtering (combined filt). (D) The performance of
each standalone program or the combined programs was compared using the Average nucleotide
Sensitivity (nSn). Shown are the mean nSn scores for the synthetic data (AM: Algorithm
Markov), semi-synthetic data (AR: Algorithm Real) and real data (MR: Model Real). The
asterisks (***) indicate that the average nSn score of the combined filtered programs is
statistically higher than the average nSn score using Weeder alone at p<0.01. Each error bar
represents the 95% mean confidence interval. (E) The partition of final true positives found by
the three motif discovery tools after filtering is shown. Shared results are motif nucleotides
retrieved by at least two of the standalone programs. Filtering and combining the standalone
programs are the basis of Promzea.
74
Table 3.2. Combination of motif discovery programs based on measures of True Positive and
False Positive nucleotides.
Synthetic data
(AM)
Semi-synthetic data
(AR)
Real data (MR)
Tools
Averages
nTP
nFP
nTP
nFP
nTP
nFP
average
nTP
average
nFP
BioProspector
995
10668
940
9889
1638
11797
1191
10785
MEME
1503
21861
1134
25832
798
42253
1145
29982
Weeder
2104
86064
2251
74945
1895
53365
2083
99561
Combined
3067
110825
2876
102531
3462
110089
3135
107815
Combined filt.
2813
85186
2676
73534
3078
81756
2856
80159
Note: The Table shows the numbers illustrated in Figure 3A-C. Each value is the average result
of three runs for each standalone unfiltered program, as well as the scores after combining the
outputs of the three programs without filtering (combined) or with filtering (combined filt).
75
76
Figure 3.5. Effectiveness of combining different motif discovery programs. The output of each
motif discovery program, applied to the Sandve et al. (2007) benchmark dataset, was measured
using the Nucleotide Correlation Coefficient (nCC) and the nucleotide Sensitivity (nSn). Shown
are scores for the three datasets that comprise the Sandve dataset: (A) synthetic (Algorithm
Markov), (B) semi-synthetic (Algorithm Real), and (C) real promoters (Model Real). Shown are
the scores of each standalone unfiltered program, as well as the scores after combining the
outputs of the three programs with filtering (combined). The error bars represent the 95% mean
confidence interval.
77
Compared to each standalone program, combining all three filtered programs also
significantly improved the ratio of software-predicted true positives versus the actual number of
real motif nucleotides (sensitivity, nSn; Dunn’s Multiple Comparisons Test, p<0.01). The nSn
increased by 22% compared to the most sensitive standalone program, Weeder, under the
conditions used (Figure 3.4D, Table 3.3).
The effectiveness of our strategy was further demonstrated by examining the origin of the
final predicted nTPs after all three filtered results had been combined. Of the final number of
nTPs retrieved from the benchmark data set, 41% were found to have been discovered by
Weeder alone, 16% from MEME alone and 10% from BioProspector alone (Figure 3.4E). Only
33% of nTPs had been found by two or three of the standalone programs. This result confirms
that widely used motif discovery programs retrieve distinct sets of motifs and that combining the
predictions increases the chance of discovering new regulatory motifs.
3.4.4 Promzea: a pipeline for motif discovery in maize
These principles were integrated into the Promzea software pipeline for motif discovery
in maize (Figure 3.1, see Methods). To match the user input cDNA to the maize genome, a total
of 61,889 full length maize cDNAs were retrieved from MaizeSequence.org. For each predicted
gene, the corresponding promoter and first intron were compiled into a list: the flat file of 1 kb
upstream sequences consisted of 39,589 predicted maize promoters; the database of first introns
consisted of 39,654 sequences. For motif discovery in Promzea, we applied the same parameters
for motif discovery and filtering as used in the benchmark validation (see Methods). The
predicted motifs were ranked using their MNCP scores. An analysis of the benchmark Model
real data set showed that as the MNCP score of the predicted motif increased, the chance that it
was composed of nucleotide false positives decreased (Table 3.4). As false positives were found
78
to remain in the predictions using the benchmark data set, Promzea gives the user tools to
validate each predicted motif. For validation using gene annotations, 18,922 well annotated
genes were compiled into a flat file using data from MaizesSequence.org.
79
Table 3.3. Effectiveness of combining different motif discovery programs based on nucleotide
sensitivity scores.
tools
average
nSn
synthetic
datasets (AM)
semi-synthetic
datasets (AR)
real datasets (MR)
nSn
C.I.
nSn
C.I.
nSn
C.I.
BioProspector
BioProspector
filt.
MEME
0.17
0.15
0.07
0.16
0.07
0.19
0.08
0.14
0.15
0.06
0.12
0.05
0.14
0.07
0.16
0.23
0.08
0.18
0.07
0.08
0.04
MEME filt.
0.16
0.23
0.08
0.18
0.07
0.06
0.04
Weeder
0.36
0.39
0.08
0.41
0.09
0.29
0.08
Weeder filt.
0.31
0.31
0.02
0.36
0.02
0.27
0.08
Combined
0.49
0.53
0.09
0.52
0.09
0.42
0.09
Combined filt.
0.44
0.47
0.09
0.47
0.09
0.37
0.09
Note: The Table shows the numbers illustrated in Figure 3D. C.I. is the 95% confidence interval
of the mean.
Table 3.4. The effect of MNCP score cut-offs to the motif prediction from the Sandve’s
benchmark.
MNCP threshold nTP
nFN
nFP
nSn
nPPV
nSP
nPC
nCC
nASP nFDR
combined
128
202
3341
0.39
0.04
0.92
0.03
0.0942
0.21
0.96
mncp 1.5
112
218
3031
0.36
0.04
0.92
0.03
0.0896
0.20
0.92
mncp 2
104
226
2602
0.35
0.04
0.93
0.04
0.0931
0.19
0.92
mncp 3
82
248
1813
0.31
0.05
0.95
0.04
0.0944
0.18
0.83
mncp 4
47
283
1151
0.22
0.03
0.96
0.02
0.0612
0.12
0.61
mncp 5
40
290
769
0.18
0.05
0.97
0.04
0.0724
0.11
0.51
Note: Each statistic represents the average of three runs. The abbreviations and corresponding
formulas for each statistic are described in the Methods and in Sandve et al. (2007).
80
3.4.5 Validation of Promzea using experimentally defined transcriptional binding sites
The effectiveness of Promzea was tested based on its ability to detect experimentally
defined binding sites for the maize transcription factors, C1 and P, which up-regulate enzymes
responsible for the biosynthesis of anthocyanin and phlobaphene, respectively (Figure 3.6)
(Dooner et al., 1991; Grotewold et al., 1994; Tuerck and Fromm, 1994; Lesnick and Chandler,
1998). Eight gene promoters containing the C1 and P binding sites were selected (Figure 3.6,
marked in grey). The corresponding cDNAs (including all close homologs, 13 total) were used as
input into Promzea based on experimental evidence or inference from the above literature.
Promzea retrieved 28 genes matching these cDNAs after BLAST searching; from the
corresponding promoters, 12 motifs were identified along with their MNCP scores (Figure 3.7).
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Figure 3.6. Genes in the maize anthocyanin and phlobaphene biosynthesis pathways regulated
by transcription factors C1 and P. Genes encoding biosynthetic enzymes regulated by C1 are
shown in grey text; those also regulated by P are underlined.
82
Figure 3.7. Motifs predicted by Promzea for genes encoding the maize anthocyanin biosynthesis
pathway. Promzea searched for motifs in sequences upstream (-200 bp to +1) of the genes
indicated in Figure 5 as well as their closest DNA sequence paralogs (see Methods). Shown are
the sequence logos, the motif discovery program that identified each motif and the corresponding
MNCP score. BioP, BioProspector.
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Of the motifs with the highest MNCP scores predicted by Promzea, three matched the
experimentally defined C1 and/or P binding sites (Figure 3.8). Promzea Motif3 had a high
MNCP score (Cavg=128) and was found to be identical (Matalign, p< 0.001) to the defined ARE
motif binding site of C1 (Tuerck and Fromm, 1994). Interestingly, Motif3 was overrepresented
in the -120 to -80 promoter region (Figure 3.8), consistent with the experimentally defined -98 to
-88 binding site of C1 in the A1 promoter (Tuerck and Fromm, 1994). Motif3 was retrieved
using Clover in five out of the eight input genes shown experimentally to contain the C1 binding
site in their promoters (Figure 3.6, red labels); two copies were found in the first 200 bp of the
promoter of PAL1, phenylalanine ammonia lyase (Figure 3.8). Motif1 (Cavg = 173) was
statistically close (Matalign, p< 0.001) to the C1 binding site in the A2 promoter (Lesnisk et al.
in 1998) (Figure 3.8). Motif1 was retrieved in five out of eight input genes (Figure 3.6, red
labels); three copies were found in the first 200 bp of the promoter of A1 (Dihydroflavonol-4reductase, DFR; Figure 3.8).
84
Figure 3.8. Motifs predicted by Promzea compared to experimentally defined motifs in the
literature using Dialign and Matalign. Shown are the motif binding sites for transcription factors
C1 and P in the anthocyanin and phlobaphene biosynthetic pathways, respectively. The
preferential position of each motif predicted by Promzea is indicated in the fourth column from
the right. The p-value for Matalign is indicated by the False Discovery Rate (FDR). The
superscript number in the extreme right column represents the number of motif copies present in
the promoter of the indicated gene (-200 bp to +1).
85
The experimentally defined P binding site had two motifs which matched the Promzea
predictions: Motif3 and Motif6 with a p< 0.001 in Matalign (Grotewold et al., 1994; Kankainen
and Loytynoja, 2007). Motif3 and Motif6 were overrepresented in the -120 to -100 promoter
region and -120 -100, -80-60 and -40-20 regions, respectively (Figure 3.8), consistent with the
experimentally defined -123 to -88 binding site of P in the A1 promoter (Grotewold et al., 1994).
Motif3 and Motif6 were retrieved using Clover in 4/4 and 3/4 of the anthocyanin input
promoters, respectively, that were shown experimentally to contain the P binding site (Figure
3.6, red labels); two copies of each motif, which were related, were found in the first 200 bp of
gene the PAL1 promoter (Figure 3.8). The ability to retrieve experimentally defined promoter
motifs validates Promzea as an effective pipeline for motif discovery in maize.
3.4.6 Novel candidate motifs in the anthocyanin pathway
Promzea also retrieved nine candidate motifs in the anthocyanin biosynthetic pathway not
previously defined experimentally (Figure 3.7). For example, Motif5 (Figure 3.9A) had a high
MNCP score (Cavg=101) and was overrepresented in the -120 to -100 promoter region (Figure
3.9B). When the maize genome was searched for promoters containing Motif5, a total of 808
promoters were found (Appendix Table 1); the over-represented annotations based on iGa
statistical results and identified for the corresponding genes were related to cytochrome and
heme function (Figure 3.9C). Motif5 was retrieved from the promoters of three enzymes in the
anthocyanin pathway, including the rate-limiting step in phenylpropanoid biosynthesis,
phenylalanine ammonia lyase (PAL1; Figure 3.10).
86
Figure 3.9. Example of the Promzea output for anthocyanin pathway Motif5. For each predicted
motif, the following outputs are displayed: (A) The sequence logo (upper) and the plain
consensus sequence (lower); (B) the frequency of occurrence of the motif at each upstream
position range from the user input dataset; (C) summary of annotations of genes containing the
motif from the genome-wide retrieval (when applicable). A user can click on the Gene List link
and Over-Represented Annotation link to retrieve lists of genes containing the motif and detailed
gene annotations, respectively.
87
88
Figure 3.10. The presence of Promzea-predicted motifs upstream of genes encoding anthocyanin
and phlobaphene biosynthesis enzymes and encoding their known transcription factors. (A)
Shown are predicted motifs present in the promoters of the known transcription factors; the
genes they are known to regulate in the anthocyanin and phlobaphene biosynthetic pathways are
indicated in dark red text. (B) Shown are predicted motifs present in the promoters of the
enzymatic genes. The R gene indicated is R-S. Each motif is present in the gene indicated or
functional paralog.
89
3.4.7 Other genes containing the same motifs as the anthocyanin promoters
As noted above, each motif predicted by Promzea from the anthocyanin pathway (Figure
3.7) was used to search the genome to retrieve genes containing that motif. A keyword search of
the results was conducted using terms corresponding to anthocyanin biosynthesis and regulation
as well as related pathways. There were four classes of anthocyanin-related genes retrieved that
were not in the original input gene set (Appendix Tables 1-2):
First, the genome-wide search for Promzea-predicted motifs retrieved several paralogs of
the original input anthocyanin cDNAs (Figure 3.6 - grey labels, Table 3.5). The well-known
paralog of C2, WhP (Taylor and Briggs, 1990; Dooner et al., 1991), was retrieved multiple times
as it contained nine of the 12 Promzea-predicted motifs (Figure 3.10). Four paralogs of Bz1,
anthocyanidin 5,3-O-glucosyltransferase genes, were recovered (Table 3.5). Searching using
motifs also recovered paralogs for PAL1, flavonol synthase/flavanone 3-hydroxylase (F3H), and
anthocyanidin 3-O-glucosyltransferase (Bronze2, Bz2; Table 3.5).
90
Table 3.5. List of input cDNAs from the maize anthocyanin pathway used for Promzea searches.
Genbank genes from the anthocyanin were retrieved. Their corresponding genes from
MaizeSequence.org (red text, true loci; blue text, closest paralogs) and additional functional
paralogs (extreme right column) were retrieved from genome-wide searches using Promzeapredicted motifs from the maize anthocyanin biosynthetic pathway.
91
gene
name
gene description
cDNA Genbank
ID
cDNA annotation
genes Identified by BLAST in maize
genome (www.maizesequences.org)
known paralogs containing same motifs in their promoters
PAL1
phenylalanine
ammonia-lyase
M95077.1
PAL1,
Phenylalanine
Ammonia Lyase
GRMZM2G074604,
GRMZM2G160541
GRMZM2G081582, GRMZM2G118345, GRMZM2G063917
BT042976.1
C2, chalcone
synthase
GRMZM2G422750,
GRMZM2G151227
GRMZM2G108894
BT061979.1
C2, chalcone
synthase
GRMZM2G422750,
GRMZM2G151227
GRMZM2G108894
C2
C2
Chalcone synthase C2
(Naringenin-chalcone
synthase C2)
Chalcone synthase C2
(Naringenin-chalcone
synthase C2)
CHI
chalcone isomerase
NM001156113.1
CHi, Chalcone
Isomerase
GRMZM2G060011
/
CHI
chalcone isomerase
EU963832.1
Chalcone isomerase
GRMZM2G060011
/
F3H
flavanone 3hydroxylase1
BT063640.1
GRMZM2G083574,
GRMZM2G350020
GRMZM2G175343
GRMZM2G026930,
GRMZM2G013726
GRMZM5G860241, GRMZM2G057328, GRMZM2G152175
A1
A1
A1
Anthocyanidin 3-Oglucosyltransferase anthocyaninless1
Anthocyanidin 3-Oglucosyltransferase anthocyaninless1
Anthocyanidin 3-Oglucosyltransferase anthocyaninless1
BT034095.1
F3H, putative
flavonoid
3hydroxylase
A1,
dihydroflavonol-4reductase
BT043174.1
dihydroflavonol-4reductase, putative
GRMZM2G026930,
GRMZM2G013726
GRMZM5G860241, GRMZM2G057328, GRMZM2G152175
BT067630.1
dihydroflavonol-4reductase, putative
GRMZM2G026930,
GRMZM2G013726
GRMZM5G860241, GRMZM2G057328, GRMZM2G152175
/
A2
Leucoanthocyanidin
dioxygenase anthocyaninless2
NM001112604.1
A2
GRMZM2G345717,
GRMZM5G869840,
GRMZM2G058340,
GRMZM2G057891,
AC202707.3FG002
Bz1
UDP-glucose flavonoid
3-O-glucosyltransferase
-Bronze-1
DQ335126.1
Bz1, Bronze1
GRMZM2G165390
GRMZM2G063550, GRMZM2G036409, GRMZM2G455075,
GRMZM2G010987
Bz2
Probable glutathione Stransferase BZ2 Bronze-2
GRMZM2G016241
GRMZM2G146246,GRMZM2G056388, GRMZM2G077183,
GRMZM2G161905, GRMZM2G132093, GRMZM2G150474,
GRMZM2G146887, GRMZM2G025190, GRMZM2G330635,
GRMZM2G019090, GRMZM2G116273, GRMZM2G178079,
GRMZM2G330635, GRMZM2G156877
AF377543.1
Bz2, Bronze2
92
Second, the genome-wide search within promoter sequences using Promzea-predicted
motifs retrieved genes encoding enzymes that act upstream and downstream of the input cDNAs
(Figure 3.6). Surprisingly, four Promzea-predicted motifs including Motif3 and Motif6 retrieved
the gene encoding prephenate dehydratase (P-protein, E.C. 4.2.1.51), a shikimate pathway
enzyme required to synthesize the anthocyanin precursor, phenylalanine (Knaggs, 2003)
(Appendix Table 2). Seven different Promzea-predicted motifs, including Motif3, were found in
the promoter of anthocyanidin 5,3-O-glucosyltransferase (E.C.2.3.1.153) which acts downstream
of Bz1(Fujiwara et al., 1997) (Appendix Table 2).
Third, searching the genome using Promzea-predicted motifs retrieved genes encoding
transcription factors known to regulate the anthocyanin biosynthetic pathway, including C1, Pl,
P, R, PAC1 and VP1 (Appendix Table 2) (Dooner et al., 1991; Carey et al., 2004). For example,
Motif3, which was almost identical to the experimentally predicted binding sites of transcription
factors P and C1/Pl (Figure 3.8), was present in the promoters of these same transcription factors
suggesting auto regulation of the anthocyanin pathway (Figure 3.10A). The related Motif6 was
present in the promoters of transcription factors R and Vp1 (Figure 3.10A), the latter known to
activate expression of C1 (Dooner et al., 1991). Novel Promzea-predicted Motif11 appears to be
particularly interesting as it was found in the promoters of four regulators of the anthocyanin
pathway (C1, R, P, PAC1) as well as four biosynthetic genes (PAL1, C2/Whp, ChI, Bz1) (Figure
3.10A,B).
Finally, Promzea-predicted motifs were also present in the promoters of stress genes
related to the activation of anthocyanins including cold, phosphate starvation and wounding
(Appendix Table 1) (Chalker-Scott, 1999). For example, genome searching retrieved enzymes
93
(Bx8, Bx9) required for the biosynthesis of benzoxazinone, a shikimate-derived compound that
confers resistance to wound-causing pathogens (Von Rad et al., 2001) (Appendix Table 1).
The ability of Promzea to retrieve maize genes in pathways related to anthocyanin further
validates it as an effective motif discovery pipeline for maize. The built-in motif genome search
function of Promzea may allow researchers to predict new genes that may be part of a broader
co-regulated network.
3.5 Discussion
Promzea provides the maize community with a customized interface to detect de novo
cis-acting motifs that are over-represented in the promoters or introns of co-expressed maize
genes. By filtering and combining the results of multiple standalone motif discovery programs,
Promzea predicts more true motifs than current individual programs without increasing the false
discovery rate (Figure 3.4). For each run output, Promzea provides a ranking of the predicted
motifs based on their MNCP scores (Figure 3.7). An MNCP score of ≤1 means that the motif is
more frequently present in a random set of maize sequences than the user co-expression data set.
This measurement can help eliminate motifs found in repetitive elements which are abundant in
the maize genome including transposons and retro-elements (Baucom et al., 2009). False
positives are, however, a problem in any motif discovery program; furthermore, cis-acting motifs
regulate genes at different biological levels that may or may not be of interest (e.g.
developmental cue versus an environmental stimulus). Given these caveats, Promzea generates
additional outputs to help a user decide which motif(s) to pursue, placing the emphasis back on
the user. In particular, Promzea searches the maize genome for genes that contain each predicted
motif; the corresponding gene annotations are summarized so that a user can decide whether the
predicted motif is relevant to the input gene cluster (e.g. belongs to the biological pathway of
94
interest; Table 3.4). Since gene annotations are often limiting, Promzea also generates the
complete list of genes that contain each predicted motif (Appendix Tables 1-2); a user can then
search the list using relevant keywords to determine whether a predicted motif retrieves expected
genes. The Promzea pipeline thus narrows the number of candidate cis-acting motifs for
subsequent experimental validation. Promzea should be especially useful to molecular biologists
for the prediction of specific promoters for transgene research and targeted maize improvement;
few such promoters currently exist for the maize community.
Users can maximize the utility of Promzea. First, prior to using Promzea, it is critical for
the user to define robust clusters of co-expressed genes since motif discovery can be diluted by
the presence of extra genes that are not part of the real gene network of interest (McNicholas and
Murphy; Kim et al., 2009). Second, it is important for the user to know that Promzea employs
algorithms that are stochastic in nature, including BioProspector and the selection of random
background sequences required for the filtering process. As a result, each Promzea run can
generate slightly different outputs. Users are recommended to run Promzea multiple times to
verify the uniformity of their results. Finally, Promzea does not compare predicted motifs to
motifs previously defined by the research community; for this, the user is encouraged to use
STAMP to match a motif to online databases (Mahony and Benos, 2007) or Matalign
(Kankainen and Loytynoja, 2007) for comparisons to motifs found in the literature (Figure 3.8).
Matalign may also be used to compare the different motifs predicted by Promzea to determine if
there are likely duplicates.
In this study, the Promzea pipeline was validated by its ability to retrieve experimentally
defined binding sites for the transcription factors C1 and P which regulate the maize anthocyanin
and phlobaphene biosynthetic pathways, respectively (Figure 3.6) (Cone et al., 1986; Grotewold
95
et al., 1994; Tuerck and Fromm, 1994; Bodeau and Walbot, 1996; Sainz et al., 1997; Lesnick and
Chandler, 1998; Grotewold et al., 2000; Carey et al., 2004). Our case study revealed that
Promzea could potentially identify motifs not only from co-expression data, but also from a
virtual data set which might be expected to have a common cis-acting motif, such as a
biochemical pathway (Figure 3.6). Our case study also demonstrated that Promzea could not
only retrieve valid cis-acting motifs, but could make novel predictions about the corresponding
biological network. In particular, Promzea identified additional genes that share the putative cisacting motifs, including paralogs of anthocyanin biosynthetic enzymes and other upstream and
downstream enzymes. Surprisingly, Promzea also showed that the genes encoding the
biosynthetic enzymes share common cis-acting motifs with the transcription factors C1 and P, as
well as other transcription factors known to regulate the anthocyanin pathway, including PAC1,
VP1 and R (Dooner, 1979, 1985; Kao et al., 1996; Selinger and Chandler, 1999). Promzea has
thus predicted a broader co-regulated network than has been identified experimentally (Figure
3.10), revealing potential feed-forward or feedback regulation.
As a final lesson, it is noteworthy that mutants in maize transcription factors C1 and P
were isolated and characterized 100 years ago (East, 1912). The genes encoding these
transcription factors began to be isolated 70-80 years later (Styles and Ceska, 1977; Cone et al.,
1986). The binding sites for C1 and P were defined biochemically one decade later (Grotewold et
al., 1994; Tuerck and Fromm, 1994; Sainz et al., 1997). Our study now shows that the
bioinformatics prediction of cis-acting motifs may help to uncover genetic relationships even in
well-studied biological pathways.
96
3.6 Conclusion
There was a need for software program to help maize researchers identify de novo cisacting motifs underlying co-expressed suites of genes. Here we analyzed the accuracy of the
most widely used motif discovery programs and showed that they had limited accuracy and
retrieved distinct sets of motifs. We applied statistical filters to reduce the false discovery rates of
these programs and then combined the search results to improve motif prediction. These
principles were integrated into an online software program for motif discovery that was
customized for maize called Promzea. Promzea was able to retrieve binding sites of the maize
transcription factors C1 and P previously defined experimentally defined. Interestingly, the
genome-wide motif discovery function of Promzea predicted a broader network of co-regulated
genes. Promzea should be a useful tool for de novo predictions of cis-acting motifs from
transcriptome data. Promzea is publicly available (www.promzea.org).
97
4. Association of cis-acting elements with juvenile stage-selective
gene expression in maize (Zea mays L.)
Author contributions: Christophe Liseron-Monfils conducted all microarray and bioinformatics
analyses. Plants were grown by Wenqing Wu and Tara Signorelli (Steven Rothstein`s laboratory,
University of Guelph). RNA extraction was led by Yong-Mei Bi (Steven Rothstein`s laboratory,
Guelph). Part of the annotation of the microarray was done by Gregory Downs (Lewis Lukens`
laboratory, University of Guelph). The array hybridizations were realized by Xi Chen and Eddie
Bondo at Syngenta Biotechnology Inc. (Research Triangle Park, North Carolina, 27709, USA).
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4.1 Abstract
The objective of this study was to determine if maize (Zea mays L.) juvenile
development could be sub-divided into distinct developmental stages based on gene expression,
and to identify cis-acting promoter motifs for each stage. A custom Affymetrix 82K-array was
used to analyze gene expression in 50 tissues from seedling emergence to post-flowering.
Distinct stage- and organ-selective gene expression clusters were identified for emergence (Ve,
coleoptile), V1 (two-leaf) and V2 (four-leaf) stages. Leaves and roots at each stage were
associated with distinct promoter motifs. Organ- and stage-selective genes were also identified as
landmarks for juvenile development. The most interesting landmark genes encoded biosynthetic
enzymes for the hormones, auxin (indole-3-glycerol-phosphate synthase, Ve coleoptiles),
abscisic acid (zeaxanthin epoxidase, V1 roots) and ethylene (ACC oxidase, V2 seminal roots).
Additional landmark genes included chloroplast-associated genes (APE1, LIL1, V2-stage
leaves), and genes encoding biosynthetic enzymes for the anti-pathogenic metabolite DIMBOA
(Ve coleoptiles). Landmark genes associated with nutrient uptake/transport included paralogs of
nitrate transporter NTR1.1 (V1 roots), ammonium transporter AMT1;3 (V2 seminal roots) and
phosphate transporter PHT1;7 (V2 seminal roots). As the young maize root system backbone
consists of two distinct organs, seminal roots and nodal (crown) roots, their transcriptomes were
also compared: 1035 probes were differentially expressed. Surprisingly, 7/21 nuclear genes
associated with Photosystem I were selectively up-regulated in seminal roots. Probes upregulated in nodal roots were related to antioxidant and oxidative stress responses. Distinct
promoter motifs were identified for each root organ. These results demonstrate precise
transcriptional control of gene expression during juvenile maize development.
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4.2 Introduction
As in many angiosperms, shoot development in maize (Zea mays L.) has been first
divided into two vegetative phases, juvenile and adult, based on characteristics including leaf
shape and surface wax, which are followed by the reproductive phase (Poethig, 1990, 2010). In
maize, the juvenile phase starts with coleoptile leaf emergence (Ve) and ends after emergence of
the first 4-6 embryonic leaves which are pre-formed during seed development (Kiesselbach,
1999) but this development can be slightly different depending on the inbred line. The V1 stage
or one leaf-stem node visible corresponds to two leaves, while the V2 stage or two leaf-stem
nodes visible corresponds to four leaves, which is followed by the adult phase represented in this
study from the V5 stage or eight leaves emerged (Kiesselbach, 1999). The reproductive phase is
characterized by the emergence of reproductive organs and is further divided into stages of seed
development based on the number of days after pollination (DAP). Underground, the juvenile
maize root system consists of a single primary root and variable number of seminal roots. By the
V2 stage, shoot-borne nodal roots (crown roots) initiate below ground, and subsequently form
the backbone of the adult and reproductive root systems (Gaudin et al., 2011).
The juvenile phase of maize development, including emergence, is the critical stage for
seedling establishment. Recent transcriptome studies have described gene expression patterns in
juvenile maize leaves, including describing diurnal gene regulation in a juvenile leaf (Jończyk et
al., 2011). An in-depth study by Li et al. (Li et al., 2010) described gene expression along a tipbase gradient within a juvenile maize leaf, and demonstrated that the growing base of the leaf
was dominated by genes involved in respiration, cell elongation and the production of
chlorophyll precursors including heme-binding proteins; whereas genes expressed at the tip were
involved in photosynthesis, sugar storage and export (Li et al., 2010). An additional study
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examined gene expression in maize leaves during the transition from juvenile to adult stages
(Strable et al., 2008). A final exhaustive study compared gene expression in different organs
across maize development, focusing on the lignin biosynthetic pathway (Sekhon et al., 2011).
Given the importance and interest in the maize juvenile phase, it would be useful to
identify the cis-acting promoter motifs underlying this stage of development to begin to
understand the underlying transcriptional gene regulation. Such information is largely missing,
and could also lead to engineering stage- and/or organ-specific promoters for targeted genetic
research.
Here, we used microarray analysis to first identify gene expression clusters in roots and
leaves at different stages within the juvenile development phase. These clusters were then used
to identify over-represented motifs in the promoters of the genes within each expression cluster.
Finally, interesting landmark genes that were both organ- and stage-specific were identified as
developmental markers for sub-stages within juvenile maize development.
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4.3 Materials and Methods
4.3.1 Plant growth and tissue harvest.
Proprietary hybrid SRG150 seeds were grown in a semi-hydroponic system in pots
containing Turface® clay in a glasshouse during the summer of 2007 at the University of
Guelph. Growth conditions were: 16 h light (~600 µmol m-2 s-1) at 28˚C, 8 h dark at 23˚C, and
50% relative humidity. Plants were watered with a nutrient solution containing: 0.4 g/L 28-14-14
fertilizer, 0.4 g/L 15-15-30 fertilizer, 0.2 g/L NH4NO3, 0.4 g/L of MgSO4•7H2O and 0.03 g/L of
micronutrient mix (S, Co, Cu, Fe, Mn, Mo and Zn). There were three biological replicates per
tissue/stage. All samples were harvested at ~11 am.
4.3.2 Microarray analysis and normalization
RNA was isolated from 50 tissues/stages, three biological replicates per tissue/stage.
RNA was hybridized onto 150 maize Affymetrix 82K Unigene arrays customized for Syngenta,
as previously described (Wagner and Radelof, 2007). Bioconductor (Gentleman et al., 2004) and
R (R-Development-Core-Team, 2009) were used for analysis of gene expression: array gene
expression was normalized using the RMA method (Irizarry et al., 2003).
4.3.3 Statistical analysis of tissue-specific gene expression
If the linear model had been used to fit all contrasts for each of the 50 samples, all
possible pairwise comparisons would have been necessary to discover the tissue specific genes,
corresponding to:
∑(
)
∑
Where n = 50, the number of sample types, the number of contrasts or pair-wise comparisons
would be 1225.
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In order to detect tissue specific and tissue selective gene expression, the Intersection
Union Test (IUT) (Berger and Hsu, 1996) was employed by modifying pre-existing R coding
from: http://ppw.kuleuven.be/okp/software/BayesianIUT/ (Van Deun et al., 2009). The null
hypothesis tested by IUT was that gene expression in the target tissue was not significantly
different than one or more other tissues. The alternative hypothesis was that tissue-specific genes
are more expressed in the target tissue than all other tissues. A gene was reported as being tissue
specific based on performing all possible pairwise t-tests for significant differences in mean gene
expression between a target tissue and all other tissues analyzed. Sidak’s correction was used to
correct the multiple testing methodology of the custom R package, equivalent to the Bonferroni
correction (Sidak, 1967).
4.3.4 Statistical analysis of seminal versus nodal roots
Differential gene expression was measured by fitting a linear model to the data using the
Limma Package from Bioconductor (Smyth, 2005). The linear model was adjusted using the
empirical Bayesian method (modified t-test) from the Limma Package (Smyth, 2005). Multiple
testing was corrected using the Benjamini-Hochberg method applied to the raw p-value
(Benjamini and Hochberg, 1995). The significance threshold of the adjusted p-value was set at
0.05. This procedure was used to compare seminal to nodal roots.
4.3.5 Gene Ontology detection
To link microarray probes to known genes, a custom Perl script was created to retrieve
protein sequences from Genbank that matched the array probes. These Genbank protein
sequences were then matched to the filtered B73 maize gene set from MaizeSequence.org using
standalone protein BLAST searches (Schnable et al., 2009). A list of MaizeSequence.org gene
IDs was created for each tissue comparison, and a GO term was assigned to each retrieved gene
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using AgriGO (Du et al., 2010). GO terms were determined to be enriched for a specific
tissue/stage using the hypergeometric test from AgriGO.
4.3.6 Promoter motif discovery
For each tissue selective or tissue specific array probe, the corresponding maize gene(s)
was retrieved using the custom Perl script described above. Promoter sequences (-500 to +1
region) upstream of all genes within each expression cluster were then analyzed for overrepresented de novo cis-acting motifs (≥ 6 bp) using a Perl-based motif discovery program
developed for the maize genome, called Promzea (see Chapter 3.3, Materials and Methods
section). Briefly, for each expression list, the gene IDs retrieved from MaizeSequence.org were
used to generate a set of promoter sequences. Over-represented motifs in each promoter set were
then identified using three motif discovery tools: Weeder (Pavesi et al., 2007), MEME (Bailey
and Elkan, 1994) and BioProspector (Liu et al., 2001). Each motif was re-evaluated statistically
using the hypergeometric test or the binomial test. All significant motifs found in the search were
compared to the motif databases; Athamap (Bülow et al., 2009) and PLACE (Higo et al., 1999),
using STAMP software (Mahony and Benos, 2007). Only motifs were reported that were
preferentially located at one or more common positions within the promoters of each expression
cluster.
4.4 Results and Discussion
4.4.1 Overview
RNA was collected from 50 maize tissues from the vegetative emergence stage to
31 days after pollination (DAP) (Table 4.1) and hybridized to custom maize 82K Unigene arrays.
Combining all tissues, 53,554 probe sets were expressed (relative expression >100), representing
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64.8% of the array. Interestingly, there were 145 probe sets that were selective for a single-stage
juvenile root or leaf tissue, identifying these as developmental markers (Figures 1, 2).
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Table 4.1. Detailed description of developmental stages and tissues sampled.
developmental
stage
tissue/organ
number of
visible leaves
detail of the harvested sample
VE
leaf
0
coleoptile
VE
seminal root
0
root
V1
leaf
2
1st & 2nd leaf
V1
seminal root
2
root
V2
seminal root
4
seminal root
V2
nodal root
4
nodal root
V2
stalk
4
stalk
V2
leaf
4
leaf (actively growing leaf--- 4th leaf)
V4
tassel
6
V5
seminal root
8
seminal root
V5
nodal root
8
nodal root
V5
stalk
8
stalk below tassel (2cm)
V5
leaf
8
V5
tassel
8
tassel 3-5mm
V7
ear
12
tassel 2cm
V7
tassel
12
top ear shoot
V8~V9
tassel
13~14
tassel 12~14 cm
V8~V9
ear
13~14
top ear 3~5mm
1mm tassel meristem & 1mm uppermost stem
below tassel
leaf (actively growing leaf--- 8th leaf, 15cm
including tip)
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Table 1 (continued)
V10~V11
tassel
15~16
top 10cm of tassel (~20cm)
V10~V11
ear
15~16
top ear 1~1.5cm
V13~V15
tassel
15~16
spikelet of tassel (~22cm)
V13~V15
ear
15~16
top ear 3~3.5cm
V15~V16
floret
15~16
top ear(5cm) floret
V15~V16
cob
15~16
top ear (5cm)cob
V15~V16
silk
15~16
top ear (5cm)silk
V15~V16
tassel
15~16
spikelet of tassel (top 10cm)
VT
anthers
15~16
anther
R1
ovule
15~16
R1-ovule of top ear
R1
cob
15~16
R1-cob of top ear
R1
silk
15~16
R1-silk of top ear
R1
husk
15~16
R1-most inner husk of top ear
R1
leaf
15~16
R1-15cm tip of 2nd leaf above top ear
R1
nodal root
15~16
R1-adult root
R1
stalk
15~16
R1-15cm stalk below tassel
5DAP
ovule
15~16
ovule of top ear
5DAP
cob
15~16
cob of top ear
10DAP
embryo
15~16
embryo of top ear
10DAP
endosperm
15~16
endosperm of top ear
10DAP
leaf
15~16
15cm tip of 2nd leaf above top ear
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Table 1 (continued)
17DAP
embryo
15~16
embryo of top ear
17DAP
endosperm
15~16
endosperm of top ear
17DAP
pericarp
15~16
pericarp of top ear
17DAP
leaf
15~16
15cm tip of 2nd leaf above top ear
24DAP
leaf
15~16
15cm tip of 2nd leaf above top ear
24DAP
nodal root
15~16
root
24DAP
pericarp
15~16
pericarp of top ear
24DAP
embryo
15~16
embryo of top ear
24DAP
endosperm
15~16
endosperm of top ear
31DAP
leaf
15~16
15cm tip of 2nd leaf above top ear
31DAP
embryo
15~16
embryo of top ear
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4.4.2 Stage-selective leaf expression
4.4.2.1 Ve coleoptile-selective expression and DIMBOA
A total of 43 probes representing 23 genes showed coleoptile-selective expression at the
Ve emergence stage (Figure 4.1A, B). There were several Ve leaf-selective genes of interest,
including a gene encoding indole-3-glycerol-phosphate synthase (IGPS) (Table 4.2), which
catalyzes the fourth step in tryptophan biosynthesis, an important enzyme in the precursor
pathway for synthesis of auxin (IAA, indole-3-acetic acid) (Ouyang et al., 2000). In maize, the
coleoptile tip has been shown to produce IAA (Mori et al., 2005). However, IGPS is also
involved in the synthesis of protective secondary metabolites, including DIMBOA (2,4dihydroxy-7-methoxy-1,4-benzoxazin-3-one, KEGG: zma00402), an important anti-pathogen
compound produced by grasses (Frey et al.). Consistent with this, genes encoding three enzymes
in the DIMBOA biosynthetic pathway showed Ve coleoptile-selective expression:
Benzoxazinless1, Benzoxazinone Synthesis 2 and Benzoxazinone Synthesis 8 (Frey et al.) (Table
4.2). Interestingly, it has been shown that DIMBOA is abundant in maize seeds and seedlings up
to 10 days after germination (Cambier et al., 2000), consistent with our gene expression data.
We found over-represented motifs in the promoters of genes selectively expressed in Ve
coleoptile leaves which we refer to as motifs of Maize Ve-stage Leaves (MVeL). MVeL1 and
MVeL2 were similar to RE-alpha and RE-beta cis-elements, respectively as shown in Figure
4.1C (Degenhardt and Tobin, 1996). The RE motifs were first characterized as adjacent elements
in the promoter of the Lemna gibba light-harvesting complex II gene Lhcb2.1 and were shown to
be responsible for phytochrome-mediated regulation, facilitating promoter repression in darkness
(Degenhardt and Tobin, 1996).
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4.4.2.2 V1 leaf selective expression
Only 15 probes corresponding to five genes were selective for V1 stage leaves (Figure
4.1A, B). This small number did not allow for a reliable search for cis-acting elements
underlying this expression cluster.
4.4.2.3 V2 leaf selective expression and light regulation
A total of 59 probe sets, representing 29 genes, were V2 leaf selective (Figure 4.1A,B).
One promoter motif was most over-represented in this cluster, which we refer to as a motif of
Maize V2-stage Leaves (MV2L1) (Figure 4.1C). MV2L contained an ACGTA core previously
found in the A-box subfamily of ACGT elements, shown to bind bZIP transcription factors
(Foster et al., 1994). MV2L also showed a 6 bp match to the ABA regulated ABRE3 cis-element
of the barley Hva22 gene (GCCACGTACA) (Shen and Ho, 1995), and a 5 bp perfect match
(GCCAC) to SORLIP1, a motif over-represented in phytochrome A-induced promoters (Hudson
and Quail, 2003). Consistent with the latter match, 10/29 of the V2 leaf-selective genes were
associated with the chloroplast (data now shown). Among the chloroplast-associated genes was
an ortholog of the Arabidopsis gene, Acclimation of Photosynthesis to Environment (Ape1)
(Table 4.2). Ape1 mutants reduce the ability of a plant to acclimate following a shift from low
light to high light, and are unable to restore rates of photosynthesis and/or levels of chlorophyll
(Walters et al., 2003). A gene encoding the LIGHT-HARVESTING LIKE 3 (LIL3) protein was
also highly selective for growing V2 leaves (Table 4.2). During chloroplast biogenesis, LIL3
appears to be the essential protein that binds to chlorophyll to enable formation of the light
harvesting complex (LHC) following a shift from extended darkness to light (de-etiolation)
(Reisinger et al., 2008). These data suggest the existence of light-regulated gene expression
specific to V2 leaves in maize.
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Table 4.2: Tissue/stage-specific interesting genes
Gene name
Description
Ve Leaf
GRMZM2G169516
GRMZM2G085381
GRMZM2G085661
GRMZM2G085054
V2 Leaf
GRMZM2G099367
GRMZM2G477236
GRMZM2G007160
GRMZM2G012717
GRMZM2G034243
GRMZM2G038494
GRMZM2G066107
GRMZM2G067853
GRMZM2G074857
GRMZM2G105539
GRMZM2G111216
GRMZM2G319109
V1 Root (seminal)
GRMZM2G086496
GRMZM2G127139
V2 Root (seminal)
GRMZM2G072529
GRMZM2G166639
GRMZM2G114503
GRMZM2G028736
GRMZM2G070087
Putative indole-3-glycerol-phosphate synthase, hypothetical
protein LOC100274566
Benzoxazineless 1, Indole-3-glycerol phosphate lyase,
chloroplastic Precursor (EC 4.1.2.8)
Benzoxazinone synthesis 2, benzoxazineless 2, Cytochrome P450
71C4
Benzoxazinone synthesis 8 (bx8), UDP-glucosyltransferase
Ortholog of Arabidopsis chloroplast ACCLIMATION OF
PHOTOSYNTHESIS TO ENVIRONMENT (APE1)
lil3 protein
chloroplastic hydrolase, alpha beta fold family protein
light responsive zinc finger (B-box type) family protein
chloroplast NAD(P)H dehydrogenase complex, NDHDEPENDENT CYCLIC ELECTRON FLOW 1 (NDF2)
chloroplastic GTP-binding protein-related
chloroplast CAAX amino terminal protease family protein
chloroplast ATPase cadmium-transporting
EMB1374, chloroplast sulfur E
anion-transporting ATPase family protein located in chloroplast
CHLOROPLAST STEM-LOOP BINDING PROTEIN 41
FZO-LIKE (FZL) GTP binding GTPase thiamin-phosphate
diphosphorylase regulation of organization of the thylakoid
network
Ortholog of Arabidopsis NRT1.1, CHL1
zeaxanthin epoxidase, chloroplast precursor
ACC oxidase
ACC oxidase
RADIALIS , ortholog of ATRL6
ammonium transmembrane transporter , ortholog of ATAMT1;2
Rice protein inorganic phosphate transporter 1-7, putative
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Figure 4.1. Juvenile leaf stage-selective array expression and associated over-represented
promoter motifs. (A) Relative probe expression heatmap summary showing selective expression
for Ve (emerging coleoptile), V1 (two leaf) and V2 (four leaf) stages. Each heatmap row
represents a unique probe set, and the relative probe expression ranges from low (yellow) to high
(dark blue). (B) Relative expression of the corresponding probes is shown more quantitatively.
(C) Over-represented cis-acting elements present in the promoters of each stage-selective leaf
gene expression cluster. Matches to previously identified motifs (Similar to) along with the
similarity score (E-value) are shown. Only the most overrepresented motifs are shown.
Abbreviations: V, vegetative pre-flowering stage; R, reproductive post-flowering stage; nDAP,
days after pollination. Refer to Table 4.1 for tissue sampling details.
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4.4.3 Stage-selective root expression
4.4.3.1 Ve root selective expression
Twenty probes representing 11 genes were selective for Ve stage root tissue (Figure
4.2A,B). A previously uncharacterized motif, which we refer to as a motif of Maize Ve-stage
Roots (MVeR1, consensus GATGGANT) was over-represented in Ve root selective gene
promoters (Figure 4.2C). This sequence was similar to the in vivo HOX (homeodomain) binding
site of the PBC-HOX1/LAB heterodimer complex [TGAT(t/g)GAT(t/g)] from Drosophila
required to specify anteroposterior segment identity in multicellular animals, in particular its
GATGG core (Ebner et al., 2005; Mann et al., 2009).
4.4.3.2 V1 root selective expression
A total of 17 probes, representing 10 genes, were selective for V1 stage roots (Figure
4.2A, B). One interesting V1 stage root-selective gene was a paralog of Ntr1.1
(GRMZM2G097851; Table 4.2), a low affinity nitrate transporter (Crawford and Glass, 1998;
Gaudin et al., 2011). This data is suggestive of stage and tissue specific regulation of nutrient
uptake in maize, consistent with recent data from Arabidopsis (Krapp et al., 2011). Also
selectively expressed in V1 roots was a gene encoding zeaxanthin epoxidase (ZEP,
GRMZM2G127139, Table 4.2), which converts zeaxanthin to violaxanthin carotenoids, trace
amounts of which have been found in roots (Howitt and Pogson, 2006). However, ZEP is also
the first step in the biosynthesis of the hormone abscisic acid (ABA), and in accordance ZEP loci
are often called Aba1 or Aba2. ABA production has been reported in roots involving
accumulation of ZEP mRNA, particularly during stress (Audran et al., 1998). Functional
experiments will be required to understand the role of a V1 root-specific ZEP in maize.
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A novel putative partly palindromic cis-acting element, TCGGTTCGCGAA, was
identified as over-represented in the genes co-expressed in V1 roots, which we refer to as a motif
of Maize V1-stage Roots (MV1R1) (Figure 4.2C). The core of this motif (GTTCGC) was
identical to the core of the binding site for ClgR (GTTCGC-5N-GCG) in Streptomyces bacteria
where it acts as a transcriptional regulator of genes involved in an unusual form of prokaryotic
differentiation (Bellier and Mazodier, 2004).
4.4.3.3 V2 seminal root selective expression and ethylene
In seminal roots, 17 probes representing 19 genes were V2-root tissue selective (Figure
4.2A, B). Amongst these were two genes encoding two distinct ACC oxidases (Table 4.2),
enzymes which catalyze the last step in the biosynthesis of ethylene, a hormone that plays a
critical role during root development (Ruzicka et al., 2007). At higher concentrations, ethylene
has been shown to be a repressor of root cell elongation via auxin (Ruzicka et al., 2007) and can
inhibit the growth of immature primary and lateral roots (Ruzicka et al., 2007; Gallie et al., 2009;
Tian et al., 2009). At low concentrations, ethylene can promote lateral root initiation and
enlargement (Ivanchenko et al., 2008). One speculative hypothesis is that selective ACC oxidase
expression in V2 stage seminal roots may help to regulate the change in root architecture
observed between juvenile and adult maize stages (Singh et al., 2010). Also selectively expressed
in V2 seminal roots was the maize gene Radialis (RAD), a putative ortholog of Arabidopsis
ATRL6/RSM3, which encodes a MYB transcription factor first identified in Antirrhinum as
regulating floral asymmetry and shown to be expressed along ab-adaxial or radial domains
(Baxter et al., 2007). Interestingly, in Arabidopsis, a mutation in a paralog of ATRL6, RSM1,
has been shown to participate in an important ethylene-auxin cross-talk signalling pathway
involving HOOKLESS 1 (Hamaguchi et al., 2008).
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Other interesting genes that were selectively expressed in V2 seminal roots were related
to nutrient uptake and/or transport, including orthologs of rice Phosphate Transporter 1.7
(PHT1;7) and Arabidopsis Ammonium Transporter 1.2 (AMT1;2) (Table 4.2).
Over-represented in V2 root promoters was a motif, which we refer to as a motif of
Maize V2-stage Roots (MV2R1, consensus TAcTAT), very similar to the plant SURE box
[sugar responsive element, consensus (a/t)(t/c)ACT(a/g)T(t/g)](Grierson et al., 1994)(Figure
4.2C). The SURE box was first identified as the SP8b motif (TACTATT) which binds the
WRKY-family SP8 transcription factor in the sugary roots of sweet potatoes (Ishiguro and
Nakamura, 1994; Agarwal et al., 2011). Subsequently, it has been demonstrated that a few
WRKY transcription factors, such as SP8, may independently bind to SURE as well as a
canonical W-box element (Rushton et al., 2010). Included on this list of WRKY proteins is the
transcription factor SUSIBA2/HvWRKY46 which regulates expression of anabolic carbohydrate
enzymes in barley endosperm (Sun et al., 2003). This data suggests that a SURE-WRKY regulon
may operate in V2 stage maize roots to modulate gene expression based on sugar availability.
4.4.3.4 V2 crown root selective expression
No probes showed selective expression for V2 crown roots (Figure 4.2A).
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Figure 4.2. Juvenile root stage-selective probe expression and associated over-represented
promoter motifs. (A) Relative probe expression heatmap summary showing selective expression
for Ve stage (emerging coleoptile), V1 stage (two leaf) and V2 stage (four leaf). Each heatmap
row indicates a unique probe set, and the relative expression of each probe ranges from low
(yellow) to high (dark blue). (B) More quantitative expression of the corresponding probes is
shown. (C) Over-represented motifs present in the promoters of each stage-selective root
expression cluster. Matches to previously identified motifs (Similar to) along with the similarity
score (E-value) are indicated. Only the most overrepresented motifs are shown. Abbreviations:
V, vegetative pre-flowering stage; R, reproductive post-flowering stage; nDAP, days after
pollination. Refer to Table 4.1 for additional tissue sampling information.
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4.4.4 Comparison of the transcriptomes of seminal versus nodal root organs
The young maize root system backbone consists of two distinct organs, seminal roots and
nodal roots, also named crown roots (Figure 4.3A). To characterize genetic differences between
these root organs, their gene expression patterns were compared. For this comparison, results
were pooled from V2 and V5 stages to make the data more robust against stage-specific
expression. A total of 1035 probes were differentially expressed between the two organ types:
711 probes were up-regulated in seminal roots compared to nodal roots, while 334 probes were
up-regulated in nodal roots (Figure 4.3B). Proteins associated with heme binding and electron
carrier activity were common to the two root organ types (Figure 4.3C, D). Surprisingly, probes
corresponding to seven out of the 21 nuclear genes associated with Photosystem I were
selectively up-regulated in seminal roots (Table 4.3). The seminal root cluster was also overrepresented for genes associated with the chloroplast and photosynthesis including the thylakoid
membrane (Figure 4.3C; Table 4.3). As expected, these photosynthetic genes were less expressed
in roots compared to the foliar tissues (Figure 4.4). Previous studies have similarly shown that
Photosystem I genes can be expressed in roots, but the underlying reason is not understood
(Sullivan and Gray, 1999; Stöckel and Oelmüller, 2004; Yabe et al., 2004). It has been inferred
that plastids in dark-treated shoots and/or in roots could signal the expression of nuclear-encoded
photosynthesis genes (Sullivan and Gray, 1999). Our results suggest that plastids in maize
seminal roots able to signal nuclei but not those in nodal roots, a novel finding worth
investigating.
Probes selectively up-regulated in nodal roots (crown roots) were related to antioxidant
and oxidative stress responses (Figure 4.3D), implicated in the hormonal control of root
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development (De Tullio et al., 2010). Curiously, a few genes related to sexual reproduction were
also selectively expressed in nodal roots but not in seminal roots (Figure 4.3D).
One motif was over-represented in the promoters of genes selectively expressed in
seminal roots compared to nodal roots, and was named the Maize Seminal Root motif (MSR1):
AACAGGCG (Figure 4.3E). Reversed, MSR1 was similar to the anaerobic response motif
having the consensus sequence AACAGGG consensus and associated with abiotic stress
(Mohanty et al., 2005). The core of MSR1 also matched the consensus sequence AACAGG of
the E-box motif implicated in binding class A bHLH transcription factors (Hsu et al., 1994).
Two motifs were over-represented in the promoters of genes selectively expressed in
nodal roots (crown roots) compared to seminal roots, and were named motifs of Maize Nodal
Roots: CCTCTCTCTC (MNR1) and GNACGTA (MNR2) as shown in Figure 4.3E. MNR1 is
similar to the CT-rich motif known to be an enhancer of the CaMV 35S promoter (Pauli et al.,
2004). The core of MNR1 is identical to a motif (CTCTCTC) over-represented in Arabidopsis
promoters that are under diurnal regulation and are dark induced (Janaki and Joshi, 2004), which
may be related to differences in the expression of photosynthesis genes in seminal versus nodal
roots, as discussed above. When reversed, the core of MNR1 matches GAGAG elements in
Drosophila that bind transcription factors containing a GAF domain (van Steensel et al., 2003).
The GAF domain is conserved in plant sensory proteins (e.g. ethylene receptor ETR) including
those involved in phytochrome B signaling (Su and Lagarias, 2007). The core of MNR2 is found
in the A-box subfamily of ACGT elements (ACGTA), shown to bind bZIP transcription factors
(Foster et al., 1994).
118
Figure 4.3. GO annotation summary of corresponding genes selectively up-regulated in seminal
roots compared to nodal roots. (A) Cartoon illustrating maize seminal roots (SR) and nodal roots
(NR or crown roots). (B) Number of genes (probes) up-regulated in seminal roots and nodal
roots. (C, D) GO annotation of genes up-regulated in (C) seminal roots and (D) nodal roots. (E)
Corresponding over-represented promoter motifs associated with each organ type, seminal roots
(MSR) and nodal roots (MNR). For this analysis, array expression data was pooled from V2 and
V5 stages.
119
120
Figure 4.4. Relative expression of array probes corresponding to photosynthesis related genes in
roots compared to leaves. These probes were shown to be up-regulated in seminal roots (V2 and
V5 stages pooled) compared to nodal roots.
121
Table 4.3: GO terms of the photosynthetic genes up-regulated in seminal roots compared to
nodal roots.
Name
GO terms
GO source
Description
GO:0015979 photosynthesis
GRMZM2G013342
IPR003685 Photosystem I protein PsaD
GO:0009538 photosystem I reaction center
GO:0016020 membrane
GRMZM2G149428
IPR001344 Chlorophyll A-B binding protein
GO:0009765 photosynthesis, light harvesting
GO:0015979 photosynthesis
GRMZM2G017290
Photosystem I reaction centre protein
IPR003666
PsaF, subunit III
GO:0009538 photosystem I reaction center
GO:0015979 photosynthesis
GRMZM2G024150
IPR003685 Photosystem I protein PsaD
GO:0009538 photosystem I reaction center
GO:0009522 photosystem I
GRMZM2G012397 GO:0015979 photosynthesis
IPR017493 --IPR016370 --IPR000549 Photosystem I PsaG/PsaK protein
GO:0003824 catalytic activity
IPR008990 Electron transport accessory protein
GO:0009536 plastid
IPR003375
Photosystem I reaction centre subunit
IV/PsaE
GRMZM2G016066
GO:0015979 photosynthesis
GO:0009538 photosystem I reaction center
GO:0046406 magnesium protoporphyrin IX
IPR013217 --methyltransferase activity
GO:0015995 chlorophyll biosynthetic process
IPR013216 Methyltransferase type 11
GO:0050825 ice binding
IPR010940
Magnesium-protoporphyrin IX
methyltransferase, C-terminal
GRMZM2G161673
Magnesium protoporphyrin OGO:0042309 homoiothermy
IPR010251
methyltransferase
GO:0050826 response to freezing
IPR000104 Antifreeze protein, type I
GO:0015979 photosynthesis
122
GO:0015979 photosynthesis
GRMZM2G451224
Photosystem I reaction centre subunit
IPR004928
GO:0009538 photosystem I reaction center
VI
GO:0009522 photosystem I
IPR017494 ---
GO:0015979 photosynthesis
IPR000549 Photosystem I PsaG/PsaK protein
GRMZM2G377855
GO:0031361 integral to thylakoid membrane
GO:0015979 photosynthesis
GRMZM2G448174
IPR002325 Cytochrome f
GO:0020037 heme binding
GO:0009055 electron carrier activity
Note: This annotation gene list was obtained from the AgriGO website. In the some cases, the
description is inferred from the target.
123
4.5 Study Limitations and Significance
One of the challenges for microarray studies that compare a diversity of tissues is how to
normalize for any differences in overall gene expression between tissues. Here, a global RMA
method was used for array normalization (Irizarry et al., 2003) but this could be seen to introduce
biases in the data, because RMA forces the expression of all tissues to be within the same range.
Imposing such expression uniformity may create artifacts, as the level of gene expression in
actively growing leaves may not be the same as in fully emerged leaves or anthers. However, a
previous study has shown that biases caused by RMA normalization are negligible when
comparing different tissues in a microarray experiment (Eschrich et al., 2008).
Another challenge of this study was that some array probe sets matched multiple paralogs
in the maize genome. The maize genome is an ancient allotetraploid and contains large gene
families (Schnable et al., 2009). As these genes were used to define the promoter datasets for
motif searching, it may be that a subset of the promoters used for this purpose were incorrect,
reducing the possibility to discover the exact consensus motif.
The goal of this study was to determine if specific organ and stage-selective gene
expression clusters could be distinguished during juvenile maize development, and if so, to
identify associated over-represented promoter motifs. Distinct over-represented promoter motifs
corresponding to each stage of juvenile development were identified for leaf and root organs.
Several of these motifs have not previously been reported in plants. In addition, organ- and
stage-selective genes were also identified as landmarks for maize juvenile development,
including genes involved in hormone and secondary metabolite biosynthesis, nutrient
uptake/transport and light-regulated genes. These results suggest that juvenile maize vegetative
development can be subdivided into distinct developmental stages, corresponding to emergence
124
(Ve, coleoptile), V1 (two leaf) and V2 (four leaf) stages. Each stage can be identified by
distinguishable promoter motifs and selective transcription of landmark genes as noted in this
study. If validated experimentally, the predicted promoter motifs should permit improved
targeted gene expression in maize with applications for basic research and biotechnology.
125
5. Promoter motifs associated with leaf and root gene expression at
the juvenile, adult and reproductive phases of maize (Zea mays
L.) development
Author contributions: Christophe Liseron-Monfils conducted all microarray and bioinformatics
analyses. Plants were grown by Wenqing Wu and Tara Signorelli (Steven Rothstein`s laboratory,
University of Guelph). RNA extraction was led by Yong-Mei Bi (Steven Rothstein`s laboratory,
Guelph). Part of the annotation of the microarray was done by Gregory Downs (Lewis Lukens`
laboratory, University of Guelph). The array hybridizations were performed by Xi Chen and
Eddie Bondo at Syngenta Biotechnology Inc. (Research Triangle Park, North Carolina, 27709,
USA).
126
5.1 Abstract
The objective of this study was to identify leaf and root cis-acting promoter motifs
associated with the three distinct developmental phases of maize (Zea mays L.): juvenile, adult
and reproductive. Affymetrix 82K-microarrays were used to analyze gene expression in 50
tissues from juvenile to post-flowering stages. Distinct stage- and organ-selective gene
expression clusters were found and used to identify over-represented promoter motifs within
each cluster. All the juvenile leaf and juvenile root promoter motifs contained AGG and GAA
trinucleotides and resembled the Arabidopsis FLOWERING LOCUS C Motif 2 binding site.
Three 5-bp promoter motifs were identified for the adult leaf-selective cluster (AACAA,
CCACG, CCGTT) which matched over-represented motifs from the adult root-selective cluster.
These results suggest that similar transcription factors regulate phase identity in both, roots and
shoots, an unexpected result. Database searches suggested that the shared adult-phase 5-bp
motifs bind MYB and bZIP factors. When comparing juvenile-to-adult expression clusters, 12
common genes were differentially expressed in both roots and leaves, identifying potential
whole-plant phase-change genes; these included APETALA1-like and MADS-box genes.
Additional whole-plant expressed genes encoded wax biosynthesis enzymes including
GLOSSY1/CER1, suggesting that wax, a well-known leaf phase-change trait, is also involved in
root phase-change. Root and leaf expression clusters from pre-flowering/vegetative growth
stages were compared to post-flowering/mature stages when maize shifts resources from
vegetative growth to nutrient remobilization. Distinct promoter motifs specific for roots or leaves
were identified associated with pre-flowering versus post-flowering stages. These results provide
novel insights into whole-plant transcriptional regulation of phase change in maize.
127
5.2 Introduction
Shoot development in higher plants including maize (Zea mays L.) is divided into three
phases: juvenile, adult and reproductive (Poethig, 1990, 2010). There is interest in understanding
the underlying gene regulation responsible for these shifts in development. Morphological
markers can distinguish juvenile from adult leaves: in maize, juvenile leaves are narrow and
possess a thin cuticle, but their adaxial surface is covered with epicuticular wax. By contrast,
adult maize leaves are wide, have a thick cuticle, and their adaxial surface lacks wax (Poethig,
1990). In maize, the juvenile vegetative phase starts at coleoptile leaf emergence (Ve) and ends
after emergence of the first 4-6 embryonic leaves which are pre-formed during seed development
(Kiesselbach, 1999, 1999). The adult vegetative phase then begins represented in this study
fromV5 stage; five stem-nodes formed; eight leaves emerged) until all leaf primordia on the
main shoot axis are formed. The shoot apical meristem then converts into an inflorescence
meristem which initiates the reproductive phase. This post-flowering phase includes seed
development which is characterized based on the number of days after pollination (DAP)
(Kiesselbach, 1999). Underground, the juvenile maize root system consists of a single primary
root and variable number of seminal roots. Early during juvenile development, shoot-borne nodal
roots (crown roots) initiate below ground, and subsequently form the backbone of the adult and
reproductive root systems (Gaudin et al., 2011). Limited information exists about the role that
roots play during phase change, though roots have been shown to help regulate the vegetative to
reproductive transition in maize (Poethig, 1990).
The existence of these major developmental phases has also been demonstrated at the
molecular level. The two phase transitions have been shown to be regulated by transcription
factors, miRNAs and chromatin remodelling factors that work together in a complex network
128
that integrates environmental cues (Kaufmann et al., 2010; Poethig, 2010). In maize and
Arabidopsis, a small RNA (miRNA156) was found to be a necessary and sufficient regulator of
juvenility: it was shown to build up during the juvenile phase then decline during the adult
transition (Wu and Poethig, 2006; Chuck et al., 2007; Wu et al., 2009). The targets of miR156
are Squamosa Promoter Binding Protein (SBP) genes (Rhoades et al., 2002; Schwab et al.,
2005). SBP and Squamosa promoter binding-like proteins (SPL), have been shown to be
involved in juvenile, adult and reproductive phase transitions (Wu and Poethig, 2006; Shikata et
al., 2009). When over-expressed, SBP genes targeted by miR156 cause early flowering (Cardon
et al., 1997; Wu and Poethig, 2006). In Arabidopsis, the MADS box transcription factor,
FLOWERING LOCUS C (FLC), previously shown to repress genes that promote flowering, was
also shown to delay the transition from juvenile to adult phases via SPL15 through binding of its
cis-element targets, of which 505 were identified (Deng et al., 2011). Of these targets, 69% were
similar to the canonical MADS box cis-element [CArG motif, CCAAAAAAT(G/A)G], while
39% bound to G-A rich cis-acting promoter elements (Deng et al., 2011). These observations
confirm an antagonistic connection at the molecular level between juvenility and flowering,
which has long been known morphologically (Poethig, 1990). The results also demonstrate that
large scale transcriptional networks are involved in phase change.
Microarray studies across developmental phases and organs have begun to shed light on
the larger transcriptional networks affected by phase transition in plants (Schmid et al., 2005;
Strable et al., 2008; Jiao et al., 2009; Wang et al., 2010; Sato et al., 2011; Sekhon et al., 2011).
For example, Strable et al. (2008) examined gene expression in maize leaves during the
transition from juvenile to adult stages, and showed genes related to photosynthetic traits were
up-regulated in juvenile leaves.
129
Here, we used microarray analysis to identify gene expression clusters in roots and leaves
at juvenile, adult, pre-flowering and post-flowering stages. We then used these gene expression
clusters to identify over-represented motifs in the promoters of the genes within each expression
cluster using a software program we recently created for the maize genome called Promzea (see
Chapter 3.3, Materials and Methods section). We report that motifs associated with changes in
gene expression from the juvenile-to-adult transition and from pre-flowering to flowering stages,
are shared by both root and leaf gene clusters. We also identify shared genes that are upregulated in both roots and shoots during phase transition. Combined, these results suggest root
and shoot coordination of phase change in maize.
130
5.3 Materials and Methods
5.3.1 Plant growing conditions and tissues sampled.
The same plant samples were used as described in Chapter 4.
5.3.2 Affymetrix array hybridization and normalization procedure
The same 150 arrays were used as indicated in Chapter 4.
5.3.3 Statistical analysis of phase change
Differential probe expression was measured by fitting a linear model to the results using
the Limma Package from Bioconductor (Smyth, 2005). The linear model was adjusted by using
the empirical Bayesian method (modified t-test) obtained from the Limma Package (Smyth,
2005). Multiple testing was corrected by using the Benjamini-Hochberg methodology, applied to
the raw p-value (Benjamini and Hochberg, 1995). The significance threshold of the adjusted pvalue was set at 0.05.
5.3.4 Gene Ontology (GO) analysis
To match microarray probes to known genes, a custom Perl script was written to retrieve
protein sequences from Genbank that matched the microarray probes. The Genbank protein
sequences were then matched to the filtered B73 maize gene set from MaizeSequence.org using
protein BLAST searches (Schnable et al., 2009). A list of MaizeSequence.org gene IDs was
created for all organ comparisons, and GO terms were assigned to all retrieved genes using
AgriGO (Du et al., 2010). The hypergeometric test from AgriGO was used to determine if GO
terms were enriched for a specific organ or developmental stage.
5.3.5 Discovery of over-represented promoter motifs
For all organ-selective or organ-specific array probes, corresponding maize genes were
retrieved using the custom Perl script noted above. Promoter sequences (-500 to +1 region)
131
upstream of all genes within each expression cluster were then analyzed for over-represented de
novo cis-acting motifs (≥ 6 bp) using a Perl-based motif discovery program which we developed
for the maize genome, called Promzea (see Chapter 3.3, Materials and Methods section). Briefly,
for each expression list, the gene IDs retrieved from MaizeSequence.org were used to generate a
set of promoter sequences. Over-represented motifs in each promoter set were then identified
using three motif discovery tools: Weeder (Pavesi et al., 2007), MEME (Bailey and Elkan, 1994)
and BioProspector (Liu et al., 2001). Each motif was statistically re-evaluated using the
binomial test or the hypergeometric test. All significant motifs retrieved were compared to the
following motif databases using STAMP software (Mahony and Benos, 2007): Athamap (Bülow
et al., 2009) and PLACE (Higo et al., 1999). Motifs were reported only if they were
preferentially located at one or more common positions within the promoters of each gene
expression cluster.
132
5.4 Results and Discussion
5.4.1 Overview of transcriptome results
RNA was harvested from 50 maize tissues from the seedling emergence stage until
31 days after pollination (DAP) (see Table 4.1) and hybridized to custom 82K maize Unigene
arrays. After combining results from all tissues, 53,554 probe sets were expressed (relative
expression >100), which represented 64.8% of the array. Above ground, 82% (41,948) of the
expressed probe sets were expressed in leaves; 77.3% of the expressed probes were detected in
juvenile leaves (Ve, V1 and V2), and 74.3% were expressed in leaves of later stages. Only 8.1%
(4,333) of expressed probes were selective for juvenile leaves compared to later-stage leaves (V5
to 31DAP). Below ground, 77.4% of the expressed probe sets were detected in at least one root
stage; 72.2% of expressed probes were expressed in juvenile root tissues, and 74.1% were
detected in roots at later stages. Comparing roots of different stages, only 3.3% (1,785) of probe
sets were selective for juvenile roots, whereas 5.1% (2,767) were selective for later-stage roots.
A total of 6,955 probes, equivalent to 13% of the expressed probe sets in the study, were
selective for juvenility (leaves and roots combined) (data not shown).
5.4.2 Juvenile to adult transition
Comparisons were made between leaves and roots of V2 stage tissue (leaf 4 actively
growing) versus V5 stage tissue (growing leaf 8, 15 cm from tip) to detect over-represented
promoter motifs associated with the transition from juvenile to adult vegetative development.
5.4.2.1 Juvenile versus adult leaves
A total of 187 probe sets (96 genes) were differentially expressed between leaf 4 (V2)
and leaf 8 (V5) (Figure 5.1A). Interestingly, there were five probe sets that were specifically
expressed in leaf 8 at the V5 stage, and were not expressed in leaf 8 at any other stage of
133
development, or in any other vegetative tissue at any stage of development (Figure 5.1B; see
Table 4.1). One of these probes corresponded to an uncharacterized DUF607 superfamily protein
containing a coiled-coiled domain also found in mitochondrial calcium uniporter proteins
(Interpro Protein Domain: IPR006769, GRMZM2G425863). The remaining probes had no clear
gene annotation in any plant genome. The promoters of these genes should serve as useful
markers of adult vegetative development.
Genes that were comparatively up-regulated in juvenile leaf 4 included those associated
with growth (e.g. fatty acid biosynthesis) (Figure 5.2A). There were no over-represented GO
annotation categories associated with up-regulated genes in leaf 8/V5 tissue, likely because only
24 genes could be confidently identified that corresponded to these probes (data not shown).
Two motifs were over-represented in the promoters of the genes that were up-regulated in
juvenile leaf 4 (V2 stage), which we have termed motifs of Maize Juvenile Leafs (MJL1-2)
(Table 5.1). Three novel motifs were over-represented upstream of genes that were up-regulated
in adult leaves (leaf 8, V5), which we have called motifs of Maize Adult Leaves (MAL1-3)
(Table 5.1).
134
Table 5.1: Over-represented motifs associated with vegetative phase change.
Motif name
Consensus/Reverse
Preferential
position
Up-regulated
tissue
-200 -150
juvenile leaves
-100 -50
juvenile leaves
MJL2
TTCACCTTCCA
/TGGAAGGTGAA
TACCTTTTC/GAAAAGG
MJR1
TCCTTTTCCT/AGGAAAAGGA
-500 -450
juvenile roots
MJR2
TGGTTTCCCT/AGGGAAACCA
-500 -450
juvenile roots
MAL1
CATGCAACAA/TTGTTGCATG
-300 -250
adult leaves
MAL2
ACACCACG/CGTGGTGT
-100 -50
adult leaves
MAL3
CCCCCGTT/AACGGGGG
-50 +1
adult leaves
MAR1
GTTTGTTTG/CAAACAAAC
-150 -100
adult roots
MAR2
TNGAAACAAA/TTTGTTTCNA
-200 -150
adult roots
MAR3
CCACGC/GCGTGG
-100 -50
adult roots
MAR4
TCCGTTTCCC/GGGAAACGGA
-50 +1
adult roots
MAR5
CAGACTGC/GCAGTCTG
-50 +1
adult roots
MJL1
135
Figure 5.1. Gene expression comparison between juvenile and adult vegetative tissues. (A) Venn
diagram summarizing the number of differentially expressed genes between juvenile (V2) and
adult (V5) leaves or roots. The intersection represents the number of shared genes that are
differentially expressed genes in both leaves and roots before and after the juvenile-adult
transition. (B) Genes that are selectively expressed in V5 stage adult leaves.
136
Figure 5.2. GO annotation summary of genes showing differential regulation before versus after
the juvenile to adult transition. (A) GO annotation of genes up-regulated in juvenile leaves (V2)
compared to adult leaves (V5). The slice size is proportional to the significance of the p-value of
each annotation. (B) GO annotation of genes up-regulated in juvenile roots (V2) compared to
adult roots (V5) (seminal and nodal roots pooled). (C) GO annotation of genes up-regulated in
adult roots (V5) compared to juvenile roots (V2) (seminal and nodal roots pooled).
137
5.4.2.2 Juvenile versus adult roots
A total of 370 probes (208 genes) were differentially expressed between roots at the leaf
4/V2 stage compared to roots at the leaf 8/V5 stage (seminal and nodal roots pooled) (Figure
5.1A). Genes that were up-regulated in both juvenile and adult stage roots included those related
to tetrapyrrole and heme/iron binding (Figure 5.2B, C). Roots require the tetrapyrrole siroheme,
an essential co-factor for nitrite and sulfite reduction (Mochizuki et al., 2010). Genes that were
up-regulated only in juvenile-stage roots were related to oxido-reductive activities, known also to
be involved in nutrient uptake and assimilation (Figure 5.2B) (Dechorgnat et al., 2011). Genes
only up-regulated in adult-stage roots were related to antioxidant and oxidative stress responses
(Figure 5.2C), known to be involved in hormonal control of root development including auxin
regulation of the root apical meristem (De Tullio et al., 2004).
Two motifs were over-represented in the promoters of the genes that were up-regulated in
juvenile V2 expressed roots compared to adult roots; we have termed these, motifs of Maize
Juvenile Roots (MJR1-2; Table 5.1). Five motifs were over-represented upstream of genes upregulated in V5 roots compared to V2 roots, and we refer to these as motifs of Maize Adult
Roots (MAR1-5), with MAR1 and MAR2 having a similar AAAACAA core (Table 5.1).
5.4.2.3 Juvenile leaf and juvenile root promoter motifs have a shared core sequence
The two juvenile leaf promoter motifs (MJL1, MJL2) and the two juvenile root promoter
motifs (MJR1, MJR2) all share a GAA trinucleotide adjacent to a AGG trinucleotide (orange and
blue lettering, respectively; Table 5.1). Furthermore, the 7 bp core of MJL2 and MJR1 exactly
match one another (GAAAAGG, Table 5.1, underlined). This type of apparent motif sharing
might have been an artifact if many of the promoters used for juvenile and adult motif-retrieval
were the same (i.e. same genes expressed in both tissues); however, out of 34 and 88 promoters
138
used for juvenile leaf and root motif searches, respectively, only 3 genes were shared. This data
suggests that juvenile-selective promoters in maize roots and shoots may be activated by a
common family of transcription factors, suggesting root-shoot coordination of gene expression.
The MJL1,2 and MJR1,2 motifs (reversed: 7-10 G/A nucleotides) resembled the Motif 2
binding site of MADS-box transcription factor, FLOWERING LOCUS C (FLC) (Deng et al.,
2011). FLC is a key regulator of vegetative and reproductive transitions in Arabidopsis (Deng et
al., 2011). FLC binding site Motif 2 represented 39% of the 505 gene targets bound by FLC in
Arabidopsis, and was shown to be G/A rich (Deng et al., 2011). The MJL1,2 and MJR1,2 motifs
also resembled Motif1 of FLC and other MADS-box factors [CArG-box, consensus 5′CC(A/T)4NNGG-3′] which include APETALA (AP1,3 but not AP2) and AGAMOUS (Shiraishi
et al., 1993; Riechmann et al., 1996). It has been reported that a terminal AAA followed by GG
are highly conserved in the CArG box (Deng et al., 2011); this sequence was found in MJL1,
MJL2 and MJR1. The core of MJL1 (CTTCC) also exactly matched part of the MADS Agamous
transcription factor binding site AG301 (Shiraishi et al., 1993). This was of interest because an
APETAL1-like protein and a MADS box protein were associated with phase change in this study
(Table 5.2, see text below).
The MJL and MJR motifs also resembled the degenerate binding site of GT transcription
factors in plants called the GT element (Zhou, 1999). GT elements contain one or two G
nucleotides followed by four-five T or A nucleotides [5′-G-(A/G)-(T/A)-A-A-(T/A)-3′] (Zhou,
1999). When reversed, MJR1 contains the 6 bp binding site (GT-1consensus motif, GGAAAA)
for GT-1-like trihelix transcription factors, which have diverse functions in plants including
mediating dark/light cues and stress tolerance responses (e.g. involving salicylic acid) (Zhou,
1999). The core of MJR2 matches the GT-motif binding site (TGGTTT) of AtMYB2 (Hoeren et
139
al., 1998). GT-1 and GT-2 transcription factors are related to S1F factors (see below) and have
been shown to be expressed in both root and shoot (Villain et al., 1996), consistent with the motif
being detected in both juvenile root and shoot expressed promoters.
MJL and MJR motifs also matched additional promoter motifs from the literature. The
GAAAAG core sequence common to MJL2 and MJR1 were present in a 10 bp motif
(GAAAAGc/tGAA) responsible for gene expression in plant embryo suspensor tissues
(Kawashima et al., 2009). The core of MJL2 and MJR1 was identical to the pyrimidine box (Pbox, CCTTTT) that comprises one of the tripartite cis-acting elements required for gibberellin
(GA) responses, termed the GA responsive complex (GARC) (Skriver et al., 1991; Gubler and
Jacobsen, 1992; Rogers et al., 1994). The reverse sequences of MJL2 and MJR1 were also
identical to the cis-element (AAAAG) that binds Dof (DNA binding with one finger)
transcription factors implicated in numerous processes including carbon metabolism, light- and
leaf-regulated gene regulation (Yanagisawa and Sheen, 1998). Finally, the MJR1 core also
matched the NF-AT binding site (reversed, TTTTCC) in mammals (Tsytsykova et al., 1996).
These data suggest common G/A-rich promoter motifs help to coordinate root and leaf
gene expression associated with juvenility in maize.
140
Table 5.2: Probe sets differentially expressed in leaf and root tissues
Leaves
Probe
set
Description
(probe set similarity to
existing protein)
1
Apetala1-like protein
2
CER1 expressed
3
CER1 protein
4
5
Arabidopsis long chain
acyl-CoA synthetase 1
Putative rice protein
SHR5-receptor-like
kinase
6
No Description
7
No Description
8
hypothetical protein
9
m28 protein, LpMADS3
10
m28 protein, LpMADS3
11
12
13
14
Glossy1-like gene, rice
CER1 protein
Putative rice protein
SHR5-receptor-like
kinase
Putative rice protein
SHR5-receptor-like
kinase
Putative rice protein
SHR5-receptor-like
kinase
Probe homology to
protein found in maize
genome
GRMZM2G147716_P01
GRMZM2G066578_P01
GRMZM2G066578_P01
GRMZM2G101875_P02
Roots
Fold
change
(log2)
Average
expression
(log2)
P-value
Fold
change
(log2)
Average
expression
(log2)
P-value
7.46
7.86
2.14E-44
4.40
7.86
2.46E-37
3.71
7.29
2.35E-06
3.99
7.29
5.45E-15
3.32
6.62
1.21E-05
3.73
6.62
6.34E-15
-2.55
8.20
8.42E-09
-2.19
8.20
7.61E-13
6.36
7.06
5.52E-31
5.11
7.06
1.36E-35
2.22
8.56
9.15E-06
2.04
8.56
1.56E-10
2.57
5.60
0.000522
2.23
5.60
5.16E-07
2.48
7.13
0.000291
2.08
7.13
7.75E-07
5.52
7.78
6.61E-39
2.03
7.78
3.82E-17
6.93
9.87
3.78E-42
4.86
9.87
8.38E-42
3.85
6.66
2.50E-06
3.86
6.66
2.83E-13
7.07
5.93
4.69E-34
5.40
5.93
6.21E-37
6.87
5.61
4.30E-31
5.71
5.61
4.86E-37
6.23
4.96
9.29E-27
4.87
4.96
3.33E-30
GRMZM2G151567_P01
na
na
na
GRMZM2G147716_P01
GRMZM2G147716_P01
GRMZM2G066578_P01
GRMZM2G151567_P01
GRMZM2G151567_P01
GRMZM2G151567_P01
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5.4.2.4 Adult leaf and adult root promoter motifs have shared core sequences
Interestingly, the core of every promoter motif from the adult leaf-expressed (MAL) gene
cluster matched a core sequence in promoters of the adult root-expressed (MAR) gene cluster
(see shared coloured letters, Table 5.1). As with the results from juvenile tissues, this motif
sharing could have been an artifact caused by common genes being used for both juvenile and
adult motif-retrieval; however, out of 24 and 123 promoters used for adult leaf and root motif
searches, respectively, only 3 promoters were shared. This data suggests that related transcription
factors may regulate adult vegetative phase identity in both roots and shoots in maize.
The 5 bp core of MAL1 (AACAA) matched the core of MAR1 and MAR2 (green, Table
5.1). These sequences matched the AACA-box shown to bind a subset of MYB transcription
factors in plants, including MYB regulators of abiotic stress (MYBCORE, reversed CTGTTG)
and seed storage protein expression (AACAA or AACAAA) (Urao et al., 1993; Takaiwa et al.,
1996). This core motif also overlapped the sequence CAACA in MAL1 (with similar sequences
in MAR1 and MAR2) which binds the N-terminus of the AP2 transcription factor domain
(Kagaya et al., 1999). This result was of interest as an AP2-like transcription factor
(GLOSSY15) has been shown to regulate the juvenile-adult transition in maize leaf epidermis
(Evans et al., 1994; Moose and Sisco, 1996). The enlarged core of MAR1 and MAR2 (reversed,
TTTGTTT) also matched the 7 bp core binding site of FOX D3 [Forkhead box D3, consensus
A(a/t)T(a/g)TTTGTTT], a winged helix transcription factor family transcription factor in
animals required to maintain pluripotent stem cells during embryogenesis (Sutton et al., 1996).
MAL1 contains the internal 5 bp (TTGTT) of FOX D3. In general, TTTGTTT is associated with
many developmentally regulated promoters in animals (Sutton et al., 1996).
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The 5 bp core of MAL2 (CCACG) matched the core of MAR3 (purple, Table 5.1). This
core is identical to the binding site for bZIP proteins that require cooperative binding, such as
with NF-Y factors (e.g. UPR promoters, ERSE box) (Schindler et al., 1992; Yoshida et al., 2001;
Martínez and Chrispeels, 2003; Liu and Howell, 2010).
The 5 bp core of MAL3 (CCGTT) matched the core of MAR4 (light blue, Table 5.1).
This sequence, when reversed (AACGG) matched the core of the MYB transcription factor
binding site (MYB core) in plants (Planchais et al., 2002). In MAL3, this motif overlapped a
sequence similar to the anoxia inducible cis-element CCCCCG (Gupta and Goldwasser, 1996;
Mann et al., 2011).
Finally, the 5’ region of MAL1 (CATGC) and the 3’ region of MAR5 (ACTGC) weakly
resembled one another, and contained an ATG trinucleotide core (pink, Table 5.1). The MAL1
sequence is identical to the pentanucleotide core of the RY-motif (g/c)CATGCxx(g/c) in plants
which mediates developmental gene expression (Hoffman and Donaldson, 1985; Bobb et al.,
1997). In MAR5, the CATGC core overlapped the recognition site (CAGAC) of the Smad
transcription factor family in the TGFß signalling pathway (Dennler et al., 1998; Pais et al.,
2010). Intriguingly, a Smad-interacting protein (DAWDLE, containing a Forkhead Associated
Domain) has recently been characterized in Arabidopsis and is involved in the biogenesis of
miRNAs; this is of interest because parallel regulators (Serrate, Hasty) of miRNA processing
affect juvenile to adult phase change in plants (Yu et al., 2008). Finally, MAR5 was related to an
ABA responsive motif (ABRE motif III) (Shen et al., 2004).
It is noteworthy that MAR1, MAR2 and MAR5 all had putative associations with
Forkhead transcription factors. It may be that one or members of this family play an important
regulatory role in adult roots in maize.
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These results suggest that related MYB and bZIP transcription factors, and possibly AP2,
Forkhead and RY motif binding proteins, regulate adult stage gene expression in maize roots and
leaves. The existence of multiple binding protein matches to each of our retrieved motifs may
simply be an artifact of probability, or may reflect cooperative regulation, for example different
transcription factors that respond to developmental age compared to organ type.
5.4.2.5 Shared phase change genes associated with juvenility or adulthood
A total of 14 shared probe sets representing 12 genes were differentially expressed in
both adult leaves and adult roots compared to juvenile leaves and roots, respectively (Figure
5.1A; Table 5.2). These genes may thus be critical for vegetative phase change as their
expression is based on developmental phase rather than organ type. This shared list of genes
included at least two genes putatively linked to wax biosynthesis (Table 5.2). In maize,
differences in epicuticular wax are used as visual markers to distinguish juvenile from adult
leaves (Poethig, 1990). During the early steps of wax biosynthesis, C16 and C18 long-chain fatty
acids are synthesized in plastids, and they are subsequently mobilized to the cytosol where they
are activated by co-enzyme A by a long chain acyl-CoA synthetase (CER8 in Arabidopsis) (Lü
et al., 2009). Later, long-chain acyl-CoAs can be modified to alkanes perhaps by CER1 in
Arabidopsis, a putative aldehyde decarbonylase (Aarts et al., 1995; Sturaro et al., 2005; Lü et al.,
2009). One of the differentially expressed probes matched a long chain acyl-CoA synthetase
while three probes matched CER1, of which one was annotated as Glossy 1 in maize (probe set
11, Table 5.2). Glossy1 is an ortholog of Cer1; GLOSSY1 is active in juvenile leaves but not in
adult leaves, and a mutation in GL1 causes the adult wax phenotype in juvenile leaves in maize
(Sturaro et al., 2005). To our knowledge, a change in wax composition has not previously been
noted during the juvenile to adult transition in maize roots. However, leaf wax biosynthesis
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pathway enzyme GL8 was reported to be expressed also in maize roots (Xu et al., 1997).
Therefore, our data predicts that the juvenile to adult vegetative transition in maize involves
coordinated changes in epicuticular wax gene expression in both roots and shoots, a novel
finding.
Among probes corresponding to regulatory genes that were regulated by developmental
phase rather than organ type were: an SHR5-receptor-like kinase; an APETALA1-like protein;
and a MADS box protein orthologous to MADS3 in Lolium perenne shown in Table 5.2
(Petersen et al., 2004). The APETALA (AP) and MADS box proteins are known to play
significant regulatory roles during plant development (Bommert et al., 2005). As noted above,
motifs moderately resembling the binding sites of AP/MADS-box proteins were overrepresented in gene expression clusters in this study.
5.4.3 Pre-flowering versus post-flowering
During the beginning of the reproductive stage, maize plants start to shift their resources
away from vegetative growth to remobilizing nutrients (e.g. from senescing leaves) for
reproductive development. Gene expression patterns in expanding lower leaves during preflowering stages (growing coleoptile, growing juvenile leaves, and growing adult leaf 8) were
compared to fully expanded, higher leaves after flowering (leaves above the ear, 15 cm to tip).
Gene expression in the corresponding roots were also compared. Clear differences in gene
expression patterns were found (Figures 5.3, 5.4).
5.4.3.1 Growing pre-flowering leaves versus mature post-flowering leaves
The leaf results integrated changes caused by the floral transition (pre- versus postflowering), the position of the leaf on the stalk (lower versus higher), as well as the metabolic
age of the leaves (growing versus expanded). A total of 4936 probes, representing 9.1% of the
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probes expressed (in at least one of the 50 tissues of the complete microarray data set), were
differentially expressed in expanding lower leaves during juvenile/adult stages compared to
fully-expanded higher leaves during reproductive development: 2409 probes were up-regulated
in growing lower leaves while 2527 probes were up-regulated in expanded, higher leaves (Figure
5.3A). Genes associated with small conjugating protein ligase activity, required for ubiquitinmediated protein degradation, were over-represented in mature leaves during reproductive stages
(Figure 5.3B), consistent with senescence and/or nutrient scavenging.
A subset of the differentially expressed probes (100 probes with the highest p-values,
representing 47 genes) was used to search for over-represented promoter motifs. One motif,
which we refer to as a motif of Maize Old Reproductive Stage Leaves (MORSL1, consensus
ACCATT) was associated with promoters that were up-regulated in higher leaves during
reproductive stages (Figure 5.3C). This motif matched the core of the S1F binding site
(CCATG/CCATT/CCATT) conserved in many plastid related genes (Zhou et al., 1992), and
exactly matched the S1F1 site (-160 bp) in the nuclear-encoded plastid ribosomal protein L21
gene (Lagrange et al., 1997). The S1F1 motif appears to mediate repression of genes required for
photosynthesis in non-photosynthetic tissues (Villain et al., 1994), consistent with photosynthesis
being repressed in older leaves compared to young growing leaves. This interpretation is also
consistent with an earlier study showing that the largest class of genes up-regulated in juvenile
leaves compared to leaf 9 (adult leaves) was associated with photosynthesis (Strable et al., 2008).
In lower, pre-flowering growing leaves, GO annotations showed that genes associated
with various biosynthetic activities were over-represented, including cellulose biosynthesis and
iron scavenging (enterobactin biosynthesis), along with genes involved in microtubule
movement (Figure 5.3D). Growing tissues are dependent on membrane trafficking and
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cytoskeleton reorganization to permit cell growth and division (Jürgens, 2004; Hussey et al.,
2006). These results are consistent with gene expression directed towards leaf growth.
A subset of the differentially expressed probes (100 probes with the highest p-values,
representing 65 genes) was used to search for over-represented promoter motifs associated with
gene expression in lower, growing leaves at pre-flowering stages. A motif which we refer to as a
motif of Maize Young Lower Leaves (MYLL1, consensus GGAACG), was over-represented in
the promoters of genes that were up-regulated in lower, growing leaves (Figure 5.3E). A
literature search suggests that this motif has not been identified in plants; however when reversed
(CGTTCC), it exactly matches a putative cis-element over-represented in the promoters of the
yeast transcription factor family YAP, a member of the bZIP family which is abundant in plants
(Fernandes et al., 1997; Kiełbasa et al., 2001).
5.4.3.2 Pre-flowering versus post-flowering roots
Only 94 probes (80 genes) were down-regulated in juvenile/adult roots (Ve-V5 stage,
seminal and nodal roots combined) compared to roots of reproductive stage shoots (Figure
5.4A). No genes with an inverse expression pattern were identified (IUT test, data not shown).
An unusual feature of the down-regulated pre-flowering root cluster was an overabundance of genes linked to mitochondrial transport as well as ATP/GTP-dependent helicase
activity (Figure 5.4B). RNA helicases remodel RNA and RNA-protein complexes involved in
ribosome biogenesis, mRNA splicing and export, translation and degradation (Linder and
Jankowsky, 2011). DEAD-box RNA helicases have been implicated in helping to mediate root
responses to potassium (K+) and iron (Fe) (Ricachenevsky et al., 2010; Xu et al., 2011).
Two motifs, which we refer to as motifs of Maize Old Reproductive Stage Roots
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Figure 5.3. Gene expression comparison between pre-flowering, growing leaves and postflowering, mature leaves. (A) Relative gene expression heatmap summary. Each heatmap row
indicates an array probe set, and the relative expression of each gene ranges from low (yellow) to
high (dark blue). (B) GO annotation summary of genes up-regulated in post-flowering, mature
leaves. (C) Sequence logo showing the most significant over-represented motif in the promoters
of genes up-regulated in post-flowering mature leaves. (D) GO annotation summary of genes
up-regulated in pre-flowering, growing leaves. (E) Sequence logo showing the most significant
over-represented motif in the promoters of genes up-regulated in pre-flowering growing leaves.
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(MORSR) were over-represented in the promoters of genes that were down-regulated in preflowering roots (juvenile and adult) but up-regulated in reproductive stage roots:
G(g/c)GTGATT (MORSR1) and GGGCCNG (MORSR2) (Figure 5.4C). When reversed, the
core of MORSR1 matched the CACCC box which binds an uncharacterized protein in the
promoters of maize histone genes (Brignon and Chaubet, 1993). In Drosophila and mammals,
CACCC elements bind Kruppel-like zinc fingers involved in cell proliferation and death,
differentiation and development (Pearson et al., 2008). The core of MORSR2 was identical to the
SORLIP2AT cis-element (Sequences Over-Represented in Light-Induced Promoters, GGGCC)
which was computationally identified based on its high frequency in the promoters of
phytochrome A-induced genes in Arabidopsis (Hudson and Quail, 2003).
These results demonstrate that the floral transition above ground has an affect below
ground, albeit limited, as reflected by differential gene expression clusters and the retrieval of
distinct over-represented promoter motifs associated with gene expression in roots before and
after flowering.
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Figure 5.4. Gene expression comparison between pre-flowering and post-flowering roots. (A)
Relative gene expression heatmap summary. Each heatmap row indicates an array probe set, and
the relative expression of each gene ranges from low (yellow) to high (dark blue). (B) GO
annotation summary of genes up-regulated in post-flowering roots. (C) Sequence logo showing
the most significant over-represented motifs in the promoters of the genes up-regulated in postflowering roots. Matches to previously identified motifs (Similar to) along with the similarity
score (E-value) are indicated.
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5.5 Study limitations, significance and summary
The goal of this study was to identify cis-acting promoter motifs responsible for gene
expression in leaves and roots before and after the juvenile-to-adult transition, and before and
after the floral transition. A limitation of this study was that it was sometimes difficult to match
an array probe to a single gene, due to the existence of paralogs. The maize genome is duplicated
and contains large gene families (Schnable et al., 2009). As the genes were used to define the
promoters used for motif searching, a subset of the promoters used for this purpose were likely
incorrect, which would have reduced the strength of the consensus motif signal.
One interesting result was that only 8% and 3% of array probes were selectively
expressed in juvenile leaves and roots, respectively, compared to later stages. We found five
probe sets that were specifically expressed in leaf 8 at the V5 stage, and were not expressed in
leaf 8 at any other stage of development, nor in other vegetative tissues. This result offers hope
for organ and phase-specific targeting of gene expression in maize. A surprising result was that
all the over-represented juvenile leaf promoter motifs as well as the juvenile root promoter
motifs shared common sequences. Furthermore, promoter motif cores from the adult leafselective cluster were identical to motif cores present in the adult root-selective cluster,
suggesting transcription factors with the same DNA binding domains regulate vegetative phase
identity in both roots and shoots. These predictions will require experimental confirmation.
When comparing juvenile to adult gene expression clusters, common genes were differentially
expressed in both leaves and roots which was also unexpected. Included on this latter list were
genes involved in wax biosynthesis, only previously thought to be a trait associated with phase
change in leaves, as well as three regulatory genes including an APETALA1-like gene and a
MADS-box gene, which should be of significant interest for future research. With respect to
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comparisons made of gene expression in pre-flowering growing leaves lower on the plant to
post-flowering mature leaves higher up the plant, GO annotations appeared to reflect the age of
the leaves (growing versus mature/senescing). Clear and distinct over-represented promoter
motifs were found in these comparisons both above ground and below ground.
All of these results help to clarify how phase change is regulated at the whole plant level
in maize and identifies new markers for maize development. Once validated, the overrepresented motifs from this study should assist in the design of novel promoters for targeted
gene expression in maize. Finally, the only gene that was differentially expressed between all of
the above transitions was Wax synthase isoform 1 (GRMZM2G013357) previously shown to be
involved in seed phytosterol synthesis (Zou and Chen, 2010).
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6. Spatio-temporal gene expression and cis-acting promoter motifs
associated with nitrogen transporter and assimilation genes in
maize (Zea mays L.)
Author contributions: Christophe Liseron-Monfils conducted all microarray and bioinformatics
analyses. Plants were grown by Wenqing Wu and Tara Signorelli (Steven Rothstein`s laboratory,
University of Guelph). RNA extraction was led by Yong-Mei Bi (Steven Rothstein`s laboratory,
Guelph). Part of the annotation of the microarray was done by Gregory Downs (Lewis Lukens`
laboratory, University of Guelph). The array hybridizations were performed by Xi Chen and
Eddie Bondo at Syngenta Biotechnology Inc. (Research Triangle Park, North Carolina, 27709,
USA).
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6.1 Abstract
Nitrogen is considered the most limiting nutrient for maize (Zea mays L.), but there is
limited understanding of the regulation of nitrogen-related genes during maize development. A
custom Affymetrix 82K maize array was used to analyze the expression of 65 nitrogen uptake
and assimilation probes in 50 maize tissues from seedling emergence to 31 days after pollination.
Four nitrogen-related gene expression clusters were identified in roots and shoots corresponding
to, or overlapping, juvenile, adult and reproductive phases of development. Though these phases
have been used to characterize shoot development, our data suggests they may have an impact on
the root transcriptome. Surprisingly, expression of nitrogen-related genes was consistently high
in anthers. The promoters corresponding to each gene expression cluster were screened for overrepresented cis-acting elements. The 8 bp core of a recently identified 43 bp nitrogen response
element (NRE-43) from the promoter of Arabidopsis NiR1 (Nitrite Reductase 1), was overrepresented in promoters of genes encoding nitrate (Nrt1, Nrt2.1) and ammonium transporters,
suggesting this motif is critical across angiosperms. This conserved motif, herein referred to as
NRE/Acore (NRE-43 angiosperm core motif), was over-represented in genes highly expressed
during early root and leaf development. Interestingly, each expression cluster was associated
with distinct cis-acting promoter motifs, including motifs previously shown to mediate responses
to carbon availability. We report expression of putative orthologs of nitrite transporters (NiTR1),
a transporter not previously reported in maize, in early and late-stage leaves. These results
demonstrate tissue-selective and developmental stage-selective regulation of expression of
nitrogen-related genes in maize.
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6.2 Introduction
Plants have evolved multiple strategies to cope with wide variation in concentrations of
soil nitrate and ammonium (Crawford and Glass, 1998; Gaudin et al., 2011; Kant et al., 2011).
For example, at low external nitrogen, plants employ high affinity nitrogen transporters, while
low affinity transporters are used when external nitrogen is high (Crawford and Glass, 1998). To
allow for fine-tuned control, plants have evolved transporter paralogs that perform similar
functions but in different tissues, to facilitate nitrogen uptake from soil, xylem loading from roots
for transport to shoot tissues, unloading in shoot organs and storage in vacuoles (Dechorgnat et
al., 2011). For example, the Arabidopsis genome encodes at least 67 nitrate transporters,
including 53 Nrt1 genes, 7 Nrt2 genes and 7 AtClc (chloride channel) genes (Forde, 2000;
Dechorgnat et al., 2011). Nitrogen demand also changes throughout plant development (Peng et
al., 2010). Part of this changing plant demand is met by scavenging nitrogen from senescing
tissues, requiring additional intra-plant nitrogen transport (Masclaux-Daubresse et al., 2010).
Plants also coordinate nitrogen assimilation with energy availability, as the conversion of nitrate
to ammonium alone consumes 12-26% of the primary photosynthetic reductant (Noctor and
Foyer, 1998). In maize (Zea mays L.), significant gaps remain in characterizing the regulation of
nitrogen uptake and assimilation genes in different tissues and at different stages of development.
With respect to nitrogen transporters in maize, at least two genes encoding low affinity
nitrate transporters (ZmNrt1.1, ZmNrt1.2) and three genes encoding high affinity nitrate
transporters (ZmNrt2.1, ZmNnrt2.2, ZmNnrt2.3) have been reported (Quaggiotti et al., 2003;
Quaggiotti et al., 2004; Schnable et al., 2009; Gaudin et al., 2011). NRT2 requires interaction
with co-transporter NAR2 (NRT3) proteins to be functionally active (Orsel et al., 2002;
Okamoto et al., 2006; Yong et al., 2010). The maize genome encodes at least two NAR2-
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encoding genes (ZmNar2.1, ZmNar2.2) (Gaudin et al., 2011). In higher plants, a chloroplastlocalized nitrite transporter (CsNitr1-L) was reported in cucumber, with a functional ortholog in
Arabidopsis (Sugiura et al., 2007) but none have been reported in maize. The genomes of higher
plants have been reported to encode up to 14 ammonium transporter paralogs (AMT1 family),
with the highest affinity transporters (AMT1;1; AMT1;3; AMT1;5) typically localized to root
hairs and outer root cells, and the lower affinity transporter(s) (AMT1;4) located in the root
endodermis (Masclaux-Daubresse et al., 2010). In Arabidopsis, at least five gene families have
been reported to transport amino acids and peptides, some of which also transport inorganic
nitrogen (Masclaux-Daubresse et al., 2010).
With respect to nitrogen assimilation, higher plants directly assimilate ammonium into
glutamate (Masclaux-Daubresse et al., 2010). By contrast, nitrate is first converted to nitrite in
the cytoplasm by nitrate reductase (NR), followed by reduction to ammonia in plastids by nitrite
reductase (NiR) (Masclaux-Daubresse et al., 2010). Ammonium is fixed onto glutamate to form
glutamine by glutamine synthetase (GS; Gln gene family), of which a plastidic isoform (GS2)
and a cytosolic isoform (GS1) exist. A single gene in maize encodes GS2 (Gln2) whereas at least
five genes encode GS1 (Gln1-1 to Gln1-5) which are differentially expressed during
development (Sakakibara et al., 1992; Martin et al., 2006). Glutamine can also react with 2oxoglutarate to form two molecules of glutamate via glutamine 2-oxoglutarate amino transferase,
also called glutamate synthase or GOGAT (Suzuki and Knaff, 2005). Plants have two types of
GOGAT enzymes, NADH-GOGAT and Fd-GOGAT, which use NADH and ferredoxin as
electron donors, respectively (Suzuki and Knaff, 2005). Different GOGAT paralogs show
constitutive or tissue specific gene expression in plants, including in maize (Sakakibara et al.,
1992; Suzuki and Knaff, 2005). Following nitrogen assimilation, glutamine and glutamate, other
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amino acids including asparagine and aspartate, and inorganic nitrogen, are transported by
vascular tissues to growing organs (Masclaux-Daubresse et al., 2010).
Plant development above ground has been divided into distinct developmental phases
based on characteristics including leaf shape, surface wax, the presence of trichomes and
underlying genetic networks (Poethig, 1990, 2010). In maize, the juvenile vegetative phase (V) is
from seedling emergence (Ve) to the formation of leaves 4 to 6 (V2 stage), which is followed by
the adult vegetative phase (here ≥V5). Flowering initiates the reproductive phase (R), which
includes seed formation, the latter divided into stages based on the number of days after
pollination (DAP). Much less information has been reported on whether these phases have any
importance in categorizing root development.
Here we characterized the global expression pattern of nitrogen transport and assimilation
genes during maize development. Our results suggest that both maize leaves and roots exhibit
distinguishable expression clusters of nitrogen related genes corresponding to juvenile, adult and
reproductive phases. Each expression cluster is also associated with distinct cis-acting promoter
motifs.
6.3 Materials and Methods
6.3.1 Plant growth and tissue harvest
As indicated in Chapter 4, Syngenta hybrid SRG150 seeds were grown in a greenhouse
during the summer of 2007 at the University of Guelph, using the following conditions: 16 h
light (~600 µmol m-2 s-1 ) at 28˚C, 8 h dark at 23˚C, and 50% relative humidity. Plants were
grown semi-hydroponically in pots containing Turface® clay, watered with a modified
Hoagland’s solution containing: 0.4 g/L 28-14-14 fertilizer, 0.4 g/L 15-15-30 fertilizer, 0.2 g/L
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NH4NO3, 0.4 g/L of MgSO4•7H2O and 0.03 g/L of micronutrient mix (S, Co, Cu, Fe, Mn, Mo
and Zn). Three biological replicates per tissue/stage were harvested, always at ~11 am.
6.3.1 Microarray analysis
RNA isolation and microarray analysis was previously described in detail as indicated in
Chapter 4. RNA was isolated from 50 tissues/stages (three biological replicates) and hybridized
onto customized maize Affymetrix 82K Unigene arrays (Wagner and Radelof, 2007). Array
expression was normalized using the RMA method (Irizarry et al., 2003) from Bioconductor
(Gentleman et al., 2004), and analyzed for tissue selective gene expression using the Intersection
Union Test, also named IUT (Berger and Hsu, 1996) using R coding modified from
http://ppw.kuleuven.be/okp/software/BayesianIUT/ (Van Deun et al., 2009). Multiple testing was
corrected using Sidak’s adjustment, equivalent to Bonferroni’s correction (Sidak, 1967). To
compare juvenile tissues (Ve-V2 stage leaf/root) to adult tissue (V5 stage), a linear model was
fitted to the data using the Limma Package from Bioconductor (Smyth, 2005), adjusted using the
empirical Bayesian method, and corrected for multiple testing using the Benjamini-Hochberg
method (Benjamini and Hochberg, 1995), with the p-value set at 0.05.
6.3.2 Annotation and clustering of nitrogen related genes
Clustering was conducted using K-means clustering (Hartigan and Wong, 1979). Array
probes corresponding to nitrogen-related genes were retrieved using three methods. First, as the
probes were designed from the maize Unigene set, the corresponding original Genbank sequence
were used to retrieve matches, using nucleotide BLAST against the B73 maize genome
(MaizeSequence.org, release 4a.53). Probe sets with no expression (relative expression < 100) in
any of the 150 microarray experiments were removed from the annotation (26,989 probe sets).
Each probe set consisted of 16 probes of 25 nucleotides each. If 75% of the probes in the probe
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set (12/16) matched the same gene model, the probe set was identified as a match for that gene.
If only 12% - <75% of the probes in the probe set (1/16-11/16) matched the same gene model,
the probes were considered as a partial match for that gene. A probe was required to have 85%
sequence identity with the gene model to be considered as a valid match of that gene. A total of
33,664 probe sets matching to unique gene models were mapped using these steps. Exonerate
alignment (Slater and Birney, 2005) was used to annotate an additional 9,919 probes. Nucleotide
BLAST was not successful in identifying EST matches because of the biases created by gene
model issues related to gene-calling software (GeneBuilder or FGENESH). The remaining
12,089 probe sets on the array showed expression, however did not map to the maize genome.
After the elimination of the probe sets that showed no expression, cross-hybridization or
redundancy, there were 22,787 high-quality annotated probes. Additional methods were used.
Specifically, the array probe sequences were re-screened for matches with EST sequences from
NCBI using BLAST. Finally, nitrogen uptake and assimilation keywords were used to search
gene annotations and protein domains in the B73 maize genome from MaizeSequence.org, and
the search results were each matched to a Genbank protein with the highest homology with the
microarray probe set.
6.3.3 Promoter motif discovery
Microarray probes were matched to known genes from the filtered B73 maize gene set
from MaizeSequence.org as previously described in Chapters 4 and 5. Over-represented de novo
motifs present in the promoters (-500 to +1 region) of the genes within each expression cluster
were then searched using a Perl-based motif discovery program developed for the maize genome,
called Promzea (see Chapter 3.3, Materials and Methods section). Promzea filtered and
combined results from three motif discovery tools: Weeder (Pavesi et al., 2007), MEME (Bailey
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and Elkan, 1994) and BioProspector (Liu et al., 2001), and performed additional validation tests
as shown. Retrieved motifs were matched to previously defined motifs using Athamap (Bülow et
al., 2009) and PLACE (Higo et al., 1999) using STAMP software (Mahony and Benos, 2007).
Promzea predicted motifs ≥ 6 bp.
6.4 Results
6.4.1 Tissue and developmental stage selective expression
RNA was collected from 50 tissues from the seedling emergence stage to 31 days after
pollination (DAP; Table 6.1) and hybridized onto customized maize Affymetrix 82K Unigene
arrays (Wagner and Radelof, 2007). A total of 65 nitrogen uptake and assimilation array probes
were analyzed. The expression patterns from all 50 tissue samples is summarized (Figure 6.1). In
reproductive tissues, the highest nitrogen-related expression was observed in anthers (Figure
6.1). Interestingly, probes corresponding to nitrite transporters (NiTR1) (Sugiura et al., 2007), a
gene class not previously reported in maize, were expressed (Figure 6.2; Figure 6.1). In
vegetative tissues, four nitrogen-related gene expression clusters were detected (Figure 6.2).
Cluster 1 probes showed juvenile-selective expression, with peak expression in early juvenile
stage roots (Ve-V2) and vegetative stage leaves (Ve-V5). Cluster 1 probes matched genes
encoding a high affinity transporter NRT2.1, the low affinity transporter NRT1.1, and
ammonium transporters. Cluster 2 probes were leaf-selective and more highly expressed in
vegetative stage leaves (juvenile and adult: Ve-V5) than post-flowering leaves (R1-R31). Cluster
2 probes matched low affinity nitrate transporters including NRT1.5, nitrite transporter NiTR1,
and nitrate reductases (NR1, NR2). Cluster 3 probes were root selective and were expressed
throughout development (juvenile to post-flowering). Cluster 3 probes matched genes encoding
glutamine synthetases including Gln4/Gln1-4 and Gln5/Gln1-5 as well as several glutamate
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synthases (Figure 6.2). Also included in Cluster 3 were ammonium transporters, the low affinity
transporter NRT1.1, and the companion protein (NAR2.1) of the high affinity nitrate transporter
complex. Finally, Cluster 4 probes were leaf selective and showed the most consistent expression
in older leaves at later stages of development (adult to post flowering: V5-R31). Several Cluster
4 probes matched genes encoding nitrate reductase (NR1) and nitrate transporters, as well as one
NAR2 paralog and the nitrite transporter NiTR1 (Figure 6.2).
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Table 6.1. Detailed description of developmental stages and tissues sampled.
developmental
number of visible
tissue/organ
stage
detail of the harvested sample
leaves
VE
leaf
0
coleoptile
VE
seminal root
0
root
V1
leaf
2
1st & 2nd leaf
V1
seminal root
2
root
V2
seminal root
4
seminal root
V2
nodal root
4
nodal root
V2
stalk
4
stalk
V2
leaf
4
leaf (actively growing leaf--- 4th leaf)
V4
tassel
6
1mm tassel meristem & 1mm uppermost
stem below tassel
V5
seminal root
8
seminal root
V5
nodal root
8
nodal root
V5
stalk
8
stalk below tassel (2cm)
V5
leaf
8
V5
tassel
8
tassel 3-5mm
V7
ear
12
tassel 2cm
V7
tassel
12
top ear shoot
V8~V9
tassel
13~14
tassel 12~14 cm
V8~V9
ear
13~14
top ear 3~5mm
leaf (actively growing leaf--- 8th leaf, 15cm
including tip)
162
Table 6.1 (continued)
V10~V11
tassel
15~16
top 10cm of tassel (~20cm)
V10~V11
ear
15~16
top ear 1~1.5cm
V13~V15
tassel
15~16
spikelet of tassel (~22cm)
V13~V15
ear
15~16
top ear 3~3.5cm
V15~V16
floret
15~16
top ear(5cm) floret
V15~V16
cob
15~16
top ear (5cm)cob
V15~V16
silk
15~16
top ear (5cm)silk
V15~V16
tassel
15~16
spikelet of tassel (top 10cm)
VT
anthers
15~16
anther
R1
ovule
15~16
R1-ovule of top ear
R1
cob
15~16
R1-cob of top ear
R1
silk
15~16
R1-silk of top ear
R1
husk
15~16
R1-most inner husk of top ear
R1
leaf
15~16
R1-15cm tip of 2nd leaf above top ear
R1
nodal root
15~16
R1-adult root
R1
stalk
15~16
R1-15cm stalk below tassel
5DAP
ovule
15~16
ovule of top ear
5DAP
cob
15~16
cob of top ear
10DAP
embryo
15~16
embryo of top ear
10DAP
endosperm
15~16
endosperm of top ear
10DAP
leaf
15~16
15cm tip of 2nd leaf above top ear
163
Table 6.1 (continued)
17DAP
embryo
15~16
embryo of top ear
17DAP
endosperm
15~16
endosperm of top ear
17DAP
pericarp
15~16
pericarp of top ear
17DAP
leaf
15~16
15cm tip of 2nd leaf above top ear
24DAP
leaf
15~16
15cm tip of 2nd leaf above top ear
24DAP
nodal root
15~16
root
24DAP
pericarp
15~16
pericarp of top ear
24DAP
embryo
15~16
embryo of top ear
24DAP
endosperm
15~16
endosperm of top ear
31DAP
leaf
15~16
15cm tip of 2nd leaf above top ear
31DAP
embryo
15~16
embryo of top ear
164
Figure 6.1. Relative expression of nitrogen-related genes across vegetative and reproductive
tissues. The heatmap shows the expression of nitrogen-related genes expression in vegetative and
reproductive tissues from the seedling emergence stage to 31 days after pollination (DAP). Each
row represents an array probe. The relative expression levels of the probes range from low
expression (yellow) to high expression (dark blue). See Table 6.1 for a detailed description of
developmental stages, tissues sampled and abbreviations.
165
166
Figure 6.2. Heatmap showing relative expression of nitrogen-related genes in root and leaf
tissues at different developmental stages. Each row represents a unique array probe. The relative
expression level of each probe ranges from low expression (yellow) to high expression (dark
blue). V1-V5 stages refer to the number of visible stem-leaf nodes. Tissue sampling was as
follows: Ve leaf: coleoptile tissue; V1 leaf: leaves 1 and 2; V2 leaf: actively growing leaf 4; V5
leaf: actively growing leaf 8, 15 cm from the tip; R1-R31 leaf: second leaf above top ear, 15 cm
from the tip; V1-V5 sroot: seminal root from vegetative stages; V2-V5 nsroot: nodal root (crown
root) from vegetative stages; R1-R24 nroot: nodal root (crown root) from reproductive stages.
Abbreviations: V, vegetative pre-flowering stage; R, reproductive post-flowering stage; nDAP,
days after pollination. Refer to Supplemental Files for additional details.
167
168
Over-represented cis-acting promoter motifs.
Four over-represented motifs were present in the promoters of the nitrogen-related genes
expressed in Cluster 1 (early root/leaf cluster), of which three were similar to previously
identified cis-acting elements (Table 6.2). Interestingly, one Cluster 1 motif was very similar to
the core of the 43 bp pseudo-palindromic nitrogen response element [43 NRE core,
(t/c)GACcCTT] recently identified in dicot nitrite reductase (NiR) genes and shown to be
necessary and sufficient for nitrate-responsive gene transcription (Konishi and Yanagisawa,
2010). Within Cluster 1, this 8 bp motif (consensus CGACCCTT ) was over-represented in the
promoters of genes encoding nitrate transporters (Nrt1, Nrt2.1) and ammonium transporters
(Table 6.3).
The second Cluster 1 element was similar to the G-box 10 element and the E-Box (Table
6.2). The G-box 10 element was first characterized in tobacco (Nicotiana tabacum) and shown to
confer near-constitutive gene expression in roots, leaves, seeds and some reproductive tissues
(Ishige et al., 1999). The core of the G-box 10 element is identical to the E-box motif
(CANNTG) recently shown to be critical for nitrate induction of the Nia1 (nitrate reductase)
promoter in Arabidopsis (Wang et al., 2010). The third Cluster 1 element, NRG1 (Negative
Regulator of Glucose-repressed Genes 1), was discovered in yeast upstream of genes involved in
regulating cell sugar status (Park et al., 1999; Zhou and Winston, 2001). There were two overrepresented motifs in the promoters of Cluster 2 (early leaf cluster): LTRE (low temperature
responsive element) and YAP1. The core of the LTRE element, also called C/DRE, mediates
ABA-independent responses to cold, amplified by light via phytochrome signalling (Kim et al.,
2002). The YAP1 element was first identified as the binding site of the yeast YAP1 protein, a
conserved protein across eukaryotes including Arabidopsis (Babiychuk et al., 1995). YAP1 was
169
shown to regulate the yeast cell cycle in response to oxidative stress, but also able to regulate cell
elongation (Moye-Rowley et al., 1989; Carmel-Harel et al., 2001; Yokoyama et al., 2006).
Another over-represented motif was detected in the promoters of Cluster 3 genes (root cluster),
similar to the binding site of the Forkhead (FHL1) transcription factor in yeast, a repressor of
ribosome-encoding genes during glucose starvation (Hermann-Le Denmat et al., 1994). Finally,
one previously unidentified motif was found in the promoters of Cluster 4 genes (late leaf
cluster) with the consensus NANGAG (Table 6.2).
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Table 6.2. Promoter cis-acting motifs over-represented in the nitrogen-related genes expressed
during maize development at different stages/tissues.
Cluster
Motif Logo
Consensus
Preferential
position
Similarity
E-value
Alignment
CGACCNTT
-50 +1
NRE
core
2.26E-09
CGA C CNT T
Y GA C C C T T
CCACGTGC
-300 -250
G-BOX 10
reverse
8.78E-11
CACGCCRCAG
-250 -200
/
/
NNANGCSGCW
-50 +1
NRG1
reverse
6.23E-07
AGTCGG
-500 -450
-350 -300
LTRE
6.88E-07
TAGYCRGC
-250 -200
YAP1
6.73E-07
TRTCCGTACG
-350 -300
FHL1
1.19E-06
/
/
1
2
3
4
NANGAG
-500 -450
/
/
Gene expression clusters correspond to Figure 6.2. The most common position(s) of the motif in
the -500 bp promoter region is indicated (Preferential position). Matches to previously identified
motifs in promoter databases are identified (Similarity) along with the similarity score (E-value)
and alignment to the match (Alignment). Only the most over-represented motifs are shown.
Abbreviations: N=any nucleotide, Y=C/T, R=A/G , S = G/C, W=A/T.
171
Table 6.3: NRE/Acore motifs detected in nitrogen-related promoters from gene expression
Cluster 1
NRE/ACore
Maize annotation
Identity
Description
Downstream nucleotides
motif
percentage
high affinity nitrate transporter
-319
TGATCCTT
-313
GGCTGATCCCACGGGATGAGGCCAAGCCCA
93.24%
(nrt2.1)
-53
CGACCCTT
-47
CATGTCCATGACACGCCAGAGCTCAATCTT
100.00%
nitrate and chloride transporter
-424
CGACCTTT
-418
ATGATTTTGGGTCTTCTTTTTGAAAACGAA
96.65%
-292
CGACCCTT
-286
TTGCCGTGCGCTGCTCGAGTCTGCCTAACC
100.00%
-223
CGTGCCTT
-217
CCGTTTTAGGTTTGATTCGTCGACTTGAAT
90.03%
-95
CGACCATG
-89
TTCTTGTCATCTCTTCAGAACAGTCTGAAG
91.12%
-493
CCACCGTT
-487
AGATCGGTCACCAGGTCATAGTCCACCATG
91.12%
-303
CGATCGTT
-297
CGTCGGGCGATTGTTTATCCCCGGACTAAA
95.61%
-208
CGACACTT
-202
TATTGTAATTTTGGACTAGTCTCTCTTTTT
94.29%
-146
CGATCTTT
-140
CTACAGTGCAAGATAATAATGGAGTATCTC
95.61%
-169
CGGCCCTG
-163
GGATCCTGGCCACCGTGGGTGGGCAGATTC
90.67%
-111
CGATCCGT
-105
TGTTTGTTTTGCCGAATCAAAACTGCAATT
93.24%
-160
CGATCCTT
-154
CTCTTCTCTCCTAGAGCCACTCACCGGCGC
98.95%
GRMZM2G010280
GRMZM2G453320
GRMZM2G080045
GRMZM2G082343
GRMZM2G028736
GRMZM2G175140
ammonium transporter
symbiotic ammonium transporter
ammonium transporter (Osamt1.3)
ammonium transporter(Osamt1.1)
ammonium transporter (Osamt2.2
GRMZM2G335218
;Osamt3.1;Osamt5.1)
maize transporter consensus
CGACCCTT
dicotyledon nitrate reductases
tGACcCTT
(Konishi et Yanagisawa, 2010)
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6.5 Discussion
6.5.1 Global analysis of nitrogen-related genes during maize development.
Recent transcriptome studies have highlighted global gene expression patterns in maize,
examining juvenile leaves over a 24 hour period (Jończyk et al., 2011); a maturation gradient
along a juvenile leaf (Li et al., 2010); leaves during the transition from juvenile to adult
vegetative stages (Strable et al., 2008); and different organs across development with a focus on
lignin biosynthetic genes (Sekhon et al., 2011). The focus of this study was to examine the
expression of nitrogen transporter and assimilation genes across maize development, particularly
in roots and leaves. Four vegetative gene expression clusters were identified (Figure 6.2),
specifically an early stage-selective cluster (Cluster 1, roots and leaves), an early leaf-selective
cluster (Cluster 2, juvenile to adult leaves), a root-selective cluster (Cluster 3, juvenile to
reproductive roots), and a late leaf-selective cluster (Cluster 4, adult to reproductive leaves). This
clustering pattern demonstrates that distinct subsets of nitrogen-related paralogs are
preferentially expressed in leaves compared to roots in maize. This data is consistent with recent
data from Arabidopsis showing differences in the expression of nitrogen-related genes in young
roots versus young leaves during nitrogen starvation (Krapp et al., 2011).
Second, our data demonstrates that distinct subsets of nitrogen-related genes are
selectively expressed at different developmental phases of the shoot in maize (Poethig, 1990,
2010). For example, the shift from vegetative to reproductive development altered the expression
of nitrogen-related genes in leaves (i.e. Clusters 1 and 2), consistent with changes in nitrogen
demand during grain fill (Peng et al., 2010).
It is noteworthy that the expression of Cluster 1 nitrogen-related genes in maize roots was
particularly selective for juvenile stages of development (Figure 6.2). This latter result suggests
173
that shoot-based phases of development (Poethig, 1990), for instance juvenile versus adult, may
have biological impacts on the root transcriptome, a finding that warrants further investigation.
Previous studies have demonstrated that root growth is inhibited by accumulation of nitrate in the
shoot (Scheible et al., 1997) and that nitrogen stress responses are highly coordinated between
the shoot and root systems of maize (Peng et al., 2010; Gaudin et al., 2011; Gaudin et al., 2011).
A particularly interesting finding from this study was the high level of gene expression of
many nitrogen-related probes in anthers (Figure 6.1). In fact, >14/65 probes showed peak
expression in anthers (VT stage), including probes that showed root or shoot-selective expression
during vegetative development. Given that the normalization method used, named RMA (Irizarry
et al., 2003), standardizes the gene expression ranges between arrays (e.g. relative gene
expression from anther RNA has the same range than leaf RNA after normalization), this result
does not appear to be an artefact.
On a cautionary note, it is important not to interpret the expression of each array probe as
necessarily corresponding to a unique gene in maize. It was challenging to assign some probes as
belonging to the same gene or to separate gene paralogs. For example, there was an apparent
over-abundance of glutamate synthase probes expressed in Cluster 3 (7/18 probes) compared to
other clusters (1/13, 1/15, 1/19) (Figure 6.2). It is possible, however, that one or more of the
Cluster 3 probes corresponds to the same gene.
6.5.2 Promoter motifs underlying stage-selective gene expression.
Recently, a proximal 43 bp nitrogen response element (NRE) was identified in the
promoters of Arabidopsis nitrite reductase (NiR) genes and shown to be both necessary and
sufficient for nitrate-induced gene expression and independent of repression by glutamine
(Konishi and Yanagisawa, 2010). An alignment of dicot NiR promoters revealed a pseudo-
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palindrome bipartite consensus motif [5’- (t/c)GACcCTT --N(10) -- AAG(a/g) - 3’] in the -100
bp to -240 bp promoter region (Konishi and Yanagisawa, 2010). Here we show that the
conserved 8 bp motif within this region is also conserved upstream of maize genes (consensus:
CGACCCTT) encoding nitrate and ammonium transporters (Cluster 1); the motif is
preferentially located in the -200 to -250 bp regions of the corresponding promoters (Tables 6.2,
6.3). We therefore suggest that this 8 bp motif defines an important cis-acting element of
vegetatively expressed nitrogen-related genes in angiosperms. We propose that this conserved 8
bp motif be referred to as the NRE/Acore motif (NRE-43 angiosperm core motif, 2010).
Prior to the discovery of the proximal NRE motif noted above (Konishi and Yanagisawa,
2010), a distal NRE [core A(c/g)TCA] was shown to be conserved in the promoters of nitrate
reductase (NR) and NiR genes in both dicots and monocots including maize, but not tested for
sufficiency of nitrate induction (Hwang et al., 1998). In maize, several of the distal NRE
[A(g/c)TCA] were located in the -500 to -1000 bp promoter region (Hwang et al., 1998), more
distal than the region analyzed in this study, perhaps explaining why we did not recover this
motif in our search.
Our analysis did however reveal another putative nitrogen-related motif of interest, the Ebox motif (CANNTG) forming the core of the G-box 10 element, present in Cluster 1 (Table
6.2). The E-box motif (CANNTG) overlaps the HVH21 motif which was shown to be important
for nitrate induction of the Arabidopsis Nia1 (NR) promoter (Wang et al., 2010). Both the E-box
and the G-box are related and bind bHLH transcription factors, of which >147 members have
been identified in Arabidopsis (Toledo-Ortiz et al., 2003).
In addition to these nitrogen-associated motifs, two cis-acting elements related to carbon
availability were identified in our study, NRG1 and FHL1 (Table 6.2). The NRG1 motif
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represents the binding site of the yeast NRG1 protein, a repressor of sucrose synthase (SUC2),
glucose invertase, galactokinase 1, galactokinase 4, and genes involved in gluconeogenesis and
the Krebs Cycle (Park et al., 1999; Zhou and Winston, 2001). This glucose-repression pathway is
conserved between yeast and plants (Jang and Sheen, 1997; Ramon et al., 2008). Increased sugar
levels in roots have been shown to activate the expression of the nitrate transporter genes Nrt2.1
and Nrt1.1 in Arabidopsis (Lejay et al., 1999). In Cluster 1, the NRG1-like motif was similarly
found in the promoters of Nrt1.1 and Nrt2.1 (data not shown). As Cluster 1 genes were more
expressed early in development (Figure 6.2), when the maize seedling is heterotrophic and
dependent on the grain reserve, one possibility is that the NRG1 motif helps to regulate nitrogen
uptake based on the availability of sugar from the grain. Carbon is needed for the energy
required for nitrogen uptake/assimilation and to provide carbon skeletons for amino acid
synthesis (Masclaux-Daubresse et al., 2010).
The second carbon-related motif was FHL1 (Table 6.2), corresponding to the binding site
of the FHL1 protein, a repressor of genes important for ribosome biogenesis during glucose
starvation in yeast (Hermann-Le Denmat et al., 1994; Kim et al., 2002). The tobacco ortholog of
FHL1 is functional in yeast demonstrating the conservation of this protein across eukaryotes
(Kim et al., 2002). FHL1 is regulated by the Target of Rapamycin (TOR) pathway identified in
both yeast and plants, and shown to play a central role in turning protein translation capacity to
nutrient availability in yeast (Díaz-Troya et al., 2008; Dobrenel et al., 2011). The FHL1 motif
was over-represented in genes encoding nitrate and ammonium transporters, nitrate reductase
and glutamine synthases in Cluster 3 (data not shown), the root-selective expression cluster
(Figure 6.2). It may be that the FHL1/TOR regulon plays an important role in coordinating
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carbon availability and nitrogen uptake and assimilation with the protein synthesis machinery in
maize roots.
6.5.3 Nitrite transporter expression.
We report the expression of probes corresponding to putative maize ortholog(s) of a
nitrite transporter (NiTR) as shown in Figures 6.1 and 6.2, a gene class not previously reported in
maize. A gene encoding NiTR (Nar1) was initially reported in plants in Chlamydomonas
chloroplasts (Rexach et al., 2000). In higher plants, an NiTR gene was first reported in cucumber
(CsNitr1-L), along with a functional ortholog tested in Arabidopsis (At1g68570) where a
knockout mutation showed a five-fold increase in nitrite accumulation in leaves (Sugiura et al.,
2007). The cucumber NiTR protein was localized to the inner envelope membrane of
chloroplasts, where it was hypothesized to load nitrite from the cytoplasm into the stroma of the
chloroplast during nitrate assimilation (Sugiura et al., 2007). Consistent with chloroplast
localization, transcripts of the putative maize NiTR(s) orthologs were detected in the two leafselective expression clusters (Clusters 2 and 4; Figure 6.2) with additional strong expression in
the husk leaves surrounding the cob (Figure 6.1) but not in the root-selective clusters. Functional
data however will be needed to authenticate the genes corresponding to the putative maize
NiTR(s) probes used in this study.
177
6.5.4 Significance
Nitrogen is limiting for maize growth globally, and estimates suggest that only 50% of
nitrogen fertilizer is taken up by maize roots, with the remainder leached or volatilized (Gallais
and Hirel, 2004; Eickhout et al., 2006; Hirel et al., 2007; Kant et al., 2011). The identification of
distinct clusters of expression of nitrogen uptake and assimilation genes, and predictions of the
underlying cis-acting elements responsible for each cluster, may assist in targeting efforts for
improved nitrogen uptake from soil.
178
7. Early Reprogramming of the Maize Root Hair Transcriptome in
Response to Nitrate
Author contributions: Christophe Liseron-Monfils conducted all microarray and bioinformatics
analyses. The array hybridizations were performed by Shannon McDonald and Eddie Bondo at
Syngenta Biotechnology Inc. (Research Triangle Park, North Carolina, 27709, USA). The
University of Guelph Genomic facility performed the qPCR.
179
7.1 Abstract
Root hairs (RH) comprise the major surface area of plant roots for absorption of the
critical soil nutrient nitrogen. The genome-wide transcriptome response of root hairs (RH) to
nitrogen has not been reported in any plant species. Here, microarray analysis was used to
characterize the early RH transcriptome response to nitrate in maize (Zea mays L., corn). The
expression of >876 genes was significantly altered within 3 h of added nitrate in maize RH,
including genes encoding 127 putative transcription factors. Of these genes, 92% were downregulated at 30 min after nitrate addition while 77% were up-regulated at 3 h, suggestive of an
early reprogramming of the maize RH transcriptome in response to nitrate. This rapid
reprogramming involved 54 genes encoding hormone biosynthesis/signaling proteins as well as
numerous pathways previously implicated in regulating RH elongation. The latter included nitric
oxide (NO) signaling, epidermal cell development, reactive oxygen species (ROS) scavenging,
Ca2+ and G-protein signaling, cytoskeleton proteins, GTPases and SNARE proteins that mediate
vesicle/membrane fusion, and RH cell wall biosynthesis regulators including ROOTHAIRLESS
3 and a suppressor of extensin LRX1. Evidence was uncovered for two novel regulons acting in
RH in response to nitrate, a Dof/Opaque 2/GCN transcription factor regulon and the Target of
Rapamycin (TOR) signaling pathway (a TOR/MEI2/E2F regulon). Genes encoding the high
affinity nitrate transporter NRT2.3 and its interacting peptide NAR2.1 showed >four-fold
constitutive transcript accumulation in RH compared to intact roots, with high RH expression
also observed for the nitrogen assimilation enzyme Glutamine Synthase 5 (Gln5). Predictions
were made of candidate cis-acting promoter motifs underlying the distinct RH expression
clusters observed. Candidate promoter motifs with a CA-rich core were the most prevalent. To
facilitate future candidate gene approaches, lists were generated of RH-expressed genes that
180
physically overlap previously identified quantitative trait loci (QTLs) underlying nitrogen and
yield responses in maize. This study predicts novel genes involved in RH elongation and the
plant response to nitrogen.
181
7.2 Background
Maize (Zea mays L., corn) is one of the world’s three most important food crops (Leff et
al., 2004) but its growth is limited by soil nitrogen (Gallais and Hirel, 2004; Eickhout et al.,
2006; Hirel et al., 2007; Kant et al., 2011). Nitrogen fertilizer is expensive and a leading cause of
reduced farm income and food insecurity worldwide (Eickhout et al., 2006). It is estimated that
only ~50% of nitrogen fertilizers are taken up by maize roots, with the remainder leached into
groundwater or volatilized, contributing to environmental degradation (Eickhout et al., 2006).
The tissue in direct contact with soil nitrogen is the root epidermis. Root hairs (RH), which are
single cell epidermal projections, comprise up to ~70% of the root epidermal surface area
(Mackay and Barber, 1984). RH also interact with arbuscular mycorhizal fungi and soil microbes
for enhanced nutrient uptake (Johnston-Monje and Raizada, 2011). Though earlier reports have
begun to characterize the RH transcriptome and proteome (Covitz et al., 1998; Jones et al., 2006;
Nestler et al., 2011), no studies have been reported on the genome-wide transcriptome response
of RH to soil nutrients including nitrogen in any plant species.
Nitrate (NO3-) is a critical inorganic form of nitrogen nutrition for maize (Dechorgnat et
al., 2011). Plants have evolved different nitrogen-uptake transporter systems to cope with the
wide variation in soil nitrate concentrations (Crawford and Glass, 1998). At high nitrate, there is
a low-affinity transport system encoded by the Nrt1 gene family, whereas at low nitrate, there is
a high-affinity transport system encoded by the Nrt2 and Nar2 gene families (Crawford and
Glass, 1998). In tomato, expression of Nrt1.1 was restricted to RH after nitrate exposure (Lauter
et al., 1996), while Nrt1.2 was also expressed in Arabidopsis RH and tomato RH though not
specifically (Lauter et al., 1996; Huang et al., 1999). These observations demonstrate the
importance of RH for nitrate uptake. In general, expression of genes encoding nitrogen
182
transporters and assimilation genes in RH has been understudied in maize.
Following nitrate uptake, it is transported and /or first directy assimilated into amino
acids prior to export to the rest of the plant, requiring coordination of nitrogen, carbon and other
mineral nutrition pathways (Wang et al., 2003; Britto and Kronzucker, 2005; Krouk et al., 2009;
Khan et al., 2010; Nunes-Nesi et al., 2010; Feng et al., 2011; Kusano et al., 2011). Several
regulatory molecules have been implicated in this coordination including the transcription factor
Dof1 (Yanagisawa, 2004; Tsujimoto-Inui et al., 2009). Nitrogen uptake and assimilation are
energetically expensive processes, requiring further coordination with sugar breakdown and
energy metabolism pathways (Nunes-Nesi et al., 2010; Feng et al., 2011). In mammals, it has
been shown that when nutrient availability is low, general protein translation is also modulated, a
process mediated in part by the Target of Rapamycin (TOR) signalling pathway (Ma and Blenis,
2009).
Recently, we reported that maize growing in aeroponics responds to optimal inorganic
nitrogen (20 mM total N) by increasing both the length and number of RH compared to plants
growing under limited nitrogen (8 mM total N) (both 3:1, NO3-:NH4+) (Gaudin et al., 2011).
These RH responses were determined to be ancient traits as they were observed in the extant
wild ancestor of maize, Balsas teosinte (Gaudin et al., 2011). Enhanced RH growth by high
nitrogen was consistent with studies in wheat in this concentration range (Ewens and Leigh,
1985). In Arabidopsis, the combination of ammonium and nitrate also induced polar RH growth
(Bloch et al., 2011). At lower nitrogen concentration ranges, NH4+ and NO3- were shown to
reduce RH growth or have no effect in other grasses and other dicots (Foehse and Jungk, 1983;
Robinson and Rorison, 1987). All of these studies suggest that nitrogen can affect RH
elongation, though possibly in a species- or concentration-dependent manner.
183
RH elongation occurs by polar tip growth and is a complex process involving numerous
interacting signalling pathways (Libault et al., 2010; Terrile et al., 2010; Trevisan et al., 2011).
To facilitate polarized growth, longitudinally oriented actin cables in RH help the myosinmediated transport of organelles (Kost, 2008). Localized F-actin mediates transport of secretory
vesicles to sites of fusion with the plasma membrane at the RH tip to deposit the Golgi-derived
building materials required for expansion of the cell wall and plasma membrane (Kost, 2008).
Small GTPases of the Rho family regulate the reorganization of the actin cytoskeleton and
membrane trafficking (Kost, 2008). For example, the gene encoding ROOT HAIR DEFECTIVE
3 (RHD3) in Arabidopsis encodes a GTPase involved in vesicle trafficking in RH between the
endoplasmic reticulum and Golgi apparatus (Yuen et al., 2005). Ca2+ regulates the dynamic
reorganization of the RH cytoskeleton during tip growth (Van Bruaene et al., 2004). Ca2+ is
highly polarized and oscillates along with both pH and ROS during RH growth (Monshausen et
al., 2007). The NADPH oxidase (ROOT HAIR DEFECTIVE 2, RHD2), localized to the plasma
membrane near the RH tip (Takeda et al., 2008), releases ROS into the extracellular space
(Foreman et al., 2003; Monshausen et al., 2008). Extracellular ROS accumulates on the sides of
the RH, but not at the tip itself, to promote non-tip cell wall rigidification and hence polar growth
(Monshausen et al., 2008). Extracellular ROS also activates plasma membrane Ca2+ channels
(Foreman et al., 2003; Monshausen et al., 2008) as well as NADPH oxidase itself, thus creating a
feed-forward signalling loop (Takeda et al., 2008). Several hormones, in particular ethylene and
auxin, have been shown to affect RH elongation (Tanimoto et al., 1995; Pitts et al., 1998). In RH,
the hormone abscisic acid has been shown to regulate NADPH oxidase itself (Achard et al.,
2008). Perhaps integrating many of the above processes, the signalling molecule nitric oxide
(NO) has been shown to modulate tip growth by affecting microtubule orientation and vesicle
184
trafficking, and also by interacting with signalling pathways involving Ca2+, ROS, G-proteins
and hormones (Prado et al., 2004; Kaiser et al., 2007; Li et al., 2009; Li et al., 2010; Swanson
and Gilroy, 2010; Terrile et al., 2010). Extracellular ATP (eATP) has been shown to regulate RH
growth and induce NO and ROS production along with auxin and ethylene (Kim et al., 2006;
Clark et al., 2010; Clark et al., 2010; Swanson and Gilroy, 2010).
Here we examine the genome-wide transcriptome response of maize seedling RH at 30
min and 3 h after supplementation with added nitrate (AddN) compared to seedlings maintained
in limiting, maintenance nitrate (MaintN). A challenge of conducting such a study is the need to
change the nitrogen concentration without damaging RH and also being able to harvest sufficient
RH-specific RNA for microarray analysis. These challenges were overcome here using a slanttube agar/liquid root hair media (RHM) system combined with optimized RH RNA isolation
procedures. Using these methodologies, we characterize the early reprogramming of the maize
RH transcriptome in response to nitrate. Second, we identify candidate cis-acting promoter
motifs underlying the distinct RH expression clusters observed. Finally, we predict candidate RH
genes underlying previously identified nitrogen related quantitative responsive loci (QTLs)
(Coque et al., 2008) by virtually mapping both datasets onto the maize genome.
7.3 Methods
7.3.1 Biological material
Maize inbred line B73 originated from the USDA Stock Center (PI 550473, North
Central Regional PI Station, Ames, Iowa).
7.3.2 Growth system overview
In the optimized RH growth system, 30 ml of nutrient agar (see below) was added into a
sterile glass test tube (Sigma Pyrex® VistaTM culture tube 25 x 200 mm, Sigma-Aldrich, St
185
Louis, MO, US) which was capped with a rubber stopper (VWR* Black Rubber Stoppers,
59580-182); the agar was left to solidify at a 90˚-horizontal slant. The RH media (RHM) agar
contained 0.3 mM nitrate and was adapted from previous studies (Liu et al., 2001; Liu et al.,
2006). It consisted of: 3% (w/v) agar (Sigma-Aldrich A1296), 0.15 mM Ca(NO3)2 (Sigma
Z37124), 4.85 mM CaCl2 (Sigma 10043-52-4), 0.2 mM K2SO4 (Sigma 77778-80-5), 0.82 mM
MgSO4 (Sigma 10034-998), 0.1 mM FeNa-EDTA (PhytoTechnology Laboratories 15708-41-5)
9.1 µM MgCl2 (Fisher biotech 7773-61-5), 0.034 µM NaMoO4 (Sigma 10102-40-6), 18 µM
H3BO3 (EMD BX0865-1), 0.08 mM Ca5OH(PO4)3 (Fluka 21218), 0.2 µM CuSO4 (Sigma
C7631), 0.4 µM ZnSO4 (Sigma 7446-20-0), pH 5.5-6.0. A single germinated seed was placed on
the agar surface, 10-20 mm from the top of the tube. A home-made foam plug was used to gently
press the seed against the agar, which was covered by pieces of rockwool; this system
maintained the seed at the correct position, and prevented desiccation, pathogen contamination
and light exposure (Figure 7.1). The RHM agar contained calcium phosphate tri-basic to
simulate RH growth (Liu et al., 2001, 2006). Roots grew along the agar surface: half of the RH
penetrated the agar, which allowed for a uniform exchange of nutrients and mechanical
resistance, while the other half of the RH grew into the air which facilitated gas exchange. Liquid
RHM containing different concentrations of nitrogen were poured into the tubes at the start of
the nitrogen treatment time course, since the tubes were half-empty. Since the RH grew in the air
and in soft agar, harvesting caused minimal RH damage.
186
Figure 7.1. The custom growth system for root hair growth. Seedlings were individually
germinated (A) in Pyrex test tubes containing root hair media (RHM) agar (as shown in orange).
(B) Tubes were placed on a slant and then transferred into (C) custom boxes with plugs to keep
roots in the dark yet allow gas exchange.
187
7.3.3 Growth and nitrate treatments
Seeds were germinated on Whatmann paper (water saturated), and grown in the dark at
~28°C. Uniformly germinated 2-3 day old seedlings were transferred to the RHM agar test tubes
containing 0.3 mM nitrate (see above). All nitrate treatments were started between 9-10 am. The
tubes were placed into adapted growth boxes (Figure 7.1) which were then placed into growth
chambers. The growth conditions consisted of a 16 h photoperiod, 30˚C day/22˚C night, with
250-300 µMol m-2 s-1 light provided by incandescent bulbs and full spectrum fluorescent light
bulbs. Plants were watered everyday with ~ 1 ml of 0.3 mM nitrate RHM solution to maintain
roots in a humid environment. At 8 days after transfer (time 0), 30 ml of low nitrate (MaintN, 0.3
mM) or normal nitrate (AddN, 3 mM) RHM was added to the tubes: the low nitrate RHM
contained 0.15 mM Ca(NO3)2 and 4.85 mM CaCl2, while the normal nitrate RHM contained 1.5
mM Ca(NO3)2 and 3.5 mM CaCl2. Both solutions were supplemented with 3% (v/v) H202 as an
oxygen source. The nitrate concentrations were defined in a pilot experiment (data not shown).
Roots were harvested and frozen in liquid nitrogen at three time points following the nitrate shift:
time 0, 30 min and 3 h. There were 8-12 plants/time point/replicate and the experiment was
replicated three times in different growth chambers.
7.3.4 Root hair RNA extraction
At harvest, long forceps were used to pull intact agar containing roots from the tubes.
Root segments below the most apical lateral root node were dissected and frozen in liquid
nitrogen (LiqN) individually in 1.5 ml Eppendorf tubes which were then stored at -80˚C. On the
day of RH RNA extraction, tubes were placed in LiqN. One by one, LiqN was poured into each
tube; tweezers pre-dipped in LiqN was used to remove the root and place it above a clean
Eppendorf tube containing 200 µl TriReagent (AM9738, Ambion, USA). A second pre-chilled
188
tweezers were then used to shave the RH; the RH remained attached to the tweezers which were
then dipped into the TriReagent. One TriReagent tube was used to harvest RH RNA for every 23 plants. All tubes were re-frozen at -80˚C so that all RNA per replicate could be extracted
simultaneously. TriReagent samples from each replicate/time point were pooled to a maximum
of 800 µl which was topped up to 1 ml with TriReagent. Samples were vortexed for 30 s,
incubated at room temperature (RT) for 4-6 min, then centrifuged at 12000 x g for 10 min at 4°C.
The aqueous phase was removed to a new tube, which was extracted with 200 μl
chloroform:isoamyl alcohol (24:1) by vortexing for 15 s and incubating at RT for 3 min. Samples
were centrifuged at 12000 x g for 10 min at 4°C. The upper phase was transferred to new tube to
which was added 250 μl isopropanol (RT) and 250 μl of high salt solution (0.8 M sodium citrate
and 1.2 M sodium chloride) in order to eliminate polysaccharides and cell wall waste
(Chomczynski and Mackey, 1995). The samples were incubated for 15 min at RT, then
centrifuged at 12000 x g for 10 min at 4°C. The supernatant was carefully removed and
discarded; the RNA-containing pellet was translucent and was resuspended in 500 μl RNAsefree water. Next, 400 μl of Acid-Phenol:Chloroform (AM9720, Ambion, USA) was added to
each tube; samples were vortexed for 10 s, incubated for 3 min at RT, then centrifuged at 12000
x g for 10 min at 4°C. The upper phase was transferred to a new tube, to which was added 500 μl
isopropanol and 66 μl 3M sodium acetate pH 5.2. The samples were vortexed briefly, incubated
on ice for 10 min, then 12000 x g for 10 min at 4°C. The supernatant was discarded, and the
pellet washed twice with 1 ml 75% ethanol with 5 min centrifugations at 12000 x g at 4°C. The
pellets were slightly dried and the RNA dissolved in 50 µl of RNAse-free water with a 10 min
incubation at 55˚C and periodic vortexing.
189
7.3.5 Microarray hybridization, analysis and clustering
The custom Syngenta B73 Corn 46K Affymetrix array was used to hybridize RH RNA as
previously described (Wagner and Radelof, 2007). RNA from the following plant treatments
were hybridized: 0.3 mM nitrate (0 min, 30 min, 3 h post-shift); 3 mM nitrate (30 min, 3 h postshift). There were three biological replicates. Bioconductor (Gentleman et al., 2004) and R (RDevelopment-Core-Team, 2009) were used for subsequent gene expression analysis. Expression
normalization was performed using the RMA method (Irizarry et al., 2003). Differential gene
expression was measured using the linear model below from the Limma Package (Smyth, 2005).
Each of the five treatments (described above) was defined as categorical variables in the linear
model, defining a design matrix (X):
(
)
The linear model was adjusted using the empirical Bayesian method from the Limma
Package (Smyth, 2005). To define the effect of nitrogen at each time point after the treatment
shift, gene expression was compared between 0.3 mM nitrate versus 3 mM nitrate RHM. The
potential effect of the immersion of roots in RHM solution was also determined by comparing
gene expression from roots exposed to 0.3 mM nitrate at time 0 (before emergence) and at 30
190
min and 3 h post-emergence. For each comparison, the p-value of the Empirical Bayesian test
was corrected using the Benjamini-Hochberg method (Benjamini and Hochberg, 1995). The Pvalue was set at 0.05. Gene annotations were retrieved via a custom Perl script using MapMan
Zm_B73 file, accessed in April 2011 (Thimm et al., 2004) and MaizeSequence.org (Schnable et
al., 2009) annotations as a starting points to link genes to the corresponding microarray probes
and annotation category.
The initial MapMan annotation file had 29,142 genes, but could only identify 34% of the
probes on the microarray. After the use of MaizeSequence.org annotations, gene annotations
could be retrieved for 65% of probes. Annotation categories that were overrepresented were
identified using Fisher’s exact test using R programming.
7.3.6 Real time quantitative RT-PCR
Quantitative real time reverse transcription PCR (qRT-PCR) was conducted at the
University of Guelph Genomics Facility using gene specific primers (Table 7.1). Reverse
transcription were conducted using MultiScribe™ Reverse Transcriptase and qPCR using
PerfeCta SYBR® Green FastMix ROXTM (Quanta BioSciences, Inc., Gaithersburg, MD).
Amplification conditions were 95˚C for 3 min, followed by 40 cycles of: denaturation, 95˚C for
15 s; annealing (55˚C for Nar2.1 and 60˚C for Nrt1.1, Nrt1.2, Nrt2.1, Nrt2.2, Nrt2.3 and
Tubulin) for 30 s; extension at 72˚C for 1 min. The relative expression ratio of each target gene
was calculated based on real time PCR efficiency and was normalized to Zea mays alphatubulin-3 (Genbank EU954789.1) as previously described (Liu et al., 2009).
191
Table 7.1: Real time qRT-PCR primers used to determine the RH/root expression ratio of Nrelated genes
primers
nrt1.1-Fwd
nrt1.1-Rev
nrt1.2-Fwd
nrt1.2-Rev
nrt2.1-Fwd
nrt2.1-Rev
nrt2.2-Fwd
nrt2.2-Rev
nrt2.3-Fwd
nrt2.3-Rev
nar2.1-Fwd
nar2.1-Rev
gln5-Fwd
gln5-Rev
tubulin-Fwd
tubulin-Rev
sequences
ID
CTG TCT GGC ACC GTG ATT GT
gi|37778585
CGT AGC TGA CTG CCC ACC TAA
gi|37778585
TGT TCT CGG CGT GGT GAA
gi|63397127
CCT CTG TAC CTG ACG GAG CAA
gi|63397127
ACACGTGTGCTCCGTTGACA
GRMZM2G010251_T01
TGATTGAGCTGAATAGACGCGA
GRMZM2G010251_T01
CCATGTTCACCTGCTACCTACCT
GRMZM2G010280_T01
CGTTGGCACATCTCAACTATGTGTT GRMZM2G010280_T01
CTT CTT CAC CAC GTC CAG CTA
CT
GCC ATG ATG CCC ATG TTC TC
GCG GGT GGC GCA AGT
TTG AAC TGG CAC GCC TTG T
CCG TCC GTC GGC ATC TC
CCT CTC AAG AAT GTA GCG AGC
AA
GCG CCT GTC TGT TGA CTA TGG
GGG ATG GGT ACA CGG TGA AA
Tm
57.76
58.92
56.94
58.64
56.8
54.09
55.69
56.15
gi|63397156
58.56
gi|63397156
gi|63397072
gi|63397072
gi|162459550
56.57
60.10
57.81
58.56
gi|162459550
56.88
gi|195610153
gi|195610153
58.20
57.10
192
7.3.7 Promoter motif prediction
The 876 differentially expressed genes were clustered using the HOPACH method (Van
der Laan and Pollard, 2003). Each of the six co-expressed gene lists were searched for common
promoter motifs in their promoter sequences. De novo cis-acting motifs (≥ 6 bp) in the -200 to
+1 promoter region were predicted using a Perl-based motif discovery program that was custom
developed for the maize genome, called Promzea (see Chapter 3.3, Materials and Methods
section). Briefly, BLAST searches using the microarray probe sequences were conducted against
the full-length collection of cDNAs defined by MaizeSequence.org. Over-represented motifs in
the promoter were identified using three motif discovery tools, Weeder (Pavesi et al., 2007),
MEME (Bailey and Elkan, 1994) and BioProspector (Liu et al., 2001). Each motif was reevaluated using one of the following statistical methods: the hypergeometric test or the binomial
test. All significant motifs found in the search were compared to the motif databases, Athamap
(Bülow et al., 2009) and PLACE (Higo et al., 1999), using STAMP software (Mahony and
Benos, 2007).
7.3.8 Physical mapping of QTLs
A total of 23869 genes present on the microarray were successfully localized on the B73
genome physical map (MaizeGDB, B73 RefGen_v2). In order to use the RH microarray data to
predict candidate genes for agronomic QTLs defined previously (Coque et al., 2008), the
boundary intervals of the QTLs first had to be anchored on the B73 genome physical map. PCR
primer sequences corresponding to each QTL were anchored using the Locus Data search tool
from MaizeGDB (B73 RefGen_v2). If the marker had not been physically anchored, the adjacent
marker defined in MaizeGDB was used. Alternatively, direct BLAST searches were used. When
only one marker could be anchored to the genome, the missing physical boundary of the QTL
193
was estimated by adding 3.8 Mbp in that direction, corresponding to 2.5 cM on average in the
Coque et al. (2008) genetic map (Coque et al., 2008) which had a 5 cM average resolution
(Calculation = 3232 Mbp/2147 cM x 2.5 cM = 3.8 Mbp). Chromosome centromeres were
positioned in accordance with their physical and genetic locations in B73 (Wolfgruber et al.,
2009).
7.4 Results and Discussion
7.4.1 Root hair RNA yield
A RH growth system was designed that stimulated RH growth, offered mechanical
resistance to growing roots (Beemster et al., 1996) and had good gas exchange around the roots
while maintaining roots in the dark (Figure 7.1 B,C). The growth system also allowed for
uniform nutrient availability, facilitated exchanging the nitrogen media as desired, and
minimized RH damage during harvesting. This system was combined with an optimized RH
RNA extraction protocol (see Methods), resulting in an average yield of total RNA of 270 ng/µl
from 8-12 seedlings (Bioanalyzer 2100, Agilent Technologies Inc., Santa Clara, CA, USA).
7.4.2 Determination of nitrate concentrations
A pilot experiment was conducted to determine limiting and optimal nitrate
concentrations. Ten day old seedlings were grown in the RH growth system with Root Hair
Media (RHM) containing different concentrations of nitrate (0 mM, 0.3 mM, 3 mM or 20 mM).
The shoot dry biomass was highly significant between plants grown on 0.3 mM versus 3 mM
nitrate (p<0.01; Figure 7.2), but not significant between 0 mM versus 0.3 mM, or between 3 mM
versus 20 mM nitrate (Figure 7.2). The nutrient-rich kernel of maize was likely responsible for
the modest differences in biomass observed between the different nitrogen treatments. As a
194
result, 0.3 mM was selected as the limiting nitrogen concentration in the RH growth system,
while 3 mM was defined as the optimal nitrate concentration.
195
Figure 7.2. Determination of the nitrate concentrations needed for this experiment. The
effect of four nitrate concentrations on maize seedling growth were tested (Inbred B73). Nitrate
was supplemented into 3% agar root hair media (RHM) at a concentration of 0 mM, 0.3 mM, 3
mM and 20 mM. For each nitrate concentration, the shoot biomass for 21 plants was measured at
10 days after germination. The box plots represent the interval between the 25th and 75th
percentile. Horizontal lines represent the median shoot biomass. The biomass is expressed in
grams.
196
7.4.3 Expression summary
After initially growing seedlings on agar with limited nitrate (0.3 mM), they were
exposed to liquid media (RHM) which either maintained the 0.3 mM nitrate concentration
(maintenance nitrate, MaintN) or increased it by 10-fold (3 mM, added nitrate, AddN) with all
other nutrients remaining constant. We were interested in the RH transcriptome response to
added nitrate at 30 min and 3 h following an extended period of nitrogen limitation (Figure 7.3).
To control for possible interactions caused by adding liquid media to the seedlings, the analysis
was restricted to comparing MaintN versus AddN responses within a given time point. A total of
876 annotated genes (1043/46681 probes) were differentially expressed in RH between MaintN
and AddN treatments at 30 min and/or 3 h (Figure 7.4A, Figure 7.5). Of these genes, 256 were
differentially expressed at both time points, 286 only at 30 min and 336 genes only at 3 h.
Interestingly, the majority of the earlier response genes (236/256) were down-regulated in
response to AddN (Figure 7.4B, Figure 7.5), while the majority of later response genes (259/336)
were up-regulated in AddN (Figure 7.4C, Figure 7.5), suggestive of an early reprogramming of a
portion of the RH transcriptome.
197
Figure 7.3. Experimental flow chart. For each replicate, 48 seedlings were germinated in slant
agar tubes containing semi-solid root hair media (RHM) supplemented with 0.3 mM nitrate. At
10 days after germination (time 0), liquid RHM was added into the tubes, supplemented with
either 0.3 mM nitrate (MaintN) or 3 mM nitrate (AddN), and harvested 30 min or 3 h later. Each
treatment/time point consisted of ~12 plants. The experiment was repeated in different growth
chambers to obtain three biological replicates. Root hair RNA was extracted from each replicate
(pooled from ~12 plants), and used for microarray hybridizations. To characterize the effect of
nitrate, and no other variables such as submergence, only microarray results from the same time
point were compared between control (MaintN) and treated samples (AddN).
198
Figure 7.4. Genes differentially expressed in root hairs at 30 min versus 3 h in response to
added nitrate. (A) Summary of differentially expressed genes between control (MaintN) and
nitrate supplemented (AddN) seedlings. The blue sphere represents genes that were only
differentially expressed at 30 min, while the green sphere represents genes that were specifically
expressed at 3 h. (B) Numbers of genes that were down-regulated (DOWN) at 30 min and 3 h,
or (C) Up-regulated (UP) at 30 min and 3 h in response to added nitrate.
199
Figure 7.5. Relative expression summary heatmap. The heatmap rows represent the 876
differentially expressed genes between 0.3 mM nitrate control (MaintN) and 3mM nitrate
treatment (AddN) at the at 30 min (A), 3 h (B) or in both time point comparisons (C). The 12
columns represent microarrays, organized in 3 replicates for each of the four samples: 30min
MaintN, 30 min AddN, 3 h MaintN and 3 h AddN. The relative gene expression levels range
from low expression in yellow to high expression in dark blue.
200
7.4.4 Annotation summary
Out of a total of 876 differentially expressed annotated genes following the addition of
nitrate, 127 were putative transcription factors (15%) and another 54 were associated with
phytohormones (6%) (Appendix Table 3). Amongst the differentially expressed genes at either
and/or both 30 min and 3 h after added nitrate, several gene annotation categories were overrepresented (Appendix Table 3, Figure 7.6). This included the APETALA2 transcription factor
family (Fisher’s exact test, p=1.99e-06) known to be involved in ethylene hormone responses
(Song et al., 2005); and the DOF transcription factor family (p=13.88e-05), some members of
which have been shown to have root-specific expression (Yanagisawa, 1997, 2004; TsujimotoInui et al., 2009). Other overrepresented genes were related to other hormones (primarily ABA,
ethylene, auxin, jasmonic acid) (p=1.5e-04); E3 RING genes involved in protein degradation
(p=3.9e-04) (Smalle and Vierstra, 2004); and genes involved in stress redox reactions (p=3e-03)
and calcium signaling (p=6.5e-03), pathways previously shown to be involved in RH
development (Ewens and Leigh, 1985; Gilroy and Jones, 2000; Carol and Dolan, 2006; Libault
et al., 2010). Additional over-represented gene categories included gene involved in amino acid
biosynthesis (p=9.8e-03), post-translational protein modification (p= 0.012), or genes encoding
MAP kinases (p=0.031).
201
Figure 7.6. Genes differentially expressed in root hairs in response to nitrate classified by
gene annotation category. (A) Numbers of genes in annotation categories that were
significantly over-represented. (B-D) Numbers of genes that were (B) hormone-related, (C)
transcription factors, (D) and signalling related. All the annotation types were based on the
MapMan software maize annotation file (Thimm et al., 2004).
202
7.4.5 Genes Affecting Plant Nutrition
7.4.5.1 Nitrogen Nutrition
Three nitrate transporter genes were more highly expressed in RH than the median
relative expression level of the array (> log 2 expression = 5.7; Table 7.2). These highly
expressed genes encode the high affinity transporters NRT2.1 and NRT2.2 (Quaggiotti et al.,
2003), and a gene encoding an interacting peptide required for NRT2 to be functional, NAR2.1
(Yan et al., 2011). The gene encoding the related family member NAR2.2 had basal expression
in RH, along with the gene encoding the low affinity transporter NRT1 (Quaggiotti et al., 2003).
Real time quantitative RT-PCR was used to determine whether nitrate transporter genes were
preferentially expressed in RH compared to intact root systems. Expression was only monitored
for specific transporter genes that were neither N-responsive in roots (Figure 7.7) nor RH (data
not shown) in order to be able to generalize the results across nitrogen treatments (Figure 7.8).
The low affinity transporter genes Nrt1.1 and Nrt1.2 showed 50% lower expression in maize RH
compared to intact roots using qRT-PCR (Figure 7.8).
203
Table 7.2: Relative expression of nitrate and ammonium transporters in root hair cells.
Gene
Abbreviation
Average
expression
(log)
Highly
expressed
in R.H.
Differentially
expressed
GRMZM2G176253
similar to AtNTP3
6.20


GRMZM2G010280
Nrt2.1
6.28

GRMZM2G010251
Nrt2.2
6.28

GRMZM2G179294
NAR2.1
11.20

GRMZM2G163494
NAR2.2
3.60
GRMZM2G375113
Similar to AtPTR2-B, NTR1
8.25
GRMZM2G019806
symbiotic AMT | transcription factor activity
5.06
GRMZM2G028736
similar to OsAMT1.3
9.91

GRMZM2G043193
similar to AtAMT2.1
5.28

GRMZM2G080045
similar to OsAMT2.1,OsAMT2.3
5.83

GRMZM2G118950
similar to OsAMT1.1
9.40

GRMZM2G173967
putative ammonium transporter
4.58
GRMZM2G175140
similar to OsAMT1.2
10.49


GRMZM2G335218
putative AMT
5.74


GRMZM2G338809
putative AMT
10.36






The median relative expression of the microarray was 5.70 on a log 2 scale on the microarrays
204
Figure 7.7. Validation of N-related gene expression stability between intact roots and root
hairs. Validation that Nrt1.1, Nrt1.2, Nrt2.3, NAR 2.1 and Gln5 genes were not differentially
expressed between AddN and MaintN treatments in root hairs using quantitative real time PCR.
Shown is the Pearson coefficient of correlation (R2).
205
Figure 7.8. Fold difference in expression of nitrate uptake and assimilation genes in roots
versus root hairs. The experiment was conducted using real-time quantitative RT-PCR. The
analysis was limited to highly expressed genes in root hair cells in comparison to the median
expression of the microarray. RNA was extracted 30 min after nitrate addition (AddN). On the yaxis, the gene expression ratio (root hair/root) is shown on a Log 2 fold-change (RH/root) scale.
206
Table 7.3: Ammonium transporters retrieved from the maize genome, and orthologs from rice
and Arabidopsis.
Gene ID
AC195826.2_FG006
AC208641.3_FG005
Annotation
ammonium transmembrane
transporter activity (GO:0006810,
GO:0008519) | AtAMT2.1
ammonium transmembrane
transporter activity (GO:0006810,
GO:0008519)
Source
Maize Genbank
Accession
Rice Genbank
Accession
Gramene,
MapMan
/
/
Gramene
/
/
AC208641.3_FG008
ammonium transmembrane
transporter activity (GO:0008519)
Gramene
/
/
AC211704.3_FG003
ammonium transmembrane
transporter activity (GO:0008519)
Gramene
/
/
GRMZM2G019806
hypothetical protein LOC100194106
RefSeq peptide
NP_001132631
/
GRMZM2G028736
hypothetical protein LOC100191554 |
OsAMT1.3
RefSeq peptide
NP_001130456
AF289479,
NM_001053991
Gramene
/
/
RefSeq peptide
NP_001159318
NM_001053632
RefSeq peptide
NP_001145797
NM_001062336,
AB051864,
NM_001051237
RefSeq peptide
NP_001148121
/
RefSeq peptide
NP_001141280
NM_001059815
RefSeq peptide
NP_001136691
/
RefSeq peptide
NP_001140828
NM_001053990
Genbank
/
NM_001051467,
NC_008405
RefSeq DNA
NM_001174872
NC_008404
/
/
/
/
GRMZM2G032899
GRMZM2G043193
GRMZM2G080045
GRMZM2G082343
GRMZM2G118950
GRMZM2G173967
GRMZM2G175140
GRMZM2G335218
GRMZM2G338809
GRMZM2G473697
ammonium transporter domain
hypothetical protein LOC100304410|
OsAMT3.3
hypothetical protein LOC100279304 |
OsAMT2.1 | OsAMT2.3
symbiotic ammonium transporter
hypothetical protein
LOC100273369|OsAMT1.1
hypothetical protein LOC100216823
hypothetical protein LOC100272903|
OsAMT1.2
GO:0008519 ammonium
transmembrane transporter activity |
OsAMT2.2 | OsAMT3.1 | OsAMT5.1
hypothetical protein LOC100382111
(LOC100382111) | ammonium
transmembrane transporter activity
(GO:0008519)
ammonium transmembrane
transporter activity (GO:0008519) |
OsAMT5.2
GRMZM2G701289
ammonium transmembrane
transporter activity (GO:0008519)
GRMZM5G883969
OsAMT3.2
LOC_Os03g62200
NM_001058371
207
Table 7.4. Categories of differentially expressed genes in the root hair response to nitrate
addition.
Category
Gene
Annotation
Fold
Change
(Log2)
Average
relative
expression
Pvalue
Time
comparison
1.20
8.29
0.023
30 min and 3
h
0.79
9.50
0.018
30 min
0.57
8.44
0.030
30 min and 3
h
0.87
7.31
0.028
3h
3h
Nutrition
GRMZM2G005024
GRMZM2G104632
GRMZM2G150098
GRMZM2G391511
Orange pericarp2, tryptophan synthase
beta-subunit , ortholog of AtTSB1
(tryptophan synthase beta-subunit 1,
AT5G54810)
Glyceraldehyde-3-phosphate
dehydrogenase 1 (GAPC1) possible
chloroplastic GAPC
Cytosolic pyruvate kinase, putative
ortholog ofAtPK1 (pyruvate kinase 1,
AT5G08570)
Nicotinate phosphoribosyltransferase,
ortholog of AtNAPRT2 (nicotinate
phosphoribosyltransferase 2,
AT2G23420)
GRMZM2G024151
Glycogen synthase kinase-3 MsK-3
-0.62
7.79
0.038
GRMZM2G069542
Phosphoenolpyruvate carboxylase ( C4PEPC-1)
1.12
11.46
0.040
3h
30 min and 3
h
3h
GRMZM2G169654
DNA-binding protein RAV1
-1.41
7.81
0.002
GRMZM2G016150
Opaque2 heterodimerizing protein1
0.64
9.62
0.026
-0.78
6.32
0.034
30 min and 3
h
0.55
6.02
0.038
30 min
Dof2 (DNA binding with one finger 2)
Chloroplastic thioredoxin/transketolase
fusion protein
-0.65
5.86
0.037
0.84
9.67
0.010
GRMZM2G009223
Glucose-6-phosphate translocator 2
1.94
8.02
0.012
30 min
30 min and 3
h
30 min and 3
h
GRMZM2G147424
DNA-binding protein S1FA2
0.87
4.98
0.025
GRMZM2G394450
Beta-fructofuranosidase 1 precursor
-0.89
8.28
0.027
30 min
GRMZM2G051256
GRMZM2G018607
GRMZM2G009406
GRMZM2G033208
GRMZM2G024530
GRMZM2G082434
GRMZM2G310321
GRMZM2G169931
GRMZM2G116700
GRMZM2G049329
GRMZM2G177340
R2R3 Myb transcription factor MYBIF35
ATPase activity, putative ortholog of
transcription factor AtGCN4
(transporter, AT3G54540)
PTF1, DNA-binding domain bHLH
transcription factor
Putative ortholog of AtAAP3 ( amino
acid transmembrane transporter,
AT1G77380 )
Cytochrome complex assembly, putative
ortholog of Arabidopsis ATG1
(AT3G51790) and rice ATG1
(loc_os10g39870)
Putative ortholog of nonsense-mediated
mRNA decay NMD3 family protein
(AT2G03820) and rice NMD3 (
loc_os10g42320)
Putative ortholog of AtATG18g
(AT1G03380)
RNA polyadenylation, putative ortholog
of Arabidopsis nuclear poly(A)
polymerase (nPAP, AT4G32850)
Putative ortholog of putative
Arabidopsis (AT5G22250) and rice
(loc_os04g58810) CCR4-NOT
transcription complex protein subunit
3h
-0.76
8.81
0.043
30 min and 3
h
0.89
6.32
0.045
3h
0.53
7.49
0.041
3h
0.97
9.70
0.030
3h
0.61
8.73
0.029
3h
0.82
6.96
0.005
30 min and
3h
-1.12
6.33
0.022
30 min and
3h
208
Table 7.4 (continued)
GRMZM2G147424
DNA-binding protein S1FA2 implicated
in regulation of transcription
0.87
4.98
0.025
3h
1.64
5.46
0.011
30 min and 3
h
-3.54
4.90
0.037
3h
0.75
9.40
0.016
3h
1.64
7.99
0.013
30 min and 3
h
0.59
8.88
0.037
30 min
3h
Amino acid synthesis
GRMZM2G396212
GRMZM2G046163
GRMZM2G025366
GRMZM2G036708
GRMZM2G300801
3-deoxy-7-phosphoheptulonate synthase
activity, aromatic amino acid family
biosynthetic process
Putative tryptophan synthase, alpha
subunit ( AT4G02610)
NAD-dependent isocitrate
dehydrogenase , 3-isopropylmalate
dehydrogenase (EC:1.1.1.85)
Cysteine biosynthetic process from
serine, pyridoxal phosphate binding
Phosphoserine aminotransferase, Lserine biosynthetic process, response to
freezing
GRMZM2G015892
Tryptophan synthase activity
-3.54
4.90
0.037
GRMZM2G136266
Transcription factor PosF21
-0.58
7.76
0.025
30 min
Root hair growth
GRMZM2G080001
Ribosomal protein S6 kinase
-0.58
4.52
0.046
30 min and 3
h
GRMZM2G145496
50S ribosomal protein L27,
chloroplastic
-0.87
7.26
0.039
3h
GRMZM2G024647
60S ribosomal protein L6
0.82
6.48
0.040
30 min
GRMZM2G440543
F-box protein GID2
-1.07
6.94
0.043
3h
GRMZM2G177340
Putative ortholog of rice CCR4-NOT
transcription complex subunit 8
(loc_os04g58810)
-1.12
6.33
0.022
30 min and 3
h
GRMZM2G052515
Transcription factor E2F2
0.57
5.24
0.047
30 min
GRMZM2G157836
Adenylyltransferase and
sulfurtransferase MOCS3 2
0.51
7.34
0.044
3h
GRMZM2G123212
Ubiquitin protein ligase CIP8
2.19
7.50
0.004
GRMZM2G060216
Liguleless2
-0.63
5.68
0.039
30 min and 3
h
30 min
GRMZM2G087741
Liguleless3, knotted class 1
0.73
7.78
0.038
3h
GRMZM2G028041
Rough sheath1
1.11
8.29
0.038
3h
GRMZM2G377215
Roothair defective3 (Roothairless3)
-0.90
7.51
0.026
30 min and 3
h
1.68
4.82
0.029
3h
-1.29
7.31
0.017
30 min
-0.78
7.09
0.038
30 min
1.23
7.06
0.016
3h
1.94
6.42
0.009
30 min and 3
h
-1.09
4.90
0.043
30 min
-0.86
7.26
0.047
30 min
-0.62
5.26
0.039
30 min
Calcium and G-protein
signalling
GRMZM2G154685
GRMZM2G030882
GRMZM2G126386
GRMZM2G180622
GRMZM2G016677
GRMZM2G171600
GRMZM2G090594
GRMZM2G099425
Calmodulin binding peptidyl-prolyl
cis-trans isomerase, protein folding
Calmodulin binding protein, response to
freezing
Calcium ion binding, moderately similar
to AT3G05410
Sarcoplasmic reticulum histidine-rich
calcium-binding protein
Putative oxygen-evolving enhancer
protein 2, chloroplast precursor, calcium
ion binding
Calmodulin binding transcription
regulator
WRKY25 transcription factor,
calmodulin binding
Calcium ion binding calmodulindependent protein kinase, similar to
AtCPK7
209
Table 7.4 (continued)
GRMZM2G028086
GRMZM2G320506
GRMZM2G384897
GRMZM2G145109
GRMZM2G145075
GRMZM2G157068
GRMZM2G053868
GRMZM2G426046
GRMZM2G071100
GRMZM2G031329
GRMZM2G312661
GRMZM2G043435
GRMZM2G055957
GRMZM2G061537
GRMZM2G473411
GRMZM2G429113
Calcium-dependent protein kinase,
isoform AK1, similar to CDPK19
(AT5G19450), glycogen biosynthetic
process
Calcium-dependent serine/threonine
protein kinase, similar to AtCPK1
(AT5G04870)
Calcium-dependent serine/threonine
protein kinase
Calcium-dependent serine/threonine
protein kinase
Calcium-dependent serine/threonine
protein kinase
Calcium-dependent serine/threonine
protein kinase
Calcium-dependent serine/threonine
protein kinase
Calmodulin-like protein
Putative ortholog of calcium binding
ARF-GAP domain 11 (AGD11,
AT3G07490)
Putative calcium ion binding protein
CAST, mitochondrial inner membrane,
transmembrane transport
Putative calcium ion binding protein
CAST
Respiratory burst oxidase-like protein C,
membrane peroxidase activity, calcium
ion binding, FAD binding, acting on
NADH or NADPH, with oxygen as
acceptor
Protein serine/threonine kinase, similar
to AtCRCK3 (calmodulin-binding
receptor-like cytoplasmic kinase
3,AT2G11520)
Protein serine/threonine kinase, similar
to AtCRCK3 (calmodulin-binding
receptor-like cytoplasmic kinase
3,AT2G11520)
Similar to AtCRCK2 (calmodulinbinding receptor-like cytoplasmic kinase
2, AT4G00330)
Putative ortholog of AtXLG3 (Extra
Large GTP-binding protein 3,
AT1G31930)
-1.05
10.42
0.007
30 min
-1.18
6.76
0.025
30 min
-1.31
7.69
0.003
30 min
-1.20
9.34
0.007
30 min
-1.20
9.34
0.007
30 min
-1.10
8.08
0.004
30 min
-1.10
8.08
0.004
30 min
0.79
8.82
0.045
3h
-1.04
7.34
0.016
30 min and 3
h
-0.75
5.77
0.037
30 min
-0.89
8.61
0.008
30 min and 3
h
-0.78
4.79
0.006
30 min
-1.06
7.39
0.028
30 min
-1.34
9.22
0.005
30 min
-0.93
7.27
0.044
30 min
1.36
6.95
0.044
3h
0.63
9.92
0.038
3h
1.52
10.42
0.022
3h
1.50
8.84
0.039
3h
2.65
9.21
0.009
30 min and 3
h
-1.01
6.62
0.038
3h
1.31
10.92
0.019
30 min and 3
h
Nitric oxide and other
ROS
GRMZM2G366392
GRMZM2G125669
GRMZM2G048616
GRMZM2G067402
GRMZM2G121066
GRMZM2G134708
S-adenosylmethionine decarboxylase
proenzyme
Alternative oxidase 1, ortholog of
AtAOX1 (AT3G22370)
2-nitropropane dioxygenase, putative
ortholog of AT5G64250
Non-symbiotic hemoglobin (nsHb)
Mannose-6-phosphate isomerase,
putative ortholog of PMI1
(phosphomannose isomerase 1,
AT3G02570)
FAD dependent potassium ion transport,
similar to putative
monodehydroascorbate reductase
(AtMDAR1, AT3G52880)
GRMZM2G064106
L-ascorbate oxidase
-0.84
8.74
0.047
30 min
GRMZM2G140667
APx2, Cytosolic Ascorbate Peroxidase 2
0.98
7.22
0.027
3h
210
Table 7.4 (continued)
GRMZM2G057186
GRMZM2G131683
VTC2 (vitamin C defective 2), GDP-Lgalactose phosphorylase
glutaredoxin-related, DEP domain
electron carrier
0.59
9.50
0.034
-1.54
8.16
0.044
30 min and 3
h
30 min and 3
h
30 min and 3
h
GRMZM2G148387
Grx_C2.1 - glutaredoxin subgroup I
1.91
4.80
0.004
GRMZM2G441906
Grx_A2 - glutaredoxin subgroup III
-1.02
7.56
0.026
30 min
0.87
4.23
0.012
30 min and 3
h
-1.89
7.84
0.023
30 min
GRMZM2G032763
GRMZM2G058404
Glutaredoxin family protein,
translational initiation
Putative geranylgeranyl pyrophosphate
synthase
GRMZM2G142836
Quinolinate synthetase A
0.94
7.12
0.027
30 min
GRMZM2G136534
Peroxidase activity
-1.41
9.66
0.036
3h
GRMZM2G144153
Glutathione peroxidase
0.69
6.78
0.044
3h
30 min and 3
h
3h
GRMZM2G379252
Glutathione synthase
0.94
7.47
0.018
GRMZM2G408706
Violaxanthin de-epoxidase
1.12
5.11
0.019
GRMZM2G135722
Anthocyanidin 3-O-glucosyltransferase
0.96
4.17
0.018
30 min and 3
h
GRMZM2G043075
Transparent testa 12 protein, drug
transmembrane transporter activity
0.67
8.14
0.039
3h
1.72
7.43
0.004
30 min and 3
h
1.75
7.47
0.027
30 min and 3
h
1.28
6.79
0.035
3h
1.59
5.97
0.015
3h
-0.65
7.78
0.044
30 min
-1.19
7.51
0.021
30 min and 3
h
-1.08
7.70
0.039
3h
-0.62
4.58
0.036
3h
-1.89
9.04
0.027
30 min
-0.91
7.70
0.034
30 min
1.56
4.92
0.034
3h
-0.98
3.99
0.027
30 min
GRMZM2G031177
GRMZM2G170128
GRMZM2G078129
GRMZM2G174458
Transparent testa 12 protein, drug
transmembrane transporter activity
Transparent testa 12 protein, MATE
transporter, drug transmembrane
transporter activity
MATE transporter, drug transmembrane
transporter activity
MATE transporter, drug transmembrane
transporter activity
Cell wall
GRMZM2G073860
GRMZM2G137779
GRMZM2G115762
GRMZM2G135195
GRMZM2G149024
GRMZM2G166767
GRMZM2G115422
GRMZM2G104710
Purple acid phosphatase, putative
ortholog of AtPAP10 (AT2G16430)
Putative protein xyloglucan
galactosyltransferase, putative ortholog
of AtMUR 3 (AT2G20370),
KATAMARI1 (Oryza sativa,
loc_os03g05110)
Glycosyltransferase, putative ortholog
of AtXT2 (UDP-Xylosyltransferase 2,
AT4G02500)
Glycosyltransferase, putative ortholog
of AtGAUT4(Galacturonosyltransferase
4, AT5G47780)
Glycosyltransferase, putative ortholog
of AtGATL1 (polygalacturonate 4alpha-galacturonosyltransferase,
AT1G19300)
RHM1, 3-beta-hydroxy-delta5-steroid
dehydrogenase activity, steroid
biosynthesis and dTDP-4dehydrorhamnose reductase activity
extracellular polysaccharide
biosynthetic process
Putative ortholog of AT2G39980/rice
Loc_Os01g63480, anthranilate Nbenzoyltransferase-like or NHydroxycinnamyl transferase-like
Putative ZRP4 , O-methyltransferase
211
Table 7.4 (continued)
GRMZM2G025105
GRMZM2G014610
GRMZM2G430995
GRMZM2G332548
Cytoskeleton and vesicle
transport
GRMZM2G078725
Polygalacturonase inhibitor, putative
ortholog of ATPGIP1
(Polygalacturonase inhibitor 1,
AT5G06860)
Putative ortholog of ATNST-KST1
(nucleotide-sugar transmembrane
transporter1, AT4G39390)
Membrane xyloglucan
galactosyltransferase KATAMARI
Membrane xyloglucan
galactosyltransferase KATAMARI
Microtubule-associated protein
TORTIFOLIA1
2.00
5.74
0.015
3h
-0.76
6.88
0.038
3h
-1.19
7.51
0.021
-1.19
7.51
0.021
0.70
8.73
0.042
-0.98
4.85
0.030
3h
30 min and 3
h
30 min and 3
h
3h
GRMZM2G073888
Tubulin gamma-1 chain, gamma-3 chain
GRMZM2G045243
SAUR37-auxin-responsive,
microtubule-based process
2.82
5.98
0.001
30 min and 3
h
GRMZM2G176995
Putative ortholog of rice Copine 8
-1.08
7.54
0.014
30 min
GRMZM2G074735
GTPase activating protein
Putative RabGAP TBC domaincontaining protein
Putative ortholog of AtRAB11 (GTPase,
AT2G43130)
Prenylated Rab receptor, putative
ortholog of rice Prenylated RAB
Acceptor 1 (PRA1)
Putative ortholog of AtVAMP725
(protein vesicle-associated membrane
protein 725, AT2G32670)
Vesicle-mediated transport, putative
ortholog of AtVAMP711 (protein
vesicle-associated membrane protein
711, AT4G32150)
-1.71
8.21
0.016
-1.18
8.29
0.004
30 min
30 min and 3
h
-0.71
7.48
0.045
3h
1.14
8.70
0.022
30 min and 3
h
0.60
11.03
0.017
30 min and 3
h
0.91
4.50
0.022
3h
GRMZM2G157462
Dynamin-2A GTPase
0.40
7.99
0.046
3h
GRMZM2G097395
Nodulin-like, similar to AT3G01930
-1.23
7.47
0.027
30 min
GRMZM2G154460
Nodulin-like, similar to AT4G19450
0.74
6.51
0.031
GRMZM2G087144
AC197246.3_FG00
1
GRMZM2G147862
GRMZM2G104505
GRMZM2G027019
Nodulin-like protein
GRMZM2G076370
GRMZM2G085750
GRMZM2G107597
GRMZM2G305822
GRMZM2G050701
GRMZM2G157115
Nodulin-like, similar to AT4G19450
Early nodulin, similar to soybean early
nodulin 93
Membrane cytochrome c
oxidoreductase, similar to Arabidopsis
nodulin MtN3 family protein
Protein serine/threonine kinase,
ubiquitin ligase complex, similar to
AT5G57035
Protein kinase APK1B, similar to
AT2G07180
Protein serine/threonine kinase, similar
to AT2G07180
2.93
5.64
0.002
0.92
10.24
0.004
-1.42
6.49
0.029
30 min
-0.90
7.40
0.024
30 min and 3
h
-0.57
4.80
0.034
3h
-1.11
5.91
0.049
3h
30 min and 3
h
GRMZM2G158045
Protein serine/threonine kinase
-0.75
7.60
0.043
GRMZM2G063533
Protein serine/threonine kinase NAK
Ribosomal protein serine/threonine
kinase
Protein serine/threonine kinase, similar
to AT5G59700
-1.16
6.86
0.048
-0.55
7.52
0.044
-0.69
7.29
0.037
Protein binding
0.67
7.16
0.039
GRMZM2G055982
GRMZM2G442277
GRMZM2G381059
3h
30 min and 3
h
30 min and 3
h
30 min
30 min and 3
h
30 min and 3
h
30 min
212
Table 7.4 (continued)
GRMZM2G055957
GRMZM2G061537
GRMZM2G473411
Protein serine/threonine kinase, similar
to AtCRCK3 (calmodulin-binding
receptor-like cytoplasmic kinase
3,AT2G11520)
Protein serine/threonine kinase, similar
to AtCRCK3 (calmodulin-binding
receptor-like cytoplasmic kinase
3,AT2G11520)
Similar to AtCRCK2 (calmodulinbinding receptor-like cytoplasmic kinase
2, AT4G00330)
-1.06
7.39
0.028
30 min
-1.34
9.22
0.005
30 min
-0.93
7.27
0.044
30 min
Others
Transcription factor and
regulation
GRMZM2G156956
Putative ortholog of Arabidopsis mei2like protein 1 (AMT1, AT5G61960)
-0.95
5.61
0.038
30 min
GRMZM2G167018
NAC protein 21/22, transcription factor
-1.39
7.26
0.010
30 min
GRMZM2G038073
Putative ortholog of Arabidopsis NAC
domain containing protein 44 (anac044,
AT3G01600)
-1.42
5.13
0.004
30 min and 3
h
GRMZM2G340305
Putative ortholog of Arabidopsis NAC2
1.03
8.57
0.038
3h
GRMZM2G134073
NAC domain-containing protein
-0.74
7.07
0.047
30 min
GRMZM2G057466
Putative ortholog of Arabidopsis
Jumonji (AT5G46910)
-0.79
6.19
0.022
30 min
GRMZM2G002805
Transcription factor ZFP16-2
2.14
8.02
0.007
30 min and 3
h
GRMZM2G006707
global transcription factor group E
Putative protein transcription factor
ZFP16-2
Putative ortholog of rice nuclear
ribonucleoprotein A3, RNA recognition
motif (RRM)
Spotted leaf protein, putative protein
degradation ubiquitin E3 RING
0.65
7.43
0.048
3h
1.57
6.94
0.029
3h
-0.61
7.27
0.042
3h
-0.83
5.66
0.026
3h
GRMZM2G037422
Putative ubiquitin E3 RING
-1.47
6.26
0.013
GRMZM2G315431
Putative ubiquitin E3 RING
-1.03
6.53
0.017
GRMZM2G331208
Putative ubiquitin E3 RING
-1.62
4.74
0.004
AC226227.2_FG004
Putative ubiquitin E3 RING
-1.62
4.74
0.004
GRMZM2G084844
Putative ubiquitin E3 RING
-1.62
4.74
0.004
GRMZM2G050734
Putative ubiquitin E3 RING
-0.82
6.61
0.039
30 min
GRMZM2G452016
Putative ubiquitin E3 RING
0.73
7.41
0.008
3h
GRMZM2G312500
Putative ubiquitin E3 RING
0.75
7.07
0.027
30 min
GRMZM2G000071
Putative ubiquitin E3 RING
0.75
7.07
0.027
30 min
GRMZM2G469209
Putative ubiquitin E3 RING
0.75
7.07
0.027
30 min
GRMZM2G332135
Putative ubiquitin E3 RING
0.75
7.07
0.027
GRMZM2G073310
Putative ubiquitin E3 RING
-0.73
7.80
0.039
-0.95
7.48
0.004
30 min
30 min and 3
h
30 min and 3
h
-0.80
8.05
0.015
3h
GRMZM2G061626
GRMZM2G152526
Regulation and protein
degradation
GRMZM2G471733
GRMZM2G071277
GRMZM2G318408
Putative ubiquitin E3 RING,RING-H2
finger protein
Putative ubiquitin E3 RING, RING-H2
finger protein
30 min and 3
h
30 min and 3
h
30 min and 3
h
30 min and 3
h
30 min and 3
h
GRMZM2G303964
Putative ubiquitin E3 RING
-1.23
8.87
0.013
30 min and 3
h
GRMZM2G059042
Putative ubiquitin E3 RING
0.75
7.07
0.027
30 min
GRMZM2G478553
Putative ubiquitin E3 RING
-1.00
7.27
0.011
30 min
213
Table 7.4 (continued)
GRMZM2G037627
GRMZM2G057789
Kinases and phosphatases
6.03
0.011
3h
-1.29
7.43
0.023
30 min and 3
h
30 min
Putative ubiquitin E3 RING
-0.83
8.41
0.022
GRMZM2G134023
Putative ubiquitin E3 RING
-2.08
8.37
0.012
GRMZM2G005865
Putative ubiquitin E3 SCF F-BOX
0.56
9.45
0.031
30 min and 3
h
3h
GRMZM2G014022
Putative ubiquitin E3 SCF F-BOX
1.58
6.05
0.043
30 min
GRMZM2G095887
Putative ubiquitin E3 HECT
0.83
10.19
0.014
3h
GRMZM2G034622
Putative ubiquitin E3 HECT
0.83
10.19
0.014
3h
GRMZM2G079323
Protein phosphatase type 2A regulator
-0.88
6.41
0.028
30 min and 3
h
GRMZM2G163709
Phospholipase C activity
1.16
9.19
0.018
3h
GRMZM2G044382
Protein phosphatase type 2C
-0.73
7.96
0.033
3h
GRMZM2G108309
Protein phosphatase 2C
0.55
8.45
0.043
3h
GRMZM2G369912
Protein phosphatase 2A regulatory
subunit B
-0.60
5.85
0.043
30 min
GRMZM2G180430
DNA-binding protein phosphatase 2C
0.86
9.54
0.028
3h
1.14
9.01
0.006
30 min and 3
h
-1.01
8.57
0.007
30 min
30 min and 3
h
GRMZM2G137286
Putative ortholog of rice protein
phosphatase 2C (loc_os04g33080)
Putative ortholog of protein serine
threonine-protein phosphatase PP1
(loc_os01g24750)
GRMZM2G087186
Pyruvate decarboxylase 3
1.17
11.56
0.028
GRMZM2G164358
RHC1A
-0.50
7.46
0.043
3h
GRMZM2G054807
Avr9/Cf-9 rapidly elicited protein
Early response to dehydration 15-like
protein
-1.21
9.54
0.005
-1.87
8.95
0.009
30 min
30 min and 3
h
hypoxia induced protein
0.53
6.77
0.025
-1.67
4.98
0.014
30 min
GRMZM2G037189
GRMZM2G159691
GRMZM2G042756
GRMZM2G301860
GRMZM2G301485
GRMZM2G098696
Anthocyanin synthesis
0.83
GRMZM2G304010
GRMZM2G443509
Stress related
Putative ubiquitin E3 RING, RING-H2
finger protein ATL5F
Putative ubiquitin E3 RING, RING-H2
finger protein ATL1R
Dehydration-responsive elementbinding protein 1D
Dehydration responsive element binding
protein
Putative ortholog of rice heat shock
factor protein 4
heat shock factor protein, putative
ortholog of heat shock factor protein 7
(HSF7)
3h
1.42
6.77
0.006
30 min and 3
h
1.70
5.09
0.028
3h
0.88
5.92
0.030
3h
GRMZM2G010871
heat shock factor protein (HSF30)
1.21
6.15
0.006
3h
GRMZM2G080724
Putative ortholog of Arabidopsis
(HSP21)
1.16
5.47
0.015
3h
GRMZM2G180283
Anthocyanidin 3-O-glucosyltransferase
-1.84
6.22
0.006
30 min
GRMZM2G010468
Putative ortholog of Arabidopsis and
rice cinnamate-4-hydroxylase C4H
(AT2G30490,loc_os01g60450 )
0.94
5.36
0.011
3 hrs
GRMZM2G135722
Anthocyanidin 3-O-glucosyltransferase
0.96
4.17
0.018
30 min and 3
h
214
Putative ammonium transporter genes were retrieved by BLAST searches of the maize
genome using annotated ammonium transporters from rice (LI Bao-zhen, 2009) and Arabidopsis
in Genbank (Table 7.3). These ortholog predictions were validated by scanning for ammonium
transporter and/or transmembrane domains. Though there was no added ammonium in any
media, putative orthologs of six ammonium transporter genes from rice and Arabidopsis were
highly expressed in maize RH, with an ortholog of OsAMT1.2 (Sonoda et al., 2003)
(GRMZM2G175140) having the highest relative expression (Table 7.2). In previous studies, the
ammonium (NH4+) uptake transporter genes, Amt1.1 and Amt1.2 in tomato and Amt1.5 in
Arabidopsis, were preferentially expressed in RH after ammonium treatment (Lauter et al., 1996;
Von Wirén et al., 2000; Yuan et al., 2007). Interestingly, a probe recognizing two putative AMT
transporter genes with low expression in RH (GRMZM2G019806, GRMZM2G082343) had a
>2-fold change in expression at 30 min in AddN compared to MaintN (p = 6e-4).
The gene ZmPIP2, encoding an aquaporin required for water uptake, was highly
expressed in RH and was down-regulated by AddN. Previously it was demonstrated that upon
exposure to nitrate, maize can increase the mass flow of water into its roots by 50% which is
associated with increased nitrate uptake (Górska et al., 2010), though the increase was not shown
to be due to transcriptional activation at the whole root level (Górska et al., 2010). In the current
experiment, when roots were submerged in water upon N addition, there may have been
decreased need for mass flow of water causing the down-regulation of ZmPIP2.
Following N uptake, nitrate is converted to nitrite by nitrate reductase, followed by a
reduction to ammonia by nitrite reductase, also known as nitrite oxidoreductase (Wilkinson and
Crawford, 1993; Masclaux-Daubresse et al., 2010; Wang et al., 2010; Konishi and Yanagisawa,
2011). The gene encoding nitrate reductase, NIA1 (GRMZM2G133213), as well as the nitrate
215
reductase co-factors CNX3 and cytochrome b5 reductase (GRMZM2G157263,
GRMZM2G010238), were highly expressed in RH (Campbell and Kinghorn, 1990). A subunit
of nitrite reductase encoding ferredoxin (Campbell and Kinghorn, 1990) (GRMZM2G079381)
was similarly highly expressed in RH.
Molybdenum cofactor is the active compound at the catalytic site of nitrate reductase
(Mendel and Bittner, 2006). A gene encoding a molybdopterin synthase sulfurase/molybdenum
cofactor sulfurase (MOCS3), had a 50% increase in expression at 3 h in maize RH after nitrate
addition. This enzyme is also required for post translational modification of xanthine
dehydrogenase (Wollers et al., 2008), involved in the scavenging of ammonia from purine rings
under low nitrogen (Werner and Witte, 2011).
Following the N-reduction reactions, ammonia is then assimilated into glutamine as an
amido nitrogen followed by reductive transfer to 2-oxoglutarate to form two molecules of
glutamate via glutamate synthase. A gene encoding glutamine synthase, Gln5/Gln1-3
(GRMZM2G036464), was highly expressed in RH. Quantitative RT-PCR confirmed that
Gln5/Gln1-3 was highly expressed in RH, though it was also highly expressed in intact roots
(Figure 7.8). Expression of Gln5/Gln1-3 has previously been shown to positively correlate with
kernel number, while mutant gln5/gln1-3 plants have a 4-fold reduction in grain yield (Martin et
al., 2006). Gln5/Gln1-3 was previously shown to be expressed both in leaves and the maize root
epidermis (Martin et al., 2006).
Finally, the ammonia group from Gln is then removed by GOGAT (Lam et al., 1996), a
glutamine amidotransferases (GATase), and transferred onto new substrates that require nitrogen
groups including other amino acids. Three genes encoding GATases (GRMZM2G094304,
216
GRMZM2G379237, GRMZM2G393215) that may be involved in this process, were downregulated at both 30 min and 3 h following nitrate addition.
Amino acids must be transported from the roots to the rest of the plant. An (Okumoto et
al., 2004), was up-regulated in maize RH at 3 h after nitrate addition.
7.4.5.2 C/N Metabolism – Dof/Opaque 2/GCN Regulon
The transcription factor Dof2 was down-regulated at 30 min in RH following nitrate
addition. Maize Dof2 regulates genes involved in primary carbon assimilation, including
activating phosphoenolpyruvate carboxylase (pepcZm2A) and cytosolic orthophosophate
dikinase (cyppdk1) while repressing C4-PEPC which are required for the primary fixation of
CO2 in C4 photosynthesis (Yanagisawa, 2000). Consistent with the observed down-regulation of
its putative repressor Dof2, C4-PEPC-1 expression increased in RH by more than two-fold
following nitrate addition. The effect of Dof2 on carbon metabolism is antagonistic to the effect
of its ortholog Dof1 in both maize and Arabidopsis (Yanagisawa, 2000, 2004). The various Dof
proteins may regulate formation of the carbon skeletons required for amino acid biosynthesis
(Yanagisawa et al., 2004). Indeed, Dof1 overexpression was shown to improve the growth of
Arabidopsis under low N conditions (Yanagisawa et al., 2004) and to alter expression of multiple
nitrate uptake and assimilation genes (Tsujimoto-Inui et al., 2009). Furthermore, cis-acting
binding sites of Dof proteins were found overrepresented in co-expression clusters associated
with low nitrogen stress in Arabidopsis (Bi et al., 2007).
In maize endosperm, the Dof protein PBF interacts with the transcription factor Opaque 2
(O2) to regulate amino acid biosynthesis (Vicente-Carbajosa et al., 1997). In maize endosperm,
O2 has been shown to coordinate carbon with nitrogen metabolism (Hartings et al., 2011).
Interestingly we observed that O2 was up-regulated at 3 h following nitrate addition. Our results
217
thus appear to have identified a Dof/O2 regulon in RH that was previously only shown to exist in
endosperm to coordinate C/N metabolism in response to nitrate. Consistent with this model, an
O2-heterodimerizing protein was recently reported in the maize RH proteome (Nestler et al.,
2011).
Perhaps related to the Dof/O2 regulon, a gene in the glycolysis pathway, pyruvate kinase
(PK, GRMZM2G150098), was up-regulated in RH following nitrate addition. The maize PK
gene is a putative ortholog of Arabidopsis AtPK1 (AT5G08570) which was shown to have
increased expression in a Dof1 overexpression line (Yanagisawa, 2004).
An analysis of 24 Arabidopsis Dof gene promoters and 24 wheat Dof promoters showed
that they contain multiple cis-acting motifs including binding sites for AP2/ABI3-family
transcription factor RAV1 as well as for the R2R3-myb transcription factor P (Gaur et al., 2011).
Maize RAV1 was down-regulated in RH after nitrate addition. A recently duplicated paralog of
the maize P, ZmMYB-IF35, able to recognize the same DNA binding site as P, and previously
shown to be expressed in maize epidermal cells (Dias et al., 2003; Heine et al., 2007), was downregulated at 30 min / 3h in maize RH after nitrate addition.
Downstream, Dof proteins recognize a bipartite promoter, the endosperm box (E-box)
which contains a second motif, the GCN4 motif, that is recognized by O2 and other bZIP
transcription factors (Gaur et al., 2011). A putative ortholog of transcription factor GCN4
(AT3G54540), which is the primary transcriptional regulator in response to amino acid
starvation in yeast (Zhang et al., 2008), was up-regulated at 30 min in maize RH after nitrate
addition. Interestingly, promoters of amino acid biosynthetic enzymes in Arabidopsis have been
shown to contain both GCN4 and O2 binding motifs (Ghislain et al., 1994). This data suggests
the involvement of a Dof/O2/GCN4 regulon that acts in maize RH in response to nitrate.
218
7.4.6 Nutrition: Light, carbon and energy metabolism
In addition to fixed carbon being required for assimilatory amino acid biosynthesis,
nitrogen uptake itself is energetically expensive, requiring coordination of light and carbon
respiratory pathways (Nunes-Nesi et al., 2010; Feng et al., 2011). Interestingly, the ubiquitin
ligase gene CIP8 was highly up-regulated at 30 min and 3 h in RH following nitrate addition.
CIP8 is required for the degradation of HY5 in the dark; HY5 is a central light-activated
transcription factor that regulates thousands of genes required for photomorphogenesis (Hardtke
et al., 2002; Lee et al., 2007). HY regulates RH growth, as a hy5 mutant displays longer RH than
wild-type plants in Arabidopsis (Oyama et al., 1997). HY5 is also required for light-activated
expression of nitrate reductase, thus linking carbon with nitrogen metabolism (Jonassen et al.,
2008). There are three binding sites for HY5 in the promoter of the root-expressed nitrate
transporter gene NRT1.1 in Arabidopsis (Lee et al., 2007). Interestingly, we also found that a
putative ortholog of the rice protein phosphatase-1 (PP1, loc_os01g24750) gene was downregulated in the AddN treatment compared to the MaintN treatment. Using chemical inhibitor
studies, PP1 has been implicated as a candidate negative regulator of light regulation of nitrate
reductase perhaps via phytochrome, HY5 and photosynthesis (Sheen, 1993; Lillo, 2008). PP1
previously showed altered regulation during nitrate depletion in maize (Trevisan et al., 2011).
These data suggest the existence of a signaling pathway in RH coordinating light/dark signaling
with carbon and nitrogen metabolism.
Perhaps because RH may have been exposed to light, genes involved in the universal
regulation of plastids showed altered expression. S1FA, a DNA binding protein that is a negative
regulator of plastid ribosome protein S1 (RPS1), in turn required for ribosome binding to
mRNAs during translation (Zhou et al., 1995), was up-regulated in maize RH upon nitrate
219
addition. A gene encoding the plastidic 50S ribosome protein L27, required for the peptidyl
transferase reaction in prokaryotes, a key step of protein synthesis (Wower et al, 1988), was
down-regulated two-fold in maize RH 3 h after nitrate addition. L27 was shown to be involved in
stress responses in maize (Zhang et al., 2009). These genes potentially link nitrogen with plastid
function.
A glycolysis pathway gene, glyceraldehyde-3-phosphate dehydrogenase 1 (GAPC1,
GRMZM2G104632), was up-regulated in RH following nitrate addition. Maize GAPC1 was
annotated as a cytosolic enzyme in the maize genome, but analysis using ChloroP (Emanuelsson
et al., 2007) showed the existence of a chloroplast signal peptide (data not shown). Arabidopsis
plastidial GAPC1 is required for serine biosynthesis (Muñoz-Bertomeu et al., 2009) and thus
links carbon with nitrogen metabolism. The Arabidopsis plastidial GAPC1 is mainly expressed
in roots, where it also affects cell expansion (Muñoz-Bertomeu et al., 2009). Interestingly, the
Arabidopsis plastidial GAPC1 is also a determinant enzyme in the development of pollen tubes
(Muñoz-Bertomeu et al., 2009) which expand using tip growth similar to RH. Our expression
results are consistent with GFP images which show localized expression of plastidial GAPC1 in
Arabidopsis RH (Muñoz-Bertomeu et al., 2009).
In another related pathway, an alpha-type carbonic anhydrase (CA, GRMZM2G113165) ,
which catalyzes the interconversion of CO2 to bicarbonate and predicted to be a signal to the
mitochondrion (Emanuelsson et al., 2007), was strongly down-regulated at both 30 min and 3 h
upon nitrate addition. Alpha-type carbonic anhydrase is proposed to reduce respiratory-derived
CO2 levels in the roots to permit continued respiration (Dimou et al., 2009). In C4 plants, the
conversion by CA of CO2 to bicarbonate facilitates primary fixation by PEPC (Hatch and
Burnell, 1990).
220
Nitrate assimilation requires reductant which is generated by oxidative metabolism
including the pentose phosphate pathway; this in turn requires glucose-6-phosphate uptake into
plastids via the glucose phosphate translocator (Bowsher et al., 2007). Following nitrate
addition, maize RH showed up-regulation of glucose-6-phosphate translocator 2 (Bolstad, 2004).
A gene encoding a transketolase (GRMZM2G033208) required for the Calvin cycle and pentose
phosphate pathway, and previously shown to be induced by nitrate in Arabidopsis (Wang et al.,
2000), was up-regulated in maize RH following nitrate addition.
A maize gene encoding the beta-fructofuranosidase 1 precursor (GRMZM2G394450,
E.C. 3.2.1.256), an invertase required for sucrose breakdown (Sturm, 1999), was down-regulated
in RH following nitrate addition. The glycogen synthase kinase-3 gene MsK-3/GSK was downregulated at 3 h following nitrate addition. GSKs are a gene family previously shown in other
species to regulate carbohydrate metabolism and alter amino acid levels (Kempa et al., 2007) but
have also been shown to confer stress tolerance, regulate development and alter hormone
signaling (Yoo et al., 2006). Our results are consistent with a previous study that showed altered
Msk-3 expression in maize following nitrate treatments (Trevisan et al., 2011).
Nicotinamide adenine dinucleotide (NAD) is a critical cofactor for redox reactions and is
synthesized de novo from amino acids; when these are limiting, there is an alternative salvage
pathway which requires NICOTINATE PHOSPHORIBOSYLTRANSFERASE (NAPRT)
(Wang et al., 1997). An ortholog of Arabidopsis NAPRT2 (AT2G23420), was up-regulated at 3
h in maize RH upon nitrate addition.
Finally, the expression of a gene encoding Alternative Oxidase 1 (AOX1) increased by
three-fold in RH at 3 h following nitrate addition. AOX1 facilitates an alternative, less energygenerating route for electron transport in the mitochondria, reducing harmful ROS production
221
but also consuming sugars (Kaiser et al., 2007). AOX1a expression has been shown to modulate
the C/N balance and ratios of C-N metabolites in Arabidopsis, including amino acids (Watanabe
et al., 2010). Increased expression of AOX1 in maize RH upon nitrate addition was opposite to
Arabidopsis where expression of AOX1a was induced by low nitrate (Watanabe et al., 2010).
Meanwhile an increase AOX, as part of the respiration system, participates in the production of
ATP necessary for nutrient uptake (Millar et al., 2011).
7.4.6.1 Nutrition: Amino acid biosynthesis
In addition to the above genes involved in regulating the supply of energy and skeleton
precursors required for amino acid biosynthesis, several genes directly involved in amino acid
biosynthesis also showed altered regulation. A gene encoding 3-deoxy-7-phosphoheptulonate
synthase (E.C. 2.5.1.54), involved in phenylalanine, tyrosine and tryptophan biosynthesis (Jossek
et al., 2001), was up-regulated 3-fold at 30 min and 3 h following nitrate addition. A gene
encoding tryptophan synthase alpha subunit (E.C. 4.2.1.20), required for tryptophan biosynthesis
(Woehl and Dunn, 1999), was down-regulated 9-fold at 3 h following nitrate addition. Another
gene encoding phosphoserine transaminase (E.C. 2.6.1.52), involved in serine biosynthesis
(Pizer, 1963), was up-regulated by ~50% at 30 min following nitrate addition. A gene encoding
cysteine synthase (EC 2.5.1.47), required for cysteine biosynthesis, was up-regulated 3-fold at 30
min at 3 h following nitrate addition. Finally, a gene encoding 3-isopropylmalate dehydrogenase
(E.C. 1.1.1.85), involved in valine, leucine and isoleucine biosynthesis, was slightly up-regulated
at 3 h following nitrate addition.
7.4.6.2 Nutrition: Other Nutrients
Differential expression of transcription factors involved in the metabolism of other soil
nutrients was also observed. A gene (GRMZM2G090338) encoding sulfite reductase (SiR),
222
required for the assimilation of inorganic sulfate to sulfide and shown to affect nitrate
uptake/assimilation and amino acid levels (Khan et al., 2010), was up-regulated at 3h following
nitrate addition. The transcription factor PTF1, known to improve phosphate tolerance in maize
(Li et al., 2011), was down-regulated at both 30 min and 3 h in the AddN treatment compared to
MaintN. An ortholog of the Arabidopsis Purple Acid Phosphatase 10 (AT2G16430, PAP10),
showed a 50% decreased expression in maize RH after nitrate addition. The rice PAP10 ortholog
and additional Arabidopsis paralogs have shown altered expression under phosphate limitation in
Arabidopsis and have been speculated to facilitate P remobilization (Müller et al., 2007; Wang et
al., 2009). Interestingly, PAP10 was shown to be expressed during pollen tube development
(Wang et al., 2008) and identified as a component of the cell wall proteome (Bayer et al., 2006).
An ortholog of the Arabidopsis transcription factor PosF21 (Aeschbacher et al., 1991), which is
induced in response to K+ deficiency (Kang et al., 2004), was down-regulated at 30 min in
AddN. Finally, the myc transcription factor MYC7E, previously shown to be induced in maize
roots in response to iron starvation and to complement an iron-transport deficient yeast strain,
was down-regulated in the AddN treatment (Loulergue et al., 1998). This data may indicate coregulation of mineral nutrient uptake in maize RH, or that minerals in the AddN solution
stimulated altered RH gene expression.
7.4.6.3 Linking Nutrition with Root Hair Growth - TOR/MEI2/E2F Regulon
Ribosomal protein S6 kinase (RPS6 kinase or S6K) is considered a master regulator of
growth across eukaryotes, linking cell growth and proliferation to nutrient and oxygen
availability, by modulating the translation of selective mRNA transcripts (Williams et al., 2003;
Ma and Blenis, 2009). S6K is a substrate of the Target of Rapamycin (TOR) kinase; the TOR
signalling pathway couples energy and amino acid availability with protein translation capacity
223
(Ma and Blenis, 2009). Evidence demonstrating that S6K serves a similar function in plants
comes from the observation that Arabidopsis cells grown under nutrient limitation (glucose
starvation) require S6K for repression of cell proliferation (Henriques et al., 2010). Furthermore,
S6K shows altered expression during phosphate starvation in Arabidopsis (Müller et al., 2007).
Maize S6K, an ortholog of Arabidopsis S6K2 (AT3G08720, ATPK19), was down-regulated in
maize RH at 30 min and 3 h after nitrate addition. Interestingly, this kinase was previously
shown to be down-regulated 3 h after nitrate addition in Arabidopsis seedlings (Scheible et al.,
2004), to have altered expression during Arabidopsis pollen tube growth (Wang et al., 2008), and
to regulate epidermal root cell elongation and leaf trichome branching (Henriques et al., 2010).
Auxin has been identified as a major regulator of S6K in maize (Beltrán-Peña et al., 2002) which
shows a possible connection between the TOR/MEI2/E2F regulon and hormone signalling
(Dobrenel et al., 2011).
The Regulatory Associated Protein of TOR (RAPTOR) was shown to interact with the
Arabidopsis growth regulatory protein Arabidopsis-Mei2-Like 1 (AML1), a putative RNAbinding protein (Anderson and Hanson, 2005; Kaur et al., 2006). AML1 is hypothesized to be
another substrate of the TOR kinase (Anderson and Hanson, 2005), alongside S6K. An ortholog
of AML1 was down-regulated in maize RH 30 min upon nitrate addition. In addition to its role in
meiosis, expression of AML1 was previously detected in roots and found to affect root growth
(Kaur et al., 2006).
S6K and the TOR pathway also regulate degradation of cytoplasmic components via
autophagy to facilitate nutrient recycling during nutrient limitation (Díaz-Troya et al., 2008).
This process requires the autophagy kinase ATG1. An ortholog of Arabidopsis and rice ATG1
224
(AT3G51790, loc_os10g39870) and a putative ortholog of ATG18 (AT1G03380) were upregulated in maize RH at 3 h after nitrate addition (Díaz-Troya et al., 2008).
The TOR pathway also regulates mRNA degradation. In the TOR pathway, the CCR4NOT complex is a global regulator of gene expression (Collart, 2003), of which CCR4 is an
adenylase that accelerates mRNA degradation by degrading the polyA tail (Albig and Decker,
2001; Aslam et al., 2009). An ortholog of CCR4-NOT subunit 8 in rice (loc_os04g58810)
(Aslam et al., 2009) was down-regulated in maize RH at 30 min and 3h min/h after nitrate
addition. An ortholog of an Arabidopsis nuclear polyA polymerase (nPAP, AT4G32850) was upregulated in maize RH at 30 min and 3 h after nitrate addition.
The TOR pathway also regulates biogenesis of nutrient-rich ribosomes (Díaz-Troya et al.,
2008) and the TOR kinase complex interacts with the 60S ribosome (Xie and Guan, 2011). An
ortholog of the gene, Nonsense-Mediated mRNA Decay (NMD3, AT2G03820), which is a
protein required for export of the 60S ribosome subunit from the nucleus to the cytoplasm during
ribosome biogenesis (Ho et al., 2000), was up-regulated in maize RH at 3 h after nitrate addition.
A gene encoding the nuclear 60S ribosome L6 was up-regulated in maize RH at 30 min after
nitrate addition by two-fold.
Finally, SK6 negatively regulates plant cell division in part by interacting with the E2FRetinoblastoma-related 1 (RBR1) transcription factor cascade (Ma and Blenis, 2009). E2F
controls entry into S phase of the cell cycle by inducing the transcription of genes required for
DNA replication and cell cycle progression (Johnson et al., 1993). Interestingly, a putative E2F2
gene (GRMZM2G052515) was the only transcription factor up-regulated at 30 min in maize RH
after nitrate supplementation. E2F has been shown to have 334 gene targets in Arabidopsis
(Naouar et al., 2009), including many genes involved in nitrate assimilation including nitrate
225
reductase and glutamine synthetase as well as genes involved in N-requiring nucleotide
metabolism thus connecting cell division and nitrogen (Vlieghe et al., 2003). E2F cis-regulatory
elements may also help coordinate nitrate and hormone signaling (Nero et al., 2009).
Overexpression of an atypical ortholog of E2F called E2Ff was shown to increase RH length in
Arabidopsis (Ramirez-Parra et al., 2004).
7.4.7 Putative Genes Involved in Root Hair Growth
7.4.7.1 Growth: Root Hair Development
The Roothairless3 gene (RTH3), belonging to the COBRA family of genes implicated in
cell expansion and cell wall formation (Hochholdinger et al., 2008), was down-regulated at 30
min and 3 h following nitrate addition. The maize rth3 mutant was previously shown to be
defective in RH elongation and is expressed in RH-forming epidermal cells and in lateral root
primordia (Hochholdinger et al., 2008).
As noted earlier, the ubiquitin ligase CIP8, a negative regulator of light-activated
transcription factor HY5, was highly up-regulated upon nitrate addition. We note CIP8 in this
section because a hy5 mutant was shown to have two-fold longer RH in Arabidopsis,
demonstrating that HY5 can regulate the inhibition of RH elongation (Oyama et al., 1997). This
result suggests that up-regulation of CIP8 may help mediate the previously observed increase in
RH elongation in maize under high nitrate (Gaudin et al., 2011; Gaudin et al., 2011).
In addition to the above RH elongation genes, four regulators of maize leaf epidermal
identity were shown to have altered regulation in RH upon nitrate addition, including Liguleless
3 (LG3, up-regulated at 3 h in AddN) (Muehlbauer et al., 1997), Liguleless 2 (LG2, downregulated at 30 min in AddN) (Walsh et al., 1998; Walsh and Freeling, 1999), and Rough Sheath
1 (RS1, up-regulated at 3 h in AddN) (Becraft and Freeling, 1994). Mutant lg3 and rs1 sectors
226
were previously shown to alter leaf macrohair development (Becraft and Freeling, 1994;
Muehlbauer et al., 1997). Leaf trichome development has previously been shown to share many
signaling components in common with root hair development (Ishida et al., 2008).
227
Table 7.5: Hormone-related genes that are differentially expressed in root hairs at 0.3 mM versus
3 mM nitrate at 30 min and 3 h following addition of liquid root hair media (RHM).
Hormone
Gene
Annotation
Fold
Change
(Log2)
Average
relative
expression
Pvalue
Time point
comparison
Abscisic acid
GRMZM2G117164
Homeobox-leucine zipper protein ATHB-6
-1.32
5.76
0.006
30 min
GRMZM2G009326
FIP1, response to freezing
G-protein coupled receptor protein signaling
pathway
1.24
7.34
0.016
30min and 3 h
-0.90
7.74
0.017
30min and 3 h
GRMZM2G106819
GRMZM2G417954
Viviparous-14 (VP14)
-0.92
5.93
0.020
30 min
GRMZM2G066197
Unknown protein
-1.10
6.35
0.023
30 min
GRMZM2G114153
ABA-responsive protein-related similar AtFIP1
-0.70
5.90
0.024
30 min
GRMZM2G018336
Transcription factor, putative ortholog of rice
RAV1 ( loc_os01g49830)
-1.73
5.91
0.034
3h
GRMZM2G154987
Defense response
-0.67
6.06
0.034
30 min
GRMZM2G106622
ABA-responsive protein
2.30
9.40
0.038
3h
GRMZM2G003937
Unknown protein
-0.98
5.00
0.038
30min and 3 h
GRMZM2G092125
Aquaporin, plasma membrane intrinsic protein2
(ZmPIP2-2)
-1.25
9.01
0.046
30 min
Serine/threonine kinase-like protein
Putative ortholog of AtADC2 (arginine
decarboxylase 2, AT4G34710)
-1.01
4.63
0.048
30 min
0.70
6.95
0.033
3h
GRMZM2G045243
SAUR37 auxin-responsive
2.82
5.98
0.001
30min and 3 h
GRMZM2G091540
Metabolic process, hydrolase activity
-3.01
5.54
0.004
30min and 3 h
GRMZM2G479423
Aldo-keto reductase family 1, member B1
1.09
11.86
0.005
30min and 3 h
GRMZM2G039443
Unknown protein
1.17
6.50
0.008
30min and 3 h
GRMZM2G054028
Unknown protein
1.54
9.96
0.024
3h
GRMZM2G146108
FIP1 response to freezing
-1.40
5.94
0.028
30min and 3 h
1.79
8.67
0.033
3h
0.95
3.80
0.038
3h
0.55
6.85
0.048
3h
1.20
8.29
0.023
30min and 3 h
1.81
7.32
0.041
3h
0.51
7.34
0.044
3h
-0.95
7.48
0.004
30min and 3 h
-0.80
8.05
0.015
3h
GRMZM2G026406
GRMZM2G396553
Auxin
GRMZM2G095280
GRMZM2G024315
GRMZM2G142379
GRMZM2G005024
GRMZM2G179063
GRMZM2G157836
Indole-3-acetate beta-glucosyltransferase (IAAGlu synthetase)
Auxin-induced protein PCNT115,
oxidoreductase activity
Response to freezing
Orange pericarp 2 fragment, TSB1 (Tryptophan
synthase beta-subunit 1)
Indole-3-acetate beta-glucosyltransferase (EC
2.4.1.121) (IAA-Glu synthetase)
Putative adenylyltransferase and sulfurtransferase
MOCS3
Brassinoster
oids
GRMZM2G071277
GRMZM2G318408
Putative ubiquitin E3 RING, RING-H2 finger
protein
Putative ubiquitin E3 RING, RING-H2 finger
protein
Cytokinins
GRMZM2G009406
Dof2, zinc finger protein MNB1A
-0.65
5.86
0.037
30 min
GRMZM2G041699
Cytokinin-O-glucosyltransferase
3.02
7.69
0.001
30min and 3 h
GRMZM2G007012
Cytokinin-O-glucosyltransferase
-0.56
4.88
0.027
30 min
228
Table 7.5 (continued)
Ethylene
GRMZM2G169654
RAV1 ethylene-responsive transcription factor
Ethylene-responsive transcription factor,
response to freezing
-1.41
7.81
0.002
30min and 3 h
1.56
7.09
0.004
30min and 3 h
GRMZM2G307152
Transcription factor TINY
2.19
5.86
0.005
30min and 3 h
GRMZM2G301860
AP2/EREBP dehydration responsive
transcription factor activity
1.42
6.77
0.006
30min and 3 h
GRMZM2G164591
AP2/EREBP transcription factor
-1.21
9.77
0.009
30min and 3 h
0.67
8.52
0.010
3h
-0.88
8.56
0.011
30 min
GRMZM2G474326
GRMZM2G171569
GRMZM2G052720
Transcription factor activity, cell adhesion, actin
cytoskeleton
AP2/EREBPethylene-responsive transcription
factor, response to freezing
GRMZM2G040734
Unknown protein
-1.39
5.33
0.018
30min and 3 h
GRMZM2G020054
Transcription factor activity
-0.94
8.21
0.022
30min and 3 h
0.82
4.69
0.024
3h
0.78
8.13
0.025
3h
-1.01
4.99
0.030
30min and 3 h
-0.84
4.04
0.031
30min and 3 h
-0.64
4.35
0.042
30min and 3 h
1.08
7.07
0.044
30min and 3 h
-0.58
8.68
0.045
30min and 3 h
GRMZM2G076896
GRMZM2G121208
GRMZM2G369472
GRMZM2G103085
GRMZM2G000520
GRMZM2G175797
AP2/EREBP Ethylene-responsive transcription
factor
Similar to Arabidopsis and rice RTE1
(REVERSION-TO-ETHYLENE
SENSITIVITY1)
AP2/EREBP Ethylene-responsive transcription
factor
AP2/EREBP ethylene-responsive transcription
factor, response to freezing
AP2/EREBP transcription factor, response to
freezing
Iron binding oxidoreductase
GRMZM2G055180
Ethylene-responsive transcription factor,
response to freezing
Ethylene-responsive transcription factor
-0.86
6.76
0.046
3h
GRMZM2G089995
Ethylene-responsive transcription factor
-0.66
8.07
0.046
30min and 3 h
GRMZM2G131281
AP2/EREBP Ethylene-responsive transcription
factor
1.14
9.54
0.046
3h
GRMZM2G069146
AP2/EREBP transcription factor
-0.83
7.03
0.047
30 min
GRMZM2G164591
Putative ortholog of AtERF7
-1.21
9.77
0.009
30min and 3 h
GRMZM2G344388
Serine/threonine kinase activity MAP Kinase
Kinase, similar to AtMKK9 (AT1G73500)
-1.43
8.92
0.014
30min and 3 h
GRMZM2G051619
Gibberellin 2-oxidase 1 (GA2ox)
-1.38
6.38
0.007
30min and 3 h
GRMZM2G173630
Putative GID1-like gibberellin receptor
-0.88
8.57
0.028
30 min
0.67
7.10
0.025
3h
1.07
7.78
0.037
3h
-0.90
7.62
0.013
30 min
-1.13
8.67
0.006
30min and 3 h
-0.88
8.57
0.028
30 min
1.05
8.52
0.009
3h
-0.96
6.49
0.016
30 min
GRMZM2G174347
Gibberellins
GRMZM2G091397
GRMZM2G062019
GRMZM2G031447
GRMZM2G301934
GRMZM2G173630
GRMZM2G163427
GRMZM2G431309
Putative ortholog of rice gibberellin-insensitive
dwarf protein 1
Gibberellin receptor GID1L2|metabolic
process|hydrolase activity
Hydrolase putative ortholog of Pinus radiata
MC3, AtCXE17 (AT5G16080)
Hydrolase putative ortholog of Pinus radiata
MC3, AtCXE18 (AT5G23530)
Putative GID1-like gibberellin receptor, putative
ortholog of AtGID1C (AT5G27320)
Putative ortholog of scarecrow-like transcription
factor 9 (SCL9, AT2G37650)
Chitin-inducible gibberellin-responsive protein,
Putative ortholog of scarecrow-like transcription
factor 5 (SCL5, AT1G50600)
GRMZM2G061695
Gibberellin responsive 1, ZmGR2c
-1.44
8.52
0.044
30min and 3 h
GRMZM2G033098
Allene oxide synthase (ZmAOS)
-1.05
8.74
0.030
30 min
Jasmonates
229
Table 7.5 (continued)
GRMZM2G106303
12-oxo-phytodienoic acid reductase1 (ZmOPR-1)
2.05
10.10
0.010
30min and 3 h
GRMZM2G087192
12-oxo-phytodienoic acid reductase5 (ZmOPR-5)
1.63
10.88
0.016
30min and 3 h
GRMZM2G000236
12-oxo-phytodienoic acid reductase2 (ZmOPR-2)
1.35
10.08
0.023
3h
GRMZM2G070092
Lipoxygenase7
-1.31
5.61
0.046
30 min
GRMZM2G159179
CYP94C1 monooxygenase activity
MYC transcription factor, putative ortholog of
JAI1 (AT1G32640)
-1.25
4.30
0.039
30 min
-1.09
5.38
0.024
30 min
GRMZM2G145458
ZIM motif family protein
-1.63
5.48
0.014
30min and 3 h
GRMZM2G145412
ZIM motif family protein
-2.60
7.76
0.005
30min and 3 h
GRMZM2G343157
ZIM motif family protein
-2.18
6.20
0.004
30min and 3 h
GRMZM2G036351
ZIM motif family protein
-1.47
9.01
0.017
30min and 3 h
GRMZM2G036288
ZIM motif family protein
-2.01
4.71
0.024
30 min
GRMZM2G126507
ZIM motif family protein
-1.01
7.66
0.025
30min and 3 h
GRMZM2G445634
ZIM motif family protein
-1.23
9.45
0.028
30min and 3 h
GRMZM2G173596
ZIM motif family protein
-1.99
5.87
0.040
30 min
GRMZM2G115357
IAA24 - auxin-responsive Aux/IAA family
member
-1.06
8.19
0.028
30min and 3 h
GRMZM2G141535
Aldehyde oxidase-1 (AO-1)
0.64
10.35
0.039
3h
1.36
6.95
0.044
3h
-1.02
9.20
0.042
30 min
GRMZM2G049229
Cross-talk
GRMZM2G429113
GRMZM2G096171
Putative ortholog of AtXLG3 (extra-large GTPbinding protein 3, AT1G31930)
putative ortholog of AtARR3, two-component
response regulator activity
GRMZM2G139284
Transcription factor MYB94
0.91
5.97
0.004
3h
GRMZM2G051256
Transcription factor MYB-IF35
-0.78
6.32
0.034
30min and 3 h
GRMZM2G127857
Transcription factor MYB39
-0.86
5.66
0.005
30 min
230
7.4.7.2 Growth: Phytohormones
Auxin and ethylene (Tanimoto et al., 1995; Rahman et al., 2002; Lee and Cho, 2009)
along with jasmonic acid (Zhu et al., 2006) and abscisic acid (Bai et al., 2007; Bai et al., 2009)
have all been shown to affect RH elongation and/or initiation. The important differentially
expressed hormone related genes are listed in Table 7.5.
7.4.7.2.1
Auxin
Continuous auxin influx has previously been shown to be required for maintained RH
elongation (Jones et al., 2009) perhaps by promoting epidermal cell wall loosening (Schopfer,
2001). A gene encoding an aldehyde oxidase (EC 1.2.3.1), ZmAO-1 (Sekimoto et al., 1997), was
highly expressed in RH and up-regulated at 3 h after nitrate addition (AddN). Aldehyde oxidase
has been shown to be required in the final steps of both indole-3-acetic acid (IAA) and ABA
biosynthesis, specifically in the conversion of indole-3-acetaldehyde to IAA and abscisic
aldehyde (ABAld) to ABA (Sekimoto et al., 1997). ZmAO-1 was previously shown to be most
highly expressed in roots (Sekimoto et al., 1997) and its expression affected by nitrogen (Barabás
et al., 2000). Increased ZmAO-1 catalyzed production of IAA in RH would be consistent with
increased RH elongation observed upon nitrate addition (Barabás et al., 2000; Gaudin et al.,
2011; Gaudin et al., 2011). As noted above, MOCS3, which encodes a molybdopterin synthase
sulfurase, showed altered regulation in maize RH upon nitrate addition; this was of interest here
as the enzyme is also required for post translational modification of aldehyde oxidase (Wollers et
al., 2008). Orange Pericarp 2 (ORP2), a gene encoding tryptophan synthase beta-subunit 1
(TSB1) (Wright et al., 1991), was highly expressed in RH and was up-regulated two-fold at 30
min and 3 h upon nitrate addition. In the process of making tryptophan, tryptophan synthase
expression consumes indole, a precursor of auxin (Kriechbaumer et al., 2006), and thus high
231
expression of TSB1 in RH would decrease IAA levels (Wright et al., 1991). Finally, a gene
encoding indole-3-acetate beta-glucosyltransferase (IAA-glucose-synthase), an enzyme
responsible for modulation of active auxin levels by glucose conjugation (Leznicki and
Bandurski, 1988), showed a two-fold increase in expression in RH 30 min after nitrate addition.
In addition to genes affecting auxin levels, IAA24, a transcription factor mediating auxin
signalling (Song et al., 2009), was down-regulated at 30 min and 3 h in response to AddN.
Furthermore, the auxin-response gene SAUR37, part of the small auxin-up RNA family which
encodes Ca2+/calmodulin-binding protein (Jain et al., 2006), was up-regulated >4-fold in
response to AddN at both 30 min and 3 h. As noted earlier, calcium signalling is required for RH
growth (Kim et al., 2006; Monshausen et al., 2007; Monshausen et al., 2008; Takeda et al.,
2008). A paralog of SAUR37, SAUR39, was previously shown to have altered expression in
response to nitrate shifts in rice (Kant et al., 2009).
7.4.7.2.2
Ethylene
Ethylene can induce RH formation (Tanimoto et al., 1995) and increase RH elongation
(Pitts et al., 1998) the latter by stimulating ROS production (Jung et al., 2009). A gene encoding
the Mitogen Activated Protein Kinase 9 (MKK9), previously shown to activate the transcription
of genes encoding ethylene biosynthesis enzymes (Xu et al., 2008), was down-regulated by
AddN at both 30 min and 3 h. In addition, the ortholog of Arabidopsis RTE1 (REVERSION-TOETHYLENE-SENSITIVITY-1), a protein which interacts with the ethylene receptor ETR1 to
negatively modulate ethylene signaling (Resnick et al., 2006), was up-regulated at 3 h following
nitrate addition. Finally, an ortholog of the Arabidopsis gene, TINY, which encodes an
AP2/ethylene-responsive element binding factor (ERF) (Wilson et al., 1996), was up-regulated
four-fold at 30 min and 3 h upon nitrate addition. Overexpression of TINY causes a partial
232
classic ethylene constitutive triple response associated with decreased epidermal cell size
(Wilson et al., 1996).
7.4.7.2.3
Jasmonic acid
In Arabidopsis, exogenous methyl jasmonate (MeJA) has been shown to increase RH
initiation and branching, and reduce RH elongation by acting through ethylene (Zhu et al., 2006).
MeJA-induced RH branching was further enhanced by ammonium (Yang et al., 2011). At least,
two genes required for jasmonic acid (JA) synthesis, an allene oxide synthase (AOS) and
Tasselseed 1 (Ts1), were down-regulated at 30 min by 2 to 2.5 fold. AOS gene encodes a key
cytochrome P450 enzyme in JA biosynthesis (Song et al., 1993); Ts1 encodes a lipoxygenase
hypothesized to be required for JA biosynthesis (Acosta et al., 2009). At the opposite end of the
spectrum, a gene required for JA degradation, encoding a cytochrome P450 ortholog of
Arabidopsis CYP94C1 (Koo et al., 2011), showed two-fold decreased expression in RH upon
nitrate addition. In addition, three genes encoding 12-oxophytodienoate reductase (OPR),
required for JA biosynthesis (Tani et al., 2008), showed altered expression in maize RH 30 min
and 3 h after nitrate addition.
7.4.7.2.4
ABA
ABA has been shown to alter RH elongation (Bai et al., 2007; Bai et al., 2009) perhaps
by inducing reactive oxygen species formation (Bai et al., 2007). The putative ortholog of
AtERF7(Arabidopsis ethylene-responsive element binding factor 7), a transcriptional repressor
that mediates ABA responses (Song et al., 2005), was down-regulated at 30 min and 3 h
following nitrate addition. In Arabidopsis, AtERF7 triggers PERK4 (proline-rich extensin-like
receptor kinase) required for ABA-mediated stimulation of root cell elongation including root
hairs by altering Ca2+ homeostasis (Bai et al., 2009). Viviparous-14 (Vp14), which encodes 9233
cis-epoxycarotenoid dioxygenase (NCED), the rate-limiting step in ABA biosynthesis (Tan et al.,
1997; Messing et al., 2010), was down-regulated at 30 min following nitrate addition. Orthologs
of Arginine Decarboxylase 2 (AtADC2) and Ornithine Decarboxylase (Loc_Os09g37120),which
catalyze putrescine biosynthesis (Cuevas et al., 2008), also showed altered regulation in maize
RH. Interestingly, putrescine stimulates NCED (Cuevas et al., 2008). AtADC2 is activated by
both nitric oxide and ROS (Ahlfors et al., 2009) which in turn regulate RH elongation (Foreman
et al., 2003; Shin et al., 2005; Carol and Dolan, 2006; Kim et al., 2006; Takeda et al., 2008) as
already noted. Finally, the maize ortholog of the Arabidopsis homeodomain transcription factor
ATHB6, which acts as a negative regulator of ABA signaling (Himmelbach et al., 2002), was
reduced >2 fold by nitrate addition. ATHB-6 was previously found associated with K+deficiency in Arabidopsis (Himmelbach et al., 2002).
7.4.7.2.5
Gibberellic acid (GA)
GA has classically been shown to promote cell expansion in general, and has also been
shown to regulate RH expansion under phosphate starvation via a ROS-dependent mechanism
(Jiang et al., 2007; Achard et al., 2008). Five genes encoding putative orthologs of the rice
gibberellin receptor, Gibberellin Insensitive Dwarf1 (GID1) (Ueguchi-Tanaka et al., 2005),
showed altered gene expression in RH after nitrate addition: GRMZM2G091397,
GRMZM2G062019 were up-regulated by 50% and two-fold at 3 h; GRMZM2G301934 was
down-regulated two-fold at 30 min and 3 h; GRMZM2G173630 and GRMZM2G031447 were
down-regulated almost two-fold 30 min. GID1 perception of GA causes degradation of the
DELLA repressor protein SLR1, which is mediated by the F-box protein GID2 in rice (Gomi et
al., 2004). The F-box protein GID2 was down-regulated in maize RH by two-fold at 3 h after
nitrate addition. The GA responsive gene ZmGR2c, previously identified as the single clone
234
isolated from a differential display experiment comparing wild-type maize and GA-insensitive
mutant D8 (Ogawa et al., 1999), was down-regulated three-fold in maize RH at 30 min and 3 h
after nitrate addition. Two orthologs of GRAS family members OsCIGR2/AtSCL5
(Loc_Os07g39470/ AT1G5060) and OsCIGR2/AtSCL9 (Loc_Os11g47870/AT2G37650),
containing VHIID domains implicated in cell signalling (Pysh et al., 1999; Day et al., 2004),
showed altered regulation in maize RH after nitrate addition; the former was down-regulated
two-fold at 30 min and the latter was up-regulated 50% at 3 h. Finally, a gene encoding the
putative GA inactivation enzyme, gibberellin 2-oxidase 1 (GA2ox) (Song et al., 2011), was
down-regulated <three-fold in maize RH at 30 min and 3 h following nitrate addition.
7.4.7.2.6
Cytokinin
A cytokinin resistant mutant in Arabidopsis was previously shown to lack RH perhaps by
altering auxin signaling (Laxmi et al., 2006). However, information concerning the role of
cytokinin in RH development is limited. Nitrate has been shown to induce the accumulation of
cytokinin in maize roots (Sakakibara et al., 1998). A putative ortholog of the cytokinin response
regulator ARR3 was down-regulated by two-fold 30 min after nitrate addition. In two earlier
studies of nitrate-starved Arabidopsis, expression of ARR3 (AT1G59940) in leaves and whole
seedlings was shown to be altered by nitrate (Taniguchi et al., 1998; Scheible et al., 2004). Two
genes encoding enzymes that catalyze the O-glucosylated storage form of cytokinin, cytokininO-glucosyltransferase (GRMZM2G041699, GRMZM2G007012) (Sakakibara, 2006), showed
altered regulation upon nitrate addition in RH.
7.4.7.3 Growth: G-protein signals interacting with hormones and NADPH oxidase
Several maize G-signaling proteins were reported to be expressed in the maize RH
proteome (Nestler et al., 2011). Here we found that an ortholog of the Arabidopsis Extra Large
235
GTP-binding protein XLG3 which encodes a G-protein alpha subunit at its C-terminus (Ding et
al., 2008), was up-regulated two-fold in RH at 3 h following nitrate addition. XLG3 has been
implicated in regulating root cell size and is involved in auxin transport and ethylene signalling
(Pandey et al., 2008). In Arabidopsis, xlg3 mutants have altered expression of the GTP-binding
motif-containing Root Hair Defective 3 (RHD3) and the NADPH oxidase-encoding Root Hair
Defective 2 (RHD2) as well as the auxin efflux carriers PIN2, PIN4 and PIN7 (Pandey et al.,
2008), all of which have been shown to regulate RH elongation (Wang et al., 1997; Takeda et al.,
2008; Ganguly et al., 2010). Interestingly, a putative geranylgeranyl pyrophosphate synthase
(GGPP synthase, GRMZM2G058404) showed decreased expression in RH upon nitrate addition.
Though GGPP molecules are building blocks for the terpenoid pathway, geranylgeranyl moieties
have also been shown to post-translationally regulate ROP/RAC GTPases involved in plant tip
growth (Yalovsky et al., 2008).
7.4.7.4 Growth: Reactive Oxygen Species (ROS)
Nitrate deficiency has been shown to cause an increase in ROS production in roots
involving the NADPH oxidase-encoding RHD2 (Shin et al., 2005). RHD2 promotes ROS
formation which in turn has been shown to promote polarized RH growth (Libault et al., 2010),
perhaps by loosening of non-tip epidermal cell walls (Schopfer, 2001). Several genes involved in
ROS scavenging were previously reported to be expressed in the maize RH proteome (Nestler et
al., 2011). Here, more than 17 genes encoding proteins reported to be involved in ROS
scavenging were differentially expressed in RH upon the addition of nitrate. First, as already
noted, a gene encoding Alternative Oxidase 1 (AOX1) increased in expression in RH following
nitrate addition; AOX1 has been shown to reduce ROS levels in mitochondria (Blokhina and
Fagerstedt, 2010). A gene encoding GDP-L-galactose phosphorylase (VTC2), an ortholog of
236
Arabidopsis VTC5 which is involved in L-ascorbate synthesis (Linster and Clarke, 2008), was
up-regulated by 50% at 30 min and 3 h following the addition of nitrate. Ascorbate is a critical
ROS scavenging molecule (Blokhina and Fagerstedt, 2010). A putative ortholog of Arabidopsis
phosphomannose isomerase 1 (PMI1), required for ascorbic acid biosynthesis (Maruta et al.,
2008), was down-regulated two-fold at 3 h following nitrate addition. A gene encoding ascorbate
peroxidase 2 (APX2), an H2O2 scavenger in the cytosol and chloroplast (Pinhero et al., 1997),
was up-regulated by two-fold at 3 h following nitrate addition. APX2 was previously shown to
be root specific in maize (Pinhero et al., 1997), and an APX ortholog was induced in tomato
roots by auxin (Tyburski et al., 2008), which was already noted can also promote ROS
production (Carol and Dolan, 2006). A gene encoding ascorbate oxidase (GRMZM2G064106),
required for recycling of L-ascorbate, was down-regulated two-fold at 30 min following nitrate
addition. Ascorbate oxidase is active in the apoplast, and amongst its various roles has been
implicated in cell elongation (Kato and Esaka, 2000; De Tullio et al., 2004). Interestingly the
putative Arabidopsis ortholog of ascorbate oxidase (AT4G39830) was expressed in the pollen
tube, a cell type that experiences tip growth (Wang et al., 2008). Another maize gene,
GRMZM2G134708, encoding a potassium transport protein, was up-regulated by 2.5-fold at 30
min and 3 h after nitrate addition; by regulating matrix volume, K+ import into the mitochondria
has been shown to indirectly prevent ROS production (Blokhina and Fagerstedt, 2010). The
predicted peptide sequence of this gene shares 69% similarity (BLAST, data not shown) to a
monodehydroascorbate reductase (MDAR1) which encodes the last step in the transfer of the
hydroxide peroxide electron to NADH/NADPH (nicotinamide adenine dinucleotide phosphate)
in the peroxisome (Lisenbee et al., 2005). A gene encoding quinolinate synthetase, an enzyme
required for the conversion of L-aspartate to NAD (Kato and Esaka, 2000), a redox carrier that
237
also acts as an electron acceptor in photosynthesis and is involved in ABA signalling, oxidative
stress and senescence in Arabidopsis (Schippers et al., 2008), showed ~two-fold increased
expression in RH upon nitrate addition; however this pathway is thought to be a minor pathway
for NAD biosynthesis in maize (Tarr and Arditti, 1982; Katoh et al., 2006). Violaxanthin deepoxidase (EC 1.10.99.3, GRMZM2G408706), part of the xanthophyll cycle involved in ROS
scavenging (Niyogi et al., 1998), was up-regulated two fold at 3 h following nitrate addition.
Four genes encoding glutaredoxins, small antioxidant enzymes, were identified with differential
expression in RH upon nitrate addition, including GRMZM2G131683 which has a DEP protein
domain, shown to be required for G-protein signalling (Martemyanov et al., 2003; Chen et al.,
2006). This gene may link ROS signalling with cGMP signalling, both which have been shown
to regulate RH elongation (Carol and Dolan, 2006).
7.4.7.5 Growth: Calcium Signaling
ROS activates Ca2+ permeable channels which generates an internal Ca2+ gradient
required for tip growth (Yalovsky et al., 2008; Libault et al., 2010). In turn, calcium signalling is
required for polarized RH growth. Four maize calcium-dependent protein kinases (CDPKs)
showed decreased expression in RH 30 min after nitrate addition (see Table 7.4). CDPKs have
previously been shown to be required for calcium signalling in response to stress, hormones, root
hair mediated nodule formation and polarized growth of pollen tubes (Cheng et al., 2002).
Furthermore >28 genes that bind to calcium or to calcium activated calmodulin were identified
as differentially expressed in RH upon nitrate addition (Table 7.4). Several of these genes are
described above or below, including ARF-GAP domain 11, Copines, SNAREs and the putative
ortholog of Arabidopsis CRK2.
238
7.4.7.6 Growth: Vesicle Trafficking
Tip growth requires Golgi-synthesized cell wall and lipid components to be delivered via
vesicles and targeted to the growing tip (Kost, 2008; Nielsen et al., 2008). At the growing tip, the
vesicles fuse with the plasma membrane to deliver their cargo. Vesicle trafficking is facilitated
by small GTPases, including RAB and ARF (ADP-ribosylation factor) subfamilies, that cycle
between an active GTP-bound form and an inactive GDP-bound form (Kost, 2008; Nielsen et al.,
2008). In their active form, the GTPases recruit protein machinery required for the tethering of
cargo vesicles to target membranes as well as for subsequent membrane fusion. The latter is
likely mediated by receptor proteins called SNAREs, soluble N-ethylmaleimide-sensitive factor
(NSF) attachment protein receptors (Nielsen et al., 2008; Kato et al., 2010). A maize gene
(AC197246.3_FG001) moderately similar to an Arabidopsis gene encoding a RABA/RAB11
GTPase (AT2G43130) was down-regulated in RH following nitrate addition at 3 h. The
RABA/RAB11 subfamily has been implicated in vesicle trafficking between the trans-Golgi
network and the plasma membrane and shown to be involved in both RH and pollen tube growth
(Nielsen et al., 2008). Another gene (GRMZM2G147862), a putative ortholog of Prenylated
RAB Acceptor 1 (PRA1) in rice (Loc_Os03g53070) and Arabidopsis (PRA1.B6, AT5G07110),
was up-regulated in RH following nitrate addition [201]. PRAs bind to prenylated RAB proteins
and to VAMPs and may assist in targeting RABs to their final compartments and facilitate
membrane fusion to target membranes, respectively (Lee et al., 2011).
GTPase-activating proteins (GAPs) accelerate GTP hydrolysis and hence modulate
GTPases (Pan et al., 2006). An ARF-GAP was previously shown to be required for normal RH
growth (Yoo et al., 2008). A gene (GRMZM2G087144) encoding a putative ortholog of a TBCdomain containing RAB-GAP (Pan et al., 2006) was down-regulated in RH following nitrate
239
addition. Genes encoding a TBC domain-containing RAB-GAP and a Domain 11-containing
ARF-GAP were previously shown to be expressed in expanding pollen tubes (Wang et al., 2008)
Furthermore, several RAB GTPases were shown to be expressed in the maize RH proteome
(Nestler et al., 2011). A final gene (GRMZM2G074735) annotated as a RAB activator was
down-regulated in AddN.
With respect to the SNARE proteins that mediate vesicle/membrane fusion, two SNARE
proteins, putative orthologs of Arabidopsis AtVAMP711 and AtVAMP725 (Uemura et al.,
2004), were up-regulated at 30 min and 3hr in RH following nitrate treatment. AtVAMP711 was
previously shown to be localized to the tonoplast (Uemura et al., 2004; Leshem et al., 2010) and
was required for correct ABA-mediated localization of vacuolar-derived ROS in Arabidopsis
guard cells, while also regulating vacuole size and number (Leshem et al., 2010). AtVAMP711
was also shown to be highly expressed in pollen tubes as shown by AtGenExpress Visualization
Tool (Schmid et al., 2005). By contrast, AtVAMP725 was shown to be localized to the plasma
membrane and may facilitate trafficking of vesicles to the plasma membrane (Uemura et al.,
2004). Interestingly, AtVAMP725 was also up-regulated in pollen tubes (Becker et al., 2003).
In addition to cargo delivery, RH tips also undergo rapid endocytosis, mediated by
dynamin GTPases, to prevent excess plasma membrane or cell wall deposition (Taylor, 2011). A
dynamin 2A ortholog of Arabidopsis Dynamin Related Protein 2a (DRP2A), was up-regulated in
RH at 3 h after nitrate addition. In Arabidopsis, DRP2A was localized adjacent to the plasma
membrane at the RH tip, and altered DRP2A expression was associated with abnormal RH
growth (Taylor, 2011). In addition to the above canonical proteins involved in membrane
trafficking, a maize gene orthologous to the copine gene Bonzai 3 in Arabidopsis and to Copine
8 in rice (Yang et al., 2006), was highly expressed in maize RH and down-regulated after nitrate
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supplementation. Copine genes are involved in membrane trafficking and signal transduction
though the underlying mechanisms are poorly understood (Yang et al., 2006).
7.4.7.7 Growth: Cytoskeleton
Inhibitors of tubulin have demonstrated that microtubules are critical for directional
growth of root hairs (Bibikova et al., 1999). A TORTIFOLIA1 protein (GRMZM2G078725), a
putative ortholog of Arabidopsis protein TORTIFOLIA1 (TOR1, AT5G62580), a plant-specific
microtubule associated protein shown to regulate cortical microtubule orientation (Buschmann et
al., 2004), was up-regulated in RH in response to nitrate. TOR1 contains an armadillo (ARM)
domain repeat and tor1 mutant shoots display abnormal helical growth (Buschmann et al., 2004).
At least one maize gene encoding a gamma-tubulin was down-regulated at 3 h following nitrate
addition. Gamma-tubulins are located at the tips of microtubules and regulate both microtubule
nucleation and reorientation (Job et al., 2003), processes that are important for RH growth (Van
Bruaene et al., 2004).
7.4.7.8 Growth: Cell Wall
Expansion of the cell wall is integral to RH growth. One of the most interesting results
from this study is that maize Roothairless3 (Rth3), a gene previously shown to be expressed in
maize root hair-forming cells and to be required for normal RH expansion (Hochholdinger et al.,
2008), was down-regulated by almost two-fold at 30 min and 3 h in RH following nitrate
supplementation. Gene Rth3 belongs to the COBRA gene family which includes genes involved
in cell wall biosynthesis and/or cell expansion (Hochholdinger et al., 2008). The RTH3 protein
contains a predicted domain, the glycosylphosphatidylinositol (GPI) anchor, that has been shown
in other species to anchor proteins to the extracellular surface of the plasma membrane, be
regulated by phospholipase C and mediate polar protein localization (Schindelman et al., 2001).
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Cell wall glycoproteins, arabinogalactan proteins and extensins such as LRX1, which are
essential for RH growth, are O-glycosylated with arabinose (Velasquez et al., 2011). An ortholog
of a UDP-arabinose 4-epimerase 2 (AT4G20460), a possible paralog of MUR4 which
colocalizes with glycosyltransferases involved in the biosynthesis of arabinosylated cell wall
components (Burget et al., 2003), was down-regulated in maize RH after nitrate addition. An
ortholog of the rhamnose biosynthesis gene, Rhm1/Rol1, which encodes a UDP-L-rhamnose
synthase, was highly expressed in maize RH and was down-regulated almost two-fold after
nitrate addition; Rhm1/Rol1 is a suppressor of extensin LRX1 which is required for normal RH
cell wall formation (Diet et al., 2006; Velasquez et al., 2011). An ortholog of AT2G39980/rice
Loc_Os01g63480, encoding an anthranilate N-benzoyltransferase-like or N-Hydroxycinnamyl
transferase-like enzyme, previously shown to have altered expression in a rhm1/rol1 mutant
(Diet et al., 2006), had three-fold higher expression in maize RH at 3 h after nitrate addition.
Transcription factor PTF1, a weak ortholog of the Lotus japonicus ROOTHAIRLESS1
(LjRHL1) and At5g58010 (AtLRL3) (Karas et al., 2009), found to be co-regulated with
extensins such as LRX1 (Velasquez et al., 2011), was down-regulated in maize RH after nitrate
addition.
Root cell elongation is accompanied by a decrease in the hemicellulose content of the cell
wall (Schopfer, 2001). Xyloglucan is the principal hemicellulose found in primary cell walls
(Cavalier et al., 2008). Different genes involved in hemicellulose xyloglucan accumulation were
down-regulated in addition to nitrate in maize RH. The genes were as follows: putative
orthologs of Arabidopsis MUR3/rice KATAMARI1 (Tedman-Jones et al., 2008), Arabidopsis
ATXT2 (AT4G02500) (Cavalier et al., 2008), GALACTURONOSYLTRANSFERASE-LIKE 1
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(GLZ1, Parvus, GATL, AT1G19300) (Lee et al., 2007), and Galacturonosyltransferase 4
(GAUT4, AT5G47780) (Caffall et al., 2009).
A putative ortholog of the ATNST-KST1 (AT4G39390), a Golgi-localized nucleotide
sugar transporter which mediates the transfer of nucleotide sugars from the cytosol into the Golgi
(Rollwitz et al., 2006), was down-regulated in maize RH in response to nitrate. Such transporters
are required for the biosynthesis of cell wall polysaccharides and glycoproteins (Rollwitz et al.,
2006). Interestingly, ATNST-KST1 was previously shown to be expressed in Arabidopsis pollen
tubes (Wang et al., 2008). Polygalcturonases loosen cell walls; a putative ortholog of ATPGIP1,
POLYGALACTURONASE INHIBITING PROTEIN 1(Ferrari et al., 2006) showed a four-fold
relative expression increase in maize RH at 3 h following nitrate addition. Finally, ZRP4, an Omethyltransferase involved in cell wall digestibility and lignin content in maize (Thomas et al.,
2010), was down-regulated in RH at 3 h after nitrate addition.
7.4.7.9 Growth: Nitric oxide (NO)
The signalling molecule NO has been shown to regulate RH growth and may integrate
many of the above pathways including microtubule orientation, vesicular trafficking and
signalling involving G-proteins, Ca2+, ROS and hormones (Prado et al., 2004; Kaiser et al.,
2007; Terrile et al., 2010). Interestingly, a gene encoding a non-symbiotic hemoglobin (nsHb,
GRMZM2G067402) was up-regulated more than six-fold upon nitrate addition, consistent with
previous results (Trevisan et al., 2011). nsHb proteins are able to bind NO and appear to be the
most important mechanism to eliminate NO in plants (Perazzolli et al., 2006). nsHb proteins
localize to epidermal cells and may protect cells against overproduction of NO following nitrate
fertilization (Blokhina and Fagerstedt, 2010; Trevisan et al., 2011). In addition to nsHb, it is
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possible that some of the ROS-scavenging genes listed above may also scavenge NO (Blokhina
and Fagerstedt, 2010).
NO can be synthesized reductively from nitrite, creating a direct link between nitrate,
nitrate reductase and NO (Gupta et al., 2011). A maize gene encoding 2-nitropropane
dioxygenase (nitronate monoxygenase, EC 1.13.11.32), an enzyme that converts nitropropane to
nitrite, and which has been shown to generate NO in animals (Kohl and Gescher, 1996), was upregulated in maize RH by three-fold at 3 h after nitrate addition. Alternatively NO can be
synthesized oxidatively from L-arginine or polyamines such as putrescine (Gupta et al., 2011). A
key enzyme in polyamine biosynthesis, S-adenosylmethionine decarboxylase (EC 4.1.1.50), was
up-regulated in maize RH after nitrate was added. As noted above, orthologs of Arginine
Decarboxylase 2 (AtADC2) and ornithine decarboxylase, which catalyze putrescine biosynthesis
(Tun et al., 2006; Cuevas et al., 2008), showed altered regulation in maize RH after nitrate
addition. As noted above, MOCS3, a gene encoding a molybdopterin synthase
sulfurase/molybdenum cofactor sulfurase (MOCS3), which in turn is required for post
translational modification of xanthine dehydrogenase (Wollers et al., 2008), was up-regulated in
maize RH after nitrate addition. In addition to its functions noted above, xanthine dehydrogenase
is involved in NO production in peroxisomes (Gupta et al., 2011). It has been suggested that the
sulfuration state of the molybdenum cofactor can switch xanthine dehydrogenase function to
NADH oxidase function, the latter which generates superoxide implicated in RH growth (Bloch
et al., 2011; Werner and Witte, 2011). Finally, as noted above, the gene encoding Alternative
Oxidase 1 (AOX1), increased in expression in RH following nitrate addition. In addition to its
roles noted earlier, AOX1 has also been shown to stimulate NO production under anoxia (Kaiser
et al., 2007), a condition which might have been experienced by the RH in this experiment.
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7.4.8 Other Genes of Interest
7.4.8.1
Anthocyanin biosynthesis
Nitrate has been shown to regulate phenylpropanoid, flavonoid and anthocyanin
metabolism (Scheible et al., 2004). Several genes in the anthocyanin biosynthesis pathway
showed altered regulation in maize RH including a gene encoding cinnamate-4-hydroxylase
(Schilmiller et al., 2009). Furthermore, two putative anthocyanidin 3-O-glucosyltransferases (see
Table 7.4), possible orthologs of Bronze 1 (EC 2.4.1.115), showed altered expression at 30 min
and 3 h after nitrate addition. After their production, the flavonoids are transported from the
cytosol and stored in the vacuole. One of the flavonoid transporters in Arabidopsis is encoded by
Transparent Testa 12 (Marinova et al., 2007). Interestingly, five maize genes annotated as
orthologs of TT12 (see Table 7.4), had increased expression in RH following nitrate addition.
7.4.8.2 Targeted protein degradation
At least 26 genes encoding putative E3 ubiquitin ligase components including several
putatively containing a RING domain, responsible for targeting proteins for degradation by the
26S-proteosome (Miura and Hasegawa, 2010), showed altered regulation in maize RH in
response to nitrate (Table 7.4). This class of enzymes has been implicated in numerous
signalling pathways including light, abiotic stress, cell cycle, auxin, jasmonic acid and
gibberellin (Bu et al., 2009; Miura and Hasegawa, 2010). RING domain and F-box proteins were
previously shown to have altered regulation within 3 h after changes in nitrate exposure in
Arabidopsis (Scheible et al., 2004).
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7.4.8.3 Other regulatory genes
Several members of the NAC transcription factor family showed altered regulation
including NAC 21/22 (an ortholog of Arabidopsis NAC1), and additional putative orthologs of
Arabidopsis NAC2 and NAC44 (Olsen et al., 2005). Arabidopsis NAC1 has been implicated in
auxin-mediated regulation of lateral root development (Miura and Hasegawa, 2010). Also
showing altered regulation were ZFP16-2 and DREB-1D, transcription factors up-regulated
under drought (Liu et al., 1998; Ergen et al., 2009); RHC1A, shown in maize to regulate cell size
and organization in the root apical meristem (Jiang et al., 2010); an ortholog of a JUMONJI
family transcription factor (AT5G46910) which was also found to be expressed during pollen
tube development (Wang et al., 2008); and the Global transcription factor group E (AT5G63320,
Loc_Os02g38980) which includes homologs of bromodomain-containing transcription factors
Bdf1, BRD2 and BRD4 (LeRoy et al., 2008). The latter bromodomain-containing genes may
facilitate movement of RNA polymerase II on nucleosomes to regulate the transcription of suites
of genes including those involved in cell cycle regulation (LeRoy et al., 2008).
In addition to the above transcription factors, addition of nitrate to maize RH caused
differential expression of at least six phosphatases belonging to the PP2A and PP2C subfamilies
(Singh et al., 2010) and several kinases, including an ortholog of Arabidopsis Receptor-Like
Protein Kinase 1 (RPK1, AT3G47090) involved in ABA/drought/H202 signaling (Osakabe et al.,
2010). Several putative RNA-binding proteins also showed altered regulation including a gene
encoding heterogeneous nuclear ribonucleoprotein A3 (hnRNPA3), implicated in intracellular
RNA trafficking, telomere regulation and splicing (Ma et al., 2002).
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7.4.8.4 Nodulin-like
There were 11 receptor-like kinases that were down-regulated in response to added
nitrate. These kinases were similar to the nodulation kinase/symbiosis receptor-like kinase
(NORK/MtSYMRK), an ancient root hair receptor-like kinase involved in RH-mediated
symbiosis with both nodule-inhabiting nitrogen-fixing bacteria and arbuscular mycorrhizal fungi
(Endre et al., 2002; Stracke et al., 2002). Three of these kinases were similar to APK1b
(Hirayama and Oka, 1992) and two were also similar to the calmodulin-binding receptor-like
cytoplasmic kinases CRK2 and CRK3, a previous member of which was shown to be regulated
by ABA, calcium, ROS, salt and cold stresses (Yang et al., 2004). Another five genes annotated
as Nodulins or Early Nodulins showed altered regulation in RH in response to nitrate.
7.4.8.5 Stress
Several stress-related genes also showed altered expression in maize RH in response to
nitrate, some of which might reflect an interaction between nitrate and water stress pathways.
Among these genes were 32 related to heat shock, four to dehydration stress and four to hypoxia
or drought. Heat shock factor (HSF) transcription factors were previously shown to have altered
regulation in Arabidopsis within 3 h after changes in nitrate exposure (Scheible et al., 2004). In
terms of other stress-related genes, a gene encoding pyruvate decarboxylase 3
(GRMZM2G087186), implicated in hypoxia (Peschke and Sachs, 1993), was up-regulated twofold in maize RH after nitrate addition. A gene encoding a DEHYDRATION 15-like protein
showed a three-fold decrease in expression in RH at 30 min and 3 h after nitrate
supplementation. Finally, an ortholog of Avr9/Cf9, a pathogen resistance gene which is also
stimulated by ROS (Piedras et al., 1998), was down-regulated in maize RH at 30 min after nitrate
addition.
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7.4.9 Caviats in interpreting transcriptome results
We recommend caution in interpreting some of the microarray data. In particular, it is
possible that the experimental methodology used, namely addition of the oxygenated liquid
solution (RHM) for nitrate delivery, may have artificially contributed to altered expression of
certain genes, for example those related to ABA, ethylene and jasmonic acid. Similarly, the
presence of H202 (the oxygen source) in the liquid RHM media may have contributed to the
differential expression of genes related to ROS, though such expression is also consistent with
polar tip growth (Libault et al., 2010). Genes related to light signalling such as the CIP8/HY5
regulon, may have been an artifact of light exposure, though attempts were made to minimize
this. Indeed, the experiment was designed to control for these and other artifacts, as RH in both
the MaintN and AddN treatments were equally exposed to light, liquid RHM, other nutrients and
H202, but we cannot rule out nitrate concentration-dependent interactions. We were surprised to
find the expression of certain genes in RH cells, such as the seed-localized transcription factor
Opaque 2; however, a proteome analysis of the maize RH independently confirmed that it is
expressed in this cell type (Nestler et al., 2011).
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Figure 7.9. Over-represented cis-acting elements present in the promoters of the
differentially expressed root hair genes. The six major expression clusters are indicated.
Matches to previously identified motifs (Motif name) along with the similarity score (E-value)
are indicated. Only the most overrepresented motifs are shown; for a complete list of motifs
retrieved, please see Appendix Figure 1.
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7.4.10 Prediction of cis-acting promoter motifs
Cluster analysis was carried out on the differentially expressed genes in order to predict
candidate cis-acting promoter motifs underlying each expression cluster (Appendix Table 4).
Genes in Cluster 1 showed slight expression increases after nitrate addition at 30 min and 3 h,
while Clusters 4 and 5 showed decreases at both time points. The most overrepresented promoter
motifs in these clusters were highly similar to the ALFIN1 motif (Figure 7.9) (Bastola et al.,
1998; Wang et al., 2010). In Arabidopsis, ALFIN1 is one of three motifs that together are
sufficient to activate nitrate reductase expression (nia1::GUS) by 13-fold in response to nitrate
(Wang et al., 2010; Konishi and Yanagisawa, 2011). In maize, ALFINs are responsible for
increase grain yield (Bruce and Niu, 2010).
Genes in Cluster 2 were highly up-regulated at 30 min and 3 h after nitrate addition and
contained several critical genes that regulate NO levels (non-symbiotic hemoglobin, 2-nitropane
dioxygenase and polyamine biosynthesis). Cluster 2 promoters were over-represented with a
motif nearly identical to the AMMORESVDCRNIA1 motif (Figure 7.9) (Loppes and Radoux,
2001), previously shown to be responsible for activation of nitrate reductase (nia1) in
Chlamydomonas reinhardtii in response to ammonium treatment (Loppes and Radoux, 2001).
Several motifs similar to AMMORESVDCRNIA1 were also discovered upstream of genes in
Cluster 5 (Appendix Figure 1).
Genes in Cluster 3 were moderately down-regulated at 30 min and 3 h after nitrate
addition and contained Roothairless 3, TOR regulon master regulator S6K, numerous regulatory
genes and cell wall/vesicle transport genes. A nearly exact TGA1 motif was over-represented in
the promoters of these genes. Transcription factor TGA1 is regulated by nitric oxide (NO)
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(Lindermayr et al., 2010), and represses stress and defense genes (Eckardt, 2003). The TGA1
motif can also be bound by transcription factor HY5 (Song et al., 2008) which regulates root hair
length (Oyama et al., 1997) as noted earlier.
In addition to the ALFIN1 motif, Cluster 4 contained a motif similar to the ABAregulated motif ABRECE3ZMRAB28 (Busk and Pages, 1997). Another ABA-regulated motif,
ABI4-1, was overrepresented in Cluster 1 (Niu et al., 2002; Penfield et al., 2006).
Genes in Cluster 6 were highly down-regulated at 30 min and 3 h after nitrate addition,
including CCR4-NOT, a global regulator in the TOR signaling pathway (Collart, 2003). Cluster
6 promoters were over-represented with binding sites for the E2F transcription factor family, in
particular motifs E2FAT and E2Fb (Figure 7.9). As noted earlier, E2F regulates the cell cycle
(Johnson et al., 1993) in part by interacting with the TOR/S6K pathway (Ma and Blenis, 2009).
Several of the predicted motifs were CA-rich (ABI4-1, ALFIN1 TGA1, E2F) and
appeared similar to one another, and along with the CT-rich motif (ABRECE3ZMRAB28), were
similar to motifs upstream of Dof genes (Gaur et al., 2011).
7.4.11 Coincidence of differentially expressed genes with QTLs
Previously published nitrogen related QTLs (Coque et al., 2008) were anchored onto the
B73 maize inbred physical map along with the 876 differentially expressed RH genes in order to
predict candidate genes underlying these QTLs (Figure 7.10; Appendix Table 5). Overlaps were
found between the differentially expressed genes and QTLs associated with nitrogen uptake and
remobilization, nitrogen grain yield and nitrogen utilization efficiency. For example, distinct
clusters of differentially expressed genes were detected on chromosome 3L (Figure 7.10) which
overlapped QTLs for grain nitrogen yield (GNY) and nitrogen uptake (Nup). These regions
contained several regulatory genes, including genes encoding the epidermal cell regulators TINY
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(Wilson et al., 1996) and LIGULELESS 3 (Muehlbauer et al., 1997). The aquaporin-encoding
gene ZmPIP2 which may regulate nitrate uptake via mass flow (Górska et al., 2010), overlapped
nitrogen grain yield (GNY) and remobilization (Nrem) QTLs on Chromosome 2L. ToR regulon
master regulator S6K (Ma and Blenis, 2009; Dobrenel et al., 2011), overlapped a Nremobilization QTL (tremC) on chromosome 7L (Appendix Table 5). A putative ortholog of the
NORK/MtSYMRK, required for RH-mediated symbiosis with arbuscular mycorrhizal fungi
(Endre et al., 2002; Stracke et al., 2002), overlapped a nitrogen uptake (Nup) QTL on
Chromosome 9s. As a final example, an ortholog of Rhm1/Rol1, a suppressor of extensin LRX1
required for normal RH cell wall formation (Diet et al., 2006; Velasquez et al., 2011), overlapped
a grain nitrogen yield (GNY) QTL on chromosome 9L (Appendix Table 5).
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Figure 7.10 Physical map overlap of differentially expressed root hair genes and N-related
QTLs. Mapping of differentially expressed root hair genes in this study and previously identified
QTLs for grain yield and nitrogen responses in maize. Shown is data for each Chromosome.
Abbreviations noted can be found in Appendix Table 5
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Figure 7.10 Physical map overlap of differentially expressed root hair genes and N-related
QTLs.
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Figure 7.10 (continued)
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Figure 7.10 (continued)
256
Figure 7.10 (continued)
257
Figure 7.10 (continued)
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Figure 7.11. Summary model of the early root hair transcriptome response to nitrate. The
model summarizes transcriptome changes that may contribute to altered root hair elongation in
accordance with recent data from adult maize (Gaudin et al., 2011; Gaudin et al., 2011) along
with available molecular information for root hair growth (Kost, 2008; Lee and Cho, 2009;
Libault et al., 2010; Terrile et al., 2010). Abbreviations: N/C – carbon: nitrogen ratio; aa – amino
acids; NO – nitric oxide.
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7.5 Conclusions
The objective of this experiment was to understand how the transcriptome of maize RH
cells responds within 3 h to an increase in the external nitrate concentration. The results are
summarized (Figure 7.11) and they show rapid changes in expression levels of genes encoding
127 putative transcription factors, numerous other master regulators, and 54 hormone-related
genes, including those required for hormone biosynthesis (auxin, ABA, JA, GA), glycosylation
(auxin, cytokinin), degradation (JA) and signaling (auxin, ethylene, ABA, GA, cytokinin),
including several GA receptor orthologs. Taken together, external nitrate appears to trigger
cascades of responses within RH cells within minutes and hours following exposure, likely
resulting in a longer-term reprogramming of the RH transcriptome. The early reprogramming
includes genes involved in nitrogen assimilation, carbon metabolism and amino acid
biosynthesis, perhaps coordinated in part by a master regulon involving the transcription factors
Dof, Opaque 2 and GCN. The data also suggest involvement of a second regulon, the Target of
Rapamycin (TOR) signaling pathway (a TOR/MEI2/E2F regulon), that in mammals couples
nutrient availability with protein translation capacity. However, the largest class of genes that
showed differential expression were those previously implicated in regulating RH elongation,
consistent with studies showing that maize RH cells respond to nitrogen by altering growth
(Gaudin et al., 2011; Gaudin et al., 2011). These genes were involved in nitric oxide (NO)
signaling, Ca2+ and G-protein signaling, epidermal cell development, reactive oxygen species
(ROS) scavenging, as well as cytoskeleton proteins, GTPases, RH cell wall biosynthesis
regulators, and SNARE proteins that mediate vesicle/membrane fusions. The data provide clues
as to possible sources of NO production in RH. Though vesicle trafficking VAMP proteins have
been hypothesized to be required for tip growth, our data point to two VAMP proteins in
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particular as being potentially important, namely orthologs of AtVAMP711 and AtVAMP725. In
additional experiments, quantitative real-time expression data point to specific nitrogen uptake
and assimilation genes that are highly expressed in RH. Putative cis-acting promoter motifs with
a CA-rich were predicted to underlie the expression clusters observed. Finally, virtual genetic
mapping defined overlaps between RH-expressed genes and QTLs previously shown to be
involved in nitrogen uptake, metabolism, efficiency or yield. All of these data demonstrate that
the RH cell is an ideal model system to understand plant nitrogen sensing at the molecular level.
Our results should be interpreted in the context of our methodology, which involved
supplementing nitrate by addition of liquid media to root hairs previously growing in air or in
agar.
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8. The Early Transcriptome Response to Rehydration by Maize
Root Hairs (Zea mays L.)
Author contributions: Christophe Liseron-Monfils conducted all microarray and bioinformatics
analyses. The array hybridizations were performed by Shannon McDonald and Eddie Bondo at
Syngenta Biotechnology Inc. (Research Triangle Park, North Carolina, 27709, USA).
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8.1 Abstract
Root hairs (RH) comprise the majority of the plant root surface area for water absorption.
Nevertheless, no studies have reported the genome-wide transcriptome response of RH to
changes in water availability in any species. We used an Affymetrix-46K microarray to examine
the RH transcriptome response to rehydration following drought using maize/corn (Zea mays L.).
At least 1831 annotated genes were differentially expressed in maize RH during the first 3 h of
rehydration after drought. Orthologs of proteins shown to regulate RH growth and development
(GDII, MRH1, MRH5, AGC2, CSLD3, AtXX2, AtXTH26, DISTORTED1/ARP3, and FH5)
responded to rehydration. Genes encoding proteins implicated in drought/abiotic stress tolerance
showed altered regulation, including transcription factors (DREB/CBF, MYC/MYB, NAC,
WRKY, bZIP) and a putative regulon regulated by ESKIMO1. Downstream genes regulating the
accumulation of well-characterized osmoprotectants (LEA, proline, malate and trehalose) and
osmotic solutes (Na+, K+, Ca2+, Cl-) were differentially expressed. Interestingly, genes encoding
citrulline, implicated as an osmoprotectant in African desert watermelons, responded to water
availability. Rehydration affected upstream genes involved in ABA biosynthesis/signalling,
including secondary messengers (phospholipids, MAPK, calcium). Additional hormone
biosynthesis/signaling pathways (jasmonates, ethylene, gibberellin, auxin) responded to water
stress, including TASSELSEED1, 2 and genes containing upstream Squamosa Promoter Binding
Protein boxes. The majority of other over-represented cis-acting motifs shared by promoters of
RH-expressed genes (motifs RY/Fus3/Sph, VSF-1, SEF3, BS1-EgCCR, CA(n)-element) were
previously thought to confer seed-specific gene expression. We conclude that the plant root hair
cell is a sensitive biosensor of water availability, rapidly altering the expression of hundreds of
genes.
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8.2 Introduction
Maize/corn (Zea mays L.), one of the world’s three most important food crops, is grown
in many regions of the world which experience drought or intermittent rainfall, the latter causing
cycles of water limitation followed by rehydration (Iglesias et al., 1996; Rosenzweig et al.,
2001). Numerous studies have demonstrated how plants respond to drought and subsequent
rehydration. Conserved responses to drought at the whole plant or organ level include changes in
the cell wall to reduce water loss, altered root architecture, reduced stomatal conductance, and
induction of macromolecule osmoprotectants including Late Embryogenesis Abundant (LEA)
proteins, chaperones, proline, alcohol sugars and trehalose, as well as various osmotic solutes
(Na+, K+, Ca2+, Cl-) which act to balance the cellular osmotic pressure (Yamaguchi-Shinozaki
and Shinozaki, 2005).
The hormone abscisic acid (ABA) coordinates many responses to drought (Umezawa et
al., 2010). ABA-drought signalling involves a signal transduction cascade involving
phospholipids, calcium-dependent kinases and G proteins. Downstream responses are mediated
by various transcription factor families including dehydration response element binding
protein/C-repeat binding factors (DREB/CBF), which are members of the ERF/AP2-type
transcription factor family (Yamaguchi-Shinozaki and Shinozaki, 2005; Agarwal and Jha, 2010).
DREB/CBF proteins target genes containing DRE/CRT cis-acting promoter motifs (YamaguchiShinozaki and Shinozaki, 2005). Additional transcription factors involved in drought signalling
include MYC/MYB, NAC, WRKY and bZIP families (Xin and Browse, 1998; Medina et al.,
2005; Yamaguchi-Shinozaki and Shinozaki, 2005; Xin et al., 2007; Agarwal and Jha, 2010; Park
et al., 2010). In addition to ABA, other hormones implicated in drought and/or rehydration
responses include jasmonates in particular, in addition to ethylene, auxin, and gibberellins (GA)
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(Oono et al., 2003; Young et al., 2004; Walia et al., 2007; Rodriguez et al., 2010; Wang et al.,
2011).
Transcriptome studies involving water stress have primarily been conducted using whole
plants or intact organs including intact root systems (Oono et al., 2003; Rabbani et al., 2003; Lee
et al., 2009; Marino et al., 2009; Rodriguez et al., 2010; Zheng et al., 2010; Wang et al., 2011).
However, the tissue in direct contact with water is the root epidermis. Significantly contributing
to the root epidermal surface area are root hairs (RH), single cell epidermal projections that
mediate nutrient uptake, water uptake and interaction with root symbionts (Cailloux, 1972;
Peterson and Farquhar, 1996; Allen, 2011). Though an earlier study examined the RH
transcriptome response to salt stress in Arabidopsis (Dinneny et al., 2008), no studies have
reported the genome-wide transcriptome response of RH to drought or rehydration in any plant
species, including in maize.
Physiologically, RH have been shown to respond to drought or osmotic stress by
reducing tip elongation and becoming swollen (Zahran and Sprent, 1986; Schnall and Quatrano,
1992; Dauphin et al., 2001; Volgger et al., 2010) in a process likely involving ABA (Schnall and
Quatrano, 1992). It is well known that RH elongation is mediated by numerous interacting
signalling pathways that cause polarized tip growth (Libault et al., 2010). Experiments suggest
that when rainfall resumes following water limitation, water and its dissolved nutrients can
rehydrate individual RH which in turn then act as conduits for water for the whole plant
(Cailloux, 1972). Only a portion of the RH surface area appears to uptake water, with young RH
taking up large quantities of water compared to older RH (Cailloux, 1972). In the absence of
tolerance mechanisms, damage to RH caused by drought would affect the long-term ability of a
plant to interact with its environment (Allen, 2011).
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Here we examined the early transcriptome response of maize RH to rehydration
following an extended drought. We also searched for over-represented putative cis-acting motifs
present in the promoters of the genes that were differentially expressed. Our results suggest two
classes of drought-tolerance genes acting in RH, a late recovery group that continued to be upregulated following watering, and a down-regulated early recovery class, each under the control
of distinct candidate cis-acting motifs.
266
8.3 Methods
8.3.1 Biological material
Maize inbred line B73 originated from the USDA Stock Center (PI 550473, North
Central Regional PI Station, Ames, Iowa).
8.3.2 Growth system overview
In the optimized RH growth system, 30 ml of root hair media (RHM) agar (see below)
was added into each sterile glass test tube (25 x 200 mm, Pyrex® VistaTM culture tube, SigmaAldrich, St Louis, USA) which was capped with a rubber stopper (Black Rubber Stoppers,
#59580-182, VWR, USA). The agar was left to solidify at a 90˚-horizontal slant. The RHM agar
contained nitrate and was adapted from previous studies (Liu et al., 2001, 2006); it consisted of
3% (w/v) agar (Sigma-Aldrich A1296), 0.15 mM Ca(NO3)2 (Sigma Z37124), 4.85 mM CaCl2
(Sigma 10043-52-4), 0.2 mM K2SO4 (Sigma 77778-80-5), 0.82 mM MgSO4 (Sigma 10034-998),
0.3 mM CaNO3 (Sigma Z37124 ), 0.1 mM FeNa-EDTA (PhytoTechnology Laboratories 1570841-5) 9.1 µM MgCl2 (Fisher Biotech 7773-61-5), 0.034 µM NaMoO4 (Sigma 10102-40-6), 18
µM H3BO3 (EMD BX0865-1), 0.08 mM Ca5OH(PO4)3 (Fluka 21218), 0.2 µM CuSO4 (Sigma
C7631), and 0.4 µM ZnSO4 (Sigma 7446-20-0), pH 5.5-6.0. A single germinated seed was
placed onto the agar surface, 10-20 mm from the top of each tube. A home-made foam plug was
used to gently press the seed against the agar, which was covered by pieces of rockwool; this
system maintained the seed at the correct position, and prevented desiccation, pathogen
contamination and light exposure (Figure 8.1). The RHM agar contained calcium phosphate tribasic to simulate RH growth (Liu et al., 2001, 2006). Roots grew along the agar surface: half of
the RH penetrated the agar, which allowed for a uniform exchange of nutrients and mechanical
resistance, while the other half of the RH grew into the air which facilitated gas exchange. Since
267
the RH grew in the air and in soft agar, harvesting caused minimal RH damage. The tubes were
placed into adapted growth boxes (Figure 8.1) which were then placed into growth chambers.
8.3.3 Growth and rehydration treatments
Seeds were germinated on water-saturated Whatmann paper, and grown in the dark at
~28°C. Uniformly germinated 2-3 day old seedlings were transferred to the RHM agar test tubes
(see above). The growth conditions consisted of a 16 h photoperiod, 30˚C day/22˚C night, with
250-300 µMol m-2 s-1 light (incandescent bulbs, and full spectrum fluorescent light incandescent
light bulbs). Plants were watered every day with ~ 1 ml of RHM solution to prevent complete
desiccation of the RH growing in air, and hence the air-exposed RH experienced a mild localized
drought. At 8 days after transfer (~10 days after germination: time 0), liquid RHM containing
3% (v/v) H202 as an oxygen source was added to the tubes. Roots were harvested and frozen in
liquid nitrogen at three time points: time 0, 30 min and 3 h. There were 8-12 plants/time
point/replicate and the experiment was replicated three times in different growth chambers.
268
Figure 8.1. Custom growth system. (A) Seedlings were grown in a custom growth system with
their roots in the dark to avoid light-related responses. (B) Schematic of the growth system used.
269
8.3.4 Root hair RNA extraction
RNA was extracted following the protocol described in Chapter 7.
8.3.5 Microarray hybridization, analysis and clustering
A custom Syngenta B73 Corn 46K Affymetrix array was used to hybridize RH RNA as
previously described (Wagner and Radelof, 2007). RNAs from the three time points (time 0, 30
min, and 3 h) were hybridized in biological triplicates. Bioconductor (Gentleman et al., 2004)
and R (R-Development-Core-Team, 2009) were used for subsequent gene expression analysis.
Expression normalization was performed using the RMA method (Irizarry et al., 2003).
Differential gene expression was measured using a linear model from the Limma Package
(Smyth, 2005). The linear model was adjusted using the empirical Bayesian method (Smyth,
2005). To define the effect of rehydration at each time point after the treatment shift, gene
expression was compared at time 0, 30 min and 3 h after rehydration. For each comparison, the
p-value of the Empirical Bayesian test was corrected using the Benjamini-Hochberg method
(Benjamini and Hochberg, 1995). The p-value was set at 0.05. Gene annotations were retrieved
via a custom Perl script using MapMan Zm_B73 file, accessed in April 2011 (Thimm et al.,
2004) and MaizeSequence.org (Schnable et al., 2009) as starting points to link genes to the
corresponding microarray probes and annotation category. The initial MapMan annotation file
had 29,142 genes, but could only identify 34% of the probes on the microarray. After the use of
MaizeSequence.org annotations, gene annotations could be retrieved for 65% of probes.
Annotation categories that were overrepresented were identified using Fisher’s exact test using R
programming.
270
8.3.6 Promoter motif prediction
The 1831 differentially expressed genes were clustered using the HOPACH method (Van
der Laan and Pollard, 2003). Each of the four gene expression clusters were searched for shared
promoter motifs. De-novo cis-acting motifs (≥ 6 bp) in the -1000 to +1 promoter region were
predicted using a Perl-based motif discovery program that was custom developed for the maize
genome, called Promzea (see Chapter 3.3, Materials and Methods section). Gene promoters were
identified by taking 1000 bp upstream of their Gramene ID sequences (longest cDNA) in the
MaizeSequence.org database. Over-represented motifs in each promoter were identified using
three motif discovery tools: Weeder (Pavesi et al., 2007), MEME (Bailey and Elkan, 1994) and
BioProspector (Liu et al., 2001). Each motif was re-evaluated using one of the following
statistical methods: the hypergeometric test or the binomial test. All significant motifs found in
the search were compared to the motif databases, AGRIS (Yilmaz et al., 2011), Athamap (Bülow
et al., 2009) and PLACE (Higo et al., 1999), using STAMP software (Mahony and Benos, 2007).
In order to reduce false positives and to increase motif discovery accuracy, only the best 100
promoters from Clusters 1,2 and 3 were selected for motif discovery based on their adjusted pvalues (Benjamini-Hochberg as noted above). Cluster 4 had <100 promoters.
271
8.4 Results and Discussion
8.4.1 Overview
Seedlings were grown in slant tubes half-filled with nutrient agar to maximize the
subsequent RH harvest (Figure 8.1). Tubes were placed in a custom growth system to reduce
light exposure to roots (Figure 8.1). After germination, ~half of the RH grew in air but with 1 ml
of nutrient water added daily to prevent complete desiccation, and hence were exposed to mild
drought stress. The remaining RH grew in agar. At 10 days after germination, the roots were
fully rehydrated using an aqueous solution that contained the same concentrations of nutrients
present in the agar. RH were then harvested at 30 min and 3 h after rehydration (Figure 8.2) for
microarray analysis. In order to analyze the results, gene annotations from MapMan and
MaizeGenome.org were used in this study. A total of 29110 gene annotations were successfully
retrieved from the 46K microarray using a custom Perl script. Array expression patterns were
grouped using Principal Component Analysis. The samples before and after rehydration were
clearly separated indicating a clear genetic response to the treatment (Figure 8.3). A total of 1645
probes representing 1831 genes were differentially expressed between time 0, 30 min and 3 h
after rehydration (Appendix Table 6). Approximately half of the these genes showed altered
regulation within 30 min (t30min, 30 min minus time 0 comparison) while the other half
responded within 3 h (t3h, 3 h minus time 0 comparison) (Figure 8.4). No genes appeared to be
differentially expressed between 3 h versus 30 min after rehydration (Figure 8.4A), perhaps
because this variation was much lower than what was observed at t30min or t3h, masking it by
the statistical model used (see Methods).
272
Figure 8.2. Experimental flow chart. For each replicate, 36 seedlings were germinated in slant
agar tubes containing semi-solid root hair media (RHM). At 10 days after germination (time 0),
liquid RHM was added into the tubes and harvested 30 min or 3 h later. Each time point
consisted of ~12 plants. The experiment was repeated in different growth chambers to obtain
three biological replicates. Root hair RNA was extracted from each replicate (pooled from ~12
plants), and used for microarray hybridizations.
273
Figure 8.3. Sample clustering. Principal component analysis (PCA) was performed on the
microarray expression data. Each red dot represents the expression of a root hair microarray
sample under drought (time 0), and each blue dot represents the expression following rehydration
(30 min or 3 h after rehydration).
274
Figure 8.4. Venn diagrams summarizing differentially expressed genes in root hairs in a
time course following rehydration. (A) Summary of differentially expressed genes. The light
blue sphere represents genes that were only differentially expressed at 30 min after rehydration
compared to time 0 (t30min). The darker blue sphere represents genes specifically expressed 3 h
after rehydration compared to time 0 (t3h). The dark grey sphere represents any genes that were
differentially expressed between 3 h and 30 min following rehydration. (B) Numbers of genes
that were down-regulated (Down); (C) the numbers of genes that were up-regulated (Up).
275
8.4.2 Over-represented pathways
In the differentially expressed list of genes, 23 annotation categories and enzyme types
were over-represented. Four transcription factor families were over-represented, including
WRKY and AP2/EREBP domain containing proteins previously associated in responses to
drought and rehydration (Shinozaki and Yamaguchi-Shinozaki, 2007). The other two
transcription factor families were those containing bHLH and triple helix domains. On the
hormone side, jasmonate biosynthesis genes were the most significant represented, followed by
ethylene, abscisic acid and auxin induced responses, also all associated with water stress (Figure
8.5, Table 8.1) (Oono et al., 2003; Young et al., 2004; Walia et al., 2007; Rodriguez et al., 2010;
Wang et al., 2011). Other over-represented genes associated with drought/rehydration included
trehalose synthases, short chain dehydrogenase reductases (SDR) also called alcohol
dehydrogenases (ADH), and late embryogenesis abundant (LEA) proteins (YamaguchiShinozaki and Shinozaki, 2006). Over-represented signalling pathways included calcium
signalling, leucine rich repeat IV kinase receptors, kinase receptor like cytoplasmic VII kinases,
and proteins involved in protein trafficking to the endothelial reticulum (ER).
276
Table 8.1. Relative expression of genes related to root hair growth and development
following rehydration in root hair. Genes that were differentially expressed in maize root hairs
and their description are shown. The relative expression of each gene compared to the median
expression of the entire microarray is indicated by a color spectrum from light yellow (lowest) to
dark blue (highest). Expression is shown in log 2 scale. When a gene is differentially expressed
at both t30min (30 min after rehydration – time point zero, 0 min) and t3h (3 h – 0 min)
comparisons, the lower of the two p-values is shown.
Gene
Description
Lowest
adjusted
p-value
Dry
0 min
Rehydrated
30 min
Rehydrated
3h
0.0276
7.62
5.91
5.97
0.0377
7.36
7.57
7.60
0.0405
4.83
9.03
9.29
0.0390
4.89
6.32
6.08
0.0346
5.41
6.15
5.86
0.0134
6.07
7.23
7.25
0.0184
6.82
7.45
7.45
0.0466
7.16
5.11
5.18
0.0194
7.25
9.98
9.28
0.0327
8.82
10.75
10.40
0.0356
8.85
10.78
10.70
0.0178
8.76
6.67
6.26
0.0091
8.17
5.07
5.10
GRMZM2G066432
Putative ortholog of Arabidopsis
RKF3 (Receptor-like Kinase in
Flowers 3), NORK_MEDTR
Nodulation receptor kinase
precursor
Xyloglucan:xyloglucosyl
transferase AT4G18990
NORK_PEA Nodulation receptor
kinase precursor
NORK_PEA Nodulation receptor
kinase precursor
NORK_PEA Nodulation receptor
kinase precursor
NORK_PEA Nodulation receptor
kinase precursor
NORK_PEA Nodulation receptor
kinase precursor
NORK_PEA Nodulation receptor
kinase precursor
NORK_PEA Nodulation receptor
kinase precursor
NORK_PEA Nodulation receptor
kinase precursor
NORK_PEA Nodulation receptor
kinase precursor
Ortholog of Arabidopsis nodulin
family protein (AT3G01930)
Protein kinase APK1B
GRMZM2G093606
Putative germin-like protein
0.0002
6.90
8.12
8.12
GRMZM2G387127
Putative germin-like protein
0.0003
5.33
9.93
10.04
GRMZM2G149714
Putative germin-like protein
Putative ortholog of Arabidopsis
AGC2-1
0.0195
9.11
9.07
9.13
0.0284
6.60
7.40
7.14
GRMZM2G067727
GRMZM2G070271
GRMZM2G022897
GRMZM2G075884
GRMZM2G157115
GRMZM2G063533
GRMZM2G305822
GRMZM2G442277
GRMZM2G090732
GRMZM2G164242
GRMZM2G127031
GRMZM2G097395
GRMZM2G023204
277
Table 8.1
GRMZM2G136662
GRMZM2G055957
GRMZM2G061537
GRMZM2G027794
GRMZM2G454081
GRMZM2G436299
GRMZM2G157812
GRMZM2G047431
GRMZM2G137779
GRMZM2G021482
GRMZM2G095588
GRMZM2G135359
GRMZM2G088053
GRMZM2G324903
GRMZM2G115762
GRMZM2G332548
GRMZM2G430995
GRMZM2G143473
Putative ortholog of Arabidopsis
ARP3/DIS1 (DISTORTED
TRICHOMES 1)
Putative ortholog of Arabidopsis
CRK3
Putative ortholog of Arabidopsis
CRK3, NORK_PEA Nodulation
receptor kinase precursor
Putative ortholog of Arabidopsis
CSLC12
Putative ortholog of Arabidopsis
CSLC12
Putative ortholog of Arabidopsis
CSLD3
Putative ortholog of Arabidopsis
FH5 (FORMIN HOMOLOGY5)
Putative ortholog of Arabidopsis
GDI1
Putative ortholog of Arabidopsis
KAM1/MUR3
Putative ortholog of Arabidopsis
morphogenesis of root hair
5/Shaven3 (MRH5/SHV3,
AT4G26690)
Putative ortholog of Arabidopsis
morphogenesis of root hair 1
(MRH 1, AT4G18640)
Putative ortholog of Arabidopsis
MRH1 morphogenesis of root
hair 1
Putative ortholog of Arabidopsis
nodulin MtN21 family protein
(AT3G01930)
Putative ortholog of Arabidopsis
nodulin MtN3 family protein
(AT3G01930)
Putative ortholog of Arabidopsis
XT2
Xyloglucan galactosyltransferase
KATAMARI
Xyloglucan galactosyltransferase
KATAMARI
Xyloglucan:xyloglucosyl
transferase
0.0365
4.74
6.02
5.91
0.0300
6.83
8.03
7.93
0.0008
8.29
6.62
7.04
0.0305
6.63
6.38
6.39
0.0165
7.58
5.30
5.94
0.0384
9.25
5.58
5.79
0.0397
5.19
3.76
2.98
0.0312
6.87
6.88
6.79
0.0378
8.53
4.85
4.96
0.0386
8.26
8.32
8.60
0.0492
7.15
7.98
7.90
0.0139
8.10
8.19
8.09
0.0080
8.79
8.35
8.37
0.0116
10.09
6.79
6.37
0.0442
8.44
7.55
7.22
0.0378
8.53
10.32
10.24
0.0378
8.53
5.40
5.49
0.0313
8.56
6.26
5.90
278
Figure 8.5. Over-represented protein categories in the root hair response to rehydration.
Over-represented annotated proteins were measured using the hypergeometric test. The p-values
corresponding to the categories shown are listed in Table 8.2. The length of each bar is the –log
(p-value) of its significance based on the hypergeometric test.
279
Table 8.2. Hypergeometric test P-values corresponding to the over-represented gene
categories shown in Figure 8.5.
Gene category
P-value
Ubiquitin E3 RING
2.72E-10
WRKY transcription factors
3.33E-10
EREBP/AP2 transcription factors
1.04E-06
Short chain dehydrogenase reductase SDR
1.72E-06
Protein posttranslational modification
3.86E-06
Signalling calcium
8.30E-06
Jasmonate synthesis degradation
5.59E-05
Triple Helix transcription factors
8.45E-04
Chloroplast ribosome 50S subunit L17
1.54E-03
bHLH transcription factors
1.72E-03
Sucrose hexokinase
2.09E-03
Trehalose TPS/TPP
2.19E-03
Ethylene induced response
3.27E-03
Methionine synthesis
3.38E-03
MYB transcription factors
3.48E-03
Leucine rich repeat IV receptors kinases
3.75E-03
tetrapyrrole synthesis - uroporphyrin III C methyltransferase
3.75E-03
Abscisic acid induced response
3.76E-03
Auxin induced response
1.34E-02
Nucleotide metabolism synthesis
1.46E-02
Development late embryogenesis abundant
protein posttranslational modification - kinase receptor like cytoplasmic
kinase VII
protein targeting secretory pathway - ER
2.15E-02
2.60E-02
3.37E-02
280
8.4.3 Genes involved in root hair (RH) growth and development
A key gene in the formation of root hairs (RH) in Arabidopsis is Supercentipede1
(Scn1/GDI1, AT2G44100), which encodes a RhoGTPase GDP dissociation inhibitor (Carol et
al., 2005). GDI1 acts to localize an NADPH oxidase (RHD2) to hair tips; RHD2 produces
reactive oxygen species essential for polar RH growth (Carol et al., 2005). An ortholog of
AtGDI1 was down-regulated in maize RH in response to rehydration. At least 23 other G
signalling proteins showed altered expression (Table 8.1).
A screen for differentially expressed genes in an rhd2 mutant led to the identification of
six Morphogenesis of Root Hair (MRH) genes that showed altered RH phenotypes in knock-out
lines (Jones et al., 2006). Putative orthologs of two of these genes showed altered regulation in
maize RH following rehydration, including MRH1, a leucine-rich repeat (LRR) receptor kinase
and MRH5/Shaven 3, a glycerophosphoryl diester phosphodiesterase-like GPI protein (Parker et
al., 2000; Jones et al., 2006). Both of these genes affected RH elongation in Arabidopsis (Jones
et al., 2006).
MRH1 was one of 14 genes differentially expressed in maize RH with homology to the
nodulation kinase/symbiosis receptor-like kinase (NORK/MtSYMRK), an ancient RH receptorlike kinase required for symbiosis with both arbuscular mycorrhizal fungi and nodule-inhabiting
nitrogen-fixing bacteria (Endre et al., 2002; Stracke et al., 2002). Particularly interesting was
GRMZM2G442277, which was up-regulated in maize RH following rehydration.
A kinase involved in root hair elongation is AtAGC2-1 (At3g25250) whose expression is
stimulated by a phosphoinositide-dependent kinase-1 (AtPDK1) (Anthony et al., 2004). AGC2-1
is activated by auxin and cytokinin, and the protein moves dynamically in RH but can localize to
the RH nuclei and tips (Anthony et al., 2004). An agc2 mutant had shorter RH (Anthony et al.,
281
2004). A putative ortholog of AtAGC2-1 was up-regulated in maize RH in response to
rehydration.
Several genes that may be involved in RH cell wall formation showed differential
expression following rehydration in maize. Recently, the plant glycan synthase CSLD3
(Cellulose Synthase-Like D3), which affects RH integrity in Arabidopsis, was suggested to be
involved in the production of cellulose-like polysaccharides at RH tips (Park et al., 2011). An
ortholog of CSLD3 was down-regulated in maize RH following rehydration. Additional cellulose
synthase orthologs also showed altered regulation (Table 8.1).
Root cell elongation is accompanied by decreased hemicellulose in the primary cell wall
(Schopfer, 2001), of which xyloglucan is the primary constituent (Cavalier et al., 2008), A maize
ortholog of Arabidopsis xylosyltransferase 2 (At4g02500, AtXX2) was slightly up-regulated at
t3h. An AtXX2 and AtXX1 double mutant had no detectable xyloglucan in the cell wall and
showed impaired root hair development (Cavalier et al., 2008). A maize xyloglucan
xyloxyloglucosyl transferase, a possible ortholog of Arabidopsis xyloglucan
endotransglucosylase/hydrolase 26 (AtXTH26, At4g28850), was down-regulated three-fold at
t30min and t3h. XTHs alter xyloglucan chains in the cell wall, and AtXTH26 in particular has
been shown to be expressed in RH and to alter RH elongation perhaps by strengthening the sidewalls of RH (Maris et al., 2009). Additionally, the putative orthologs of AtXH29 (AT4G18990),
a xyloglucan endotransglycosylase, and MUR3 (AT2G20370), a xyloglucan
galactosyltransferase, also showed altered expression in maize RH following rehydration
(Tedman-Jones et al., 2008; Chevalier et al., 2010).
Actin microfilaments target the delivery of vesicles carrying cell wall and plasma
membrane components to the site of cell growth including RH tips, a process modulated by the
282
ARP2/3 (WURM/DISTORTED 1) complex (Mathur et al., 2003). Distorted 1 mutants show a
curvy RH phenotype (Mathur et al., 2003). The maize ortholog of Distorted 1 (ARP3) was downregulated in maize RH following addition of aqueous solution. A putative ortholog of
Arabidopsis Formin Homology 5 (FH5), an actin-nucleating protein (Cheung et al., 2010), was
also down-regulated in maize RH at t30min and t3h. FH5 mediates the formation of actin for
polarized vesicle trafficking to the RH tip (Cheung et al., 2010).
A germin-like protein (AT5G39110) has been shown to respond to manganese deficiency
in part by mediating changes in RH initiation and elongation (Wei Yang et al., 2008).
Differential expression of germin proteins has also been observed in Arabidopsis during
rehydration (Oono et al., 2003). Here, putative orthologs of AT5G39110 and its paralog
AT3G05950 showed differential expression in maize RH following rehydration.
8.4.4 Hormone pathways
8.4.4.1 Abscisic Acid (ABA), Phospholipid, MAPK and Ca2+ signaling
ABA coordinates responses to drought (Umezawa et al., 2010). At least 40 genes directly
related to ABA showed altered expression in maize RH after the transition from drought to
rehydration (Table 8.3). Viviparous-14 (Vp14), which encodes the rate-limiting step in ABA
biosynthesis, 9-cis-epoxycarotenoid dioxygenase (NCED) (Messing et al., 2010), and is induced
by drought in maize (Zheng et al., 2010), was up-regulated at t30min and t3h in maize RH,
possibly suggesting that ABA synthesis continued to respond to the long-term drought stress
imposed.
In the ABA signalling pathway in response to osmotic stress, phospholipases (PL)
hydrolyze phosphatidylinositol-4,5-bisphosphate (PIP2) to produce the soluble secondary
messengers diacylglycerol and inositol 1,4,5-triphosphate (Staxén et al., 1999; Zhu, 2002).
283
Several PLs showed altered expression in maize RH (Table 8.3): this included three orthologs of
PLA2, previously implicated in drought and osmotic stress (Zhu, 2002) and an ortholog of
ATPLC2, previously shown to induce osmotic stress responses and implicated in both ABA and
ethylene signal transduction (Benschop et al., 2007). The ATPLC2 ortholog was down-regulated
in RH after rehydration. A putative ortholog of inositol polyphosphate 5-phosphatase
(At5PTaseI), which hydrolyzes InsP3 (Burnette et al., 2003), was up-regulated in maize RH after
rehydration. Overexpression of At5PTaseI has been shown to confer drought tolerance in
Arabidopsis suggesting that InsP3 is a negative regulator of drought response genes (Perera et al.,
2008). The InsP3 precursor is biosynthesized via the enzyme phosphatidylinositol 4-phosphate-5kinase (PIP5K4) (Zhu, 2002). At least one PIP5K4 ortholog was down-regulated ~2-fold in
maize RH within 3 h after rehydration (Table 8.4).
284
Table 8.3. Relative expression of hormone-related genes that were differentially expressed
in maize root hairs following rehydration. See table 8.1 for details.
Description
Lowest
adjusted
p-value
Dry
0 min
Rehydrated
30 min
Rehydrated
3h
GRMZM2G164308
ABA-induce protein
0.0492
5.43
5.38
5.20
GRMZM2G417954
0.0118
5.79
6.93
6.87
0.0449
5.82
7.39
7.32
0.0053
6.98
9.54
9.71
0.0005
7.64
8.42
8.67
0.0345
8.47
3.27
3.13
0.0011
9.18
7.86
7.80
GRMZM2G000603
Viviparous-14
Putative ERD, early-responsive to
dehydration protein-related
Non-symbiotic hemoglobin
ERD 15-like protein (Early
response to dehydration 15)
ERD 15-like protein (Early
response to dehydration 15)
Putative ortholog of Arabidopsis
MYB52 (AT1G17950)
Protein phosphatase 2C
0.0162
5.10
6.07
5.71
GRMZM2G069713
Protein phosphatase 2C
0.0006
6.68
6.80
6.76
GRMZM2G010855
Protein phosphatase 2C
0.0042
6.87
8.30
8.25
GRMZM2G477325
Hydrophobic protein LTI6A
Putative ortholog of Arabidopsis
Eskimo 1 (Esk1,AT3G55990)
0.0391
6.00
11.35
11.34
0.0271
7.96
5.51
5.19
0.0325
5.22
3.27
3.13
0.0290
5.62
5.98
5.86
0.0049
6.03
7.15
7.11
0.0126
10.00
7.33
7.54
0.0263
8.77
7.65
7.94
0.0002
7.86
6.51
6.36
0.0099
3.30
7.64
7.84
0.0099
3.30
6.52
6.73
0.0101
6.64
7.42
7.06
0.0346
6.66
10.88
10.75
Gene
ABA-related
GRMZM2G128641
GRMZM2G067402
GRMZM2G037189
GRMZM2G327692
GRMZM2G455869
GRMZM2G411159
Auxin
GRMZM2G152796
GRMZM2G456644
GRMZM2G462760
GRMZM2G460861
GRMZM2G059138
GRMZM2G397402
GRMZM2G015892
GRMZM2G046163
GRMZM2G063042
GRMZM2G116204
IAA14-auxin-responsive
Aux/IAA family member
SAUR20 - auxin-responsive
SAUR family member
SAUR25 - auxin-responsive
SAUR family member
SAUR33 - auxin-responsive
SAUR family member
SAUR33 - auxin-responsive
SAUR family member
Putative ortholog of Arabidopsis
CYP71A13 (cytochrome P450,
AT2G30770)
Indole-3-glycerol phosphate
lyase, tryptophan metabolic
process
Putative tryptophan synthase,
alpha subunit
Putative indole-3-acetate betaglucosyltransferase
Endoplasmic reticulum auxin
binding protein 1 (ABP1)
285
Table 8.3
GRMZM2G163925
GRMZM2G307152
Phosphoribosylanthranilate
transferase
Transcription factor TINY
0.0278
10.29
9.01
8.91
0.0300
3.30
7.73
7.82
0.0075
4.82
10.75
10.78
0.0077
5.29
9.69
9.49
0.0433
6.60
9.69
9.49
0.0171
6.72
7.85
7.69
0.0300
3.30
7.73
7.82
0.0333
6.93
8.83
8.62
0.0333
6.93
4.64
4.50
0.0249
8.24
4.53
4.81
0.0384
5.33
7.15
7.28
0.0116
5.94
8.94
9.39
0.0012
5.36
7.74
8.11
0.0183
7.27
9.43
9.67
0.0115
8.26
6.64
6.96
0.0201
4.05
6.64
6.96
0.0426
5.66
4.52
4.63
0.0426
5.66
7.31
7.33
0.0429
6.52
9.53
9.29
0.0457
6.78
5.59
5.41
0.0469
7.85
5.84
6.02
0.0206
7.88
7.71
7.68
Ethylene
GRMZM2G164405
GRMZM2G052422
GRMZM2G072529
GRMZM2G119468
GRMZM2G307152
ACC synthase (1aminocyclopropane-1-carboxylate
synthase)
ACC oxidase (1aminocyclopropane-1-carboxylate
oxidase)
ACC oxidase (1aminocyclopropane-1-carboxylate
oxidase)
Putative ortholog of Arabidopsis
pyridoxal-5-phosphate
(AT5G51920)
Transcription factor TINY
Gibberellins
GRMZM2G016605
GRMZM2G173630
GRMZM2G062019
GRMZM2G061695
GRMZM2G440543
GRMZM2G051619
GRMZM2G031447
GRMZM2G301934
Putative GID1-like gibberellin
receptor
Putative GID1-like gibberellin
receptor
Gibberellin receptor GID1L2
ZmGR2c protein, gibberellin
responsive 1
F-box protein GID2, structural
constituent of ribosome, response
to freezing
Gibberellin 2-beta-dioxygenase
(GA2OX)
Protein prMC3, putative GID1
Putative ortholog of Rice protein
gibberellin receptor GID1L2
(loc_os07g44910)
Jasmonic Acid
GRMZM2G159179
GRMZM2G070092
GRMZM2G104843
GRMZM2G033098
GRMZM2G128577
GRMZM2G106303
GRMZM2G455809
Putative ortholog of Arabidopsis
CYP94C1, fatty acid (omega-1)hydroxylase oxygen binding
(AT2G27690)
Lipoxygenase 7
Tasselseed1 (TS1), lipoxygenase
Ortholog of Arabidopsis allene
oxide synthase (AOS,
AT5G42650)
Alcohol dehydrogenase activity,
short chain dehydrogenase
reductase (SDR)
12-oxo-phytodienoic acid
reductase 1
Tasselseed2 (TS2), alcohol
dehydrogenase
286
Table 8.3
GRMZM2G376661
GRMZM2G043602
GRMZM2G156712
GRMZM2G164074
GRMZM2G118183
GRMZM2G397055
GRMZM2G076981
GRMZM2G316789
GRMZM2G087323
GRMZM2G024898
GRMZM2G015433
GRMZM2G044180
GRMZM2G414805
Ortholog of Arabidopsis allene
oxide synthase (AOS,
AT5G42650)
Alcohol dehydrogenase activity,
short chain dehydrogenase
reductase (SDR)
12-oxo-phytodienoic acid
reductase
Ortholog of Arabidopsis
CYP94B3 (AT3G48520)
Alcohol dehydrogenase activity,
short chain dehydrogenase
reductase (SDR)
Alcohol dehydrogenase
Alcohol dehydrogenase activity,
short chain dehydrogenase
reductase (SDR)
Alcohol dehydrogenase activity,
short chain dehydrogenase
reductase (SDR)
Alcohol dehydrogenase activity,
short chain dehydrogenase
reductase (SDR)
WRKY domain transcription
factor, 6-phosphofructokinase
complex
WRKY23 transcription factor
Putative ortholog of OsEDR1
Squamosa binding protein-like 11
SPL (ZmSPL11), ortholog of
Arabidopsis SPL2/10/11
0.0077
8.04
7.21
7.67
0.0416
8.18
4.43
4.59
0.0053
8.27
4.64
4.52
0.0393
8.28
4.64
4.52
0.0292
9.58
7.63
7.60
0.0424
10.24
4.19
4.40
0.0154
10.42
6.26
6.01
0.0330
10.67
4.99
6.40
0.0259
11.51
7.89
7.85
0.0455
8.67
5.18
5.15
0.0157
9.45
5.68
5.37
0.0369
5.87
7.64
7.64
0.0283
6.71
6.49
6.77
287
Table 8.4. Relative expression of other signalling and vesicle-trafficking related genes
differentially expressed in maize root hairs following rehydration. See table 8.1 for details.
Gene
Description
Lowest
adjusted
p-value
Dry
0 min
Rehydrated
30 min
Rehydrated
3h
0.0447
9.29
3.62
3.46
0.0498
4.12
5.58
5.83
0.0015
6.28
5.24
5.12
0.0394
6.45
5.62
5.29
0.0452
7.32
6.25
5.96
GRMZM2G170299
Atypical receptor-like kinase
MARK
Putative ortholog of
Arabidopsis PIP5K4 (1phosphatidylinositol-4phosphate 5-kinase)
Protein phosphatase 2C
Putative ortholog of
Arabidopsis CIPK20
(AT5G45820)
Protein phosphatase 2C
GRMZM2G044382
Protein phosphatase 2C
0.0199
7.43
8.37
8.33
GRMZM2G109843
CDPK-related protein kinase
Ortholog of Arabidopsis CPK5
(AT4G35310)
Ortholog of Arabidopsis CPK7
(AT5G12480)
Ortholog of Arabidopsis
PIP5K4 (AT3G56960)
Putative ortholog of
Arabidopsis MAPKKK16
Ortholog of Arabidopsis CPK1
(AT5G04870)
Ortholog of Arabidopsis
CDPK3 (AT2G17290)
Alpha2-adrenergic receptor
activity, MAPKK
Phosphoinositide phospholipase
C, ortholog of Arabidopsis
PLC2 (AT3G08510)
Calcium-dependent protein
kinase, putative ortholog of
Arabidopsis CDPK3
(AT4G23650)
Ortholog of Arabidopsis CRK3
(AT2G46700)
CBL-interacting
serine/threonine-protein kinase,
ortholog of Arabidopsis CIPK1
(AT3G17510)
Calcium-dependent protein
kinase, ortholog of Arabidopsis
CDPK19 (AT5G19450)
0.0393
6.12
10.57
10.38
0.0187
10.52
9.52
9.00
0.0045
4.07
9.98
9.68
0.0498
4.12
4.82
5.08
0.0009
4.23
9.04
8.74
0.0017
5.79
8.29
8.65
0.0094
6.62
3.73
4.34
0.0144
6.96
8.86
10.01
0.0406
6.99
5.52
6.05
0.0429
7.24
7.17
7.19
0.0496
7.33
7.55
7.81
0.0161
8.06
8.63
8.50
0.0004
9.23
5.76
6.00
GRMZM2G046729
GRMZM2G036113
AC208201.3_FG002
GRMZM2G136400
GRMZM2G314396
GRMZM2G099425
GRMZM2G163826
AC204050.4_FG006
GRMZM2G320506
GRMZM2G081310
GRMZM2G344388
GRMZM2G129238
GRMZM2G025387
GRMZM2G031893
GRMZM2G075002
GRMZM2G028086
288
Table 8.4
GRMZM2G047223
Putative ortholog of
Arabidopsis IP5PI
(AT1G34120)
CDPK protein, ortholog of
Arabidopsis CPK5
(AT4G35310)
Calcineurin B-like protein,
putative ortholog of
Arabidopsis SOS3
Calcineurin B-like protein
Calcium ion binding, response
to freezing
Calmodulin-binding
transcription activator
Calmodulin-binding
transcription activator
Rab GTPase activator activity
Small GTPase mediated signal
transduction
Rho guanyl-nucleotide
exchange factor activity, pollenspecific kinase partner protein
Rho guanyl-nucleotide
exchange factor activity,
ortholog of protein pollenspecific kinase partner protein
(loc_os02g17240)
Rho guanyl-nucleotide
exchange factor activity,
ortholog of protein pollenspecific kinase partner protein
(loc_os02g17240)
Rho guanyl-nucleotide
exchange factor activity,
ortholog of protein pollenspecific kinase partner protein
(loc_os02g17240)
Protein phosphatase type 2A
regulator/ signal transducer
Rab GTPase activator activity
GRMZM2G174274
Putative rac GTPase protein
0.0123
6.20
8.04
7.93
GRMZM2G086971
GTP-binding protein YPTM1
Small GTPase mediated signal
transduction
Small GTPase mediated signal
transduction
Rab GTPase activator activity
0.0154
6.29
9.13
8.89
0.0154
6.29
8.09
7.89
0.0426
6.80
4.20
4.16
0.0003
7.28
6.75
6.67
GTP binding protein
Rho guanyl-nucleotide
exchange factor , ortholog of
pollen-specific kinase partner
protein (loc_os07g29780)
0.0161
7.46
6.04
5.92
0.0113
7.59
8.78
8.87
GRMZM2G158972
GRMZM2G321239
GRMZM2G110080
GRMZM2G137751
GRMZM2G065899
GRMZM2G153594
GRMZM2G341747
GRMZM2G150876
GRMZM2G077662
GRMZM2G377615
GRMZM2G173729
GRMZM2G442148
GRMZM2G065423
GRMZM2G079323
GRMZM2G373738
GRMZM2G420935
GRMZM2G087144
GRMZM2G028900
GRMZM2G131275
0.0134
9.66
5.76
6.00
0.0172
9.71
4.77
4.86
0.0211
10.28
6.20
5.89
0.0211
10.28
8.15
8.37
0.0378
3.83
9.03
9.09
0.0397
3.95
8.01
8.36
0.0397
3.95
8.48
8.46
0.0389
3.03
7.36
7.34
0.0336
4.24
8.66
8.88
0.0445
4.69
7.34
7.31
0.0420
5.20
3.74
4.16
0.0420
5.20
8.02
7.98
0.0421
5.58
8.02
7.98
0.0022
5.70
6.35
6.88
0.0329
5.98
7.64
7.38
289
Table 8.4
GRMZM2G128771
GRMZM2G071157
GRMZM2G090029
GRMZM2G398055
GRMZM2G023436
GRMZM2G050890
GRMZM2G052823
GRMZM2G041774
Small GTPase mediated signal
transduction, nucleocytoplasmic
transport
Rho guanyl-nucleotide
exchange factor activity,
ortholog of protein pollenspecific kinase partner protein
(loc_os10g40270)
Dopamine receptor activity, Gprotein coupled receptor protein
signaling pathway
G-protein coupled receptor
protein signaling pathway
Ras-related protein Rab11B,
nucleocytoplasmic transport
Prenylated rab acceptor family
protein
Rab GTPase activator activity,
putative TBC domain family
member
Protein serine/threonine kinase
0.0096
7.60
10.10
9.97
0.0120
7.60
10.07
9.94
0.0460
7.61
7.98
8.10
0.0495
8.23
8.16
7.93
0.0339
8.93
8.66
8.54
0.0417
10.06
8.87
9.24
0.0339
5.77
8.87
9.24
0.0094
6.08
9.60
9.23
290
The phospholipid pathway regulates Ca2+ signaling and the mitogen activated kinase
(MAPK) cascade (Staxén et al., 1999; Zhu, 2002). Several MAP kinases and 49 Ca2+ signaling
molecules showed differential expression following rehydration (Table 8.4). Genes encoding
calcium-dependent protein kinases (CDPKs) showed altered regulation (Table 8.4). In particular,
an ortholog of AtCPK6 (GRMZM2G081310), shown to be induced by osmotic stress and to
confer salt/drought tolerance (Xu et al., 2010), was up-regulated after addition of aqueous media.
The calcineurin B-like (CBL) calcium sensor protein CBL4/SOS3 has been shown to be
involved in mediating salt tolerance (Gong et al., 2004). Two putative orthologs of CBL4/SOS3
(including GRMZM2G110080) were down-regulated in maize RH following rehydration. In
Arabidopsis, CBL4/SOS3 and other CBLs form complexes with CBL-interacting protein kinases
named CIPK proteins (Gong et al., 2004). An ortholog of CIPK1 (GRMZM2G075002), which
helps to confer ABA-mediated osmotic stress tolerance in Arabidopsis (D'Angelo et al., 2006),
was down-regulated two-fold in maize RH. A CIPK-like protein 1 moderately similar to
CIPK20/PKS18, previously shown to cause hypersensitivity to ABA signalling (Gong et al.,
2002), was down-regulated. The CIPK-like protein 1 in maize was previously shown to be
triggered by drought stress (Zheng et al., 2010). The CIPK1 family has been suggested to
mediate cross-talk mediate ABA-dependent and ABA-independent abiotic stress signalling
(Gong et al., 2004). Evidence suggests that the drought response element binding protein/Crepeat binding factor (DREB/CBF) transcription factors (see below) are downstream targets of
CIPK1 (D'Angelo et al., 2006).
In Arabidopsis, the CIPK-like protein is part of the SOS2-like (Salt Overly Sensitive 2)
kinase gene family (Gong et al., 2002); SOS2 interacts with the protein phosphatase 2C (PP2C)
protein ABI2, a critical negative regulator of ABA signaling (Ohta et al., 2003). At least five
291
putative PP2C-encoding genes showed altered regulation in maize RH (Table 8.4). This included
a putative ortholog of HAI2 (AT1G07430, maize GRMZM2G010855), an ABA-induced GroupA PP2C gene very closely related to AtPP2CA/AHG3, a strong negative regulator of ABA signal
transduction (Kuhn et al., 2006; Umezawa et al., 2010).
8.4.4.2 Ethylene and Ethylene-ABA cross-talk
Ethylene has been shown to be involved in drought stress (Oono et al., 2003; Young et
al., 2004; Wang et al., 2011), but is also a key hormone involved in RH elongation (Tanimoto et
al., 1995). ACC (1-aminocyclopropane-1-carboxylate) synthase and ACC oxidase are the first
committed step and last step in ethylene biosynthesis, respectively (Lin et al., 2009). Here, genes
encoding one ACC synthase and two ACC oxidases increased in expression in maize RH after
watering (Table 8.3), indicating increased production of ethylene. Consistent with this result,
ACC oxidase has previously been shown to be up-regulated during rehydration in Arabidopsis
(Oono et al., 2003). Altered expression of ACC synthase has been shown to be a conserved
response to drought in rice (Wang et al., 2011) and to regulate drought tolerance in maize
(Young et al., 2004). The protein phosphatase 2C ABI1 has been shown to physically interact
with ACC synthases (Ludwików et al., 2009) showing cross-talk between ethylene and ABA
pathways. ACC synthases requires the active form of Vitamin B6, pyridoxal-5-phosphate (PLP),
as a cofactor at its active site (Huai et al., 2001). A PLP-dependent transferase
(GRMZM2G119468) was up-regulated in maize RH following aqueous treatment. Interestingly
in Arabidopsis, Sos4, an essential gene required for root hair development and conferral of
osmotic tolerance (Shi and Zhu, 2002), was found to encode a pyridoxal kinase required for the
synthesis of PLP, thus linking abiotic stress, ethylene and root hair signalling pathways.
292
An ortholog of Arabidopsis TINY, a repressor of cell elongation in Arabidopsis (Wilson
et al., 1996), was up-regulated in maize RH following aqueous treatment. The overexpression of
TINY gene results in the classic ethylene constitutive triple response (Wilson et al., 1996). TINY
encodes a transcription factor which contains two DNA binding domains, an AP2/ethyleneresponsive element binding factor (ERF) domain and a DREB-like domain (Sun et al., 2008),
demonstrating cross-talk between ethylene and ABA-dependent signalling pathways. Altered
expression of TINY was previously shown to be a conserved response to drought in rice roots
(Wang et al., 2011).
8.4.4.3 Jasmonates and a putative Tasselseed regulon
Jasmonates play a predominant role in abiotic stress including high salinity, drought and
rehydration (Oono et al., 2003; Walia et al., 2007; Rodriguez et al., 2010). Consistent with this,
the jasmonate biosynthetic pathway was highly overrepresented in classes of genes which
showed altered expression in this study (Figure 8.6). Genes encoding five enzymes involved in
jasmonate biosynthesis were up-regulated in maize RH. This list included: maize lipoxygenase 7
(GRMZM2G070092), two putative orthologs of Arabidopsis allene oxide synthase (AOS)
(GRMZM2G033098 and GRMZM2G376661), a key cytochrome P450 enzyme in jasmonate
biosynthesis (Song et al., 1993); and two 12-oxo-phytodienoic acid reductases (OPR), orthologs
of AtOPR, previously shown to be required for JA biosynthesis (Tani et al., 2008). In addition to
lipoxygenase, AOS and OPR have previously been identified as being involved in drought and
rehydration responses in monocots and dicots (Oono et al., 2003; Walia et al., 2007; Rodriguez
et al., 2010).
293
Figure 8.6. Hypothetical jasmonate synthesis pathway. Here is proposed a jasmonate
synthesis pathway and its regulation of the upstream Squamosa Promoter Binding Protein cisacting motif (SBP box). Green and red arrows indicate that the corresponding genes were upregulated or down-regulated, respectively, in maize root hairs following rehydration.
294
In addition to genes involved in jasmonate biosynthesis, a gene required for jasmonate
degradation, encoding a cytochrome P450 ortholog of Arabidopsis CYP94C1 (Koo et al., 2011),
was up-regulated at t3h. Therefore, both jasmonate synthesis and degradation pathways appear to
be active simultaneously in maize RH following rehydration, suggesting jasmonate turnover may
be an important aspect of the response to water stress in this cell type.
In roots, short chain alcohol dehydrogenases (ADH) are part of the fermentation pathway
activated by three factors: flooding, low temperature and ABA. Drought was also shown to
increase ABA levels in roots, which resulted in increased ADH expression (de Bruxelles et al.,
1996). In agreement with this, rehydration provoked decreased expression of seven out of nine
ADH genes in maize RH (Table 8.3). However, one ADH-encoding gene Tasselseed2 (Ts2),
showed a large increase in expression (~five-fold) during the rehydration response in RH. TS2 is
a hydroxysteroid dehydrogenase, a sex determining enzyme studied for its effects on floral
development, but relatively uncharacterized otherwise (Wu et al., 2007). TS2 was shown to be
widely expressed in maize notably in roots (Malcomber and Kellogg, 2006; Acosta et al., 2009).
Interestingly, Tasselseed1 (Ts1) expression was also enhanced in maize RH following
rehydration. TS1 is a positive regulator of TS2 expression (Calderon-Urrea and Dellaporta,
1999) and encodes a lipoxygenase required for jasmonic acid (JA) synthesis (Acosta et al.,
2009). Lipoxygenases have previously been observed as a conserved part of drought and
rehydration responses (Oono et al., 2003; Marino et al., 2009; Wang et al., 2011). Since ts1 and
ts2 mutant phenotypes can be rescued by the application of jasmonates (Acosta et al., 2009), TS2
could be a missing step in jasmonate synthesis and may play a role during abiotic stress along
with TS1. TS1 has been shown to activate miR156 either directly or indirectly, and subsequently,
miR156 targets a subset of genes for degradation in maize containing a Squamosa Promoter
295
Binding Protein (SBP)-box motif in their promoters (Hultquist and Dorweiler, 2008; Shikata et
al., 2009) including SBP-like (SPL) genes (Shikata et al., 2009). miR156 has been implicated as
a master regulator that promotes juvenile development in maize (Chuck et al., 2007).
Interestingly, a gene encoding SBP-like 11 (ZmSPL11, GRMZM2G414805), an ortholog of
AtSPL2/10/11, which contain putative target sites for miR156 (Hultquist and Dorweiler, 2008),
was repressed in maize RH during rehydration, consistent with the up-regulation of Ts1. This
result predicts the presence of a jasmonate-miR156-TS1/TS2-SBP/SPL regulon acting in RH in
response to water stress. Consistent with this result, as demonstrated later in this study (Figure
8.6), a subset of differentially expressed genes in this study contained SBP-box motifs in their
promoters.
8.4.4.4 Gibberellins
GA has been shown to be involved in drought responses, to antagonize ABA responses,
to cross-talk with ethylene, and to regulate RH expansion under phosphate starvation (Weiss and
Ori, 2007; Achard et al., 2008; Jiang and Yu, 2009; Wang et al., 2011). Gibberellin 2-betadioxygenase (GA2ox) inactivates bioactive gibberellins (Weiss and Ori, 2007), and is one of the
conserved genes that was differentially expressed in roots in response to drought (Wang et al.,
2011). After rehydration, GA2ox was up-regulated in maize RH in this study. Five genes
encoding possible orthologs of the rice gibberellin receptor GID1, Gibberellin Insensitive
Dwarf1 (Ueguchi-Tanaka et al., 2005), were also differentially expressed in RH after water
treatment. GA perception by GID1 causes degradation of a DELLA repressor, which is mediated
by the F-box protein GID2 in rice (Gomi et al., 2004). An ortholog of GID2 was up-regulated in
maize RH. Finally, the GA responsive gene ZmGR2c, previously identified in a differential
296
display experiment comparing wild-type maize and GA-insensitive mutant D8 (Ogawa et al.,
1999), was also up-regulated after rehydration.
8.4.4.5 Auxin
Genes in the auxin pathway were previously shown to be differentially expressed during
rehydration and drought (Oono et al., 2003; Rodriguez et al., 2010; Wang et al., 2011). In
general, maize RH responded to rehydration by increasing transcript levels of genes involved
biosynthesis (Table 8.3). For example, there were ~13-fold increases in the expression of two
putative orthologs of tryptophan synthase alpha chain (GRMZM2G046163, GRMZM2G015892)
which catalyzes the formation of indole, leading to IAA (indole-3-acetic acid) (Kriechbaumer et
al., 2008). A putative ortholog of indole-3-acetaldoxime dehydratase (GRMZM2G397402), a
cytochrome P450 enzyme that converts indole-3-acetaldoxime to IAA (Mahadevan, 1963), was
up-regulated ~3.5-fold. An ortholog of IAA-amino acid hydrolase ILR1 (GRMZM2G091540),
an enzyme that liberates amino-acid conjugated storage forms of IAA, was up-regulated >ninefold (LeClere et al., 2002). Consistent with an increase in free IAA, a gene encoding indole-3acetate beta-glucosyltransferase (IAA-glucose-synthase) (GRMZM2G063042), an enzyme
responsible for reducing free auxin levels by glucose conjugation (Leznicki and Bandurski,
1988), was down-regulated ~four-fold. The only gene that appeared to respond oppositely to
dehydration in maize RH encoded phosphoribosylanthranilate transferase, an enzyme involved in
the biosynthesis of the early IAA precursor, tryptophan (Rose et al., 1992), which was downregulated two-fold.
In addition to potential changes in free auxin, auxin regulatory genes also showed
differential expression in maize RH. A gene encoding Auxin Binding Protein 1 (ABP1), an auxin
receptor that mediates cell expansion (Woo et al., 2002), was up-regulated in maize RH
297
following rehydration. ABP1 was previously shown to have altered expression in maize kernels
in response to drought (Marino et al., 2009). In Arabidopsis, ABP1 regulates a subset of the IAA
family of transcriptional co-repressors as well as some genes encoding Small Auxin-Up RNAs
(SAURs) (Effendi et al., 2011). The former includes IAA14 which has been implicated in lateral
root and RH formation (Fukaki et al., 2002). In this study, maize IAA14 was down-regulated in
RH following rehydration, while IAA24 and at least five SAUR genes also showed differential
expression (Table 8.3). AtNAC1 acts downstream of the TIR1 auxin receptor in Arabidopsis
(Xie et al., 2000), and its ortholog is up-regulated in the RH zone during early nodulation
infection in Medicago (D’haeseleer et al., 2011). Two putative orthologs of AtNAC1
(GRMZM2G063522, GRMZM2G167018) showed decreased expression in maize RH in
response to rehydration.
8.4.4.6 Nitric oxide
Nitric oxide (NO) can be produced in plants during RH development and abiotic stress,
and was shown to increase tolerance to abiotic stress including drought (Zhao et al., 2004). NO
production was also shown to induce ABA responses (Desikan et al., 2002; Garc a-Mata and
Lamattina, 2002). Plant non-symbiotic hemoglobin (nsHb) directly binds and scavenges the
signal molecule nitric oxide (NO), one of the most important mechanisms of NO elimination
(Perazzolli et al., 2006). In this study, a gene encoding maize nsHb (GRMZM2G067402) was
up-regulated in RH after rehydration.
8.4.5 Transcription factors
Downstream of hormone signalling and/or independent of hormone signalling, are
transcription factors that have been shown to mediate abiotic stress responses, including the
transcription factors DREB/CBF, MYC/MYB, NAC, bZIP and WRKY (Shinozaki and
298
Yamaguchi-Shinozaki, 2007; Lata and Prasad, 2011), members of which were differentially
expressed in this study.
299
Table 8.5. Relative expression of genes encoding transcription factors and regulons related
to water stress that were differentially expressed in maize root hairs following
rehydration. See table 8.1 for details.
Gene
Description
Lowest
adjusted
p-value
Dry
0 min
Rehydrated
30 min
Rehydrated
3h
0.0424
7.09
10.39
10.19
0.0227
6.96
7.61
7.46
bZIP
GRMZM2G006578
Common plant regulatory factor
7, bZIP transcription factor
family
bZIP transcription factor family
GRMZM2G428184
bZIP transcription factor family
0.0219
5.89
10.82
10.86
GRMZM2G073427
bZIP transcription factor family
0.0026
7.08
5.65
6.00
GRMZM2G033230
bZIP transcription factor family
0.0099
6.17
7.06
6.99
GRMZM2G149150
bZIP transcription factor family
0.0095
6.85
7.64
7.31
0.0204
6.86
5.04
5.44
0.0484
8.61
9.80
9.93
0.0038
3.70
9.62
9.64
0.0054
4.03
11.70
11.55
GRMZM2G368491
DREB-related
GRMZM2G042756
DRE-binding protein 1c
(DREB1C)
LOS1; copper ion binding
translation elongation factor
Dehydration-responsive
element-binding protein 1A
DREB1D
GRMZM2G069146
Os-sbCBF6
0.0002
5.22
7.11
6.87
GRMZM2G124011
sbCBF6
Putative ortholog of rice protein
zinc finger A20 and AN1
domains-containing protein
(loc_os02g10200)
Putative ortholog of Arabidopsis
rare cold inducible gene 3
RCI3A (AT1G05260)
Putative ortholog of Arabidopsis
rare cold inducible gene 3
RCI3A (AT1G05260)
AN18, Multiple stressresponsive zinc-finger protein
ISAP1
0.0006
5.91
8.32
8.58
0.0353
5.93
11.22
11.50
0.0116
7.58
7.57
7.59
0.0399
9.40
8.50
8.47
0.0074
9.76
6.15
6.01
GRMZM2G006745
AC203173.3_FG004
GRMZM2G137341
GRMZM2G087719
GRMZM2G022740
GRMZM2G177792
GRMZM2G134334
MYB
GRMZM2G455869
Putative ortholog of Arabidopsis
MYB52 (AT1G17950)
0.0011
9.18
7.86
7.80
GRMZM2G147346
R2R3MYB-domain protein,
putative ortholog of OsMYB4
(loc_os10g33810)
0.0110
4.56
5.14
5.54
300
Table 8.5 (continued)
GRMZM2G127857
R2R3MYB-domain protein,
putative ortholog of OsMYB4
(loc_os10g33810)
R2R3MYB-domain protein,
putative ortholog of OsMYB4
(loc_os10g33810)
Transcription factor MYB31,
putative ortholog of Arabidopsis
MYB4 (AT4G38620)
R2R3MYB-domain protein,
putative ortholog of Arabidopsis
MYB4 (AT4G38620)
R2R3MYB-domain protein,
putative ortholog of Arabidopsis
MYB4 (AT4G38620)
Transcription factor MYB8,
ortholog of Arabidopsis MYB4
R2R3MYB-domain protein,
putative ortholog of Arabidopsis
MYB4 (AT4G38620)
Ortholog of Arabidopsis and rice
ERD1
(Early response to dehydration
1, AT5G51070)
0.0150
5.55
6.17
6.21
0.0449
8.99
6.41
6.56
0.0384
6.22
7.35
7.39
0.0301
6.80
7.86
7.83
0.0181
8.55
7.87
7.80
0.0136
8.13
7.87
7.78
0.0195
8.66
5.72
5.98
0.0089
7.13
6.71
7.22
0.0443
5.20
7.92
7.77
0.0083
6.10
5.40
5.88
0.0457
5.27
6.98
6.97
0.0439
4.15
6.48
6.92
0.0005
4.23
9.80
9.75
0.0031
4.41
8.34
8.00
0.0258
6.05
8.29
8.06
0.0393
7.36
9.09
9.01
GRMZM2G166721
NAC domain-containing protein
putative ortholog of anac036
(Arabidopsis NAC domain,
AT2G17040)
putative ortholog of anac044
(Arabidopsis NAC domain,
AT3G01600)
ANAC010
Ortholog of rice ANAC014
(loc_os08g06140)
NAC domain-containing protein,
putative ortholog of Arabidopsis
ANAC055 (AT3G15500)
ANAC075
0.0223
7.45
7.15
7.28
GRMZM2G134073
NAC domain-containing protein
0.0116
8.02
7.08
7.24
GRMZM2G347043
NAC1 transcription factor
NAC domain-containing protein
21/22,
putative ortholog of Arabidopsis
NAC1
0.0051
8.95
5.29
5.67
0.0225
8.51
6.35
6.34
GRMZM2G048295
GRMZM2G050305
GRMZM2G405094
GRMZM2G089244
GRMZM2G041415
GRMZM2G077789
GRMZM2G172230
MYC
GRMZM2G001930
GRMZM2G049229
Transcription factor MYC7E,
ATMYC2 (AT1G32640)
binding to RD22
Putative ortholog of Arabidopsis
MYC2/RD22BP1 (AT1G32640)
NAC
GRMZM2G179049
GRMZM2G059428
GRMZM2G038073
GRMZM2G058518
AC196475.3_FG005
GRMZM2G079632
GRMZM2G167018
301
Table 8.5 (continued)
GRMZM2G163418
NAC domain-containing protein,
putative ortholog of Arabidopsis
NAC1
Putative ortholog of
ATWRKY33 (AT2G38470)
WRKY domain transcription
factor, putative ortholog of
OsWRKY71
WRKY domain transcription
factor
WRKY domain transcription
factor
WRKY domain transcription
factor
WRKY domain transcription
factor
WRKY74 transcription factor
GRMZM2G057116
WRKY67 transcription factor
0.0368
5.12
9.47
9.27
GRMZM2G012724
WRKY53 transcription factor
0.0047
5.63
6.93
7.39
GRMZM2G139815
WRKY74 transcription factor
0.0039
6.05
7.94
8.22
GRMZM2G324999
0.0092
6.11
6.07
6.09
0.0068
6.32
7.22
7.16
GRMZM2G090594
WRKY69 transcription factor
WRKY domain transcription
factor
WRKY25 transcription factor
0.0054
6.49
6.54
6.42
GRMZM2G030272
WRKY55 transcription factor
0.0301
7.83
6.48
6.28
GRMZM2G148561
0.0031
8.38
4.75
5.04
0.0455
8.67
5.18
5.15
GRMZM2G015433
WRKY25 transcription factor
WRKY domain transcription
factor, 6-phosphofructokinase
complex
WRKY23 transcription factor
0.0157
9.45
5.68
5.37
GRMZM2G044180
Putative ortholog of OsEDR1
0.0369
5.87
7.64
7.64
0.0215
7.64
8.96
9.02
0.0271
7.96
5.51
5.19
0.0300
3.30
7.73
7.82
GRMZM2G063522
GRMZM2G148087
GRMZM2G120320
GRMZM2G158328
GRMZM2G147880
GRMZM2G025895
GRMZM2G061408
AC209050.3_FG003
GRMZM2G024898
0.0210
9.46
6.47
6.83
0.0147
6.33
7.41
7.95
0.0004
7.60
4.08
4.81
0.0047
4.20
4.54
4.54
0.0367
4.73
8.30
8.15
0.0008
5.01
10.72
10.29
0.0008
5.01
6.31
7.03
0.0008
5.01
8.10
8.02
Others
GRMZM2G307152
Nuclear transcription factor Y
subunit A-1 (NY-A1)
Putative ortholog of
Arabidopsis Eskimo 1
(Esk1,AT3G55990)
Transcription factor TINY
GRMZM2G169654
RAV1
0.0002
6.76
7.73
7.82
GRMZM2G018336
Putative RAV
Squamosa binding protein-like
11 SPL (ZmSPL11), ortholog of
Arabidopsis SPL2/10/11
0.0013
6.28
7.73
7.82
0.0283
6.71
6.49
6.77
GRMZM2G091964
GRMZM2G411159
GRMZM2G414805
302
8.4.5.1 DREB/CBF regulon
Critical to drought, salt and cold responses are DREB/CBF transcription factors, which
can be either ABA-dependent or ABA-independent (Shinozaki and Yamaguchi-Shinozaki,
2007). A maize ortholog of OsDREB1A (GRMZM2G137341), previously shown to confer
higher resistance to abiotic stress including drought but not induced by ABA (Dubouzet et al.,
2003), was up-regulated >4-fold in maize RH after rehydration. DREB1A has been shown to be
induced during rehydration in Arabidopsis (Oono et al., 2003). The ortholog of OsDREB1D
(GRMZM2G042756), previously shown to confer cold and stress tolerance in Arabidopsis
(Zhang et al., 2009), was also up-regulated nearly 4-fold after rehydration. A maize gene
annotated as DREB1C (GRMZM2G006745) was also up-regulated though at t3h only. In
Arabidopsis DREB1C/CBF2 has been shown to be a negative regulator of DREB1A and
DREB1B expression; a cbf2 mutant had increased tolerance to freezing, salt stress and
dehydration (Novillo et al., 2004). In addition, two putative orthologs of sorghum CBF6 (rice
loc_os09g35030) (GRMZM2G069146, GRMZM2G124011), were both up-regulated in maize
RH after rehydration.
LOS1 is an elongation factor 2 (eEF-2) shown to regulate genes downstream of
CBF/DREB1 and to cause feedback effects on CBF/DREB1 transcript levels in Arabidopsis
(Guo et al., 2002). An ortholog of Los1 was up-regulated in maize RH at t3h. In Arabidopsis,
LOS1 primarily mediates cold stress responses, but not those involving ABA (Guo et al., 2002).
The Stress Associated Proteins (SAP), containing A20 and AN1 zinc-finger domains,
have been shown to mediate abiotic stress tolerance in a variety of plants, perhaps by targeting
proteins for ubiquitin-mediated degradation (Vij and Tyagi, 2006). The promoters of rice SAP
proteins contain ABA-response element (ABRE) and dehydration-response element (DRE/CRT)
303
motifs (Vij and Tyagi, 2006) and hence are likely downstream targets of CBF/DREB1 proteins.
Two putative SAP orthologs, ISAP1 (GRMZM2G134334) and a gene most closely related to
ISAP4 (GRMZM2G087719), were both up-regulated after rehydration (Table 8.5). In rice,
ISAP1 was previously shown to be induced within 1-3 h after exposure to ABA and diverse
abiotic stresses including drought, and it conferred tolerance to drought and other abiotic stresses
when overexpressed in tobacco (Mukhopadhyay et al., 2004). ISAP4 was up-regulated by cold,
drought and salt in rice but has not been functionally characterized (Vij and Tyagi, 2006).
The gene Rare Cold Inducible 3 (RCI3) encodes a cold-, drought- and ABA-induced
peroxidase that confers increased tolerance to dehydration and salt in Arabidopsis (Llorente et
al., 2002). The promoter of RCI3 contains DRE/CRT-like elements (Llorente et al., 2002),
suggestive of it being a target of CBF/DREB proteins. Two putative orthologs of RCI3 were upregulated in maize RH following rehydration (Table 8.5). In Arabidopsis, RCI3 is proposed to be
involved in modifying the cell wall to promote reduced water loss (Llorente et al., 2002). Other
genes encoding cell wall modifying proteins, including those involved in suberin/wax
biosynthesis, also showed differential expression in this study (Appendix Table 6).
8.4.5.2 MYC/MYB regulon
Independent of the DREB/CBF pathway are abiotic stress responses mediated by MYC
and MYB transcription factors (Shinozaki and Yamaguchi-Shinozaki, 2007). A total of 3 MYC
and 21 MYB-encoding genes showed altered regulation in maize RH. Two orthologs of
AtMYC2/RD22BP1, shown to be an ABA-induced transcriptional activator of drought responses
(Abe et al., 1997; Abe et al., 2003), were up-regulated in maize RH after rehydration. A putative
ortholog of ATMYB52, a positive regulator of drought responses in the ABA pathway, perhaps
regulating cell wall biosynthesis (Park et al., 2011), was down-regulated >4-fold (Table 8.5).
304
Three putative orthologs of OsMYB4, an R2R3-type master regulator of at least 17
families of transcription factors involved in drought, cold tolerance and development (Park et al.,
2010), were all up-regulated in maize RH after rehydration. OsMYB4 confers drought tolerance
in heterologous species when overexpressed and acts independently of the DREB/CBF network
(Park et al., 2010). It has been proposed that another master regulator, Nuclear Transcription
Factor Y (NF-Y), may act as a co-regulator of this DREB/CBF-independent network,
downstream of OsMYB4 (Park et al., 2010). NF-Y binds CCAAT DNA motifs and consists of a
heterotrimeric protein complex of which the B subunit (NF-YB) was shown to confer drought
tolerance in maize when overexpressed; increasing maize yield under field conditions (Nelson et
al., 2007). Interestingly, a maize gene encoding the A subunit (NF-A1) was down-regulated
within 30 min in RH following rehydration (Table 8.5).
A subset of promoters up-regulated by OsMYB4 includes those containing an ERD1
(Early Response to Dehydration 1) cis-acting motif (Park et al., 2010). Similar to OsMYB4/NFY, ERD1 is not induced by ABA but is drought-inducible, homologous to a ClpA protease
regulatory subunit, and is plastid targeted (Nakashima et al., 1997). An ortholog of ERD1
(GRMZM2G172230) was up-regulated <two-fold in maize RH after rehydration.
8.4.5.3 NAC transcription factors
NAC transcription factors have been shown to mediate responses to drought in parallel
to DREB/CBF transcription factors (Shinozaki and Yamaguchi-Shinozaki, 2007). In
Arabidopsis, the ERD1 promoter (see above) is also regulated by three NAC transcription factors
including ANAC055 (Tran et al., 2004). ANAC055 was shown to be induced by drought, ABA
and high salt and to confer drought tolerance when overexpressed (Tran et al., 2004). A putative
ortholog of ANAC055 (GRMZM2G079632) was up-regulated ~two-fold in maize RH after
305
rehydration. At least 11 NAC proteins also showed differential expression (Table 8.5), including
ZmNAC1 (GRMZM2G347043), previously shown to be induced by several abiotic stresses
including drought (PEG) and ABA (Liu et al., 2009).
8.4.5.4 WRKY and bZIP transcription factors
bZIP and WRKY transcription factors have been shown to mediate abiotic stress
tolerance in Arabidopsis (Shinozaki and Yamaguchi-Shinozaki, 2007). Altered expression of the
WRKY gene family in rice roots in response to drought has also been demonstrated (Wang et al.,
2011). A total of 7 genes encoding bZIP proteins were differentially expressed in maize RH
following rehydration (Table 8.5). A total of 25 WRKY transcription factors also showed
differential expression including an ortholog of OsWRKY71, previously shown to help mediate
drought tolerance (Yang et al., 2009). A putative ortholog of the rice Enhanced Disease
Resistance 1 (EDR1, loc_os03g06410) kinase, involved in conferring tolerance to pathogen
infection (Shen et al., 2011), was down-regulated in maize RH following rehydration. EDR1 is a
putative repressor of WRKY transcription factors in Arabidopsis (Christiansen et al., 2011),
consistent with the fact that 23 of the 25 WRKY genes were up-regulated in maize RH following
the water treatment (Table 8.5).
8.4.5.5 ESKIMO 1 regulon
An important negative regulator of freezing tolerance in Arabidopsis, independent of the
CBF/DREB1 pathway, is ESKIMO 1 (ESK1), a member of the DUF231 domain family, which
also regulates genes affected by osmotic, salt and ABA treatments (Xin and Browse, 1998; Xin
et al., 2007). In maize RH, a putative ortholog of Esk1 was down-regulated within 30 min
following rehydration (Table 8.5). In Arabidopsis, ESK1 regulates the expression of 44 putative
transcription factors or protein phosphatase 2C (PP2C) genes (Xin et al., 2007). Putative
306
orthologs of six of these Esk1-responsive genes were differentially altered in maize RH
following rehydration. These putative orthologs included: the transcription factors ATMYB13
(AT1G06180, GRMZM2G147346), ATWRKY33 (AT2G38470, GRMZM2G148087),
AT5G36710 (bHLH, GRMZM2G397509) and RAV2/RAP2.8 (AT1G68840,
GRMZM2G169654), along with two putative PP2C phosphatases
(AT3G05640/GRMZM2G069713 and AT1G07430/GRMZM2G010855), the latter being the
putative ortholog of HAI2 described above.
8.4.6 Downstream tolerance responses
Numerous downstream targets of drought/rehydration-induced transcription factors
and/or hormone-dependent signalling have been previously shown to mediate abiotic stress
tolerance (Shinozaki and Yamaguchi-Shinozaki, 2007).
8.4.6.1 Protein and amino acid osmoprotectants
Late embryogenesis abundant (LEA) proteins protect enzymes and lipids during
desiccation and are universally induced during drought (Oono et al., 2003; Rabbani et al., 2003;
Wang et al., 2011). A putative ortholog of LEA14 (NHL25, GRMZM2G069511), shown to be
induced by osmotic stress across numerous tissues in rice (Wang et al., 2011) and containing a
water-stress domain, was down-regulated during maize RH rehydration. LEA14 also contains a
fibronectin-like domain implicated in wound healing in animal cells (Singh et al., 2005). Other
putative LEA proteins were up-regulated (Table 8.6).
307
Table 8.6. Relative expression of osmoprotectant and osmotic solute related genes that
were differentially expressed in maize root hairs following rehydration. See table 8.1 for
details.
Lowest
adjusted
p-value
Dry
0 min
Rehydrated
30 min
Rehydrated
3h
0.0101
6.28
7.66
7.68
0.0276
9.85
7.57
7.37
GRMZM2G304378
Adhesive/proline-rich protein
Anther-specific proline-rich protein
APG
Hybrid proline-rich protein1
0.0172
4.64
7.56
7.59
GRMZM2G044448
Putative proline rich extensin
0.0008
5.62
8.46
8.29
GRMZM2G429982
Osmotin-like protein
Adenosyl 5'-phosphosulfate
reductase (APR), ortholog of
Arabidopsis APR2 (AT1G62180)
LEA protein (late embryogenesis
abundant)
LEA protein (late embryogenesis
abundant protein)
NHL25, LEA protein
Root cap protein, putative ortholog
of Arabidopsis LEA protein-related
(AT3G19430)
Delta-pyrroline-5-carboxylate
synthetase (P5cs)
Putative uroporphyrin-III Cmethyltransferase (tetrapyrrole
synthesis), porphyrin biosynthetic
process
Uroporphyrin-III Cmethyltransferase (tetrapyrrole
synthesis), porphyrin biosynthetic
process
0.0498
5.21
10.00
9.98
0.0178
7.10
7.70
7.58
0.0443
7.98
7.69
7.35
0.0298
8.65
4.52
4.44
0.0029
6.30
6.91
7.15
0.0099
7.70
7.34
7.15
0.0369
7.89
8.01
7.80
0.0123
3.13
9.33
9.31
0.0007
5.49
3.81
3.49
0.0272
7.37
7.39
7.49
0.0353
6.79
7.46
7.65
0.0428
5.83
9.67
9.61
Gene
Description
Proteins
GRMZM2G354834
GRMZM2G070178
GRMZM2G087254
GRMZM2G061305
GRMZM2G157845
GRMZM2G069511
GRMZM2G097316
GRMZM2G375504
GRMZM2G000739
GRMZM2G105604
Sugars
GRMZM2G057983
GRMZM2G153704
GRMZM2G466545
Ortholog of Arabidopsis ALMT9
(aluminum-activated malate
transporter 9, AT3G18440),
Ortholog of rice ALMT1
(loc_os02g49790)
Hexose transporter, Glucose
translocator1, ortholog of
Arabidopsis GLT1 (glucose
plastidic translocator, AT5G16150)
Ortholog of Arabidopsis and rice
PHO1 (protein phosphate
transporter 1,AT3G23430,
loc_os02g56510)
308
Table 8.6 (continued)
GRMZM2G044237
Glutamate N-acetyltransferase
0.0459
7.73
5.84
6.15
GRMZM2G147450
Carbamoyl-phosphate synthase
Hexokinase, ortholog of
Arabidopsis HKL1
(HEXOKINASE-LIKE 1,
AT1G50460)
Hexokinase-1, putative ortholog of
Arabidopsis HXK2
(HEXOKINASE 2, AT2G19860)
Glucose-6-phosphate/phosphate
translocator
Invertase 1, beta-fructofuranosidase
1 precursor (EC 3.2.1.26)
Trehalose biosynthetic process,
ortholog of Arabidopsis trehalosephosphatase synthase 9 (TPS9,
AT1G23870)
Trehalose biosynthetic process,
ortholog of Arabidopsis trehalosephosphatase synthase 9 (TPS9,
AT1G23870)
Putative hexokinase, ortholog of
Arabidopsis HKL1
(HEXOKINASE-LIKE 1,
AT1G50460)
Trehalose biosynthetic process,
ortholog of Arabidopsis trehalose6-phosphatase synthase
(AT4G39770)
Trehalose biosynthetic process,
ortholog of Arabidopsis trehalosephosphatase synthase 7 (TPS7,
AT1G06410)
Trehalose biosynthetic process,
ortholog of Arabidopsis trehalosephosphatase synthase 7 (TPS7,
AT1G06410)
0.0147
8.44
5.06
5.46
0.0384
5.06
3.54
3.75
0.0339
6.59
3.90
4.02
0.0361
6.79
4.41
4.26
0.0158
9.37
4.41
4.26
0.0367
5.01
6.24
6.89
0.0367
5.01
7.25
7.17
0.0150
5.63
6.52
6.64
0.0094
6.89
4.88
5.09
0.0276
7.40
6.87
7.49
0.0450
8.38
6.87
7.49
0.0243
5.76
6.66
6.43
0.0130
6.57
6.66
6.43
0.0207
9.32
6.66
6.43
0.0305
4.02
6.83
6.82
0.0327
8.08
6.90
6.85
GRMZM2G068913
GRMZM2G051806
GRMZM2G009223
GRMZM2G394450
GRMZM2G008226
GRMZM2G366659
GRMZM2G467069
GRMZM2G151044
GRMZM2G123277
GRMZM2G304274
Solutes
GRMZM2G414540
GRMZM2G113165
GRMZM2G057616
GRMZM2G022915
GRMZM2G063492
Syntaxin, SNAP receptor activity,
vesicle-mediated transport, putative
ortholog of Arabidopsis SYP121
(syntaxin of plants 121)
Putative ortholog of Arabidopsis
alpha carbonic anhydrase 7 (ACA7,
AT1G08080)
Chloride channel protein, ortholog
of Arabidopsis chloride channel A
(CLC-A, AT5G40890)
Ortholog of Arabidopsis potassium
channel 1 (AKT1, AT2G26650)
Sodium/hydrogen antiporter,
ortholog of Arabidopsis NHX2
(SODIUM HYDROGEN
EXCHANGER2, AT3G05030)
309
Table 8.6 (continued)
GRMZM2G338809
GRMZM2G138731
GRMZM2G395114
GRMZM2G444801
Ammonium transmembrane
transporter, ortholog of Arabidopsis
AMT2.1
Putative ortholog of Arabidopsis
NRT1.2 (nitrate transporter 1.2,
AT1G69850)
Sulfate transporter, ortholog of
Arabidopsis sulfate transporter 91
(AST91/SULTR3.3, AT1G23090)
Sulfate transporter 3.4
0.0457
11.10
7.70
7.58
0.0106
6.09
8.20
8.06
0.0415
6.42
8.66
8.28
0.0167
6.80
5.25
5.21
310
Proline is an important osmoprotectant during drought and salt stress (Székely et al.,
2008). The enzyme delta-1-pyrroline-5-carboxylate synthetase (P5CS) catalyses the rate-limiting
step of proline biosynthesis from glutamate, and is up-regulated by ABA, osmotic stress and
drought in Arabidopsis (Székely et al., 2008; Zhou et al., 2010). Surprisingly, a P5CS was upregulated in maize RH within the first 3 h (Table 8.6), suggesting that the proline biosynthetic
pathway response to rehydration may be delayed. Several proline-rich proteins also showed
altered regulation (Table 8.6).
The amino acid citrulline is a compatible solute implicated in drought tolerance in
African melon xerophytes, accumulating to up to 50% of the amino acid content in leaves during
drought (Kawasaki et al., 2000). Two enzymes required for citrulline biosynthesis were upregulated in maize RH including glutamate N-acetyltransferase (GRMZM2G044237), which
encodes the first and fifth step in citrulline biosynthesis, and carbamoyl-phosphate synthase
(GRMZM2G147450), which encodes the last step (Takahara et al., 2005). Citrulline is a
precursor for arginine but none of the genes encoding subsequent enzymes for arginine (or
ornithine) biosynthesis were differentially expressed in this study, suggesting that citrulline may
accumulate and protect RH during stress, a novel finding that will require further experiments.
The above osmoprotectant amino acids and proteins require macronutrients such as
nitrogen (N), sulfur (S) and phosphorus (P). Several genes implicated in uptake, transport or
assimilation of these minerals were differentially expressed in maize RH following rehydration,
including transporters for N (NRT1.2; AMT2), P (PHO1) and S (ortholog of AtSULTR3.3;
SULTR3.4) (Table 8.6). One of the most dramatic changes in gene expression in maize RH
following rehydration was a gene encoding uroporphyrinogen III methyltransferase (SUMT,
GRMZM2G105604) which was up-regulated 10-fold and 23-fold at t30 and t3h, respectively.
311
SUMT has been implicated in the synthesis of siroheme (Leustek et al., 1997), a tetrapyrrole cofactor that regulates nitrite reductase and sulfite reductase, enzymes required for N and S
assimilation, respectively (Tripathy et al., 2010). Another gene (GRMZM2G000739) encoding a
similar tetrapyrrole methylase domain (IPR000878) was also up-regulated three-fold in maize
RH at t3h. In addition to nutrient assimilation, siroheme is required for enzymes involved in
stress-mediated scavenging of ROS including during drought (Tripathy et al., 2010). A gene
encoding the key enzyme for sulfate assimilation, adenosyl 5'-phosphosulfate reductase and
ortholog of AtAPR2 (Kopriva and Koprivova, 2004), was also differentially expressed during
rehydration.
8.4.6.2 Malate and sugar osmoprotectants
The dicarboxylic acid malate is a well-known compatible solute associated with drought
tolerance (Meyer et al., 2010). An ortholog of aluminum-activated malate transporter 9, ALMT9,
which encodes a vacuole transporter for malate (Kovermann et al., 2007), was down-regulated in
maize RH after rehydration. Knockouts of ALMT orthologs are associated with defects in ABA
signalling (Meyer et al., 2010).
Trehalose, a disaccharide consisting of two glucose molecules, has been shown to protect
plants against dehydration and is the major soluble sugar in resurrection plants such as
Selaginella ssp, where it protects membranes and proteins (Fernandez et al., 2010). Exogenous
trehalose treatment in Arabidopsis induced genes related to drought stress including cell wall
formation, ethylene and jasmonate signalling (Bae et al., 2005). Similar to the proline pathway,
orthologs of the Arabidopsis trehalose biosynthesis genes, trehalose-phosphate synthases
ATTPS9 and ATTPS7, were up-regulated up to two-fold in RH at 3 h following aqueous
treatment (Table 8.6). A putative ortholog of trehalose-6-phosphate phosphatase (TPP),
312
previously shown to be repressed during drought in maize tassels (Fernandez et al., 2010), was
down-regulated in RH after aqueous treatment.
Trehalose was shown to reduce the expression of genes involved in starch breakdown
including a glucose plastidic translocator (GLT1, AT5G16150) (Ramon et al., 2007). Contrary to
the increase in trehalose synthesis in maize RH, the ortholog of GLT1 was activated ~two-fold at
t3h in RH cells. Additionally, a glucose-6-phosphate translocator (GRMZM2G009223) was upregulated in maize RH in response to rehydration.
Hexokinases phosphorylate hexose sugars such as glucose and regulate their availability
in the cell (Claeyssen and Rivoal, 2007). The ortholog of the hexokinase AtHKL2, maize
Hexokinase I, was up-regulated. This gene was previously shown to be expressed during drought
stress (Claeyssen and Rivoal, 2007). Two of the putative orthologs of the AtHKL1 hexokinase
(GRMZM2G068913, GRMZM2G467069), had opposite changes in expression. HKL1 is a
repressor of plant growth during stress (Karve and Moore, 2009) and activates ABA signalling
during drought (Arenas-Huertero et al., 2000; Lin et al., 2007).
Finally, a paralog of maize Invertase 1 (GRMZM2G394450) was down-regulated at
t30min and t3h. In Arabidopsis, Invertase 1 was previously shown to affect RH elongation under
osmotic stress (Qi et al., 2007).
8.4.6.3 Inorganic osmotic solutes
Inorganic ions, including Na+, K+, Ca2+ and Cl-, contribute to osmotic adjustment during
drought. The maize ortholog of NHX2, which encodes a Na+/H+ antiporter, shown to sequester
K+ in the vacuole (Bassil et al., 2011), was down-regulated in maize RH following rehydration.
In wheat, NHX2 appears to be induced by salt, cold, osmotic stress and ABA (Yu et al., 2007).
An ortholog of the K+ transporter AKT1, also shown to be involved in regulating Na+ uptake and
313
distribution in plants (Kronzucker and Britto, 2011), was up-regulated in maize RH. A putative
ortholog of the membrane vesicle trafficking (SNARE) protein SYNTAXIN OF PLANTS 121
(SYP121) was also up-regulated. SYP121 was previously identified in a genetic screen for genes
involved in ABA and drought, and was later shown to interact with the AKT1 K+ channel
subunit to regulate K+ uptake including in root epidermis (Honsbein et al., 2009). Two putative
chloride channel orthologs, including an ortholog of chloride channel A (ATCLC-A), were both
down-regulated in maize RH following rehydration. ATCLC-A was previously shown to be
repressed by ABA (Quettier et al., 2006), though its up-regulation was associated with drought
and salt tolerance in Arabidopsis (Zhou et al., 2010). ATCLC-A was also shown to be critical for
nitrate accumulation in plant vacuoles (De Angeli et al., 2006).
An alpha-type carbonic anhydrase (CA, GRMZM2G113165), which catalyzes the
interconversion of CO2 to bicarbonate, was up-regulated in maize RH following rehydration. CA
reduces respiratory-derived CO2 in the root to permit continued respiration, but exported
bicarbonate is also required for cation uptake from soil by roots (e.g. K+, Na+, Ca2+) via protonmediated base exchange (Dimou et al., 2009). Interestingly, CA was also strongly up-regulated
during rehydration in the resurrection plant Craterostigma plantagineum (Rodriguez et al., 2010).
8.4.6.4
Other Genes Implicated in Drought/Rehydration
Two putative orthologs of Early Response to Dehydration 15 (ERD15,
GRMZM2G327692, GRMZM2G037189), a small acidic protein which has been shown to be a
negative regulator of ABA signalling (Kariola et al., 2006), were both up-regulated in maize RH
following rehydration. ERD15 overexpression has been shown to reduce drought tolerance in
Arabidopsis, and appears to mediate JA-dependent biotic stress tolerance, perhaps helping to
coordinate abiotic and biotic stress responses (Kariola et al., 2006). A putative ortholog of ERD4
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(GRMZM2G128641) was down-regulated in maize RH after rehydration. Overexpression of
maize ERD4 has been shown to be induced by ABA and drought, to improve drought tolerance
in Arabidopsis, and has been suggested to be part of the chloroplast envelope proteome (Liu et
al., 2009).
An ortholog of the hydrophobic integral plasma membrane protein RCl2A/LTI6a,
induced by ABA and several abiotic stresses including dehydration (Medina et al., 2005), was
down-regulated <two-fold in maize RH following rehydration. RCl2A/LTI6a has been used as
an important marker of the CBF/DREB1-independent response to cold, salt and dehydration in
Arabidopsis (Medina et al., 2005).
Metallothionein-like (MT) proteins, which bind metals, were identified as abiotic stress
related genes (Rabbani et al., 2003; Wang et al., 2011). A gene encoding Metallothionein 1
(MT1) was down-regulated in maize RH at t30min and t3h. Overexpression of the ortholog of
MT1 (OsMT1) conferred improved drought tolerance in rice (Yang et al., 2009), perhaps by
detoxifying heavy metals and reactive oxygen species (ROS) (Yang et al., 2009). OsMT1 is
highly expressed in roots and activates the expression of three genes known to be involved in
drought tolerance including OsWRKY71 and OsZF1 (Yang et al., 2009). Interestingly, putative
orthologs of OsWRKY71 (GRMZM2G120320) and OsZF1 (GRMZM2G113860) were upregulated in maize RH in this study. Maize Uncoupled 5 (UCP5), an ortholog of another gene
implicated in alleviating ROS stress (AtUCP1), was also up-regulated in maize RH after
watering. UCPs uncouple electron transport from ATP synthesis in the mitochondrion, and
AtUCP1 expression improves tolerance to salt and drought in transgenic tobacco (Begcy et al.,
2011). An ortholog of Arabidopsis magnesium/proton exchanger 1 (MHX1, AT2G47600), which
regulates the transport of metal ions between the vacuole and the cytoplasm (Berezin 2008), was
315
down-regulated in maize RH at t3h. MHX1 had been linked to ABA expression during drought
stress (Huang et al., 2008).
The Target of Rapamycin (TOR) kinase pathway couples amino acid and energy supplies
with protein translation capacity (Ma and Blenis, 2009). In the TOR pathway, the CCR4-NOT
complex acts as a global regulator of gene expression (Collart, 2003). Altered expression of
CCR4 associated proteins have been observed during nutrient limitation, rehydration and drought
(Oono et al., 2003; Lee et al., 2009). An ortholog of rice CCR4-NOT subunit 8
(loc_os04g58810) (Aslam et al., 2009) was up-regulated in maize RH after watering.
Downstream of the TOR kinase is MAF1, an important repressor of RNA polymerase III which
represses the transcription of genes encoding 5S RNA and tRNA in yeast, coupling nutrient
limitation or stress to protein translation (Upadhya et al., 2002). Maize MAF1 was downregulated in maize RH in response to rehydration. Furthermore, a gene encoding a putative
ortholog of Arabidopsis-Mei2-Like 1 (AML1) protein (Anderson and Hanson, 2005; Kaur et al.,
2006), was also down-regulated. AML1 could be phosphorylated by the TOR kinase (Anderson
and Hanson, 2005) and was previously shown to be involved in root growth (Kaur et al., 2006).
Several genes involved in vesicle trafficking showed altered regulation during
rehydration. Synaptotagmin 1 (SYT1), a calcium-dependent membrane fusion protein that
facilitates delivery of lipid membrane to wound sites, has been proposed to be involved in
plasma membrane repair such as following osmotic stress, freezing or drought (Schapire et al.,
2008). Maize Syt3, a homolog of Syt1, was down-regulated in RH following rehydration (Table
8.7). Syntaxins also participate in vesicle-mediated transport; several syntaxins showed altered
regulation in maize RH in this study, including orthologs of SYP121 as noted above (Honsbein
et al., 2009) and SYP132 (Table 8.7).
316
During various stresses such as drought and salt, autophagy proteins help to degrade and
recycle cellular contents and toxins via autophagosome vesicles which traffic to vacuoles and
lysosomes (Liu et al., 2009). During the maize RH response to rehydration, four autophagyrelated proteins were down-regulated: Autophagy-Related ATG4A, ATG4B, ATG8 and an
ortholog of AtATG18d (AT3G56440).
317
Table 8.7. Relative expression of other drought-related genes that were differentially
expressed in maize root hairs following rehydration. See table 8.1 for details.
Gene
Description
Lowest
adjuste
d
pvalue
Dry
0
min
Rehydrate
d 30 min
Rehydrate
d 3h
0.0468
7.93
9.82
9.64
0.0352
8.51
9.49
9.60
0.0458
9.37
5.03
4.98
0.0218
8.52
4.89
5.33
Autophagyrelated
GRMZM2G064212
GRMZM2G173682
GRMZM2G076826
GRMZM2G069177
Autophagy-related 4a variant
protein
Autophagy-related 4b variant
protein
Autophagy-related 8c variant
protein
Putative ortholog of Arabidopsis
ATG18d (AT3G56440)
Biotic stress
GRMZM2G006468
Wound responsive protein
0.0112
4.97
4.25
4.21
GRMZM2G003682
0.0453
5.73
5.57
6.16
0.0433
6.47
6.11
6.26
GRMZM2G073548
Nematode-resistance protein
Pollen signalling protein with
adenylyl cyclase activity
TMV response-related protein
0.0004
6.79
6.98
6.88
GRMZM2G082199
Elicitor-responsive protein
0.0006
7.89
7.01
7.11
GRMZM2G054807
Avr9/Cf-9 rapidly elicited protein
0.0002
7.97
7.68
7.60
GRMZM2G171036
0.0462
8.87
9.53
9.58
0.0376
9.45
8.92
8.69
GRMZM2G149809
Plant viral-response family protein
Disease resistance response
protein
Thaumatin-like protein
0.0312
8.61
8.51
GRMZM2G112524
Pathogenesis-related protein
0.0174
6.29
6.11
GRMZM2G112538
Pathogenesis-related protein
0.0174
5.17
4.78
GRMZM2G132273
Disease resistance response
protein
0.0116
6.39
6.23
GRMZM2G072612
Pathogenesis-related protein
0.0369
9.53
10.0
6
10.0
6
10.4
0
10.8
6
6.39
6.23
GRMZM2G050118
Heat shock protein binding
0.0288
4.50
7.25
7.33
GRMZM2G124644
Heat shock protein binding
Heat shock 70 kDa protein
binding
Heat shock protein binding,
protein folding
Heat shock protein binding
Heat shock protein binding,
putative ortholog of Arabidopsis
HSFA6B
Heat shock protein binding,
0.0391
4.80
5.84
5.74
0.0450
5.54
9.13
9.04
0.0200
5.60
8.44
8.64
0.0196
6.03
9.31
9.33
0.0062
7.93
7.53
7.33
0.0312
8.45
9.69
9.55
GRMZM2G060583
GRMZM2G320023
Heat shock
GRMZM2G063676
GRMZM2G469901
GRMZM2G117836
GRMZM2G125969
GRMZM2G448368
318
protein folding
GRMZM2G019056
Drought-induced heat shock
Table 8.7 (continued)protein binding, protein
GRMZM2G099067
Heat shock protein binding,
protein folding
Harpin-induced protein
GRMZM2G049288
Heat shock protein binding
GRMZM2G003635
0.0361
8.62
9.01
9.05
0.0077
9.73
11.06
10.88
0.0106
7.04
9.81
9.55
0.0425
6.73
9.73
9.59
0.0004
8.26
9.06
9.34
0.0061
8.51
6.79
6.55
0.0443
12.2
2
7.95
7.68
0.0352
7.99
8.39
8.43
0.0149
9.08
5.63
5.51
0.0225
12.5
4
7.54
7.49
0.0379
8.45
6.75
6.89
0.0133
9.28
6.90
7.38
0.0391
6.00
5.38
5.20
0.0321
7.64
9.02
8.51
0.0162
6.83
4.98
6.24
0.0288
8.04
9.77
9.75
0.0158
9.98
10.83
10.68
0.0375
5.14
7.63
7.47
0.0038
5.26
7.49
7.71
0.0458
8.09
5.25
5.47
Phenylpropanoids
GRMZM2G375159
GRMZM2G010987
GRMZM2G147245
GRMZM2G114471
GRMZM2G051005
GRMZM2G160541
GRMZM2G038722
GRMZM2G118345
Ortholog of putative rice protein
10-deacetylbaccatin III 10-Oacetyltransferase
Anthocyanidin 5,3-Oglucosyltransferase
Ortholog of Arabidopsis transcinnamate 4 hydroxylase (C4H,
AT2G30490)
Putative ortholog of Arabidopsis
Transparent Testa 4 (TT4,
AT5G13930), naringeninchalcone synthase
Putative ortholog of Arabidopsis
hydroxycinnamoyltransferase
(HCT, AT5G48930) shikimate Ohydroxycinnamoyltransferase
Phenylalanine ammonia-lyase
(PAL), ortholog of Arabidopsis
PAL4 (AT3G10340)
Myb-related protein Zm1, putative
ortholog of Arabidopsis MYB63
(AT1G79180)
Phenylalanine ammonia-lyase
(PAL), ortholog of Arabidopsis
PAL1 (AT2G37040)
Additional
GRMZM2G477325
GRMZM2G102347
GRMZM2G156956
GRMZM2G121166
GRMZM2G436593
GRMZM2G448883
GRMZM2G177340
GRMZM2G149636
Hydrophobic protein RCI2/LTI6A
Putative ortholog of Arabidopsis
abscisic acid-responsive HVA22
family protein
Putative ortholog of Arabidopsis
MEI2-like protein 1 (AT5G61960)
Repressor of RNA polymerase III
transcription MAF1
Uncoupled protein 5 (UCP5)
Phi-1-like phosphate-induced
protein
Putative ortholog of rice CCR4NOT subunit 8 (loc_os04g58810)
Ortholog of rice senescenceassociated protein 15 (SAP15,
loc_os03g14170)
319
Putative ortholog of rice zincfinger protein 1 (OsZF1,
loc_os03g32230)
GRMZM2G161154
Metallothionein-like protein type
Table 8.7 (continued) Metallothionein 1,
GRMZM2G164229
metallothionein-like protein
GRMZM2G163157
6b-interacting protein
GRMZM2G113860
GRMZM2G088064
GRMZM2G126601
GRMZM2G140443
GRMZM2G044527
GRMZM2G330772
Alanine aminotransferase
Ortholog of Arabidopsis
magnesium proton exchanger 1
(MHX1, AT2G47600)
Ortholog of Arabidopsis
synaptotagmin 3 (SYTC,
AT5G04220)
Syntaxin, SNAP receptor activity,
ortholog of Arabidopsis syntaxin
of plants 132 (SYP132)
Syntaxin, SNAP receptor activity,
ortholog of Arabidopsis syntaxin
of plants 132 (SYP132)
0.0006
2.84
8.01
8.33
0.0477
7.70
7.89
7.80
0.0246
9.24
9.05
8.96
0.0073
6.52
8.21
8.25
0.0433
8.03
5.69
5.80
0.0433
7.90
5.95
6.25
0.0115
5.18
6.75
6.78
0.0484
8.60
6.75
7.01
0.0484
8.60
7.75
7.73
320
Additional classes of genes that showed altered regulation in maize RH following
rehydration included chaperone/heat shock proteins, genes involved in phenylpropanoid
biosynthesis including phenylalanine ammonia lyase (PAL), peroxidases, wound-induced genes,
and biotic stress resistance genes including those involved in the hypersensitive response (HR)
(Table 8.7). Members of these gene classes have previously been implicated in drought and/or
rehydration (Lee et al., 2009; Marino et al., 2009; Wang et al., 2011). One of the most interesting
of these responses was the up-regulation of the ortholog of tobacco 6b-Interacting Protein (SIP),
a transcription factor that mediates cell expansion and proliferation following interaction with
Agrobacterium oncogene 6b (Kitakura et al., 2002). Furthermore, five senescence-associated
genes were differentially expressed in maize RH, notably two genes encoding orthologs of rice
senescence-associated protein 15 (SAP15), previously shown to be expressed during drought
stress in rice (Wang et al., 2011). A gene encoding alanine aminotransferase (AlaAT) showed
enhanced expression in maize RH following rehydration. AlaAT catalyzes the transfer of an
amino group from alanine to alpha-ketoglutarate, the products of this reversible reaction being
glutamate and pyruvate. AlaAT has shown altered regulation during hypoxia (Miyashita et al.,
2007) but also rehydration (Good and Zaplachinski, 1994; Oono et al., 2003). A putative
ortholog of HVA22, an ABA-, drought- and abiotic stress inducible gene family proposed to be
involved in stress tolerance but of unknown biochemical function (Chen et al., 2002), was downregulated in this study. An ortholog of phi-1-like phosphate-induced protein (Sano et al., 1999),
previously shown to be induced during rehydration in Arabidopsis (Oono et al., 2003), was also
activated in maize RH at t3h. The promoter of the Arabidopsis ortholog if phi-1-like contains the
motif ACTCAT associated with rehydration (Satoh et al., 2002; Oono et al., 2003).
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8.4.7 Interpreting transcriptome results
As shown by these results, many genes normally induced by drought in previous studies
(Rabbani et al., 2003; Lee et al., 2009; Zheng et al., 2010; Wang et al., 2011) were surprisingly
induced in maize RH during the first 3 h following rehydration. These genes including those
involved in ABA and JA biosynthesis, transcription factors such as DREB/CBF, and downstream
osmoprotectants and osmotic solutes. The simplest explanation is that some of these genes were
continuing to respond to the extended 10 day localized drought treatment. In Arabidopsis, a
transcriptome analysis using whole-seedlings demonstrated that rehydration and recovery
responses extended over a 24 hour period (Oono et al., 2003). If we interpret the data presented
here in that context, our differentially expressed drought genes can be categorized into two broad
classes: late recovery genes (up-regulated drought genes) acting as markers of drought, and early
recovery genes (down-regulated drought genes) acting as markers of rehydration. An alternative
hypothesis, however, is that our rehydration treatment may have triggered a new osmotic stress
in the short-term, caused by an imbalance in the solute concentration in the RH cells compared to
the aqueous solution added. An extended time course following rehydration may help in
interpreting the results of this study.
Another caveat when interpreting these results is that our rehydration treatment involved
adding not only water, but water containing nutrients, to RH. If RH responses to nutrients can be
local rather than global, some of the differentially expressed genes from this study may have
been responding to added nutrients rather than rehydration per se (e.g. nitrogen, phosphate,
sulfur pathways). In soil, however, it could be argued that rainfall following an extended drought
would similarly dissolve minerals, and hence these results are mimicking the real-world
response.
322
The last cautionary note is that some of these results may not have been responses to
rehydration but rather to anoxia or ROS, as our RH were submerged in H20 for 3 h with the
oxygen source being H202. An argument against an anoxia interpretation, is that the canonical
markers for anoxia, alcohol dehydrogenase (ADH) (Mustroph et al., 2010), were primarily
down-regulated rather than up-regulated, following watering (Table 8.3). We also did not
observe many of the transcriptome responses normally associated with flooding (Mustroph et al.,
2010). However, as noted below, a cis-element motif associated with anaerobic stress was one of
the motifs found to be over-represented in the promoters of the genes that were differentially
expressed in this study, suggesting caution in interpreting some of the responses observed.
8.4.8 Prediction of cis-acting promoter motifs
Finally, we searched for putative cis-acting motifs in the promoters (-1000 to +1) of the
genes that were differentially expressed in maize RH following rehydration. Promoters were first
grouped into non-ambiguous gene expression clusters where possible (Figure 8.7). Shared de
novo motifs within each cluster were then searched (see Chapter 3.3, Materials and Methods
section), but only the most over-represented motifs are presented here. The majority of the
candidate motifs were previously identified as regulating the transcription of seed storage protein
genes, many of which are regulated by ABA (Giraudat et al., 1992; Thomas, 1993).
323
Figure 8.7. Cis-acting elements found in the promoters of genes differentially expressed in
root hairs following rehydration. The four expression clusters are illustrated as heatmaps
where dark blue represents up-regulated genes and yellow represents down-regulated genes at
each time point following rehydration. The consensus sequence of each over-represented motif is
shown, where N=any nucleotide, Y=C/T. The frequency of the location of each motif within the
promoters is indicated (Motif Frequency).
324
First, two seed storage protein promoter motifs were retrieved in Cluster 1 which
included 839 genes highly expressed during drought but then repressed within 30 min following
rehydration. The first promoter motif over-represented in Cluster 1 was SEF3, first identified as a
binding site for Soybean Embryo Factor 3, responsible for transcription of seed storage protein
ß-conglycinin (Allen et al., 1989; Lessard et al., 1991). The second Cluster 1 promoter motif
retrieved (CAAACNCAC) was highly similar to the CA(n)-element CAAACAC first identified
as part of the B-box in the promoter of the gene encoding Brassica napus seed storage protein
napin A (Stålberg et al., 1996; Ezcurra et al., 2000). The CA(n)-element was shown to be one of
two motifs required for seed specific expression, the other being the ABA Response Element,
ABRE (Stålberg et al., 1996; Yamaguchi-Shinozaki and Shinozaki, 2005). The CA(n)-element
was shown to be conserved in >103 out of 113 seed storage protein promoters across species and
thought to amplify the response of the ABRE box (Stålberg et al., 1996). A napin A ortholog was
recently shown to be induced during drought in maize plants (Zheng et al., 2010).
The 583 genes in Cluster 2 were repressed during drought but activated by watering,
achieving peak expression within 30 min. Cluster 2 motifs included CCTGTTC, highly similar to
a motif previously identified in the promoter of the rice seed storage protein glutenin gene (Kim
and Wu, 1990). Two closely related motifs highly similar to the bZIP Vascular Specificity Factor
(VSF-1) binding site GCTCCGTTG (Ringli and Keller, 1998) were also over-represented in
Cluster 2 promoters. The VSF-1 binding site has been found in promoters of maize seed storage
protein zein genes (So and Larkins, 1991) as well as the promoter of the ABA-inducible LEA
gene AtEm1 (Vicient et al., 2000).
Two additional clusters, not originally separated from Clusters 1 and 2 using the
microarray empirical Bayesian model (Smyth, 2004), were identified using the HOPACH
325
clustering method (Van der Laan and Pollard, 2003) (Figure 8.7). The 259 genes in Cluster 3
were repressed during drought and reactivated by water, achieving peak expression 3 h later.
Three motifs closely related to a motif over-represented in anaerobically-induced genes
(ANAERO4CONSENSUS, GTTTHGCAA) (Mohanty et al., 2005) were abundant in Cluster 3
promoters. One possibility is that RH experienced mild anoxia 3 h after the water treatment in
spite of the presence of an oxygen source, as noted above. Another two motifs retrieved in
Cluster 3 promoters contained the core consensus sequence CCCGCTT, highly related to the
BS1 EgCCR gene promoter motif (CCCGCT). This motif was originally identified in the
promoter of the Eucalyptus gunnii cinnamoyl-CoA reductase gene, which encodes the first step
in lignin biosynthesis (Lacombe et al., 2000). The BS1 EgCCR motif was located adjacent to
MYB binding sites, but was not required for MYB binding (Rahantamalala et al., 2010). More
recently, the BS1 EgCCR motif was found in four seed-specific promoters in maize, but whether
or not this motif contributes to this tissue specificity has not been reported (Fu, 2011).
Cluster 4 was intriguing as these genes were highly expressed during drought, repressed
within 30 min following rehydration, but then moderately reactivated 2.5 hours later. The RYrepeat motif, also known as the FUS3/Sph motif (CATGCA) (Giraudat et al., 1992; Reidt et al.,
2000), was present in the promoters of 17 out the 18 genes in Cluster 4. The RY motif can bind
Domain 3 of the master ABA transcription factors ABI3 and VP1, and is thought to be the
ancestral target of these proteins, now replaced by ABRE in angiosperms (Giraudat et al., 1992;
Reidt et al., 2000; Sakata et al., 2010). The RY motif controls late embryogenesis and seed
development, and its ACGT core regulates cereal seed storage genes (Reidt et al., 2000;
Yamamoto et al., 2006). The RY motif may also help to mediate signal cross-talk, as the B3
domain is present in proteins related to ABA, ethylene (ERF) and auxin (ARF) signalling as well
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as the cold responsive transcription factor RAV1 (Yamasaki et al., 2004; Nag et al., 2005). At
least two genes encoding B3 domain-containing RAV proteins (PF02362), ZmRAV1
(GRMZM2G169654) and a putative RAV (GRMZM2G018336), were differentially expressed in
maize RH in response to rehydration.
Most of the Cluster 4 promoters also contained a Squamosa Promoter Binding Protein
(SBP)-box, shown to be involved primarily in floral development but also trichome initiation
(Shikata et al., 2009). As noted earlier, this result is predictive of a jasmonate -Tasselseed 1 (Ts1)
regulon acting in RH through miR156, as the latter two regulators have been implicated in
regulating a subset of genes in maize containing an SBP box (Hultquist and Dorweiler, 2008;
Shikata et al., 2009).
Many of the above cis-acting motifs and their binding proteins have been described as
being completely seed specific (Thomas, 1993). Indeed some of the motifs identified here are
often found adjacent to one another in the promoters of genes encoding seed storage molecules.
For example, the upstream sequence of the soybean oleosin gene contains SEF, CA(n), RY and
ABRE elements (Rowley and Herman, 1997). Our results now suggest that the regulatory
programs operating in seeds, including those involving ABA signalling, may also be functioning
in RH to regulate drought/rehydration responses.
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8.5 Conclusions
To our knowledge, no previous experiments have reported the transcriptome response by
RH to water availability in any species, including maize. At least 1831 genes were differentially
expressed in maize RH during the first 3 h of rehydration following an extended drought,
including genes encoding proteins previously shown to help mediate drought and abiotic stress
tolerance (summarized in Figure 8.8). Differentially expressed genes included those encoding
transcription factors DREB/CBF, MYC/MYB, NAC, WRKY and bZIP. A putative ESKIMO1
regulon was also uncovered. Maize RH also respond to a change in water availability by altering
the expression of genes regulating osmotic solutes and osmoprotectants. Microarray results
suggest that the amino acid citrulline, previously shown to be important in drought tolerance of
African xerophytic melons, may also be an important osmoprotectant in maize RH. Drought and
rehydration affected genes involved in secondary messenger signalling involving phospholipids,
kinases and calcium, along with altered expression of hormone biosynthesis and signaling
pathways (jasmonates, ethylene, GA, auxin). Important genes involved in RH development and
growth were also affected by water stress. Interestingly, the majority of candidate cis-acting
motifs shared by promoters of differentially expressed genes expressed in RH, were previously
categorized as conferring seed-specific gene expression, a novel finding. Microarray and
promoter motif results are consistent with a jasmonate-Tasselseed -Squamosa Promoter Binding
Protein (SBP/SPL) regulon acting in RH in response to water availability. We conclude that the
RH is a sensitive single cell reporter of water stress in plants. This study adds to the limited
physiological and molecular information about root hair-water relationships.
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Figure 8.8. Summary of root hair gene expression during early rehydration. Summarized
are previously characterized genes involved in water stress that were differentially expressed in
maize root hairs in the first 3 h following rehydration.
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9. Two QTLs Act Cooperatively to Bypass the Requirement for
Callus Induction Media (CIM) During in vitro Shoot
Regeneration in Arabidopsis thaliana (L.)
Author Contributions: Christophe Liseron-Monfils conducted all microarray experiments
and analyses and quantitative RT-PCR experiments. Steven P. Chatfield helped to conceive the
experiments, performed the hormone experiments and time course developmental analysis, and
helped to edit the manuscript. Jan Brazolot performed the DNA marker experiments. SJD
assisted with regeneration assays. Adrienne Davidson assisted with RT-PCR experiments. Erin
Hewitt performed the initial natural variation survey. RO generated the backcross mapping
populations. Natalie DiMeo, Salome Ndung’u, Arani Kajenthira, Carly A. Wight, Amelio Thé
and Mimi Tanimoto assisted with the hormone and/or regeneration assays.
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9.1 Abstract
Plant hormones are used to regulate in vitro organogenesis from plant tissues. Across
diverse species, a high auxin/low cytokinin pre-treatment, known as Callus Induction Media
(CIM), is often required to render excised tissues competent to regenerate shoots in vitro. Here,
we conducted a natural variation screen in Arabidopsis thaliana to discover ecotypes that could
regenerate in the absence of CIM. Nossen-0 (No-0) was identified as a CIM-bypass ecotype.
Regeneration from No-0 explants was less sensitive to alterations in the concentration/ratio of
exogenous auxin/cytokinin compared to other ecotypes. Introgression of two No-0 chromosome
segments, corresponding to previously identified QTLs that promote shoot regeneration,
conferred the CIM-bypass ability to ecotype Landsberg erecta (Ler). These chromosome
segments acted cooperatively as dosage-dependent genetic enhancers of one another. In a Ler
Near Isogenic Line population (Ler-NIL), the Chromosome 5 No-0 segment caused intact
seedlings to become less sensitive to exogenous auxin or cytokinin. ATH1 arrays were used to
test the effects of each introgressed No-0 chromosome segment on the Ler-NIL transcriptome.
The Chromosome 5 No-0 segment caused differential expression of 507 genes compared to 130
genes by the Chromosome 4 segment, reflective of their relative impacts on shoot regeneration.
No-0 segment-responsive genes that showed altered transcript accumulation encoded: auxin
biosynthetic enzymes (Nitrilase 3; CYP79B2); an enzyme that degrades cytokinin (Cytokinin
Oxidase 3) or mediates cytokinin/ethylene signalling (Cytokinin Response Factor 3); and two
ACC Oxidases that encode the last step in ethylene biosynthesis. We conclude that these two
chromosome segments encode major regulators of shoot regeneration competency.
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9.2 Introduction
In nature and in the laboratory, tissues excised from plants often demonstrate a
remarkable ability to regenerate new shoots and organs. In vitro, these explants often require a
high auxin/low cytokinin (HA/LC) pre-treatment for a few days in Callus Induction Media
(CIM) which contains high auxin/low cytokinin (HA/LC), to make them competent to regenerate
new organs (Christianson and Warnick, 1984; Hicks, 1994; Sugiyama, 1999; Che et al., 2002;
Che et al., 2006). Following the CIM pre-treatment, continued exposure to a HA/LC medium
promotes root organogenesis, whereas exposure to high cytokinin/low auxin (in Shoot Induction
Media, SIM) promotes shoot organogenesis (Skoog and Miller, 1957; Christianson and Warnick,
1983, 1985; Valvekens et al., 1988). Some species are able to regenerate organs directly and do
not require a high auxin pre-treatment, but the mechanism underlying this ability is not well
understood (Cary et al., 2002).
Understanding how CIM promotes competency to regenerate is of great interest and
tremendous applied value. Classically, it was hypothesized that callus-induction promotes
dedifferentiation, and generates a large population of de-programmed cells more amenable to
subsequent redifferentiation (Hicks, 1994; Sugiyama, 1999; Che et al., 2006). Subsequent data
using Arabidopsis thaliana mutants supported the idea that exogenous auxin creates an auxin
maxima that is required for cytokinin to act as a shoot induction signal (Duclercq et al., 2011). A
number of elegant experiments have recently shown that CIM in fact induces callus from explant
xylem pole pericycle cells or pericycle-like cells that are already in an undifferentiated state, and
do not need to be stimulated to undergo de-differentiation (Che et al., 2007; Gordon et al., 2007;
Atta et al., 2009; Sugimoto et al., 2010; Sugimoto et al., 2011). Pericycle cells normally initiate
lateral roots (LR), and mutants that block LR formation also inhibit callus production (Atta et al.,
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2009; Sugimoto et al., 2010). Since auxin gradients regulate LR initiation and development, a
model has emerged wherein the role of auxin is to stimulate LR primordia from explants (Atta et
al., 2009; Sugimoto et al., 2010; Sugimoto et al., 2011).
A previous study (Lall et al., 2004) demonstrated that a major QTL from Arabidopsis
ecotype Columbia (Col) on Chromosome 5 (at 106.5 cM) and a minor QTL from ecotype
Landsberg erecta (Ler) on Chromosome 4 (at 60.9 cM) promoted shoot regeneration in a Ler x
Col recombinant inbred line (RIL) population from root explants. In that study, the explants were
always pre-treated with CIM prior to the SIM treatment. Shoot regeneration from recombinant
inbred lines (RILs) that contained these two QTLs co-segregated with microarray expression
clusters for genes that showed differential expression in explants on SIM media that had been
pre-treated with CIM (DeCook et al., 2006). These QTLs were classified as expression QTLs
(eQTLs) for shoot regeneration. However, the genes underlying these two QTLs have not been
isolated, nor has the physiological mechanism(s) by which these two QTLs act, been
characterized.
Following a natural variation screen and generation of near isogenic lines (NIL), here we
demonstrate that two chromosome segments from ecotype No-0 can confer on ecotype Ler-0 the
ability to bypass the requirement for CIM pre-treatment during shoot regeneration in
Arabidopsis. These segments were found to overlap the two QTLs identified earlier by Lall et al.
(2004). We demonstrate that the No-0 alleles affect auxin and cytokinin responses in intact
seedlings. We use global gene expression experiments to demonstrate that the No-0 alleles affect
the expression of genes related to hormone biosynthesis and signalling.
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9.3 Methods
9.3.1 Plant Material and Growth Conditions
The stock numbers of all ecotypes used are in Supplemental Table 9.1. The major
ecotypes used for subsequent analysis were from Lehle Seeds (Round Rock, Texas) with the
following catalogue numbers: Col-0 (WT-2), DijG (WT-10), Est-1 (WT- 6A), Ler-0 (WT-4) and
No-0 (WT-9). Where noted, an alternative Ler-0 (CS20) was used from the ABRC Stock Centre,
in particular for genetic mapping.
Seeds were surface sterilized by shaking them in 15% bleach with 0.01% Silwet (Lehle
Seeds, Round Rock, Texas) for 20 min, followed by 45 sec in 70% ethanol, and then rinsed five
times in sterile water. Sterilized seeds were then cold-treated at ~4 ºC for 2 –7 d in sterile water
to promote uniform germination. Seeds were then placed in 0.1% agar and plated onto
Germination Media consisting of 2.2 g/L MS+B5 (Phytotechnology Laboratories M404), 0.97
g/L MES (Phytotechnology Laboratories M825), 10 g/L sucrose, at a pH of 5.7 with KOH, and 3
g/L Phytagel (Sigma, P8169) in 100x25 mm Petri dishes. Using a Pasteur pipet, seeds were
individually plated onto a grid consisting of 26 evenly-spaced. All plates were sealed with
Micropore™ surgical tape (3M, 1530-1). The growing conditions for germination were 24-h
constant light (Cool White fluorescent lamps, 50-80 μMol m-2 s-1) at 23-25 ºC for 6-7 d.
9.3.2 Cotyledon Regeneration Assay and Analysis
Cotyledons were detached at the base of the blade (petiole tissue excluded) with fine
forceps at 6 days post-germination unless otherwise noted. Only healthy donor organs of a
uniform size were used. Detached tissues were placed onto either high cytokinin/low auxin Shoot
Induction Media (SIM) (default) or high auxin/low cytokinin Callus Induction Media (CIM) in
100x25mm Petri dishes using the grid noted above. SIM media (Zhao et al., 2002) consisted of
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20 g/L Glucose, 0.5 g/L MES with 1X Gamborg’s B5 with vitamins (Sigma G5893) and 3g/L
Phytagel (Sigma, P8169; pH 5.8 with KOH), with 4.4 μM 2-ip and 0.5 μM NAA. The hormones
in CIM media were substituted with 0.1 mg/L Kinetin and 0.5 mg/L 2,4-D. Hormones were
added after autoclaving and cooling to 55°C. The default regeneration conditions were: SIM
media for 14 days and then onto fresh SIM media for the remaining 30 d. Where used, the CIM
pre-treatment lasted 4-5 d followed by SIM media for 10 d, then a final transfer onto fresh SIM
media. Again, all plates were sealed with Micropore™ surgical tape (3M, 1530-1). Postdetachment regeneration conditions were: 24 hour constant low light (Cool White fluorescent
light ~20 μMol m-2 s-1) at 23 ºC in a Conviron growth chamber. Tissues with precocious
regeneration (less than one week post-excision) were not included in subsequent scoring. Petri
dishes were continuously randomized during regeneration in the growth chamber.
Regeneration was scored 5 weeks post-injury, unless otherwise noted. Regeneration was
scored for: the numbers of explants with at least one shoot (defined as a minimal of two leaves),
total number of shoots per plate and fresh weight (with roots dissected away). Statistical analysis
was performed using InStat 3.0 for Mac (GraphPad Software).
9.3.3 Time Course of Regeneration
Twenty-seven cotyledon explants were individually labelled and tracked for each
treatment (SIM or CIM pre-treatment) for each of the 5 ecotypes. These cotyledons were imaged
in the plates every 2-3 d using a Retiga 1300R digital camera mounted on a Leica MZFLIII
microscope using Openlab (v 4.0.3, Improvision Ltd.).
9.3.4 Genetic Mapping
Ler-Near Isogenic Lines (NILs) line were developed from a cross between Ler-0 (ABRC,
CS20) x No-0 (Lehle Seeds), backcrossed 4 times into Ler as the recurrent female parent. Lines
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were selected for shoot regeneration at each F1 generation in the absence of CIM (Figure 9.5A).
Genomic DNA was extracted from 100 BC4-F2 progeny, 50 which regenerated shoots and 50
that did not, using a DNeasy Plant Mini Kit (Qiagen). Based on published results (Lall et al.,
2004; DeCook et al., 2006), two markers were used in this study: a No-0 versus Ler-0
polymorphic SSLP marker, nga129, located on Chromosome 5 at 105.4 cM (Lister and Dean
Map) at position 19007 kb, and CAPS marker g4539, located on Chromosome 4 at 57.6 cM at
position 9631 kb. The nga129 primer sequences were CACACTGAAGATGGTCTTGAGG and
TCAGGAGGAACTAAAGTGAGGG. The g4539 primer sequences were
CAAACACCATTTAATCTTGACA and CAACAGGTTTCTTCTTCTTCTC. For G4539, 10 μL
of the PCR product was directly digested in a 20 μL reaction with 0.3 U HindIII for 2 h.
Fragments were run on 4% Metaphor (1xTAE) at 5 V/cm for 2 h to distinguish polymorphisms.
Statistical tests were performed using Instat 3.0 (GraphPad Software).
9.3.5 Seedling Hormone Assays
Seeds of ecotypes Col-0, Ler-0, Estland, Dijon-G and Nossen were surface-sterilized and
imbibed at 4 ºC for 3 d in sterile distilled water. The nutrient medium used for hypocotyl
elongation and cotyledon expansion assays was 0.5X MS, buffered with 4.5 mM MES, pH 5.7
with KOH, amended with 1% sucrose and solidified with 3 g/L phytogel (Sigma-Aldrich Co.).
Hormone stocks were made up fresh by initially dissolving the auxin or cytokinin in either 1 ml
of ethanol or 0.1 M KOH respectively, as 1000X stocks in 70% ethanol or filter sterilised 10 mM
KOH. Hormones or control stocks were added to the molten media at 45 ºC and mixed by
swirling for 2 min. To measure inhibition of hypocotyl elongation in the dark, the seeds were
moved from 4 ºC to room temperature for 24 h to permit germination prior to resuspension in
sterile 0.1% agar. The seeds were then spotted individually on agar plates at a density of 27 seeds
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per 9 cm deep-dish plate (VWR International Ltd.). Plates were wrapped in foil and placed in the
dark at room temperature for 6 d or 7 d. Plates were then opened, the hypocotyls flattened
against the surface of the media with tweezers and the plates scanned using a Snapscan Scanner
(Agfa Software). Hypocotyl lengths were measured from TIFF files using ImageJ (NIH). This
experimental design was repeated to determine the effect of the Nossen QTL loci on auxin
responses in a Ler background.
9.3.6 RNA Isolation for Microarray Experiments
The different Ler NIL genotypes used contained respectively: the chromosome 4 Nossen
QTL (4Nos-5Ler), chromosome 5 Nossen QTL (4Ler-5Nos), both Nossen QTLs (4Nos-5Nos) or
none of them (4Ler-5Ler). Three independent NIL Ler BC4-F3 lines were chosen for each of the
above genotypes. Plants were grown on germination media (Petri plates) for 7 d as described
above, then cotyledons were detached and placed on SIM for 6 d. Regeneration conditions were
as described earlier. Total RNA was extracted from 150 mg of frozen treated cotyledons for each
sample using TRI-Reagent® (Ambion, Inc) and a lithium chloride purification. RNA quality and
quantification were checked by agarose gel electrophoresis and spectrophotometer. RNA
concentrations were at least 0.5 µg/µL.
9.3.7 Microarray Hybridizations and Data Analysis
RNA labelling, array hybridizations and scanning were performed on ATH1 Genome
GeneChips (Affymetrix, Inc) at the CAGEF GeneChip facility at the University of Toronto,
following the Affymetrix procedure (http://www.affymetrix.com). A total of 12 hybridizations
were performed for the four genotypes (Ler background NIL with 4Ler-5Ler, 4Nos-5Nos, 4Nos5Ler or 4Ler-5Nos QTLs) with three biological replicates each.
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Normalization, differential expression and clustering were conducted using Bioconductor
(Gentleman et al., 2004) and R (R-Development-Core-Team, 2009). First, the package affyPLM
was used to correct fluorescence intensity background by the “Low End is Signal” (LESN)
method (Bolstad, 2004). Data were then normalized by the quantile-robust technique, and probe
set expression was summarized by median-polish (Appendix Table 8). The quality of expression
normalization was controlled with the Affy package (Gautier et al., 2004). Finally, differential
gene expression was determined using the following linear model from the Limma package
(Smyth, 2005): Y = X + ; where Y is the gene expression level in response to the presence or
absence of one or two of the No-0 QTLs; X is the basal Ler gene expression level;  is the
treatment (in this case presence of QTLs); and  is the error. Gene specific F-scores were
equivalent to a one-way ANOVA with a moderated mean square across genes. P-values were
corrected by the False Discovery Rate (FDR) method of Benjamini-Hochberg (Benjamini and
Hochberg, 1995). The P-value cut-off was set at a 1% rate of expected false positives.
Data were annotated using the Annaffy package (Smith, 2008). K-means clustering of the
selected genes was performed with PAM from the Cluster package (Maechler et al., 2005). GO
annotations were identified using GOstats (Falcon and Gentleman, 2007).
9.3.8 Semi-quantitative RT-PCR
The same detached cotyledon RNA samples utilized for the microarray experiment were
used for semi-quantitative RT-PCR. Total RNA was treated with DNAse I for 30 min, then 2.5
μg was used for first strand cDNA synthesis at 42 ◦C with 0.5 μg oligoT (Fermentas), and 200 U
of M-MuLV Reverse transcriptase (Fermentas), in the presence of RiboLock Ribonuclease
Inhibitor (Fermentas). PCR reactions were performed with gene-specific primers. The cycle
number before saturation was determined to be 29 after testing different dilutions. PCR reactions
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were performed with 5 μL of cDNA template and 0.2 μg of each forward and reverse of primers
in 20 μL of 2x Gotaq Green Master Mix (Promega). Amplification conditions were, 29 cycles of:
94 ˚C for 30 sec, 53 ˚C to 60 ˚C for 30 sec, and 72 ˚C for 1 min. Reaction products were
separated on 1% agarose. Ethidium bromide fluorescence intensities were measured against
GeneRuler™ Ultra Low Range DNA Ladders by FluoChem 8800 v3.1 software (Alpha
Innotech).
9.4 Results
9.4.1 Natural variation screen
To find alleles that could bypass the requirement for a CIM pre-treatment for shoot
organogenesis, excised cotyledons from 60 Arabidopsis ecotypes were screened in the absence
of a CIM pre-treatment. Cotyledons from six-day old seedlings were placed directly onto high
cytokinin/low auxin shoot induction media (SIM) for 4 weeks. A total of 9360 cotyledons were
screened. Comparing ecotypes, regeneration efficiency ranged from 0-98% in terms of the
percentage of cotyledons that regenerated shoots (Figure 9.1A, Appendix Table 7). The most
regenerative ecotype was Nossen-0 (97%) followed by Estland (84%). Ecotypes DijonG (DijG)
and Columbia (Col-0) had almost no shoot regeneration (1%, 0%, respectively). Landsberg
erecta (Ler-0) had low regeneration, which varied according to the seed source (0% from ABRC
or 9% from Lehle Seeds). Interestingly, there was no relationship between shoot organogenesis
(Figure 9.1A) and callus proliferation (Figure 9.1B). The five ecotypes noted were selected for
further study.
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Figure 9.1. Natural variation screen for ecotypes that can bypass the high auxin/low
cytokinin (CIM) pre-treatment normally required for efficient shoot regeneration. For 60
ecotypes, cotyledons from six-day-old seedlings were placed directly onto high cytokinin/low
auxin shoot induction media (SIM) (A) Shoot regeneration is represented as the percentage of
cotyledon explants that regenerated shoots. The histogram is the mean of three completely
independent replicates (n=52 per replicate). (B) This graph shows the corresponding mean mass
per explant (g) of shoot and callus tissue (excluding roots) for two independent replicates (n=26
per replicate). The error bar shown represents the standard deviation (SD). Ecotypes marked with
an asterisk were used for subsequent experiments in this study. Precise measurements and stock
numbers are provided in Appendix Table 7.
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9.4.2 Explants of Nossen-0 are less sensitive to changes in exogenous auxin and cytokinin
compared to other ecotypes
To better characterize ecotype-specific shoot regeneration responses, 27 individual
cotyledons per ecotype were photographed every 48-72 h for 4 weeks following excision.
Cotyledons were either exposed to high cytokinin:low auxin media (SIM) alone, or first treated
for 5 days with CIM followed by SIM (Figure 9.2). At wound sites, 2,4-D-containing CIM
caused more cell ablation than SIM alone, but this tissue damage seemed to be equivalent across
ecotypes (Figure 9.2, day 7). Confirming the natural variation survey, whereas Ler and DijG
were CIM-dependent and whereas Col-0 primarily produced callus, Est and No-0 regenerated
shoots in the absence of a CIM pre-treatment (Figure 9.2, day 16-24). Interestingly, CIM caused
Est to produce more roots than shoots compared to an SIM-only pre-treatment, whereas shoot
regeneration from No-0 explants occurred in both treatments (Figure 9.2, day 24). The relative
insensitivity of No-0 explants to CIM versus SIM pre-treatments was confirmed quantitatively
(Figure 9.3A). Further experiments showed that in the absence of a CIM pre-treatment, most
ecotypes were very sensitive to any change in the ratio of cytokinin (2-iP) to auxin (NAA)
present in SIM with respect to shoot regeneration (Figure 9.3B-E); the exception again was No-0
(Figure 9.3B). When the absolute concentrations of auxin and cytokinin in SIM media were
altered from 100% to 10-250%, No-0 was again the most insensitive ecotype (Figure 9.3F, G).
These results demonstrate that explants of No-0 are less sensitive to changes in exogenous auxin
and cytokinin compared to other ecotypes tested.
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Figure 9.2. Time course showing ecotype specific responses to pre-treatments with or
without a CIM pre-treatment. Cotyledons were all excised at 7 days after germination and
placed either on CIM for 5 days, followed by SIM or directly on SIM as noted. The days noted
on the y-axis are days post-excision (PE). For each treatment, 27 cotyledons were photographed,
and a representative explant is shown. The arrow indicates when the first visible shoots appeared.
The last time point for Est is day 28 PE as this ecotype regenerated shoots slowly.
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A
B
C
D
E
€
F
G
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Figure 9.3. Ecotype-specific differences in shoot regeneration in response to exogenous
auxin and cytokinin. (A) The effect of 4 days of post-detachment pre-treatment with high
auxin/low cytokinin (CIM) followed by high cytokinin/low auxin (SIM) or SIM alone as
measured 4 weeks after excision. Each histogram is the mean of 3 replicates (each CIM replicate
n=26; each SIM replicate, n=52). (B-E) The effect of altering the cytokinin:auxin ratio in the
shoot induction media. Shown is the absolute percentage change in the number of explants that
regenerate shoots for each ratio compared to normal SIM. The ecotypes shown are (B) No-0, (C)
Est, (D) Ler-0 (Lehle Seeds) and (E) DijG. Standard SIM contains 4.4 μM 2-iP and 0.5 μM
NAA. In this experiment, NAA levels were kept constant, while cytokinin was adjusted in
accordance with the x-axis scale. There was no CIM pre-treatment. Each histogram is the mean
of 78 cotyledons tested. For DijG, the total number of shoots that regenerated is shown, because
regeneration was very poor across all treatments. (F,G) The effect of altering the absolute total
concentration of SIM hormones was measured in terms of (F) the total number of shoots/explant
and (G) the percentage of explants
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9.4.3 Two chromosome segments from ecotype No-0 confer CIM-independent shoot
regeneration ability to ecotype Ler-0
In order to understand the genetic basis of the CIM-independent shoot regeneration
ability of No-0, the low CIM-requiring ecotype Ler-0 (ABRC, 0% regeneration) was crossed
with No-0 (90-100% regeneration). The F1 hybrids regenerated in the absence of a CIM pretreatment (>80% efficiency), suggesting the CIM-bypass allele(s) from No-0 was dominant. An
F2(x) Ler-0 x No-0 population regenerated at a frequency of 38% (113/300 cotyledons) in the
absence of CIM (data not shown), suggesting the presence of >two unlinked QTLs. For mapping
studies, No-0 was backcrossed into Ler-0 for four generations to create a near isogenic line (NIL)
population (Figure 9.4A). At each backcross generation, there was selection for dominant No-0
alleles that promoted regeneration in the absence of CIM.
Before screening for genetic linkage between these QTLs and randomly selected
molecular markers, a candidate marker approach was first taken. Specifically linkage was tested
between the CIM-independent shoot regeneration phenotype and two shoot-promoting Col-0
QTLs identified by Lall et al. (2004): a major QTL on Chromosome 5 (marker Cor78/marker
270 at 106.5 cM) and a minor Ler QTL on Chromosome 4 (marker mi32/near marker 190 at 60.9
cM). Polymorphic markers were screened at or closed linked to these two QTLs that could
distinguish No-0 from Ler-0 unambiguously. For the Chromosome 5 major QTL, marker nga129
was chosen, located ~1 cM proximal to the Chromosome 5 major QTL at 105.4 cM (Figure
9.4B) (Lister and Dean Map) (Lister and Dean, 1993). For the Chromosome 4 minor QTL,
marker g4539 was polymorphic in our population, located 3 cM proximal to that of the previous
study (Lall et al., 2004), at 57.6 cM (Figure 9.4B). A third (minor) QTL identified by Lall et al.
(2004) on Chromosome 1 was not tested due to an inability to find polymorphic markers.
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Shoot regeneration phenotyping was undertaken for 252 BC4-F2 lines derived from two
independent BC3 families (C33 and C132) selected for regeneration in the absence of a CIM pretreatment. The percentage of explants that regenerated shoots was 30.7% in family C33 and
37.2% in family C132. We then genotyped 50 BC4-F2 C33 and C132 individuals that
regenerated shoots and 50 siblings that did not: a very strong positive association was found
between the two physical markers from No-0 and shoot regeneration ability in the absence of a
CIM pre-treatment (Figure 9.4C, D). The data demonstrated that one copy of the No-0
Chromosome 5 marker could confer CIM-independent regeneration, and that a second copy was
additive, making its associated chromosome fragment semi-dominant (Figure 9.4C). A Chisquare Test confirmed that one or two copies of No-0 segment was significantly associated with
shoot regeneration (Chi-square statistic with Yates correction = 13.8, d.f.=1, P=0.0002). Shoot
regeneration did not occur in the absence of the Chromosome 5 No-0 chromosome segment. In
contrast, the No-0 segment associated with the Chromosome 4 minor QTL appeared not to be
required, but rather it was a recessive enhancer of CIM-independent regeneration (Figure 9.4D).
A Chi-square Test showed that two copies of the No-0 Chromosome 4 chromosome segment was
significantly associated with shoot regeneration compared to 0-1 copies (Chi2 statistic with
Yates correction = 10.3, d.f.=1, P=0.0014).
To test these allele contributions further, each of the 100 BC4-F2 lines was selfed and 52
explants per line were phenotyped in the next generation (BC4-F3). Significant shoot
regeneration was now detected in the absence of the No-0 segment linked to the Chromosome 5
major QTL (Figure 9.4E); we hypothesize that further selfing caused several recessive alleles for
regeneration to have an additive effect on shoot regeneration. However, shoot regeneration
increased significantly from having no copies of the No-0 Chromosome 5 segment (0.265
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shoots/explant) to having one copy (0.51 shoots/explant) and then two copies (1.40
shoots/explant). Therefore, the No-0 segment corresponding to the major Chromosome 5 QTL
region previously reported by Lall et al. (2004) is able to confer CIM pre-treatment-independent
regeneration in a Ler-NIL background in a semi-dominant manner.
Surprisingly, the impact of the Chromosome 4 No-0 segment appeared similar to that of
the Chromosome 5 No-0 segment in the BC4-F3 generation (Figure 9.4F). We hypothesized that
this was due to the impact of the Chromosome 5 major QTL and other potential modifiers
segregating independently in the background. This hypothesis was tested in a further experiment
(below).
348
A
B
C
D
E
F
349
Figure 9.4. The effect of two chromosome segments from Nossen-0, introgressed into Ler-0,
on shoot regeneration frequency in the absence of a high auxin/low cytokinin (CIM) pretreatment. (A) A near-isogenic line (NIL) was created by introgressing No-0 fragments into
Ler-0 (CS20, ABRC). The asterisk denotes that at each F1 generation, only progeny that could
regenerate shoots in the absence of CIM were used for further crossing, thus imposing positive
selection on No-0 chromosome segments that could enhance regeneration. (B) Two molecular
markers tightly linked to regeneration QTLs reported earlier (Lall et al., 2004) were used in this
study with Lister and Dean Map positions shown (Lister and Dean, 1993). (C-F) The association
between each marker and shoot regeneration was tested in the absence of CIM. Shoot
regeneration was scored in a non-random BC4-F2(x) population (see Results) relative to the
inheritance of the (C) Chromosome 5 major QTL marker nga129 generation and (D)
Chromosome 4 minor QTL marker g4539. Chi-square tests showed that the Chromosome 5 No-0
marker was dominant and the Chromosome 4 No-0 marker was recessive for promoting
regeneration. (E,F) Progeny from each BC4-F2 line was selfed and the phenotype of 3839 BC4F3 cotyledons compared using the assigned genotype of the parents. Each BC4-F3 histogram
represents the mean of 52 cotyledons/line multiplied by the number of lines shown in the
denominator above the histograms in panels C-D. Above each histogram is the total number of
explants that regenerated shoots as a fraction of the number tested. The result from panel F
should be read in the context of Table 9.1.
350
9.4.4 The Chromosome 4 and Chromosome 5 segments from No-0 act synergistically in a
dosage-dependent manner to promote shoot regeneration
Lall et al.(2004) reported that the Chromosome 4 minor QTL had epistatic effects on the
major Chromosome 5 QTL. Specifically, they found that when the Chromosome 4 QTL from
Ler was present, the Chromosome 5 QTL from Col was associated with reduced regeneration.
The two corresponding chromosome segments from No-0 were tested here for epistatic
interactions, though in the absence of a CIM pre-treatment (Table 9.1). In general, the
Chromosome 5 segment from No-0 was found to be epistatic to the Chromosome 4 segment, but
no consistent evidence was found that two copies of the Chromosome 4 Ler segment caused
negative epistasis on the Chromosome 5 No-0 segment. One to two copies of the Chromosome 5
segment from No-0 (in the absence of the Chromosome 4 segment) enhanced regeneration to a
greater extent than 1-2 copies of the Chromosome 4 segment from No-0 alone (Table 9.1). When
combined together, both No-0 chromosome segments acted as dosage-dependent enhancers of
each other. High levels of regeneration occurred when two copies of one No-0 chromosome
segment were combined with at least one copy of the second unlinked No-0 segment. Peak
regeneration occurred when two copies of both No-0 chromosome segments were present,
particularly in the BC3 generation (Table 9.1). Because each region is sensitive to one another’s
dosage, we hypothesize that the protein products of the associated loci may act in the same
pathway. The synergistic actions of both segments may have been responsible for the retention
of these unlinked No-0 chromosome segments during backcross selection in the Ler background.
351
Table 9.1. Evidence that the No-0 chromosome segments corresponding to the Chromosome 5
1
2
Major QTL and Chromosome 4 Minor QTL Act Synergistically in a Dosage-Dependent
Manner to Promote Shoot Regeneration in the Absence of a CIM Pre-treatment
1
The Chromosome 5 marker is nga129.
2
The Chromosome 4 marker is G4539
3
The genotype that is noted for the BC4-F3 generation is the parental genotype before selfing,
and thus heterozygotes would in reality be segregating in the F3 generation.
352
9.4.5 The Chromosome 5 segment from No-0 reduces sensitivity to exogenous auxin and
cytokinin in intact seedlings
The effect of the Chromosome 5 chromosome segment from No-0 was then tested for its
effects on the sensitivity of intact seedlings to exogenous hormones. First, wild-type seedlings
were tested. We measured the percentage reduction in elongation of dark-grown hypocotyls in
the presence of different auxins (NAA, 2,4- D)(Collett et al., 2000) or cytokinins (BA, kinetin, 2iP) (Smets et al., 2005). The greater the reduction in growth, the greater is the response of the
ecotype to the corresponding hormone. Consistently, intact ecotype No-0 seedlings showed less
or equal, but never more, responsiveness to these hormones than the other ecotypes (Figure
9.5A) consistent with the relative hormone insensitivity of this ecotype in vitro (Figure 9.3).
Next the effect of the Chromosome 5 No-0 chromosome segment on the Ler NIL
background was tested. Two sibling NIL families (NIL, BC4 F3) were compared that were either
homozygous Ler/Ler or No-0/No-0 at the Chromosome 5 segment; both had a fixed No-0/No-0
haplotype associated with the Chromosome 4 minor QTL. In the absence of exogenous
hormones, there was no significant difference between NILs containing Ler versus No-0
chromosome segments from Chromosomes 4 and 5 with respect to dark-grown hypocotyl length
(Figure 9.5B). When 1 μM BA (cytokinin) was applied, hypocotyl elongation in the Ler-NIL
containing two No-0 Chromosome 5 segments was inhibited slightly less than the Ler-0/Ler-0
line, appearing to cluster with No-0 wild-type seedlings (Figure 9.5C). Statistically, the response
of BA-treated No-0 wild-type plants did not correlate with BA-treated wild-type Ler-0 seedlings
or Ler-NILs containing two Ler Chromosome 5 segments (Pearson r2<0.13, P>0.27 not
significant). However, there was a modest, but significant correlation between the response of
BA-treated No-0 wild type plants and BA-treated Ler-NILs containing two copies of the No-0
353
Chromosome 5 segment (Pearson r2=0.443, P=0.027). These results demonstrate the No-0
Chromosome 5 segment confers partial cytokinin insensitivity to Ler seedlings.
Finally, the effects of exogenous auxin were tested. The presence of the Chromosome 5
No-0 segment caused Ler-NIL seedlings to have reduced sensitivity (reduced inhibition) to auxin
(NAA), such that the growth profile now overlapped wild-type No-0 seedlings (Figure 9.5D)
(Pearson r2=0.65; P=0.0026). Similarly, the Chromosome 5 Ler/Ler segment in a Ler NIL
background had an auxin-response profile in seedlings similar to wild-type Ler-0 seedlings
(Figure 9.5D) (Pearson r2=0.98, P<0.0001). In contrast, wild-types did not correlate with NIL
lines containing a chromosome 5 segment from a different ecotype (Pearson r2<0.08, P>0.41).
We conclude that the Chromosome 5 No-0 segment that bypasses the CIM requirement
for shoot regeneration in vitro, also confers reduced sensitivity to auxin and cytokinin in intact
seedlings.
9.4.6 Using microarray to analyze gene expression from a Landsberg genotype (Ler)
containing introgressed chromosome segments from a Nossen-0 genotype (No-0)
The next objective was to use the standard Affymetrix ATH1 GeneChip microarray to
study the influence of each No-0 chromosome segment on the Ler genome into which these
segments had been introgressed. Since ATH1 GeneChips are based on ecotype Columbia probes
(Col-0), the concern was that the array probes would differentially hybridize to transcripts
derived from Ler alleles compared to No-0 alleles on the same array.
354
355
Figure 9.5. Effect of the Chromosome 5 chromosome segment from No-0 on the sensitivity
of intact Ler-0 seedlings to auxin and cytokinin. (A) Intact wild-type seedlings were tested for
inhibition of hypocotyl elongation by synthetic auxins (1M NAA or 2,4-D) and cytokinins
(1M BA, Kinetin or 2-iP) as a percentage of control elongation. Hypocotyls were measured
after 6 days growth in the dark. Error bars are SE (N = 29-82). (B-D) Two sibling Ler near
isogenic lines (NIL) were compared for hypocotyl inhibition in the dark: one sibling possessed
an introgressed, homozygous No-0 chromosome segment containing the Major QTL from
Chromosome 5 (Ler-NIL Chromo5 No-0/No-0) whereas the second sibling (control) contained
the homozygous Ler-0 allele (Ler-NIL Chromo5 Ler/Ler). Seedling hypocotyl inhibition was
compared in (B) without hormones (control), (C) with 1 μM BA (cytokinin), and in (D) with 1
μM NAA (auxin). Seeds germinated in water for 24 h were placed on media containing the
relevant hormones or buffer control. Measurements were taken after 6 days exposure to the
treatments (n=55 to 100 per treatment per ecotype).
356
Therefore, ecotype-specific hybridization biases were first analyzed to validate the use of the
ATH1 array. First, as each gene is represented by multiple probes on the array (a probe set), the
hybridization profiles of the probes within each probe set, located inside and outside of each
QTL region, were compared; there were no obvious differences between these hybridization
patterns when comparing NIL 4Ler-5Ler to NIL 4Nos-5Nos (11% and 14% differences,
respectively) (Figure 9.6). As a second control, DNA from wild type Ler and No-0 was
hybridized onto an ATH1 array. No significant clusters of probes (i.e. corresponding to a No-0 or
Ler chromosome segment) were identified that were polymorphic between the two ecotypes in
the Chromosome 4 and 5 QTL regions (t-test with Bonferroni correction and a cut-off of 5%
(data not shown). In a later control, semi-quantitative RT-PCR (qRT-PCR) was used to validate
the expression of 17 genes located inside or outside of the introgressed No-0 chromosome
segments. When a polymorphism was detected at the GeneChip probe set level (i.e. when the
different probes within a probe set showed different hybridization patterns), expression of the
gene was usually not validated by qRT-PCR: 7 out of 9 invalid genes had a probe set
hybridization pattern that differed between the NILs (Appendix Table 7). However, when the
probe set hybridization patterns were identical between different NILs, 8 out of 10 genes were
validated by qRT-PCR giving an 80% validation rate. Only genes corresponding to probe sets
that did not differ in their hybridization patterns between different NILs, are reported in this
study.
357
A
B
C
D
E
F
G
H
Figure 9.6. Example of array probe set hybridizations. This illustrates expression biases
caused by polymorphisms between chromosome segments from Landsberg erecta and Nossen
ecotypes in the NIL background.
358
9.4.8 The Chromosome 5 segment from No-0 has a greater impact on global gene
expression in cotyledon explants on SIM than the Chromosome 4 segment
Following the validation of the use of the ATH1 GeneChip technology, global gene
expression of Ler-NILs containing introgressions of the No-0 chromosome segments were
analyzed. RNA was collected from 7-day old cotyledon explants that were placed on SIM for 6
days in the absence of the critical CIM pre-treatment. Only NILs that were homozygous at each
marker position were analyzed. Substituting Ler alleles with the Chromosome 4 and 5 segments
from Nossen caused 778 genes to be differentially expressed (Appendix Table 8, Appendix
Table 9). The Chromosome 5 Nossen-0 QTL caused 302 genes to be up-regulated, and 205
genes to be down-regulated representing 38.9% and 26.3%, respectively of all differentially
expressed genes (Appendix Table 10). By contrast, the Chromosome 4 Nossen-0 QTL caused 64
genes (8.2%) to be up-regulated and 66 genes (8.4%) to be down-regulated (Appendix Table 10).
These results indicate that two copies of the Chromosome 5 Nos-0 segment alters the expression
of three-times more Ler genes than two copies of the Chromosome 4 No-0 segment (507 genes
versus 130) in cotyledon explants placed on SIM media. This result is consistent with our earlier
phenotype observations, and that of Lall et al. (2004), which suggested that the Chromosome 5
QTL has a greater effect on phenotype in vitro than the Chromosome 4 QTL.
359
Figure 9.7. Heatmap of hormone-related genes that are differentially expressed in response
to alleles present at the Chromosome 4 and 5 chromosome segments from No-0. Expression
(Z score) ranges from up-regulated (blue) to down-regulated (yellow). Shown is cotyledon
expression after detachment.
360
9.4.9 Auxin-related gene expression dependent of No-0 chromosome segments
Substituting Ler alleles with the corresponding Chromosome 4 and 5 segments from
Nos-0, caused at least 12 auxin-related genes to be differentially expressed in cotyledon explants
on SIM (Figure 9.7, Table 9.2). Two genes involved in auxin biosynthesis were up-regulated by
the Chromosome 5 No-0 chromosome segment, including Nitrilase 3 (NIT3, At3g44320) which
catalyzes the last step in auxin biosynthesis, hydrolyzing Indole-3 Acetonitrile to Indole-3-Acetic
Acid (IAA). NIT3 is largely specific to roots, but also appears to function in auxin-dependent
vein development in cotyledons (Pollmann et al., 2002). The second up-regulated auxin
biosynthetic enzyme, cytochrome P450 CYP79B2 (At4g39950), converts tryptophan to
indole-3-acetaldoxime. It is mostly expressed in roots and induced by wounding (Mikkelsen et
al., 2000). Other up-regulated auxin genes included GDG1, which encodes a GH3-like protein
(At5g13320), that is normally expressed in cotyledons and young roots, but is also required for
the accumulation of salicylic acid in response to bacterial infection (Jagadeeswaran et al., 2007).
Finally, a SAUR gene (Small Auxin Up-Regulated, At5g53590) was up-regulated by the
Chromosome 5 No segment; this gene was previously shown to have high expression in
cotyledons (Schmid et al., 2005).
Two interesting auxin-related genes were down-regulated by the No-0 Chromosome 5
segment (Figure 9.7, Table 9.2). The first gene was ASL16/LBD29 (Asymmetric Leaves2like/Lateral Organ Boundaries domain, At3g58190), a gene which contains two auxin-responsive
promoter elements (AuxRE) and shows highest expression normally in the root (Schmid et al.,
2005). ASL16/LBD29 is regulated by auxin transcription factors ARF7 and AR19, and has been
shown to rescue lateral root formation defects in an arf7/arf19 mutant when over-expressed
(Okushima et al., 2007). As noted earlier, pericycle cells that initiate lateral roots, initiate callus.
361
The other down-regulated auxin-related gene (At4g34760) shows similarity to SAUR proteins,
has low expression in senescing leaves, seed and late stages of development, but has no known
function (Schmid et al., 2005).
The Chromosome 4 segment from No-0 caused decreased expression of two auxinrelated genes (Figure 9.7, Table 9.2), including Hydroxycinnamoyl-Coenzyme A (HCL,
At5g48930), a lignin biosynthetic enzyme, which inhibits auxin transport when silenced, a
phenotype associated with flavonoid overproduction (Besseau et al., 2007). A member of the
molybdenum co-factor synthesis family (SIR5, At4g10100), was also down-regulated; sir5
mutants cause resistance to sirtinol, a modulator of auxin signalling.
The two No-0 chromosome segments were also found to have additive effects on
accumulation of auxin-related transcripts (Table 9.2). The presence of both Chromosome 4 and
Chromosome 5 segments caused down-regulation of AIR1 (Auxin Induced Root 1, At4g12550),
HSFA4/RHA1 (At5g45710) and an AtDRM1-homolog (At2g33830). AIR1, part of the protease
inhibitor/seed storage/LTP family, was identified in auxin-treated root cultures (Neuteboom et
al., 1999), and this gene showed the greatest decrease in expression by the two No-0
chromosome segments, of the genes discussed here (Table 9.2). Mutants of HSFA4/RHA1, a
Heat Shock Factor family (HSF) member, cause altered gravitropism and resistance to an auxin
transport inhibitor and ethylene (Fortunati et al., 2008). Finally, the AtDRM1-homolog is a
dormancy-related auxin gene which is repressed in growing organs but active in dormant buds
(Mlynárová et al., 2007).
362
Table 9.2. Hormone and root-related genes found to be differentially expressed in excised
cotyledons in response to No-0 chromosome segments being introgressed into a Ler-0
background.
Symbol
TAIR
Hormone
or tissue
No-0 QTL
responsible
for
expression
changes
Description
Fold
change
Nos vs
Ler
NIL
ANOVA
adjusted
P-Value
2.21
1.69E-03
NIT3
AT3G44320
auxin
Chr 4 & 5
Nitrilase (nitrile aminohydrolase )
catalyzes the hydrolysis of indole-3acetonitrile (IAN) to indole-3-acetic acid
(IAA).
SIR5
AT4G10100
auxin
Chr 4
Molybdenum cofactor synthesis family
protein, sir loss-of-function mutants are
resistant to sirtinol, a modulator of auxin
signaling.
0.69
4.44E-03
SAUR
AT4G34760
auxin
Chr 5
Auxin-responsive family protein, similar
to Auxin responsive SAUR protein
(Medicago truncatula)
0.8
2.19E-03
1.55
4.27E-03
CYP79B2
AT4G39950
auxin
Chr 5
Belongs to cytochrome P450 and is
involved in tryptophan metabolism.
Converts Trp to indo-3-acetaldoxime
(IAOx), a precursor to IAA and indole
glucosinolates.
GDG1
AT5G13320
auxin
Chr 5
Signaling gene in disease-resistance
involved in restricting the spread of both
virulent and avirulent pathogens.
2.42
9.11E-05
AILP1
AT5G19140
auxin
Chr 4
Putative auxin/aluminum-responsive
protein, contains domain Aparagine
synthetase.
1
2.29E-03
Chr 5
Putative auxin-responsive protein,
contains InterPro domain Protein of
unknown function DUF568, DOMONlike, domain Cytochrome b561 / ferric
reductase transmembrane.
1.67
9.57E-03
0.75
2.48E-03
DUF568
AT5G35735
auxin
HCT
AT5G48930
auxin
Chr 4
Encode for the hydroxycinnamoylCoenzyme A shikimate/quinate
hydroxycinnamoyltransferase (HCT)
involved in the phenylpropanoid pathway.
Influence on the accumulation of
flavonoids which in turn inhibit auxin
transport and reduce plant growth.
SAUR
AT5G53590
auxin
Chr 5
Auxin-responsive family protein, similar
to Auxin responsive SAUR protein
(Medicago truncatula).
2.04
2.17E-03
ASL16 /
LBD29
AT3G58190
auxin
and roots
Chr 5
Encodes Lateral Organ Boundaries
Domain protein 29, contains two auxinresponsive element (AuxRE).
0.85
4.14E-03
363
Table 9.2. (continued)
AIR1
AT4G12550
auxin
and roots
Chr 4 & 5
Auxin-Induced Root 1, isolated from
differential screening of a cDNA library
from auxin-treated root culture. encodes a
protein that is related to a large family of
proteins that consist of a proline-rich or
glycine-rich N-terminus and a
hydrophobic, possibly membrane
spanning C-terminus.
HSFA4C
AT5G45710
auxin
and roots
Chr 4 & 5
Member of Heat Stress Transcription
Factor (Hsf) family.
0.62
9.31E-05
AtGrxS13like
AT1G03850
cytokinin
Chr 5
Glutaredoxin family protein, Identical to
Monothiol glutaredoxin-S13 (AtGrxS13)
1.52
8.12E-03
CKX3
AT5G56970
cytokinin
Chr 4 & 5
Cytokinin oxidase/dehydrogenase, which
catalyzes the degradation of cytokinins.
2.69
8.85E-04
47.54
1.13E-04
0.06
4.95E-04
RAP2.3
AT3G16770
cytokinin
and
ethylene
Chr 4 & 5
Encodes a member of the ERF (ethylene
response factor) subfamily B-2 of the
plant specific ERF/AP2 transcription
factor family (RAP2.3). i part of the
ethylene signaling pathway and is
predicted to act downstream of EIN2 and
CTR1, but not under EIN3.
CRF3
AT5G53290
cytokinin
and
ethylene
Chr 5
Encodes a member of the ERF (ethylene
response factor) subfamily B-5 of
ERF/AP2 transcription factor family.
1.81
7.32E-05
Chr 5
Encodes a member of the DREB
subfamily A-5 of ERF/AP2 transcription
factor family. The protein contains one
AP2 domain. There are 15 members in
this subfamily including RAP2.1, RAP2.9
and RAP2.10.
0.62
4.44E-03
Chr 4 & 5
Encodes a member of the DREB
subfamily A-4 of ERF/AP2 transcription
factor family. The protein contains one
AP2 domain. There are 17 members in
this subfamily including TINY.
1.36
4.25E-03
Chr 4 & 5
Encodes a basic chitinase involved in
ethylene/jasmonic acid mediated
signalling pathway during systemic
acquired resistance based on expression
analyses.
6.73
2.56E-03
Chr 5
Encodes a member of the DREB
subfamily A-5 of ERF/AP2 transcription
factor family. The protein contains one
AP2 domain.
1.38
8.74E-03
ERF/AP2
ERF/AP2
PR-3
AtERF 11
AT1G21910
AT2G25820
AT3G12500
AT3G50260
ethylene
ethylene
ethylene
ethylene
364
Table 9.2. (continued)
MES9
AT4G37150
ethylene
Chr 5
Putative esterase, similar to ethyleneinduced esterase (Citrus sinensis)
1.69
9.53E-04
ACC oxidase
AT5G43440
ethylene
Chr 5
encodes a protein whose sequence is
similar to ACC oxidase
2.92
6.80E-04
ACC oxidase
AT5G43450
ethylene
Chr 5
encodes a protein whose sequence is
similar to ACC oxidase
9.95
3.50E-04
AtPDR12
AT1G15520
ethylene
and roots
Chr 4 & 5
ABC transporter family involved in
resistant to lead. Localizes to plasma
membrane.
2.65
6.26E-03
0.47
4.89E-03
NRT1.1
AT1G12110
roots
Chr 4 & 5
Encodes NRT1.1 (CHL1), a dual-affinity
nitrate transporter. The protein is
expressed in guard cells and function in
stomatal opening. Mutants have less
transpiration and are more tolerant to
drought. Expressed in lateral roots.
Involved in nitrate signaling which
enables the plant root system to detect and
exploit nitrate-rich soil patches.
Comparing to the wild type, the mutant
displays a strongly decreased lateral root
proliferation phenotype in nitrate rich
patches on growth medium.
AtRFNR1
AT4G05390
roots
Chr 4
Encodes a root-type ferredoxin:NADP(H)
oxidoreductase.
0.69
8.14E-04
Chr 5
Putative xyloglucan
endotransglycosylase/hydrolase, expressed
in the mature or basal regions of both the
main and lateral roots, but not in the tip of
these roots where cell division occurs.
0.59
5.53E-03
1.62
7.15E-04
3.45
9.89E-04
XTH18
AT4G30280
roots
CSLA9/RAT4
AT5G03760
roots
Chr 4
Encodes a beta-mannan synthase that is
required for Agrobacterium-mediated
plant genetic transformation involves a
complex interaction between the
bacterium and the host plant. 3' UTR is
involved in transcriptional regulation and
the gene is expressed in the elongation
zone of the root.
DUR
AT5G44480
roots
Chr 4 & 5
UDP Glucose Epimerase, mutant has
Altered lateral root.
365
9.4.10 Cytokinin-related gene expression dependent of No-0 chromosome segments
Substituting Ler alleles with the corresponding Chromosome 4 and 5 segments from No0 caused several interesting cytokinin-related genes to be up-regulated in cotyledon explants on
SIM. First, Cytokinin Oxidase 3 (CKX3), an important regulatory gene which encodes an
enzyme that degrades cytokinins, showed increased RNA accumulation in the presence of either
the Chromosome 5 or Chromosome 4 segments from No-0 (Figure 9.7, Table 9.2). These results
were confirmed by RT-PCR (Appendix Figure 2).
The expression of Cytokinin Response Factor 3 (CRF3, At5g53290), an ERF-family
transcription factor involved in the cross-talk between cytokinin and ethylene, was up-regulated
in Ler-NIL genotypes containing both Chromosome 4 and 5 chromosome segments from No-0
(Table 9.2). CRFs have been implicated in shoot initiation (Rashotte et al., 2006), making this
another gene of particular interest here. The expression of CRF3 in NIL cotyledon explants was
confirmed by RT-PCR (Appendix Figure 2).
RAP 2.3 (AT3G16770), an ERF transcription factor in the ethylene and cytokinin
signalling pathways, showed a ~48-fold increase in transcript accumulation in genotypes with
the Chromosome 4 and 5 segments from No-0 (Table 9.2), though such a dramatic increase was
not confirmed by RT-PCR (Appendix Figure 2).
Finally, a glutaredoxin family member (AtGrxS13-like, At1g03850), induced by
cytokinin and involved in DNA biosynthesis in growing tissues (Schmid et al., 2005), was upregulated by the Chromosome 5 No-0 QTL (Table 9.2). Interestingly, AtGrxS13-like appears to
be co-regulated with the earlier described auxin biosynthesis enzyme cytochrome P450
CYP71B23 (Obayashi et al., 2009).
366
9.4.11 Ethylene-related gene expression dependent of No-0 chromosome segments
Substituting Ler alleles with the Chromosome 4 and 5 segments from No-0 also caused a
number of ethylene-related genes to be differentially expressed in cotyledon explants on SIM
(Figure 9.7, Table 9.2).
Interestingly, several critical ethylene-related genes that showed up-regulation in
response to a single No-0 chromosome segment, showed highest expression when both
Chromosome 4 and 5 segments from No-0 were present, suggesting a molecular mechanism for
the earlier additive effect of these two segments. These additive-effect, up-regulated genes
included: two putative ACC oxidases, AtMES 9/ACL (Atg37150), RAP 2.3, AtERF11,
AtPDR12, and At2g25820 (Table 9.2). The most interesting of these genes were the two ACC
oxidases (At5g43450 and At5g43440), which encode the last step in ethylene biosynthesis; these
genes were induced 10- and 3-fold, respectively, when both introgressed No-0 chromosome
segments were present, with the Chromosome 4 segment being insufficient to induce these genes
on its own. The two No-0 chromosome segments could also additively induce expression of
AtMES9/ACL, a gene induced by ethylene, which acts as an esterase, to release hormones such
as auxin (IAA) and salicylic acid from inactive conjugated forms. Also induced by No-0
chromosome segments was RAP 2.3 (AT3G16770), noted above, an ERF transcription factor in
the ethylene and cytokinin signalling pathways, shown to be induced by ethylene downstream of
EIN2 (Büttner and Singh, 1997) and to activate several downstream PR proteins via GCC box
promoter motifs (Brenner et al., 2005). Interestingly, one of these putative RAP2.3 targets, a PR3
protein, previously shown to be activated by ethylene and possibly by cotyledon wounding,
showed a 7-fold increase in expression in cotyledons containing No-0 chromosome segments
367
(Table 9.2); PR3 encodes a chitinase necessary for systemic pathogen resistance (Pre et al.,
2008).
Other genes up-regulated additively by the introgressed No-0 chromosome segments but
also by the Chromosome 5 No-0 segment alone were AtERF11 (At3g50260), a member of the
DREB transcription factor family, known to be induced by ethylene, jasmonic acid and chitin
(Libault et al., 2007), along with a paralog (At2g25820), and AtPDR12 (Pleiotopic Drug
Resistance, A1g15520). AtPDR12 is an ABC-type transporter shown to be activated by EIN2 in
the ethylene signalling pathway (van den Brûle and Smart, 2002), for transport of antifungal
compounds, though some ABC transporters have been shown to transport auxin (Badri et al.,
2008).
In addition to these up-regulated genes, the Chromosome 5 No-0 chromosome segment
caused down-regulation of YLS7 (Yellow Leaf specific, At5g51640), a leaf senescence-related
gene involved in secondary cell wall cellulose (Yoshida et al., 2001), with a suspected
connection to ethylene. The introgressed Chromosome 5 segment also caused down-regulation of
an AP2/ERF DREB-like transcription factor (At1g21910) involved in biotic and abiotic stress
tolerance (Table 9.2).
9.4.12 Root growth- and development-related gene expression dependent of No-0
chromosome segments
In addition to the above hormone-related genes, substituting Ler alleles with the
corresponding Chromosome 4 and 5 segments from No-0 caused genes related to lateral root
initiation and elongation, to be differentially expressed in cotyledon explants (Figure 9.7, Table
9.2); as noted earlier, lateral root primordia have been shown to be precursors for shoot
regeneration (Duclercq et al., 2011). Two putative regulatory genes of lateral roots were down-
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regulated by the introgressed Chromosome 5 No-0 segment, including LBD29 and AIR1
described earlier in the auxin section. Additional genes affected by these No-0 segments
appeared to be downstream genes that regulate root cell walls. For example, the introgressed
Chromosome 4 No-0 segment caused up-regulation of the Cellulose Synthase-like gene 9 /RAT4
(CSL9, t5g03760); rat4 mutants are defective in lateral root number and growth (Zhu et al.,
2003). RAT4 is expressed during root elongation but, interestingly, also in vascular tissues above
ground (Zhu et al., 2003), which are known sites of callus production. The Chromosome 5 No-0
segment caused up-regulation of an UDP Glucose isomerase (DUR, At5g44480), a gene which
may regulate cell wall sugar, and shows altered lateral root phenotypes when mutated (Burget et
al., 2003). The Chromosome 5 No-0 segment also caused down-regulation of AtXTH18
(At4g30280), a xyloglucan endotransglucosylase/hydrolase involved in secondary cell wall
organization and synthesis (Vissenberg et al., 2005) which shows high expression cell elongation
in roots (Osato et al., 2006). Finally, the Chromosome 4 and 5 No-0 chromosome segments also
caused down-regulation of NTR1.1, a nitrate transporter involved in sensing of glutamate, shown
to regulate lateral root branching (Walch-Liu and Forde, 2008) (Table 9.2).
9.5 Discussion
For decades, it has been reported that a high auxin/low cytokinin pre-treatment, as
contained in Callus Induction Media (CIM), is required to render excised plant somatic tissues
competent to regenerate organs including shoots (Christianson and Warnick, 1983, 1984; Morris
and Altmann, 1994; Che et al., 2006). This requirement has been reported across plant species
(Valvekens et al., 1988; Hicks, 1994). Here, we conducted a natural variation screen in
Arabidopsis thaliana to discover ecotypes that could regenerate in the absence of CIM. We
identified several ecotypes, including No-0, which could regenerate efficiently in the absence of
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CIM (Figures 9.1, 9.2). We demonstrated that No-0 explants were particularly insensitive to
exogenous auxin and cytokinin with respect to the shoot regeneration phenotype (Figure 9.3).
We found that introgressed No-0 chromosome segments corresponding to two previously
identified QTLs that promote shoot regeneration (Lall et al., 2004; DeCook et al., 2006), could
confer on a CIM-requiring ecotype, Ler, the ability to regenerate in the absence of CIM (Figure
9.4, 9.5). The two introgressed No-0 chromosome segments acted as dosage dependent
enhancers of one another to promote CIM-dependent shoot regeneration in the Ler-NIL
background (Table 9.1). Furthermore, in a Ler NIL population segregating for the No-0
chromosome segments, the Chromosome 5 No-0 chromosome segment was found to reduce
sensitivity to exogenous auxin and cytokinin (Figure 9.5), consistent with the earlier in vitro
result (Figure 9.3). These results suggest that an important gene(s) acting to promote shoot
regeneration in vitro also regulates exogenous hormone responses in intact seedlings.
In order to characterize the No-0 alleles, microarray analysis was conducted on Ler-0
NIL genotypes introgressed with different combination of the No-0 chromosome segments and
compared to a sibling NIL line without these introgressions. For these hybridization experiments,
RNA was isolated from detached cotyledons that had been placed on SIM for 6 days, a condition
previously identified as being the transition between the competency and organogenesis stages of
shoot development (Lall et al., 2004). The introgression lines showed that the Chromosome 5
region caused a much greater effect on global gene expression than the Chromosome 4 region,
consistent with the corresponding regeneration phenotypes of the NIL lines. The microarray
experiments also provided a molecular mechanism for the observation that the two introgressed
No-0 chromosome segments act in an additive manner to promote shoot regeneration;
specifically, the expression data showed that the expression of important genes such as ACC
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oxidase, the last step in ethylene biosynthesis (see below), was additive, dependent on whether
both No-0 chromosome segments were present. This data suggests that the factors encoded by
the two No-0 chromosome segments target the same downstream effectors.
Of the 778 genes which showed altered regulation in response to the No-0 chromosome
segments, a few hormone related genes were of particular interest, along with genes known to
affect lateral root initiation or development, as lateral root-initiating pericycle cells have been
implicated as sites of callus production (reviewed in Declerq et al. 2011).
Genes related to auxin were of particular interest from the microarray studies, as local
auxin maxima have been shown to stimulate lateral root initiation. It was particularly intriguing
that the No-0 chromosome segments caused up-regulation of two auxin biosynthetic genes,
Nitrilase 3 (NIT3, At3g44320) which catalyzes the last step of IAA biosynthesis, and
cytochrome P450 CYP79B2 (At4g39950), which converts tryptophan to indole-3-acetaldoxime
(Mikkelsen et al., 2000). Other genes affected by the No-0 chromosome segments of particular
interest were AtMES9/ACL, an esterase which could potentially release hormones such as auxin
(IAA) and salicylic acid from inactive conjugated forms, and additional paralogs not discussed,
namely AtMES2 (At2g23600) and AtMES8 (At2g23590) which also showed differential
expression (Appendix Table 8). A final auxin-related gene of particular interest was the
AtDRM1-homolog, an auxin gene which is repressed in growing organs but active in dormant
buds (Mlynárová et al., 2007). The gene AtCHR12, a SWI/SNF2-like protein, has been shown to
be a major regulator of AtDRM1 (Mlynárová et al., 2007), which may provide an epigenetic link
to shoot regeneration. The expression of eight genes related to chromatin remodelling, based on
ChromoDB (Gendler et al., 2008), were affected by the Nossen chromosome segments:
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At2g06520, At3g23930, At4g10180, At4g37800, At5g45350, At5g57785, At5g65160 and
At5g66760.
Substituting Ler alleles with the Chromosome 4 and 5 segments from Nossen also caused
a number of cytokinin related genes to be differentially expressed in cotyledon explants. The
most interesting cytokinin-related gene that showed differential expression was Cytokinin
Oxidase 3 (CKX3), which encodes a cytokinin-degrading enzyme. CKX3 was induced up to
2.7-fold by either the Chromosome 4 or 5 No-0 segments, which was confirmed by RT-PCR.
Previously, CKX3 was shown to be one of the most up-regulated genes linked to shoot
regeneration in Arabidopsis ecotype Columbia (DeCook et al., 2006). The SIM media onto
which the cotyledons used for RNA isolation were incubated, had a high concentration of
cytokinin; one possibility is that as CKX3 is excreted, it could degrade this exogenous cytokinin
in the apoplast (Schmülling et al., 2003). Cytokinin is a repressor of root meristems and of lateral
root initiation (Fukaki and Tasaka, 2009; Růžičkaa et al., 2009), and a cytokinin oxidase mutant
was previously shown to have enhanced production of lateral roots (Werner et al., 2001). These
observations are of interest since pericycle cells originate callus and regenerating shoots.
Therefore, a speculative model is that No-0 Chromosome 5 induction of CKX3 leads to
cytokinin degradation which in turn facilitates the initiation of lateral root stem cells required for
shoot regeneration.
An ERF-family transcription factor, Cytokinin Response Factor 3 (CRF3, At5g53290),
involved in the cross-talk between cytokinin and ethylene, was also up-regulated by both Nossen
Chromosome 4 and 5 segments. This was of interest as CRFs have previously been implicated in
shoot initiation (Rashotte et al., 2006). CRFs are known to be involved in embryo, cotyledon and
leaf development. CRF3 notably acts on NAC (Non Apical Meristem). A number of NAC genes
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showed differential expression in this study (Appendix Table 8) including: ANAC
001(At1g01010), ANAC 019 (At1g52890), ANAC 053 (At3g10500), ANAC 042 (At2g43000)
and ANAC 0061 (At3g44350).
We previously demonstrated that ethylene biosynthesis and signalling have major effects
on shoot regeneration in Arabidopsis (Chatfield and Raizada, 2008). Therefore, one of the most
significant results of this study was that genes encoding two ACC oxidases (At5g43450 and
At5g43440), which encode the last step in ethylene biosynthesis, were up-regulated 3- to 10-fold,
when both No-0 chromosome segments were present. Interestingly, the Chromosome 4 Nossen
segment was insufficient to induce these genes on its own, but appeared to act cooperatively in
the presence of the Chromosome 5 No-0 segment. Given that the expression of ACC oxidases
matched the epistatic and additive effects of these chromosome segments with respect to shoot
regeneration (Figure 9.4C-F), important future experiments should be aimed at understanding the
molecular relationship between the Chromosome 4 and 5 No-0 segments and these genes. The
relationships between the various genes that showed differential expression due to the
introgressed Chromosome 4 and 5 No-0 segments are summarized (Figure 9.8).
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Figure 9.8. Summary for how hormone-related genes are affected by the Major
Chromosome 4 and Chromosome 5 segments from No-0. Genes are represented in light
yellow and pink parallelograms; biological processes are represented in light pink rectangles;
hormones are represented in blue ovals. The biological processes or genes that are written in red
are up-regulated in Ler-only NILs compared to NILs containing both Chromosome 4 and
Chromosome 5 Major segments from No-0. Processes or genes indicated in black are downregulated in response to these No-0 segments.
374
10.General Discussion and Future Experiments
10.1 Summary of results
10.1.1 Objective 1
Objective 1 was to create a software program for the maize research community that
retrieves and analyzes co-expressed promoters and then applies an ensemble algorithm to enable
de novo promoter motif discovery in maize.
After analyzing the accuracy of the most widely used motif discovery programs, in
Chapter 3, it was shown that they had limited accuracy. To improve motif prediction, it was
decided to combine three motif discovery programs to create an ensemble-type application,
applying statistical filters to reduce the false discovery rates of each program. The program was
adapted to retrieve motifs from the maize genome. The program was validated using benchmark
datasets and by its ability to retrieve the experimentally defined binding sites of transcription
factors C1 and P, regulators of the maize anthocyanin and phlobaphene biosynthetic pathways,
respectively. This program is now available in an online software program that was customized
for maize called Promzea. I used Promzea in Chapters 4-8 where it retrieved motifs such as the
previously identified nitrogen response element (NRE) upstream of nitrogen-related genes.
Promzea also found shared motifs between root and shoot-expressed genes related to phase
change (Chapter 4). Given these results, Objective 1 was met, and evidence was found to
support Hypothesis 1 that improved software tools will accelerate promoter motif discovery in
maize.
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10.1.2 Objective 2
Objective 2 was to apply motif discovery software to microarray data collected before
and after the juvenile-adult and floral transitions in maize to identify phase-selective promoter
motifs.
In Chapter 4, a custom Affymetrix 82K-array was used to analyze gene expression in 50
tissues from seedling emergence to post-flowering. Distinct stage- and organ-selective gene
expression clusters associated with juvenile, adult and reproductive phases of development were
found. Over-represented promoter motifs within each phase were also identified. All the juvenile
leaf and juvenile root promoter motifs contained AGG and GAA trinucleotides and resembled
the FLOWERING LOCUS C Motif 2 binding site. Three 5-bp promoter motifs were identified
for the adult leaf-selective cluster (AACAA, CCACG, CCGTT), and these were found to match
over-represented motifs from the adult root-selective cluster. These results suggest that similar
transcription factors regulate phase identity in both, roots and shoots, an unexpected result.
Database searches suggested that the shared adult-phase 5-bp motifs may bind MYB and bZIP
factors, a result that will require functional experiments. I discovered that genes involved in
epicuticular wax biosynthesis, a well-known marker for the juvenile phase in maize leaves, were
also up-regulated in juvenile roots, a novel finding that further demonstrates whole plant
coordination of plant development. A high-priority future experiment would be to analyze both
surface and endodermal wax in juvenile and adult maize roots. In Chapter 4, root and leaf
expression clusters were also compared from pre-flowering/vegetative growth stages to postflowering/mature stages at a time when maize shifts resources from vegetative growth to nutrient
remobilization. Distinct promoter motifs were identified that were specific for roots or leaves
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associated with pre-flowering or post-flowering stages. Therefore, Objective 2 was met, and
support was gained for Hypothesis 2.
10.1.3 Objective 3
Objective 3 was to apply motif discovery software to juvenile stage-specific microarray
data to identify promoter motifs that are selective for different stages of juvenile maize
development.
In Chapter 5, additional results from the 50-tissue developmental series microarray panel
noted above were analyzed. Distinct stage- and organ-selective gene expression clusters were
identified for the following juvenile stages: emergence (Ve, coleoptile), V1 (two-leaf) and V2
(four-leaf). Leaves and roots at each stage were associated with distinct promoter motifs. Organand stage-selective genes were also identified as landmarks for juvenile development. For
example, it was demonstrated that biosynthetic enzymes for the anti-pathogenic metabolite
DIMBOA were selectively up-regulated in emergence stage coleoptiles, a result that may have
field applications. As the young maize root system backbone consists of two distinct organs,
seminal roots and nodal (crown) roots, their transcriptomes were also compared: 1035 probes
were differentially expressed. Thus, Objective 3 was completed and support was gained for
Hypothesis 3.
10.1.4 Objective 4
Objective 4 was to analyze microarray expression data of genes related to nitrogen, based
on expression data from different tissues and developmental stages in maize.
In Chapter 6, additional results from the 50-tissue developmental series microarray panel
described above were analyzed. Distinct clusters of expression of nitrogen uptake and
assimilation genes were identified as well as over-represented promoter motifs associated with
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each expression cluster. Specifically, four nitrogen-related gene expression clusters were
identified in roots and shoots corresponding to, or overlapping, juvenile, adult and reproductive
phases of development. Interestingly, each expression cluster was associated with distinct cisacting promoter motifs, including motifs previously shown to mediate responses to carbon
availability. Among the cis-elements identified was the experimentally defined nitrate responsive
element (NRE) previously only shown in dicots, suggesting this element is conserved across
angiosperms. Thus, Objective 4 was completed and support was gained for Hypothesis 4. After
an extensive literature review, this is the first time that a comprehensive analysis has been
conducted on the spatio-temporal expression of nitrogen-related genes in maize.
10.1.5 Objective 5
Objective 5 was to optimize a system for growing maize root hairs and harvesting root
hair-specific RNA, then using this RNA to undertake microarray analysis of RH in response to
added nitrate.
In Chapter 7, the results of the first study ever conducted on the transcriptome response
by root hairs of any species to nitrogen, or any other nutrient, was reported. First, optimized
protocols for maize root hair growth, harvesting and isolation of root hair-specific RNA to
facilitate microarray analysis, have been created. Microarray experiments were then undertaken
to analyze the early response of the maize root hair transcriptome to an increase in the external
nitrate concentration. The hypothesis was that genes related to nitrate uptake would primarily
respond to the nitrate treatment; however this hypothesis was not supported by the data. Instead,
many of the root hair-responsive genes appeared to be related to tip growth. In parallel to this
study, in our lab, Amélie Gaudin, discovered that maize root hairs respond to ammonium nitrate
by elongating, and hence these two independent studies support one another. Specifically, >876
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genes were differentially expressed within 3 hours of added nitrate in maize root hairs. Of these
genes, 92% were down-regulated at 30 min after nitrate addition while 77% were up-regulated at
3 hours, suggestive of an early reprogramming of the maize root hair transcriptome in response
to nitrate. Furthermore, root hair responsive genes were physically overlapped with previously
identified quantitative trait loci (QTLs) underlying nitrogen and yield responses in maize to
facilitate future candidate gene discovery efforts. Promzea was also used to identify overrepresented promoter motifs associated with different root hair nitrate-response expression
clusters. Therefore, Objective 5 was met, and support was gained for Hypothesis 5, albeit the
classes of genes that showed differential expression were somewhat unexpected.
Future experiments should now be directed towards functional analysis of the important
genes that showed altered regulation. For example, future experiments could include transposon
knockouts, RNAi, overexpression lines, natural variation hunts. Of particular interest were the
transcription factors Dof, Opaque 2 and GCN, as well as genes related to the Target of
Rapamycin (TOR) signaling pathway (a TOR/MEI2/E2F regulon), and two putative SNARE
protein orthologs, AtVAMP711 and AtVAMP725, that mediate vesicle/membrane fusions, as
these may be critical for root hair elongation. The involvement of SNARE protein has been
suspected in RH elongation, but their gene expression has never been identified. Most
fundamentally, the physiological significance of the altered root hair elongation response to
added nitrate needs to be determined.
10.1.6 Objective 6
Objective 6 was to undertake microarray analysis of RH in response to added water
following an extended period of drought.
379
In a parallel experiment to Chapter 7, in Chapter 8, the first ever analysis of the effects
of water availability on the transcriptome of plant root hairs was conducted. Specifically, I
analyzed the early rehydration response of maize root hairs following an extended mild drought
stress. At least 1831 annotated genes were differentially expressed in maize root hairs during the
first 3 hours of rehydration after drought. Surprisingly, a class of genes that are normally upregulated in response to drought, was up-regulated here in response to rehydration. It might be
that part of the root hair rehydration response is slow, which would be consistent with previous
studies involving intact plants as noted in this Chapter. In order to clarify this result, a future
experiment would be to perform microarray analysis using an extended time course (e.g. 24
hours following rehydration). In any case, during the first 3 hours following rehydration, genes
encoding proteins implicated in drought/abiotic stress tolerance showed altered regulation,
including transcription factors (e.g. DREB/CBF) and a putative regulon regulated by ESKIMO1.
Downstream genes regulating the accumulation of well-characterized osmoprotectants and
osmotic solutes were differentially expressed. Interestingly, genes encoding citrulline, implicated
as an osmoprotectant in African desert watermelons, responded to water availability.
Rehydration affected upstream genes involved in ABA biosynthesis and signaling.
Additional hormone biosynthesis/signaling pathways responded to water stress, including
TASSELSEED1,2 and genes containing upstream Squamosa Promoter Binding Protein boxes.
Therefore, Objective 6 was met, and support was gained for Hypothesis 6, albeit the continued
responsiveness of root hairs to drought was unexpected.
In Chapter 8, Promzea was also used to screen for over-represented motifs in the
promoters of these root hair-responsive genes. Interestingly, the majority of the over-represented
promoter motifs shared by promoters of these genes were previously thought to confer seed-
380
specific gene expression. Functional experiments (e.g. promoter deletion analysis) involving
transgenic plants will be needed to confirm the activity and specificity of these motifs.
10.1.7 Objective 7
Objective 7 was to conduct transcriptome analysis of the effects of QTLs that promote
shoot regeneration in Arabidopsis in the absence of auxin.
In Chapter 9, the results of this side-project in which Arabidopsis was used as a model
system for maize was reported to identify candidate genes responsible for improved shoot
regeneration from callus; shoot regeneration is primarily limited to one genotype in maize
(A188) which significantly limits maize transformation. Specifically, RNA samples from
detached cotyledons were isolated; microarray experiments were conducted to understand the
effects of two chromosome segments that bypass the need for auxin during shoot regeneration. It
was discovered that each regeneration-promoting segment altered the expression of suites of
genes including those involved in hormone biosynthesis and signaling. These expressed genes
are now candidate genes for future efforts to improve shoot regeneration in higher plants. Future
experiments should be directed at overlapping these candidate genes to QTLs mapped in maize
that promote shoot regeneration in inbred A188.
10.2 Overall Significance
Fixed nitrogen limits maize production worldwide, and nitrate represents a major cost to
hundreds of millions of maize farmers, and is particularly expensive for the world’s subsistence
farmers. Furthermore, ~50% of applied nitrate is simply leached from the soil into groundwater
or volatilized into potent greenhouse gases. By studying the global expression of nitrogen related
genes in maize as well as genes specifically expressed in root hairs in response to nitrate, both
381
for the first time, along with mapping these responses onto yield QTLs, fundamental information
has been gained which may aid in crop improvement efforts.
Similarly, since maize is grown in intermittent rainfall environments, such as in SubSaharan Africa in semi-arid regions, my analysis of the maize root hair response to rehydration
following drought, may also aid in future efforts to breed drought-tolerant maize.
Either of the above efforts to improve nitrogen use efficiency or drought-tolerance could
involve either traditional breeding or transgenic approaches. The latter has been limited by the
lack of tissue or stage-specific promoters as well as poor shoot regeneration by most maize
genotypes. With respect to the challenge of few promoters available, this thesis has resulted in
the creation of a new promoter-motif discovery tool for the maize community called Promzea. In
this thesis, Promzea was used to identify several candidate motifs which should assist in the
design of improved promoters for maize. Candidate genes discovered in this thesis that are
involved in more efficient shoot regeneration, may help to make a contribution to the latter
challenge of improving the transformation efficiency of maize and the world’s other major crops
that have poor transformation efficiency.
382
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12. Appendices
Appendix Table 1: Gene lists and annotations found in genome-wide searches for Promzeapredicted motifs (M1-M12) from the maize anthocyanin biosynthetic pathway.
Appendix Table 2: Anthocyanin-related gene lists and annotations found in genome-wide
searches for Promzea-predicted motifs (M1-M12) from the maize anthocyanin biosynthetic
pathway.
Appendix Table 3: List of genes that are differentially expressed in root hairs at 0.3 mM nitrate
versus 3 mM nitrate at 30 min and 3 h following addition of liquid root hair media (RHM).
Appendix Table 4: Clusters of differentially expressed genes in RH in response to nitrate
addition
Appendix Table 5: QTL overlap with differentially expressed genes
Appendix Table 6: List of all 1831 annotated genes that were differentially expressed in maize
root hairs following rehydration.
Appendix Table 7: Relative expression of genes from the one channel ATH1 microarray after
normalization (see Methods). Values are in natural logarithms.
Appendix Table 8: Natural variation survey of Arabidopsis ecotypes for the ability to regenerate
shoots in the absence of a high auxin:low cytokinin CIM pre-treatment, on shoot induction media
(SIM).
Appendix Table 9: TAIR identification and descriptions of differentially expressed genes (pvalue<0.01).
Appendix Table 10: QTL related clustering of differentially expressed genes (p-value<0.01).
479
Appendix Figure 1: Comparison between overrepresented promoter motifs predicted from this
study and existing promoter motif. Here are presented a summary of STAMP outputs. The
existing promoter motifs were been retrieved in PLACE and Athamap databases.
Appendix Figure 2: Semi-quantitative RT-PCR validation of the microarray relative expression
data for the 4 NILs. The third graph represents the array probe set hybridization pattern for each
gene.
480