Genome-Wide Detection of Condition-Sensitive
Alternative Splicing in Arabidopsis Roots1[C][W]
Wenfeng Li, Wen-Dar Lin, Prasun Ray, Ping Lan, and Wolfgang Schmidt*
Institute of Plant and Microbial Biology, Academia Sinica, 11529 Taipei, Taiwan (W.L., W.-D.L, P.L., W.S.); The
Samuel Roberts Noble Foundation, Ardmore, Oklahoma 73401 (P.R); Graduate Institute of Biotechnology,
National Chung Hsing University, 40227 Taichung, Taiwan (W.S.); and Genome and Systems Biology Degree
Program, College of Life Science, National Taiwan University, 10617 Taipei, Taiwan (W.S.)
ORCID ID: 0000-0002-7850-6832 (W.S.).
Iron (Fe) deficiency is a world-wide nutritional disorder in both plants and humans, resulting from its restricted bioavailability
for plants and, subsequently, low Fe concentration in edible plant parts. Plants have evolved sophisticated mechanisms to
alleviate Fe deficiency, with the aim of recalibrating metabolic fluxes and maintaining cellular Fe homeostasis. To analyze
condition-sensitive changes in precursor mRNA (pre-mRNA) splicing pattern, we mapped the transcriptome of Fe-deficient
and Fe-sufficient Arabidopsis (Arabidopsis thaliana) roots using the RNA sequencing technology and a newly developed software
toolbox, the Read Analysis & Comparison Kit in Java (RACKJ). In alternatively spliced genes, stress-related Gene Ontology
categories were overrepresented, while housekeeping cellular functions were mainly transcriptionally controlled. Fe deficiency
increased the complexity of the splicing pattern and triggered the differential alternative splicing of 313 genes, the majority of
which had differentially retained introns. Several genes with important functions in Fe acquisition and homeostasis were both
differentially expressed and differentially alternatively spliced upon Fe deficiency, indicating a complex regulation of gene
activity in Fe-deficient conditions. A comparison with a data set for phosphate-deficient plants suggests that changes in
splicing patterns are nutrient specific and not or not chiefly caused by stochastic fluctuations. In sum, our analysis identified
extensive posttranscriptional control, biasing the abundance and activity of proteins in a condition-dependent manner. The
production of a mixture of functional and nonfunctional transcripts may provide a means to fine-tune the abundance of
transcripts with critical importance in cellular Fe homeostasis. It is assumed that differential gene expression and nutrient
deficiency-induced changes in pre-mRNA splicing represent parallel, but potentially interacting, regulatory mechanisms.
The removal of introns from the immature mRNA
by a process called “pre-mRNA splicing” occurs in
the vast majority of eukaryotic protein-coding genes.
Pre-mRNA splicing is catalyzed by elaborate ribonucleoprotein megadalton complexes referred to as
spliceosomes (Wahl et al., 2009). Multiple mRNA isoforms can be generated from a single gene locus by
alternative splicing, potentially producing functionally
distinct protein isoforms (Hsu and Hertel, 2009). In
mammals, alternative splicing dramatically increases
protein diversity, yielding proteins that differ in
function, activity, binding properties, or subcellular
localization, and is believed to account for the multiexonic gene expression diversity, generating an estimated 100,000 proteins encoded by 25,000 genes in
humans (Modrek and Lee, 2002; Kelemen et al., 2013).
1
This work was supported by Academia Sinica (grant no. 02234g
to W.S.).
* Corresponding author; e-mail [email protected].
The author responsible for distribution of materials integral to the
findings presented in this article in accordance with the policy described in the Instructions for Authors (www.plantphysiol.org) is:
Wolfgang Schmidt ([email protected]).
[C]
Some figures in this article are displayed in color online but in
black and white in the print edition.
[W]
The online version of this article contains Web-only data.
www.plantphysiol.org/cgi/doi/10.1104/pp.113.217778
1750
In humans, more than 95% of the intron-containing
genes are alternatively spliced (Pan et al., 2008). Alternative splicing is less prominent in plants, and its
importance has been debated. Recent estimates based
on RNA sequencing (RNA-seq) data suggest that in
Arabidopsis (Arabidopsis thaliana), up to 61% of the
intron-containing genes are alternatively spliced (Filichkin
et al., 2010; Marquez et al., 2012).
About 80% of the nuclear genes in plant genomes
contain noncoding introns (Alexandrov et al., 2006),
many of which can be spliced in various modes. The
dominant mechanisms in alternative splicing among
species are intron retention, skipping of alternative
(cassette) exons (exon skipping), and alternative 59 and
39 splice sites (alternative donor/acceptor). In contrast
to mammals, in which exon skipping accounts for the
vast majority of alternative splicing events, the predominant form of alternative splicing in plants is
intron retention (Filichkin et al., 2010; Marquez et al.,
2012; Walters et al., 2013). However, a recent study
showed that many intron retention transcripts are low
in abundance, suggesting that the importance of intron
retention in plants might be overestimated (Marquez
et al., 2012). In animals, exon skipping is believed to
contribute most to phenotypic diversity by increasing
protein diversity (Keren et al., 2010). Recent studies
showed that changes in alternative splicing evolve
faster than changes in gene expression and contribute
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Alternative Splicing in Arabidopsis Roots
largely to species-specific differences and evolutionary
adaptation (Irimia et al., 2009; Barbosa-Morais et al.,
2012; Merkin et al., 2012). Surprisingly, considering the
high plasticity of plant postembryonic development, in
plants the number of genes that undergo exon skipping was estimated to account for only a small percentage of the alternatively spliced genes (Wang and
Brendel, 2006; Marquez et al., 2012; Walters et al.,
2013).
Alternative splicing frequently produces isoforms
that harbor a premature termination codon (PTC) and
are degraded by the “nonsense-mediated mRNA
decay” (NMD) surveillance pathway or are targeted
by microRNAs. It has been assumed that the inclusion
of a PTC and subsequent degradation via the NMD
pathway represent a mode of controlling functional
transcript levels, a mechanism referred to as “regulated unproductive splicing and translation” (Lareau
et al., 2007). Recent estimates suggest that, in Arabidopsis, 13% to 18% of the intron-containing genes are
regulated by alternative splicing and NMD (Kalyna
et al., 2012), a percentage that is comparable to those
that have been reported for other eukaryotes (Hansen
et al., 2009).
Iron (Fe) deficiency, caused by the generally low
bioavailability of Fe, is a major problem for both plants
and humans. Approximately 1.6 billion people are
affected by Fe deficiency, causing increased maternal
and child mortality, retarded physical and cognitive
development, and a general reduction in fitness. In
particular, in places where plants are the major dietary
source, anemia is often widespread. Furthermore,
suboptimal availability of Fe limits plant growth in
many agricultural soils, causing yield losses and
decreased food and forage quality. Plants have evolved
elaborate mechanisms to improve Fe acquisition when
Fe is limited. In Arabidopsis, Fe is taken up after
reduction of the trivalent Fe generally prevailing in
Fe chelates by the FERRIC REDUCTION OXIDASE2
(FRO2) via the ferrous IRON TRANSPORTER1 (IRT1;
Eide et al., 1996; Robinson and Lemire, 1996). This
reduction-based Fe uptake is aided by proton extrusion mediated by the P-type PLASMA MEMBRANE
PROTON ATPASE2 AHA2, increasing the solubility of
Fe, which strictly depends on the pH (Santi and Schmidt,
2009). The control of cellular Fe homeostasis is thought to
be mainly under transcriptional control. Two bHLH
transcription factors, FER-LIKE REGULATOR OF IRON
UPTAKE and POPEYE (PYE), control nonoverlapping
subsets of genes that contribute to the acquisition, distribution, and storage of Fe (Bauer et al., 2007; Long et al.,
2010). Proteomic studies revealed several Fe-responsive
proteins that were not associated with changes of their
corresponding transcripts, implying other, unexplored
levels of homeostatic control (Lan et al., 2011).
Pre-mRNA splicing has been attributed to mechanisms that regulate stress responses in both animals
and plants. In humans, yeast, and plants, abiotic stress
can increase nonproductive isoforms, counteracting
translation (Pleiss et al., 2007; Filichkin et al., 2010;
Dutertre et al., 2011). In plants, genes encoding regulatory proteins are overrepresented in populations of genes
that undergo alternative splicing, supporting a regulatory
role of alternative splicing (Kazan, 2003; Duque, 2011). In
principle, stress-induced changes in alternative splicing
pattern could provide an alternative route of adjusting
the active transcriptome and thus the protein profile to
the prevailing conditions, acting in concert with the differential expression of genes. Microarray-based transcriptional profiling does not allow for monitoring
changes in splicing patterns. Research into alternative
splicing has been much advanced by next-generation
sequencing of mRNAs (RNA-seq), which provides an
integrative picture of gene expression changes in response to environmental signals. In this study, we set
out to explore changes in splicing patterns that occur in
response to Fe deficiency, analyzed with a novel toolbox that provides an easy-to-use package for the analysis of RNA-seq data. We chose Fe deficiency as a case
study, since both the transcriptional responses and
changes in the protein profiles have been well explored
in previous studies. We report that differential alternative splicing is independently regulated from gene
expression but that several genes that play critical roles
in cellular Fe homeostasis were controlled both transcriptionally and posttranscriptionally by alternative
splicing, indicating an orchestrated regulation of gene
activity. A comparison of the changes in alternative
splicing patterns induced by Fe deficiency with those
induced by phosphate (Pi) deficiency revealed that
changes in splicing patterns are nutrient specific and
not, or at least not chiefly, caused by “weak” splicing
sites. We further report that intron retention is largely
induced in Fe- and Pi-deficient plants, potentially due
to decreased splicing fidelity or a less efficient removal
of nonsense transcripts by NMD under nutrientdeficient conditions. These data indicate that splicing
patterns are adjusted to environmental conditions, providing a fast and efficient means of gene regulation.
RESULTS
Detection of Alternative Splicing Events
Gene expression and splicing patterns of pre-mRNA
in Arabidopsis roots were explored using the RNA-seq
technology on the Illumina GAIIx platform. Samples
were analyzed in triplicate, resulting in a total of 49.6 and
59.7 million uniquely mapped reads for Fe-sufficient and
Fe-deficient plants, respectively (Supplemental Data Set
S1). Under control conditions, a total of 13,824 splice
junction (SJ)-containing genes (out of a total of 20,633
detected genes) were found to be expressed in roots.
Chromosome coverage profiles revealed an equal
distribution of transcriptional activity over the five
chromosomes (Supplemental Fig. S1). In samples from
Fe-deficient plants, a comparable (not statistically different when applying the x 2 test; P = 0.16) but slightly
higher number (14,229) of SJ-containing genes was
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Li et al.
identified from a total of 20,897 detected genes. Splicing patterns were analyzed with the Read Analysis &
Comparison Kit in Java (RACKJ) software toolbox,
which separately computes the number of reads
matching to exons and introns, mapping SJs according
to the alignment of reads to the genome. Source codes
for the RACKJ software are available online at http://
rackj.sourceforge.net/. All four major types of alternative splicing (intron retention, exon skipping, alternative 59 splice site, and alternative 39 splice site),
presumably covering the vast majority of the alternative splicing events, were investigated in control and
Fe-deficient plants (Fig. 1). We first identified all SJs
using conservative criteria (five or more reads per SJ in
all three runs, at least two of which aligned to different
starting positions). With these criteria, we detected
82,231 SJs under control conditions, corresponding to
14,177 intron-containing genes (Fig. 2A; Supplemental
Data Set S2). Under Fe-deficient conditions, the number of detected SJs was increased by 5.1% to a total
of 86,429 in 14,600 intron-containing genes (Fig. 2A;
Supplemental Data Set S2). Using a threshold of five
reads per alternative splicing feature in all three
experiments, 6,855 genes were defined as being alternatively spliced (Fig. 2B). As anticipated from previous
studies in Arabidopsis and Brachypodium spp. (Filichkin
et al., 2010; Marquez et al., 2012; Walters et al., 2013),
under control conditions, mRNAs with retained introns
constituted the largest fraction of alternatively spliced
transcripts (5,690 genes), followed by transcripts with
alternative 59 (donor) and 39 (acceptor) splice sites
(ADA; 2,266 genes; Fig. 2C; Supplemental Data Set S3).
For ADA detection, a minimum of two out of five
reads per alternative splicing feature had to align to
different starting positions for consideration, to avoid
the detection of false positives. Out of the 2,810 ADA
events, alternative 59 splice sites were slightly more
abundant than alternative 39 splice sites (1,406 versus
1,101 events); a small subset had variations in both 59
Figure 1. Major types of alternative splicing. The different forms of
alternative splicing occurring in plants, intron retention, ADA, and
exon skipping, are schematically illustrated. Exons are represented by
boxes and introns by lines. [See online article for color version of this
figure.]
Figure 2. Alternative splicing in roots of Arabidopsis under control and
Fe-deficient conditions. A, Genes with (orange) and without (yellow)
introns in control and Fe-deficient plants. B, Number and percentage
of alternatively spliced (AS) genes in control and Fe-deficient plants. C
and D, Types of alternative splicing in plants grown in control (C) and
Fe-deficient (D) conditions. Numbers represent alternatively spliced
genes. ES, exon skipping; IR, intron retention. [See online article for
color version of this figure.]
and 39 sites (303 events). Transcripts with skipped exons
(523 genes) constituted only a small portion of the alternatively spliced genes (Fig. 2C; Supplemental Data
Set S3). A substantial overlap was noted between the
different forms of alternative splicing either in the same
intron or a different intron, indicating sophisticated
patterns of pre-mRNA processing.
Differential Alternative Splicing upon Fe Deficiency
For plants grown under Fe-deficient conditions, a
similar pattern in the distribution of alternative splicing events was observed (Fig. 2; Supplemental Data
Set S3). Also, the total percentage of intron-containing
genes that were alternatively spliced was substantially
higher (x 2 test; P = 2.6e-13) when plants were starved
of Fe (Fig. 2B). For all alternative splicing features
identified in the three samples of each growth type
(control and Fe-deficient), a P value based on Student’s
t test was calculated, and alternative splicing events
with P , 0.05 and a fold change . 2 between control
and Fe-deficient samples were defined as differentially
alternatively spliced (DAS). Only features that were
detected in all three parallel runs with at least five
reads per run were considered. Using these criteria, a
set of 313 DAS genes was identified, the majority of
which had differential intron retention (DIR; Fig. 3;
Supplemental Data Set S4). A subset of 59 ADA events
was differentially distributed between samples from
control and Fe-deficient plants (DADA), and five genes
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Alternative Splicing in Arabidopsis Roots
Figure 3. A and B, Distribution of DAS events in Fe-deficient (A) and Pi-deficient (B) plants. C, Numbers and overlap of DAS
genes in roots from Fe-deficient and Pi-deficient plants. Data of Pi-deficient plants derived from a published RNA-seq data set
(Lan et al., 2012a) were reanalyzed for alternative splicing patterns. Up, induced (i.e. the preference of an alternative splicing
event in samples from Fe-deficient plants was higher than in those from control plants); down, repressed (i.e. the preference of
an alternative splicing event in samples from Fe-deficient plants was lower than in those from control plants). [See online article
for color version of this figure.]
produced transcripts with exons that were differentially skipped upon Fe deficiency. The majority of the
DIR events were induced upon Fe deficiency (i.e. the
preference of an intron being retained in samples from
Fe-deficient plants was higher than in those from
control plants; Fig. 3; Supplemental Data Set S4).
Changes in Splicing Patterns Are Nutrient Specific
To investigate whether the observed changes in splicing pattern were specific to Fe deficiency, we analyzed a
data set derived from plants that have been deprived of
Pi but were grown under otherwise similar conditions
(Lan et al., 2012a). The number of genes with differential
exon skipping events was comparably low in both samples from Fe-deficient and Pi-deficient plants (Fig. 3B).
Also, the distribution of the significantly altered alternative splicing events differed between the two nutrient regimes: while DADA was clearly lower in
Pi-deficient plants, the number of DIR genes was about
2-fold higher in the latter condition. Similar to samples
from Fe-deficient plants, the majority of intron retention events were induced upon Pi starvation, with this
trend being more pronounced in Pi-deficient plants
when compared with Fe-deficient plants (Fig. 3;
Supplemental Data Set S4). Comparing the Gene Ontology (GO) category “biological process” in genes that
were affected in their splicing pattern by Fe or Pi
starvation revealed overrepresentation of different GO
categories in both growth types (Fig. 4). With the exception of the categories “response to cadmium ion”
and “response to salt stress,” which were strongly
enriched for genes from plants grown under both Fe
and Pi deficiency, the changes in splicing patterns
appeared to be largely nutrient specific. In Fe-deficient
plants, stress-specific categories such as “cellular response to iron ion” and “cellular response to nitric
oxide” were found to be most strongly and exclusively
overrepresented in Fe-deficient plants (Fig. 4). In Pideficient plants, the category “cellular response to
phosphate starvation” and other processes important
for Pi homeostasis, such as “phosphate transport” and
“protein dephosphorylation,” were strongly overrepresented. Stress-specific regulation of DAS is also evident from the surprisingly small overlap of genes with
alternatively spliced features in Fe-deficient and Pideficient conditions (Fig. 3C).
To validate the bioinformatic analysis, we confirmed predicted splicing events by quantitative
reverse transcription-PCR following the delta-delta
threshold cycle method. Samples from control, Fedeficient, and Pi-deficient plants were analyzed, and
the Fe/Pi deficiency-induced fold changes for the
reference isoform (constitutively expressed) and the
DIR isoform were calculated. All of the tested transcripts clearly validated the predicted event in three
independent RNA preparations from Fe-sufficient
and Fe-deficient plants with a clear trend (Fig. 5).
These intron retention events remained unchanged
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Li et al.
Figure 4. Functional categorization (biological
process) of DAS genes in Fe-deficient and Pideficient plants. Data of Pi-deficient plants derived from a published RNA-seq data set (Lan
et al., 2012a) were reanalyzed for alternative
splicing patterns. [See online article for color
version of this figure.]
when plants were subjected to Pi-deficient conditions.
The 4-coumarate:CoA ligases CL1 and CL2 have been
implicated in the production of phenylpropanoids
that, after excretion into the rhizosphere, may chelate
Fe from a pool of low availability (Yang et al., 2010).
For EMBRYO SAC DEVELOPMENT ARREST7 (EDA7)
and glutathion transferase L3 (GSTL3), no function in
Fe acquisition or homeostasis has been assigned yet.
Alternatively Spliced and Differentially Expressed Genes
Are Separately Regulated
Using the same criteria as for DAS, a subset of 429
genes was defined as differentially expressed (DE)
between control and Fe-deficient plants (Supplemental
Table S1). Marker genes for Fe-deficient plants, such as
IRT1, FRO2, and bHLH100, were highly induced (57-,
58-, and 357-fold, respectively), indicating that the
plants were truly Fe deficient. A subset of 26 DE genes
also showed significantly altered intron retention, exon
skipping, or ADA upon Fe deficiency. Categorization
of the biological functions of DAS and DE genes revealed that overrepresentation of GO categories differed largely between both groups, indicating separate
regulation of gene expression and alternative splicing
in response to Fe starvation (Fig. 6). For example, some
GO categories, such as “Suc biosynthetic process” and
“Met biosynthetic process,” were only overrepresented
in DAS genes, while many were only overrepresented
in or largely dominated by DE genes (Fig. 6). Several
biological functions that are important for cellular Fe
homeostasis, such as “cellular response to nitric oxide,” “iron ion transport,” “cellular response to ethylene stimulus,” and “response to zinc ion,” were
overrepresented in both DE and DAS genes. This indicates that the control of gene expression and alternative splicing is not completely independent and that
genes with critical functions in Fe acquisition are regulated both transcriptionally and posttranscriptionally.
Notably, most genes that were highly (more than 10fold) up-regulated under Fe-deficient conditions also
showed a highly significant tendency for at least one
intron being retained under Fe deficiency (Table I). For
example, the oxidoreductase FRO2, important for the
obligatory reduction of ferric chelate, and the Fe
transporter gene IRT2 produced significantly more
transcripts with retained introns under Fe-deficient
conditions (Table I). This is contrary to expectations
and may point to either a decrease in splicing fidelity
or to a fine-tuning mechanism that adjusts the amount
of functional transcripts to the cellular Fe level. In both
cases, more nonproductive transcripts might be produced, a scenario that may contribute to the generally
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Alternative Splicing in Arabidopsis Roots
Figure 5. Validation of alternative splicing events
by quantitative reverse transcription-PCR. A, DIR
features were determined on samples from control, Fe-deficient, and Pi-deficient plants, and the
Fe/Pi deficiency-induced fold changes for the
reference isoform (Ref; constitutively expressed)
and the DIR isoform were calculated by normalizing the data to the reference isoform under
control conditions. Four genes were tested: two
(4CL1 and 4CL2) showed repressed DIR and two
(EDA7 and GSTL3) showed induced DIR in response to Fe-deficient conditions. Splicing of all
tested genes was predicted to remain unchanged
in response to Pi deficiency. Note that different
controls were used for Fe- and Pi-deficient plants.
B, Schematic diagram of the gene model and
primer design strategy. Primers 1 and 2 were used
to measure the abundance of the reference isoform, and primers 3 and 4 were intron retention
specific. Regions with retained introns are magnified. [See online article for color version of this
figure.]
low concordance of transcript levels and protein
abundance (Baginsky et al., 2005; Rogers et al., 2008).
However, this scheme does not hold true for all highly
up-regulated genes, suggesting different modes of
regulation. Also, only a small subset of the DE genes
are also differentially alternatively spliced (Fig. 7),
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Li et al.
Figure 6. Functional categorization (biological
process) of DE and DAS genes. [See online article
for color version of this figure.]
arguing against this assumption. It should also be
noted that the basal (Fe sufficient) transcript level of
many highly induced genes is very low, and alternative splicing features may be either very infrequent or
not yet classified as such in transcripts from Fe-sufficient
plants using our stringent criteria, which would overestimate the potential significance of DAS in this group
of genes. A similarly small overlap of DE and DAS
genes was observed for Pi-deficient plants (Fig. 7B).
Notably, this overlap was substantially smaller when
only those transcripts were considered for which a
cognate protein was identified (Fig. 7). It can thus be
assumed that alternative splicing and differential gene
expression represent parallel, but potentially interacting,
regulatory levels.
Noise or Regulated Changes in Splicing Patterns?
To investigate whether the splicing patterns are
affected by the gene architecture, we analyzed the
number and length of introns in genes that produced
isoforms with retained introns and in those in which
no such events or any other type of alternative splicing
under investigation were detected. We first analyzed
the dependence of the probability to detect an intron
retention event on the number of introns in a given
gene. As anticipated, this ratio increased with the increasing number of introns; no further increase was
observed for genes with 10 or more introns (Fig. 8A). A
similar trend was observed for samples from Fe-deficient
plants. Also with respect to intron length, there was a
clear tendency for a higher probability for an intron
being retained up to an intron length of approximately
1,000 nucleotides (Fig. 8B). Again, no differences were
observed between samples from both growth types. It
can thus be stated that the detection of intron retention
is not affected by the nutrient regime. We next analyzed if the detection of DIR is affected by the gene
architecture. For Fe-deficient plants, there was no clear
dependence of detecting DIR events on the intron length
(Fig. 8C). The DIR-intron retention ratio was generally
higher for samples from Pi-deficient plants, indicating
that the probability of identifying DIR events was
somewhat higher under these conditions. The difference between the two growth types was less pronounced for very long (greater than 700 nucleotides)
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Alternative Splicing in Arabidopsis Roots
Table I. Transcriptional and posttranscriptional regulation of genes in GO categories that are relevant for cellular Fe homeostasis
Genes were selected that were DE, DAS, or both. –, Not regulated; ∞, not expressed under control conditions. Genes that occur in different
categories are only shown once.
Gene Identifier
Gene Description
Fe Deficient/Fe Sufficient
DAS Type-Regulation
RPKM
GO categories
At1g56160
At5g55620
At3g12900
At2g41240
At3g53280
At1g01580
At4g19690
At5g38820
At4g19680
At5g04150
At5g36890
At5g03570
At5g04950
At2g28160
At1g02500
At3g21240
At1g51680
At5g67330
At2g05830
At5g26820
At3g47640
At3g25190
At3g56090
At5g24380
At4g04770
At1g21140
At1g76800
At2g40300
At3g11050
At5g01600
At2g28190
GO categories
At3g13610
At1g49820
At5g48930
At2g37040
At3g53260
At2g45400
At4g14710
At5g53850
At5g46845
At4g36220
At1g71030
At5g04410
At5g20980
At1g14810
At1g32100
GO categories
At3g07720
At3g58810
At4g33020
At5g13740
At1g16150
At5g59520
At5g13750
At1g04410
At3g09200
response to iron ion and iron transport and homeostasis
MYB72, Myb domain protein72
Unknown protein
2-Oxoglutarate (2OG) and Fe(II)-dependent oxygenase superfamily protein
BHLH100, basic helix-loop-helix protein100
CYP71B5, cytochrome p450 71b5
FRO2, ferric reduction oxidase2
IRT1, iron-regulated transporter1
Transmembrane amino acid transporter family protein
IRT2, iron-regulated transporter2
BHLH101, basic helix-loop-helix protein101
BGLU42, b-glucosidase42
IREG2, FPN2, iron regulated2
NAS1, nicotianamine synthase1
FIT, FER-like regulator of iron uptake
SAM1, S-adenosylmethionine synthetase1
4CL2, AT4CL2, 4-coumarate:CoA ligase2
4CL1, 4-coumarate:CoA ligase1
NRAMP4, natural resistance-associated macrophage protein4
NagB/RpiA/CoA transferase-like superfamily protein
IREG3, MAR1, iron-regulated protein3
PYE, bHLH DNA-binding superfamily protein
Vacuolar iron transporter (VIT) family protein
FER3, ferritin3
YSL2, yellow stripe-like2
ABC1, ATP-binding cassette protein1
Vacuolar iron transporter (VIT) family protein
Vacuolar iron transporter (VIT) family protein
FER4, ferritin4
FER2, ferritin2
FER1, ferritin1
CSD2, copper/zinc superoxide dismutase2
Met biosynthetic process and phenylpropanoid biosynthetic process
2-Oxoglutarate (2OG) and Fe(II)-dependent oxygenase superfamily protein
MTK, S-methyl-5-thioribose kinase
HCT, hydroxycinnamoyl-CoA shikimate/quinate hydroxycinnamoyltransferase
PAL1, Phe ammonia lyase1
PAL2, Phe ammonia-lyase2
BEN1, NAD(P)-binding Rossmann-fold superfamily protein
ATARD2, RmlC-like cupins superfamily protein
Haloacid dehalogenase-like hydrolase family protein
MIR160/MIR160C, microRNA
CYP84A1, FAH1, ferulic acid 5-hydroxylase1
MYBL2, MYB-like2
NAC2, NAC domain-containing protein2
MS3, Met synthase3
Semialdehyde dehydrogenase family protein
PRR1, pinoresinol reductase1
response to zinc ion and zinc transport
Gal oxidase/Kelch repeat superfamily protein
MTPA2, metal tolerance protein A2
ZIP9, ZIP metal ion transporter family
ZIF1, zinc-induced facilitator1
WAKL4, wall-associated kinase-like4
ZIP2, ZRT/IRT-like protein2
ZIFL1, zinc-induced facilitator-like1
Lactate/malate dehydrogenase family protein
Ribosomal protein L10 family protein
Plant Physiol. Vol. 162, 2013
∞
∞
546.9
357.4
128.0
58.2
57.1
49.6
21.8
18.0
9.9
7.7
4.4
4.2
3.8
3.6
3.2
2.4
2.4
2.3
2.2
0.5
0.5
0.5
0.4
0.2
0.2
0.2
0.2
0.2
–
–
–
DIR-up
DIR-up
–
DIR-up
DADA-up
–
DIR-up
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Li et al.
Figure 7. Venn diagram of the overlap of genes that are DE, DAS, or
differentially regulated at the protein level (DP). Protein expression
data were taken from Lan et al. (2011; Fe deficient) and Lan et al.
(2012a; Pi deficient). [See online article for color version of this figure.]
introns (Fig. 8C). With regard to intron number, there
was a slight trend of increasing the likelihood to detect
DIR events for genes with more introns, which was
more pronounced in transcripts from Pi-deficient plants
when compared with Fe-deficient plants (Fig. 8D).
Generally, these trends were not very pronounced, and
it can be stated that differential alternative splicing is
not or not strongly biased by the gene architecture,
except for genes with a high (more than 15) number of
introns, which might be slightly more prone to intron
retention under the tested nutrient conditions.
We further compared the representation of the GO
category “biological processes” in genes that underwent alternative splicing with those that were not alternatively spliced. This comparison revealed clearly
that in both populations, different GO categories were
overrepresented (Fig. 9). Generally, in genes that produce alternative transcripts, several GO categories
related to stress, such as “response to salt stress,”
“response to cold,” “defense response to bacterium,”
and “response to wounding,” among others, were
overrepresented, while housekeeping functions such
as “protein folding,” “DNA repair,” and “chloroplast
organization” were overrepresented in genes that were
not alternatively spliced. For Fe-deficient plants, a
generally similar picture emerged. In the stress-related
categories, the possibility of genes that undergo alternative splicing was more pronounced than genes that
were not alternatively spliced, supporting the assumption that, generally, stress-related genes are more
predisposed to pre-mRNA processing than genes encoding proteins that are involved in basic cellular
Figure 8. Dependence of the probability of detecting intron retention events on the gene structure. A and B, Dependence of intron
number (A) and intron length (B) on the ratio between intron retention events and detected intron-containing genes of samples from
control and Fe-deficient plants. C and D, Ratio of DIR versus intron retention (IR) events with respect to the intron length (C) and the
intron number of DIR versus intron retention genes (D). Data of Pi-deficient plants derived from a published RNA-seq data set (Lan
et al., 2012a) were reanalyzed for alternative splicing patterns. [See online article for color version of this figure.]
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Alternative Splicing in Arabidopsis Roots
Figure 9. Functional categorization (biological process) of alternatively spliced (AS) and nonalternatively spliced (nonAS) genes
in control and Fe-deficient conditions. Data of Pi-deficient plants derived from a published RNA-seq data set (Lan et al., 2012)
were reanalyzed for alternative splicing patterns. [See online article for color version of this figure.]
functions (Fig. 9). A similar pattern was observed for
Pi-deficient plants, suggesting that these observations
were general and not affected by the growth regime
(Fig. 9).
DISCUSSION
While underestimated and almost neglected a decade ago, recent studies using massively parallel RNA
sequencing show that a large percentage of genes in
Arabidopsis undergo alternative splicing (Filichkin
et al., 2010; Marquez et al., 2012), suggesting a massive
effect on gene activity. This underestimation derived
mainly from the widely used microarray platforms to
catalog gene expression, which rather reports a mixture of different splicing isoforms matching a precast
probe set and does not distinguish between different
mRNAs that derive from the same gene. Our analysis
here suggests that, under control conditions, 48% of
the intron-containing genes detected in Arabidopsis
roots are alternatively spliced. This number is slightly
higher than that reported by Filichkin et al. (2010; 42%)
and somewhat lower than a recent study that revealed
alternative splicing for 61% of multiexonic genes for
a normalized complementary DNA (cDNA) library,
which facilitates the detection of alternative splicing
events in transcripts with low abundance (Marquez
et al., 2012). A comparable percentage (56%) was estimated for maize (Zea mays) leaves (Li et al., 2010). It
can be assumed that, due to the distinguished phenotypic plasticity associated with the sessile lifestyle of
plants, the extent of alternative splicing is elaborated
by adaptive processes. This assumption has been supported by a recent analysis of the splicing patterns of
various circadian clock genes under different stresses.
For example, heat stress was shown to support the expression of a CCA1 isoform that harbors a PTC, while
under cold stress the canonically spliced isoform was
predominant (Filichkin and Mockler, 2012), suggesting
stress-induced changes of alternative splicing to regulate
gene activity.
Nutrient Deficiency Induces More Complex Transcript
Isoform Patterns
Due to the differences in the architecture of mammalian and plant genomes, different types of alternative splicing are prevalent in the two groups. In
contrast to animals, intron retention and alternative
donor/acceptor are much more prominent than exon
skipping, which makes the detection of alternative splicing features and predictions regarding the
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Li et al.
biological relevance more difficult. Supporting previous
studies, the prevalent form of alternative splicing in
Arabidopsis roots was intron retention, which seems to
be conserved in plants. It is noteworthy to mention that
a large subset of genes was affected by multiple forms
of alternative splicing, suggesting complex patterns of
mRNA isoforms. The estimate for exon skipping and
alternative 59 and 39 splice sites appears to differ among
species and/or tissues. Li et al. (2010) observed a substantially higher (32%) percentage of exon skipping in
maize leaves, while the number of exon-skipping events
appears to be much lower in Arabidopsis (Filichkin
et al., 2010; Marquez et al., 2012; Walters et al., 2013; this
study). Notably, in maize leaves, the estimate for 59 and
39 alternative splice sites was substantially lower than
what we observed for Arabidopsis, indicating a highly
variable amount of low-abundance splice isoforms. Fe
and Pi deficiency enhanced the complexity of alternative splicing in Arabidopsis roots, increasing the
percentage of alternatively spliced genes. This finding
suggests that the total number of genes may increase
when more genome-wide studies under different stress
conditions become available. All types of alternative
splicing were affected by the nutrient regime, which
might be indicative of a decrease in splicing fidelity.
However, the changes in splicing patterns were highly
specific to the growth type, with a very small, random
overlap between samples from Fe-deficient and Pideficient plants, arguing against such an assumption
and in favor of the physiological significance of the observed changes. Furthermore, GO categories of growth
type-relevant functions were significantly overrepresented in the respective conditions, further supporting
regulated changes in splicing patterns.
Stress-Induced Changes in Splicing Patterns May Have
Functional Implications
While it is clear that a large number of transcripts
undergo alternative splicing, the biological significance
of this process in plants remains enigmatic. One possible cause of alternative splicing is stochastic noise,
imprecise operation of the splicing machinery that
causes the production of a certain percentage of unproductive mRNAs that are not translated into proteins and degraded via the NMD pathway. Such
stochastic noise may have functional advantage by
stabilizing the system via a fast increase in functional
heterogeneity (Blake et al., 2006; Simpson et al., 2009;
Eldar and Elowitz, 2010). However, the fact that unrelated stresses induce unique molecular profiles
argues against this assumption, without excluding that
stochastic fluctuations may cause the production of
a subset of alternatively spliced transcripts. Furthermore, the analysis of GO categories of genes that
undergo alternative splicing and of those that are not
alternatively spliced clearly shows differences between
the two populations, suggesting the biological function
of alternative splicing.
Alternatively spliced transcripts may be translated
into novel proteins with altered functions, increasing
the diversity of the proteome. However, the fact that
most of the alternative splicing events in plants are
intron retention, which may contain PTCs, does not
support this scenario. A prerequisite for biologically
meaningful alternative splicing is a regulated selection
of splice sites. While our analysis does not allow for
a clear-cut distinction between noisy and regulated
alternative splicing, we favor the hypothesis that at
least a subset of alternatively spliced genes is part of an
additional, in plants largely unexplored, layer of gene
regulation. Differential gene expression and differential alternative splicing may represent separate but
cooperative regulatory levels for adjusting the abundance of a given protein to a given environmental
condition. Such regulated unproductive splicing and
translation has been described as a regulatory mechanism for several genes in yeast and mammals (Lareau
et al., 2007). An argument in favor of this hypothesis
is that the costs for transcription are relatively low
compared with the production of a protein (and its
potential degradation). Among the mRNAs with Fe
deficiency-induced intron retention, some transcripts
with crucial functions in Fe uptake and homeostasis
were found, including FRO2, IRT1, IRT2, bHLH100,
and bHLH101. All of the intron-retained isoforms
contain PTCs. An attractive scenario that would explain our findings involves stress-specific changes in
histone modification signatures that affect alternative
splicing, either by the rate of Pol II elongation or by
the recruitment of a specific set of splicing factors. In
mammalian cells, methylation or acetylation of core
histones can bias splicing patterns (Alló et al., 2009;
Luco et al., 2010). In the case of plants, such a mechanism awaits experimental validation. Alternatively,
or in addition to such a mechanism, the production of
a mixture of functional and nonfunctional transcripts
may provide a means to fine-tune the abundance of
transcripts with critical importance for cellular Fe homeostasis without going to a much slower and more
costly cycle of protein production and degradation to
adjust the level of protein to fluctuating conditions.
Such a dual regulation is common in biological systems and has also been observed for the control of Fe
homeostasis. Two examples are the bHLH transcription factor PYE and the putative E3 ligase BRUTUS,
which were suggested to have opposite effects on the
expression of a subset of genes with important roles in
Fe homeostasis by acting with common binding partners (Long et al., 2010). Both genes are up-regulated
upon Fe starvation, possibly to allow for a fast adaptation of the activity of target genes. Alternatively (or
additionally), retaining introns may serve as an adequate means to avoid the translation of transcripts that
do not contribute to stress adaptation as an alternative
to the repression of transcription. Intron retention and
alternative 59 and/or 39 splice sites in conjunction with
NMD may work in this way and may represent a mechanism to adapt the proteome profile to the prevailing
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Alternative Splicing in Arabidopsis Roots
conditions. In plants, intron retention transcripts are
often insensitive to NMD, which may also provide an
explanation for the high frequency of intron retention
events in plants (Kalyna et al., 2012).
Nonfunctional Alternative Splicing May Represent a Fast
Fine-Tuning Mechanism of Gene Activity
It is interesting that intron retention was repressed
in a subset of transcripts, indicative of an increased
splicing fidelity of the encoded proteins that is crucial
for the recalibration of nutrient homeostasis. Alternatively, Fe and Pi deficiency may induce a more efficient
decay of aberrant transcripts. It is further possible that
the subset of genes with retained introns is enriched in
more ambiguous splice signals that are, under control
conditions, more frequently missed by the splicing
machinery. Stress, such as Fe or Pi deficiency, may
trigger a more efficient removal of the introns. Such a
mechanism has been demonstrated for yeast (Saccharomyces cerevisiae), in which different stresses led to an
increased or decreased splicing efficiency for stressspecific subsets of genes, suggesting a regulated
splicing mechanism as a means to control gene expression in response to stress (Pleiss et al., 2007). A
similar scenario may apply for plants. Since, in contrast to yeast, the majority of genes contain multiple
introns, condition-specific changes in splicing patterns
may be much more complex. In yeast, the response of
the splicing machinery to environmental conditions is
rapid and independent of protein synthesis. Thus, alternative splicing might represent a rapid component
of a multilayered regulation of gene expression. What
we describe in this study is a steady-state level of alternatively spliced transcripts that might be rapidly
turned over. It can be speculated that conditionsensitive alternative splicing provides a means to
regulate gene activity by fine-tuning the production of
a certain subset of proteins, which may be specifically
required under the respective circumstances, and
shutting down others that are not required in a particular stress situation. A further possibility is that
differential gene expression and differential alternative
splicing represent separate but cooperative regulatory
levels for adjusting the abundance of proteins to a
given environmental condition. The expression level of
several DAS genes was not changed significantly in
response to Fe deficiency, indicating a regulation exclusively at the posttranscriptional level. Most of these
genes have not been associated with responses to Fe
deficiency, but a function in Fe metabolism might be
inferred for some of these genes upon closer inspection. For example, ZINC-INDUCED FACILITATORLIKE1 (ZIFL1) was shown to possess a dual function
in auxin transport and drought resistance (Remy et al.,
2013). Interestingly, the function of ZIFL1 was regulated by alternative splicing (Remy et al., 2013). Auxin
responsiveness is altered in Fe-deficient plants (Lan
et al., 2012b), making it tempting to suggest that DAS
could modulate auxin-related processes in Fe-deficient
roots. Another gene for which a function of DAS can
be assumed is the copper/zinc superoxide dismutase
CDS2. DIR of CSD2 was repressed in Fe-deficient
roots, possibly to compensate for the compromised
activity of Fe superoxide dismutase. At3g09200 encodes
one out of three paralogous ribosomal L10 family
proteins, structural components of the large subunit of
cytosolic ribosomes. The composition of ribosomes
was shown to be responsive to environmental conditions (Hummel et al., 2012), possibly altering translation. The repression of DADA of At3g09200 transcripts
may thus contribute to the selective translation of a
subset of mRNAs coding for proteins with important
functions in Fe homeostasis. While such a cooperative
gene regulation by DE and DAS needs to be experimentally verified, the analysis presented here provides
a straightforward way for directing experimental
strategies.
MATERIALS AND METHODS
Plant Growth
Arabidopsis (Arabidopsis thaliana) plants were grown in a growth chamber
on an agar-based medium as described previously (Estelle and Somerville,
1987). Seeds of the Columbia accession were obtained from the Arabidopsis
Biological Resource Center. Seeds were surface sterilized by immersing them
in 5% (v/v) NaOCl for 5 min and 96% ethanol for 7 min, followed by four
rinses in sterile water. Seeds were placed onto Petri dishes and kept for 1 d at
4°C in the dark; the plates were then transferred to a growth chamber and
grown at 21°C under continuous illumination (50 mmol m22 s21; Philips TL
lamps). The medium was composed of (mM): KNO3 (5), MgSO4 (2), Ca(NO3)2
(2), KH2PO4 (2.5); (mM): H3BO3 (70), MnCl2 (14), ZnSO4 (1), CuSO4 (0.5), NaCl
(10), Na2MoO4 (0.2); and 40 mM Fe-EDTA solidified with 0.3% Phytagel
(Sigma-Aldrich). Suc (43 mM) and 4.7 mM MES were included, and the pH was
adjusted to 5.5. After 10 d of precultivation, plants were transferred either to
fresh agar medium without Fe and with 100 mM 3-(2-pyridyl)-5,6-diphenyl1,2,4-triazine sulfonate, medium without phosphate, or fresh control medium
and grown for 3 d. The lower concentration of potassium because of the
absence of KH 2 PO 4 in the phosphate-free medium was corrected by the
addition of KCl.
RNA-seq
Total RNA was extracted from roots grown under control and Fe- or Pideficient conditions using the RNeasy Plant Mini Kit (Qiagen). Equal amounts
of RNA were collected from three independent experiments and used for
sequencing. cDNA libraries for sequencing were prepared from 5 mg of total
RNA following protocols provided by the instrument manufacturer (Illumina). The cDNA libraries were enriched by 15 cycles of PCR amplification.
The resulting cDNA libraries were sequenced on a single lane per sample of
the Illumina Genome Analyzer II. The RNA-seq and data collection followed
published protocols (Mortazavi et al., 2008). The length of the cDNA library
ranged from 250 to 300 bp with a 59 adapter of 58 bp and a 39 adapter of 63 bp
at both ends. The fragment length of the cDNA ranged from 129 to 179 bp.
For high-throughput sequencing, the library was prepared according to the
manufacturer’s instructions and submitted to 80-nucleotide sequencing using
the Illumina GAIIx system.
Read Alignment to the Arabidopsis Genome
A total of 56,698,709 and 68,360,588 reads were obtained from Illumina
sequencing for Fe-sufficient and Fe-deficient conditions. Reads were aligned to
The Arabidopsis Information Resource 10 (TAIR10) reference genome using
the BLAT program (Kent, 2002) with minimum 95% identity, but only the
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Li et al.
alignment with the highest identity for each read was considered for mapping.
Multireads were distributed in proportion to the number of unique and splice
reads recorded at similar loci using the Enhanced Read Analysis of Gene
Expression strategy (Mortazavi et al., 2008). Subsets of 51,786,440 and 62,485,423
reads were mapped to the TAIR10 genome for each sample from treated and
untreated roots.
Computing DE Genes
Adapters were trimmed from reads, with approximately 20.0 M 80-mer
reads for each sample in three replicates. RPKM values (reads per kilobase of
exon model per million mapped reads) were computed as described (Mortazavi
et al., 2008). A transcript was defined as present when it was detected with at
least five reads in all three experiments within one growth type (i.e. either
treated or untreated). A gene was denoted as DE between control and Fedeficient plants at P , 0.05 calculated by Student’s t test and a Fe-deficient/
control fold change . 2.
threshold cycle method was used to determine the relative amount of gene
expression (Livak and Schmittgen, 2001).
GO Analysis
Enrichment analysis of GO categories was done in the Gene Ontology
Browsing Utility (Lin et al., 2006) using the “elim” method from the aspect
“biological process.” The elim method is a Java implementation of the TopGO
elim algorithm (Alexa et al., 2006). The GO categories shown in the figures
were chosen based on the following criteria: more than 10 genes must be listed
in TAIR10, and P , 0.005 (P , 1e-6 in Fig. 9) calculated by the elim method.
The selected categories were sorted from the smallest to the biggest P value.
Sequence data from this article can be found in the GenBank/EMBL data
libraries under accession number SRA045009.
Supplemental Data
SJ Detection
Splicing patterns were explored using the RACKJ software toolbox, which
separately computes the number of reads matching to exons, introns, and SJs.
Source codes for the RACKJ software are available online at http://rackj.
sourceforge.net/. To diminish the number of potential false positives that are
predicted by erroneous alignment, we performed a prediction of SJs with a minimum of eight-nucleotide identical alignment blocks to the genome and supported
by at least five reads with at least two of them having different starting positions.
Detection of Condition-Sensitive Alternative
Splicing Events
The following materials are available in the online version of this article.
Supplemental Figure S1. Transcriptional profile of genes in roots of Fesufficient and Fe-deficient plants.
Supplemental Table S1. DE genes between control and Fe-deficient plants.
Supplemental Table S2. Primers used for the validation of DAS features.
Supplemental Data Set S1. Read numbers and RPKM values from the
transcriptome analysis of samples from control and Fe-deficient plants.
Supplemental Data Set S2. SJs in samples from control and Fe-deficient
plants.
We investigated the four main types of alternative splicing in plants: intron
retention, exon skipping (cassette exon), alternative 59 splice site (alternative
donor), and alternative 39 splice site (alternative acceptor). Alternative splicing
events were computed using the RACKJ program. We defined DAS events
using the “splicing index” method (Griffith et al., 2010). Essentially, the
expression of each event was normalized to the expression level of the gene
to which it belongs (splicing index value) before two samples (control and
treatment) were compared. Student’s t test was then applied to validate differences in the splicing index values for a particular alternative splicing event
between samples from control and treated plants. The fold change was calculated as (Ti/Tj)/(Ci/Cj) for the i-th exon (intron) of the j-th gene in control
(C) and treated (T) samples. Alternative splicing events with significant P values
(P , 0.05) and fold change . 2 were denoted as DAS events.
Received March 13, 2013; accepted June 3, 2013; published June 4, 2013.
Primer Design for the Validation of Alternative
Splicing Events
LITERATURE CITED
For the validation of DIR, primers were designed to cover the predicted
retained intron with either of the two primers corresponding to the putatively
retained intronic sequence. Another pair of reference primers that amplify the
exon next to the retained intron was designed to monitor the expression level
of its corresponding gene. The melting temperature of primers was in the
range of 58°C to 62°C. Primer pairs were selected using Primer3 (http://
primer3.sourceforge.net/). Elongation factor1-b2 (At5g19510) was used as an
internal control for transcript normalization. Primers used for the validation
are listed in Supplemental Table S2.
Quantitative Reverse Transcription-PCR
Total RNA was isolated using the RNeasy Plant Mini Kit (Qiagen) and
treated with DNase using the TURBO DNA-free Kit (Ambion) as suggested by
the manufacturer. cDNA was synthesized using 4 mL of DNA-free RNA with
oligo(dT)20 primer and SuperScript II reverse transcriptase (Invitrogen). After
incubation at 50°C for 1 h followed by 70°C for 15 min, 1 mL of RNase H was
added and incubated for 20 min at 37°C. The cDNA was used as a PCR
template in a 20 mL reaction system using the SYBR Green PCR Master Mix
(Applied Biosystems) with programs recommended by the manufacturer in
the ABI Prism 7500 Sequence Detection System (Applied Biosystems). Three
independent replicates were performed for each sample. The delta-delta
Supplemental Data Set S3. Alternative splicing features in samples from
control and Fe-deficient plants.
Supplemental Data Set S4. DAS features.
ACKNOWLEDGMENTS
We thank Ally Kuo (IPMB) for figure artwork and editing of the manuscript, Thomas J. Buckhout (Humboldt University) for critical comments, and
the Bioinformatics Core Facility at the Institute of Plant and Microbial Biology
for proficient support.
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