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Electronic Theses, Treatises and Dissertations
The Graduate School
2007
Gene Expression in Leaves, Mesophyll
Tissues and Guard Cells of Arabidopsis
Thaliana and the Effect of Sucrose
Maitreyi Chattopadhyay
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THE FLORIDA STATE UNIVERSITY
COLLEGE OF ARTS AND SCIENCES
GENE EXPRESSION IN LEAVES, MESOPHYLL TISSUES AND GUARD
CELLS OF ARABIDOPSIS THALIANA AND THE EFFECT OF SUCROSE
By
MAITREYI CHATTOPADHYAY
A Thesis submitted to the
Department of Biological Science
in partial fulfillment of the
requirements for the degree of
Master of Science
Degree Awarded:
Spring Semester, 2007
The members of the Committee approve the Thesis of Maitreyi Chattopadhyay defended
on February 13, 2007.
George W. Bates
Professor Directing Thesis
Hank W. Bass
Committee Member
William H. Outlaw Jr.
Committee Member
The Office of Graduate Studies has verified and approved the above named committee members.
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I dedicate this thesis to my parents Sunil Bhattacharyya and Jogmaya Bhattacharyya for
their love, to my beloved daughter Abjini, and to my husband Somesh Chattopadhyay for
his encouragement.
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ACKNOWLEDGEMENTS
I would like to acknowledge and show my deep appreciation for my thesis director Dr.
George W. Bates for his help, support and guidance through my graduate study at Florida
State University. My deep appreciation is also for my committee members: Dr. William H.
Outlaw and for Dr. Hank W. Bass for their support and many important suggestions for
completing this thesis.
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TABLE OF CONTENTS
List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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List of Abbreviations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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Abstract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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1. INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
1.1 Guard Cell Biochemistry . . . . . . . . . . . . . . . . . . . . . . . .
1.2 Sucrose Transport and Metabolism in Plant Cells . . . . . . . . . .
1.3 Sugar Sensing by Plants . . . . . . . . . . . . . . . . . . . . . . . .
1.4 The Research Goals of this Study . . . . . . . . . . . . . . . . . . .
1.5 Specific Experimental Goals of this Thesis . . . . . . . . . . . . . .
1.6 Candidate Genes for this Study and the Rational for their Selection
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2. MATERIALS AND METHODS . . . . . . . . . . . . . . . . . .
2.1 Plant Material . . . . . . . . . . . . . . . . . . . . . . . . .
2.2 Measurement of Stomatal Aperture Size . . . . . . . . . . .
2.3 Preparation of Leaf Strips and Sugar Treatments . . . . . .
2.4 Large Scale RNA Isolation . . . . . . . . . . . . . . . . . . .
2.5 Micro Scale RNA Isolation . . . . . . . . . . . . . . . . . . .
2.6 Reverse Transcription . . . . . . . . . . . . . . . . . . . . .
2.7 Design of Gene-specific Primers . . . . . . . . . . . . . . . .
2.8 Primers of our Selected Genes . . . . . . . . . . . . . . . . .
2.9 Standard PCR Reactions and Purification of PCR Products
2.10 Quantitative Real-time PCR and Data Analysis . . . . . . .
2.11 Generating the Absolute Standard Curves . . . . . . . . . .
2.12 RNA Amplification . . . . . . . . . . . . . . . . . . . . . . .
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3. RESULTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.1 Diurnal Changes in Stomatal Movement . . . . . . . . . . . . . . . . . .
3.2 Quantification of Transcripts in RNA Isolated from Leaf Strips of Arabidopsis Treated with Sucrose or Mannitol and the Problem of Variability
between Biological Replicate Samples. . . . . . . . . . . . . . . . . . . .
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3.3 Variability between Samples is not due to Variation in the Q-PCR or
cDNA Reactions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
3.4 Comparison of ACT2, EF1 and CYP as Normalizer Genes . . . . . . . .
3.5 Summary Data on the Effects of Sucrose and Mannitol Treatments on
Gene Expression in Leaf Strips . . . . . . . . . . . . . . . . . . . . . . .
3.6 Quantification of RNA Isolated from Microdissected Mesophyll Cells . .
3.7 Investigation of the Use of RNA Amplification for Analysis of Gene
Expression in Sub-nanogram Sized Samples of RNA from Mesophyll Cells
3.8 Quantification of RNA from Microdissected Guard Cells . . . . . . . . .
4. DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
4.1 The Problem of Variability between Replicate Samples . . . .
4.2 Gene Expression in Leaf Strips and the Effects of Sucrose . . .
4.3 Gene Expression in Mesophyll Tissue and RNA Amplification
4.4 Measurement of Gene Expression in Guard Cells . . . . . . .
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REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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BIOGRAPHICAL SKETCH . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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LIST OF TABLES
3.1
The effect of sucrose and mannitol treatment on RBCS, KAT1, TPS1, STP1
and ACT2 in leaf strips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
23
The effect of sucrose and mannitol treatments on ACT2 and SUC2 expression
in leaf strips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
26
The effect of sucrose and mannitol treatments on ACT2, and HAB1 expression
in leaf strips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
28
Raw Q-PCR data for ACT2, CYP and EF1 in RNA from sucrose- and manitoltreated leaf strips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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3.5
Summary data for sucrose-regulated gene expression in leaf strips . . . . . .
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3.6
Gene expression in different samples of mesophyll tissue cut from the same
biological replicate of leaf strips treated with sucrose . . . . . . . . . . . . .
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Gene expression in different samples of mesophyll tissue cut from the same
biological replicate of leaf strips treated with mannitol . . . . . . . . . . . .
34
The effect of sucrose and mannitol treatments on gene expression in mesophyll
cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
36
Q-PCR data of sample S6/2 before and after 100 fold RNA dilution and
amplification with T7 RNA polymerase . . . . . . . . . . . . . . . . . . . . .
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3.10 Q-PCR data of samples S5/31, S6/2 and M5/31, M6/2 before and after
dilution and RNA amplification . . . . . . . . . . . . . . . . . . . . . . . . .
41
3.11 Absolute and normalized quantities of transcripts in RNA from freeze-dried
mesophyll tissue before and after dilution and amplification . . . . . . . . . .
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3.12 Effect of holding freeze-dried tissue at room temperature on RNA quality . .
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3.13 Gene expression in guard cells and the effects of sucrose and mannitol . . . .
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3.2
3.3
3.4
3.7
3.8
3.9
vii
LIST OF FIGURES
3.1
The diurnal changes in stomatal aperture size . . . . . . . . . . . . . . . . .
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3.2
Effect of sucrose and mannitol on RBCS, KAT1, TPS1, STP1 and ACT2 in
leaf strips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
24
Expression of genes in leaf strips relative to the expression of ACT2 in the
same sample . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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3.4
The gene expression in response to sucrose in leaf strips . . . . . . . . . . . .
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3.5
Top: Relative expression of genes to ACT2 in mesophyll tissue. Bottom:
Relative expression of genes to ACT2 in leaf strips . . . . . . . . . . . . . . .
38
Comparison of relative expression of genes before and after RNA dilution and
amplification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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3.7
Gene expression relative to ACT2 in guard cells . . . . . . . . . . . . . . . .
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4.1
Comparison of gene expression profiles in mannitol-treatmed leaf strips,
mesophyll tissue, and guard cells . . . . . . . . . . . . . . . . . . . . . . . .
53
3.3
3.6
viii
LIST OF ABBREVIATIONS
ACT2
ADPGase
Ampl
aRNA
Avg
Biol
Btw
cDNA
Ch
Ct
CV
CYP
Diff
Exp
h
HAB1
KAT1
Man
nd
No
NTC
Q-PCR
RBCS
Repl
SD
SE
SPS
STP1
Suc
SUC1
SUC2
Actin2 gene
ADP-glucose pyrophosphorylase gene
Amplification
Antisense RNA
Average
Biological
Between
Complementary DNA
Change
Thresold Cycle
Coefficient of Variation
Cyclophilin gene
Difference
Experiment
hour
Protein phosphatase 2C gene
Potassium inward channel gene
Mannitol treatment
Not determined
Number
Non template control
Quantitative polymerase chain reaction
Ribulose-1, 5-bisphosphate carboxylase small subunit gene
Replicate
Standard deviation
Standard Error
Sucrose phosphate synthase gene
Arabidopsis H+ -monosaccharide symporter gene
Sucrose treatment
Sucrose transporter1 gene
Sucrose transporter2 gene
ix
SUS
TPS1
Undet
Sucrose synthase gene
Trehalose 6- phosphate synthase1 gene
Undetected
x
ABSTRACT
Sugar, the end product of photosynthesis, not only plays an important role in carbon and
energy metabolism and in polymer biosynthesis, it also functions as a hormone like signaling
molecule that regulates the expression of many genes involved in growth, development and
resource allocation in plants. This study focuses on the gene expression profiles in leaves
and guard cells of the model plant Arabidopsis thaliana and the response of these genes
to sugar. Guard cells are specialized cells that flank each stoma on the surface of the
leaf epidermis. Guard cells regulate stomatal aperture thereby controlling the rate of carbon
dioxide uptake during photosynthesis and the rate of water loss during transpiration. During
stomatal opening, solute content within guard cells builds up due to the uptake of ions and
other solutes from outside of the cell. Solute content also builds up by intercellular solute
production within guard cells. As a result water is driven into guard cells osmotically, turgor
pressure within the cells increases, the guard cells swell, and stomatal aperture increases
in size. Stomatal closure is initiated with the dissipation of these solute gradients. Guard
cell chloroplasts cannot perform significant amounts of photosynthetic carbon fixation due
to a low activity of the enzyme rubisco. Guard cells also lack functional plasmodesmata.
Therefore, guard cells depend on extracellular sugars (specifically sucrose).
Under the
conditions of high light intensity and high transpiration rates, sucrose is swept by the
transpiration stream from the mesophyll cells and is deposited in the cell wall of guard cells.
Delivery of sucrose into guard cells via sucrose transporters, or breakdown of the sucrose
by different sucrose cleaving enzymes on the cell wall and transport of those hexoses into
cell, provides the energy needed for guard cell metabolism and may also have a signaling
role in the swelling and shrinking of guard cells. This study examines gene expression
profiles in leaves, mesophyll cells, and in guard cells, and the transcriptional responses of
these genes to sucrose. The ultimate goal of the study was to demonstrate the feasibility
xi
of analyzing gene expression in small samples of individually dissected guard cells (about
40-50 guard cells per sample) of Arabidopsis. The panel of genes studied here included
several genes preferentially expressed in guard cells (monosaccharide symporter 1 (STP1),
trehalose phosphate synthase 1 (TPS1), protein phosphatase 2C (HAB1), potassium inward
channel (KAT1) and ADP-glucose pyrophosphorylase (ADPGase)), a gene that should be
preferentially expressed in mesophyll cells (ribulose bisphosphate carboxylase, RBCS), two
genes inovled in sucrose transport (sucrose transporters 1 and 2, SUC1 and SUC2), and
three control genes (Actin-2, ACT2, elongation factor 1a, EF1, and Cyclophilin, CYP).
Gene expression was assayed by quantitative real-time PCR (Q-PCR).
In an initial experiment gene expression was analyzed in Arabidopsis leaf strips that were
incubated in either 150 mM sucrose or mannitol for 5 hours. This work established the gene
expression profile in leaves and showed that the expression of ACT2, HAB1, and KAT1
were up regulated by sucrose, and RBCS was down regulated. RBCS was the most highly
expressed of all the genes assayed in leaf strips, followed by SUC1, then STP1, HAB1,
and SUC2. CYP, ADPGase, KAT1, and TPS1 were all expressed at low levels in leaf
strips. Next, small samples (approximately 10 µg) of mesophyll tissues were microdissected
from freeze-dried Arabidopsis leaf strips that had been treated with sucrose or mannitol.
RNA was isolated and analyzed by Q-PCR. The mesophyll cells gave a similar profile of
gene expression to that observed in the leaf strips. Because of inter sample variation, and
because this experiment was done in duplicate rather than triplicate, it was not possible to
document sucrose induced changes in gene expression in the mesophyll tissues. Next, the
mesophyll RNA samples were diluted 100 and 1000 fold, the RNA was amplified using T7
RNA polymerase, and transcript levels were determined by Q-PCR. The amplified RNA
samples gave gene expression profiles that were very similar to that in the unamplified RNA
from mesophyll cells. This result indicates the reliability of RNA amplification using T7
RNA polymerase. Finally, samples of guard cells were microdissected from freeze-dried
Arabidopsis leaves (50 guard cells per sample), RNA was isolated, amplified using T7 RNA
polymerase, and transcript levels were determined by Q-PCR. The gene expression profile
observed in the guard cells was quite different from what was found in leaf strips and in
mesophyll cells. In guard cells STP1 and KAT1 had the highest level of expression relative
to ACT2. TPS1, HAB1, ADPGase, and CYP were all expressed at higher levels in guard
xii
cells than in mesophyll cells. SUC2 expression was very low in guard cells, but surprisingly
RBCS transcripts levels were moderately high in the guard cell samples. To date very little
work has examined changes in gene expression in guard cells because of the difficulty of
isolating sufficient numbers of these cells. This study documents the feasibility of studying
gene expression in guard cells by manually microdissecting them out of free dried leaves and
then amplifiying the RNA with T7 RNA polymerase to give sufficient transcript levels for
Q-PCR analysis. This approach opens the possibility of studying the role of gene expression
in stomatal movements.
xiii
CHAPTER 1
INTRODUCTION
Terrestrial plants have many adaptations to control their water loss through transpiration
and evaporation. The evolution of stomata is one of the most important adaptations for
plants to control their water loss through transpiration. Stomata are small openings in the
leaf epidermis. A pair of guard cells surrounds each stoma. The change in shape of the
guard cell regulates the opening and closing of the stomata to minimize the loss of water
through transpiration and maximize carbon dioxide uptake during photosynthesis. During
stomatal opening, solute content within guard cells builds up due to the uptake of ions,
particularly K+ , and other solutes from outside of the cell. Solute content also builds up
though intercellular solute production within guard cells. As a result water is driven into
guard cells osmotically, turgor pressure within the cells increases; the guard cells swell, and
stomatal aperture increases in size. Stomatal closure is initiated with the dissipation of
these solute gradients. Growing evidence has shown that besides K+ , sucrose also plays
an important role in guard cells’ osmoregulation (Talbott and Zeiger 1998[1]). It has been
found that transpiration-linked sucrose accumulation reaches about 150 mM in the guard
cell wall (Lu et al. 1995[2], 1997[3]; Outlaw & De Vlieghere-He 2001[4]). This sucrose
accumulation causes stomatal closure (Ewert et. al. 2000[5]) and may serve to balance water
loss through transpiration and CO2 uptake during photosynthesis. Sucrose, the end product
of photosynthesis not only provides the structural and metabolic resources for plants but also
is a known regulator of gene expression in plant cells (Koch 2004[6]). It is documented that
genes of sucrose metabolism in guard cells are regulated by drought (Kopka et al 1997[7]) and
sucrose is an internal solute responsible for stomatal opening under some conditions (Outlaw
& De Vlieghere-He 2001[4]). The goal of this study is to develop experimental methods for
studying sucrose-modulated gene expression in guard cells of Arabidopsis, which can later
1
be used to test the hypothesis that sugar-induced changes in gene expression play a role of
guard cell movements.
1.1
Guard Cell Biochemistry
Stomata are small openings found primarily in the leaf and stem surfaces. Each stoma
is flanked by a pair of specialized epidermal cells, known as guard cells.
Guard cells
modulate stomatal aperture thereby controlling the rate of water loss during transpiration
and the rate of CO2 uptake during photosynthesis. In the natural environment carbon
dioxide and atmospheric humidity are potent regulators of stomata. Elevated intercellular
CO2 concentration stimulates stomatal closure whereas elevated relative humidity promotes
stomatal opening. A recent study has revealed these responses are intertwined. The elevated
relative humidity sensitizes the guard cells of Vicia faba to elevated CO2 (Talbott et al.
2003[8]). Light also plays an important role in stomatal movement. In general stomata open
in the light and close in the dark. Another important regulator of stomatal aperture size is
abscisic acid (ABA), a plant growth regulator. ABA is exported from the roots and moves
to leaves via the transpiration stream (Wilkinson & Davies 2002[9]; Dodd 2003[10]). ABA
accumulates in guard cells, which triggers the signal transduction network that is involved in
gene expression and causes stomatal closure by altering guard cell ion transport (Schroeder
et al. 2001[11]).
The molecular mechanism behind the stomatal movement involves the uptake and release
of potassium ions but sucrose uptake can play a role as well (Outlaw 1983[12]; Zeiger 1983[13];
Talbott and Zeiger 1998[1]). During opening accumulation of K+ in the guard cells results
in osmotically driven water uptake, which increases turgor pressure within the guard cells
resulting in enlargement of the guard cells; as a consequence stomatal aperture increases.
The stomatal aperture closes when the built up solute gradients are dissipated. The process
of stomatal opening starts with the activation of the guard cells’ plasma membrane ATPase.
The activated ATPase hyperpolarizes the membrane by extrusion of H+ , which results in
opening of a voltage regulated potassium (K+ ) in channel and uptake of K+ into the cell.
Chloride (Cl− ) and sucrose are also being taken up. During this process K+ antiport and Cl−
uptake into the vacuole result from H+ pumping into the vacuole. The increase in guard cell
solutes leads to water uptake and therefore an increase in guard cell volume and stomatal
2
aperture size. Stomatal closure is initiated by activation of the anion channel and inhibition
of ATPase, which results in depolarization of the plasma membrane. This effect activates a
voltage regulated K+ out channel and efflux of K+ . ABA is also involved in stomatal closure
on water stress. ABA acts through an ABA receptor on the plasma membrane. ABA binds to
its receptor and activates a signal transduction pathway resulting in an IP3-mediated release
of Ca++ into the cytoplasm. The increase in concentration of Ca++ promotes opening of
plasma membrane anion channels and a K+ out channel, and inhibits opening of K+ in
channel. As a result more ions leave the cell than enter, water follows, turgor is lost, and
the stomatal pore is closed.
The guard cell’s chloroplasts have very low activity of Rubisco and other Calvin cycle
enzymes (Wilmer and Dittrich 1974[14]; Raschke and Dittrich 1977[15]; Outlaw et al.
1979[16], 1982[17]; Reckmann et al. 1990[18]). Guard cells rely on carbohydrate import
from the apoplast because they lack significant photosynthetic CO2 fixation and functional
plasmodesmata. It has been found in guard cells of Vicia faba that there is a correlation
between transpiration and apoplastic as well as cytosolic sucrose concentration. (Lu et
al. 1995[2]). Pulse labeling of intact broad bean leaves with
showed that
14
14
CO2 (Lu et al. 1997[3])
C-labeled sucrose identified in guard cell is actually a product of the palisade
parenchyma.
Outlaw et al.
(2003[19]) have proposed a model on transpiration- linked sucrose
accumulation in the guard cell wall and how this sucrose could modulate stomatal aperture.
According to this model sucrose is synthesized in cytosol of mesophyll source cells and
moves to phloem parenchyma through plasmodesmata. Sucrose then moves apoplastically
to the companion cell/sieve tube complex where it accumulates to a high concentration.
Accumulation of sucrose drives water in to that complex and sucrose is transported out of
the leaf through this osmotically driven bulk flow. At the same time the transpiration stream
enters the leaf through tracheary elements. This transpiration streams moves through the
cell wall space and sweeps sucrose along the apoplast to the guard cell wall. Evaporation of
water from cell wall leads to accumulation of sucrose in the cell wall of the guard cell, which
drives water out of guard cell causing shrinkage of the guard cell and a reduction in stomatal
aperture.
The work of Lu et al. (1995[2], 1997[3]) provided initial support for this model by
showing that the sucrose concentration in the guard cell wall reaches 150 mM after 5 hr of
3
leaf illumination under conditions of high transpiration rate.
It is also known that starch degradation and synthesis is related to guard cell movements.
Starch degradation occurs during stomatal opening (Talbott & Zeiger 1998[1]; Outlaw
2003[19]). Degradation of starch produces phosphoenol pyruvate, which eventually forms
malate, and malate acts as a counter ion for K+ during stomatal opening.
During
stomatal closing, starch synthesis increases with increasing 3-phosphoglycerate, the product
of photosynthesis.
Because guard cells do not have significant photosynthetic activity,
the carbon and energy source for starch synthesis must come from the uptake of some
external metabolite, likely sucrose. The regulatory enzyme in starch synthesis is ADP-glucose
pyrophosphorylase, which catalyzes the step from glucose 1-phosphate to ADP-glucose, the
precursor of starch.
Sucrose, which acts as a metabolic resource in plant growth and development, can also
act as a hormone-like signaling molecule that modulates gene expression in plant cells (Koch
2004[6]). Sucrose itself can act as a signaling molecule or the breakdown products of sucrose,
that is glucose and fructose, can act as signaling molecules. This observation suggests that
the concentration of sucrose in the guard cell wall may not only act osmotically to adjust
stomatal aperture but it may also modulate stomatal aperture through changes in guard cell
gene expression.
1.2
Sucrose Transport and Metabolism in Plant Cells
Sugars are transported by the phloem from source to sink tissues, and in apoplastic phloem
loaders sucrose is the main sugar that is transported (Lalonde et al. 2003[20]). Once it
reaches the sink cells sucrose may be taken up directly or it may be cleaved prior to uptake.
Invertase and sucrose synthase (SUS), the only known sucrose cleaving enzymes in plants,
degrade sucrose in vivo.
However the products of their enzymatic activities are quite
different. Degradation of sucrose by invertase generates free glucose and fructose. SUS
on the other hand generates fructose and UDP glucose. The invertase pathway, which is
irreversible, generates twice as much hexose-based sugar signal than the signal generated
by sucrose synthase pathway. The genes that encode sucrose cleaving enzymes are feedback
regulated by their own products. They are also responsive to sugar signals. Movement of
sucrose also acts as linker between sucrose metabolism and sugar signals. Sucrose can move
to the cytoplasm of the sink cell via plasmodesmata or by crossing the plasma membrane
4
or the cell wall space. Depending upon various means of sucrose transport from source
to sink cells, sucrose can be cleaved by cell wall invertase, sucrose synthase in cytoplasm,
cytoplasmic invertase or vacuolar invertase. The plasma membrane of the sink cell can be
exposed to higher amounts of sucrose and /or hexose if plasmodesmata’s connections between
the cells are absent or become functionally limited. (Koch 1996[21]; Lalonde et al. 1999[22]).
It has been found that those cells have elevated expression of sugar transporters. Sucrose
can be transported through H+ sucrose transporter (AtSUC1, AtSUC2 in Arabidopsis) or
products from its cleavage by cell wall invertase can be taken up into the cell via different
monosaccharide transporters (Sherson et al. 2003[23]). If plasmodesmatal continuity is
present, it provides the major pathway to transport sucrose. In that case imported sucrose
has minimal effects on eliciting known signaling mechanisms (Koch 1996; Lalonde 1999[22]).
Inside the cell sucrose is mainly degraded by sucrose synthase, because cytoplasmic invertases
are minimally present in most of the tissues (Winter & Huber 2000[24]).
Vacuolar invertase also generates abundant hexoses and hexose based sugar signaling
(Sturm 1999[25]; Koch and Zeng 2002[26]; Sonnewald et al. 1991[27]). Sucrose can be
transported into the vacuole via H+ sucrose transporter or bi-directional uniporters. Cellular
enzymes metabolize the imported sucrose, and products from its breakdown are used as
metabolic fuel for sink tissues.
Triose phosphate, the primary product of photosynthesis, is converted into ADP glucose
by ADP glucose pyrophosphorylase.
ADP glucose is the precursor of starch that is
stored in the chloroplast. Triose phosphate can be exported from the chloroplast to the
cytosol via bi-directional phosphate translocator, where it equilibrates with fructose-1-6
bisphosphate. In the cytosol fructose-1-6 bisphosphate is dephosphorylated to fructose-6phosphate and fructose-6-phosphate combines with UDP- glucose to make sucrose. This
latter step is catalyzed by sucrose phosphate synthase (SPS). The plastid membrane is not
permeable to sucrose but is permeable to triose phosphate (chloroplast) or hexose phosphate
(amyloplast), both of which are used in the synthesis of ADP-glucose, the presursor of
starch. Interconversion between fructose-1-6 bisphosphate and fructose-6-phosphate are
highly regulated and very critical. Conversion of fructose-1-6 bisphosphate to fructose-6phosphate starts sucrose synthesis whereas the reverse reaction starts glycolysis where triose
phosphate acts as precursor.
Because they are low in Rubisco and the Calvin cycle enzymes, guard cells must import
5
their energy and carbon from surrounding cells, and they appear to import it in the form of
sucrose. There are no plasmodesmata between guard cells and their neighbors; therefore the
guard cells must obtain their carbon and energy from compounds present in the apoplast.
Outlaw et al. have shown that high levels of sucrose can occur in the guard cell apoplast
but that glucose is low or absent (Lu et al.1995[2]; Outlaw, personal communication), Cell
wall invertase also appears to be absent in guard cells (Outlaw; personal communication).
Sucrose is imported into the guard cell via H+ cotransporters (Ritte et al. 1999[28]),
and is important for formation of starch and other metabolites. Starch degrades during the
stomatal opening. It is degraded into phosphoenol pyruvate and eventually into malate, a
counter ion for accumulated K+ . (Wilmer and Dittrich 1974[14]; Outlaw and Manchester
1979[29]; Schnabl et al. 1982[30]; Tarczynski and Outlaw 1990[31]). Guard cell starch
increases during stomatal closure via allosteric regulation of ADP-Glc pyrophosphorylase
(ADPGase) (Outlaw and Tarczynski 1984[32]) but may also involve gene expression. Cycling
between sucrose synthesis and degradation is mediated by SUS and SPS.
1.3
Sugar Sensing by Plants
Sugars, which are often thought of exclusively as metabolic and structural resources in
plants, are now also known as potent signaling molecules that regulate gene expression
during growth, development and other physiological processes. By analyzing a limited set
of genes it has been found that significant numbers of plant genes are regulated by sugars
at the steady state mRNA level. Many studies have suggested the existence of hexokinasedependent, hexokinase independent and sucrose specific signaling pathways. (Rook et al.
2003[33]; Smeekens 2000[34]; Pego et al. 2000[35]; Koch 1996[21]; Rolland et al. 2002[36]).
More recently by using the Affymetrix Arabidopsis gene chip it has been found that many
genes involved in carbon metabolism are sugar regulated (Price et al. 2004[37]; Thum et
al. 2004[38]). Several lines of studies indicate that many genes are regulated by interactions
between light and sugar signaling (Thum et al. 2004[38]). Those genes belong to the group
of genes involved mainly in metabolism.
In the transition from stomatal opening to closure, guard cell metabolism must switch
from starch degradation and malate synthesis to starch synthesis. Expression of the genes
for many of the key enzymes in these processes have been shown to be affected by sucrose or
glucose. Thus, it is reasonable to suppose that extracellular sucrose or intracellular sucrose
6
or glucose may be important intracellular signaling molecules during stomatal movements.
1.4
The Research Goals of this Study
Sugars imported into and surrounding guard cells have three important roles to play. They
can act osmotically to control stomatal aperture. They can act as a carbon source for the
synthesis of starch and other metabolites and they can act as signaling molecules and regulate
gene expression in the guard cells. The goal of this study is to develop a set of experimental
methods with which sucrose modulated gene expression can be studied in guard cells of
Arabidopsis. It is hoped that this system can subsequently be used to test the hypothesis
that sucrose induced changes in gene expression play a role in stomatal movements. The
overall approach will be to look at the effects of externally applied sucrose and mannitol, on
the expression of a panel of genes in guard cells and mesophyll cells of Arabidopsis.
Many important studies of guard cell biology and biochemistry have been done using the
plant Vicia faba. However, Arabidopsis, the most studied plant model system, is ideal for
studies of gene expression because the Arabidopsis genome has been sequenced and its protein
coding genes identified, and because a wide array of genetic tools are available including gene
knockout mutants and commercially available microarrays. There are difficulties however, in
working with Arabidopsis guard cells. Compared to Vicia faba, the guard cells of Arabidopsis
are small and its leaves are covered with trichomes, which make it impossible to harvest
guard cells using epidermal peels. Nonetheless, the huge pool of genetical and molecular
information and resources available for Arabidopsis makes this plant preferable to work with
over Vicia if the technical difficulties of analyzing gene expression in Arabidopsis guard cells
can be overcome.
Two different approaches have been used to isolate sufficiently large samples of guard
cells to permit studies of gene expression, epidermal peeling and protoplasting. In some
plants, including Vicia faba, peeling the leaf epidermis with fine forceps can used to harvest
large numbers of living guard cells, free of contamination with epidermal cells or mesophyll
cells (Poffenroth et al. 1992[39]), and these guard cell preparations have been used in
studies of gene expression (Aghoram et al. 2000[40]). However, the presence of trichomes
makes peeling the epidermis of Arabidopsis leaves extremely difficult. Another approach for
isolation of large numbers of guard cells has been to use cellulytic enzymes to convert cells
of the leaf to protoplasts. Because the guard cells have much thicker walls than mesophyll
7
cells, the mesophyll protoplasts are released first during protoplasting and can be discarded;
the guard cells are released later and can be purified. Leonhardt et al. (2004[41]) used this
approach to study gene expression in Arabidopsis guard cells. A problem with protoplasting
is that the prolonged enzyme treatment needed to digest away the cell wall can itself result
in major changes in gene expression (Fleck et al.1982[42], Takahashi et al.1989[43]). To
overcome this difficulty Leonhardt et al. [41] included RNA synthesis inhibitors in their
protoplasting medium. However, the concern remains that gene expression may be altered
by the protoplasting treatment. Also, guard cell protoplast preparations can be contaminated
with other leaf cells (epidermal cells, cells from the leaf veins, as well as mesophyll cells.).
Because of these concerns protoplasting was not used in this study.
The objective of this study was to analyze the gene expression profile of guard cells
that had been microdissected from freeze-dried leaves of Arabidopsis. mRNA isolation and
measurement from small clumps of tissue and even from single cells has been reported for
plants (Brandt et al. 1999[44]; 2002[45]; Laval et al. 2002[46], Kerk et al. 2003[47]). Lasercapture microdissection of individual cells and subsequent mRNA analysis has also been
reported for plants (Kerk et al. 2003[47]). However, manual microdissection of individual
guard cells from freeze-dried leaves was chosen for this study because this technology has
already been perfected in the Outlaw laboratory, and because of concerns about potential
damage to RNA during the chemical fixation and embedding steps needed for laser-capture
microdissection and the heat generated by the laser when cutting out individual cells and
tacking them on a thermoplastic film. Once RNA has been isolated from a tiny tissue sample
the RNA has to be amplified if the expression of multiple genes is going to be analyzed.
RNA amplification is generally done converting mRNA into cDNA using an oligo-dT primer
containing a T7 RNA polymerase binding site, and then using T7 RNA polymerase-driven
transcription to make many antisense RNA (aRNA) copies of the original mRNAs. The
aRNAs can then be quantified by quantitative real-time PCR (Q-PCR). RNA amplification
using T7 RNA polymerase has been shown to be linear, have little bias for different mRNAs,
and can give amplifications of 1000 fold or more (Polacek et al. 2003[48]; Zhao, et al.,
2002[49]). Thus the overall objective of this study was to examine the feasibility of analyzing
gene expression in T7 RNA polymerase-amplified RNA from small samples of guard cells
that had been manually microdissected from freeze-dried Arabidopsis leaves. Prior to freeze
drying the leaves were treated with 150 mM sucrose or mannitol (as an osmotic control) so
8
that the effect of sucrose on gene expression could also be assessed. Because the combination
of techniques planned for this project had not been attempted before a stepwise approach was
planned. First gene expression was examined in leaf strips and in small clumps of mesophyll
tissue. Then, in a series of experiments, mesophyll RNA was diluted and amplified and
gene expression was examined. Finally, RNA was isolated from small samples of guard cells,
amplified and analyzed by Q-PCR.
1.5
Specific Experimental Goals of this Thesis
1. Analysis of gene expression in Arabidopsis leaf strips that had been treated with sucrose
or mannitol. The purpose of this first experiment is to work out the necessary QPCR methods and get baseline data on gene expression in leaves for evaluation of the
effectiveness of RNA isolation and amplification from small clumps of tissues or isolated
cells in subsequent experiments. This experiment will also provide data on the effects
of sucrose on the expression of a panel of genes in leaf tissue. The panel included genes
that were preferentially expressed in mesophyll cells, genes preferentially expressed in
guard cells, and some control genes.
2. Analysis of gene expression in small samples (approximately 10 µg) of mesophyll tissue
from freeze-dried Arabidopsis leaves. This experiment will determine whether we will
be able to analyze gene expression in RNA extracted from freeze-dried Arabidopsis
tissues.
3. Analysis of gene expression in samples of mesophyll RNA that had been diluted
and then amplified using T7 RNA polymerase. This experiment was designed to
determine whether RNA amplification followed by Q-PCR is sensitive enough to permit
quantification of transcripts in samples as small as 50 cells. The experiment also
provides data on the uniformity of T7 RNA polymerase amplification of different
transcripts.
4. Analysis of gene expression in samples of 40-50 individually isolated guard cells that
had been microdissected by hand from freeze-dried leaf strips of Arabidopsis. This
experiment was designed to demonstrate the feasibility of our unique approach and
9
to provide preliminary data on whether sucrose induced changes in gene expression in
guard cells may have a role in stomatal movement.
1.6
Candidate Genes for this Study and the Rational
for their Selection
1.6.1
Sucrose Transporters
Expression of sucrose transporters in guard cells would provide circumstantial evidence that
sucrose is taken up from the apoplast. Since apoplastic sucrose levels can vary diurnally it is
possible that expression of these genes in guard cells is regulated by sucrose. Nine members
of the sucrose-H+ symporter gene family have been identified in Arabidopsis: expression of
SUC1 and SUC2 will be examined in this study.
SUC2 is the major sucrose transporter essential for phloem loading and long distance
transport. The SUC2 gene is highly expressed in leaves and its expression has been reported
to be confined to companion cells of phloem in both source and sink tissues (Truernit and
Saucer 1995[50]; Stadler and Saucer 1996[51]). Expression of the SUC2 gene was found to
be enhanced by two fold in Arabidopsis leaf strips floated on 150 mM sucrose (Bates and
Outlaw, unpublished microarray data). The Arabidopsis pho3 mutation is due to a defect
in the SUC2 gene (Lloyd and Zakhleniuk 2004[52]). The pho3 mutant has greatly reduced
growth and accumulates high levels of sugars and starch (Zakhleniuk et al. 2001[53]). Lloyd
and Zahkleniuk (2004)[52] used microarrays to compare gene expression in leaves of wild type
and pho3 Arabidopsis plants as a way to examine the effects of altered sugar metabolism on
global gene expression.
SUC1. Though the expression of this gene has been reported to be specific to flowers
(Stadler et al. 1999[54]), microarray analysis of Arabidopsis pho3 mutant showed that SUC1
is expressed in leaves and its expression was similar in both wild type and pho3 leaves (Lloyd
et al. 2004[52]). This view is supported by the microarray analysis done by Bates and Outlaw
(unpublished data); SUC1 transcript levels were abundant in Arabidopsis leaves and were
unchanged by treatment with sucrose.
The other members of the sucrose transporter gene family did not give a detectable level
of transcripts in the microarray analysis of pho3 mutant. (Lloyd et al. 2004[52]). Therefore
these genes are excluded from this study, although at this point it cannot be ruled out that
10
one of them is preferentially expressed in guard cells
1.6.2
The Hexose Transporter STP1
This gene encodes a H+ -monosaccharide symporter and is preferentially expressed in guard
cells (Stadler et al. 2003[55]). Therefore this gene makes a good marker for guard cells.
Expression of this gene suggests that guard cells may be taking up glucose or fructose, which
could be the product of the action of cell wall invertase on sucrose. It is possible that
expression of this gene would be enhanced by sugars.
1.6.3
Genes Involved in Starch Synthesis
ADP-glucose pyrophosphorylase (ADPGase): This enzyme catalyses a regulatory step in
starch biosynthesis. It has two subunits, referred to as the small and large subunit. One of
the large subunit genes, the AtAPL4 gene, has been reported to be expressed preferentially
in guard cells (Leonhardt et al 2004[41]), which makes this gene another good guard cell
marker.
Lloyd et al.
(2004)[52] reported a large (7-20 fold) increase in expression of
two ADPGase large subunit genes (AtAPL3 and AtAPL4) in leaves of the Arabidopsis
pho3 mutant compared with wild type leaves. This observation suggests that expression of
these genes is coupled to sugar metabolism. A two-fold increase in expression of ADPGase
was observed in leaves of Arabidopsis floated on sucrose (Bates and Outlaw, unpublished
microarray data). The expression of the AtAPL4 gene will be examined to determine whether
expression of this gene in guard cells is modulated by sucrose.
Trehalose 6- phosphate synthase (TPS1): This enzyme catalyzes the formation of T6P
from glucose- 6-phospahte and UDP-glucose. T6P is converted to trehalose by trehalose
phosphate phosphatase (TPP) and trehalose is cleaved to glucose by the enzyme trehalase
(Wingler 2002[56]). Several studies have shown that T6P, plays a role in regulation of sugar
utilization in eukaryotes ranging from yeast to plants. Overall 11 TPS-like genes, which
catalyze the formation of T6P, have been found in Arabidopsis. One of them (TPS1) has
been shown to code for a functional TPS (Blazquez et al.1998[57]; Leyman et al. 2001[58]).
Disruption of TPS1 in Arabidopsis leads to arrest in embryo development early in the phase
of cell expansion and storage reserve deposition. (Eastmond et al. 2002[59]). Transgenic
Arabidopsis plants that over express T-6-P synthase have elevated levels of T6P, elevated
ADPGase activity, and increased starch synthesis in leaves compared to wild type (Kolbe
11
et al. 2005[60]). TPS1 has been found to be preferentially expressed in guard cells and is
also induced by ABA (Leonhardt et al 2004[41]). The TPS1 gene also has been found to be
repressed by glucose in Arabidopsis leaves (Price et al. 2004[37]). Therefore, TPS1 is a good
candidate gene for the present study.
1.6.4
Genes Directly Involved in Stomatal Movements
The potassium channel protein KAT1 is an inward K+ channel; and contributes to K+
uptake during stomatal opening. The KAT1 gene is preferentially expressed in guard cells
and is down regulated by ABA (Leonhardt et al. 2004[41]). Price et al. (2004)[37] found
that expression of this gene in leaves was enhanced four fold by glucose. Because the KAT1
protein is a key player in guard cell opening and closing it is of interest to determine whether
its expression is modulated in guard cells by sucrose.
1.6.5
Genes Involved in Carbon Fixation
Rubisco (ribulose-1, 5-bisphosphate carboxylase) catalyses CO2 fixation during photosynthesis. This protein consists of a heteromultimeric complex, composed of large and small
subunits. The large subunit gene is encoded in the chloroplast and the small subunit gene
(RBCS) is nuclear encoded. Expression of one of the small subunit gene family members was
slightly down regulated or unchanged in pho3 mutant (Lloyd et al. 2004[52]). Many studies
have shown that long term (5 to 24 hours or longer) treatment of leaves or plants with sugars
results in significant down regulation of expression of the RBCS small subunit gene (Krapp et
al.1993[61]). Guard cells have extremely low levels of rubisco activity (Wilmer and Dittrich
1974[14]; Raschke and Dittrich 1977[15]; Outlaw et al. 1979[16], 1982[17]; Reckmann et al.
1990[18]) compared with mesophyll cells. Expression of the RBCS gene will be examined
in this study because its expression is expected to be abundant in mesophyll cells and is
likely to be reduced in guard cells. Thus, RBCS expression could serve as a marker gene for
mesophyll cells.
1.6.6
Genes in the ABA Signal Transduction Pathway
The protein phosphatase 2C (PP2C) gene family member, ATP2C-HA (HAB1), is preferentially expressed in guard cells and is upregulated in presence of ABA (Leonhardt et
12
al. 2004[41]). Mutations in this gene lead to hypersensitivity to ABA and induce stomatal
closure (Leonhardt et al. 2004[41]). This gene is also known as ABI1. Microarray analysis by
Bates and Outlaw (unpublished) showed two fold repression of this gene by sucrose treatment
of Arabidopsis leaves. It is now well documented that hexokinase-mediated glucose signaling
is connected to ABA signaling. Glucose has been shown to modulate expression of genes
involved in ABA signaling (Price et al. 2004[37]; Arroyo et al. 2003[62]) and some of
the ABA deficient mutants and ABA insensitive mutants are allelic to glucose insensitive
mutants (Arenas-Huertero et al. 2000[63]; Huijser et al. 2000[64]; Laby et al. 2000[65]).
The expression of the AtP2C-HA gene will be investigated because this gene is preferentially
expressed in guard cells and is likely to be responsive to sucrose.
1.6.7
Endogenous Control Genes
Actin-2 (At5g09810) will be used in this study as an endogenous control. The expression of
this gene has been found to be unaffected by ABA treatment in guard cells and in mesophyll
cells (Leonhardt et al. 2004[41]). This gene has also been found to be unaffected by
glucose treatment in seedlings of Arabidopsis (Price et al. 2004[37]). This gene will be
used as an endogenous control to normalize the expression of other genes in this study.
Cyclophilin (AtCyp18-1) and EF1 (At5g60390) were also included in this study as potential
reference genes. Cyclophilin (Atcyp18-1) has been identified to be expressed in all tissues
of Arabidopsis (Romano et al. 2004[66]) and used as a control gene in number of studies.
EF1 has also been found to be used as a housekeeping control gene in studies with potato
during biotic and abiotic stress and in tomato plant using EST data (Nicot et al. 2005[67]
and Coker et al. 2003[68])
13
CHAPTER 2
MATERIALS AND METHODS
2.1
Plant Material
Plants of Arabidopsis thaliana, ecotype Columbia, were grown in a plant growth chamber, at
20◦ C, 60% relative humidity, with an 8 h light/16 h dark photoperiod (250 µ E m−2 sec−2 ).
Leaves were collected from vegetative plants approximately 7-10 weeks old were used in the
experiments in this thesis. Under the growth conditions used here the plants begin to flower
after 11-12 weeks.
2.2
Measurement of Stomatal Aperture Size
Green, unblemished leaves were chosen form the top of the plants’ rosettes. Epidermal
strips were peeled from the lower epidermis and cleaned up with a wet artist’s brush to
remove any mesophyll cells associated with it. Then sections of the peel were observed with
a microscope and an area was selected where abundant numbers of stomata were visible.
Stomatal opening and closing was recorded every 2 h beginning at the start of the light
period (8:30 a.m.) and continuing until the end of the light period (4:30 p.m.). For each
time point three observations of ten stomata, total of thirty stomata, were observed and
their aperture sizes were measured using an ocular micrometer.
2.3
Preparation of Leaf Strips and Sugar Treatments
100 mg of leaves (approximately 4-6 leaves) were cut lengthwise using a scalpel and the
midvein was removed. The tip and the base (approximately 10% of the leaf length at each
end) were removed and discarded. The remaining leaf halves were cut (transverse direction)
into small strips 1-2 mm in thickness. The leaf strips then were vacuum infiltrated with
14
a solution of 150 mM sucrose + 50 mM KCl +10 mM MES, 0.1 mM CaCl2 , pH 6.1, and
incubated for 5 h in 12.5 ml of this solution in a 125 ml Erlenmeyer flask at 20◦ C (100
µ E m−2 sec−2 illumination) on a rotary shaker. In control samples 150 mM mannitol was
substituted for sucrose. After the 5 h incubation the leaf strips were blotted to remove excess
liquid and either ground by mortar and pestle in liquid nitrogen for large scale RNA isolation
or quickly freeze-dry for micro scale RNA isolation. Freeze-drying and micro dissection of
the tissues were done by following the protocol established in Dr. Outlaw’s laboratory.
2.4
Large Scale RNA Isolation
Total RNA was isolated from leaf strips with Trizol reagent (Invitrogen Corp., Carlsbad, CA,
catalog number 15596-026) following the manufacturer’s instructions. The concentration of
the isolated RNA was determined spectrophotometrically and samples with 260/280 values
of 1.8-2 were kept for further analysis. An OD value of 1.8 or higher indicates pure RNA.
In some experiments large scale RNA isolation was performed with the PicoPure RNA
Isolation Kit (Arcturus Bioscience Inc., Mountain View, CA). This kit was used following
the manufacturer’s directions but with the slight modification that 100 µL of extraction
buffer (instead of 10 µL) was added to the leaf tissue after grinding and samples were
centrifuged at highest speed (14,000g) for 2 minutes. Then 100 µL 70% EtOH was added
to the collected supernatant and loaded to preconditioned purification column treated with
conditioning buffer. After a brief centrifugation and washing of the column with the wash
buffers recommended by the manufacturer, RNA was eluted from the column with 30 µL of
elution buffer. Samples with OD260 1.8-2 were kept for further analysis.
2.5
Micro Scale RNA Isolation
RNA was isolated from microdissected mesophyll and guard cells with the PicoPure RNA
Isolation Kit (Arcturus Corp.) following the manufacture’s instructions. Approximately 10
to 15 micrograms of mesophyll cells, or 50 guard cells, were cut out of freeze-dried leaf strips.
During cutting some of the cells were deliberately nicked to facilitate release of RNA. The
cell samples were collected in a small plastic boat and 10 µL of extraction buffer was added
to the sample. After a quick pipetting up and down, the sample was loaded into 0.2 ml
centrifuge tubes and incubated at 42◦ C for 30 min. After centrifugation (14,000 g, 2 min),
15
the supernatant was collected, 10 µL of 70% EtOH was added to it, and the mixture was
loaded into a preconditioned purification column. After binding of the RNA to the column
(100 ×g, 1 min), the column was washed and treated with DNase and the RNA was eluted
from the column with 20 µL of elution buffer.
2.6
Reverse Transcription
For the large-scale RNA isolations one microgram of total RNA was used for reverse
transcription. For the micro-scale RNA isolations the RNA concentration was too low to be
determined spectrophotometircally, therefore we simply used 8µL (out of a total of 20 µL
in each sample) for reverse transcription. First strand cDNA synthesis was performed using
Invitrogen’s Superscript II following the manufacturer’s instructions. In most experiments
the primer used for first strand synthesis was anchored oligo-dt (0.5 µg. µL−1 ) (Integrated
DNA Technologies Corp., Coralville IA). In experiments where RNA had been amplified
using T7 RNA polymerase the RNA was diluted (10 or 100 fold in case of microdissected
mesophyll cells, and 3 fold in case of microdissected guard cells) with water and 8 µL
of diluted RNA was reverse transcribed into cDNA using gene-specific primers (2 µM).
After reverse transcription E.coli RNase H (2 U µL−1 ) was added to digest the RNA from
RNA:cDNA hybrids.
2.7
Design of Gene-specific Primers
Gene specific primers were designed using Wisconsin GCG software. Primers were designed
to be within 600 bases of the 3′ end (except for TPS1 where they were within about 1800
bases) and the expected PCR products were no longer than 150 base pair long (exception
SUC2 is 219bp long).
Primer specificity was verified by blast search, by using them in standard PCR reactions
with cDNA prepared from total leaf RNA (any primer pairs that gave more than one PCR
product were redesigned), and by DNA sequencing of some of our selected genes.
16
2.8
Primers of our Selected Genes
Gene
ACT2, At5g09810,
Primers
(forward primer, 5′ -ATCCCTCAGCACCTTCCAAC-3′ ;
reverse primer, 5′ -ACAAACTCACCACCACGAAC-3′ )
CYP, AtCYP18-1,
(forward primer, 5′ -CCATCTTTGGCAAAGTCATTC-3′ ;
reverse primer, 5′ -CACACGGTTTAGCCTTATCTC-3′ )
EF1, At5g60390,
(forward primer, 5′ -GTCATCATCATGAACCACCC-3′ ;
reverse primer, 5′ -ATCTCCTTACCAGAACGCC-3′ )
SUC2, At1g22710,
(forward primer,5′ -AGCCATTACGTTTAGCATTCC-3′ ;
reverse primer, 5′ -CGCCAATACACCACTTACC-3′ )
SUC1, At1g71880,
(forward primer, 5′ -CATCCATATTCTCAAGCTGCTC-3′ ;
reverse primer, 5′ -GCTAATACTCCACTAATCGCC-3′ )
STP1, At1g11260,
(forward primer, 5′ -CCTTGTTTTCGCCTTTTTCG -3′ ;
reverse primer, 5′ -TTCCCATACTCACCATCCTC -3′ )
ADPGase, At2g21590, (forward primer, 5′ -ATTGGTGAACGATCACGTC-3′ ;
reverse primer, 5′ -ATTGGAACCTTTCCTTCTGC -3′ )
TPS1, At1g78580,
(forward primer, 5′ -TGACCTCAAAGGAGAGAACTAC-3′ ;
reverse primer, 5′ -TTCTCAAGGAAGCAAACGAC-3′ )
RBCS, small subunit, (forward primer, 5′ -ACTCACCCGGATACTATGATG-3′ ;
At1g67090
reverse primer, 5′ -CACTCTTCCACTTCCTTCAAC-3′ )
KAT1, At5g46240,
(forward primer, 5′ -AGCAACCAAATCATCAAGCC-3′ ;
reverse primer, 5′ -CAGCCTCCAAACTTCTCAC-3′ )
HAB1, At1g72770,
(forward primer, 5′ -GAAATAGCAAGGAGACGG-3′ ;
reverse primer, 5′ -GTAGAGCAAGCATTGAGAGG-3′ )
2.9
Standard PCR Reactions and Purification of
PCR Products
Standard PCR was performed with 2 µL of cDNA, 45 µL of platinum PCR Supermix
(Invitrogen) and with 15 µM of forward and reverse primers of our selected genes in 50 µL
PCR reactions for 30 cycles. The PCR cycle program was as follows: 1 cycle of 2 min at
94◦ C, 30 cycles of 30 s at 94◦ C, 45 s annealing at 48◦ C, 60 s at 72◦ C, followed by 1 cycle
of 7 min at 72◦ C for final extension. To check our primers’ specificity, 20% of each PCR
product was run on a 1.5% agarose gel with 1X TAE and 0.5 µg/µL−1 EtBr. To make DNA
standards for each of our selected genes the PCR products were purified using Qiagen’s
QIAquick PCR Purification Kit (Qiagen Inc., Valencia, CA).
17
2.10
Quantitative Real-time PCR and Data Analysis
Real time PCR was performed in ABI 7500 Real Time Thermal Cycler (Applied Biosystems,
Foster City, CA) using quantiTech SYBR green (Qiagen Inc) according to the manufacture’s
instructions with 1X master mix, 0.3µ M forward and reverse primers (final concentration)
in a twenty five µL master mix reaction. Two µL of cDNA was added to the master mix
for reactions of unknowns. For standards, cDNA was replaced with 10 µL of standards.
All pipetting steps for standards and unknowns were carried out separately in two different
places designated as a post PCR area and pre PCR area. Control for no template (NTC)
were run for each master mix but not for every single gene.
The real time PCR reactions were incubated at 95◦ C for 15 min to activate hot star Taq
DNA polymerase, followed by 40 cycles of 15 s at 94◦ C for denaturation of DNA, 45 s at
48◦ C to anneal the primers, and 60 s at 72◦ C for extension. Data collection was done in
the extension step. The specificity of the PCR amplification was checked with melting curve
analysis (from 65◦ C to 95◦ C) following the final cycle of the PCR. Baseline and threshold
for Ct calculation were set automatically by machine or manually when needed.
Data was analyzed with ABI 7500 Thermal Cycler following Applied Biosystems’ instructions. To quantify the amount of template, an absolute standard curve method was
followed. In this method a standard curve was first constructed from a cDNA of known
concentration, and then this curve was used as a reference standard for extrapolating
quantitative information for mRNA targets of unknown concentrations. Standard curves
were constructed with purified PCR products generated from standard PCR of cDNAs using
primer pairs for each of our selected genes. PCR products were purified with Qiagen’s
PCR clean up kit.
Quantification of purified PCR products was then determined by
spectrophotometry and a 10 fold dilution series of known amount in grams was used in
real time PCR to generate the Ct values. Ct values were then plotted against log of their
respective numbers of cDNA dilution series in excel to generate the standard curve. Overall
efficiencies of PCR were calculated from the slope of the standard curve according to the
formula E = 10(−1/slope) − 1 for serial dilution in steps of 10 [log (10) scale]. E=100% reflects
a doubling of DNA in each PCR cycle. Errors are given as standard deviation of means.
Significant was defined according to P -value from two tailed t-test analysis. F test was
performed prior to t-test to test equal variance. In one experiment nested anova model with
18
two factors was used to analyze the data.
2.11
Generating the Absolute Standard Curves
The standard curve for ACT2 was derived by taking the averages of Ct values from two
experiments and plotted against the respective serial dilution of PCR products from a range
of 10−2 ng to 10−6 ng in excel. The calculated slope of the standard curve was −3.5275
which reflects the overall efficiency of 90.22%. The same approach was taken for the genes
SUC2 and CYP. Where averages of Ct values from two experiments were taken and plotted
against their respective dilution factor from a range of 10−3 to 10−7 in excel. The slope of
the standard curve for SUC2 and CYP were −3.3988 and −3.5275 with overall efficiencies
of 96.89% and 92.08% respectively. For HAB1, RBCS, SUC1 and ADPGase, Ct values were
plotted against serial dilution from a range of 10−2 to 10−6 . Calculated slopes were −3.503
with 92.96% efficiency for HAB1, −3.827 with 82.52% efficiency for RBCS, −3.467 with
95.01% efficiency for SUC1 and −3.431 with efficiency 94.65% for ADPGase. Ct values were
plotted against serial dilution series from range of 10−3 to 10−7 for KAT1, TPS1, STP1 and
EF1. The calculated slopes for these four genes were −3.738, −3.265, −3.32 and −3.33
respectively with 99.75% efficiency for TPS1 and 85.15% for KAT1. For STP1 and EF1
the efficiency was 100% which indicates perfect doubling of amplification products per cycle
during exponential phase of PCR. The strong linear relationship between fractional copy
number and log of the starting copy number with the correlation coefficient of r2 > .99 was
observed for all of our selected genes except KAT1 which has r2 > .97.
2.12
RNA Amplification
RNA extracted from microdissected mesophyll cells and guard cells was amplified using
R
HS RNA Amplification Kit (Arcturus Bioscience Inc., Mountain View,
Arcturus’ RiboAmp
CA), which utilizes T7 RNA polymerase for amplification.
The manufacture’s protocol was followed exactly for “round one” amplifications with the
exception that primer 3 was used instead of primer 1 during first strand cDNA synthesis.
To be used in amplification, isolated RNA from micro dissected mesophyll cells was diluted
10 fold or 100 fold with the RNase free DEPC water. For the “round one” amplification,
10 µL of diluted RNA was taken and after first strand and second strand synthesis of cDNA
19
followed by in vitro transcription using T7 RNA polymerase 12 µL of antisense RNA was
recovered at the end.
For amplification from RNA extracted from microdissected guard cells, 10 µL of extracted
R
HS RNA
RNA was put through two rounds of amplification using Arcturus’ RiboAmp
amplification kit following the manufacturer’s instructions.
20
CHAPTER 3
RESULTS
3.1
Diurnal Changes in Stomatal Movement
The diurnal changes of stomatal aperture size in the plants used in this study are shown in
Figure 3.1. Guard cell opening began in the late morning, reached a peak in midafternoon
and closed by the end of the light period. These data indicate that the plants used here
were actively regulating stomatal aperature size. In Vicia apoplastic sucrose concentration
reaches its maximum when the stomates are fully opened (Outlaw WH Jr, De Vlieghere-He
Figure 3.1: The diurnal changes in stomatal aperture size: The averages of 30 stomatal pores
were measured every 2 hours beginning when the lights in the incubator came on (8:30 am)
and ending when the lights went off (4:30 pm), n=30.
21
(2001)[4]). If the same is true in Arabidopsis, then apoplastic sucrose concentration would
reach its highest level about 4 to 5 hours into the light period. This correlates well with the
length of the sugar treatment used in these experiments.
3.2
Quantification of Transcripts in RNA Isolated
from Leaf Strips of Arabidopsis Treated with
Sucrose or Mannitol and the Problem of
Variability between Biological Replicate Samples.
In initial experiments 100 mg samples of leaf strips were incubated for 5 h in 0.5 M mannitol
or sucrose, and total RNA was isolated and analyzed by Q-PCR. RNA was isolated from
three biological replicate samples for each treatment (S1, S2 and S3 for sucrose-treated leaf
strips and M1, M2 and M3 for ones treated with mannitol). For Q-PCR 1 µg of total RNA
was taken from each sample, reverse transcribed into cDNA, and aliquots of the cDNAs
were used for Q-PCR. In the very earliest experiments we noted that there was typically 2
or 3 fold variation between biological replicates in the amount of transcript detected for each
gene, and sometimes variations of 5 to 10 fold or larger were encountered. An example of
the data is shown in Table 3.1. Panel A shows Q-PCR results for each gene in each sample.
ACT2 gave the highest level of expression in the samples from sucrose-treated leaves and
RBCS expression was highest in mannitol-treated leaves, TPS1 expression was the lowest
of all the genes in both treatments. After averaging the expression data it was observed
that ACT2 and KAT1 were higher in sucrose than mannitol, and STP1, RBCS, and TPS1
expression were higher in mannitol than sucrose. However, none of these differences were
statistically significant because of the sometimes large variations between replicate samples
(ranging from a low of 1.6 fold for TPS1 from sucrose-treated leaves to a high of 152 fold for
STP1 from mannitol-treated leaves).
The variability of expression could be due to differences in the RNA samples, or to
differences in the reproducibility of the cDNA or Q-PCR reactions. To control for differences
between the samples the data for each gene in a given RNA sample was normalized relative
to the expression of ACT2 in that sample. The normalized data are shown in panel B of
Table 3.1. Normalization reduced the fold differences between the replicate samples but some
large variations remained (for example STP1 in the mannitol samples). The effects of sugar
treatment observed in the normalized data were similar to those in the raw data; KAT1
22
Table 3.1: The effect of sucrose and mannitol treatment on RBCS, KAT1, TPS1, STP1
and ACT2 in leaf strips. Panel A shows the raw Q-PCR data of three biological replicate
samples (S1, S2 and S3 for sucrose and M1, M2 and M3 for mannitol) assayed for KAT1,
RBCS, STP1, TPS1 and ACT2. Panel B shows the values of each gene after normalization
to the expression of ACT2. The absolute and normalized quantities are in nanograms of
transcripts per 100 ng of total RNA used in a cDNA reaction. Inter sample variation for
each gene is shown by the fold difference between replicates (by taking the ratio of highest
to lowest values of replicates) and also by the standard deviation value. The expression of
genes in response to sucrose is shown by the ratio of transcripts in sucrose and mannitol.
P -values were calculated using the t-test with significance level of α=0.05.
A. Raw Data
Gene
ACT2
KAT1
STP1
RBCS
TPS1
ACT2
KAT1
STP1
RBCS
TPS1
S1
2.4E-04
4.4E-06
7.4E-06
2.4E-04
8.9E-08
M1
3.5E-04
5.6E-06
2.5E-04
2.6E-03
2.9E-06
Sample
S2
2.0E-04
1.1E-06
2.6E-06
9.7E-05
2.5E-07
M2
6.2E-05
2.0E-07
1.7E-06
4.2E-04
1.3E-07
Fold
Diff
Ratio
btw
Suc/ P -value
Repl Average
SD Man (T -test)
2.4 3.1E-04 1.6E-04
1.9
0.327
8.9 5.1E-06 4.4E-06
2.5
0.382
5.5 8.0E-06 5.8E-06
0.1
0.440
3.8 2.3E-04 1.3E-04
0.2
0.232
1.6 2.5E-07 1.6E-07
0.2
0.394
S3
4.9E-04
9.9E-06
1.4E-05
3.6E-04
4.1E-07
M3
9.3E-05
5.6
4.5E-07 27.4
7.1E-06 151.9
9.9E-04
6.2
5.2E-07 22.5
1.7E-04
2.1E-06
8.8E-05
1.3E-03
1.2E-06
1.6E-04
3.0E-06
1.4E-04
1.1E-03
1.5E-06
B. Data Normalized to ACT2 in each Sample
Gene
KAT1
STP1
RBCS
TPS1
KAT1
STP1
RBCS
TPS1
S1
9.1E-06
1.5E-05
4.9E-04
1.9E-07
M1
5.6E-06
2.5E-04
2.6E-03
2.9E-06
Sample
S2
2.7E-06
6.2E-06
2.3E-04
6.1E-07
M2
1.1E-06
9.3E-06
2.3E-03
7.3E-07
S3
9.9E-06
1.4E-05
3.6E-04
4.1E-07
M3
1.7E-06
2.7E-05
3.7E-03
2.0E-06
Fold Diff
Ratio P -value
btw Repl Average
SD Suc/Man (T -test)
3.7 7.2E-06 3.9E-06
2.6
0.173
2.5 1.2E-05 5.0E-06
0.1
0.343
2.1 3.6E-04 1.3E-04
0.1
0.004
3.3 4.0E-07 2.1E-07
0.2
0.087
4.9
27.3
1.6
4.1
23
2.8E-06
9.7E-05
2.9E-03
1.9E-06
2.4E-06
1.4E-04
7.3E-04
1.1E-06
is up regulated by 2.6 fold in sucrose and RBCS, TPS1 and STP1 were down regulated in
sucrose by 8 fold, 4.7 fold, and 8 fold respectively. The effect of sucrose on RBCS expression
was significant (p = 0.004) and the effect on TPS1 approached significance (p = 0.08). The
effects of sucrose and mannitol on expression of each of above genes are shown graphically
Absolute and Normalized Quantity
1.00e−06
.001
1
in Figure 3.2.
Gene Expression in Leaf Strips
Actin−2
Rubisco
Kat1
Stp1
Tps1
Genes Name
Average
−−−−−−−−−−
Not normalized, Sucrose
Not normalized, Mannitol
Normalized, Sucrose
Normalized, Mannitol
SE
−−−−
Figure 3.2: Effect of sucrose and mannitol on RBCS, KAT1, TPS1, STP1 and ACT2 in
leaf strips. Normalized and unnormalized values are shown to compare the inter sample
variation. A total of six RNA samples S1, S2, and S3 for sucrose and M1, M2 and M3
for mannitol were assayed for transcripts of the above genes. RNA was isolated with Trizol
reagent from leaf strips incubated for 5 h in 150mM sucrose or manntol. One µg of RNA from
each sample was reverse transcribed into their corresponding cDNAs and 10% of the cDNA
was quantified by Q-PCR for each gene. Ct values generated by Q-PCR were converted into
quantities by using gene specific standard curves. SEs are shown by the error bars.
24
3.3
Variability between Samples is not due to
Variation in the Q-PCR or cDNA Reactions.
To investigate the source of the variability in the Q-PCR data two experiments were
performed, one that examined the variability in the Q-PCR reaction and another that
examined the variability in the cDNA reaction. In order to investigate the variability in
the Q-PCR reaction three replicate Q-PCR reactions were done for two genes (ACT2 and
SUC2) using cDNAs from RNA samples S1, S2 and S3 (sucrose-treated leaf strips) and M1,
M2 and M3 (mannitol-treated leaf strips). The results are shown in Table 3.2. The data
clearly show that the Q-PCR reaction is not the source of the variability in our samples.
The greatest difference in any of the triplicate Q-PCR reactions was an approximately 2-fold
variation in SUC2 expression for samples S1 and S2; on average replicate Q-PCR reactions
agreed to within 30%. However both ACT2 and SUC2 had large inter sample variability
between biological replicates. For ACT2 this variation was 3 fold in sucrose and 8 fold in
the mannitol-treated sample and for SUC2 it was much higher, 50 and 400 fold, respectively.
Normalization with ACT2 partially reduced this variability.
In order to reinforce the finding that the Q-PCR reaction was reproducible and that much
of the variability was either in the biological replicates themselves or in the cDNA reactions,
we performed two factor nested model ANOVA. In this two factor nested ANOVA model
the first factor is treatment. The second factor cDNA sample is nested within treatment
because the cDNA samples are synthesized from the leaves only after the leaves are treated
with sucrose or mannitol and RNA is isolated. We performed the ANOVA separately for
ACT2 and SUC2 without any normalization. In these models the effect of PCR replicates
was the residual or error. The R2 was the proportion of the total variation in gene expression
that could be explained by the model, i.e., by the treatment plus the cDNA reaction. The
R2 value for the ACT2 was 0.9972. Therefore, 99.72% of total variation in ACT2 expression
was attributable to treatments plus the cDNA reactions and only 0.28% was attributable
to Q-PCR reaction. We also looked at the mean square values for different sources of
variation. The mean square values give estimates of the variation due to corresponding
sources. For ACT2 the mean squares for treatments (sucrose versus mannitol), biological
replicates (plus the cDNA reaction), and PCR replicates were 9.5 × 10−07 , 2.1 × 10−07 and
4.1 × 10−10 respectively. This again showed that the variation due to the PCR replicates was
25
Table 3.2: The effect of sucrose and mannitol treatments on ACT2 and SUC2 expression
in leaf strips. cDNAs of three biological replicate samples S1, S2 and S3 for sucrose and
M1, M2 and M3 for mannitol treatment were assayed in triplicate for ACT2 and SUC2 by
Q-PCR. Panel A shows the raw data and Panel B shows the data for SUC2 after normalzing
to ACT2 expression. The absolute and normalized quantities are in nanograms of transcript
per 100 ng of total RNA used in a cDNA reaction. Inter sample variation for each gene
is shown by fold difference of replicates (the ratio of highest to lowest values of replicates)
and also by the standard deviation values. The expression of genes in response to sucrose
is shown by the ratio of transcripts in sucrose and mannitol. P -value were calculated using
the t-test at significance level of α=0.05.
A. Raw Data
Sample
S1
S2
S3
3.9E-04 4.03E-04 9.7E-04
3.4E-04 3.46E-04 9.7E-04
3.2E-04 3.62E-04 9.9E-04
Sucrose Avg
3.5E-04 3.7E-04 9.7E-04
SD
3.7E-05 3.0E-05 1.1E-05
SUC2
2.1E-06 3.0E-07 2.1E-05
3.5E-06 5.1E-07 2.3E-05
4.0E-06 3.3E-07 1.9E-05
Sucrose Avg
3.2E-06 3.8E-07 2.1E-05
SD
9.7E-07 1.2E-07 2.2E-06
M1
M2
M3
ACT2
2.4E-04 3.3E-05 3.4E-05
2.5E-04 3.2E-05 3.1E-05
2.6E-04 3.5E-05 2.9E-05
Mannitol Avg 2.5E-04 3.3E-05 3.2E-05
SD
1.1E-05 1.5E-06 2.4E-06
SUC2
3.3E-05 6.8E-08 2.4E-07
3.0E-05 7.9E-08 3.2E-07
3.8E-05 9.7E-08 2.7E-07
Mannitol Avg 3.4E-05 8.1E-08 2.8E-07
SD
4.5E-06 1.5E-08 4.0E-08
Gene
ACT2
Fold Fold
Diff
Diff
Ratio
(Q-PCR (Biol
Suc/ P -value
Repl) Repl) Average Man (T -test)
1.2
2.8 5.7E-04
5.4
0.14
1.2
1.0
1.9
1.7
1.2
55.7
8.2E-06
1.1
1.1
1.2
7.8
1.0E-04
1.3
1.4
1.3
414.5
1.1E-05
0.7
B. Data Normalized to ACT2 in each Sample
Gene
S1
SUC2 8.9E-06
M1
3.4E-05
Sample
Fold Diff btw
Ratio P -value
S2
S3
Avg Biol Replicates Suc/Man (T -test)
1.0E-06 2.1E-05 1.0E-05
21.2
0.8
0.89
M2
M3
6.1E-07 2.2E-06 1.2E-05
55.6
26
0.82
much smaller than that due to treatment and differences between biological replicates/cDNA
reactions. For SUC2 the value of R2 was 0.9835, i.e., 98.35% of total variation in SUC2
expression was attributable to treatments and biological replicates/cDNA reactions and
only 1.65% was attributable to PCR replicates. This was also shown by the mean square
values (4.3 × 10−11 , 7.5 × 10−10 and 4.2 × 10−12 respectively for treatments, biological
replicates/cDNA reactions and PCR replicates). The above results clearly show that there
was much less variation in the PCR replicates compared to the differences between the
biological replicates or the cDNA reactions.
To find out whether the inter sample variation we observed was due to variability of
the cDNA reactions an experiment was designed in which three cDNAs were prepared from
each of two different RNA samples, S3 and M9:25. The S3 sample was RNA isolated from
sucrose-treated whole leaves using Trizol. This RNA sample had been assayed in previous
Q-PCR experiments. The M9:25 sample was RNA isolated from mannitol-treated leaf strips
using the Picopure Kit. Two genes were assayed in each of the cDNAs ACT2 and HAB1;
the results are shown in Table 3.3. The fold difference between cDNA replicates was small
compared to what we had observed between biological replicates. For S3 the fold difference
was about 2 fold for ACT2 and 6 fold for HAB1. In sample M9:25 the variation between
different cDNAs was no more than about 2 fold. We also computed the coefficient of variation
(CV) to measure the variability between cDNA replicates for each gene in each treatment.
CV measures the spread in the data relative to the mean. Like the SD the small value of
CV indicates less variation, CV is free of scale and hence the variation in different data sets
with different scales can be compared by using their CVs. This measure was appropriate
for comparison of absolute variation in transcript numbers between different genes because
the variation in transcript numbers for a gene was likely to be large or small depending on
whether the transcript numbers for that gene were themselves large or small. CVs were small
for both ACT2 and HAB1.
These small CVs indicate that the variation in transcript numbers due to differences
between replicate cDNA reactions was small. In view of this result and the results obtained
for the replicate Q-PCR reactions, it seems that primary source of the variability between
our biological replicates is biological variability or differences in RNA quality between the
different samples. It is also of note that variability was less in RNA isolated using the
Picopure Kit (sample M9:25), which is based on silica gel, compared with RNA isolated
27
Table 3.3: The effect of sucrose and mannitol treatments on ACT2, and HAB1 expression
in leaf strips. Three cDNAs were prepared from each of two different RNA samples, S3
and M9:25, and assayed for ACT2, and HAB1. The S3 sample was RNA isolated from
sucrose-treated whole leaves using Trizol (panel A). This RNA sample had been assayed in
previous Q-PCR experiments. The M9:25 sample was RNA isolated from mannitol-treated
leaf strips using the Picopure Kit (panel B). The absolute quantities are in nanograms of
transcripts per 100 ng of RNA in used in the cDNA reaction. Inter sample variation for each
gene is shown by fold difference of replicates by taking the ratio of highest to lowest values
of replicates and also by CVs.
A. RNA from Sample S3
Gene
ACT2
HAB1
cDNA Samples
Fold Diff
1
2
3 btw Repl Average CV
8.1E-04 1.1E-03 6.1E-04
1.7 8.2E-04 0.07
5.5E-06 3.2E-05
2E-05
5.9 1.9E-05 0.48
B. RNA from Sample M9:25
Gene
ACT2
HAB1
cDNA Samples
Fold Diff
1
2
3 btw Repl Average CV
1.5E-03 1.9E-03 1.8E-03
1.2 1.7E-03 0.01
8.4E-05 1.6E-04 1.4E-04
1.9 1.3E-04 0.10
using Trizol (sample S3), which is based on phenol. This difference was not pursued further
but all RNA samples used in later sections of this thesis (RNA from freeze-dried mesophyll
tissue and guard cells) were isolated using the Picopure Kit.
3.4
Comparison of ACT2, EF1 and CYP as
Normalizer Genes
One way to control for differences in RNA quality and quantity between the samples is to
normalize the expression of each gene in a given sample relative to the expression of some
standard gene in the sample. Many studies in plants and animals use ACT2 as a normalizer
gene because it is expressed at high levels and its expression is relatively constant. In our
previous experiments (Tables 3.1 and, 3.2 ) the data were improved somewhat by normalizing
with ACT2, however all those experiments also showed that ACT2 was upregulated by
sucrose. A better control gene would be one that doesn’t change due to the treatment. We
therefore examined two additional potential normalizer genes, EF1 and CYP. Q-PCR data
28
for these genes is shown in Table 3.4. Based on these data, EF1 expression was induced by
sucrose and this change was even larger than that seen for ACT2 (7% more induced than
ACT2). CYP changed the least in response to the sugar treatment (20% change), however
it was expressed at a much lower level than the other two genes. Therefore, neither appears
to be better as a normalizer than ACT2. Despite it limitations, ACT2 was used as the
normalizer genes for all later experiments in this thesis.
Table 3.4: Raw Q-PCR data for ACT2, CYP and EF1 in RNA from sucrose- and manitoltreated leaf strips. RNA was isolated using Trizol and cDNAs of three biological replicate
samples S1, S2 and S3 for sucrose and M1, M2 and M3 for mannitol treatment were assayed
for ACT2, CYP and EF1 by Q-PCR. The absolute quantities are in nanograms of transcripts
per 100 ng of RNA in the cDNA reactions. The expression of genes in response to sucrose
is shown by the ratio of transcripts in sucrose and mannitol.
Genes
ACT2
CYP
EF1
ACT2
CYP
EF1
3.5
Sample in Sucrose
S1
S2
S3
2.8E-04 7.7E-05 5.1E-04
1.3E-06 1.3E-07 1.4E-06
2.3E-04 2.5E-05 2.7E-04
Sample in Mannitol
M1
M2
M3
1.4E-04 1.2E-04 5.7E-05
7.6E-07 8.0E-07 7.7E-07
9.1E-05 5.2E-05 3.9E-05
Ratio
Avg Suc/Man
2.9E-04
2.7
9.7E-07
1.2
1.7E-04
2.9
1.1E-04
7.8E-07
6.0E-05
Summary Data on the Effects of Sucrose and
Mannitol Treatments on Gene Expression in Leaf
Strips
Throughout these experiments with leaf strips each of our genes was assayed multiple times
and in 3 to 4 different biological replicates. Because normalizing with ACT2 or other genes
did not greatly reduce the inter sample variability we decided to pool all the data for each
gene to see whether the pooled data would yield statistically significant differences between
the sucrose and mannitol treatments. Where a single gene was assayed many times in one
biological replicate the results of those assays were averaged and the average values for the
29
biological replicates were compared for the two treatments (sucrose and mannitol) using the
two sample t-test. The results for the summary data are tabulated in Table 3.5.
Table 3.5: Summary data for sucrose-regulated gene expression in leaf strips. Average
quantities (nanograms) and Standard deviation of raw Q-PCR data over all experiments
for each gene in each treatment performed with leaf strips are shown here. Number of
experiments denotes the number of times each gene was assayed in triplicate biological
replicates by Q-PCR. The expression of genes in response to sucrose is shown by the ratio
of transcripts in sucrose and mannitol. P -values were calculated by the t-test at significance
level of α=0.05.
Gene Name No. of
Sucrose
Mannitol
Ratio P -Value
Exp Average
SD Average
SD Suc/Man
ACT2
8 4.7E-04 4.2E-04 1.5E-04 1.1E-04
3.2
0.005
ADPGase
1 1.3E-05 1.6E-05 7.9E-07 8.2E-07
16
0.321
CYP
2 3.7E-06 5.5E-06 1.3E-06 1.0E-06
2.9
0.452
HAB1
3 2.9E-05 2.6E-05 5.9E-06 5.2E-06
4.9
0.04
KAT1
4 7.0E-06 5.9E-06 1.8E-06 2.0E-06
3.8
0.013
RBCS
3 8.7E-04 6.7E-04 2.3E-03 1.2E-03
.37
0.005
STP1
2 1.3E-05 1.1E-05 7.0E-05 1.1E-04
.18
0.252
SUC1
1 1.6E-03 1.9E-03 2.7E-04 4.1E-04
5.7
0.308
SUC2
3 4.7E-06 6.5E-06 1.0E-05 1.5E-05
.45
0.315
TPS1
2 8.3E-07 6.8E-07 1.6E-06 2.0E-06
.53
0.436
ACT2 was assayed 8 times across 4 biological replicate samples, more times than any
other gene was assayed, and showed a statistically significant 3 fold up-regulation in sucrose.
The data for ADPGase showed a 16 fold induction by sucrose compared with mannitol but
this effect was not statistically significant. This gene was assayed in only one experiment
(three biological replicates each assayed only once), replication of the experiment might yield
more significant results but the low level of expression of this gene in the mannitol-treated
samples makes the data inherently more variable. CYP was induced by sucrose about 3
fold but it had very low relative expression in both sucrose and mannitol and the difference
between the treatments was not significant. HAB1 was assayed 3 times, it expression was
5 fold higher in sucrose and this difference was significant. KAT1 had relatively low levels
of expression in our samples; its expression was upregulated by sucrose by 4 fold which
was statistically significant. RBCS gave the highest level of expression of all the genes
30
Figure 3.3: Expression of genes in leaf strips relative to the expression of ACT2 in the same
sample. RBCS had highest level of relative expression in both treatment followed by SUC1.
STP1 and SUC2 had moderately high expression in mannitol and lower expression in sucrose.
HAB1, KAT1, and ADPGase were expressed at moderate to low levels and expression was
higher in sucrose than mannitol. CYP and TPS1 had very low expression in both treatments.
assayed, its expression was down regulated by sucrose compared with mannitol and this
down regulation was statistically significant. STP1 expression was about 5 fold lower in
sucrose than mannitol but the difference was not statistically significant perhaps because
of large inter sample variability. SUC1 was assayed only once (three biological replicates
each assayed only once). The expression level of this gene was very high, next to RBCS in
the sample (8 fold less in mannitol than RBCS). The raw data did not give a significant
difference between sucrose and mannitol treatments by the t-test but induction of this gene
in sucrose was 5 fold. This gene may be induced by sucrose treatment, however, further
replication would be needed to verify this observation. SUC2 was assayed 3 times and this
gene appeared not to be changed by sucrose treatment. The expression of TPS1 was the
lowest of all the genes assayed. Its expression declined by 2 fold in sucrose compared with
mannitol but the differences are not significant. The low level of expression of this gene
may have reduced the sensitivity of our assay. The expression of the above genes relative to
ACT2 is shown in Figure 3.3, and gene expression in response to sucrose is shown by the
ratio of transcripts in sucrose and mannitol in Figure 3.4.
31
Figure 3.4: The gene expression in response to sucrose in leaf strips. Plotted here are
the average expressions of each gene in sucrose-treated leaf strips divided by its average
expression in mannitol-treated leaf strips. The expression of ACT2, HAB1, KAT1 and
RBCS was significantly affected by sucrose treatment.
3.6
Quantification of RNA Isolated from
Microdissected Mesophyll Cells
The main purpose of this experiment was to determine whether RNA can be isolated from
mesophyll tissue that had been microdissected from freeze-dried leaf strips and whether this
RNA is of sufficient quality to permit analysis of gene expression by Q-PCR. The approach
used here for assessing RNA quality is to compare the gene expression profiles for our panel
of genes in microdissected mesophyll cells with the profile already obtained for leaf strips.
Because leaves are composed almost entirely of mesophyll cells, the two profiles should be
very similar. A second goal of this experiment is to provide baseline data for assessing the
effectiveness of later experiments in which RNA will be amplified with T7 RNA polymerase
prior to Q-PCR.
In this experiment we had two biological replicates for each treatment. Samples S5/31
and S6/2 represent two different samples of leaf strips (biological replicates) treated with
sucrose and freeze-dried (their names indicate the date when they were treated and freezedried). Similarly, samples M5/31 and M6/2 represent two samples treated with mannitol.
32
In an initial experiment three different samples of mesophyll tissue were cut from both
S5/31 and M6/2 and RNA from these samples was analyzed. Each sample consisted of
approximately 10-15 µg of microdissected mesophyll cells. RNA was isolated from these
samples (using Arcturus’ Picopure Kit), converted to cDNA and analyzed by Q-PCR. The
results are shown in Tables 3.6 and 3.7. The number of transcripts detected in this experiment
Table 3.6: Gene expression in different samples of mesophyll tissue cut from the same
biological replicate of leaf strips treated with sucrose. Three different 10-15 µg-sized samples
of mesophyll tissue were cut from sample S5/31 and were assayed for gene expression by
Q-PCR. Raw and normalized data are shown here. Data was normalized using ACT2 as a
standard. Values are nanograms of transcripts detected in the Q-PCR samples. Intersample
variation for each gene is shown by fold difference of replicates by taking the ratio of highest
to lowest values of replicates and also by their CV value.
Genes
ACT2
ADPGase
CYP
HAB1
KAT1
RBCS
STP1
SUC1
SUC2
TPS1
ADPGase
CYP
HAB1
KAT1
RBCS
STP1
SUC1
SUC2
TPS1
Raw Data
Fold
S5/31-1 S5/31-2 S5/31-3 Difference
1.8E-06 5.9E-06 5.0E-06
3.2
2.5E-08 1.1E-07 5.8E-08
1.9
2.8E-08 7.0E-08 7.0E-08
2.5
7.3E-08 2.7E-07 1.4E-07
3.7
2.3E-08 9.0E-08 5.8E-08
3.9
6.3E-07 2.3E-06 1.8E-06
3.7
1.3E-07 8.4E-08 1.5E-07
1.8
4.5E-06 1.7E-05 8.8E-06
3.8
8.4E-08 3.2E-08 3.6E-07
11.3
1.0E-08 1.6E-08 5.0E-09
3.1
Values Normalized to ACT2
8.2E-08 1.1E-07 6.8E-08
1.6
8.9E-08 7.0E-08 8.2E-08
1.3
2.3E-07 2.7E-07 1.6E-07
1.6
7.5E-08 9.0E-08 6.8E-08
1.3
2.0E-06 2.3E-06 2.1E-06
1.1
4.2E-07 8.4E-08 1.8E-07
2.4
1.5E-05 1.7E-05 1.0E-05
1.7
2.7E-07 3.2E-08 4.2E-07
8.4
3.3E-08 1.6E-08 5.8E-09
2.1
CV
0.25
0.44
0.19
0.39
0.34
0.30
0.08
0.40
1.24
0.27
0.06
0.01
0.06
0.02
0.01
0.58
0.06
0.67
0.58
for ACT2, SUC1, and RBCS were 100 times (or more) above background (depending on the
experiment and the gene, background is about 0.5 to 1 ×10−8 ng of transcripts). These genes
33
were also found to be highly expressed in leaf strips in our study. Genes that are expressed
preferentially in guard cells (ADPGase, HAB1, TPS1, STP1 and KAT1) were expected to
have low transcript numbers in RNA isolated from mesophyll cells. Among these genes we
found ADPGase, TPS1 had extremely low expression in the mesophyll tissue samples, only
1 to 5 times background. The expression of HAB1, STP1, and KAT1 were a bit higher but
still quite low (ranging from 5 to 15 times background) as were the expression of CYP and
SUC2.
Table 3.7: Gene expression in different samples of mesophyll tissue cut from the same
biological replicate of leaf strips treated with mannitol. Three different 10-15 µg-sized
samples of mesophyll tissue were cut from sample M6/2 and were assayed for gene expression
by Q-PCR. Raw and normalized Q-PCR data are shown here. Data was normalized using
ACT2 as a standard. Values are nanograms of transcripts detected in the Q-PCR samples.
Intersample variation for each gene is shown by fold difference of replicates by taking the ratio
of highest to lowest values of replicates and also by their CV value. Undet. is undetected.
Gene
ACT2
ADPGase
CYP
HAB1
KAT1
RBCS
STP1
SUC1
SUC2
TPS1
ADPGase
CYP
HAB1
KAT1
RBCS
STP1
SUC1
SUC2
TPS1
Raw Data
Fold
M6/2-1 M6/2-2 M6/2-3 Difference CV
8.5E-07 2.2E-06 3.6E-06
4.2 0.4
1.6E-09
undet 3.1E-09
2.0 0.2
1.9E-08 3.2E-08 2.0E-07
10.5 1.5
4.4E-08 1.9E-07 2.7E-07
6.3 0.5
6.4E-10
undet 9.0E-08
140.2 1.9
4.7E-06 1.2E-06 6.3E-07
7.4 1.0
1.5E-07 4.6E-08 1.0E-07
3.2 0.3
7.2E-07 6.7E-07 1.8E-07
4.1 0.3
3.5E-08 3.5E-09 1.7E-07
46.9 1.6
8.9E-10 8.0E-10 2.8E-08
31.6 2.5
Values normalized to ACT2
6.7E-09
undet 3.1E-09
2.1 0.3
7.9E-08 5.3E-08 2.0E-07
2.5 0.5
1.8E-07 3.2E-07 2.7E-07
1.7 0.1
2.7E-09
undet 9.0E-08
33.4 1.8
2.0E-05 1.9E-06 6.3E-07
3.0 2.1
6.3E-07 7.7E-08 1.0E-07
8.2 1.4
3.0E-06 1.1E-06 1.8E-07
6.3 1.0
1.5E-07 5.8E-09 1.7E-07
28.2 0.7
3.7E-09 1.3E-09 2.8E-08
7.5 1.8
34
In this early experiment we also observed substantial variation between technical replicates. This variation was expected since the samples undoubtedly contain different amounts
of RNA (the amount of tissue that was cut out could not be precisely controlled and the
samples were too small to weigh accurately), and the most variable samples were observed
for genes with the lowest expression. Genes’ expression in sucrose-treated samples had less
intersample variation (Table 3.6). For example about 4-fold and 11-fold differences between
replicate samples was observed for KAT1 and SUC2 in sucrose treated samples but 140and 46-fold differences were found for these two genes respectively in the mannitol treated
samples (Table 3.7). In order to control this variability, gene expression was normalized
with respect to ACT2, and normalization did help to reduce this variability to some extent.
For KAT1 and SUC2 variability was reduced from 4-fold and 11-fold differences to 2- and
8-fold respectively in the sucrose treated samples and 140- and 46-fold differences to 33- and
28-fold in the mannitol-treated samples.
In next part of the experiment two different biological replicates were analyzed for each
treatment (samples S5/31, S6/2 and M5/31, M6/2). The data are shown in Table 3.8.
As observed before, expression of some of the genes was at or barely above background.
There was also considerable intersample variability between the raw values for biological
replicates (Table 3.8, part A) although the variability was somewhat less than for the
technical replicates in the previous experiment. Normalization of the data (using the level
of expression of ACT2 in each sample as an internal standard) helped to reduce the fold
difference between duplicate samples (Table 3.8, part B). For example, the fold difference
between replicates for ADPGase and CYP in the mannitol treated sample was reduced from
10 fold to 3 fold. For STP1 this intersample variation was reduced from 10 fold to 3.3 fold
in sucrose-treated sample.
When comparing gene expression between the sucrose and mannitol-treated samples only
the data for HAB1 showed a significant difference between the two treatments. HAB1
showed higher expression in sucrose than in mannitol, which is similar to the response seen
in the leaf strip experiments. Despite the lack of significant differences in response to sugar
treatment the direction of the response to sugars was the same in the mesophyll cells as
it was in leaf strips for most of the genes. However, RBCS was unchanged in response to
the sugar treatment (or slightly elevated in sucrose), whereas in leaf strips its expression
was significantly repressed by sucrose, and STP1 was slightly higher in the sucrose-treated
35
Table 3.8: The effect of sucrose and mannitol treatments on gene expression in mesophyll
cells. Q- PCR data of duplicate samples of S5/31, S6/2, M5/31 and M6/2 are shown
here. Panel A shows the raw data. Panel B shows normalized data using expression of
ACT2 as an internal standard. The absolute and normalized quantities are in nanograms of
transcripts detected in Q-PCR samples. Intersample variation for each gene is shown by the
fold difference between replicates (the ratio of the highest to the lowest values of replicates).
The expression of genes in response to sucrose is shown by the ratio of transcripts in sucrose
and mannitol. P -value is calculated by t-test at significance level of α=0.05.
A. Raw Data
Genes
ACT2
ADPGase
CYP
HAB1
KAT1
RBCS
STP1
SUC1
SUC2
TPS1
Sample in
S5/31
7.5E-06
6.5E-08
2.7E-08
3.1E-07
1.4E-07
2.3E-06
2.1E-07
2.0E-05
8.4E-08
3.2E-09
Sucrose
S6/2
2.1E-05
3.4E-07
1.3E-07
7.8E-07
1.4E-07
1.3E-05
2.0E-06
4.1E-05
4.3E-07
1.4E-08
Smaple in
M5/31
7.0E-06
6.9E-08
2.8E-08
4.4E-07
1.4E-08
3.5E-06
6.0E-07
3.3E-05
1.8E-07
6.5E-09
mannitol Fold
M6/2 Suc
2.0E-06 2.8
6.1E-09 5.3
2.7E-09 5.1
1.4E-07 2.5
2.5E-09 1.0
2.7E-06 5.6
1.2E-07 9.2
5.0E-06 2.0
3.5E-08 5.2
9.3E-10 4.3
Diff
Ratio T -Test
Man Suc/Man P -value
3.5
3.2
0.307
11.4
5.4
0.364
10.6
5.2
0.362
3.2
1.9
0.459
5.7
16.9
0.002
1.3
2.4
0.486
5.0
3.0
0.506
6.6
1.6
0.584
5.3
2.4
0.512
7.0
2.2
0.515
B. Data Normalized to ACT2in each Sample
Genes
ADPGase
CYP
HAB1
KAT1
RBCS
STP1
SUC1
SUC2
TPS1
Sample in
S5/31
1.8E-07
7.5E-08
8.7E-07
3.9E-07
6.5E-06
6.0E-07
5.7E-05
2.4E-07
8.9E-09
Sucrose
S6/2
3.4E-07
1.3E-07
7.8E-07
1.4E-07
1.3E-05
2.0E-06
4.1E-05
4.3E-07
1.4E-08
Sample in
M5/31
6.9E-08
2.8E-08
4.4E-07
1.4E-08
3.5E-06
6.0E-07
3.3E-05
1.8E-07
6.5E-09
Mannitol Fold diff
Ratio
T -Test
M6/2 Suc Man Suc/Man P - value
2.2E-08 1.9
3.2
5.8
0.123
9.5E-09 1.8
3.0
5.5
0.112
5.0E-07 1.1
1.1
1.8
0.021
8.9E-09 2.7
1.6
23.2
0.174
9.5E-06 2.0
2.7
1.5
0.541
4.3E-07 3.3
1.4
2.5
0.379
1.8E-05 1.4
1.9
1.9
0.170
1.2E-07 1.8
1.5
2.2
0.221
3.3E-09 1.5
2.0
2.3
0.155
36
mesophyll samples (compared with mannitol-treated tissue) but was lower in the sucrosetreated leaf strips than in the mannitol-treated leaf strips. Large intersample variation, lack
of additional replication of the mesophyll tissue measurements, and the very low level of
gene expression in the mesophyll samples might be the reason for these different outcomes.
Genes those are preferentially expressed in guard cells (HAB1, STP1, KAT1, ADPGase and
TPS1) had low expression in our sample.
Although the effects of sugars on gene expression in the mesophyll tissue samples did
not parallel that seen in leaf strips, the expression pattern of the different genes relative
to each other was remarkably similar in the two experiments. Figure 3.5 (top) shows the
relative expression of genes in sucrose- and mannitol-treated mesophyll tissue, and Figure 3.5
(bottom) shows the relative expression of genes in mannitol-treated and sucrose-treated leaf
strips. Comparison of these data gave a rank correlation coefficient of 0.9 in sucrose-treated
samples and 0.87 in mannitol-treated samples.
3.7
Investigation of the Use of RNA Amplification for
Analysis of Gene Expression in Sub-nanogram
Sized Samples of RNA from Mesophyll Cells
The ultimate goal of this project was to analyze gene expression in guard cells of Arabidopsis
that had been isolated by hand dissection from frozen dried leaves. Because of the difficulty
of this dissection each sample would be limited to about 50 guard cells, and investigation
of gene expression in such tiny samples would require RNA amplification before Q-PCR.
The accepted approach for RNA amplification involves in vitro transcription by T7 RNA
polymerase (Eberwine et al., 1992[69]). First, total RNA is isolated and converted to cDNA
using an oligo-dT primer that contains a T7 RNA polymerase promoter. Then the cDNAs
are made double stranded using a random primer to prime second strand synthesis. Finally,
T7 RNA polymerase is used to produce antisense RNA transcripts from the cDNAs and these
transcripts can be analyzed by Q-PCR using gene-specific primers. Amplification of mRNA
using T7 RNA polymerase has been shown to be linear and to amplify different transcripts to
similar degrees (Polacek et al. 2003[48]; Zhao, et al., 2002[49]). The experiments described
in this section were designed to test the feasibility of using RNA amplification to analyze
transcripts in tiny samples of RNA from mesophyll cells. The approach was to take RNA
isolated from freeze-dried mesophyll cells, dilute the RNA down to levels that would be
37
Figure 3.5: Top: Relative expression of genes to ACT2 in mesophyll tissue. Average
expression of each gene divided by the expression of ACT2 is plotted here. Bottom: Relative
expression of genes to ACT2 in leaf strips. Average expression of genes in leaf strips relative
to the expression of ACT2 in the same sample is plotted here. The relative expression
of genes from mesophyll cells and leaf strips shows remarkable similarities with 0.90 rank
correlation coefficient in sucrose treated sample and 0.87 in mannitol treated sample.
similar to the amount of RNA expected for samples of 50 guard cells, and then amplify this
diluted RNA and analyze it by Q-PCR. The Q-PCR results for the amplified RNA samples
can then be compared with the results obtained for the unamplified mesophyll RNA samples
38
described in the previous section.
The following calculation was made to estimate how much to dilute the mesophyll RNA.
Estimating that Arabidopsis mesophyll cells have a dry weight of about 5 ng (about half
that of a Vicia faba mesophyll cells (Jones et al., 1977[70])), then 10 µg of dry Arabidopsis
mesophyll tissue would contain about 2000 cells. Assuming that Arabidopsis mesophyll cells
and guard cells are similar in weight and RNA content, it would be expected that a 40-fold
dilution of RNA from 10 µg of mesophyll cells should make a sample comparable to that
expected for RNA from 50 guard cells. However, this rough calculation could easily be a
10-fold overestimate because the relative amounts of RNA in Arabidopsis mesophyll and
guard cells, and the efficiency of RNA isolation from small tissue samples, are unknown.
Therefore, we decided to analyze mesophyll RNA samples that had been diluted 100 fold
and 1000 fold.
In an initial experiment RNA from mesophyll sample S6/2 was diluted 100 fold, amplified,
and assayed by Q-PCR for the levels of ACT2, CYP and RBCS transcripts. The result is
shown in Table 3.9. For comparison the levels of ACT2, CYP and RBCS transcripts before
Table 3.9: Q-PCR data of sample S6/2 before and after 100 fold RNA dilution and
amplification with T7 RNA polymerase. RNA from sample S6/2 was diluted 10 fold,
amplified one round with T7 RNA polymerase, and the antisense RNA was diluted again
by 10 fold (making an overall 100 fold dilution), reverse transcribed into cDNA using genespecific primers, and Q-PCR was done to determine the levels of ACT2, CYP and RBCS
transcripts. Ct is the threshold value obtained in the Q-PCR analysis and absolute quantity
are the transcript levels calculated from the Ct values in nanograms of transcripts. Fold
difference was determined by taking the ratio of absolute quantity of transcripts in the after
amplification assay to that in the before amplification assay for each gene.
Before Dilution
After Dilution
Fold
and Amplification
and Amplification
Difference
Genes
Ct values Absolute Ct values Absolute Suc/Man
quantity
quantity
ACT2
20.5
2.1E-05
24
2.1E-04
9.8
CYP
24.7
1.3E-07
29
4.9E-06
36.7
RBCS
22.6
1.3E-05
26
1.0E-04
8.0
RBCS relative
6.0E-01
4.9E-01
0.8
to ACT2
39
dilution and amplification are also shown in the table (data from Table 3.8). In this table
fold difference refers the ratio of transcripts after and before amplification and dilution. The
fold differences for ACT2 and RBCS are similar (9.8 and 8 fold, respectively). Considering
that the RNA had been diluted 100 fold the results indicate a 980 fold amplification of
ACT2 transcripts by T7 RNA polymerase and an 800 fold amplification for RBCS. CYP
however was amplified to a much greater degree (3770 fold). This may be because the level
of CYP transcripts in the unamplified sample was low, near the limit of detection by QPCR, and therefore was not accurately quantified in the unamplified sample. It has been
noted previously that T7 RNA polymerase amplification boosts rare transcripts more than
abundant ones (Patel et al., 2005[71]; Polacek et al. 2003[48]), and it has been argued
that the amplified data more accurately reflect the real transcript levels and that Q-PCR
underestimates the abundance of rare transcripts (Patel et al., 2005[71]).
Having found that transcripts were readily detectable after 100 fold dilution and amplification with T7 RNA polymerase an experiment was performed in which the RNA had been
diluted 1000 fold before amplification. In this experiment all four mesophyll RNA samples
were analyzed (sucrose-treated samples S5/31 and S6/2 and mannitol-treated samples M5/31
and M6/2) and the entire panel of genes was analyzed except ADPGase, KAT1 and TPS1,
because of the very low level of expression of these genes in mesophyll cells. The results are
shown in Table 3.10. For most of the genes (including CYP) the Ct values and corresponding
absolute transcript levels were exactly same, or very similar, before and after dilution and
amplification. This indicates a generally uniform amplification of about 1000 fold for all the
genes. There are scattered exceptions in the data where the variation was larger (see for
example, SUC2 S5/31, CYP S6/2, RBCS M6/2) but overall it was quite uniform. However,
for several genes the Ct values were 30 or higher, which is near background (the no transcript
controls, NTC, generally have a ct value of about 35, which corresponds to a concentration of
about 0.5 to 1 ×10−8 ng of transcripts). This indicates that these genes are near the detection
limit of this assay and 1000 fold dilution of the RNA is the lower limit for transcript detection
after one round of RNA amplification.
The variation between replicate samples in both the before and the after dilution and
amplification assays is undoubtedly partly due to differences in RNA quantity. Because we
could not precisely control the amount of tissue that was cut out, and because the samples
were too small to weigh accurately, each of the mesophyll samples differed in size by an
40
Table 3.10: Q-PCR data of samples S5/31, S6/2 and M5/31, M6/2 before and after dilution
and RNA amplification. RNA from microdissected mesophyll cells of samples S5/31, S6/2
(sucrose-treated leaves) and M5/31, M6/2 (mannitol-treated leaves) was diluted 100 fold
and amplified for round one with T7 RNA polymerase. The resulting antisense RNA was
diluted by 10 fold (making an overall 1000-fold RNA dilution), converted to cDNAs using
gene-specific primers and analyzed by Q-PCR. The absolute quantities are nanograms of
transcripts. Columns of ratios are the ratios of the number of transcripts of each gene after
dilution and amplification to those before.
Genes
ACT2
ACT2
CYP
CYP
HAB1
HAB1
RBCS
RBCS
STP1
STP1
SUC1
SUC1
SUC2
SUC2
Before/
After
Ampl
Before
After
Before
After
Before
After
Before
After
Before
After
Before
After
Before
After
Absolute
Sucrose
S5/31
S6/2
5.9E-06 2.1E-05
3.1E-06 1.2E-05
7.0E-08 1.3E-07
1.3E-07 4.0E-07
1.4E-07 7.8E-07
8.8E-08 1.4E-07
1.8E-06 1.3E-05
1.6E-06 1.3E-05
1.5E-07 2.0E-06
8.0E-08 1.1E-06
8.8E-06 4.1E-05
3.9E-06 3.6E-05
8.4E-08 4.3E-07
1.4E-08 1.5E-07
quantity
Ratio of Trans Aft/Bef Amp
Mannitol
Sucrose
Mannitol
M5/31
M6/2 S5/31 S6/2 M5/31 M6/2
7.0E-06 3.6E-06
0.5
0.6
0.7
1.7
5.0E-06 6.2E-06
2.8E-08 2.0E-07
1.9
3.1
2.7
2.6
7.6E-08 5.2E-07
4.4E-07 2.7E-07
0.6
0.2
0.5
1.1
2.1E-07 3.1E-07
3.5E-06 6.3E-07
0.9
1.0
1.5
0.4
5.3E-06 2.3E-07
6.0E-07 1.0E-07
0.5
0.6
0.5
2.8
3.0E-07 2.8E-07
3.3E-05 1.8E-07
0.4
0.9
1.0
1.3
3.3E-05 2.4E-07
1.8E-07 5.3E-07
0.2
0.3
0.3
1.2
5.8E-08 6.4E-07
unknown amount. This inter sample variation was sometimes over 100 fold or more in
case of SUC1 in mannitol treatment in both assays. An example is shown in Table 3.11,
where RBCS had more than 20 fold difference in replicate samples in mannitol treatment
in after amplification assay. To control this intersample variation genes were normalized
with ACT2 and the results are shown in Table 3.11. Normalization reduced this variation
for nearly every gene in each treatment. But there still were large inter sample differences,
particularly in the mannitol-treated samples and in genes STP1. SUC1, and RBCS. The
average fold difference between replicate samples was reduced by normalization from 5.9
to 2.0 for the sucrose-treated samples before amplification and from 7.2 to 2.4 fold for the
same samples after amplification. However, the average fold difference was much larger in
the mannitol-treated samples even after normalization. Much, but not all, of this variation
41
Table 3.11: Absolute and normalized quantities of transcripts in RNA from freeze-dried
mesophyll tissue before and after dilution and amplification. Quantities are ng of transcripts.
Fold difference is the ratio of the highest to the lowest value in biological replicate samples.
For normalization, each gene was normalized relative to ACT2 in the same sample.
Genes
ACT2
CYP
HAB1
RBCS
STP1
SUC1
SUC2
CYP
HAB1
RBCS
STP1
SUC1
SUC2
Genes
ACT2
CYP
HAB1
RBCS
STP1
SUC1
SUC2
CYP
HAB1
RBCS
STP1
SUC1
SUC2
Before Amplification
Absolute Quantity
Sample in Sucrose Sample in Mannitol
Fold Diff
Fold Diff
S5/31
S6/2 M5/31
M6/2 in Sucrose in Mannitol
5.9E-06 2.1E-05 7.0E-06
3.6E-06
3.6
1.9
7.0E-08 1.3E-07 2.8E-08
2.0E-07
1.9
7.1
1.4E-07 7.8E-07 4.4E-07
2.7E-07
5.6
1.6
1.8E-06 1.3E-05 3.5E-06
6.3E-07
7.2
5.6
1.5E-07 2.0E-06 6.0E-07
1.0E-07
13.3
6.0
8.8E-06 4.1E-05 3.3E-05
1.8E-07
4.7
183.3
8.4E-08 4.3E-07 1.8E-07
5.3E-07
5.1
2.9
Average Fold Difference
5.9
29.8
Normalized with ACT2
2.5E-07 1.3E-07 2.8E-08
3.9E-07
1.9
13.9
5.0E-07 7.8E-07 4.4E-07
5.3E-07
1.6
1.2
6.4E-06 1.3E-05 3.5E-06
1.2E-06
2.0
2.9
5.3E-07 2.0E-06 6.0E-07
1.9E-07
3.7
3.1
3.1E-05 4.1E-05 3.3E-05
3.5E-07
1.3
94.3
3.0E-07 4.3E-07 1.8E-07
1.0E-06
1.4
5.7
Average Fold Difference
2.0
20.3
After Amplification
Absolute Quantity
Sample in Sucrose Sample in Mannitol
Fold Diff
Fold Diff
S5/31
S6/2 M5/31
M6/2 in Sucrose in Mannitol
3.1E-06 1.2E-05 5.0E-06
6.2E-06
3.9
1.2
1.3E-07 4.0E-07 7.6E-08
5.2E-07
3.1
6.8
8.8E-08 1.4E-07 2.1E-07
3.1E-07
1.6
1.5
1.6E-06 1.3E-05 5.3E-06
2.3E-07
8.1
23.0
8.0E-08 1.1E-06 3.0E-07
2.8E-07
13.8
1.1
3.9E-06 3.6E-05 3.3E-05
2.4E-07
9.2
137.5
1.4E-08 1.5E-07 5.8E-08
6.4E-07
10.7
1.0
Average Fold Difference
7.2
26.0
Normalized with ACT2
5.0E-07 4.0E-07 9.4E-08
5.2E-07
1.3
5.5
3.4E-07 1.4E-07 2.6E-07
3.1E-07
2.4
1.2
6.2E-06 1.3E-05 5.3E-06
2.9E-07
2.1
18.6
3.1E-07 1.1E-06 3.7E-07
2.8E-07
3.6
1.3
1.5E-05 3.6E-05 3.3E-05
3.0E-07
2.4
110.9
5.4E-08 1.5E-07 7.2E-08
6.4E-07
2.8
8.9
Average Fold Difference
2.4
24.4
42
Figure 3.6: Comparison of relative expression of genes before and after RNA dilution and
amplification. The number of transcripts of each gene was divided by the number of
transcripts of ACT2 in the same sample and the average results for biological replicates
before and after RNA dilution and amplification are plotted here.
was attributable to the results obtained for one gene (SUC1) in the mannitol-treated sample
M6/2. In fact the M6/2 data seem odd. Compared with the other samples, the expression
of all the genes in M6/2 were very similar to each other. Perhaps the RNA in this sample
was partially degraded.
The expression of the assayed genes relative to the expression of ACT2 is shown in
Figure 3.6. The results showed that the pattern of gene expression was similar before and
after dilution and amplification. SUC1 had the highest level of relative expression in both
treatments and had same expression pattern (i.e., a little bit higher in mannitol than sucrose
in before and after amplification assays). Next to SUC1, RBCS had high expression in both
treatments. RBCS had a slightly higher expression in sucrose than mannitol in both before
and after dilution and amplification assay. STP1 and HAB1 had low expression and HAB1
had higher expression in mannitol than sucrose. The expression pattern was same in both
experiments for these two genes. SUC2 and CYP had very low expression relative to ACT2.
43
3.8
Quantification of RNA from Microdissected
Guard Cells
The purpose of this experiment was to demonstrate the feasibility of analyzing gene
expression in small samples of guard cells that had been isolated by microdissection. My
work on the dilution and amplification of RNA from mesophyll cells indicated that it should
be possible to analyze gene expression in samples of 50 guard cells. However, microdissection
of this many guard cells from freeze-dried tissues was a difficult task in one sitting. Therefore,
initially 10 to 12 guard cells were microdissected at a time and stored in a freezer until 50
cells had been accumulated. During this process some cells were inevitably lost and the
cells were also subjected to repeated freeze thawing cycles which might damage RNA. It
seemed better to store the microdissected guard cells in a Petri dish on the lab bench until
50 cells had been collected. Therefore, a preliminary experiment was needed to determine
whether freeze-dried tissue could be stored at room temperature for a few days without
compromising RNA quality and this experiment was conducted on mesophyll tissue since
that is easier dissect than guard cells.
For this experiment (results shown in Table 3.12, six, 10 - 15 µg sized samples of mesophyll
tissue were microdissected from mannitol-treated freeze-dried leaves (sample M5/31). Two
Table 3.12: Effect of holding freeze-dried tissue at room temperature on RNA quality. Six
samples of mesophyll tissue were cut from freeze-dried leaf sample M5/31. Two samples were
analyzed immediately, two were held for two days at room temperature and then analyzed,
and two were analyzed after 4 days at room temperature. The data are the nanograms of
transcripts for ACT2, CYP, and RBCS as determined by Q-PCR. The results of normalizing
the data for CYP and RBCS relative to ACT2 are also shown.
Sample
Day
Day
Day
Day
Day
Day
0
0
2
2
4
4
Raw Q-PCR Data
ACT2
CYP
RBCS
3.90E-06 4.30E-08 7.80E-06
2.30E-06 3.40E-08 7.00E-06
1.70E-06 2.20E-08 1.90E-06
3.60E-06 3.70E-08 4.00E-06
3.30E-06 3.10E-08 1.00E-05
5.90E-06 7.00E-08 1.90E-05
44
Data Normalized
CYP
4.30E-08
5.77E-08
4.66E-08
3.70E-08
5.54E-08
7.00E-08
to ACT2
RBCS
7.80E-06
1.19E-05
2.07E-06
4.00E-06
1.79E-05
1.90E-05
samples were taken immediately for RNA isolation and Q-PCR analysis (Day 0), two samples
were held at room temperature for two days before RNA isolation and analysis (Day 2), and
the last two samples were held at room temperature for 4 days before analysis (Day 4). The
samples were assayed for genes ACT2, CYP and RBCS.Although there was a dip in the level
of RBCS transcripts at Day 2 compared with Day 0, this was not observed in the Day 4
samples and there was no evidence of progressive loss of ACT2 or CYP transcripts. Overall,
the data are highly consistent and indicate no loss of transcripts due to holding the samples
for 4 days at room temperature before analysis.
Having confirmed that keeping the microdissected freeze-dried tissues for a few days
outside of the freezer does not result in RNA degradation, we turned to isolation and analysis
RNA from microdissected guard cells. Two samples were analyzed, S5/31 (sucrose-treated
leaves) and M5/31 (mannitol-treated leaves) and the results are shown in Table 3.13. About
Table 3.13: Gene expression in guard cells and the effects of sucrose and mannitol. RNA was
isolated from two samples of 50 microdissected guard cells, one sample was guard cells from
sucrose-treated leaves (S5/31) and one was from mannitol-treated leaves (M5/31). The RNA
was amplified (two rounds of amplification with T7 RNA polymerase) and transcript levels
were determined by Q-PCR. The absolute quantities are ng of transcrips after normalization
to correct for differences in the amount of aRNA in the two samples. NTC, no transcript
control for the Q-PCR reaction; undet undetectable, did not reach threshold in the Q-PCR
reaction; nd - not determined.
Genes
ACT2
ADPGase
CYP
HAB1
KAT1
RBCS
STP1
SUC1
SUC2
TPS1
S5/31
19.47
20
27
21
17
19
13.84
19.35
21.74
21.46
Ct values
M5/31
19.72
20.53
18.97
22.33
17.36
17.85
13.46
17.3
38.35
24
NTC
nd
33.92
38.07
nd
nd
35.67
undet
nd
38
nd
Absolute
S5/31
3.9E-04
2.8E-04
9.5E-07
1.0E-04
9.6E-04
8.7E-04
5.5E-03
3.8E-04
2.3E-05
1.6E-04
Quantity
Ratio
M5/31 Suc/Man
5.2E-04
0.75
3.1E-04
0.91
2.8E-04
0.0034
6.6E-05
1.53
1.2E-03
0.79
2.7E-03
0.32
1.1E-02
0.49
2.3E-03
0.16
4.6E-10
65609
4.1E-05
3.80
50 guard cells were cut out from each sample and RNA was isolated and amplified. Unlike
45
the previous experiments with amplification of mesophyll RNA, the guard cell RNA was put
through two rounds of amplification with T7 RNA polymerase to further boost the number
of transcripts. The resulting antisense RNA (aRNA) was quantified by spectrophotometery.
The concentration of RNA in the S5/31 guard cell sample was 5 µg in 22 µl of total volume
of isolated RNA. In M5/31 the concentration was 3.2 µg in 22 µl of total volume of isolated
RNA. cDNAs were made from aRNAs by using gene specific primers and transcript levels
were quantified by Q-PCR. Because there was more aRNA in the S5/31 sample the data
were normalized for the aRNA concentration in the two samples by multiplying the M5/31
data by 1.6 when calculating the absolute transcript levels.
The Q-PCR results (Table 3.13) showed that for all genes (except SUC2 in sample M5/31)
the Ct values were far below the NTC controls. For example, RBCS had a NTC value of
36 which is much higher than Ct values found for this gene in both treatments. Thus, the
transcript levels in these samples are high and the data should be reliable. The Ct value for
SUC2 in M5/31 was very high, close to its NTC control which implies complete absence or
very low expression of this gene in that sample. To reconfirm this finding the M5/31 aRNA
was reassayed for SUC2 and the results confirmed the original Q-PCR data. Except for
HAB1, TPS1, and SUC2, transcript levels for all the genes were higher in the RNA of guard
cells from the mannitol-treated leaves. Table 3.13 also shows the fold difference between
the transcript levels for each gene in the mannitol- and sucrose-treated samples. Each of
the genes investigated was normalized relative to the transcript levels of ACT2 in the same
sample and the results are shown in Figure 3.7. Among all genes assayed, STP1 had the
highest level of expression in both treatments followed by RBCS and SUC1 in mannitol and
KAT1 in both treatments. ADPGase had moderately high expression in both treatments.
Next to ADPGase, HAB1 and TPS1 had moderately higher expression in sucrose than in
mannitol. The lowest level expression was found for SUC2 in both treatments and for CYP
in mannitol treatment. This pattern of gene expression is distinct from that observed for
mesophyll cells and genes that have been reported to be preferentially expressed in guard
cells are more highly expressed in these samples, particularly KAT1, STP1, and ADPGase.
46
Figure 3.7: Gene expression relative to ACT2 in guard cells. STP1 had the highest level of
expression in both treatments followed by RBCS and SUC1 in cells from mannitol-treated
leaves and KAT1 in both treatments. ADPGase had moderately high expression in both
treatments. Next to ADPGase, HAB1 and TPS1 had moderately high expression in sucrose
than in mannitol. The lowest level of expression was found for SUC2 in both treatments and
for CYP in the mannitol treatment.
47
CHAPTER 4
DISCUSSION
The purpose of this study was to determine the feasibility of studying sugar-regulated gene
expression in guard cells of Arabidopsis using RNA extracted from small samples of guard
cells cut out of freeze-dried leaves. Before performing quantitative analysis of gene expression
at the level of individual cells like guard cells, it was important to compare the gene expression
patterns in sucrose-and mannitol-treated leaf strips to get baseline data for evaluating the
effectiveness of RNA isolation and amplification from small clumps of mesophyll cells and
finally from isolated guard cells. The panel of genes studied in these experiments was chosen
to include genes that previous studies had shown to be preferentially expressed in guard
cells (STP1, KAT1, TPS1, ADPGase(AtApl4) and HAB1), genes that are expressed in all
tissues (ACT2, CYP, EF1), genes for two sucrose transporters (SUC1 and SUC2) because of
their potential importance in sucrose responses, and one gene that should be preferentially
expressed in mesophyll cells (RBCS).
4.1
The Problem of Variability between Replicate
Samples
In the baseline study using RNA isolated from leaf strips, we observed some large variations in
gene expression between biological replicates (ranging from a low of 1.6 fold for TPS1 from
sucrose-treated leaves to a high of 152 fold for STP1 from mannitol-treated leaves (data
in Table 3.1). This variability made it difficult to detect statistically significant effects of
sugars on gene expression. In order to find the sources of this large inter sample variation two
experiments were performed. In one experiment triplicate Q-PCR reactions were performed
on cDNAs from each of six different RNA samples (three from sucrose-treated leaf strips and
three from mannitol-treated leaf strips). In a second experiment, three replicate cDNAs were
48
prepared from two different RNA samples, and Q-PCR was performed on these cDNAs. The
results from these two experiments showed that neither the Q-PCR nor the cDNA reaction
was contributing much to the observed inter sample variation (data in Tables 3.2 and 3.3);
rather the primary source of this variability must be some uncontrolled source of biological
variation or differences in the quality and quantity of RNA extracted from the replicate
samples.
A standard approach to dealing with variation between replicates in Q-PCR studies is to
normalize the expression of each gene in a sample to the expression of some internal reference
or control gene. Use of an internal reference should correct for differences in the amount
of RNA in the biological replicates. An ideal internal reference gene is one expressed at
a high level and whose expression is unaffected by the treatment under study. ACT2 is a
commonly used reference gene and its expression has been shown to be unaffected by ABA
treatment in guard cells and mesophyll cells (Leonhardt et al. 2004[41]). ACT2 expression
has also been shown to be unaffected by glucose treatment in seedlings of Arabidopsis (Price
et al. 2004[37]). However, in this study ACT2 expression was induced by the sucrose
treatment. Therefore two additional internal reference genes, CYP and EF1, were evaluated.
Of the three, ACT2 expression was the most consistent, probably because of its high level
of expression. Both CYP and EF1 were expressed at levels close to background, where
measurement errors would be expected to be high. So, although ACT2 was not an ideal
internal reference for this study, it was the best of the genes investigated. Other potential
internal reference genes could have been investigated, but because of the significant time
required to perform those experiments we left it for a future research project. Whenever
ACT2 was used to normalize data in this thesis it was only used to normalize differences
between biological replicates within a treatment and not between treatments. Normalizing
the data using ACT2 expression did reduce the variability between biological replicates. For
example, in the initial experiment on gene expression in leaf strips (Table 3.1) the average
fold difference between replicate samples before normalization was 5 fold for sucrose-treated
samples and 19 fold (ignoring the data for STP1, which was aberrant) for mannitol-treated
samples. Normalization reduced the average fold differences to 3 fold for sucrose-treated
samples and 3.5 fold for the mannitol-treated samples. Similarly, in the experiments on
mesophyll tissue (data in Table 3.8), normalization with ACT2 reduced the differences
between replicates from 5.4 fold to 2.2 fold for sucrose-treated samples and from 6.2 fold
49
to 2.4 fold for the mannitol-treated samples.
4.2
Gene Expression in Leaf Strips and the Effects of
Sucrose
Even with normalization substantial inter sample variation remained. However, for the
experiments with leaf strips so many independent measurements were made that it proved
possible to get a good view of gene expression by pooling the data from all the different
measurements for each gene in each biological replicate. Among the genes assayed we found
that RBCS had the highest level of expression in mannitol-treated leaf strips. The expression
of RBCS was about 3000 fold higher than ADPGase, which had the lowest level expression
in mannitol-treated leaf strips. Next to ADPGase we found CYP, TPS1 and KAT1 were
about 1800-, 1500- and 1200-fold less abundant, respectively, than RBCS in the mannitol
treatment. SUC1 had high expression, about 8 fold below that of RBCS, and the expression
of ACT2 was about 15-fold lower than RBCS. STP1 had moderately high expression in
mannitol-treated leaf strips (about 33 fold lower than RBCS expression) and the expression
of SUC2 and HAB1 were 230- and 400-fold (respectively) below that of RBCS.
Sucrose treatment changed the expression of a number of the genes assayed in the
experiments with leaf strips (Table 3.5). For example, RBCS was down regulated in sucrose
by around 3 fold and this change was highly significant. Many workers have documented
the down-regulation of this gene by sugars (for example, see Krapp and Stitt 1993[61]). The
expression of STP1 may also be down regulated by sucrose in leaf strips. We observed a
5-fold down regulation but the difference was not statistically significant. STP1 has been
reported to be preferentially expressed in guard cells (Stadler et al. 2003[55]). There was
good statistical evidence for the up regulation of three genes in this study, ACT2, HAB1,
and KAT1. ACT2 was up regulated by about 3 fold in sucrose-treated leaf strips and this
observation is consistent with Bates and Outlaw’s unpublished microarray data. HAB1 was
5-fold up regulated in sucrose-treated leaf strips and KAT1 was 4 fold up regulated. Both
of these genes have been reported to be preferentially expressed in guard cells and KAT1
expression has been shown to be enhanced by glucose in Arabidopsis leaves (Price et al.
2004[37]). Two other genes, SUC1 and ADPGase, appear to have been up regulated by
sucrose (6 fold for SUC1 and 16 fold for ADPGase), however each gene was assayed in only
a single experiment and because of variability between replicates the responses to sucrose,
50
although large, were not statistically significant. Lloyd et al. (2004)[52] found that both
SUC1 and ADPGase were up regulated by sugars in a microarray analysis of the Arabidopsis
pho3 mutant. The raw data for CYP showed a 2.9-fold increase in expression in sucrose
and both SUC2 and TPS1 showed a 2-fold decrease in response to sucrose. However, none
of these changes were statistically significant even though each of these genes was assayed
multiple times. Therefore, it is likely that the expression of these genes does not change in
response to sucrose, at least in the leaf strips. TPS1 has been reported to be preferentially
expressed in leaves and repressed by glucose ( Price et al. 2004[37]), however, we were unable
to verify this observation is sucrose-treated leaf strips.
4.3
Gene Expression in Mesophyll Tissue and RNA
Amplification
In the experiments with mesophyll cells we successfully demonstrated that RNA can be
isolated from freeze-dried leaves and analyzed by Q-PCR. For RNA isolation, tissue was
microdissected by hand, based on the experience of Lu et al. (1997)[3], from freeze-dried
leaves that had been treated with sucrose or mannitol. mRNA isolation and measurement
from small clumps of tissue and even from single cells have been reported for plants (Brandt et
al. 1999[44]; 2002[45]; Laval et al. 2002[46], Kerk et al. 2003[47]), but in this study we showed
the feasibility of RNA isolation and measurement from freeze-dried leaves of Arabidopsis.
Because we could not accurately weigh each sample of mesophyll tissue before RNA isolation
and analysis, it was anticipated that the samples would contain different amounts of RNA
and indeed large differences were observed in the expression of each gene between replicate
samples. However, normalization to ACT2 reduced the inter sample variation to two to three
fold depending on the gene. Also, the expression profiles of the genes (the order from the gene
with the highest expression to that with the lowest) was very similar for replicate samples.
Comparison of the gene expression profiles for leaf strips and mesophyll cells showed a 0.90
value of rank correlation coefficient in the sucrose-treated samples and 0.87 in mannitoltreated samples. This observation was expected since mesophyll cells make up the majority
of cells in leaves. Moreover, genes that other groups had designed as preferentially expressed
in guard cells (STP1,KAT1, TPS1, ADPGase(AtApl4) and HAB1) were expressed in low
levels in RNA isolated from mesophyll cells. The expression of SUC2 was also found to be
very low. This was expected since this gene has been reported to be expressed specifically in
51
phloem (Truernit and Saucer 1995[50]; Stadler and Saucer 1996[51]). Only HAB1 expression
showed a statistically significant change in response to sugar treatment (induction by sucrose)
and that was in the normalized data. Had the experiment been done in triplicate, rather than
in duplicate, it would have improved the data statistically. Surprisingly RBCS expression
was higher in the sucrose-treated samples than in the mannitol-treated samples, which is
the opposite of what was observed for leaf strips and is contrary to what is reported in the
literature. This observation is also likely due in part to the lack of sufficient replication of
the experiment. However, one of the mannitol-treated mesophyll RNA samples, M6/2, had
by far the lowest gene expression, suggesting this sample may have been partially degraded.
After reproducibly isolating and analyzing RNA from microdissected mesophyll cells we
turned to RNA amplification. RNA isolated from mesophyll cells was diluted 100 or 1000
fold and amplified one round using T7 RNA polymerase. These RNA dilutions were designed
to simulate the tiny RNA samples expected from samples of 50 guard cells. In both dilution
experiments gene expression was detecteble, although in the RNA samples that were diluted
1000 fold, those genes whose expression was low in undiluted mesophyll RNA samples were
at the lower limit of detection in the diluted and amplified samples. The level of transcripts
before and after dilution and amplification was similar. The ratios of the average number
of transcripts detected for each gene in biological replicate samples ranged from 0.71 to
1.6 (indicating a 710 fold to 1600 fold amplification with T7 RNA polymerase). However,
there were some differences in the degree of amplification for individual genes. SUC2 tended
to be amplified less than the other genes investigated and CYP amplified more than the
others. These two genes were expressed at levels very near background (1 × 10−7 ng of
transcripts) in both the undiluted samples and the diluted and amplified samples. Thus,
the measurements for these genes are expected to be the least accurate. Also, amplification
was greater for sample M6/2 than the other three samples, and this was observed for all
the genes in that sample except RBCS. Difficulties with sample M6/2 have already been
pointed out. In samples S5/31, S6/2, and M5/31 the ratios of RBCS transcripts after and
before amplification were 0.9, 1.0, and 1.5 respectively, but in sample M6/2 the ratio was
0.37. In fact, gene expression in sample M6/2 was the lowest of all the samples and the
transcript levels for the highly expressed genes, SUC1 and RBCS, were particularly low in
this sample. This is further evidence that the RNA in this sample was odd and possibly
partially degraded.
52
4.4
Measurement of Gene Expression in Guard Cells
The amount of RNA after 1000 fold dilution was estimated to give approximately the same
amount of RNA as would be expected from 40 to 50 guard cells. This number of guard
cells was manageable for us to microdissect, however microdissection of 40 to 50 Arabidopsis
guard cells was a really difficult task in one sitting. Thus, we microdissected 10 to 12 guard
cells at a time until we accumulated 50 guard cells. Because detection of gene expression
was difficult in the RNA samples that had been diluted 1000 fold, it was decided that the
samples of guard cell RNA would be amplified through two rounds with T7 RNA polymerase
rather than one round. After amplification, high levels of transcripts were detected in the
guard cell RNA samples for nearly all the genes. CYP expression was very low in guard cells
from sample S5/31 as was SUC2 expression in guard cells from sample M5/31. Whether
these results reflect the real level of expression of those genes or are simply due to failure
of those genes to amplify is unclear. As shown in Figure 4.1, the gene expression profile in
guard cells was quite different than that for mesophyll cells or leaf strips. ADPGase, CYP,
Figure 4.1: Comparison of gene expression profiles in mannitol-treatmed leaf strips, mesophyll tissue, and guard cells. STP1, CYP, KAT1, ADPGase and TPS1 were preferentially
expressed in guard cells. RBCS had highest level of expression in leaf strips but this gene
also found to be expressed unexpectedly high in guard cells. SUC1 and HAB1 had relatively
same level of expression in three sources, whereas SUC2 had lowest expression in guard cells.
53
KAT1, STP1 and TPS1 were all expressed at levels 100 fold higher in the guard cell samples
than in the mesophyll samples. Except for CYP, each of these genes has been reported to be
preferentially expressed in guard cells in other studies (Stadler et al. 2003, Leonhardt et al.,
2004). The expression of RBCS was unexpectedly high in the guard cell samples. Perhaps
Arabidopsis guard cells are different in terms of RBCS expression than other species that
have been more extensively studied (for example Vicia), or perhaps the low light intensities
in which our plant material was grown resulted in increased RBCS expression in the guard
cells. Because only one guard cell sample was assayed for sucrose and for mannitol treatments
little can be concluded about the effect of sugars on guard cell gene expression. The results
suggest that TPS1 might be induced by sucrose and SUC1 may be repressed. However,
further replication would be required to draw any serious conclusions.
Taken together the results of this study demonstrate the feasibility of studying gene
expression in guard cells and other sub microgram-sized tissue samples of plants. It was
found that RNA could be isolated from freeze-dried tissues, amplified, and analyzed by QPCR. Similar gene expression profiles were obtained for mesophyll cells and leaf strips and
for mesophyll cells before and after RNA amplification, all of which supports the reliability
of the RNA isolation and amplification process. Additional supporting evidence is provided
by the observation of tissue-specific gene profiles for mesophyll cells and for guard cells
that were largely consistent with what is know for these cell types from the literature.
Because of variability between replicate samples and the lack of sufficient replication in
these experiments little can be concluded about the effects of sugars on gene expression in
guard cells or mesophyll tissues. However, with increased replication and with the addition
of RNA profile analysis following T7 RNA polymerase amplification, these approaches could
become a powerful tool for cell-specific gene expression in Arabidopsis.
54
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BIOGRAPHICAL SKETCH
Name:
Occupation:
Maitreyi Chattopadhyay
Teaching and Research Assistant, Department of Biological
Science Florida State University
Education:
M.S. in Cell and Molecular Biology, 08/2004-spring 2006, Department of Biological Science, Florida State University, Tallahassee, FL
Post Graduate Diploma in Environment Management, 08/199508/1997, Indian Institute social welfare and Business management, Calcutta, India.
B.S. Of Botany (Hons.), 08/1992-08/1995, University of Calcutta. Calcutta, India
Research Position:
08/2004 08/2006
Internship:
Teaching Experience:
Teaching and Research Assistant, Department of Biological
Science, Florida State University Tallahassee, Fl
Barn Standard Company LTD, Howrah, India (Govt. of India)
and did a project on Air and Water pollution in 1997.
• Organized and guided introductory Biology lab (major)
• Teaching Assistant for Biology Lecture Course for majors.
Research Experience:
• Used Q-PCR to evaluate gene expression profile in microdissected mesophyll cells and guard cells of Arabidopsis
thaliana.
• Used freeze dried tissue to microdissect mesophyll cells and
guard cells by hand.
• Used Bioinformatics tool (GCG Software) to design gene
specific primers to study gene expression.
61
• Used Northern blot analysis to study gene expression in
leaf strips of Arabidopsis thaliana.
62