1 Laboratory of Plant Molecular Biology, The Rockefeller University, 1230 York
Avenue, New York, NY 10021, USA
2 E. I. DuPont de Nemours, DuPont Agriculture & Nutrition Molecular
Genetics, PO Box 6104, Newark, Delaware 19714-6104, USA
* Author for correspondence (e-mail: chua{at}rockvax.rockefeller.edu)
Accepted 19 September 2002
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Summary |
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Key words: ABA, Gene expression, abi1, MPSS, Stress response, Growth
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Introduction |
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Analysis of ABA mutants has identified some components of the signaling
network. Three classes of mutants: ABA-deficient, -hypersensitive, and
-insensitive mutants have been characterized. In ABA-deficient mutants,
ABA-induced stomatal closure and expression of some genes are impaired leading
to a wilty phenotype (De Bruxelles et al.,
1996; Seo et al.,
2000
; Taylor et al.,
2000
; Xiong et al.,
2001
; Xiong et al.,
2002
). Several Arabidopsis mutants display ABA
hypersensitivity resulting in diminished germination rates at low ABA
concentrations and reduced water loss due to enhanced ABA-induced stomatal
closure (Cutler et al., 1996
;
Lu and Fedoroff, 2000
;
Hugouvieux et al., 2001
;
Steber and McCourt, 2001
).
ABA-insensitive mutants including abi1 to abi5 and
gpa1 are affected in ABA-mediated inhibition of germination and
growth and they are also impaired in stomatal movement
(Leung and Giraudat, 1998
;
Koornneef et al., 1984
;
Wang et al., 2001
). Changes in
ABA-regulated gene expression result from mutations in the putative
transcription factors ABI4 and ABI5
(Finkelstein and Lynch, 2000
;
Lopez-Molina and Chua, 2000
;
Söderman et al., 2000
).
ABI1 and ABI2 encode protein phosphatases 2C. Although no
target protein has yet been identified, an impaired expression of a few
reported genes in abi1-1 and abi2-1 suggests that
dephosphorylation events may regulate ABA-mediated gene expression
(Gilmour and Thomashow, 1990
;
Leung et al., 1994
;
Meyer et al., 1994
;
Gosti et al., 1995
;
Strizhov et al., 1997
;
Uno et al., 2000
). It is,
however, not conclusively known whether the dominant abi1-1 and
abi2-1 mutations are neomorphic or whether ABI1 and ABI2 are indeed
components of ABA signaling because no null allele lacking phosphatase protein
expression has yet been isolated. Although suppressor mutants of
abi1-1 lack phosphatase activity, they still produce mutant proteins
that may have a signaling function, which is independent of its phosphatase
activity (Gosti et al.,
1999
).
In addition to the analysis of ABA signaling mutants, the use of
microinjection identified cyclic ADP ribose (cADPR) as an early mediator of
ABA responses. The ABA signal is transduced and sustained by increases in
cytosolic [Ca2+] stimulated by cADPR and phosphoinositides,
respectively (Wu et al., 1997;
Sanchez and Chua, 2001
).
Nevertheless, a link between the nature of [Ca2+] oscillations and
gene expression has not yet been shown in plants
(McAinsh et al., 2000
;
Schroeder et al., 2001
).
Despite substantial advances in the understanding of ABA-mediated
transcriptional control, only a few regulatory components have been identified
thus far. In view of the diversity and complexity of the signaling network
underlying physiological responses to ABA and the potential crosstalk with
other signaling pathways, many fundamental mechanisms remain to be resolved.
One approach is the identification of ABA-regulated genes on a genome-wide
scale. Whereas the regulation of single genes can be easily examined by RNA
gel blot hybridizations or RT-PCR, DNA microarrays provide a tool to monitor
changes in expression levels of a larger number of genes simultaneously
(Desprez et al., 1998;
Schaffer et al., 2001
;
Schenk et al., 2001
;
Seki et al., 2001
). However,
plant DNA microarrays represent closed systems that prevent whole genome scans
of gene expression. Prior to the very recent release of the Affymetrix
GeneChip Arabidopsis ATH1 (approximately 24,000 genes represented), the only
available plant DNA microarrays carried a limited number of genes. To monitor
ABA-dependent gene expression on a genome-wide scale, we used MPSS on WT and
abi1-1 samples. The MPSS technique combines the physical separation
of complex nucleic acid samples by in vitro cloning of templates on microbeads
with ligation-based signature sequencing
(Brenner et al., 2000a
;
Brenner et al., 2000b
).
Starting from the GATC site closest to the polyA tail, 17-base long sequences
are collected from the cloned cDNA molecules and the frequency of occurrence
of each sequence is counted to determine the transcript abundance. The
availability of the Arabidopsis genomic sequence and information on
numerous expressed sequence tags allowed us to assign the signature sequences
to annotated genes and obtain the transcript level of all expressed genes.
Here, we report a genome-wide gene expression study identifying 1354 ABA-responsive genes in Arabidopsis. We have uncovered gene subclasses previously not known to be regulated by ABA. In the ABA-insensitive mutant abi1-1, the ABA response of about 84.5% of the identified genes was dramatically altered. Nearly 9% of the ABA-responsive genes are regulated by a separate pathway that is insensitive to the abi1-1 mutation. The gene expression in abi1-1 was impaired in the absence of ABA suggesting that the dominant negative mutation also acts independently of exogenous ABA.
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Materials and Methods |
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RNA gel blot analysis, RT-PCR and expression of GFP fusions in onion
cells
RNA gel blot analysis was performed as described
(Ausubel et al., 1994). Each
lane contained 10 µg total RNA. 200-250 bp fragments from the 5'-end
or 3'-regions of the indicated genes were amplified using HotStarTaq DNA
Polymerase (Qiagen, Valencia, CA). The fragments were purified using the
Qiaquick Gel extraction protocol (Qiagen), verified by sequencing analysis and
labeled with 32P-dCTP and 32P-dATP by random priming
(Amersham, Arlington Heights, IL). Hybridization signals were monitored using
the STORM phosphoimager system and analyzed using the ImageQuant software
(Molecular Dynamics, Sunnyvale, CA).
RT-PCR was performed using the Titan one tube RT-PCR system (Roche Molecular Biochemicals, Mannheim, Germany) according to the manufacturer's protocols. 20 cycles of PCR amplification were used for each of sample except the control actin-2, which was detected at 15 cycles. The primers used for PCR amplification of At5g57520 were 5'-GGACTACCAGCCAAACACATCCCTACGTC-3' and 5'-CCACTCTCCGGCACACGGCGGGC-3'; primers used for At2g46510 were 5'-CTCCTCGGCCACGATGTCTCTCCGC-3' and 5'-CATAATCCGCCAAAATCTCTTCCATTCCTTC-3'; primers used for At2g35940 were 5'-CACGATGAAGATTCTAGAAGAACGGCAAGGG-3' and 5'-CGGTTTCTCCTTCGAGAGAGATGGGTTTATGC-3'; primers used for At4g18160 were 5'-GAGTAAAGCAGAGTATGTGATATACAAACTGAAGGAGATGG-3' and 5'-GATGTGAATCCAGTGAATCCTGCTTAACCAATTATGC-3'; primers used for At3g43600 were 5'-CCACCCGATTCACAAGCGGTTATCCGG-3' and 5'-CCTCTGAGCCATTCACAAGGTTTCCACC-3'; primers for actin-2 (U37281) were 5'-GCCGGACTTACCGTTGTATGTACCGTCC-3' and 5'-ACAATGGAACTGGAATGGTGAAGGCTGG-3'. Amplified DNAs were separated in a 1.6% agarose gel. All DNA bands resulting from the RT-PCR reaction were tested for RNAase A sensitivity.
For transient expression in onion epidermal cells, the GFP coding
sequence was fused in-frame to the 3' ends of the ABI1 and
abi1-1 cDNAs as previously described
(Kost et al., 1999).
ABI1 and abi1-1 cDNAs were generated by using primers to
amplify the coding region from the ATG start codon
(5'-CGACTTCTCGAGATGGAGGAAGTATCTCCGGC-3') with an additional
XhoI site, to the TGA stop codon
(5'-GCGAACTGAGGTACCGTTCAAGGGTTTGCTCTTG-3') thus adding a
KpnI site and deleting the stop codon. GFP localization was monitored
14-16 hours after transfection of onion cells.
Data acquisition and analysis
In vitro cloning of polyA RNA, formation of microbead libraries, sequencing
of DNA on microbeads and base calling were performed as described
(Brenner et al., 2000a;
Brenner et al., 2000b
). The
number of signatures collected (corresponding to the number of mRNA molecules
analyzed) was 1,477,653 for the WT control sample, 1,266,435 for the WT
treated sample, 1,656,984 for the abi1-1 control sample, and
1,241,725 for the abi1-1 treated sample. Four separate sequencing
runs were performed for each sample to produce the total number of signatures.
Abundance for each distinct signature was counted and normalized in parts per
million to estimate transcript abundance. Differences in expression levels
were deemed significant when the ratio of the abundances was at least 3 and/or
statistically significant at the 0.0005 level as determined on the basis of
the total number of signatures collected in each sample using a formula
previously described (Audic and Claverie,
1997
). When the lower parts per million (ppm) count was less than
10, larger fold ratios are required in order to be statistically significant.
For comparison of ABA-responsive gene expression in the abi1-1 mutant
to WT we considered a twofold change at the 0.0005 level to be statistically
significant in abi1-1. In the supplementary data
(http://jcs.biologists.org/supplemental)
`induced.xls' and `repressed.xls' we marked each gene with one of the
following codes (column J): code 0, if the expression of the particular gene
is ABA-responsive in WT but ABA-insensitive in abi1-1 [e.g. the
induction factor in abi1-1 (column G) is not significant (n.s.)];
code 1 for comparable regulation in WT and abi1-1, if the quotient of
the induction factor in WT (column D) and the induction factor in
abi1-1 (column G) is in a range between 0.5 and 2; code 2 for similar
regulation, if the particular gene is ABA-sensitive in both WT and
abi1-1 but to a different extent. The quotient of the induction
factor in WT (column D) and the induction factor in abi1-1 (column G)
is greater than 2 or less than 0.5; code 3 for genes that are induced by ABA
in WT but repressed in abi1-1 or vice versa. In this case, the
induction factor in abi1-1 (column G) is less than 0.5.
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Results |
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Verification of the MPSS data
To verify the results obtained with MPSS we isolated RNA samples from two
independent but otherwise identical ABA treatments that were performed by
different investigators. We confirmed the MPSS data
(Fig. 2A) by RNA gel blot
analyses, using as probes newly identified ABA-responsive genes encoding
proteins with very different functions. These include a putative NPK1-related
MAP kinase (At1g05100), a putative protein phosphatase 2C (At1g07430), the
ethylene responsive element binding factor 4 (At3g15210), a citrate
synthase-like protein (At3g58750), a putative RNA-binding protein (At1g09340),
and the MAP kinase AtMPK6 (At2g43790). For some ABA-regulated genes that were
expressed at very low levels in both induced and control samples (3-27 ppm),
the MPSS data were confirmed by RT-PCR
(Fig. 2B). These included the
zinc finger protein ZFP2 (At5g57520), a putative bHLH transcription factor
(At2g46510), a putative homeodomain transcription factor (At2g35940), a
potassium channel-like protein (At4g18160), and AtAAO2 (At3g43600). Besides
confirmation of the results through other techniques, the MPSS data set was
also confirmed by analysis of the regulation of the large number of
ABA-upregulated genes previously reported in the literature.
Table 1 shows a list of
ABA-responsive genes including the prominent marker genes KIN2, KIN1,
COR47, RD20, and COR15A. Note, that the expression of the actin
genes ACT2 and ACT8, which are frequently used as internal
controls in gene expression experiments, was not affected by ABA.
|
|
Functional classification of ABA-responsive genes
The classification of genes into groups of similar function is one approach
to understanding gene reguation by ABA at the genomic level. We performed a
functional classification based on the classification of the MIPS database. In
addition, protein-protein BLAST analysis enabled the identification of
characteristic protein motifs suggesting putative gene functions.
Fig. 3 summarizes our
classification of ABA-responsive genes into 9 different groups. In the
Arabidopsis genome many genes still do not have a clearly defined
function and are therefore referred to as `unclassified'. The fraction of
unclassified genes is more prominent among the downregulated genes. The
proportion of genes induced or repressed in most categories did not differ.
However, there were significant differences in the number of genes belonging
to the `Cell rescue, defense, ageing' class. Less than 1% of all downregulated
genes was related to cell rescue and defense, whereas more than 5% of the
upregulated genes belong to this group. This is consistent with the role of
ABA in plant stress responses.
|
The ABA mutant abi1-1 is largely affected in gene
expression
Although the abi1-1 mutant had been previously reported to be
impaired in ABA-responsive gene expression, the analysis was limited to only a
few genes (e.g. Gilmour and Thomashow,
1990; Leung et al.,
1997
; Leung and Giraudat,
1998
). To extend this analysis to the whole Arabidopsis
genome, we performed the same MPSS analysis on RNA samples isolated from
abi1-1 mutant plants. The majority of signature sequences, which were
ABA-responsive in WT, were not differentially regulated in abi1-1
(Fig. 4). Of the 1354
ABA-responsive genes 75.2% were unaffected and 9.3% showed inverse regulation
by ABA in abi1-1 (supplementary data, `induced.xls' and
`repressed.xls', code 0 and 3, respectively). About 7% of the genes were still
responsive to ABA in abi1-1 albeit with a diminished induction or
repression (supplementary data, `induced.xls' and `repressed.xls', code 2).
Nearly 9% of the genes such as the transcriptional activators HB8
(At4g32880) and NAC1 (At1g56010) showed very similar transcript
levels and regulation in both abi1-1 and WT indicating that their
ABA-mediated expression is insensitive to abi1-1 (supplementary data,
`induced.xls' and `repressed.xls', code 1). Surprisingly, an induction of
ABI1 itself was observed in both WT (from 41 up to 671 ppm) and
abi1-1 (from 52 ppm up to 157 ppm), although to slightly different
levels. This result is at variance with the impaired upregulation of
ABI1 in abi1-1 after 55 hours of ABA incubation reported by
Leung et al. (Leung et al.,
1997
). To investigate the time-dependent transcriptional control
of ABI1, we performed a detailed kinetic analysis of ABA induction.
RNA gel blot analyses demonstrated a dramatic upregulation of ABI1
after 1 hour ABA but not after mock treatment
(Fig. 5A). The transcription
level reached a peak after 4 hours and decreased slightly after more than 5
hours. In the dominant mutant abi1-1 the mutant abi1-1 gene
exhibited the same induction kinetics indicating that ABI1 does not
control its own early ABA-mediated expression. The homologous ABI2
was ABA-responsive in WT like ABI1, but its induction was abolished
in the abi1-1 mutant (Fig.
5A).
|
|
In contrast to WT samples, only 24764 and 24044 unique signature sequences
were found in ABA-treated and untreated abi1-1 samples, respectively.
This suggests that fewer genes were expressed in the mutant even under control
conditions. We identified 194 genes that were expressed at a highly
significant level in WT plants (ppm22), but not in abi1-1
irrespective of the treatment (ppm=0). These 194 genes could be subdivided
into two groups: (1) 71 genes induced by more than threefold by ABA; and (2)
123 genes the expression of which is independent of the hormone.
As the abi1-1 mutation caused dramatic changes in gene expression, we studied the subcellular localization of the WT and mutant protein by introducing ABI1-GFP and abi1-GFP fusion genes into onion epidermal cells using a particle gun. Expression of both fusion proteins was observed in the cytoplasm and in the nucleus (Fig. 5B) indicating that the mutation did not affect the subcellular localization of the protein.
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Discussion |
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Compared with cDNA-microchip experiments, MPSS offers several advantages.
(1) The problem of cross-hybridization between highly homologous sequences in
cDNA-microchip experiments is not encountered, thereby ensuring much higher
gene specificity. In 97.2% of all the signatures, 17 bases were sufficient to
uniquely identify the corresponding gene in the Arabidopsis genome.
This discrimination, even between members of highly homologous gene families,
cannot always be obtained in microarray experiments. (2) The MPSS technique
offers a high resolution through very deep sampling, thus providing
information about genes expressed at very low levels
(Brenner et al., 2000b). (3)
Previous knowledge of genes is not required for MPSS. In microarray
experiments DNA fragments of annotated genes are spotted as probes. The still
evolving annotation of the Arabidopsis genome therefore results in a
partial loss of information obtained from DNA microarrays whilst the complete
information of the MPSS experiment survives this evolution.
In comparison with techniques that depend on hybridization of probes to
microarrays followed by the detection of a fluorescent signal, techniques
based on counting of signatures of DNA fragments [so called digital northern
blots (see Audic and Claverie,
1997)] are statistically more robust, especially when the size of
the sample that is being counted is very large. The counting statistics are
well modeled by the Poisson distribution
(Audic and Claverie, 1997
) and
confidence intervals that account for sampling errors can be assigned to the
data without the need for repetitions. These confidence intervals have to be
interpreted as the boundaries for abundance estimates that could be obtained
by analysing the same starting material multiple times (i.e. they refer to the
error in measuring the abundance of each transcript) but do not take into
consideration possible variations arising from the use of different biological
materials that are being investigated (i.e they do not address the possibility
that the variation among two experiments is due to factors other than the
treatments being applied to them). In view of the costs of MPSS experiments we
addressed this issue in different ways. (1) The RNA samples were isolated
after treatment of at least 250 seedlings for each sample, thus providing an
average of plants at the same developmental stage. (2) We have selected a very
stringent significance level (at least a threefold change and
P<0.0005) in spite of the high sensitivity of the MPSS technique.
Changes lower than threefold were not regarded as biologically significant.
(3) The regulation of several novel ABA-dependent genes was confirmed by RNA
gel blot analyses or RT-PCR (Fig.
2). For these confirmations we performed two independent but
otherwise identical ABA treatments that were performed by two different
investigators. Following these independent treatments we were able to confirm
ABA-induced changes in gene expression at very low transcript levels by RT-PCR
(Fig. 2). In addition, we
uncovered many genes whose ABA responsiveness has been previously reported,
thus verifying our results (Table
1). This list is not exhaustive for different reasons. For
example, some genes are ABA-regulated in embryos but not in seedlings and
different ABA concentrations and incubation times used in other studies could
yield different results. A detailed kinetic analysis of induction would be a
prerequisite to relate changes at the transcriptional level to physiological
responses. Transcripts in which the GATC sequence is either lacking (not
clonable) or more than 1000 bases away from the polyA end (not amplified well)
and those that form a double palindrome (not sequencable) would not be
detected by MPSS.
Many new gene targets are regulated by ABA
By extending the study of ABA-responsive gene expression to the genomic
scale, we have identified large numbers of ABA-responsive genes that encode
putative ABA signaling components including transcription factors, kinases,
and phosphatases (Fig. 3). In
addition, we discovered gene families that have not previously been reported
to be ABA-regulated. As examples, we discuss genes encoding ribosomal proteins
and proteins involved in regulated proteolysis. (1) Transcription factors and
DNA-binding proteins: protein biosynthesis is required for ABA induction of
some genes (Shinozaki and
Yamaguchi-Shinozaki, 1996). The proteins that need to be
synthesized include transcription factors that in turn amplify gene expression
in a secondary response. We identified about 100 genes that encode
transcription factors or DNA-binding proteins whose expression was regulated
by ABA. This suggests that a cascade of transcription factors may mediate
stimulus-dependent gene expression in ABA responses. (2) Ribosomal proteins
decorate the rRNA cores of each ribosome subunit to stabilize their tertiary
structure and control the dynamics of protein biosynthesis. Individual
ribosomal proteins may play roles in regulating cell growth, proliferation,
and death (Naora, 1999
;
Maguire and Zimmermann, 2001
).
Protein expression studies in maize suggested that ribosomal subunit
heterogeneity at the tissue or cellular level might regulate the efficiency of
the translation machinery (Szick-Miranda
and Bailey-Serres, 2001
). In Arabidopsis none of the 249
genes encoding ribosomal proteins is single copy and most proteins might be
encoded by three or four expressed genes thus producing ribosome heterogeneity
(Barakat et al., 2001
). Here,
we show that ABA contributes to the regulation of ribosomal proteins at the
transcriptional level. Whereas only five genes encoding ribosomal proteins
were induced, 16 genes were downregulated by ABA treatment. This may result in
a diminished overall protein biosynthesis or an altered pattern of protein
expression in plants confronting stress. (3) Proteins involved in regulated
proteolysis: regulated proteolysis mediated by the ubiquitin-proteasome system
is a key regulatory component of many cellular processes including cell cycle
control, transcription, and receptor desensitization
(Ciehanover, 1998
;
Kirschner, 1999
). Recently,
Lopez-Molina et al. demonstrated that the bZIP factor ABI5 is rapidly degraded
in the absence, but not in the presence, of ABA
(Lopez-Molina et al., 2001
).
This degradation can be blocked by inhibitors of the 26S proteasome suggesting
that the ubiquitin-proteasome system may play a role in ABA signaling.
Table 2 summarizes the
regulation of 25 genes coding for proteins putatively involved in regulated
proteolysis. Three quarters of these genes are upregulated, eight of them more
than tenfold. ABA might trigger the controlled degradation of a variety of
cellular regulatory proteins via the ubiquitin pathway. The gene products
include hypothetical proteins with RING finger motifs, F-boxes, or U-boxes,
which may interact with target proteins of the ubiquitin-proteasome pathway
(del Pozo and Estelle, 2000
;
Azevedo et al., 2001
). The
ABA-mediated repression of other genes encoding proteins related to the
pathway suggests that ABA can also block protein degradation as shown for
ABI5. (4) Kinases and phosphatases: protein phosphorylation/dephosphorylation
events represent key steps in signal transduction. Twenty-nine and 31 protein
kinase genes were induced and repressed following ABA treatment. By contrast,
protein phosphatase genes were almost exclusively upregulated and they
predominantly encode type 2C protein phosphatases including ABI1,
ABI2 and AtPP2C. All three gene products have been suggested to
act in the ABA signaling network, thus correlating ABA-induced expression of a
gene with its function in the signaling pathway
(Leung et al., 1994
;
Meyer et al., 1994
;
Sheen, 1998
). We found that
the transcriptional upregulation of ABI1 by ABA was detected 1 hour
after treatment. This early ABA response was unaffected in abi1-1,
indicating that the mutation does not block its own early ABA-responsive
expression (Fig. 5A). However,
ABA induction of ABI2 was abolished in abi1-1
(Fig. 5A). ABI2 may therefore
act downstream of ABI1, thus explaining why an abi1-1/abi2-1 double
mutant is not more resistant to ABA than the single mutants
(Finkelstein and Somerville,
1990
). It has recently been suggested that in guard cells the
abi2-1 mutation disrupts early ABA signaling downstream of the
abi1-1 mutation (Murata et al.,
2001
).
|
In the presence of ABA, dephosphorylation events may activate or inhibit
transcription factors. However, target proteins for dephosphorylation have not
yet been identified. Alternatively, ABI1-mediated dephosphorylation could be
involved in determining the cytosolic Ca2+ concentration thereby
controlling transcription. In fact, it has been reported that the
abi1-1 mutation reduced the ABA-induced elevation in cytosolic
[Ca2+] in Arabidopsis guard cells
(Allen et al., 1999). In
animals cells, the nature of [Ca2+] oscillations determines gene
expression (Dolmetsch et al.,
1998
; Li et al.,
1998
). It is possible that ABA-induced [Ca2+]
oscillations also optimize the efficiency and specificity of gene expression
in guard cells.
Dissecting the regulation of gene expression in response to drought
and ABA
In spite of the number of experimental parameters that affect gene
expression data, our results correspond well with those obtained by
full-length cDNA microarray experiments on drought-induced gene expression.
Using an array with 1300 spotted cDNAs, Seki et al. identified 14 known and 30
new drought-induced genes (Seki et al.,
2001). Comparing our results with these data we determined a
two-thirds correspondence (Table
3). Large differences in abundance ratios seen in array and MPSS
data may be explained by a combination of two factors. First, the treatments
of plant samples used in both experiments are very different. Second, these
differences may reflect the higher dynamic range of MPSS compared to arrays.
The correlation between the ratios from the MPSS and the array experiment is
significant for genes that are highly expressed in the absence of ABA [e.g.
above 50 ppm (r=0.79, P<0.001)]. However, the correlation
is not significant for genes with expression levels below 50 ppm in the
absence of ABA (r=0.26, P=0.472). For these lowly expressed
genes the ratios from MPSS are significantly higher than those from microarray
experiments (Mann-Whitney U test P=0.025). This may indicate that
ratios from array experiments may be underestimated for lowly expressed genes
because of high background.
|
The majority of drought-responsive genes may therefore require ABA as a
mediator of the drought response. Genes that are inducible by drought but not
by ABA are targets of an ABA-independent pathway
(Shinozaki and Yamaguchi-Shinozaki,
2000). This pathway has been postulated because genes that are not
responsive to exogenous ABA are still induced by dehydration in ABA-deficient
mutants (Ingram and Bartels,
1996
). Different cis-acting promoter elements, ABREs (ABA-response
elements), have been identified through the functional dissection of promoter
regions of ABA-responsive genes (Busk and
Pagès, 1998
; Leung and
Giraudat, 1998
; Seki et al.,
2001
; Shinozaki and
Yamaguchi-Shinozaki, 2000
). However, ABRE-like motifs are not
involved in the regulation of all known ABA-responsive genes
(Iwasaki et al., 1995
). The
large number of new ABA-responsive genes described in this study provides a
basis for the identification of additional cis-acting elements and a better
understanding of the contribution of different cis-acting elements to
ABA-dependent gene expression. This could also help to dissect the different
signaling pathways involved in stress responses.
What is the role of the abi1-1 mutation in gene
expression?
The ABA-insensitive mutant abi1-1 is affected in many different
ABA-dependent processes during early development as well as in the adult
plant. The impairment of ABA-responsive expression of few genes in
abi1-1 has been previously reported (e.g.
Gilmour and Thomashow, 1990;
Leung et al., 1997
;
Leung and Giraudat, 1998
).
Using MPSS we have extended this analysis to the genomic scale and shown that
the abi1-1 mutation results in a dramatic impairment of
ABA-responsive transcription (supplementary data;
Fig. 4). A possible explanation
for this impairment could be that the mutation changes the localization of the
protein within the cell. However, the subcellular localization of both the WT
and the mutant phosphatase protein is identical and therefore cannot account
for the observed differences (Fig.
5B). Assuming that ABI1 acts in the ABA pathway and that the ABA
signal is transduced in a single linear pathway, all ABA-responsive genes
should be deregulated in the abi1-1 mutant. Nonetheless, our results
show that some genes continue to be regulated by ABA as in WT plants. This
indicates the existence of a separate ABA pathway that still operates in
abi1-1. Future investigations of the transcriptional control of genes
that are unaffected by the abi1-1 mutation will help to identify
signaling components of this second pathway. The genomic-scale expression
profiling also revealed that a large number of ABA-responsive genes are
expressed in WT but not in abi1-1 even in the absence of exogenous
ABA (c.f. Strizhov et al.,
1997
). Thus, these genes may respond to low levels of endogenous
ABA through high affinity ABA-responsive elements. Furthermore, this
observation suggests that endogenous ABA concentrations may play an important
role in normal cellular processes. A detailed analysis of signature sequences
that differ between WT and abi1-1 may shed light on these processes
which may not necessarily be related to stress responses (S.H., M.M., S.V.T.
and N.-H.C., unpublished).
Supplementary data
Two separate Excel-files, `induced.xls' and `repressed.xls', provide the
660 induced and the 694 repressed genes, respectively. Besides the respective
signature sequence, the MIPS-ID and the gene, the tables provide the
induction/repression factor, the normalized abundances in parts per million
for WT as well as abi1-1, and the putative functional category of the
gene product. If the abundance in one condition was 0 ppm it was considered 1
ppm to determine the factor of change. Column J contains a code that is
described in Materials and Methods.
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Acknowledgments |
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![]() |
References |
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