JXB Advance Access originally published online on November 16, 2006
Journal of Experimental Botany 2007 58(2):229-240; doi:10.1093/jxb/erl163
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RESEARCH PAPER |
Barley transcript profiles under dehydration shock and drought stress treatments: a comparative analysis
1Department of Agroenvironmental Sciences and Technology, University of Bologna, 40127 Bologna, Italy
2Department of Biochemistry, University of Arizona, Tucson, AZ 85721, USA
3Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
To whom correspondence should be addresssed. E-mail: roberto.tuberosa{at}unibo.it
Received 17 February 2006; Accepted 21 August 2006
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Abstract |
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A microarray including 1654 cDNAs, mainly derived from dehydration-shocked barley leaf tissues, was utilized to monitor expression changes in leaves of barley plants subjected to slow drying conditions (7 d and 11 d: 7d-WS and 11d-WS) in soil and after rehydration. The results were compared with those obtained under shock-like conditions imposed with a 6 h dehydration treatment. A total number of 173 transcripts (
10% of all transcripts profiled) were declared up- or down-regulated in at least one of the conditions tested. The majority of the transcripts were regulated by only one of the drought treatments, with 57% of the differentially expressed transcripts exclusively affected in the dehydration shock treatment, 6% at 7d-WS, 14% at 11d-WS, and 6% after rehydration. Irrespective of the low percentage of transcripts (10%) with similar expression changes between shock and slow stress treatments, a sizeable portion of these transcripts shared a common expression trend under the different drought treatment conditions, as evidenced by low but significant correlations between the fast occurring and the 7d-WS and 11d-WS treatments (r=0.32 and 0.41, P=0.001, respectively). These results are discussed with respect to the merit of different dehydration treatments in the investigation of the changes in transcript profiling. Key words: Barley, cDNA microarray, dehydration shock, drought stress, drought-responsive transcripts
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Introduction |
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TopAbstractIntroductionMaterials and methodsResults and discussionConclusionsReferences |
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Drought stress influences plant growth and severely limits crop productivity (Passioura, 1996; Blum, 2000). Consequently, efforts are directed towards a better understanding of the genetic basis of the adaptive response of plants to drought and how best to exploit this knowledge for breeding purposes (Bohnert et al., 1995; Bajaj et al., 2000; Hasegawa et al., 2000; Zhang et al., 2000; Tuberosa and Salvi, 2004). More recently, following the increased availability of sequence data, expression profiling has been used to identify genes involved in the adaptive responses to drought and other abiotic stresses (Kawasaki et al., 2001; Fowler and Thomashow, 2002; Kreps et al., 2002; Ozturk et al., 2002; Oono et al., 2003; Rabbani et al., 2003; Hazen et al., 2005; Rensink and Buell, 2005). An important application of these studies relates to the identification of drought-inducible genes which may identify essential or important functions with an effect on tolerance or defence reactions against water loss. Such candidate genes might be correlated with quantitative trait loci (QTLs) with an important role in influencing drought tolerance under field conditions (Diab et al., 2004). In turn, this information may offer additional opportunities for a more effective application of marker-assisted selection, genetic engineering, and/or other genomics approaches (e.g. EcoTILLING; Comai et al., 2004) for the release of drought-resilient cultivars.
The experimental procedures that have been applied in transcript-profiling studies that mimic drought conditions differ greatly in terms of the dynamics and/or intensity of the water-stress treatments applied. Therefore, it is important to verify the correspondence of changes in expression profiles occurring under different experimental conditions mimicking drought conditions in the field. In most cases (Kawasaki et al., 2001; Kreps et al., 2002; Ozturk et al., 2002; Seki et al., 2002; Rabbani et al., 2003; Atienza et al., 2004; Lan et al., 2005; Rensink and Buell, 2005), transcriptome profiling for the response to water deficit has been performed on samples collected from plants subjected to high-intensity stress treatments frequently developed in a very short time (i.e. ‘shock-like’ treatments), thus precluding the identification of those long-term responses in gene expression which may play an important role in the adaptation to drought under field conditions. Less numerous are the studies where a slowly developing stress treatment has been applied to investigate the effects of drought on transcription profiles (Rizhsky et al., 2002; Giuliani et al., 2005; Hazen et al., 2005; Luo et al., 2005). More importantly, none of these studies investigated to what extent the results might be influenced by the dynamics of the dehydration treatment. Hazen et al. (2005) measured differences in transcriptional responses to dehydration stress (moderate and severe treatments) among phenotypically divergent accessions of rice and their transgressive segregants to associate stress-related gene expression changes with QTLs for osmotic adjustment. The changes in gene expression reported in their study, when compared with those obtained in similar studies in rice, showed a difference in both the magnitude and the nature of the response to dehydration stress possibly due also to the different way in which water stress was imposed.
The objective of the present work was to compare the changes in transcript profiles induced by a slow, physiological drought-stress treatment in barley (Hordeum vulgare L.) with those induced by a rapidly imposed, severe water deficit.
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Materials and methods |
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TopAbstractIntroductionMaterials and methodsResults and discussionConclusionsReferences |
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This study follows a previous analysis of barley transcripts involved in drought and salt tolerance response (Ozturk et al., 2002), where stress treatments were administered under shock-like conditions.
Plant material and stress treatments
In this study, expression profiling under different water regimes was performed on Er/Apm, a barley variety well adapted to dry environments that was developed at ICARDA (International Center for Agricultural Research in Dry Areas, at Aleppo, Syria). Seeds were surface-sterilized and pre-germinated in Petri dishes for 48 h at room temperature in the dark. Seedlings at a similar germination stage were transferred into pots containing compost, vermiculite, and sand (3:2:1, by vol.) and were grown under greenhouse conditions (27 °C day and 22 °C night, 12 h photoperiod, 500 µmol m–2 s–1 photon flux) until the four-leaf stage when plants were subjected to a ‘dehydration shock’ (DHSH) or a ‘drought stress’ treatment.
The DHSH experiment followed a protocol described by Ozturk et al. (2002) and is only briefly summarized herein. Pots were arranged according to a completely randomized design; two replications of five pots (six plants per pot) for each treatment were considered. Plants were well-watered until the four-leaf stage, then stress was applied by gently removing whole plants (at 09.00 h) from soil and leaving them on paper towels for 6 h at 27 °C and 500 µmol m–2 s–1 photon flux. Subsequently, leaf samples (third leaf) were collected, frozen in liquid nitrogen and stored at –80 °C until use. Control plants were well-watered and their leaves harvested at the same time as the stressed plants.
As compared with the DHSH experiment, in the drought-stress experiment, a larger number of plants were grown to accommodate the higher number of samplings: two replications consisting of 15 pots (six plants per pot) for each treatment were considered. Pots were arranged according to a completely randomized design and their position was changed daily. Plants were well-watered until the four-leaf stage when water stress (WS) treatment was started by withholding water. Leaf samples (third leaf) were collected, from both treated and control plants, at 15.00 h of day 7 and day 11 of the WS treatment (hereafter indicated as 7d-WS and 11d-WS) when the relative soil moisture content corresponded to 55% and 40% of the soil water-holding capacity (SWC) for the stressed plants and to 98% SWC for the irrigated (control) plants (pots were weighed and watered daily). At day 12 after starting the drought-stress treatment, plants were irrigated again (rehydration and leaf tissue was collected 1 d later at 15.00 h). Samples were frozen in liquid nitrogen and stored at –80 °C.
Physiological data
Leaf relative water content (RWC) was measured on the third leaf and computed as (fresh weight–dry weight)/(turgid weight–dry weight)x100. The concentration of leaf abscisic acid (ABA) was determined according to Quarrie et al. (1988). Free amino acids were isolated from drought-stressed and control plants exclusively at 11d-WS following a procedure described by Thomas et al. (1992). Proline concentration was determined in a Beckman-7300 amino acid analyser (Beckman, Fullerton, CA, USA).
cDNA microarrays
The microarray analysis deployed barley cDNA clones isolated from three cDNA libraries (HB, HC, and HAD) obtained from well-watered and dehydration-shocked plants of the barley variety Tokak as previously described (Ozturk et al., 2002). The HB library includes transcripts combined from leaves subjected to a 6 h or a 10 h DHSH treatment; the HC library includes RNA from dehydration-shocked roots; and the HAD library includes RNA from control leaves and roots. The sequence of individual cDNA clones was determined from the 5' ends and their homologies were examined by comparison with those in the GenBank database using a BLAST search program. A total of 1654 cDNA clones were used in the microarray analysis: 689 derived from the HB library, 773 from the HC library, and 192 from the HAD library. Inserts of cDNA clones were amplified by polymerase chain reaction (PCR), quantified, and prepared for microarray spotting as described before (Ozturk et al., 2002). Each DNA element was spotted in four replicates. As negative controls and to monitor the detection sensivity limit, five different human expressed sequence tags (ESTs) were spotted in four replicates in multiple locations on the slides as described in Ozturk et al. (2002).
Microarray hybridization and data analysis
Total RNA was isolated from leaf tissue pooled from >20 plants that received the same treatment in each of the two replicates. Probe preparation, hybridization, and normalization procedures were conducted as described in Ozturk et al. (2002). Briefly, total RNA was isolated using TRIZOL Reagent (Life Technologies, Rockville, MD, USA), and poly(A+) RNA was isolated using an mRNA isolation kit (PolyAT-tract mRNA Isolation System IV; Promega, Madison, WI, USA). For the cDNA microarray analysis, each mRNA sample was reverse transcribed in the presence of Cy3-dUTP or Cy5-dUTP (Amersham Pharmacia Biotech, Dubendorf, Switzerland). Each hybridization included Cy3/Cy5-labelled human probes of these ESTs, each at a different concentration to control for low and high signal intensities and to adjust for equal Cy3 and Cy5 signal strength. Microarrays were scanned using a ScanArray 3000 (GSI Luminomics, Watertown, MA, USA) and analysed by ImaGene III Software (BioDiscovery, Los Angeles, CA, USA). Background fluorescence was subtracted from the value of each spot on the array. Normalization of the signal intensities was carried out according to Deyholos and Galbraith (2001). Transcript regulation has been expressed as the ratio of intensities between stress and control samples. Changes in signal intensity between stress and control experiments exceeding a 
2.5-fold difference in repeat experiments were considered significant. Transcripts which were shown to be differentially regulated were then subjected to cluster analysis using the programme Cluster/Treeview (Eisen et al., 1998).
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Results and discussion |
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TopAbstractIntroductionMaterials and methodsResults and discussionConclusionsReferences |
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Physiological parameters
After 6 h of DHSH treatment, leaf RWC declined to 61% and leaf ABA increased >16-fold (from 182 ng to 3070 ng of ABA g–1 dry weight). As to the drought stress and rehydration treatments, leaf RWC decreased from 91% at 7d-WS to 81% at 11d-WS, and increased to 94% at rehydration. As compared with the well-watered controls, leaf ABA increased
2.8-fold at 7d-WS (from 182 ng to 507 ng of ABA g–1 dry weight) and slightly more at 11d-WS (529 ng ABA g–1 dry weight). After rehydration, leaf ABA decreased to 1.5-fold of the value of the control (302 compared with 182 ng of ABA g–1 dry weight). As an additional physiological parameter and only for plants subjected to 11d-WS and the corresponding well-watered control, the total amount of amino acids and proline concentration was determined. Among other compatible osmolytes, such as glycine betaine or sugar alcohols, proline is the most commonly used osmolyte accumulated under drought stress conditions in plants (Blum, 1988; Delauney and Verma, 1993). As compared with the controls, the total amount of amino acids increased from 350 to 599 pmol µl–1, with the proline concentration increasing 11.7-fold (from 1.8 to 21.6 pmol µl–1).
Changes in transcript profiles
To examine the effect of drought treatments, a cDNA microarray composed of 1654 cDNA clones corresponding to metabolic and dehydration-responsive genes, and partially overlapping (65% of identity) with the transcripts included in the microarray previously described by Ozturk et al. (2002), was designed and used. The reproducibility of the changes in transcripts of a particular sample was verified by comparing duplicated mRNA hybridizations from the same isolation and labelling reaction: the conformity of transcript profiles in duplicate experiments reached 92–95% (data not reported). Additionally, mRNA samples isolated from different biological replicates showed an 90% repeatability (data not shown). These results were in line with the degree of variability previously observed in similar experiments (Kawasaki et al., 2001; Ozturk et al., 2002) and indicated a level of reproducibility and accuracy sufficient to calculate reliably, for most cases, the expression level of each DNA element as the average value of the corresponding eight spots (four replicates/slidextwo biological replicates).
Data analysis revealed that the transcripts showed differential expression profiles in response to drought treatments. In total, 173 transcripts (i.e. 10% of all transcripts profiled) changed their expression level in response to at least one of the different treatments. When evaluating the transcripts differentially regulated under the slow occurring drought stress and rehydration treatments, the proportion decreased to 5%, a reduction partially justified considering that most of the cDNAs included in the array derived from libraries of shock-stressed barley plants.
Among the regulated transcripts, 106 increased in abundance and 61 were down-regulated, while six transcripts were either induced or repressed depending on the treatment considered. Interestingly, a large number of transcripts were exclusively regulated by only one of the drought treatments; in particular, 72 transcripts corresponding to 68% of the up-regulated transcripts were induced only by the DHSH treatment, 22 transcripts, corresponding to 36% of the down-regulated transcripts were drought stress-specific, and only 10 transcripts corresponding to 6% of the regulated transcripts were differentially expressed exclusively after rehydration.
Table 1 reports the expression pattern of the transcripts up-regulated (Table 1a) or down-regulated (Table 1b) within the different treatments tested. While many functional categories were similarly represented in the up- and downregulated groups, there was a greater occurrence of up-regulated rather than down-regulated changes for transcripts encoding proteins involved in the response to abiotic stimulus and stress, such as allene oxide synthase (involved in jasmonate biosynthesis), jasmonate-responsive proteins, late embryogenesis abundant (LEA) proteins, and osmoprotectant biosynthesis-related proteins (e.g. arginine decarboxylase and 5PCS). Induction of transcripts for the biosynthesis of jasmonate, known to act as a signal in pathogen defence and under drought conditions (Reymond and Farmer, 1999; Wiestra and Kloppstech, 2000), has been observed in other studies (Reymond et al., 2000; Kawasaki et al., 2001; Ozturk et al., 2002). Many other genes induced in the present experiment are believed to be involved in maintaining the integrity of cell structure, such as lipid transferases, dehydrins, and LEA proteins which may protect against the effects of desiccation (Shinozaki and Yamaguchi-Shinozaki, 1999). Some up-regulated transcripts encoded sugar transporters, thought to be involved in osmotic adjustment under stress conditions, and protease inhibitors, which may perform a defensive role against proteases, providing other examples of proteins with a potentially protective role in stress tolerance (Rabbani et al., 2003). Moreover, there was extensive up-regulation of genes predicted to encode antioxidants, calcium-regulated proteins, and protein kinases believed to be involved in the signalling cascade from sensing the stress event to the activation of defence and acclimation pathways (Knight and Knight, 2001; Seki et al., 2001; Chen et al., 2002).
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As expected, most of the strongly down-regulated transcripts are related to photosynthesis, photorespiration, and metabolism of amino acids and carbohydrates. In total, 44 transcripts corresponding to
25% of the differentially expressed transcripts have been classified in either the ‘unknown’ or ‘no homology’ category, the latter indicating that transcripts in this class have not been previously described in other organisms. However, the number of functionally unknown transcripts is probably larger because many transcripts are assigned to categories based on domain homologies with other deduced protein sequences while their actual function has not been documented.
Expression profiles under dehydration shock treatment and comparison with drought-stress treatments
The main objective of this study was to compare the transcriptional responses between a shock-like dehydration treatment and the gradual imposition of drought. Approximately 57% of the transcripts differentially regulated changed in expression exclusively under the DHSH treatment and only 10% were commonly regulated by both shock and stress treatments (Fig. 1a).
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Most of the transcripts that were influenced by the DHSH treatment were also found to be differentially expressed in the previous study in barley (Ozturk et al., 2002). They code for proteins known to be drought stress-related. Many transcripts, among the 26 strictly downregulated under DHSH treatment, are related to photosynthesis or to sugar transport, and only six transcripts showed an expression pattern similar to what was observed under drought stress treatments. In particular, two transcripts are related to photosynthesis and amino acid metabolism, one transcript codes for an extensin, and two transcripts are involved in protein transport (Table 1b).
In total, 13 transcripts were up-regulated in both treatments, including four encoding metallothionein-like proteins, one encoding a sugar transporter, one involved in jasmonic acid biosynthesis, and one involved in osmoprotectant synthesis. Although the same functional categories are also represented among the transcripts exclusively up-regulated under DHSH treatment, the number of transcripts included in this last group is more than twice as large as the slow dehydration-responsive group and mainly includes transcripts encoding jasmonate-induced proteins, dehydrins, S-adenosylmethionine decarboxylases, and other abiotic stress-responsive proteins.
Among the transcripts related to the synthesis of osmoprotectants, one involved in proline biosynthesis (HC102B08 encoding 
-pyrroline-5-carboxylate synthetase) was up-regulated under DHSH and showed a 2.3-fold change in expression also at 11d-WS. This last observation could be extended to a larger group of transcripts as shown from the cluster analysis performed on the expression profiles of the 173 differentially regulated transcripts (Fig. 2). In fact, despite the low percentage of transcripts (10%) showing a similar expression pattern between shock and stress treatments, a good number of transcripts shared a common expression trend under different drought conditions and were clustered in common subgroups based on their expression profile analysis. Nonetheless, the expression levels obtained for the DHSH treatments were much higher than those obtained under drought stress treatments which, in most cases, did not reach the threshold value of a 2.5-fold change. The partial overlap between the expression profiles obtained under DHSH and drought stress treatments is also evidenced by the correlation of the values obtained for the DHSH treatment with the values of the 7d-WS and 11d-WS treatments (Table 2). The low but significant correlation values between the DHSH and the two drought-stress treatments (r=0.29 and 0.41, P=0.001, for 7d-WS and 11d-WS, respectively) underline the higher correspondence between the changes in transcripts expression observed in the 11d-WS treatment with those observed in the DHSH experiment. This result is not unexpected in relation to the substantially lower RWC of the 11d-WS treatment (81%) as compared with the 7d-WS treatment (91%).
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Comparison of drought-stress and rehydration treatments
In this study, large-scale changes in gene expression of barley leaves in response to rehydration following the slow occurring drought-stress treatment were also measured. The total number of 68 transcripts showing a change in expression in response to drought-stress and rehydration treatments was almost equally split in up- and down-regulated transcripts (34 up- and 35 down-regulated transcripts, respectively), while five transcripts were either induced or repressed depending upon the treatment (Table 1; Fig. 2).
The number and the frequency of transcripts differentially regulated for each time point are reported in Table 1 and Fig. 2. Twenty-three transcripts were differentially regulated at 7d-WS; this number increased to 42 at 11d-WS and decreased again at rehydration (22 transcripts). A low number of transcripts (11) were differentially expressed in more than one of these conditions.
At 7d-WS, half of the down-regulated transcripts are classified as functionally unknown and, among the up-regulated transcripts, some are involved in osmoprotectant synthesis and in carbohydrate metabolism (Table 1). At 11d-WS, one dehydrin-related transcript, one related to jasmonate biosynthesis, and several additional sequences encoding metallothionein-like proteins or proteins involved in sugar or lipid transport were among the up-regulated transcripts, while other transcripts involved in protein degradation or carbohydrate metabolism were repressed.
As to the rehydration treatment, a very low overlap mainly including functionally unknown transcripts was observed with the transcripts differentially regulated under drought stress conditions. Among the up-regulated transcripts, one encoding cytochrome P450 (HB01H03) was expressed only after rehydration. Induction of cytochrome P450 genes has already been observed in another study monitoring expression profiles of Arabidopsis genes during the rehydration phase. Although the function of these genes in the rehydration process is not fully understood, one possible function is their involvement in ABA degradation (Oono et al., 2003). Similar to observations by Oono et al. (2003), the rehydration-inducible genes identified here included transcripts corresponding to proteins involved in the recovery process from dehydration-induced damage, such as enzymes involved in protein degradation (e.g. polyubiquitin), detoxification enzymes (e.g. peroxidases thought to be involved in protection from reactive oxygen species), and regulatory proteins (e.g. protein kinases) probably involved in the recovery processes from dehydration to rehydration. Among the genes down-regulated by rehydration, many are drought stress-inducible genes, like those coding for protein transport and protein kinases; the repression of dehydration-inducible genes during rehydration had already been observed in Arabidopsis by Oono et al. (2003). These authors suggested that regulation during the recovery from drought may involve regulation at both transcriptional and post-transcriptional levels.
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Conclusions |
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TopAbstractIntroductionMaterials and methodsResults and discussionConclusionsReferences |
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This study indicated changes in expression profiles that varied considerably according to the dynamics of the dehydration treatment (i.e. shock-like versus gradual stress). In general, as compared with the sudden and more severe dehydration experienced by leaves in the DHSH experiment, the gradual dehydration of leaves during slow drought imposition revealed a lower number of differentially regulated transcripts. Additionally, the fold changes in expression levels observed in the shock treatment were considerably higher than those measured under slow drought treatments which, in most cases, did not reach the chosen threshold value of 2.5. Only a small portion of transcripts (
10%) showed similar changes regardless of the dynamics of the water stress treatment. This notwithstanding, cluster analysis of the expression profiles indicated that a considerable number of transcripts shared a common trend, if not the magnitude, of change in expression under both experimental conditions. From a more practical standpoint, the results suggest that caution should be exerted when transcriptome information obtained under conditions of water deficit induced in a very short time (e.g. a few hours) is used (i) to understand better how plants may regulate gene expression in response to a water deficit developed under more naturally induced drought conditions; and/or (ii) to identify candidate genes for QTLs of field-related traits with an adaptive role in drought. However, it should be noted that for those genes that responded rather similarly to a decrease in water content irrespective of the dynamics of the dehydration protocol, a shock-like treatment may actually provide an easier, faster, and more effective way to identify and characterize functionally different alleles involved in the adaptive response to drought. For this, a critical analysis of the wealth of data available from existing transcriptome profiling experiments and from protein and metabolite profiling studies conducted under various dehydration regimes may reveal additional information useful to identify candidate genes and processes whose manipulation may improve drought tolerance. Ideally, one strategy could be to carry out both types of treatments in time-course experiments for a recording of transcript dynamic changes involved in the response of plants to conditions of water deficit. Shock-like treatments tend to measure the capacity of a plant to respond to a severe and acute change in the environment. This response is based on the regulation of genes involved in the sensing, signalling, and immediate response categories, many of which, while reporting the degree or severity of a stress, might not be translated into bulk changes of proteins. However, the immediate water deficit created by letting the barley plants wilt is different from the gradual change in shoot water status in intact plants responding to drying soil, and the results document this different behaviour. Experiments that induce water deficit by soil drying in, for example, different breding lines in a comparative fashion have not been conducted. It is thus unknown to what degree responses to shock treatment may be indicative of a plant's capacity to adapt to a gradual change in the water potential of the soil. In contrast, a slow decrease in soil moisture would lead to gradual changes in sensing/signalling that, several days after the onset of the drought episode, might return to a pre-stress level. Such drought-stress treatments would then more appropriately measure the result of acclimation reported by transcripts and proteins that provide long-term protection.
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Acknowledgements |
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The work has been supported by NSF DBI-223905 and by a contribution of the University of Bologna (Interdepartmental Centre for Biotechnology, University of Bologna, Italy).
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Footnotes |
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* Present address: Institut für Pflanzenwissenschaften, Universität Heidelberg, Heidelberg, Germany
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Abbreviations |
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ABA, abscisic acid; DHSH, dehydration shock; EST, expressed sequence tag; LEA, late embryogenesis abundant; QTL, quantitative trait locus; RWC, relative water content; SWC, soil water-holding capacity; WS, water stress.
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References |
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