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‘Omics’ analyses of regulatory networks in plant abiotic stress responses
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‘Omics’ analyses of regulatory networks in plant abiotic stress responses Kaoru Urano1, Yukio Kurihara2, Motoaki Seki2 and Kazuo Shinozaki1 Plants must respond and adapt to abiotic stresses to survive in various environmental conditions. Plants have acquired various stress tolerance mechanisms, which are different processes involving physiological and biochemical changes that result in adaptive or morphological changes. Recent advances in genome-wide analyses have revealed complex regulatory networks that control global gene expression, protein modification, and metabolite composition. Genetic regulation and epigenetic regulation, including changes in nucleosome distribution, histone modification, DNA methylation, and npcRNAs (non-protein-coding RNA) play important roles in abiotic stress gene networks. Transcriptomics, metabolomics, bioinformatics, and high-through-put DNA sequencing have enabled active analyses of regulatory networks that control abiotic stress responses. Such analyses have markedly increased our understanding of global plant systems in responses and adaptation to stress conditions. Addresses 1 Gene Discovery Research Team, RIKEN Plant Science Center, 3-1-1 Koyadai, Tsukuba, Ibaraki 305-0074, Japan 2 Plant Genomic Network Research Team, RIKEN Plant Science Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan Corresponding author: Shinozaki, Kazuo ([email protected])
Current Opinion in Plant Biology 2010, 13:132–138 This review comes from a themed issue on Genome studies and molecular genetics–Plant biotechnology Edited by Douglas R. Cook and Rajeev K. Varshney Available online 14th January 2010 1369-5266/$ – see front matter # 2010 Elsevier Ltd. All rights reserved. DOI 10.1016/j.pbi.2009.12.006
Introduction Plant growth and productivity are greatly affected by environmental stresses such as dehydration, high salinity, and low temperature. It is important to understand plants’ stress responses to improve crop productivity under unfavorable or stressful conditions. Plants respond and adapt to these stresses at molecular, cellular, physiological, and biochemical levels [1]. Both forward and reverse genetic approaches have elucidated genes and gene products that are involved in gene expression, signal transduction, and stress tolerance [1]. In the post-genomics era, comprehensive analyses using functional genomics technologies such as transcriptomics, proteomics, and metabolomics Current Opinion in Plant Biology 2010, 13:132–138
have increased our understanding of the complex regulatory networks associated with stress adaptation and tolerance. In this article, we review recent progress on integrated transcriptomics and metabolomics analyses of regulatory networks that control plant physiological processes during abiotic stress responses. We also discuss the limitations, realities, and future prospects of these genome-scale analyses.
Transcriptome analyses of plants under abiotic stresses Microarray technologies are powerful tools for the global analysis of transcripts. In Arabidopsis, the AtGenExpress project (http://www.arabidopsis.org/portals/expression/ microarray/ATGenExpress.jsp) has collected thousands of transcript profiles on the basis of the Affymetrix ATH1 GeneChip that are now publicly available. This contribution has enabled the discovery of candidate genes on the basis of expression profiles in various tissues, developmental stages, and environmental conditions. Transcriptome analysis technologies have advanced to the point where high-through-put DNA sequencers and high density microarrays such as tiling arrays are readily available. These technologies provide new opportunities to analyze non-coding RNAs and also to clarify aspects of epigenetic regulation of gene expression. Whole-genome analysis for non-protein-coding (npc) RNAs in abiotic stress responses
Microarray analyses have been used to analyze Arabidopsis transcriptomes under various stress conditions, and have identified thousands of stress-responsive genes [2– 4]. Although such analyses can detect the majority of protein-coding genes, they cannot detect genes in genome regions that have not been annotated previously. Recently, two groups conducted analyses using Affymetrix tiling arrays [5,6] to detect unannotated regions [7,8]. These studies revealed whole-genome transcriptomes of plants exposed to abiotic stresses such as dehydration, cold, heat, high-salinity, and osmotic stresses, as well as ABA treatment [7,8]. Their results revealed that these stresses upregulate or downregulate accumulation of transcripts not only from previously identified stressresponsive genes, but also from thousands of unannotated non-protein-coding regions. Matsui et al. estimated that approximately 80% of previously unannotated upregulated transcripts arise from antisense strands of sense transcripts. There was a significant linear correlation www.sciencedirect.com
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between the expression ratios (stress-treated/untreated) of the sense transcripts and the ratios of the antisense transcripts [7]. Interestingly, the data suggested that such stress-responsive antisense transcripts are derived from antisense strands of the stress-responsive genes RD29A and CYP707A1. Whether or not such antisense transcripts have biological functions is an important issue that remains to be resolved.
Figure 1
Small RNAs control stress responses
Small RNAs may emerge from sense–antisense transcript pairs as described by Matsui et al. [7]. A very wellknown example is the natural cis-antisense transcript (NAT) siRNA (nat-siRNA) derived from the overlapping region of the sense–antisense pair P5CDH and SRO5 [9]. P5CDH encodes D1-pyrroline-5-carboxylate dehydrogenase, which functions in proline catabolism, while the function of SRO5 is unknown. Borsani et al. showed that under salt stress, accumulation of SRO5 transcripts and 24-nt nat-siRNAs is upregulated, whereas that of P5CDH is downregulated. In this model, the 24-nt natsiRNAs guide the initial cleavage of the P5CDH transcript, which generates secondary 21-nt nat-siRNAs by phasing cleavage. The secondary nat-siRNAs also suppress P5CDH transcripts and, after accumulation of the osmoprotectant proline, the plant acquires tolerance to salt stress. A bioinformatics study by Henz et al. showed that small RNAs registered in public databases are not enriched in cis-NATs when compared with non-overlapping neighboring gene pairs, and then suggested that siRNA-mediated silencing does not play a major role in global regulation of cis-NAT expression [10]. Therefore, production of nat-siRNAs from overlapping gene pairs may rarely occur, at least in Arabidopsis. In addition, a homology search showed that P5CDH homologs exist in the genomes of rice, soybean, poplar, grape, Lotus japonicus, and Physcomitrella patens, but SRO5 homologs are not present on the antisense strand of the P5CDH genes in these six plant species. It is still unknown whether this nat-siRNA functions only in tolerance to salt stress in Arabidopsis. Cytoplasmic RNA-containing granules involved in stress responses
Transcriptome analyses show mRNA accumulation, but this does not necessarily mean that mRNAs of expressed genes are actively translated. In addition to the transcriptome profile, it is important to examine which mRNAs are translated, degraded, or temporarily stored during stress treatments (Figure 1). Transcribed mRNAs form messenger ribonucleo protein complexes (mRNPs), depending on developmental stages or environmental conditions. Polysome-associated mRNAs are usually translated. On the contrary, non-translated mRNA is localized in two kinds of cytoplasmic mRNP granules; an mRNA processing body (P-Body, PB) or a stress granule (SG) [11,12]. In yeast and mammals, the PB contains components of www.sciencedirect.com
Present concept of regulatory network of transcriptome profile in abiotic stress response. Some mRNAs are destined to be translated (polysome), degraded (P-body, PB), or temporarily stored (stress granule, SG) during stress treatment. Some are processed by gene activation such as a histone modification, and some are regulated at a post-transcriptional level (e.g., siRNA, miRNA, or antisense RNA).
mRNA decay machinery such as the DCP1/DCP2 decapping complex and 50 –30 exoribonuclease XRN1, and executes 50 –30 destruction of unnecessary mRNAs. On the contrary, the SG contains translation initiation factors such as eIF4E, eIF4G, and eIF4A, the 40S ribosomal subunit, the poly(A)-binding protein and some RNAbinding proteins, and stores non-translated mRNAs that have been stalled during initiation of translation. In yeast and mammals, cells subjected to environmental stresses show increases in the number of SGs and their assembly [12,13]. Because stress responses often involve a transient inhibition of the initiation of translation, SGs accumulate during a wide range of stress responses. SGs often dock to P bodies, which suggests that mRNAs move between these two compartments. Recent reports have revealed that PBs and SGs also exist in plants [14,15,16,17]. Weber et al. observed dynamic changes in the assembly of these granules during heat stress, using DCP1, DCP2, and XRN4 as markers of PBs, or eIF4E, RBP47, and UBP1 as markers of SGs [14]. UBP1 and RBP47 are RRM-type RNA-binding proteins and plant orthologs of the TIA-1 protein, a component of SGs in mammals. Previous reports showed that UBP1 functions in nuclear pre-mRNA maturation and also protects mRNA from degradation by binding with its Current Opinion in Plant Biology 2010, 13:132–138
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30 -UTR [18]. Weber et al. also revealed that UBP1 and RBP47 predominantly localize in the nucleus under control conditions, while they re-localize in several cytoplasmic granules when cells are exposed to heat-stress conditions. Cycloheximide treatment, which blocks translation elongation, prevents the formation of SGs. Therefore, plant SGs are regulated in a dynamic exchange with polysomes. Yeast two-hybrid analyses and in vitro binding assays identified UBA1 and UBA2, RRM-type RNA-binding proteins, as UBP1-interacting partners [19]. UBA2a localizes throughout the nucleus under control conditions. However, ABA treatment results in relocalization of UBA2a into nuclear speckle structures that are storage sites of spliceosomal components [20]. The levels of splice variants of UBA2a and UBA2c transcripts are upregulated by wounding [21]. It is possible that some RRM-type RNA-binding proteins play important roles in regulation of mRNA metabolism and cell homeostasis under stress conditions. Microarray analyses showed that some stress-responsive transcripts such as RD20, COR15A, AtGolS2, and PP2C are upregulated in the mutant of DCP2 that encodes a component of the decapping complex [17]. Taken together, the results of studies on SGs and PBs suggest that they are key cytoplasmic structures for controlling gene expression during plant stress responses.
activation, in response to dehydration stress. Dehydration stress resulted in enrichment of H3K23ac and H3K27ac at the coding regions of RD29B, RD20, and At2g20880, but not at the coding region of RD29A. H3K4me3 enrichment occurred on the coding regions of RD29A and At2g20880 after accumulation of Pol II. However, these reports describe only isolated examples of chromatin modification during stress responses. Large-scale analyses using ChIP-seq or ChIP-chip methods are necessary to increase our understanding of the roles of histone modification in abiotic stress responses.
Metabolome analyses in abiotic stress responses The metabolic changes in plants in response to environmental stress factors have been extensively analyzed using several MS technologies and bioinformatics [28]. Integrated metabolome and transcriptome analyses of model plants have markedly increased our understanding of plants’ responses to various stresses. Metabolite profiling has been used to characterize stress responses to abiotic stresses such as water deficit (dehydration and high salinity) and extreme temperature (cold and heat) for comprehensive analyses of the final steps of stress signal transduction pathways. Dehydration-stress response
Histone modification under abiotic stress conditions
Changes of transcriptional states in response to environmental stresses are coupled with chromatin remodeling. In general, these changes are accompanied by posttranslational modification of histone N-tails such as acetylation, methylation, and phosphorylation [22,23]. Various modifications of histones occur during stress responses in plants [24,25,26]. The chromatin immunoprecipitation (ChIP) assay is the best method to detect the state of histone modification under stress conditions. Tri-methylation of histone H3 Lys27 (H3K27me3) is generally a negative marker of transcription [27]. Using ChIP assays, Kwon et al. demonstrated that H3K27me3 modification gradually decreases at the loci of two cold-responsive genes, COR15A and AtGolS3, during exposure to cold temperatures [24]. When coldexposed plants are returned to normal conditions, transcriptions of these genes are repressed to their initial levels, but the cold-triggered decrease in H3K27me3 is still maintained. This decrease does not enhance the induction of transcription when plants are returned to cold temperatures. Using ChIP assays, Kim et al. monitored histone H3 modifications at the coding regions of four dehydrationstress-responsive genes, RD29A, RD29B, RD20, and an AP2 transcription factor (At2g20880), during dehydration stress [25]. At all four gene loci, there was an enrichment of H3K4me3 (tri-methylation of H3 Lys4) and H3K9ac (acetylation of H3 Lys9), a positive marker of gene Current Opinion in Plant Biology 2010, 13:132–138
Molecular studies on the dehydration-stress response have revealed both abscisic acid (ABA)-dependent and ABA-independent pathways [1]. The endogenous ABA level significantly increases response to water-deficit stress to regulate physiological stress responses and gene expression. Recently, an integrated analysis of the metabolome and transcriptome of the dehydration-stress response was carried using GC-TOF–MS, CE-MS, and DNA microarrays. These methods were used to analyze the dehydration-stress response of an Arabidopsis NCED3-knockout mutant and the wild-type plant [29]. NCED3 plays a role in the dehydration-inducible biosynthesis of ABA [1]. Metabolite profiling revealed that the ABA accumulated during dehydration regulates the accumulation of various amino acids and sugars such as glucose and fructose. In particular, the dehydrationinducible accumulations of BCAAs (branch-chain amino acids), saccharopine, proline, and agmatine are correlated with the dehydration-inducible expression of their key biosynthetic genes (BCAT2, LKR/SDH, P5CS1, and ADC2, respectively), which are regulated by endogenous ABA. On the contrary, the levels of raffinose and galactinol are not regulated by ABA during dehydration stress. In addition, metabolic network analysis showed global metabolite–metabolite correlations among dehydrationincreased amino acids in the WT, but a strong correlation between dehydration stress and raffinose in the nced3 mutant. These results indicated that ABA has an important role in regulating the metabolic changes that occur during the dehydration-stress response. www.sciencedirect.com
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Transcript and metabolite profiles were compared between dehydration and salinity stress in grapevine [30]. Metabolic profiling revealed higher concentrations of glucose, malate, and proline in dehydration-treated plants, compared with salt-stressed plants [30]. These differences in the levels of metabolites were correlated with those of transcript levels of many genes involved in energy metabolism and nitrogen assimilation. Compared with salt-stressed plants, dehydration-treated plants have a greater need to adjust osmotically, detoxify ROS, and ameliorate photoinhibition [30]. Metabolic profiling revealed that sucrose replaces proline in plants as the major osmoprotectant during the more severe combined dehydration and heat-stress treatment [31].
response to heat shock overlapped with those produced in response to cold shock. Moreover, these results suggested that a metabolic network of compatible solutes including proline, monosaccharides (glucose and fructose), galactinol, and raffinose has an important role in tolerance to temperature stress. Natural variations in freezing tolerance were analyzed in nine Arabidopsis accessions. Plants acclimating to cold conditions were analyzed using a combination of genomewide transcript profiling and metabolite profiling. The global changes in metabolite profiles were not correlated with plants’ responses to cold stress, whereas global changes in transcriptome profiles were correlated with plants’ abilities to acclimate to cold conditions [36].
Temperature stress response
Plants’ responses and acclimation to temperature stress have been precisely characterized by metabolite profiling [32,33,34–36]. A recent metabolome analysis showed common metabolites in the responses to cold and other stresses, and demonstrated a prominent role for the DREB1/CBF (dehydration responsive element-binding factor/C-repeat) transcriptional network in the coldresponse pathway [32,33]. In Arabidopsis and rice, the DREB1/CBF cold-response pathway is one of the most well-characterized genetic systems in cold-responsive gene expression and acclimation [1]. Metabolome analysis of transgenic Arabidopsis overexpressing DREB1A/CBF3 revealed that there is a striking similarity between the low-temperature regulated metabolome (monosaccharides, disaccharides, oligosaccharides, and sugar alcohols) and that regulated by the DREB1A/ CBF3 transcription factor [32,33]. In particular, the low-temperature-inducible accumulation of galactinol and raffinose is correlated with the expression of the GolS3 gene, which is a direct target of DREB1A/CBF3 [32,33]. In addition, Maruyama et al. also analyzed increased metabolites with those in cold-treated plants, those accumulated in the 35S:DREB1A-overexpressing transgenic plants and 35S DREB2A-CA (active form of DREB2A)-overexpressing transgenic plants. DREB2A overexpression did not increase the level of any lowtemperature regulated metabolites in transgenic plants [33]. It was previously reported that overexpression of DREB2A-CA in transgenic plants increased their tolerance to dehydration stress, but only slightly increased their tolerance to freezing stress [1]. These results indicate that the increased tolerance to freezing stress in transgenic plants overexpressing DREB1A may depend on the accumulation of low-temperature regulated metabolites, especially sucrose, raffinose, galactinol, and myo-inositol. Comparative metabolite analysis between Arabidopsis Columbia (Col-0) plants responding to heat shock and cold shock was carried out using GC–MS [34] and GCTOF–MS [35]. The majority of metabolites produced in www.sciencedirect.com
Salt stress response
Metabolome analysis of a new model halophyte was carried out to clarify aspects of genome evolution under salt stress. GC–MS and microarrays were used to analyze Arabidopsis and Thellungiella halophila, a closely related halophytic species [37]. Metabolome analyses revealed drastically different profiles between the two species. Compared with Arabidopsis, Thellungiella maintained higher levels of metabolites levels in both the absence and presence of salt stress. Even in control conditions, Thellungiella contains higher levels of various osmolytes, such as fructose, sucrose, complex sugars, malate, and proline, compared with Arabidopsis. Transcriptome analysis also showed that several stress-related genes were expressed at high levels in Thellungiella, even in the absence of salt stress [37]. The results suggest that a constant state of stress-anticipatory preparedness exists in Thellungiella. Metabolic profiles of Arabidopsis T87 cell cultures responding to salt stress were analyzed using GC–MS and LC–MS [38]. This metabolome analysis was focused on data mining of metabolite profiles at different time points after high-salinity treatment by using principal component analysis (PCA) and batchlearning self-organizing mapping analysis (BL-SOM). The results revealed synergetic induction of several pathways; the methylation cycle for the supply of methyl groups, the phenylpropanoid pathway for lignin production, and glycinebetaine biosynthesis, during the short-term response to salt stress. In the long-term response to salt stress, however, glycolysis and sucrose metabolism were co-induced, and then the methylation cycle was co-reduced. ABA was also shown to have important roles in determining metabolite profiles of Arabidopsis under salt stress [39]. Data-mining analysis of metabolite profiles by GC-TOF–MS and public transcript data by AtGenExpress demonstrated that a complex readjustment of carbohydrate metabolism occurs during salt stress, and Current Opinion in Plant Biology 2010, 13:132–138
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Figure 2
Transcriptome and metabolome regulation of dehydration, high-salinity, and low-temperature stress responses in Arabidopsis. The abscisic acid (ABA)-dependent and DREB/CBF pathways are important in osmotic stress response. ABA and DREB/CBF regulate gene expression and the stress metabolome [29,32,33]. ABA regulates biosynthesis of several amino acids and monosaccharides [29]. Some are regulated at the transcriptional level. During dehydration stress, biosyntheses of branched-chain amino acids (BCAA), polyamines, proline, and saccharopine rely on branched-chain aminotransferase (BCAT2), arginine decarboxylase (ADC2), D1-pyrroline-5-carboxylate synthase (P5CS1), and lysine ketoglutarate reductase/ saccharopine dehydrogenase (LKR/SDH), respectively [29]. On the contrary, biosyntheses of RFO (raffinose family oligosaccharides) biosynthetic pathway was not controlled by ABA [29]. DREB1/CBF regulated galactinol synthase, GolS3 expression that is key gene for RFO at low temperatures [32,33].
that ABA triggers the initial steps of carbon mobilization.
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Conclusions and perspectives Remarkable technical advances in transcriptomics and metabolomics are available to clarify the molecular configuration in response to abiotic stress (Figure 2). ‘Omics’ analyses are crucial to understand the whole processes of molecular networks in response to abiotic stress. It is important to elucidate the functions of newly identified stress-responsive protein-coding and non-coding RNAs to understand the complex abiotic stress responses of plants. Integrated metabolome and transcriptome analyses have revealed that many important metabolic pathways are regulated at the transcriptional level. However, there are also many metabolic pathways that are not regulated at the transcriptional level [40], but at a post-transcriptional level, for example, by RNA processing, translational, post-translational regulation, or feedback mechanisms. In addition, metabolites not only have functional roles in stress tolerance but also act as signaling molecules [41]. Integrated omics analyses are necessary to identify the broad function of metabolite regulatory networks during responses to abiotic stresses. Current Opinion in Plant Biology 2010, 13:132–138
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‘Omics’ analyses of regulatory networks in plant abiotic stress responses Kaoru Urano1, Yukio Kurihara2, Motoaki Seki2 and Kazuo Shinozaki1 Plants must respond and adapt to abiotic stresses to survive in various environmental conditions. Plants have acquired various stress tolerance mechanisms, which are different processes involving physiological and biochemical changes that result in adaptive or morphological changes. Recent advances in genome-wide analyses have revealed complex regulatory networks that control global gene expression, protein modification, and metabolite composition. Genetic regulation and epigenetic regulation, including changes in nucleosome distribution, histone modification, DNA methylation, and npcRNAs (non-protein-coding RNA) play important roles in abiotic stress gene networks. Transcriptomics, metabolomics, bioinformatics, and high-through-put DNA sequencing have enabled active analyses of regulatory networks that control abiotic stress responses. Such analyses have markedly increased our understanding of global plant systems in responses and adaptation to stress conditions. Addresses 1 Gene Discovery Research Team, RIKEN Plant Science Center, 3-1-1 Koyadai, Tsukuba, Ibaraki 305-0074, Japan 2 Plant Genomic Network Research Team, RIKEN Plant Science Center, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan Corresponding author: Shinozaki, Kazuo ([email protected])
Current Opinion in Plant Biology 2010, 13:132–138 This review comes from a themed issue on Genome studies and molecular genetics–Plant biotechnology Edited by Douglas R. Cook and Rajeev K. Varshney Available online 14th January 2010 1369-5266/$ – see front matter # 2010 Elsevier Ltd. All rights reserved. DOI 10.1016/j.pbi.2009.12.006
Introduction Plant growth and productivity are greatly affected by environmental stresses such as dehydration, high salinity, and low temperature. It is important to understand plants’ stress responses to improve crop productivity under unfavorable or stressful conditions. Plants respond and adapt to these stresses at molecular, cellular, physiological, and biochemical levels [1]. Both forward and reverse genetic approaches have elucidated genes and gene products that are involved in gene expression, signal transduction, and stress tolerance [1]. In the post-genomics era, comprehensive analyses using functional genomics technologies such as transcriptomics, proteomics, and metabolomics Current Opinion in Plant Biology 2010, 13:132–138
have increased our understanding of the complex regulatory networks associated with stress adaptation and tolerance. In this article, we review recent progress on integrated transcriptomics and metabolomics analyses of regulatory networks that control plant physiological processes during abiotic stress responses. We also discuss the limitations, realities, and future prospects of these genome-scale analyses.
Transcriptome analyses of plants under abiotic stresses Microarray technologies are powerful tools for the global analysis of transcripts. In Arabidopsis, the AtGenExpress project (http://www.arabidopsis.org/portals/expression/ microarray/ATGenExpress.jsp) has collected thousands of transcript profiles on the basis of the Affymetrix ATH1 GeneChip that are now publicly available. This contribution has enabled the discovery of candidate genes on the basis of expression profiles in various tissues, developmental stages, and environmental conditions. Transcriptome analysis technologies have advanced to the point where high-through-put DNA sequencers and high density microarrays such as tiling arrays are readily available. These technologies provide new opportunities to analyze non-coding RNAs and also to clarify aspects of epigenetic regulation of gene expression. Whole-genome analysis for non-protein-coding (npc) RNAs in abiotic stress responses
Microarray analyses have been used to analyze Arabidopsis transcriptomes under various stress conditions, and have identified thousands of stress-responsive genes [2– 4]. Although such analyses can detect the majority of protein-coding genes, they cannot detect genes in genome regions that have not been annotated previously. Recently, two groups conducted analyses using Affymetrix tiling arrays [5,6] to detect unannotated regions [7,8]. These studies revealed whole-genome transcriptomes of plants exposed to abiotic stresses such as dehydration, cold, heat, high-salinity, and osmotic stresses, as well as ABA treatment [7,8]. Their results revealed that these stresses upregulate or downregulate accumulation of transcripts not only from previously identified stressresponsive genes, but also from thousands of unannotated non-protein-coding regions. Matsui et al. estimated that approximately 80% of previously unannotated upregulated transcripts arise from antisense strands of sense transcripts. There was a significant linear correlation www.sciencedirect.com
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between the expression ratios (stress-treated/untreated) of the sense transcripts and the ratios of the antisense transcripts [7]. Interestingly, the data suggested that such stress-responsive antisense transcripts are derived from antisense strands of the stress-responsive genes RD29A and CYP707A1. Whether or not such antisense transcripts have biological functions is an important issue that remains to be resolved.
Figure 1
Small RNAs control stress responses
Small RNAs may emerge from sense–antisense transcript pairs as described by Matsui et al. [7]. A very wellknown example is the natural cis-antisense transcript (NAT) siRNA (nat-siRNA) derived from the overlapping region of the sense–antisense pair P5CDH and SRO5 [9]. P5CDH encodes D1-pyrroline-5-carboxylate dehydrogenase, which functions in proline catabolism, while the function of SRO5 is unknown. Borsani et al. showed that under salt stress, accumulation of SRO5 transcripts and 24-nt nat-siRNAs is upregulated, whereas that of P5CDH is downregulated. In this model, the 24-nt natsiRNAs guide the initial cleavage of the P5CDH transcript, which generates secondary 21-nt nat-siRNAs by phasing cleavage. The secondary nat-siRNAs also suppress P5CDH transcripts and, after accumulation of the osmoprotectant proline, the plant acquires tolerance to salt stress. A bioinformatics study by Henz et al. showed that small RNAs registered in public databases are not enriched in cis-NATs when compared with non-overlapping neighboring gene pairs, and then suggested that siRNA-mediated silencing does not play a major role in global regulation of cis-NAT expression [10]. Therefore, production of nat-siRNAs from overlapping gene pairs may rarely occur, at least in Arabidopsis. In addition, a homology search showed that P5CDH homologs exist in the genomes of rice, soybean, poplar, grape, Lotus japonicus, and Physcomitrella patens, but SRO5 homologs are not present on the antisense strand of the P5CDH genes in these six plant species. It is still unknown whether this nat-siRNA functions only in tolerance to salt stress in Arabidopsis. Cytoplasmic RNA-containing granules involved in stress responses
Transcriptome analyses show mRNA accumulation, but this does not necessarily mean that mRNAs of expressed genes are actively translated. In addition to the transcriptome profile, it is important to examine which mRNAs are translated, degraded, or temporarily stored during stress treatments (Figure 1). Transcribed mRNAs form messenger ribonucleo protein complexes (mRNPs), depending on developmental stages or environmental conditions. Polysome-associated mRNAs are usually translated. On the contrary, non-translated mRNA is localized in two kinds of cytoplasmic mRNP granules; an mRNA processing body (P-Body, PB) or a stress granule (SG) [11,12]. In yeast and mammals, the PB contains components of www.sciencedirect.com
Present concept of regulatory network of transcriptome profile in abiotic stress response. Some mRNAs are destined to be translated (polysome), degraded (P-body, PB), or temporarily stored (stress granule, SG) during stress treatment. Some are processed by gene activation such as a histone modification, and some are regulated at a post-transcriptional level (e.g., siRNA, miRNA, or antisense RNA).
mRNA decay machinery such as the DCP1/DCP2 decapping complex and 50 –30 exoribonuclease XRN1, and executes 50 –30 destruction of unnecessary mRNAs. On the contrary, the SG contains translation initiation factors such as eIF4E, eIF4G, and eIF4A, the 40S ribosomal subunit, the poly(A)-binding protein and some RNAbinding proteins, and stores non-translated mRNAs that have been stalled during initiation of translation. In yeast and mammals, cells subjected to environmental stresses show increases in the number of SGs and their assembly [12,13]. Because stress responses often involve a transient inhibition of the initiation of translation, SGs accumulate during a wide range of stress responses. SGs often dock to P bodies, which suggests that mRNAs move between these two compartments. Recent reports have revealed that PBs and SGs also exist in plants [14,15,16,17]. Weber et al. observed dynamic changes in the assembly of these granules during heat stress, using DCP1, DCP2, and XRN4 as markers of PBs, or eIF4E, RBP47, and UBP1 as markers of SGs [14]. UBP1 and RBP47 are RRM-type RNA-binding proteins and plant orthologs of the TIA-1 protein, a component of SGs in mammals. Previous reports showed that UBP1 functions in nuclear pre-mRNA maturation and also protects mRNA from degradation by binding with its Current Opinion in Plant Biology 2010, 13:132–138
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30 -UTR [18]. Weber et al. also revealed that UBP1 and RBP47 predominantly localize in the nucleus under control conditions, while they re-localize in several cytoplasmic granules when cells are exposed to heat-stress conditions. Cycloheximide treatment, which blocks translation elongation, prevents the formation of SGs. Therefore, plant SGs are regulated in a dynamic exchange with polysomes. Yeast two-hybrid analyses and in vitro binding assays identified UBA1 and UBA2, RRM-type RNA-binding proteins, as UBP1-interacting partners [19]. UBA2a localizes throughout the nucleus under control conditions. However, ABA treatment results in relocalization of UBA2a into nuclear speckle structures that are storage sites of spliceosomal components [20]. The levels of splice variants of UBA2a and UBA2c transcripts are upregulated by wounding [21]. It is possible that some RRM-type RNA-binding proteins play important roles in regulation of mRNA metabolism and cell homeostasis under stress conditions. Microarray analyses showed that some stress-responsive transcripts such as RD20, COR15A, AtGolS2, and PP2C are upregulated in the mutant of DCP2 that encodes a component of the decapping complex [17]. Taken together, the results of studies on SGs and PBs suggest that they are key cytoplasmic structures for controlling gene expression during plant stress responses.
activation, in response to dehydration stress. Dehydration stress resulted in enrichment of H3K23ac and H3K27ac at the coding regions of RD29B, RD20, and At2g20880, but not at the coding region of RD29A. H3K4me3 enrichment occurred on the coding regions of RD29A and At2g20880 after accumulation of Pol II. However, these reports describe only isolated examples of chromatin modification during stress responses. Large-scale analyses using ChIP-seq or ChIP-chip methods are necessary to increase our understanding of the roles of histone modification in abiotic stress responses.
Metabolome analyses in abiotic stress responses The metabolic changes in plants in response to environmental stress factors have been extensively analyzed using several MS technologies and bioinformatics [28]. Integrated metabolome and transcriptome analyses of model plants have markedly increased our understanding of plants’ responses to various stresses. Metabolite profiling has been used to characterize stress responses to abiotic stresses such as water deficit (dehydration and high salinity) and extreme temperature (cold and heat) for comprehensive analyses of the final steps of stress signal transduction pathways. Dehydration-stress response
Histone modification under abiotic stress conditions
Changes of transcriptional states in response to environmental stresses are coupled with chromatin remodeling. In general, these changes are accompanied by posttranslational modification of histone N-tails such as acetylation, methylation, and phosphorylation [22,23]. Various modifications of histones occur during stress responses in plants [24,25,26]. The chromatin immunoprecipitation (ChIP) assay is the best method to detect the state of histone modification under stress conditions. Tri-methylation of histone H3 Lys27 (H3K27me3) is generally a negative marker of transcription [27]. Using ChIP assays, Kwon et al. demonstrated that H3K27me3 modification gradually decreases at the loci of two cold-responsive genes, COR15A and AtGolS3, during exposure to cold temperatures [24]. When coldexposed plants are returned to normal conditions, transcriptions of these genes are repressed to their initial levels, but the cold-triggered decrease in H3K27me3 is still maintained. This decrease does not enhance the induction of transcription when plants are returned to cold temperatures. Using ChIP assays, Kim et al. monitored histone H3 modifications at the coding regions of four dehydrationstress-responsive genes, RD29A, RD29B, RD20, and an AP2 transcription factor (At2g20880), during dehydration stress [25]. At all four gene loci, there was an enrichment of H3K4me3 (tri-methylation of H3 Lys4) and H3K9ac (acetylation of H3 Lys9), a positive marker of gene Current Opinion in Plant Biology 2010, 13:132–138
Molecular studies on the dehydration-stress response have revealed both abscisic acid (ABA)-dependent and ABA-independent pathways [1]. The endogenous ABA level significantly increases response to water-deficit stress to regulate physiological stress responses and gene expression. Recently, an integrated analysis of the metabolome and transcriptome of the dehydration-stress response was carried using GC-TOF–MS, CE-MS, and DNA microarrays. These methods were used to analyze the dehydration-stress response of an Arabidopsis NCED3-knockout mutant and the wild-type plant [29]. NCED3 plays a role in the dehydration-inducible biosynthesis of ABA [1]. Metabolite profiling revealed that the ABA accumulated during dehydration regulates the accumulation of various amino acids and sugars such as glucose and fructose. In particular, the dehydrationinducible accumulations of BCAAs (branch-chain amino acids), saccharopine, proline, and agmatine are correlated with the dehydration-inducible expression of their key biosynthetic genes (BCAT2, LKR/SDH, P5CS1, and ADC2, respectively), which are regulated by endogenous ABA. On the contrary, the levels of raffinose and galactinol are not regulated by ABA during dehydration stress. In addition, metabolic network analysis showed global metabolite–metabolite correlations among dehydrationincreased amino acids in the WT, but a strong correlation between dehydration stress and raffinose in the nced3 mutant. These results indicated that ABA has an important role in regulating the metabolic changes that occur during the dehydration-stress response. www.sciencedirect.com
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Transcript and metabolite profiles were compared between dehydration and salinity stress in grapevine [30]. Metabolic profiling revealed higher concentrations of glucose, malate, and proline in dehydration-treated plants, compared with salt-stressed plants [30]. These differences in the levels of metabolites were correlated with those of transcript levels of many genes involved in energy metabolism and nitrogen assimilation. Compared with salt-stressed plants, dehydration-treated plants have a greater need to adjust osmotically, detoxify ROS, and ameliorate photoinhibition [30]. Metabolic profiling revealed that sucrose replaces proline in plants as the major osmoprotectant during the more severe combined dehydration and heat-stress treatment [31].
response to heat shock overlapped with those produced in response to cold shock. Moreover, these results suggested that a metabolic network of compatible solutes including proline, monosaccharides (glucose and fructose), galactinol, and raffinose has an important role in tolerance to temperature stress. Natural variations in freezing tolerance were analyzed in nine Arabidopsis accessions. Plants acclimating to cold conditions were analyzed using a combination of genomewide transcript profiling and metabolite profiling. The global changes in metabolite profiles were not correlated with plants’ responses to cold stress, whereas global changes in transcriptome profiles were correlated with plants’ abilities to acclimate to cold conditions [36].
Temperature stress response
Plants’ responses and acclimation to temperature stress have been precisely characterized by metabolite profiling [32,33,34–36]. A recent metabolome analysis showed common metabolites in the responses to cold and other stresses, and demonstrated a prominent role for the DREB1/CBF (dehydration responsive element-binding factor/C-repeat) transcriptional network in the coldresponse pathway [32,33]. In Arabidopsis and rice, the DREB1/CBF cold-response pathway is one of the most well-characterized genetic systems in cold-responsive gene expression and acclimation [1]. Metabolome analysis of transgenic Arabidopsis overexpressing DREB1A/CBF3 revealed that there is a striking similarity between the low-temperature regulated metabolome (monosaccharides, disaccharides, oligosaccharides, and sugar alcohols) and that regulated by the DREB1A/ CBF3 transcription factor [32,33]. In particular, the low-temperature-inducible accumulation of galactinol and raffinose is correlated with the expression of the GolS3 gene, which is a direct target of DREB1A/CBF3 [32,33]. In addition, Maruyama et al. also analyzed increased metabolites with those in cold-treated plants, those accumulated in the 35S:DREB1A-overexpressing transgenic plants and 35S DREB2A-CA (active form of DREB2A)-overexpressing transgenic plants. DREB2A overexpression did not increase the level of any lowtemperature regulated metabolites in transgenic plants [33]. It was previously reported that overexpression of DREB2A-CA in transgenic plants increased their tolerance to dehydration stress, but only slightly increased their tolerance to freezing stress [1]. These results indicate that the increased tolerance to freezing stress in transgenic plants overexpressing DREB1A may depend on the accumulation of low-temperature regulated metabolites, especially sucrose, raffinose, galactinol, and myo-inositol. Comparative metabolite analysis between Arabidopsis Columbia (Col-0) plants responding to heat shock and cold shock was carried out using GC–MS [34] and GCTOF–MS [35]. The majority of metabolites produced in www.sciencedirect.com
Salt stress response
Metabolome analysis of a new model halophyte was carried out to clarify aspects of genome evolution under salt stress. GC–MS and microarrays were used to analyze Arabidopsis and Thellungiella halophila, a closely related halophytic species [37]. Metabolome analyses revealed drastically different profiles between the two species. Compared with Arabidopsis, Thellungiella maintained higher levels of metabolites levels in both the absence and presence of salt stress. Even in control conditions, Thellungiella contains higher levels of various osmolytes, such as fructose, sucrose, complex sugars, malate, and proline, compared with Arabidopsis. Transcriptome analysis also showed that several stress-related genes were expressed at high levels in Thellungiella, even in the absence of salt stress [37]. The results suggest that a constant state of stress-anticipatory preparedness exists in Thellungiella. Metabolic profiles of Arabidopsis T87 cell cultures responding to salt stress were analyzed using GC–MS and LC–MS [38]. This metabolome analysis was focused on data mining of metabolite profiles at different time points after high-salinity treatment by using principal component analysis (PCA) and batchlearning self-organizing mapping analysis (BL-SOM). The results revealed synergetic induction of several pathways; the methylation cycle for the supply of methyl groups, the phenylpropanoid pathway for lignin production, and glycinebetaine biosynthesis, during the short-term response to salt stress. In the long-term response to salt stress, however, glycolysis and sucrose metabolism were co-induced, and then the methylation cycle was co-reduced. ABA was also shown to have important roles in determining metabolite profiles of Arabidopsis under salt stress [39]. Data-mining analysis of metabolite profiles by GC-TOF–MS and public transcript data by AtGenExpress demonstrated that a complex readjustment of carbohydrate metabolism occurs during salt stress, and Current Opinion in Plant Biology 2010, 13:132–138
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Figure 2
Transcriptome and metabolome regulation of dehydration, high-salinity, and low-temperature stress responses in Arabidopsis. The abscisic acid (ABA)-dependent and DREB/CBF pathways are important in osmotic stress response. ABA and DREB/CBF regulate gene expression and the stress metabolome [29,32,33]. ABA regulates biosynthesis of several amino acids and monosaccharides [29]. Some are regulated at the transcriptional level. During dehydration stress, biosyntheses of branched-chain amino acids (BCAA), polyamines, proline, and saccharopine rely on branched-chain aminotransferase (BCAT2), arginine decarboxylase (ADC2), D1-pyrroline-5-carboxylate synthase (P5CS1), and lysine ketoglutarate reductase/ saccharopine dehydrogenase (LKR/SDH), respectively [29]. On the contrary, biosyntheses of RFO (raffinose family oligosaccharides) biosynthetic pathway was not controlled by ABA [29]. DREB1/CBF regulated galactinol synthase, GolS3 expression that is key gene for RFO at low temperatures [32,33].
that ABA triggers the initial steps of carbon mobilization.
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Conclusions and perspectives Remarkable technical advances in transcriptomics and metabolomics are available to clarify the molecular configuration in response to abiotic stress (Figure 2). ‘Omics’ analyses are crucial to understand the whole processes of molecular networks in response to abiotic stress. It is important to elucidate the functions of newly identified stress-responsive protein-coding and non-coding RNAs to understand the complex abiotic stress responses of plants. Integrated metabolome and transcriptome analyses have revealed that many important metabolic pathways are regulated at the transcriptional level. However, there are also many metabolic pathways that are not regulated at the transcriptional level [40], but at a post-transcriptional level, for example, by RNA processing, translational, post-translational regulation, or feedback mechanisms. In addition, metabolites not only have functional roles in stress tolerance but also act as signaling molecules [41]. Integrated omics analyses are necessary to identify the broad function of metabolite regulatory networks during responses to abiotic stresses. Current Opinion in Plant Biology 2010, 13:132–138
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41. Verbruggen N, Hermans C: Proline accumulation in plants: a review. Amino Acids 2008, 35:753-759.
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