Comprehensive expression analysis suggests overlapping and specific roles of rice glutathione S-transferase genes during development and stress responses
© Jain et al; licensee BioMed Central Ltd. 2010
Received: 3 August 2009
Accepted: 29 January 2010
Published: 29 January 2010
Glutathione S-transferases (GSTs) are the ubiquitous enzymes that play a key role in cellular detoxification. Although several GSTs have been identified and characterized in various plant species, the knowledge about their role in developmental processes and response to various stimuli is still very limited. In this study, we report genome-wide identification, characterization and comprehensive expression analysis of members of GST gene family in crop plant rice, to reveal their function(s).
A systematic analysis revealed the presence of at least 79 GST genes in the rice genome. Phylogenetic analysis grouped GST proteins into seven classes. Sequence analysis together with the organization of putative motifs indicated the potential diverse functions of GST gene family members in rice. The tandem gene duplications have contributed a major role in expansion of this gene family. Microarray data analysis revealed tissue-/organ- and developmental stage-specific expression patterns of several rice GST genes. At least 31 GST genes showed response to plant hormones auxin and cytokinin. Furthermore, expression analysis showed the differential expression of quite a large number of GST genes during various abiotic stress (20), arsenate stress (32) and biotic stress (48) conditions. Many of the GST genes were commonly regulated by developmental processes, hormones, abiotic and biotic stresses.
The transcript profiling suggests overlapping and specific role(s) of GSTs during various stages of development in rice. Further, the study provides evidence for the role of GSTs in mediating crosstalk between various stress and hormone response pathways and represents a very useful resource for functional analysis of selected members of this family in rice.
Glutathione transferases (GSTs, EC 220.127.116.11), formerly known as glutathione S-transferases, are the enzymes involved in cellular detoxification by conjugating the tripeptide (γ-Glu-Cys-Gly) glutathione (GSH) to a wide variety of substrates such as endobiotic and xenobiotic compounds . GSTs have been identified in all the organisms, including plants, animals, fungi and bacteria analyzed to date [2, 3]. Although most of GSTs exist as soluble enzymes, distantly related mitochondrial Kappa GSTs and microsomal GSTs have also been identified in animals . GST proteins are represented by a multi-gene family in plants similar to other organisms [5–7]. Several GSTs have been identified and characterized in various plant species with differential and overlapping substrate specificities [5, 8, 9]. Based on the predicted amino acid sequences, the soluble GSTs in plants have been grouped into several classes, including Phi, Tau, Lambda, dehydroascorbate reductase (DHAR), Theta, Zeta, elongation factor 1 gamma (EF1G) and tetrachlorohydroquinone dehalogenase (TCHQD). Among these classes, Phi, Tau, Lambda and DHAR classes are plant specific .
Plant GSTs have been a focus of attention because of their role in herbicide detoxification. Some evidences showed that GSTs are present at every stage of plant development from early embryogenesis to senescence and in every tissue type examined [5, 7, 11]. GSTs have been found to be differentially regulated by a variety of stimuli, including abiotic and biotic stresses, plant hormones such as auxins, cytokinins and ABA, heavy metals, GSH and hydrogen peroxide [12–15]. Despite their suspected crucial role in stress responses and significant efforts made, the specific role(s) of GST enzymes have not been elucidated. The role of plant GSTs has also been proposed in the transport and metabolism of secondary compounds [16–18]. Plant GSTs can also act as glutathione peroxidases [19, 20], protect cells from oxygen toxicity  and suppress apoptosis . Some of plant GSTs were originally identified as auxin- and cytokinin-binding proteins [23–25], pointing their role in hormone signal transduction pathways as well.
Among GSTs, the members of Tau and Phi classes are most studied in plants. The reason may be attributed to their larger number. They are dimeric and catalyze the conjugation of a diverse range of xenobiotics and detoxify selective herbicides . Theta GSTs have limited transferase activity towards xenobiotics but are highly active GSH-dependent peroxidases . Zeta class GSTs have been shown to differ from other GSTs in showing no GSH conjugating or GSH peroxidase activity, rather these are involved in GSH-dependent tyrosine catabolism [26, 27]. The recently discovered DHAR class GSTs are monomeric and act as GSH-dependent oxidoreductases . EF1G class of GST proteins encodes γ subunit of eukaryotic translation elongation factor. It has been proposed that the N-terminal GST domain present in this class of proteins may be involved in mediating the assembly of EF1 and regulation of formation of multisubunit complexes containing EF1 . Another recently identified GST from Arabidopsis closely resembles the TCHQD enzymes from prokaryotes . The functional characterization of this protein has not been reported.
Although quite a few GST proteins have been characterized in rice, the functions of majority of members in this family remain unknown. In the first identification and classification of GST family in rice based on analysis of EST database and unfinished genomic sequence, a total of 61 members were identified and their expression patterns analyzed by querying EST databases . In this study, the members of GST family in rice have been reanalyzed based on complete genome sequence and annotation, and a total of 79 putative GST genes were identified. In addition, a comprehensive expression analysis during various stages of development, hormone treatments, abiotic and biotic stress conditions, have been performed. The results reported in this study will provide a very useful reference for further functional analysis of members of this family in rice.
Results and Discussion
Identification of genes encoding GST proteins in rice
GSTs are represented by multigene family in plants. Several members of GST family have been identified and divided into different classes in Arabidopsis, maize and soybean [5, 6]. Soranzo et al  reported the presence of 61 members of GST family in rice based on analysis of EST database and unfinished genomic sequence and divided them into four classes. In this study, we performed domain search for the proteins containing GST N-terminal domain (PFAM domain PF02798) in the Rice Genome Annotation Project (RGAP) database (release 5) or HMM profile search against the downloaded proteome of rice. Subsequently, the proteins which did not show the presence of GST_N domain (characteristic of GST proteins) in SMART analysis were eliminated. Taken together, a total of 79 non-redundant gene loci were predicted to contain GST_N domain and encode putative GST proteins in rice. The number of GST proteins predicted in this study is 29.5% greater than the previously reported number in rice (61) . A comparative analysis showed that 52 among the 61 ESTs/cDNA clones encoding GST proteins in rice reported by Soranzo et al  correspond to the gene loci predicted in this study. The sequences for five genes (NM_1903851, OsGSTF11; P0493G01.11, OsGSTF13; OJ1006_F06.6, OsGSTF16; OSJNBa0033P04.19, OsGSTU36 and OSJNBa0018H01.7, OsGSTMU37) could not be retrieved as they have become obsolete entries in NCBI, OsGSTU6 (AF379376) represents a viral sequence, OsGSTT2 (AY541762) has been annotated as a ty1-copia subclass retrotransposon, OsGST35 (AY533125) did not show the presence of GST_N domain and OsGSTU7 (AF402794) was redundant with another GST gene OsGSTU18 (AF402805). In total, this study reports 27 new gene loci encoding GST proteins in rice as compared to Soranzo et al . The locus ID, open reading frame length, protein length and chromosomal location of all the 79 GST genes are given in Additional file 1.
To reveal the evolutionary relationship among the rice GST proteins, a phylogenetic tree was generated using their full-length protein sequences (Additional file 2). The results suggested that the rice GST family can be classified into seven classes (Additional file 2). Based on the protein sequence alignments and evolutionary relationship, largest number of GST genes (52) were included in Tau class followed by 17 genes in Phi, four in Zeta, two in DHAR, two in EF1G and one each in Theta and TCHQD classes. The members included in Tau, Phi, Zeta, DHAR, EF1G, Theta and TCHQD classes were designated as OsGSTU, OsGSTF, OsGSTZ, OsDHAR, OsEF1G, OsGSTT and OsTCHQD, respectively, followed by a number (Additional file 1). To keep the nomenclature of GST family consistent, the name of reported genes has been retained and the systematic names of the genes reported previously but not identified in this study were assigned to newly identified members (Additional file 1). All the newly identified members within a class were named according to their sequential position on rice chromosomes from top to bottom.
Tandem duplications are responsible for the family expansion
Differential expression of GST gene family members in various tissues/organs
Although the roles of GSTs have been explored in various stress responses, the evidences for their role in plant growth and development are very limited. The overlapping and tissue-specific expression patterns of GST genes have been observed in some plant species, including rice, by querying EST databases [5, 7, 9]. The study of gene expression patterns of all the members of a gene family provides insight into their functional diversification. The expression evidence for 62 of the rice GST genes was found in terms of the availability of their corresponding full-length cDNA and/or EST evidence. We surveyed the transcript accumulation of GST genes across a wide range of tissues/organs and developmental stages of rice employing two approaches. In the first approach, we used the data from rice Massively Parallel Signature Sequencing (MPSS) database to quantify the expression of individual GST gene. MPSS technology provides a quantitative measure of transcript accumulation of virtually all the genes in a tissue sample in terms of number of small signature sequences corresponding to each gene . The survey of 22 rice MPSS libraries  representing 18 tissue samples showed that at least 77 GST genes have corresponding 17 base signatures, suggesting that most of the GST genes are expressed in rice. However, significant signatures (that uniquely identify individual GST gene) were found for 61 GST genes (Additional file 4). The number of tags (in tpm, tags per million) for rice GST genes varied significantly, indicating marginal (1-3 tpm) to strong (>250) expression. In addition, the number of tags revealed differential expression patterns of individual GST genes in various rice tissues/organs.
The expression of eight Tau class GST genes (OsGSTU9, 22, 25, 27, 31, 32, 33 and 34) for which microarray data was not available, was explored in terms of availability of their corresponding FL-cDNA, EST and/or MPSS tags. We found all these evidences of expression (FL-cDNA, EST and MPSS tags) for three GST genes (OsGSTU9, U27 and U34) and one GST gene (OsGSTU22) had corresponding FL-cDNA/EST available. Although MPSS tags were available for other four GST genes, significant (that uniquely identify individual gene) tags were available for two (OsGSTU31 and 33) of them. Among these GST genes, OsGST9 was expressed in a wide range of tissues, whereas OsGSTU27, 31, 33 and 34 were preferentially expressed in stressed and/or non-stressed young roots (Additional file 4). Taken together, our results indicate that all the 79 GST genes identified in this study are expressed in one or the other rice tissue and exhibit overlapping and/or specific expression patterns with quantitative differences.
Duplicated GST genes exhibit redundant and divergent expression patterns
To investigate the probable explanation for divergence in expression patterns of duplicated GST genes, we analyzed their promoter sequences 1 kb upstream of translational start site. The putative cis-regulatory elements were identified using PLACE (a database of plant cis-acting regulatory DNA elements) search. This analysis revealed that the regulatory elements are more conserved in duplicated GST genes with similar expression patterns (for example, OsEF1G1/EF1G2 and OsGSTF6/F14) as compared to the GST genes with divergent expression patterns (for example, OsGSTF12/F17 and OsGSTU51/U52). The considerable difference in the regulatory elements of duplicated genes might explain their divergent expression patterns. However, experimental validation is required to reach this conclusion. Further, the existence of some other regulatory mechanism, which is responsible for divergent expression patterns and/or non-functionalization of one of the duplicates, can not be ruled out.
Differential expression of GST genes during hormone treatment
Some of the plant GSTs are induced by plant hormones auxins and cytokinins. The transcript level of GST genes is induced very rapidly in the presence of auxin [37, 38]. In this study, we used two microarray datasets to assess the effect of auxin and cytokinin on the expression profiles of GST genes. First dataset includes microarray analysis of 7-day-old rice seedlings treated with indole-3-acetic acid (IAA) and benzyl aminopurine (BAP) up to 3 h each . Second dataset includes microarray analysis of root and leaf tissues of two-week-old seedlings treated with trans-zeatin (tZ) for 30 min and 120 min . The data analysis showed that a total of 31 GST genes exhibit significant differential expression under at least one of the conditions analyzed (Additional file 8, 9). Interestingly, majority (27) of them belonged to Tau class. Quite a large number (14) of GST genes showed differential expression in the presence of auxin. All but one (OsGSTF10) of these 14 genes were up-regulated significantly. A total of 24 genes were differentially expressed in the presence of cytokinin. Three genes which showed up-regulation in the presence of BAP in first dataset did not show any differential expression in the presence of tZ in second dataset. Among the 21 genes which showed differential expression in the second dataset, 11 genes were differentially expressed in roots as compared to 15 in leaf. Five genes showed differential expression both in roots and leaf, whereas six and ten genes were unique to root and leaf, respectively. These results suggest the differential response of rice GST genes with respect to age of seedlings, tissue-type and/or cytokinin type. The differential expression of some representative genes in the presence of IAA and/or BAP has also been validated by real-time PCR analysis (Additional file 8).
Differential expression of GST genes during abiotic stress
Differential expression of GST genes during biotic stress
Striga hermonthica is an obligate root hemiparasite of rice and other cereals that causes severe loss of yield. To understand the possible interaction between rice roots and parasitic plant S. hermonthica at molecular level, global gene expression profiling was performed by Swarbrick and colleagues . We took advantage of the availability of this data to study the expression profiles of rice GST genes in roots of susceptible (IAC165) and highly resistant (Nipponbare) cultivars in response to infection with S. hermonthica after 2, 4 and 11 dpi. The data analysis revealed that at least 17 genes were significantly up- and down-regulated by more than 2-fold in Nipponbare as compared with 28 genes in susceptible IAC165 cultivar (Fig. 7, Additional file 12). In IAC165, 15 and 13 genes were up- and down-regulated, respectively, whereas nine and eight GST genes were up- and down-regulated, respectively, in Nipponbare. Twelve GST genes showed differential expression in both cultivars. Among the total 48 GST genes differentially expressed in two datasets, 30 genes belonged to Tau class, 12 to Phi, two to Zeta, two to EF1G and one each to DHAR and TCHQD classes.
Overlap of GST responses to various stimuli and developmental processes
Given that plant GSTs are induced by a plethora of environmental factors, it was proposed that GST expression is universally induced by the production of stress-associated active oxygen species (AOS) signaling molecules, which in turn counteracts the adverse effects of AOS by their GSH-dependent peroxidase activity . However, our study showed that, although several GSTs are commonly regulated, many of them exhibit differential and specific response to various stresses as well. Similar observations have been reported in other studies too [6, 15]. These results indicate that the induction of GST family members occurs via multiple and independent pathways and a subset of which may involve AOS as signaling molecules. It has been reported that GSTs are induced very rapidly by pathogens and typically precede the induction of well-known defense genes such as pathogenesis-related proteins [42, 46, 47]. Based on analysis of mutants, this rapid induction of GSTs has been found to be dependent on combined SA- and ethylene signaling . This was further supported by the increased production of SA and ethylene by the plants inoculated with pathogen . This clearly indicates a cross-talk between various signaling pathways.
Many evidences show crosstalk between various developmental processes and environmental stimuli [30, 38, 48]. We also found relation between tissue-/developmental stage-specific expression pattern and stress responses of few GST genes. For example, OsGSTU4 is preferentially expressed in the root and stages of seed development and was also found to be highly up-regulated by plant hormones, abiotic stress, arsenate stress and biotic stress conditions. Likewise, OsGSTU5 and OsGSTU37 are preferentially expressed in root and are also up-regulated by auxin and various stress conditions. The OsGSTF10 was specifically expressed in root and was down-regulated by most of the environmental stimuli analyzed in this study. Other GST genes, OsGSTU10, U18 and U36, which were preferentially expressed in root, were also down-regulated by one or more of the stimuli. These commonly regulated GST genes might mediate plant growth responses to various environmental stimuli in specific tissues/organs and/or developmental stage.
This study provides not only an updated annotation and nomenclature of the GST family in rice, but also the identification of several tissue- and/or developmental stage-specific, hormone-responsive and abiotic and biotic stress-responsive GST genes included in various classes. Considering the fact that a very limited number of GST genes have been characterized till date, our results provide a very useful framework and starting point for revealing the function(s) of GST family members in rice, especially those involved in specific developmental processes, hormone response and stress tolerance.
Database search and sequence analysis
GSTs were identified by keyword, domain name and HMMER searches of rice proteome available at Rice Genome Annotation Project  database using the Hidden Markov Model (HMM) profile (build 2.3.2) of GST_N domain (PF02798) downloaded from PFam. The presence of GST_N domain in individual protein was further confirmed by SMART analysis. Multiple sequence alignment analyses were performed using ClustalX (version 1.83) program. The GST genes present on duplicated chromosomal segments were identified by segmental genome duplication of rice available at RGAP with the maximum length distance permitted between collinear gene pairs of 500 kb. The GST genes separated by a maximum of five genes were identified as tandemly duplicated genes. The unrooted phylogenetic trees were constructed by neighbor-joining method and displayed using Treeview program. Putative conserved motifs were identified using MEME (version 4.1.0) program .
The tissue samples of mature leaf, Y leaf and various stages of panicle and seed development were collected from field grown rice (Oryza sativa ssp. indica var. IR64) plants as described . Roots were harvested from 7-day-old seedlings grown hydroponically. For salt, desiccation, cold and arsenate stress treatments, 7-day-old light-grown rice (Oryza sativa L. ssp. indica var. IR64) seedlings were transferred to a beaker containing 200 mM NaCl solution, dried between folds of tissue paper at 28 ± 1°C, kept at 4 ± 1°C and, transferred to a beaker containing 50 μM sodium arsenate solution, respectively, each for 3 h. Likewise, 7-day-old light-grown rice seedlings were transferred to a beaker containing 50 μM solution of indole-3-acetic acid and 50 μM solution of benzyl aminopurine for auxin and cytokinin treatment, respectively. The control seedlings were kept in water for 3 h, at 28 ± 1°C.
Microarray data analysis
The microarray data publicly available at GEO database under the series accession numbers GSE6893 (expression data for reproductive development), GSE7951 (expression profiling of stigma), GSE6901 (expression data for stress treatment), GSE4471 (expression data from rice varieties Azucena and Bala grown in arsenate), GSE5167 (expression data for auxin and cytokinin response), GSE6719 (expression data for cytokinin response), GSE7256 (expression data for virulent infection by Magnaporthe grisea), and GSE10373 (expression data for interaction with the parasitic plant Striga hermonthica) were used for expression analysis of rice GST genes. The entire microarray experiments used in this study are listed in Additional file 5. The Affymetrix CEL files were imported into Genespring GX (version 10) software (Agilent Technologies). The normalization and probe summarization was performed by Gene Chip Robust Multi Array (GCRMA) method. We performed a stringent statistical analysis consisting of one-way ANOVA over all the samples in a series and the Benjamini-Hoschberg multiple testing correction was applied to the data (P ≤ 0.05).
The IDs of probe sets present on the Affymetrix rice genome array representing the GST genes were identified using Rice Multi-platform Microarray Search  tool. The data for only one probe set for each GST gene was used for expression analysis. This resulted in identification of probe sets for 71 GST genes that were represented on the Affymetrix rice genome array. After normalization and log transformation of data for all the rice genes present on the chip, the log signal intensity values for rice probe IDs corresponding to GST genes were extracted as a subset and all the subsequent analyses were done on this subset only. The genes that are up- or down-regulated equal to or more than two-fold with a P-value of at least 0.05 were considered to be differentially expressed significantly. We generated tab-delimited files for average log signal values for development data and fold-change values for abiotic stress, biotic stress and hormone treatments and imported them into TIGR MultiExperiment Viewer (MeV)  to carry out clustering analysis. Hierarchical clustering was performed based on Euclidean distance matrix and Complete Linkage rule.
Real-time PCR analysis
To confirm the differential expression of representative GST genes in various rice tissues/developmental stages and stress/hormone treatments identified by microarray data analysis, real-time PCR analysis was performed using gene-specific primers as described earlier . The primer sequences are listed in Additional file 14. At least three biological replicates of each sample and three technical replicates of each biological replicate were analyzed for real-time PCR analysis. The expression of each gene in different RNA samples was normalized with the expression of the suitable internal control gene, UBQ5  to ensure the equal amount of cDNA used for individual reactions. The mRNA levels for each candidate gene in different tissue samples were calculated using the ΔΔCT method.
MPSS data analysis
Expression evidence from MPSS (Massively Parallel Signature Sequencing) tags was determined from the Rice MPSS project [32, 54]. The signature was considered to be significant if it uniquely identifies an individual gene and shows perfect match (100% identity over 100% of the length of the tag). The normalized abundance (tags per million, tpm) of these signatures for a given gene in a given library represents the quantitative estimate of expression of that gene. MPSS data for 17-base signatures from 22 mRNA libraries representing 18 different tissues/organs of rice (Additional file 4) were used for the analysis.
This work was supported by the Department of Biotechnology, Government of India, New Delhi, under the Innovative Young Biotechnologists Award scheme and core grant from NIPGR. CG and AB acknowledge the award of research fellowship from the Department of Biotechnology and the Council for Scientific and Industrial Research, New Delhi, respectively. We are thankful to Professor Akhilesh K. Tyagi for reading of the manuscript.
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