Epigenetic regulation during salinity stress response in chickpea (WGBS)
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ABSTRACT:
PROVIDER: PRJNA842020 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR19383309_1.fastq.gz | Fastqsanger.gz | |||
| SRR19383309_2.fastq.gz | Fastqsanger.gz | |||
| SRR19383310_1.fastq.gz | Fastqsanger.gz | |||
| SRR19383310_2.fastq.gz | Fastqsanger.gz | |||
| SRR19383311_1.fastq.gz | Fastqsanger.gz |
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Project description:Bisulphite sequencing of salinity sensitive and salinity tolerant chickpea genotypes during salinity stress response using Illumina platform has been performed. At least 195 million reads in bisulphite sequencing were generated in each sample. Methylated cytosines in each sample were identified for their genomic location and sequence context.
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Project description:In this study, we aim to present a global view of transcriptome dynamics during salinity stress in different chickpea genotypes. We generated about 600 million high-quality reads from 16 libraries (control and stress samples for two chickpea genotypes for salinity stress at two developmental stages) using Illumina high-throughput sequencing platform. We mapped the reads to the kabuli chickpea genome for estimation of their transcript abundance in different tissue samples. The transcriptome dynamics was studied by differential gene expression analyses between stress treatment and control sample for each genotype.
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Project description:Salinity stress response in chickpea
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Project description:In this study, we performed transcriptomic analysis salinity stress response in salinity sensitive and tolerant genotypes of chickpea using Illumina platform. A total of 87 million reads in RNA-sequencing data were generated in all the samples. Mapping of the reads to the Kabuli genome was performed using tophat (v2.1.1). Differentially expressed genes were identified using cufflilnks-cuffdiff (2.2.1) pipeline.
2023-02-15 | GSE204727 | GEO
Project description:In this study, we aim to present a global view of transcriptome dynamics during various abiotic stresses in chickpea. We generated about 252 million high-quality reads from eight libraries (control, desiccation, salinity and cold stress samples for roots and shoots) using Illumina high-throughput sequencing GAII platform. We mapped the reads to the desi chickpea genome for estimation of their transcript abundance in different tissue samples. The transcriptome dynamics was studied by differential gene expression analyses between stress treatment and control sample. We collected different tissue samples (root and shoot tissues of 10-day-old seedlings subjected to control (kept in water), desiccation (transferred on folds of tissue paper), salinity (transferred to beaker containing 150 mM NaCl solution) and cold (kept in water at 4 M-BM-1 1M-BM-0C) stress for 5 h. Total RNA isolated from these tissue samples was subjected to Illumina sequencing. The sequenced data was further filtered using NGS QC Toolkit to obtain high-quality reads. The filtered reads were mapped to annotated chickpea genome using TopHat and fragments per exon kilobase per million (FPKM) was calculated using Cufflinks software for each gene in all the sample to measure their gene expression. Differential expression analysis was performed using Cuffdiff software. The differentially expressed genes during various abiotic stress conditions were identified.
2014-08-27 | E-GEOD-53711 | biostudies-arrayexpress
Project description:‘Pulsechip’, a boutique cDNA microarray, generated from a set of chickpea (Cicer arietinum L.) unigenes, grasspea (Lathyrus sativus L.) ESTs and lentil (Lens culinaris Med.) resistance gene analogs, was employed to generate an expression profile of chickpea accessions tolerant and susceptible to high-salinity stress. Two groups of a tolerant and susceptible accession were challenged with high-salinity stress. The experiments were performed in three biological replications. The experiments were conducted in reference design where respective tissues from unstressed plants served as control. The leaf/shoot and root tissues were collected at 24 and 48 h post-treatment (hpt) and used for hybridization to measure changes in RNA abundance of treatment vs. control. The tissues from five experimental replicate plants per biological replication were pooled together (shoot and root tissues separate for each time point) before RNA extraction. This RNA was used to prepare cDNA targets for expression analysis using microarray. The microarray had six technical replicate spots per EST. The transcript level for each EST/cDNA was firstly calculated as the average intensity of the six technical replicates and then the average intensity of three biological replicates. Data analysis included LOWESS normalization (LOcally WEighted polynomial regreSSion) to adjust for differences in quantity of initial RNA, labeling and detection efficiencies. A dye swap in one biological replicate adjusted dye bias, if any. The Differentially Expressed (DE) ESTs were identified as those with a 95% confidence interval for mean fold change (FC) that extended beyond the two-fold cut-off and also passed the Students t test (P<0.05) and FDR correction. These cut-offs translate into induced ESTs having a log2 ratio > 1 and repressed ESTs a ratio of < -1. The analysis consisted of three fold comparison. Firstly, the ESTs that were differentially expressed between treatment and control plants of each accession were detected. Then the ESTs that were similarly expressed by tolerant and susceptible accessions were then eliminated by comparison. This included a two-way comparison, where tolerant and susceptible genotypes were compared within and between groups. Lastly, ESTs that were consensually differentially expressed between tolerant and susceptible accessions of the two batches were identified. The hypothesis was that if a putative gene was consistently expressed only in tolerant or susceptible genotype for a particular stress, it might be a candidate for tolerance/susceptibility for that stress. Globally, the level of 409 transcripts was affected in response to high-salinity stress in all the genotypes and tissue types studied. Of the transcripts consistently expressed in tolerant genotypes in response to high-salinity stress, the annotation of transcripts at 24 hpt suggest a reduction in energy production in shoots and roots by repression of putative genes including P700 chlorophyll a-apoprotein (DY475501) and NADH-plastoquinone oxidoreductase subunit I (DY475287), cytosolic fructose 1,6-bisphosphatase (DY475548) and splicing factor-like protein (DY396290). The ATHP3 (DY396300) and protein kinase (DY475077) that are potentially involved in signalling cascades responsible for sensing and relaying osmotic stress signals, were consistently repressed in tolerant genotypes in response to high-salinity. Additionally a glycine rich protein (DY396342) that is associated with lignification of cell walls in response to wounding and pathogen attack was repressed in tolerant genotypes. In tolerant genotypes at 48 hpt, two energy and metabolic-related transcripts were consistently repressed in roots, including a carbonic anhydrase (DY475403) and putative thiazole biosynthetic enzyme (DY475242). In shoots, only a pathogenesis-related protein (DY396301) was consistently repressed at 48 hpt, but a similar transcript (DY396281) was induced in roots of tolerant genotypes at the same time. Only four transcripts were DE in susceptible genotypes at 24 hpt, all occurring in root tissue. Two of these were unknown/unclear, but the others included a proline oxidase transcript (DY475225) and a nuclear transport factor 2 (DY396436). At 48 hpi, a putative splicing factor-like protein (DY396290) and polyubiquitin (DY396328) were repressed in roots of susceptible genotypes. Interstingly, a putative xylosidase (DY475408) was induced in susceptible roots at 48 hpi. Finally, several unknown/unclear transcripts were DE in both tolerant and susceptible genotypes. Of interest were two unknowns (DY475293 and DY475521) that were consistently expressed in tolerant genotypes and may be important for high-salinity tolerance. Keywords: Chickpea, High-salinity stress, tolerant, susceptible, cDNA microarray
2007-04-03 | GSE7418 | GEO
Project description:In this study, we aim to present a global view of transcriptome dynamics during various abiotic stresses in chickpea. We generated about 252 million high-quality reads from eight libraries (control, desiccation, salinity and cold stress samples for roots and shoots) using Illumina high-throughput sequencing GAII platform. We mapped the reads to the desi chickpea genome for estimation of their transcript abundance in different tissue samples. The transcriptome dynamics was studied by differential gene expression analyses between stress treatment and control sample.
2014-08-27 | GSE53711 | GEO
Project description:Gene expression profiling during salinity stress response in chickpea (RNA-Seq)
| PRJNA842022 | ENA
Project description:‘Pulsechip’, a boutique cDNA microarray, generated from a set of chickpea (Cicer arietinum L.) unigenes, grasspea (Lathyrus sativus L.) ESTs and lentil (Lens culinaris Med.) resistance gene analogs, was employed to generate an expression profile of chickpea genotype ICC 3996 to drought, cold and high-salinity stresses. The experiments were performed in three biological replications. The experiments were conducted in reference design where respective tissues from unstressed plants served as control. The leaf/shoot, flower/pod and/or root tissues were collected and used for hybridization to measure changes in RNA abundance of treatment vs. control. The tissues from five experimental replicate plants per biological replication were pooled together (leaf/flower/root tissues pooled separately) before RNA extraction. This RNA was used to prepare cDNA targets for expression analysis using microarray. The microarray had six technical replicate spots per EST. The transcript level for each EST/cDNA was firstly calculated as the average intensity of the six technical replicates and then the average intensity of three biological replicates. Data analysis included LOWESS normalization (LOcally WEighted polynomial regreSSion) to adjust for differences in quantity of initial RNA, labeling and detection efficiencies. A dye swap in one biological replicate adjusted dye bias, if any. The Differentially Expressed (DE) ESTs were identified as those with a 95% confidence interval for mean fold change (FC) that extended beyond the two-fold cut-off and also passed the Students t test (P<0.05) and FDR correction. These cut-offs translate into induced ESTs having a log2 ratio > 1 and repressed ESTs a ratio of < -1. Overall, 46, 54 and 266 ESTs were identified as DE under drought, cold, and high-salinity stresses, respectively. The important ones DE in response to drought stress include induction of transcripts associated with dehydrin-cognate, lipid-transfer protein precursor, and glutamate-hydrolysing asparagine synthetase, whilst repression of transcripts associated with senescence, photosynthesis/energy metabolism, auxin-repressed protein, starch metabolism, AP2/EREBP1 DNA binding domain, putative ARF1 GTPase activating protein, and histidine-containing phosphotransfer protein ATHP3. The interesting transcripts DE in response to cold-stress included induction of phosphate-induced protein, cationic peroxidase, UDP-glucose 4-epimerase, Avr9/Cf9 rapidly elicited protein, DNA-J like protein involved in intracellular protein transport, and protein kinase, whist repression of transcripts associated with a hypothetical transmembrane protein, membrane related protein CP5, lipid-transfer protein precursor, WD repeat protein and several transcripts associated with cellular metabolism, cell cycle and DNA processing, protein synthesis and photosynthesis/energy metabolism. Under high-salinity stress, several transcripts were DE only in roots at 24 hpt but DE in shoots or both, shoots and roots at 48 hpt, relating to the theory of upward movement of salt to shoots at later stages when roots fail to restrict it (Munns et al., 2002). The important transcripts DE in response to high-salinity stress included induction of aluminum-induced protein, auxin-repressed proteins, metallothionein-like protein, glutamate dehydrogenase, sucrose synthase, UDP-glucose 4-epimerase, xylose isomerase, class 10 pathogenesis related protein, disease resistance protein, SNAKIN 2 antimicrobial peptide, and DNA-J like protein involved in intra-cellular protein transport. Whilst high-salinity stress caused the repression of transcripts associated with cell rescue/death, cell cycle/DNA processing, cellular metabolism, photosynthesis/energy metabolism, and transport facilitation. Several of the above transcripts have been previously implicated to be associated with abiotic stress response in other crops. Hence, the study of more genotypes and transcriptional changes at several time points may provide a better picture of involvement of the genes being interrogated here in drought tolerance/susceptibility. Subsequently, the functionality of candidate tolerance genes detected through this approach could be validated by overexpressing the genes through transgenics or silencing them using knockout-mutants/antisense/RNAi. Keywords: abiotic stress response, drought, cold, high-salinity, chickpea
2007-07-24 | GSE8554 | GEO