Gene expression profiling in different organs of chickpea
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ABSTRACT:
ORGANISM(S): Cicer reticulatum Cicer arietinum
PROVIDER: GSE103561 | GEO | 2018/07/15
REPOSITORIES: GEO
Similar Datasets
Project description:In this study, we have elucidated the DNA methylation patterns in different organs of a cultivated chickpea genotype ICC 4958 (leaf, root, flower and young pod) and leaf of wild chickpea PI 489777 using bisulphite sequencing. Approximately 108 million read pairs were analyzed per sample. The extent of methylation along-with the context and genomic location of methylated Cs was identified. Further processing was performed to identify the differentially methylated regions among samples with leaves of ICC 4958 as the reference sample. The high resolution methylome maps of different organs and differentially methylated regions will serve as reference for understanding the epigenetic regulation in chickpea.
2018-07-15 | GSE103575 | GEO
Project description:The total RNA were extracted from pooled tissues of leaves and flowers from several plants of chickpea (Cicer arietinum) using TRIzol reagent (Invitrogen) according to the manufacturer's instructions. Then small RNAs ranging in 18–30 nucleotides were size fractionated electrophoretically, isolated from the gel, ligated with the 5′ and 3′ RNA adapters. The ligated product was reverse transcribed and subsequently amplified using 10–12 PCR cycles. The purified PCR product was sequenced using Illumina Genome Analyzer II. The qualified reads were used to predict microRNAs and phased small interfering RNAs from chickpea. Identification of microRNAs and phased small inferfering RNAs in chickpea (Cicer arietinum) by analyzing small RNA sequencing profiles of leaves and flowers using Illumina GAII.
2015-05-08 | E-GEOD-62216 | biostudies-arrayexpress
Project description:We report small RNA data from the leaves of wild chickpea PI 489777. Small RNA library was prepared and sequencing was performed using Illumina platform. A total of 23 million reads were generated, which represented 0.95 million unique reads. These were mapped to the chickpea genome using Bowtie to obtain the non-redundant set of unique small RNA sequences.
2018-07-15 | GSE103571 | GEO
Project description:The total RNA were extracted from pooled tissues of leaves and flowers from several plants of chickpea (Cicer arietinum) using TRIzol reagent (Invitrogen) according to the manufacturer's instructions. Then small RNAs ranging in 18–30 nucleotides were size fractionated electrophoretically, isolated from the gel, ligated with the 5′ and 3′ RNA adapters. The ligated product was reverse transcribed and subsequently amplified using 10–12 PCR cycles. The purified PCR product was sequenced using Illumina Genome Analyzer II. The qualified reads were used to predict microRNAs and phased small interfering RNAs from chickpea.
2015-05-08 | GSE62216 | GEO
Project description:This study was aimed to deal with a comparative proteome analysis of the two chickpea genotypes with contrasting response to drought stress, ICC 4958 (drought-tolerant, DT) and ICC 1882 (drought-sensitive, DS). Proteins were extracted from the root tissues collected from the control and drought stressed plants of both the genotypes. NanoLC-MS/MS analysis of the protein sample was performed using EASY-nLC 1000 system for the separation and identification of peptides/proteins. This study provided a mechanistic insight of drought stress tolerance in chickpea.
2023-07-20 | PXD041434 | Pride
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 drought stress. Two groups of a tolerant and susceptible accession were challenged with drought 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 and flower/bud 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 and flower tissues separate) 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 114 transcripts was affected in response to drought stress in all the genotypes and tissue types studied. The DE transcripts in response to drought stress coded for various functional and regulatory proteins, most of which were repressed. Protein and other solute transport was repressed in susceptible-1 flowers but induced in tolerant-2 flowers, as evidenced by the induction of a protein-transport facilitation protein (DY475074) in flowers of tolerant-2 and repression of a aquaporin-like membrane channel protein (DY396334) and DNA-J like protein involved in intracellular protein transport (DY475488) in flowers of susceptible-1. Two putative auxin-repressed proteins (DY396289, DY396359) were highly repressed in flowers and leaves of tolerant-2, whilst being induced in flowers and leaves of susceptible-1. Defence-related genes including pathogenesis-related proteins (DY396305 and DY396343), nematode-resistance protein (CV793603), Cf-9 gene cluster (DY396352) and disease resistance response proteins (DY396265 and DY396276) were repressed in flowers of tolerant and susceptible genotypes. A Pea (pi230) disease resistance response protein (DY396390) and a multi-resistance protein ABC transporter (CV793605) were induced in flowers of both tolerant genotypes. Some genes involved in energy metabolism (DY396279 and DY475316) were repressed in leaves and flowers of tolerant and susceptible genotypes. Additionally, some transcripts related to senescence, including auxin responsive protein IAA9 (DY396315), senescence-associated protein DIN 1 (DY396338), and dehydration stress-induced protein (DY396321) were repressed in leaves and flowers of the tolerant genotypes. Of the 114 DE transcripts expressed in drought tolerant and susceptible genotypes, only two were consistently expressed. These included a cytosolic fructose 1,6-bisphosphatase (DY475548) and a gene with unknown function, which were repressed in flowers of both susceptible genotypes. Keywords: Chickpea, Drought stress, Tolerant, Susceptible, cDNA microarray
2007-04-03 | GSE7416 | GEO
Project description:In this study, we aim to present a global view of transcriptome dynamics during flower development in chickpea. We generated around 234 million high-quality reads for eight flower development stages (ranging from 16 to 40 million reads for each stage) and 91 million high-quality reads from three vegetative tissues using Illumina high-throughput sequencing GAII platform. Because of non-availability of reference genome sequence, we mapped the reads to chickpea transcriptome comprised of 34,760 transcripts for estimation of their transcriptional activity in different tissue samples. The transcriptome dynamics was studied by comparison of gene expression during flower development stages with vegetative tissues. We collected different tissue samples used in this study and total RNA isolated 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 34760 chickpea transcripts and reads per kilobase per million (RPKM) was calculated for each gene in all the sample to measure their gene expression. Differential expression analysis was performed using DESeq software. The genes preferentially expression during various stages of flower development as compared to vegetative stages and those with speciifc expression were identified.
2014-01-09 | E-GEOD-42679 | biostudies-arrayexpress
Project description:Drought is one of the major constraints for crop productivity across the globe. Chickpea (Cicer arietinum L.) is mainly cultivated in the arid and semi-arid tropical regions under rain-fed conditions and drought stress is one of the major constraints, which causes up to 50% yield losses annually. In this study, transcriptomics, proteomics and metabolomics datasets from root tissues of contrasting drought responsive chickpea genotypes, ICC 4958 (drought-tolerant), JG 11 (drought-tolerant); an introgression line, JG 11+ (drought-tolerant) and ICC 1882, (drought-sensitive) under control and stress conditions were generated. The integrated analysis of these multi-omics data revealed complex molecular mechanism underlying drought stress response in chickpea. Transcriptomics integrated with proteomics data identified enhancement of hub proteins encoding isoflavone 4’-O-methyltransferase (Ca_06356), UDP-D-glucose/UDP-D-Galactose 4-epimerase (Ca_15037) and delta-1-pyrroline-5-carboxylate synthesis (Ca_24241). These proteins highlighted the involvement of critical pathways such as antibiotic biosynthesis, galactose metabolism and isoflavonoid biosynthesis in activating drought stress response mechanism. Subsequently, integration of metabolomics data identified six key metabolites (fructose, galactose, glucose, myo-inositol, galactinol and raffinose) that showed enhanced correlation with galactose metabolism. Further, integration of root -omics data together with genomic dataset of the “QTL-hotspot” region harbouring several drought tolerance related traits revealed involvement of candidate genes encoding aldo keto reductase family oxidoreductase (Ca_04551) and leucine rich repeat extensin 2 (Ca_04564). These results from integrated multi-omics approach provided a comprehensive understanding and new insights into the drought stress response mechanism of chickpea.
2023-08-23 | PXD027033 | Pride
Project description:In this study, we aim to present a global view of transcriptome dynamics during drought stress in different chickpea genotypes. We generated about 800 million high-quality reads from 14 libraries (control and stress samples for two chickpea genotypes for drought 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.
2016-07-08 | GSE70274 | GEO
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.
2016-07-08 | GSE70377 | GEO