CLAVATA signaling pathway genes modulates agronomic traits in chickpea
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ABSTRACT:
PROVIDER: PRJEB47198 | ENA |
REPOSITORIES: ENA
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2022-02-22 | GSE197103 | 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: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.
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2016-07-08 | GSE70377 | GEO
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 sequenced small RNA content from seven major tissues/organs employing Illumina technology. More than 154 million reads were generated using Illumina high-throughput sequencing GAII platform, which represented more than 20 million distinct small RNA sequences. After pre-processing, several conserved and novel miRNAs were identified in chickpea. Further, the putative targets of chickpea miRNAs were identified and their functional categorization was analyzed. In addition, we identified miRNAs exhibitng differential and specific expression in various tissues/organs. 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 pre-processed using modified perl script provided in the miRTools software. After quality control, the identical reads were collapsed into a unique read and read count for each sequence was recorded. All the filtered unique reads from each sample were screened stepwise against annotated non-coding RNA sequences, including plant snoRNA, tRNA and rRNA. The remaining reads were screened against repeat sequences from RepBase and chickpea chloroplast sequence. Conserved miRNAs were identified based on similarity with miRBase database and novel miRNAs were identified using miRDeep-P pipeline. For differential expression analysis, the read count for each miRNA was normalized using DESeq software. The genes preferentially and specifically expressed in various tissues/organs were identified.
2014-09-08 | E-GEOD-51300 | biostudies-arrayexpress
Project description:Affymetrix SNP array data for analysis of peanut agronomic traits
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Project description:In order to identify genes and pathways involved in drought tolerance, RNA was isolated from control and 15-days drought-stressed chickpea plants. Two chickpea genotypes, Desi PI598080 (“D”) and Kabuli Flip07 318C (“K”), respectively sensitive and tolerant to drought stresses were used. The 12 extracted RNAs (2 genotypes x 2 water regimes x 3 biological replicates) were sequenced, and the transcriptomic changes between the genotypes and water conditions were analysed. The genotype with higher drought sensitivity showed a generally higher change of gene transcripts than the genotype with less sensitivity, upregulating genes involved in photophosphorylation process (transferases, oxygen lyases and oxidoreductases), hormones (brassinosteroids, abscissic acid and gibberellin response), solute transporters, nutrient uptake and cell wall properties (cellulose synthases, hemicellulose synthases, poligalacturonases, pectate lyases). These results will be helpful for further studies aiming at identifying genes and molecular markers to develop chickpea cultivars resilient to water stress.
2023-09-03 | E-MTAB-13037 | biostudies-arrayexpress
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.
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