Chickpea Small RNA Atlas - Development
Ontology highlight
ABSTRACT:
ORGANISM(S): Cicer arietinum
PROVIDER: GSE51300 | GEO | 2014/09/08
SECONDARY ACCESSION(S): PRJNA222362
REPOSITORIES: GEO
Similar Datasets
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: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: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.
2014-01-09 | GSE42679 | 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: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: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:In this study, global transcriptome profiling was performed for different organs of ICC 4958 (leaves, roots, flowers and young pod) and leaves of wild chickpea, PI 489777. More than 50 million high-quality reads were obtained from each sample using Illumina platform. A consensus reference-guided assembly was generated for the transcriptome data from all samples and gene expression was analysed.
2018-07-15 | GSE103561 | GEO
Project description:In this study, we have identified small RNA during salinity stress response in chickpea. Small RNA library was prepared and sequencing was performed using Illumina platform. A total of 79 million reads were generated. These reads were mapped to the chickpea genome using Bowtie.
2023-02-15 | GSE204728 | GEO
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