Porteresia transcriptome sequencing
Ontology highlight
ABSTRACT:
ORGANISM(S): Oryza coarctata
PROVIDER: GSE44913 | GEO | 2013/11/05
SECONDARY ACCESSION(S): PRJNA192453
REPOSITORIES: GEO
Similar Datasets
Project description:In this study, we aim to present the complete transcriptome of Asian wild rice, Porteresia. We generated about 375 million high-quality reads for five different conditions (ranging from 65 to 90 million reads for each condition) using Illumina high-throughput sequencing GAII platform. We mapped the reads to Porteresia transcripts for estimation of their transcriptional activity in different tissue samples. The transcriptome dynamics was studied by comparison of gene expression during conditions. We collected different tissue samples after various treatments (control, in water; salt450, in 450 mM sodium chloride solution; salt700, in 700 mM sodium chloride solution; submergence, submerged in water; salt+submergence, submerged in 450 mM sodium chloride solution) 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 Porteresia transcripts and reads per kilobase per million (RPKM) was calculated for each transcript in all the samples to measure their gene expression. Differential expression analysis was performed using DESeq software. The genes showing differential expression under various stress conditions were identified.
2013-11-05 | E-GEOD-44913 | 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 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 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: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
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 in different tissues/organs/developmental stage in chickpea. We generated about ~31-95 million reads from each of 94 libraries representing 32 different tissues/organs using Illumina platform. We generated a hybrid assembly of these data along with PacBio data to produce full-length transcriptome assembly. We mapped the reads to the transcriptome assembly for estimation of the abundance of coding and long non-coding transcripts in different tissue samples. The transcriptome dynamics was studied by differential and tissue-specific expression analyses, and co-expression network and transcriptional regulatory network analyses.
2022-10-26 | GSE147831 | 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.
2014-09-08 | GSE51300 | GEO
Project description:Extracellular microRNAs (miRNAs) embedded in circulating exosomes may serves as prognostic biomarkers in cancer. This study was performed to identify and evaluate plasma exosomal miRNAs for prognostication in castration resistant prostate cancer (CRPC). RNA sequencing was performed to identify candidate exosomal miRNAs associated with overall survival in a screening cohort of 23 CRPC patients. Candidate miRNAs were further evaluated for prognosis using qRT-PCR in a follow-up cohort of 100 patients. Cox regression and Kaplan–Meier survival curve analysis were used to evaluate prognostic value of miRNA candidates with and without incorporation of clinical prognostic factors (age, Gleason score and time from androgen deprivation therapy to clinical progression). In the screening cohort, we obtained ~6.80 million mappable RNA reads per patient. Of those with normalized read counts ? 5, 43% were mapped to miRNAs for a total of 375 known and 57 novel miRNAs. Cox regression analysis identified an association of miR-1290, -1246, and -375 with overall survival (FDR<0.1). Of those, higher levels of miR-1290 and -375 were verified to be significantly associated with poor overall survival (p<0.004) in the follow-up cohort. The miR-1290/-375-based prediction model showed better performance with time-dependent area under the curve (AUC) =72% compared to clinical variable-based model with AUC=65%. Plasma exosomal miR-1290 and miR-375 are promising prognostic biomarkers for CRPC patients. Prospective validation is needed for further development of these candidate miRNAs.
2014-12-30 | GSE58410 | GEO