Small RNAs in stress-related rice cultivars
Ontology highlight
ABSTRACT:
ORGANISM(S): Oryza sativa
SUBMITTER: Mukesh Jain
PROVIDER: E-GEOD-64651 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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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 in different rice cultivars (IR64, Nagina 22 and Pokkali) under control and stress conditions. More than 50 million high quality reads were obtained for each tissue sample using Illumina platform. Reference-based assembly was performed for each rice cultivar. The transcriptome dynamics was studied by differential gene expression analyses between stress treatment and control sample. We collected seedlings of three rice cultivars subjected to control (kept in water), desiccation (transferred on folds of tissue paper) and salinity (transferred to beaker containing 200 mM NaCl solution) treatments. Total RNA isolated from these tissue samples was subjected to Illumina sequencing. The sequence data was further filtered using NGS QC Toolkit to obtain high-quality reads. The filtered reads were mapped to Japonica reference genome using Tophat software. Cufflinks was used for reference-based assembly and differential gene expression was studied using cuffdiff software. The differentially expressed genes during various abiotic stress conditions were identified.
2015-12-31 | E-GEOD-60287 | biostudies-arrayexpress
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 transcriptome analysis of medicinal plant, Catharanthus roseus. We generated about 343 million high-quality reads from three tissues (leaf, root and flower) using Illumina platform. We performed an optimized de novo assembly of the reads and estimated transcript abundance in different tissue samples. The transcriptome dynamics was studied by differential gene expression analyses among tissue samples. We collected different tissue samples from the mature plants. Total RNA isolated from these tissue samples was subjected to Illumina sequencing. The sequence data was further filtered using NGS QC Toolkit to obtain high-quality reads. The filtered reads were used for de novo assembly optimization. The reads were further mapped to the Catharanthus transcripts via CLC Genomics Workbench and differential gene expression analysis was performed using DESeq software.
2014-07-29 | E-GEOD-57326 | biostudies-arrayexpress
Project description:Purpose: To study the differential gene expression by comparing resistant and susceptible rice cultivars against the rice blast fungus M. Oryzae. Methods: Rice leaves were collected after M. Oryzae (MO36) infection from resistant and susceptible cultivars, preserved on deep freezer on -80O C frozen on liquid nitrogen, Total RNA from rice plant tissues was extracted using RNeasy Plant Mini Kit (Qiagen) by following manufacturer protocol. RNA libraries were prepared for sequencing using standard Illumina protocols. Results: Around 35 million pairs of filtered 150 base paired reads were obtained for each biological sample. These reads were mapped against RGAP7 using reference assembly tool of CLC Genomics Workbench. The mapped read data was summarised in to a matrix for each sample. count data was compared between the samples to identify the differentially expressed genes. genes were further filtered based on fold change, p value and FDR p value. The count data was further statistically analysed using Kal's Z test integrated into CGWB. Genes exhibiting 3 fold change and FDR p value <0.05 were filtered as either up regulated or down regulated gene. we obtained 7577 and 4290 significant (FDR adjusted p value ≤0.05) differentially expressed locus id in the resistant and susceptible rice cultivars, respectively . The number of significant DEL with fold change value greater and less than 3 were 3523 upregulated 4054 downregulated and 2190 upregulated & 2100 downregulated in resistance and susceptible cultivars, respectively. 2-way and and 4-way upregulated and downregulated gene comparisions was carried out. To identify the changes in biological process and molecular function the pathway and gene set enrichment analysis was performed in resistant BR2655 and susceptible HR12 rice cultivars. Conclusions: This study represents the first transcriptome analysis of resistant BR2655 and susceptible HR12 upon M.oryzae infection, generated by RNA-seq technology. This transcriptome analysis further helps to understand the differential gene expression analysis response to the M.oryzae. And candidate genes which are involved in triggering defense mechanism in rice plants. Further it helps to understand the mechanism of activating a cascade of defense responses in resistant and susceptible plants.
2024-06-01 | GSE192588 | GEO
Project description:In this study, we sequenced small RNA content from three different rice cultivars employing Illumina technology. More than 15 million reads were generated using Illumina high-throughput sequencing platform. After pre-processing, distinct small RNA sequences were identified for each rice cultivars.
2015-12-31 | GSE64651 | 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.
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Project description:In this study, we aim to present a global view of transcriptome dynamics in different rice cultivars (IR64, Nagina 22 and Pokkali) under control and stress conditions. More than 50 million high quality reads were obtained for each tissue sample using Illumina platform. Reference-based assembly was performed for each rice cultivar. The transcriptome dynamics was studied by differential gene expression analyses between stress treatment and control sample.
2015-12-31 | GSE60287 | GEO
Project description:In this study, we aim to generate genome-scale DNA methylation profiles at single-base resolution in different rice cultivars (IR64, Nagina 22 and Pokkali) under control and stress conditions. Using high-throughput whole genome bisulfite Sequencing, we generated DNA methylation maps covering the vast majority of cytosines in the rice genome. More than 152 million high quality reads were obtained for each tissue sample using Illumina platform. We discovered extensive DNA methylation in rice cultivars, identified the context and level of methylation at each site.Numerous differentially methylated regions (DMRs) among different cultivars under control and stress conditions were identified and many of them were associated with differential gene expression. The high resolution methylome maps of different rice genotypes and differentially methylated regions will serve as reference for understanding the epigenetic regulation of stress responses in plants.
2015-12-31 | GSE60288 | GEO
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2020-01-23 | PXD014844 | Pride