Cicer reticulatum
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA401928 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR6011517.fastq.gz | Fastqsanger.gz |
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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: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:Small RNA Solexa sequencing of chickpea (Cicer arietinum)
| PRJNA263491 | ENA
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:Microarrays have increasingly become a powerful tool for high throughput gene-expression studies and discovery of novel biomarker genes. Developed for a large number of organisms, including plants, microarrays are commonly performed for species that have sequenced data, for performing gene expression analysis, miRNA profiling, comparative genomic hybridization (CGH), ChIP-on-chip and SNP analysis. Genomic resources are still very limited for chickpea, a very important food legume crop. Here, we report the design and comprehensive validation of Next Generation Sequencing transcriptome data for chickpea through microarray technology to develop a high-throughput resource for studying the expression of all the transcripts in different biological samples to help functional genomics and breeding programs. This microarray design was developed and validated jointly by Genotypic Technology Private Limited and National Institute of Plant Genome Research. First, we designed 400k probes using reads covering 35k assembled contigs and 100k singletons chickpea transcripts. The 400k chip was hybridized with DNA and RNA samples of chickpea and microarray analysis was carried out. A total of 73,922 probes were found to be specific to chickpea transcripts. Best probes were filtered from the analyzed data and a total of 61,659 probes were selected to develop the final microarray design in 60k gene-expression microarray format. The probes represented 51,444 unique transcripts. The probes were annotated based on their corresponding chickpea transcript and similarity with other plants species. Microarray results were concordant with previous results from the NGS studies. The design of custom oligonucleotide probes for microarrays have varied functional genomic applications and this approach represents a valuable resource for chickpea.
2017-01-07 | GSE78985 | GEO
Project description:The chloroplast (cp) genome is an adequate genomic resource to investigate evolutionary relationships among plant species and it carries marker genes available for species identification. The Cicer reticulatum is one of perennial species as the progenitor of cultivated chickpeas. Although a large part of the land plants has a quadruple chloroplast genome organization, the cp genome of C. reticulatum consists of one LSC (Large Single Copy Region), one SSC (Small Single Copy Region), and one IR (Inverted Repeat) region, which indicates that it has an untypical and unique structure. This type of chloroplast genome belongs to the IR-lacking clade. Chloroplast DNA (cpDNA) was extracted from fresh leaves using a high salt-based protocol and sequencing was performed using DNA Nanoball Sequencing technology. The comparative analysis employed between the species to examine genomic differences and gene homology. The study also included codon usage frequency analysis, hotspot divergence analysis, and phylogenetic analysis using various bioinformatics tools. The cp genome of C. reticulatum was found 125,794 bp in length, with an overall GC content of 33.9%. With a total of 79 protein-coding genes, 34 tRNA genes, and 4 rRNA genes. Comparative genomic analysis revealed 99.93% similarity between C. reticulatum and C. arietinum. Phylogenetic analysis further indicated that the closest evolutionary relative to C. arietinum was C. reticulatum, whereas the previously sequenced wild Cicer species displayed slight distinctions across their entire coding regions. Several genomic regions, such as clpP and ycf1, were found to exhibit high nucleotide diversity, suggesting their potential utility as markers for investigating the evolutionary relationships within the Cicer genus. The first complete cp genome sequence of C. reticulatum will provide novel insights for future genetic research on Cicer crops.
| S-EPMC10587350 | biostudies-literature
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:Microarrays have increasingly become a powerful tool for high throughput gene-expression studies and discovery of novel biomarker genes. Developed for a large number of organisms, including plants, microarrays are commonly performed for species that have sequenced data, for performing gene expression analysis, miRNA profiling, comparative genomic hybridization (CGH), ChIP-on-chip and SNP analysis. Genomic resources are still very limited for chickpea, a very important food legume crop. Here, we report the design and comprehensive validation of Next Generation Sequencing transcriptome data for chickpea through microarray technology to develop a high-throughput resource for studying the expression of all the transcripts in different biological samples to help functional genomics and breeding programs. This microarray design was developed and validated jointly by Genotypic Technology Private Limited and National Institute of Plant Genome Research. First, we designed 400k probes using reads covering 35k assembled contigs and 100k singletons chickpea transcripts. The 400k chip was hybridized with DNA and RNA samples of chickpea and microarray analysis was carried out. A total of 73,922 probes were found to be specific to chickpea transcripts. Best probes were filtered from the analyzed data and a total of 61,659 probes were selected to develop the final microarray design in 60k gene-expression microarray format. The probes represented 51,444 unique transcripts. The probes were annotated based on their corresponding chickpea transcript and similarity with other plants species. Microarray results were concordant with previous results from the NGS studies. The design of custom oligonucleotide probes for microarrays have varied functional genomic applications and this approach represents a valuable resource for chickpea.
2017-01-05 | GSE76972 | GEO