Project description:Drought is one of the major constraints for crop productivity across the globe. Chickpea (Cicer arietinum L.) is mainly cultivated in the arid and semi-arid tropical regions under rain-fed conditions and drought stress is one of the major constraints, which causes up to 50% yield losses annually. In this study, transcriptomics, proteomics and metabolomics datasets from root tissues of contrasting drought responsive chickpea genotypes, ICC 4958 (drought-tolerant), JG 11 (drought-tolerant); an introgression line, JG 11+ (drought-tolerant) and ICC 1882, (drought-sensitive) under control and stress conditions were generated. The integrated analysis of these multi-omics data revealed complex molecular mechanism underlying drought stress response in chickpea. Transcriptomics integrated with proteomics data identified enhancement of hub proteins encoding isoflavone 4’-O-methyltransferase (Ca_06356), UDP-D-glucose/UDP-D-Galactose 4-epimerase (Ca_15037) and delta-1-pyrroline-5-carboxylate synthesis (Ca_24241). These proteins highlighted the involvement of critical pathways such as antibiotic biosynthesis, galactose metabolism and isoflavonoid biosynthesis in activating drought stress response mechanism. Subsequently, integration of metabolomics data identified six key metabolites (fructose, galactose, glucose, myo-inositol, galactinol and raffinose) that showed enhanced correlation with galactose metabolism. Further, integration of root -omics data together with genomic dataset of the “QTL-hotspot” region harbouring several drought tolerance related traits revealed involvement of candidate genes encoding aldo keto reductase family oxidoreductase (Ca_04551) and leucine rich repeat extensin 2 (Ca_04564). These results from integrated multi-omics approach provided a comprehensive understanding and new insights into the drought stress response mechanism of chickpea.
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.
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.
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.
Project description:The primary objective of this study is to investigate the molecular differences between chickpea varieties with early and late flowering, focusing on gene expression in response to heat stress. Through the analysis of differentially expressed genes under high-temperature conditions, we aim to gain a deeper understanding of the molecular mechanisms underlying early flowering in chickpea. This approach will not only help bridge the current gaps in our scientific knowledge but may also provide valuable insights for the development of targeted genetic improvement strategies to enhance the thermal resilience of chickpea crops.
Project description:Purpose: Molecular analysis of chickpea-Foc interaction; Methods: Four LongSAGE libraries of wilt-resistant and wilt-susceptible chickpea cultivars prepared after Foc inoculation and sequenced using Ion Torrent PGM. Results: Transcriptome analyses revealed expression of several plant defense and pathogen virulence genes with their peculier expression patterns in wilt-resistant and wilt-susceptible chickpea cultivars. Conclusion: The study identified several candidate Foc resistant genes, which can be used for crop improvement after their functional validation.
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.