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 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.
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: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.
Project description:Background Drought is the major constraint to increase yield in chickpea (Cicer arietinum). Improving drought tolerance is therefore of outmost importance for breeding. However, the complexity of the trait allowed only marginal progress. A solution to the current stagnation is expected from innovative molecular tools such as transcriptome analyses providing insight into stress-related gene activity and, combined with molecular markers and expression (e)QTL mapping, may accelerate knowledge-based breeding. SuperSAGE, an improved version of the serial analysis of gene expression (SAGE) technique, currently is the most advanced tool for transcriptome analysis. SuperSAGE generates genome-wide, high-quality transcription profiles from any eukaryote. The method produces 26bp long fragments (SuperTags26bp tags) from defined positions in cDNAs, providing sufficient sequence information to unambiguously characterize the mRNAs. Further, SuperSAGE Tags may be immediately used to produce so called SuperTag microarrays and probes for real-time-PCR thereby overcoming the lack of genomic tools in non-model organisms. Results We applied SuperSAGE to the analysis of gene expression in chickpea roots in response to drought. To this end, we sequenced 80,238 26bp SuperTtags representing 17,493 unique transcripts (UniTags) from drought-stressed and non-stressed control roots. A total of 7,532 (43%) UniTags were more than 2.7-fold differentially expressed , and 880 (5.0%) were regulated more than 8-fold upon stress. Their large size enabled the unambiguous annotation of 2,798 (16.3%) UniTags to genes or proteins in public data bases and thus to stress-response processes. We designed a microSuperTag array carrying 3,000 of these SuperTags26bp tags. The chip data confirmed the SuperSAGE results in 79 % of cases whereas RT-PCR confirmed the SuperSAGE data in all cases. Conclusions This study represents the most comprehensive analysis of the drought-response transcriptome of chickpea available to date. It demonstrates that - inter alias - signal transduction, transcription regulation, osmolyte accumulation, chromosome organization, and ROS scavenging undergo strong transcriptional remodelling in chickpea roots already 6h after drought stress. Certain transcript isoforms characterizing these processes are potential targets for breeding for drought tolerance. We demonstrate that these can be easily accessed by micro-arrays and RT-PCR assays readily produced downstream of SuperSAGE. Our study proves that SuperSAGE has a good potential is best suited for molecular breeding also in non-model crops.