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Author: search.filters.author.Pradhan, SeemaSubject: search.filters.subject.Chickpea

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    A high-density SNP-based linkage map using genotyping-by-sequencing and its utilization for improved genome assembly of chickpea (Cicer arietinum L.)
    (Springer Nature Publishing AG, 2020) Gaur, Rashmi; Verma, Subodh; Pradhan, Seema; Ambreen, Heena; Bhatia, Sabhyata
    Genotyping-by-sequencing (GBS) allows rapid identification of markers for use in development of linkage maps, which expedite efficient breeding programs. In the present study, we have utilized GBS approach to identify and genotype single-nucleotide polymorphism (SNP) markers in an inter-specific RIL population of Cicer arietinum L. X C. reticulatum. A total of 141,639 raw SNPs were identified using the TASSEL-GBS pipeline. After stringent filtering, 8208 candidate SNPs were identified of which ~ 37% were localized in the intragenic regions followed by genic regions (~ 30%) and intergenic regions (~ 27%). We then utilized 6920 stringent selected SNPs from present study and 6714 SNPs and microsatellite markers available from previous studies for construction of linkage map. The resulting high-density linkage map comprising of eight linkage groups contained 13,590 markers which spanned 1299.14 cM of map length with an average marker density of 0.095 cM. Further, the derived linkage map was used to improve the available assembly of desi chickpea genome by anchoring 443 previously unplaced scaffolds onto eight linkage groups. The present efforts have refined anchoring of the desi chickpea genome assembly to 55.57% of the ~ 520 Mb of assembled desi genome. To the best of our knowledge, the linkage map generated in the present study represents one of the most dense linkage map developed for the crop till date. It will serve as a valuable resource for fine mapping and positional cloning of important quantitative trait loci (QTLs) associated with agronomical traits and also for anchoring and ordering of future genome sequence assemblies.
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    Dissecting the root nodule transcriptome of chickpea (Cicer arietinum L.)
    (PLOS, 2016) Kant, Chandra; Pradhan, Seema; Bhatia, Sabhyata
    A hallmark trait of chickpea (Cicer arietinum L.), like other legumes, is the capability to convert atmospheric nitrogen (N2) into ammonia (NH3) in symbiotic association with Mesorhizobium ciceri. However, the complexity of molecular networks associated with the dynamics of nodule development in chickpea need to be analyzed in depth. Hence, in order to gain insights into the chickpea nodule development, the transcriptomes of nodules at early, middle and late stages of development were sequenced using the Roche 454 platform. This generated 490.84 Mb sequence data comprising 1,360,251 reads which were assembled into 83,405 unigenes. Transcripts were annotated using Gene Ontology (GO), Cluster of Orthologous Groups (COG) and Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways analysis. Differential expression analysis revealed that a total of 3760 transcripts were differentially expressed in at least one of three stages, whereas 935, 117 and 2707 transcripts were found to be differentially expressed in the early, middle and late stages of nodule development respectively. MapMan analysis revealed enrichment of metabolic pathways such as transport, protein synthesis, signaling and carbohydrate metabolism during root nodulation. Transcription factors were predicted and analyzed for their differential expression during nodule development. Putative nodule specific transcripts were identified and enriched for GO categories using BiNGO which revealed many categories to be enriched during nodule development, including transcription regulators and transporters. Further, the assembled transcriptome was also used to mine for genic SSR markers. In conclusion, this study will help in enriching the transcriptomic resources implicated in understanding of root nodulation events in chickpea.
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    Global transcriptome analysis of developing chickpea (Cicer arietinum L.) seeds
    (Frontiers Media S.A., 2014) Pradhan, Seema; Bandhiwal, Nitesh; Shah, Niraj; Kant, Chandra; Gaur, Rashmi; Bhatia, Sabhyata
    Understanding developmental processes, especially in non-model crop plants, is extremely important in order to unravel unique mechanisms regulating development. Chickpea (C. arietinum L.) seeds are especially valued for their high carbohydrate and protein content. Therefore, in order to elucidate the mechanisms underlying seed development in chickpea, deep sequencing of transcriptomes from four developmental stages was undertaken. In this study, next generation sequencing platform was utilized to sequence the transcriptome of four distinct stages of seed development in chickpea. About 1.3 million reads were generated which were assembled into 51,099 unigenes by merging the de novo and reference assemblies. Functional annotation of the unigenes was carried out using the Uniprot, COG and KEGG databases. RPKM based digital expression analysis revealed specific gene activities at different stages of development which was validated using Real time PCR analysis. More than 90% of the unigenes were found to be expressed in at least one of the four seed tissues. DEGseq was used to determine differentially expressing genes which revealed that only 6.75% of the unigenes were differentially expressed at various stages. Homology based comparison revealed 17.5% of the unigenes to be putatively seed specific. Transcription factors were predicted based on HMM profiles built using TF sequences from five legume plants and analyzed for their differential expression during progression of seed development. Expression analysis of genes involved in biosynthesis of important secondary metabolites suggested that chickpea seeds can serve as a good source of antioxidants. Since transcriptomes are a valuable source of molecular markers like simple sequence repeats (SSRs), about 12,000 SSRs were mined in chickpea seed transcriptome and few of them were validated. In conclusion, this study will serve as a valuable resource for improved chickpea breeding.