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dc.contributorKhan, Aamiren_US
dc.contributorKumar, Vinayen_US
dc.contributorGaur, Pooranen_US
dc.contributorKatta, Mohan AVSen_US
dc.contributorVanika, Gargen_US
dc.contributorRoorkiwal, Manishen_US
dc.contributorSamineni, Srinivasanen_US
dc.contributorVarshney, Rajeeven_US
dc.creatorThudi, Mahendaren_US
dc.date2016-01-27en_US
dc.date.accessioned2017-04-20T14:48:10Z
dc.date.available2017-04-20T14:48:10Z
dc.identifierhttp://oar.icrisat.org/id/eprint/9311en_US
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/3e6mnm6Uen_US
dc.identifier.citationMahendar Thudi, Aamir Khan, Vinay Kumar, Pooran Gaur, Mohan AVS Katta, Garg Vanika, Manish Roorkiwal, Srinivasan Samineni, Rajeev Varshney. (27/1/2016). Whole genome re-sequencing reveals genome-wide variations among parental lines of 16 mapping populations in chickpea (Cicer arietinum L. ). BMC Plant Biology, 16 (10), pp. 53-64.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/6858
dc.description.abstractBackground: Chickpea (Cicer arietinum L.) is the second most important grain legume cultivated by resource poor farmers in South Asia and SubSaharan Africa. In order to harness the untapped genetic potential available for chickpea improvement, we resequenced 35 chickpea genotypes representing parental lines of 16 mapping populations segregating for abiotic (drought, heat, salinity), biotic stresses (Fusarium wilt, Ascochyta blight, Botrytis grey mould, Helicoverpa armigera) and nutritionally important (protein content) traits using whole genome resequencing approach. Results: A total of 192.19 Gb data, generated on 35 genotypes of chickpea, comprising 973.13 million reads, with an average sequencing depth of ~10 X for each line. On an average 92.18 % reads from each genotype were aligned to the chickpea reference genome with 82.17 % coverage. A total of 2,058,566 unique single nucleotide polymorphisms (SNPs) and 292,588 Indels were detected while comparing with the reference chickpea genome. Highest number of SNPs were identified on the Ca4 pseudomolecule. In addition, copy number variations (CNVs) such as gene deletions and duplications were identified across the chickpea parental genotypes, which were minimum in PI 489777 (1 gene deletion) and maximum in JG 74 (1,497). A total of 164,856 line specific variations (144,888 SNPs and 19,968 Indels) with the highest percentage were identified in coding regions in ICC 1496 (21 %) followed by ICCV 97105 (12 %). Of 539 miscellaneous variations, 339, 138 and 62 were interchromosomal variations (CTX), intrachromosomal variations (ITX) and inversions (INV) respectively. Conclusion: Genomewide SNPs, Indels, CNVs, PAVs, and miscellaneous variations identified in different mapping populations are a valuable resource in genetic research and helpful in locating genes/genomic segments responsible for economically important traits. Further, the genomewide variations identified in the present study can be used for developing high density SNP arrays for genetics and breeding applications.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherBioMed Centralen_US
dc.rightsCC-BY-NC-4.0en_US
dc.sourceBMC Plant Biology;16,(2016) Pagination 53,64en_US
dc.subjectresequencingen_US
dc.subjectcopy number variationsen_US
dc.subjectmapping populationen_US
dc.subjectChickpeaen_US
dc.titleWhole genome re-sequencing reveals genome-wide variations among parental lines of 16 mapping populations in chickpea (Cicer arietinum L.)en_US
dc.typeJournal Articleen_US
cg.creator.idThudi, Mahendar: 0000-0003-2851-6837en_US
cg.creator.idRoorkiwal, Manish: 0000-0001-6595-281Xen_US
cg.creator.idSamineni, Srinivasan: 0000-0001-9350-8847en_US
cg.creator.ID-typeORCIDen_US
cg.creator.ID-typeORCIDen_US
cg.creator.ID-typeORCIDen_US
cg.subject.agrovocagricultureen_US
cg.subject.agrovocgenomicsen_US
cg.subject.agrovocchickpeasen_US
cg.contributor.centerInternational Crops Research Institute for the Semi-Arid Tropics - ICRISATen_US
cg.contributor.crpCGIAR Research Program on Grain Legumes - GLen_US
cg.contributor.funderNot Applicableen_US
cg.coverage.regionSouthern Asiaen_US
cg.coverage.countryINen_US
cg.contactT.MAHENDAR@CGIAR.ORGen_US
cg.identifier.doihttps://dx.doi.org/10.1186/s12870-015-0690-3en_US
dc.identifier.statusOpen accessen_US
mel.impact-factor3.631en_US


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