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dc.contributorClevenger, Joshen_US
dc.contributorPandey, Manish Ken_US
dc.contributorWang, Huien_US
dc.contributorShasidhar, Yaduruen_US
dc.contributorChu, Yeen_US
dc.contributorC. Fountain, Jakeen_US
dc.contributorChoudhary, Divyaen_US
dc.contributorCulbreath, Albert K.en_US
dc.contributorLiu, Xinen_US
dc.contributorHuang, Guodongen_US
dc.contributorWang, Xingjunen_US
dc.contributorDeshmukh, Rupeshen_US
dc.contributorHolbrook, C. Corleyen_US
dc.contributorBertioli, David Johnen_US
dc.contributorOzias-Akins, Peggyen_US
dc.contributorJackson, Scotten_US
dc.contributorVarshney, Rajeeven_US
dc.contributorGuo, Baozhuen_US
dc.creatorAgarwal, Gauraven_US
dc.date2018-04-10en_US
dc.date.accessioned2019-05-01T09:45:31Z
dc.date.available2019-05-01T09:45:31Z
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/d12c1a1ff0f00860a53308d5f8efd6e8en_US
dc.identifier.citationGaurav Agarwal, Josh Clevenger, Manish K Pandey, Hui Wang, Yaduru Shasidhar, Ye Chu, Jake C. Fountain, Divya Choudhary, Albert K. Culbreath, Xin Liu, Guodong Huang, Xingjun Wang, Rupesh Deshmukh, C. Corley Holbrook, David John Bertioli, Peggy Ozias-Akins, Scott Jackson, Rajeev Varshney, Baozhu Guo. (10/4/2018). High‐density genetic map using whole‐genome resequencing for fine mapping and candidate gene discovery for disease resistance in peanut. Plant Biotechnology Journal, 16 (11).en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/9899
dc.description.abstractWhole‐genome resequencing (WGRS) of mapping populations has facilitated development of high‐density genetic maps essential for fine mapping and candidate gene discovery for traits of interest in crop species. Leaf spots, including early leaf spot (ELS) and late leaf spot (LLS), and Tomato spotted wilt virus (TSWV) are devastating diseases in peanut causing significant yield loss. We generated WGRS data on a recombinant inbred line population, developed a SNP‐based high‐density genetic map, and conducted fine mapping, candidate gene discovery and marker validation for ELS, LLS and TSWV. The first sequence‐based high‐density map was constructed with 8869 SNPs assigned to 20 linkage groups, representing 20 chromosomes, for the ‘T’ population (Tifrunner × GT‐C20) with a map length of 3120 cM and an average distance of 1.45 cM. The quantitative trait locus (QTL) analysis using high‐density genetic map and multiple season phenotyping data identified 35 main‐effect QTLs with phenotypic variation explained (PVE) from 6.32% to 47.63%. Among major‐effect QTLs mapped, there were two QTLs for ELS on B05 with 47.42% PVE and B03 with 47.38% PVE, two QTLs for LLS on A05 with 47.63% and B03 with 34.03% PVE and one QTL for TSWV on B09 with 40.71% PVE. The epistasis and environment interaction analyses identified significant environmental effects on these traits. The identified QTL regions had disease resistance genes including R‐genes and transcription factors. KASP markers were developed for major QTLs and validated in the population and are ready for further deployment in genomics‐assisted breeding in peanut.en_US
dc.languageenen_US
dc.publisherWiley Open Accessen_US
dc.rightsCC-BY-NC-4.0en_US
dc.sourcePlant Biotechnology Journal;16,(2018)en_US
dc.subjectgeneticen_US
dc.titleHigh‐density genetic map using whole‐genome resequencing for fine mapping and candidate gene discovery for disease resistance in peanuten_US
dc.typeJournal Articleen_US
cg.creator.idPandey, Manish K: 0000-0002-4101-6530en_US
cg.creator.ID-typeORCIDen_US
cg.contributor.centerInternational Crops Research Institute for the Semi-Arid Tropics - ICRISATen_US
cg.contributor.centerUniversity of Georgia - UGAen_US
cg.contributor.centerBeijing Genomics Institute- Shenzhen - BGI-Shenzhenen_US
cg.contributor.centerShandong Academy of Agricultural Sciencesen_US
cg.contributor.centerUniversity of Missouri - MU USAen_US
cg.contributor.centerUnited States Department of Agriculture, Agricultural Research Service - USDA-ARSen_US
cg.contributor.centerUniversity of Brasíliaen_US
cg.contributor.crpCGIAR Research Program on Grain Legumes and Dryland Cereals - GLDCen_US
cg.contributor.funderCGIAR System Organization - CGIARen_US
cg.coverage.regionGlobalen_US
cg.contactBaozhu.Guo@ars.usda.goven_US
cg.identifier.doihttps://dx.doi.org/10.1111/pbi.12930en_US
dc.identifier.statusOpen accessen_US
mel.impact-factor6.305en_US


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