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dc.contributorXu, Xunen_US
dc.contributorWang, Jieen_US
dc.contributorSingh, Vikasen_US
dc.contributorMarshal, Daviden_US
dc.contributorEdwards, Daviden_US
dc.contributorHickey, Johnen_US
dc.contributorRibaut, Jean-Marcelen_US
dc.creatorVarshney, Rajeeven_US
dc.date.accessioned2017-08-14T11:47:18Z
dc.date.available2017-08-14T11:47:18Z
dc.identifierhttp://oar.icrisat.org/id/eprint/9161en_US
dc.identifierhttps://mel.cgiar.org/reporting/download/hash/9W6evlHmen_US
dc.identifier.citationRajeev Varshney, Xun Xu, Jie Wang, Vikas Singh, David Marshal, David Edwards, John Hickey, Jean-Marcel Ribaut. (5/12/2015). Analytical and Decision Support Tools for Genomics-Assisted Breeding. Trends in Plant Science, 1, pp. 1-10.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/7366
dc.description.abstractTo successfully implement genomics-assisted breeding (GAB) in crop improvement programs, efficient and effective analytical and decision support tools (ADSTs) are ‘must haves’ to evaluate and select plants for developing next-generation crops. Here we review the applications and deployment of appropriate ADSTs for GAB, in the context of next-generation sequencing (NGS), an emerging source of massive genomic information. We discuss suitable software tools and pipelines for marker-based approaches (markers/haplotypes), including large-scale genotypic and phenotypic, data management, and molecular breeding approaches. Although phenotyping remains expensive and time consuming, prediction of allelic effects on phenotypes opens new doors to enhance genetic gain across crop cycles, building on reliable phenotyping approaches and good crop information systems, including pedigree information and target haplotypes.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherElsevieren_US
dc.rightsCC-BY-NC-4.0en_US
dc.sourceTrends in Plant Science;1,(2015) Pagination 1,10en_US
dc.subjectgenomics-assisted breedingen_US
dc.subjectgenetic mappingen_US
dc.titleAnalytical and Decision Support Tools for Genomics-Assisted Breedingen_US
dc.typeJournal Articleen_US
dcterms.available2015-12-05en_US
dcterms.extent1-10en_US
cg.subject.agrovocplant breedingen_US
cg.subject.agrovocplant genetic resourcesen_US
cg.subject.agrovocdata managementen_US
cg.subject.agrovocmarker assisted selectionen_US
cg.subject.agrovocgenomic selectionen_US
cg.subject.agrovocdecision support toolsen_US
cg.contributor.centerInternational Crops Research Institute for the Semi-Arid Tropics - ICRISATen_US
cg.contributor.centerBeijing Genomics Institute- Shenzhen - BGI-Shenzhenen_US
cg.contributor.centerUniversity of Oklahoma, Center for Spatial Analysis - OU - CSAen_US
cg.contributor.centerThe James Hutton Institute - JHIen_US
cg.contributor.centerThe University of Western Australia, Faculty of Science, School of Plant Biology - UWA - FoS - SoPBen_US
cg.contributor.centerUniversity of Edinburgh, College of Medicine & Veterinary Medicine, Royal (Dick) School of Veterinary Studies - ED - CMVM - VETen_US
cg.contributor.centerInternational Maize and Wheat Improvement Center - CIMMYTen_US
cg.contributor.crpCGIAR Research Program on Grain Legumes - GLen_US
cg.contributor.funderNot Applicableen_US
cg.coverage.regionGlobalen_US
cg.contactR.K.Varshney@CGIAR.ORGen_US
cg.identifier.doihttps://dx.doi.org/10.1016/j.tplants.2015.10.018en_US
cg.isijournalISI journalen_US
dc.identifier.statusOpen accessen_US
mel.impact-factor10.899en_US
cg.issn1360-1385en_US
cg.journalTrends in Plant Scienceen_US
cg.volume1en_US


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