Efficacy of plant breeding using genomic information

dc.creatorMontesinos-Lopez, O.A.
dc.creatorBentley, A.R.
dc.creatorSaint Pierre, C.
dc.creatorCrespo-Herrera, L.A.
dc.creatorRebollar-Ruellas, L.
dc.creatorValladares-Celis, P.C.
dc.creatorLillemo, M.
dc.creatorMontesinos-Lopez, A.
dc.creatorCrossa, J.
dc.date2023-06-22T20:20:11Z
dc.date2023-06-22T20:20:11Z
dc.date2023
dc.date.accessioned2023-07-17T20:10:38Z
dc.date.available2023-07-17T20:10:38Z
dc.identifierhttps://hdl.handle.net/10883/22621
dc.identifier10.1002/tpg2.20346
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7514364
dc.descriptionGenomic selection (GS) proposed by Meuwissen et al. more than 20 years ago, is revolutionizing plant and animal breeding. Although GS has been widely accepted and applied to plant and animal breeding, there are many factors affecting its efficacy. We studied 14 real datasets to respond to the practical question of whether the accuracy of genomic prediction increases when considering genomic as compared with not using genomic. We found across traits, environments, datasets, and metrics, that the average gain in prediction accuracy when genomic information is considered was 26.31%, while only in terms of Pearson's correlation the gain was of 46.1%, while only in terms of normalized root mean squared error the gain was of 6.6%. If the quality of the makers and relatedness of the individuals increase, major gains in prediction accuracy can be obtained, but if these two factors decrease, a lower increase is possible. Finally, our findings reinforce genomic is vital for improving the prediction accuracy and, therefore, the realized genetic gain in genomic assisted plant breeding programs.
dc.languageEnglish
dc.publisherJohn Wiley and Sons Inc
dc.relationhttps://acsess.onlinelibrary.wiley.com/doi/10.1002/tpg2.20346#support-information-section
dc.rightsCIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose
dc.rightsOpen Access
dc.source16
dc.source20346
dc.source1940-3372
dc.sourcePlant Genome
dc.subjectAGRICULTURAL SCIENCES AND BIOTECHNOLOGY
dc.subjectGenomic Selection
dc.subjectGenomic Prediction
dc.subjectGenomic Best Linear Unbiased Predictor
dc.subjectPLANT BREEDING
dc.subjectGENOMICS
dc.subjectMARKER-ASSISTED SELECTION
dc.subjectENVIRONMENT
dc.subjectWheat
dc.titleEfficacy of plant breeding using genomic information
dc.typeArticle
dc.typePublished Version
dc.coverageUSA


Este ítem pertenece a la siguiente institución