Response to early generation genomic selection for yield in wheat

dc.creatorBonnett, D.G.
dc.creatorYongle Li
dc.creatorCrossa, J.
dc.creatorDreisigacker, S.
dc.creatorBasnet, B.R.
dc.creatorPerez-Rodriguez, P.
dc.creatorAlvarado Beltrán, G.
dc.creatorJannink, J.L.
dc.creatorPoland, J.A.
dc.creatorSorrells, M.E.
dc.date2022-02-03T01:10:17Z
dc.date2022-02-03T01:10:17Z
dc.date2022
dc.date.accessioned2023-07-17T20:08:51Z
dc.date.available2023-07-17T20:08:51Z
dc.identifierhttps://hdl.handle.net/10883/21936
dc.identifier10.3389/fpls.2021.718611
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7513704
dc.descriptionWe investigated increasing genetic gain for grain yield using early generation genomic selection (GS). A training set of 1,334 elite wheat breeding lines tested over three field seasons was used to generate Genomic Estimated Breeding Values (GEBVs) for grain yield under irrigated conditions applying markers and three different prediction methods: (1) Genomic Best Linear Unbiased Predictor (GBLUP), (2) GBLUP with the imputation of missing genotypic data by Ridge Regression BLUP (rrGBLUP_imp), and (3) Reproducing Kernel Hilbert Space (RKHS) a.k.a. Gaussian Kernel (GK). F2 GEBVs were generated for 1,924 individuals from 38 biparental cross populations between 21 parents selected from the training set. Results showed that F2 GEBVs from the different methods were not correlated. Experiment 1 consisted of selecting F2s with the highest average GEBVs and advancing them to form genomically selected bulks and make intercross populations aiming to combine favorable alleles for yield. F4:6 lines were derived from genomically selected bulks, intercrosses, and conventional breeding methods with similar numbers from each. Results of field-testing for Experiment 1 did not find any difference in yield with genomic compared to conventional selection. Experiment 2 compared the predictive ability of the different GEBV calculation methods in F2 using a set of single plant-derived F2:4 lines from randomly selected F2 plants. Grain yield results from Experiment 2 showed a significant positive correlation between observed yields of F2:4 lines and predicted yield GEBVs of F2 single plants from GK (the predictive ability of 0.248, P < 0.001) and GBLUP (0.195, P < 0.01) but no correlation with rrGBLUP_imp. Results demonstrate the potential for the application of GS in early generations of wheat breeding and the importance of using the appropriate statistical model for GEBV calculation, which may not be the same as the best model for inbreds.
dc.languageEnglish
dc.publisherFrontiers
dc.relationhttps://hdl.handle.net/11529/10548576
dc.relationhttps://figshare.com/collections/Response_to_Early_Generation_Genomic_Selection_for_Yield_in_Wheat/5787197
dc.relationNutrition, health & food security
dc.relationAccelerated Breeding
dc.relationGenetic Innovation
dc.relationBill & Melinda Gates Foundation
dc.relationCGIAR Trust Fund
dc.relationhttps://hdl.handle.net/10568/126319
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.source12
dc.source1664-462X
dc.sourceFrontiers in Plant Science
dc.source718611
dc.subjectAGRICULTURAL SCIENCES AND BIOTECHNOLOGY
dc.subjectEarly Generation
dc.subjectGenomic Selection
dc.subjectLinear and Non-Linear Kernels
dc.subjectGenomic Matrices
dc.subjectWheat Breeding
dc.subjectBreeding Methodology
dc.subjectResponse to Selection
dc.subjectMARKER-ASSISTED SELECTION
dc.subjectGENOMICS
dc.subjectWHEAT
dc.subjectPLANT BREEDING
dc.subjectBREEDING METHODS
dc.titleResponse to early generation genomic selection for yield in wheat
dc.typeArticle
dc.typePublished Version
dc.coverageSwitzerland


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