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Genomic selection in a single cross doubled-haploid wheat population Song, Jiayin (Susan)

Abstract

A traditional wheat breeding program normally takes 7 to 12 years to develop a new cultivar to be eligible for commercial release. Genomic selection (GS), which uses single-nucleotide polymorphism (SNP) marker information to predict breeding values, has been proven to be an efficient method to accelerate the lengthy breeding process and increase the resultant gain in many animal and plant species. In this study, two GS algorithms, Genomic Best Linear Unbiased Prediction (GBLUP) and Reproducing Kernel Hilbert Space (RKHS) regression, were evaluated using grain yield data generated from a single hard red winter wheat (Triticum aestivum L.) full-sib doubled-haploid (DH) population in two consecutive generations. In each generation, a total of 257 individuals were genotyped with 14,028 SNP markers using “Genotyping-by-Sequencing” (GBS). Due to the uniformity of genetic material across generations, year effect was considered as an environmental factor or replication for the analysis. Potential upward bias in model’s predictive accuracy was estimated by comparing the within-year cross-validation scheme with the cross-year prediction scheme. The effect of SNP marker number on the models’ predictive ability was also analyzed by creating SNP subsets filtered with absolute pairwise correlation (t) value. In general, RKHS produced higher predictive ability than GBLUP for predicting grain yield in this population. A 32 and 38% decrease in predictive ability was observed for GBLUP and RKHS models, respectively, when comparing within-year cross-validation and cross-year prediction models’ results. A t value of 0.4 could produce a similar predictive ability compared to using the unfiltered full SNP set, providing less computation- and time-consuming strategy. In the context of an ongoing breeding program, this study also demonstrated confidence of line selection based on GS results, advocating the implementation of GS in wheat variety development.

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Attribution-NonCommercial-NoDerivatives 4.0 International

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