Five SNPs were analyzed across 4,801 Holstein-Friesian cows, including three QTN for milk fat yield: DGAT1, GHR, and AGPAT6; a QTN for stature: PLAG1; and a control SNP with no effect on milk fat yield. Dominance was observed for DGAT1, AGPAT6 and PLAG1. A base model of 35,000 SNPs was run in GenSel using BayesB. In addition to the base model 1) SNP dosage was fit as a random covariate, or 2) SNP genotype was fit as a fixed covariate, or 3) SNP dosage was fit as a fixed covariate. Including these QTN as random covariates increased accuracy of direct genomic value prediction. Including QTN as fixed covariates slightly decreased accuracy and increased bias. Including DGAT1 as a fixed covariate decreased bias. These results suggest inclusion of QTN genotypes can potentially increase accuracy and decrease bias of DGV, although only slightly.
Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Genetic Improvement Programs: Selection using molecular information (Posters), , 505, 2014
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