Abstract

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.

Melanie K Hayr, Mahdi Saatchi, Ric G Sherlock, Dave Johnson, Dorian J Garrick

Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume Genetic Improvement Programs: Selection using molecular information (Posters), , 505, 2014
Download Full PDF BibTEX Citation Endnote Citation Search the Proceedings



Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.