Variance components and animal rankings for milk yield and fat yield in a multibreed dairy cattle population using genomic-polygenic, genomic and polygenic models

Comparative accuracies of genetic values predicted for economically important milk traits, genome-wide association, and linkage disequilibrium patterns of Canadian Holstein cows

“…Estimates of heritability using G matrix based on the bovine HD Beadchip were 0.31, 0.39, and 0.51 (Buitenhuis et al, 2013) and 0.21, 0.33, and 0.40 (Poulsen et al, 2015) for MY, FY, and PY, respectively, in Danish Holstein populations. Wongpom et al (2018) estimated genetic parameters for MY and FY in a multibreed dairy population (91% of all animals were at least 75% Holstein) and reported heritability estimates of 0.38 for MY and 0.41 for FY. Karimi et al (2018) predicted the reliability and the prediction bias of GBLUP method using G matrix based on the 50k genotype records from Canadian Holstein bulls and estimated heritabilities at 0.41, 0.34, and 0.37 for MY, FY, and PY, respectively.…”

“…Heritability estimates from GBLUP and BayesB models in the current study are lower than those reported in previous studies. As indicated by Wongpom et al (2018), differences in heritability estimates from different studies could be affected by the type and the number of SNP markers in the genome analyses, LD between SNP markers and genes affecting milk yield traits in each population, the size of reference populations, the statistical models used in each country, and the population structure across countries.…”