|Van tassell, Curtis - Curt|
Submitted to: Journal of Dairy Science
Publication Type: Peer reviewed journal
Publication Acceptance Date: 2/25/2000
Publication Date: 8/11/2000
Citation: Van Tassell, C.P., Misztal, I., Varona, L. 2000. Method r estimates of additive genetic, dominance genetic, and permanent environmental fraction of variances for yield and health traits of holsteins. Journal of Dairy Science. vol. 83, pp. 1873-77. Interpretive Summary: The objective of this study was to estimate genetic parameters associated with dominance genetic effects and inbreeding depression for milk, fat, and protein yields, somatic cell score, and productive lifetime in Holstein dairy cattle. Optimization of breeding programs in the presence of significant dominance genetic effects would require mate allocation strategies to maximize genetic improvement of the population. Estimates from this research indicate that dominance variance is very important for maximizing genetic gain for length of productive life, moderately important for improving milk, fat, and protein yields, and not important for somatic cell score. Inbreeding depression estimates indicated that minimizing inbreeding by avoiding mating related animals is critical for maximizing length of productive life, fairly important for maximum milk, fat, and protein yields, and not important for somatic cell score. These estimates can be incorporated into the national genetic evaluation to account for dominance genetic effects and inbreeding to maximize genetic progress and productivity.
Technical Abstract: Fractions of variance accounted for by additive genetic, dominance genetic, and permanent environmental effects for milk, fat, and protein yields, somatic cell score, and productive life were estimated from Holstein data used for national genetic evaluations. Contemporary group assignments were determined using the national procedure. Data included 1,973,317 milk and fat records for 812,659 cows, 1,019,421 protein records for 462,067 cows, 468,374 lactation average somatic cell score records for 232,909 cows, and 735,256 cows with productive life records. Variance components were estimated with the JAADOM program, which uses iteration on data and second-order Jacobi iteration for obtaining solutions to the mixed model equations and Method R for estimation of variance components. Ten different random data subsets were used to estimate parameters for each trait. Estimated additive genetic, dominance genetic, and permanent environmental fractions of variance were .33, .06, and .10 for milk yield; .34, .05, and .10 for fat yield; .32, .05, and .09 for protein yield; and .17, .01, and .16 for lactation average somatic cell score. Estimated additive genetic and dominance genetic fractions of variance were .12 and .06 for productive life. Mean empirical standard errors of additive genetic, dominance genetic, and permanent environmental variance fractions were .003, .008, and .008.