|Van Vleck, Lloyd|
Submitted to: Journal of Animal Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/26/1999
Publication Date: N/A
Citation: Interpretive Summary: Relatively recent developments in statistical computing allow for consider- ation of relationships among all animals with records and of adjustment for inbreeding of an animal and of its dam in programs used for genetic evaluations of beef cattle. The simplest sire model considers only relationships between a sire and his progeny even though sires and dams of progeny may be related. The most complete animal model considers all relationships among animals, sires, and dams. Complex models and calcula- tion of inbreeding coefficients to be used as covariates result in more computing costs. This study of a herd of Hereford cattle under selection since 1934 compared 12 genetic models ranging from the simple sire model to the complete animal model as well as including or not including adjust- ments for inbreeding of animal and dam. The simple sire model was found to be inadequate for estimation of genetic parameters and for prediction of breeding values. Sire and dam models that account for genetic relation ships resulted in estimates and ranks for breeding values similar to those for the full animal model. Thus, if computationally possible, full animal models are recommended for genetic evaluation of weight traits of beef cattle. On the other hand, failure to account for effects of inbreeding had essentially no effect on estimates of genetic parameters or on prediction of breeding values. These results suggest that the computationally costly procedure of calculating inbreeding coefficients to use as covariate adjustments may not be necessary.
Technical Abstract: Different analytical models were compared to estimate genetic parameters for birth (BWT, n=4155), 205-day (WWT, n=3884) and 365-day (YWT, n=3476) weights for Line 1 Hereford cattle selected for postweaning growth from 1934 to 1989 at ARS-USDA, Miles City, MT. Model 1 included fixed effects of year, sex, age of dam; covariates for birth day and inbreeding coefficients sof animal and dam; and additive genetic and residual effects. Model 2 ignored inbreeding coefficients. Model 3 was same as Model 1 but included maternal genetic and permanent environmental effects. Model 4 ignored inbreeding. Model 5 was same as Model 1 but with a random sire instead of animal genetic effect. Model 6 ignored inbreeding. Model 7 was a sire model, but considered relationships among males. Model 8 was a sire model, assuming sires to be unrelated, and with uncorrelated dam effects. Model 9 was a sire and a dam model with relationships to account for direct and maternal genetic effects; and with dams to account for uncorrelated maternal permanent environmental effects. Model 10 was a sire model with uncorrelated maternal grandsire and dam effects. Model 11 was a sire- maternal grandsire model, with dams as uncorrelated effects but with sires and maternal grandsires assumed to be related using male relationships and full relationships (Model 12). Heritability estimates and rankings on predicted breeding values were similar whether or not inbreeding coefficients for animal and dam were included. The full animal model (Model 3) or the sire and dam model with relationships (Model 9) was needed to estimate variances and covariances for direct, maternal genetic and permanent environmental effects.