EVALUATION, DEVELOPMENT, AND USE OF GENETIC RESOURCES TO IMPROVE LIFE-CYCLE EFFICIENCY OF BEEF CATTLE AND SHEEP
Location: Genetics, Breeding, & Animal Health
Title: Estimation of genetic parameters for average daily gain using models with competition effects
| Chen, Ching-Yi - UNIV OF NEBRASKA-LINCOLN |
| Kachman, Stephen - UNIV OF NEBRASKA-LINCOLN |
| Johnson, Rodger - UNIV OF NEBRASKA-LINCOLN |
| Newman, Scott - GENUS-HENDERSONVILLE, TN |
| Van Vleck, Lloyd |
Submitted to: Journal of Animal Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 29, 2008
Publication Date: October 1, 2008
Citation: Chen, C., Kachman, S.D., Johnson, R.K., Newman, S., Van Vleck, L.D. 2008. Estimation of genetic parameters for average daily gain using models with competition effects. Journal of Animal Science. 86:2525-2530.
Interpretive Summary: Competition among animals in a pen seems likely. Recently animal breeders have looked at how to account for such effects in genetic evaluations. Original work by plant breeders occurred in the 1960’s. Most such studies with mammals have involved pigs or, in one case, cattle. The current study is probably the most comprehensive with pigs. Several statistical models were compared, some including competition effects (genetic and environmental) and some ignoring competition effects. The data were furnished by the Pig Improvement Company and included records of growth of 11,235 pigs in pens with 14 penmates. Because many effects in the model are confounded or partially confounded, partitioning variation, especially that due to environmental effects such as pen, competition environmental and residual effects was impossible with some statistical models. Estimates of functions of these variances were estimable and were dependent on number in a pen. In general, and in agreement with most studies with pigs, variance due to competition genetic effects was small enough to be not important. Another key result, in agreement with a simulation study, was that variation that would have been associated with pen effects is due to competition environmental effects. Models for genetic evaluation should include either pen or competition environmental effects. Computations with pen effects in the model are much easier than with competition environmental effects.
Components of variance for ADG with models including competition effects were estimated from data provided by Pig Improvement Company on 11,235 pigs from 4 selected lines of swine. Fifteen pigs with average age of 71 d were randomly assigned to a pen by line and sex and taken off test after approximately 89 days (off-test weights ranged from 61 to 158 kg). Models included fixed effects of line, sex and contemporary group, with random direct genetic, competition (genetic and environmental), pen and residual effects. With the full model, variances due to direct, direct-competition and genetic competition (co)variance components could be partitioned with genetic competition variance small but statistically significantly different from zero. Variances due to environmental competition, pen, and residual effects could not be partitioned but combinations of environmental variances were estimable. With either pen effects or environmental competition effects in the model variances could be partitioned. Environmental competition effects seemed to be the source of variance associated with pens. With pen as a fixed effect and without environmental competition effects in the model, genetic components of variance could not be partitioned but combinations of genetic (co)variances were estimable. With both pen and environmental competition effects ignored, estimates of direct-competition and genetic competition (co)variance components were greatly inflated. With competition (genetic and environmental) effects ignored, the estimate of pen variance increased by 30% with little change in estimates of direct genetic or residual variance. When both pen and competition (genetic and environmental) effects were dropped from the model, variance due to direct genetic effects was inflated. Estimates of variance due to competition effects were small in this study. Including environmental competition effects as permanent environmental effects in the model did not change estimates of genetic (co)variances. We conclude that including either pen effects or environmental competition effects as random effects in the model seems desirable to avoid bias in estimates of genetic variances but including pen effects is much easier.