Abstract
Livestock producers often select for animals which are genetically superior for yield. Competition among animals in the same pen may affect yield of pen mates. If competitiveness has a genetic component, selection should be for direct genetic effects for yield and for genetic effects of competitiveness on yield of penmates (Muir and Schinkel, 2002). This simulation study examined estimates of variance components from models which ignored competition effects. A population structure of 642 related animals was created. Random effects were residual and pen effects and direct and competition genetic values with genetic correlation. Conclusions, based on 400 replications for 16 different sets of variance parameters, were that competition effects, if ignored, may inflate estimates of pen variance and of direct genetic variance and that ignoring pen effects may increase estimates of the genetic correlation and both genetic variances. Key words: Associative Effects, Genetic Correlation, REML
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This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.
Recommended Citation
Van Vleck, L. , D. and Cassady, J. P.
(2004).
"RANDOM MODELS WITH DIRECT AND COMPETITION GENETIC EFFECTS,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1149
RANDOM MODELS WITH DIRECT AND COMPETITION GENETIC EFFECTS
Livestock producers often select for animals which are genetically superior for yield. Competition among animals in the same pen may affect yield of pen mates. If competitiveness has a genetic component, selection should be for direct genetic effects for yield and for genetic effects of competitiveness on yield of penmates (Muir and Schinkel, 2002). This simulation study examined estimates of variance components from models which ignored competition effects. A population structure of 642 related animals was created. Random effects were residual and pen effects and direct and competition genetic values with genetic correlation. Conclusions, based on 400 replications for 16 different sets of variance parameters, were that competition effects, if ignored, may inflate estimates of pen variance and of direct genetic variance and that ignoring pen effects may increase estimates of the genetic correlation and both genetic variances. Key words: Associative Effects, Genetic Correlation, REML
