|Azevedo, Jr., Jairo|
|Cushman, Robert - Bob|
Submitted to: Journal of Agricultural Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 6/16/2013
Publication Date: 9/1/2013
Citation: Azevedo, Jr., J., Souza, J.C., Cushman, R.A., Bink, M.C.A.M., Perazza, C.A., Meirelles, S.L., Goncalves, T.M. 2013. Alternative models in genetic analyses of carcass traits measured by ultrasonography in Guzerá cattle: A Bayesian approach. Journal of Agricultural Science 5(9):29-36. Interpretive Summary: The Guzerá breed has excelled in Brazil, and there is a need to formulate a selection index for carcass traits in this breed that will both ensure the improvement of carcass traits and help to prevent negative impacts of selection for carcass traits on fertility in the cow herd. The majority of traits in beef cattle are controlled by many genes each having very small effects on the overall phenotype. There are different ways to model these genetic effects to estimate their relationship to production traits. It was hypothesized that a combination of the most used models would allow the separation of polygenic and major gene effects for rib-eye area, rump fat thickness, and back fat thickness. The combined model indicated the possibility of up to three major genes for rib-eye area and up to two major genes for back fat thickness in the Guzerá breed that could be the targets for the development of genetic markers to aid in improving carcass traits. Application of this combined model may aid in improving production traits in the Guzerá breed.
Technical Abstract: The objective was to study alternative models for genetic analyses of carcass traits assessed by ultrasonography in Guzerá cattle. Data from 947 measurements (655 animals) of Rib-eye area (REA), rump fat thickness (RFT) and backfat thickness (BFT) were used. Finite polygenic models (FPM), infinitesimal polygenic models (IPM) and FPM combined with IPM (IPM + FPM) were empirically tested, adjusting for the effects of permanent environment, age and weight at measurement and the contemporary group. A Bayesian analysis using the computer package FlexQTL™ was adopted. The combined model adjusted to the data, allowing reliable genetic analyses of REA and BFT. For the RFT, the IPM model was the only one to have convergence and, in this case, the trait should be analyzed by a polygenic model. The presence of up to three major genes (MGs) controlling the expression of REA and two MGs for BFT was detected. The additive genetic action was over dominance to REA, and for BFT the dominance genetic action was greater. Heritability estimates, and respective standard error, adjusted for the combined model to REA were 0.15 (0.00025) for the polygenic fraction and 0.10 (0.00019) for the oligogenic fraction; for BFT was 0.19 (0.00027) and 0.13 (0.00025), respectively. Heritability of 0.17 (0.00028) was estimated for RFT when the model was adjusted to IPM. There are major genes segregating within the population studied for REA and BFT traits, thus, their genetic analyses must be studied considering oligogenic effects. The major gene effects detected for a small number of genes, may possibly help to increase the reliability in detecting chromosomal regions that explain and control the phenotypic expression of these traits, facilitating research on detection and validation of molecular markers in this population.