Submitted to: Journal of Animal Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: March 29, 2012
Publication Date: October 1, 2012
Repository URL: http://handle.nal.usda.gov/10113/57883
Citation: Schneider, J.F., Rempel, L.A., Rohrer, G.A. 2012. Genome-wide association study of swine farrowing traits. Part I: Genetic and genomic parameter estimates. Journal of Animal Science. 90(10):3353-3359. Interpretive Summary: Higher costs especially of feed and fuel are putting new demands on improving the efficiency of swine production. Measures of the swine female’s reproduction were studied to determine potential contributions to improvement in efficiency based on the performance of the female and her relatives (quantitative genetics) versus the contributions of the individual’s molecular genetic makeup. The performance traits studied included total number born, number born alive, number born dead, number still born, number of mummified fetuses, total litter birth weight, and average piglet birth weight. The results of this study indicate that both methods, quantitative and molecular, can contribute to genetic improvement of swine reproductive efficiency. The quantitative results may be directly incorporated into swine selection programs by knowledgeable advisors. The molecular results serve as a starting point for scientists to begin the identification of specific molecular markers that can be used in selection.
Technical Abstract: The primary objective of this study was to determine genetic and genomic parameters among swine farrowing traits. Genetic parameters were obtained by using MTDFREML and genomic parameters were obtained using GenSel. Genetic and residual variances obtained from MTDFREML were used as priors for the Bayes C analysis of GenSel. Farrowing traits included total number born (TNB), number born alive (NBA), number born dead (NBD), number still born (NSB), number of mummies (MUM), litter birth weight (LBW), and average piglet birth weight (ABW). Statistically significant heritabilities included TNB (0.093, P = 0.048), NBA (0.092, P = 0.041), LBW (0.197, P = 0.002), and ABW (0.260, P < 0.0001). Statistically significant genetic correlations included TNB-NBA (0.965, P < 0.0001), TNB-LBW (0.742, P < 0.0001), NBA-LBW (0.562, P < 0.0017), NSB-LBW (0.872, P < 0.0395), and LBW-ABW (0.631, P < 0.0002). Genetic parameters are similar to others found in the literature. The proportion of phenotypic variance explained by genomic markers generated by GenSel was TNB (0.044), NBA (0.055), NBD (0.001), NSB (0.010), MUM (0.002), LBW (0.112), and ABW (0.309). Limited information is available in the literature about genomic parameters. Only the estimate for NSB is significantly lower than what has been published. The estimate for ABW is higher than the estimate for heritability found in this study; whereas, other estimates of the proportion explained by genomic markers for traits with significant heritability were half the value of heritability. Our results indicate that significant genetic markers will be found for TNB, NBA, LBW, and ABW that will have either immediate use in industry or provide a roadmap to further research with fine mapping or sequencing of areas of significance. Furthermore, these results indicate that genomic selection implemented at an early age would have similar annual progress as traditional selection, and could be incorporated along with traditional selection procedures to improve genetic progress of litter traits.