Location: Location not imported yet.Title: A novel analytical method detects response of the Angus (Bos taurus) genome to artificial selection on complex traits Author
|Kim, Jaw Woo|
Submitted to: Genome Biology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/9/2012
Publication Date: 11/9/2012
Citation: Mcclure, M.C., Decker, J.E., Vasco, D.A., Mckay, S.D., Rolf, M.M., Kim, J., Northcutt, S.J., Bauck, S., Woodward, B., Schnabel, R.D., Taylor, J.F. 2012. A novel analytical method detects response of the Angus (Bos taurus) genome to artificial selection on complex traits. Genome Biology. DOI: 10.1186/1471-2164-13-606. Interpretive Summary: Recent research suggests that the identification of genomic regions in domestic species that have been subjected to strong human selection for desired traits requires the use of complex statistical models. In this study, the search for genomic regions responding to selection is merged with genome-wide associations to quantify the genome-wide response to selection in US registered Angus cattle. By relating the detected signatures of selection to traits, we infer that artificial selection in US registered Angus cattle has historically been focused on growth and maternal traits. This result is directly confirmed by the response to selection in these traits estimated directly using EPDs estimated by the American Angus Association.
Technical Abstract: Several methods have recently been developed to identify selective sweeps within genomes. However, recent theoretical and empirical work suggests that polygenic models are required to identify the genomic regions that have responded to selection on complex traits. Using DNA samples from US registered Angus beef bulls born over a 50 year period, we examine the effects of selection on the genome of this breed. We present results from the application of a quantitative genetic model to identify signatures of recent ongoing selection. We show that US Angus cattle have been selected to systematically alter their mean additive genetic merit for almost all of the 16 production traits routinely recorded by breeders. We further estimate the time-dependency of allele frequency for 44,817 SNP loci using genomic best linear unbiased prediction, BayesCp, and generalized least squares. Finally, we reconstruct the primary phenotypes that have historically been exposed to selection from a genome-wide analysis of the 16 production traits and gene ontology enrichment analysis. We demonstrate that polygenic quantitative genetic models correct for sampling effects which lead to time-dependent pedigree stratification and reveal genomic signatures of ongoing selection. Because multiple traits have historically been simultaneously selected and most quantitative trait loci have small effects, selection has incrementally altered allele frequencies throughout the genome. Two QTL of large effect were not among the most strongly selected loci due to their antagonistic pleiotropic effects on strongly selected phenotypes. Our method may readily be extended to temporally-stratified human or model organism populations.