Multivariate analysis of a genome-wide association study in dairy cattle.

Multiple-trait genome-wide association study (GWAS) analyses were compared with single-trait GWAS for power to discover and subsequently validate genetic markers (single nucleotide polymorphisms; SNP) associated with dairy traits. The SNP associations were discovered in 1 Holstein population and validated in both a Holstein population consisting of bulls younger than those in the discovery population and a Jersey population. The multivariate methods used were a principal component analysis and a series of bivariate analyses. The statistical power of detecting associations using multiple-trait GWAS was as good as or better than that of the best single-trait GWAS. Additional SNP associations were found with the multivariate methods that had not been discovered in the single-trait analyses; this was achieved without an increase in the false discovery rate. From the multivariate analysis, 4 common pleiotropic patterns were identified among the putative quantitative trait loci (QTL) affecting the Australian selection index. These patterns could be interpreted as a primary effect of the putative QTL on 1 or more milk components and secondary effects on other components. The multivariate analysis did not appear to increase the precision with which putative QTL were mapped. Copyright (c) 2010 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.