Genome-wide association study of growth in crossbred beef cattle

Chromosomal regions harboring variation affecting cattle birth weight and BW gain to 1 yr of age were identified by marker association using the highly parallel BovineSNP50 BeadChip (50K) assay composed of 54,001 individual SNP. Genotypes were obtained from progeny (F-1; 590 steers) and 2-, 3-, and 4-breed cross grandprogeny (F-1(2) = F-1 x F-1; 1,306 steers and 707 females) of 150 AI sires representing 7 breeds (22 sires per breed; Angus, Charolais, Gelbvieh, Hereford, Limousin, Red Angus, and Simmental). Genotypes and birth, weaning, and yearling BW records were used in whole-genome association analyses to estimate effects of individual SNP on growth. Traits analyzed included growth component traits: birth weight (BWT), 205-d adjusted birth to weaning BW gain (WG), 160-d adjusted postweaning BW gain (PWG); cumulative traits: 205-d adjusted weaning weight (WW = BWT + WG) and 365-d adjusted yearling weight (YW = BWT + WG + PWG); and indexes of relative differences between postnatal growth and birth weight. Modeled fixed effects included additive effects of calf and dam SNP genotype, year-sex-management contemporary groups, and covariates for calf and dam breed composition and heterosis. Direct and maternal additive polygenic effects and maternal permanent environment effects were random. Missing genotypes, including 50K genotypes of most dams, were approximated with a single-locus BLUP procedure from pedigree relationships and known 50K genotypes. Various association criteria were applied: stringent tests to account for multiple testing but with limited power to detect associations with small effects, and relaxed nominal P that may detect SNP associated with small effects but include excessive false positive associations. Genomic locations of the 231 SNP meeting stringent criteria generally coincided with described previously QTL affecting growth traits. The 12,425 SNP satisfying relaxed tests were located throughout the genome. Most SNP associated with BWT and postnatal growth affected components in the same direction, although detection of SNP associated with one component independent of others presents a possible opportunity for SNP-assisted selection to increase postnatal growth relative to BWT.