|ROLF, M - University Of Missouri|
|TAYLOR, J - University Of Missouri|
|SCHNABEL, R - University Of Missouri|
|MCKAY, S - University Of Missouri|
|NORTHCUTT, S - American Angus Association|
|KERLEY, M - University Of Missouri|
|WEABER, R - University Of Missouri|
Submitted to: Animal Genetics
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/7/2011
Publication Date: N/A
Interpretive Summary: In this study, 698 Angus steers with individual average daily feed intake, residual feed intake (RFI), average daily gain, and predicted feed intake phenotypes were genotyped for 54,000 single nucleotide polymorphisms (SNPs). Association between 41,028 SNP markers and phenotypes were determined using a forward selection model. Genomic regions surrounding each forward selected SNP were analyzed to identify regions that influence biological pathways related to growth and metabolism. SNPs identified in this study could be incorporated into commercial marker panels for genomic selection for feed efficiency traits in Angus cattle.
Technical Abstract: Phenotypes for average daily feed intake (AFI; kg/d), residual feed intake (RFI; kg/d), average daily gain (ADG; kg/d) and predicted dry matter required (pDMR; kg/d) were estimated by correcting field records for effects of pen, year and season using a mixed linear model incorporating genomic relationships for 698 Angus steers genotyped with the Illumina BovineSNP50 assay. Association analyses of estimated breeding values (EBVs) and phenotypes were performed for 41,028 single nucleotide polymorphisms (SNPs) and permutation analysis was used to empirically establish the genome-wide significance threshold (p<0.05) for each trait. SNPs significantly associated with each trait were used in a forward selection algorithm to identify genomic regions putatively harboring genes of large effect on each trait. A total of 53, 66, 68 and 71 SNPs explained 54.12%, 62.69%, 55.13% and 56.33% of the additive genetic variation in steer breeding values and 65, 18, 24 and 27 SNPs explained 52.73%, 25.49%, 27.09% and 30.25% of the phenotypic variation in AFI, RFI, ADG and pDMR, respectively within the training population. Evaluation by pathway analysis revealed that many of these SNPs are in genomic regions that harbor genes with metabolic functions. The presence of quantitative trait loci of large effect and the genetic correlations between traits resulted in 13.2% (4.6%) of SNPs selected for AFI and 4.5% (5.6%) of SNPs selected for RFI also being selected for ADG in the analysis of breeding values (phenotypes). A correlation of 0.59 between AFI and pDMR suggests that model-predicted feed intake phenotypes may usefully augment individual feed intakes for use in genetic evaluation.