4.5 Article

Genome-wide association analysis for feed efficiency in Angus cattle

Journal

ANIMAL GENETICS
Volume 43, Issue 4, Pages 367-374

Publisher

WILEY
DOI: 10.1111/j.1365-2052.2011.02273.x

Keywords

beef cattle; BovineSNP50; feed efficiency; quantitative trait loci; single nucleotide polymorphism

Funding

  1. National Research Initiative from the USDA Cooperative State Research, Education, and Extension Service [2008-35205-04687]
  2. Agriculture and Food Research Initiative from the USDA National Institute of Food and Agriculture [2009-65205-05635]
  3. Missouri Life Science Research Board [13321]
  4. NIFA [581822, 2009-65205-05635] Funding Source: Federal RePORTER

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Estimated breeding values for average daily feed intake (AFI; kg/day), residual feed intake (RFI; kg/day) and average daily gain (ADG; kg/day) were generated 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) 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 harbouring genes with effects on each trait. A total of 53, 66 and 68 SNPs explained 54.12% (24.10%), 62.69% (29.85%) and 55.13% (26.54%) of the additive genetic variation (when accounting for the genomic relationships) in steer breeding values for AFI, RFI and ADG, respectively, within this population. Evaluation by pathway analysis revealed that many of these SNPs are in genomic regions that harbour genes with metabolic functions. The presence of genetic correlations between traits resulted in 13.2% of SNPs selected for AFI and 4.5% of SNPs selected for RFI also being selected for ADG in the analysis of breeding values. While our study identifies panels of SNPs significant for efficiency traits in our population, validation of all SNPs in independent populations will be necessary before commercialization.

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