Submitted to: Midwestern Section of the American Society of Animal Science
Publication Type: Abstract Only
Publication Acceptance Date: November 8, 2007
Publication Date: September 22, 2008
Repository URL: http://asas.org/abstracts/2008sectional/Supplement_3-38.pdf
Citation: Allan, M.F. 2008. Genomic architecture of energy utilization and its role in beef cattle efficiency [abstract]. Journal of Animal Science. 86(E-Supplement 3):52. Abstract #48. Technical Abstract: Historically, academia revisits energy utilization every 10 to 15 years with each cycle providing some benefit to the producer. The lack of progress in factors limiting the understanding of the genetics of energy utilization include the difficulty and costs to accurately measure individual intakes, beef cattle’s long generation interval, difficulty in definition, and a need for evaluation in the producing adult, as well as the growing/finishing juvenile. With 70 to 80% of the total variable costs in beef production associated with feed costs, any improvement in feed efficiency will have a significant impact in profitability in segments of beef production. Heritability estimates of feed efficiency range from 0.28 to 0.44 suggesting feed efficiency can be improved through genetic selection. Technology has developed to the point that we can better measure, record and analyze phenotypes, and implement selection for energetic efficiency. Application of marker-assisted selection is limited by a lack of information on quantitative trait loci (QTL) that are representative of U.S. beef cattle populations and understanding the correlated responses for many production traits. Identification of QTL is needed to devise an optimum sampling strategy to maximize genetic change and minimize costs of phenotyping and genotyping of animals. Feed efficiency projects at USMARC are structured to provide information to map QTL in the producing female at two life stages (growing and mature) and during the finishing phase in castrate males. Genetic correlations for a wide variety of traits, including multiple components of energy utilization, will be evaluated looking at all segments of the beef cattle production cycle. Genetical genomics will be applied to further define the functional biology underlying the genetic regulation by merging the use of transcript abundance and products of metabolism with over 50,000 SNP markers per animal.