Department of Animal Science
ORCID IDs
Date of this Version
2011
Citation
Presented at Range Beef Cow Symposium XXII, November 29, 30, and December 1, 2011, Mitchell, Nebraska. Sponsored by Cooperative Extension Services and the Animal Science Departments of the University of Wyoming, Colorado State University, South Dakota State University, and the University of Nebraska–Lincoln.
Abstract
INTRODUCTION
Genomic information, in the form of Single Nucleotide Polymorphisms, has always held the promise to increase the accuracy of Expected Progeny Differences (EPD). This promise has finally been realized for those breeds that incorporate this information into their EPD calculations. For those breeds that have not, genomic information for complex traits (those controlled by many genes) is available to producers in a disjoined context and is published separately from EPD. Depending on the accuracy of the genomic test (as measured by the proportion of genetic variation explained) Marker-Assisted (or genomic enhanced) EPD can increase the accuracy of animals and lead to faster rates of genetic change.
BACKGROUND
The US Beef Industry has witnessed considerable evolution in terms of the genomic tests available in the market place. The tests that are currently being included in EPD are comprised of either 384 SNP or 50,000 (50K) SNP, although the research community is commonly using 50K or 770K genomic tests for discovery of “novel” traits (i.e. feed efficiency, disease susceptibility). The American Angus Association (AAA) began including genomic predictions into EPD calculations to producer Marker-Assisted EPDs (MA-EPD) in 2009. The list of traits for which this is done has continued to grow and can be found in table 1. The American Hereford Association (AHA) is on the verge of releasing MA-EPD and it is likely other breeds that wish to remain competitive will follow the lead of these two.
A common, and fair, question is to ask why genomic predictions are available for heavily recorded traits (i.e. growth) and not “novel” traits such as different measures of efficiency or disease susceptibility. In order to develop genomic tests, there must exist phenotypes to “train” the markers, where training is simply determining if there is an association between each marker and the trait of interest and quantifying that effect. Consequently, the first genomic tests focus on those traits for which vast phenotypic resources exist. There are large USDA funded projects currently underway that are focused on the two “novel” traits mentioned above.