1a. Objectives (from AD-416)
Use the BovineSNP50 assay to provide high-accuracy predictions of genetic merit to U.S. beef breeds; 2) Enable the adoption of whole genome enabled animal selection (WGEAS) by developing low-density and low-cost SNP assays for: a) intermediate-accuracy genetic prediction, b) mate selection, and c) parentage verification and traceability; 3) Develop, adapt and optimize statistical methodologies to: a) fully integrate SNP genotype or haplotype effects into existing genetic evaluation technologies, and b) supplement or replace pedigree data; and 4) Collaborate and coordinate U.S. and European Union WGEAS activities.
1b. Approach (from AD-416)
Genetic prediction using high-density SNP data will be implemented using MTDFREML. Implementation of more sophisticated strategies will follow using the MTGSAM programs that will be modified to accommodate extensions to the prediction model. Collaboration with a biotechnology company to develop a 384-SNP assay that is expected to dramatically decrease genotyping costs and increase sample throughput. A machine learning approach using a two-step feature subset selection algorithm will be evaluated for SNP selection for this assay. Develop BLUP approaches for the prediction of genetic merit in non-pedigreed populations using molecular relationship matrices. We shall manage this coordination and collaboration via e-mail and teleconference calls, however, we shall also meet at least annually in conjunction with the PAG or ISAG meetings alternating between the US and Europe to coordinate activities.
3. Progress Report
This report documents research conducted under funding proposal from the USDA NRI-CGP 43.1 Animal Genome. Award money was disbursed to the Beltsville Area, and then was disbursed to collaborators, including University of Missouri. This year activities focused on: 1) Genome resequencing of animals from important cattle breeds for the purpose of SNP discovery to allow development of high-density genotyping assays, 2) analysis of Illumina BovineSNP50 data sets for the development and refinement of genetic value prediction models, and 3) continued genotyping of animals from different beef breeds of registered cattle for the development of across breed molecular breeding value prediction equations. In total, about 600 billion base pairs of cattle DNA sequence information was produced by BFGL, University of Missouri, and collaborators. Sequences were aligned to the bovine UMD3.1 reference sequence to identify nearly 50 million SNP across more than 15 breeds. From these SNP, BFGL designed a second-generation 860K genotyping assay collaboratively with Illumina. Illumina has launched their 777K SNP genotyping product known as the BovineHD assay. Subsequently, Affymetrix released their 650K SNP genotyping product (BOS1) in January, 2011. We have also shown that molecular breeding value prediction equations developed for one breed perform poorly when applied to other distinct breeds. Thus, we generated BovineSNP50 genotypes for 3600 Angus, 2200 Limousin and 900 Hereford registered cattle and have production information available through the respective breed associations to aid across breed prediction equations. Fewer registered animals within each breed also results in slightly lower overall molecular breeding value accuracies relative to the dairy industry. Therefore, the cost of the BovineSNP50 assay prohibits wide application within the beef industry. To ameliorate this limitation we previously developed a reduced 384 SNP assay which predicts molecular breeding values in Angus cattle for marbling, ribeye muscle area, backfat thickness and yearling weight with accuracies up to 42%. This assay has been adopted by the American Angus Association, which now computes composite estimates of breeding value using all sources of information (phenotype, pedigree and molecular) and runs their national genetic evaluation software biweekly (rather than biannually) to deliver molecular test results to breeders. The first objective to provide high-accuracy predictions of genetic merit enhanced by DNA marker data (BovineSNP50) in U.S. cattle has been met in dairy cattle and progress has been achieved in beef cattle. Monitoring activities associated with this project included regular email correspondence and conference calls. This research supports two objectives of its related in-house project: 1) to use genotypic data and resulting bovine haplotype map to enhance genetic improvement in dairy cattle through development and implementation of whole genome selection and enhanced parentage verification approaches (obj. #2) and 2) to characterize conserved genome elements and identify functional genetic variation (obj. #3).