BIOINFORMATICS TO IMPLEMENT GENOMIC SELECTION (BIGS)
Genetics, Breeding, & Animal Health
2010 Annual Report
1a.Objectives (from AD-416)
This research and development project will develop analytical software for Bayesian analysis of genomic information and deliver it within an integrated bioinformatics infrastructure that will enable genomic evaluation using high-throughput SNP genotyping technology in livestock. We will implement these methodologies across a range of economic traits in beef cattle, first using existing genomic and phenotypic records from the U.S. Meat Animal Resarch Center and ultimately enabling researchers to submit data sets for analysis via a web interface. Collectively, we will deliver immediate and on-going opportunities in beef cattle for livestock managers, public researchers and industry geneticists to exploit genomic evaluation.
1b.Approach (from AD-416)
We will enhance existing methods for predicting missing genotypes to applications involving haplotypes and web-enable this software. We will extend theory-based single-trait Bayesian methods for additive effects to practical circumstances that can estimate allelic or haplotypic effects in the context of multiple traits, maternally influenced traits, and categorically expressed traits, to capitalize on both additive and non-additive effects. All these analytical tools will be made available via web interface. Our activities will be motivated and focused on genomic evaluation of beef cattle. Implementation of this research will fully support goals of the 2005-2010 USDA Strategic Plan, by enhancing international competitiveness of the U.S beef cattle and other economically-relevant agricultural industries through practical access to the latest advances in molecular genetic technology.
Progress of the Bioinformatics to Implement Genomic Selection (BIGS) project was monitored via email and telephone contact with the project directors, and access to the BIGS web site and source code repository. Pedigree, BovineSNP50 genotypes and phenotypes of several traits were loaded into the BIGS system, and Bayesian analyses were completed through the web interface. Results are available to collaborators for genomic predictions trained by the U.S. Meat Animal Research Center (USMARC) data. Alternate approaches to genotype inference were investigated. The programming position supported by BIGS, to continue development of genotype and haplotype inference software, was filled. Software that, where possible, determines missing genotypes from known parent and progeny genotypes according to Mendelian inheritance rules is entering the testing phase before incorporation into the BIGS system.