IMPROVING GENETIC PREDICTIONS IN DAIRY ANIMALS USING PHENOTYPIC AND GENOMIC INFORMATION
Location: Animal Improvement Programs
Project Number: 1245-31000-101-00
Start Date: Jul 24, 2012
End Date: Jul 23, 2017
The primary objective is to improve the productive efficiency of dairy animals for traits of economic interest through genetic evaluation and management characterization so that the United States and other countries can meet the dietary needs of their populations. Specific objectives include:
Objective 1. Expand national and international collection of phenotypic and genotypic data through collaboration with the Council on Dairy Cattle Breeding and the Bovine Functional Genomics Laboratory (BFGL).
Objective 2. Develop a more accurate genomic evaluation system with advanced, efficient methods to combine pedigrees, genotypes, and phenotypes for all animals.
Objective 3. Use economic analysis to maximize genetic progress and financial benefits from collected data focused on herd management practices, optimal systems for genetic improvement, quantification of economic values for potential new traits such as feed efficiency, economic values of individual traits, and methods to select healthy, fertile animals with high lifetime production.
Information from phenotypes, genotypes, and pedigrees will be collected and combined into more accurate genetic evaluations, which will aid in improving the production efficiency of future dairy animals. Statistical methods will be derived, and advanced and efficient computer programs will be developed to process the rapidly growing database of international genomic information and remove bias caused by genomic preselection. Evaluations for additional traits will be developed if their estimated economic values and heritabilities are sufficiently high to justify selection. All traits will be combined into updated genetic-economic indexes to guide breeders with selection goals, and an index targeted to grazing herds will be developed. Methods to combine genotypes from all breeds and crossbreds in the same model will be further developed and tested. Profits from alternative breeding programs and potential investments in data will be compared using simulations and deterministic models. Cooperation with other scientists in ARS, universities, and industry will result in more cost-effective genotyping tools and will maximize benefits from the data collected. Protocols for efficient international sharing of genotype and pedigree data will be developed. Phenotypic effects of management practices and interactions of genotype with environment will also be documented using the national database. Nonadditive genomic effects such as dominance and epistasis will be investigated, and precision mating strategies will be derived to reduce economic loss from inbreeding. Higher density genotyping and full or targeted sequencing may lead to discovering causative mutations that affect important traits and to including quantitative trait loci (QTLs) in predictions instead of only markers. The QTLs and markers with largest effects will be included on smaller, special-purpose chips to provide greater accuracy with less genotyping cost. Methods to impute higher density genotypes from less dense genotypes will be improved. Other species may also be improved by using the genomic selection methods developed in this research as an example.