AIP Research Project
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Research

AIP research project


ARS 1245-31000-101-00

Animal improvement program

(formerly "Improving genetic predictions in dairy animals using phenotypic and genomic information")


Project summary

The primary objective of this project 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. Collecting and combining information from phenotypes, genotypes, and pedigrees into more accurate evaluations for breeders to use in selection decisions 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 to 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. 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. Phenotypic effects of management practices and interactions of genotype with environment will also be documented using the national database. 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. Other species may also be improved by using the genomic selection methods developed in this research as an example.




Last Modified: 06/25/2014