2009 Annual Report
1a.Objectives (from AD-416)
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: Collect genotypes, specifically single-nucleotide polymorphisms (SNPs), and new phenotypes to improve accuracy and comprehensiveness of the national dairy database.
Subobjective 1.A: Increase the accuracy of pedigree information by using SNP genotypes to verify and to assign parentage.
Subobjective 1.B: Obtain additional data on health and management traits, and improve consistency of national database.
Objective 2: Characterize phenotypic measures of dairy practices, and provide the dairy industry with information needed to determine the impact of various herd management decisions on profitability.
Objective 3: Improve accuracy of prediction of economically important traits currently evaluated, determine merit and potential for developing genetic predictions for new traits, and investigate methods to incorporate high-density genomic data.
Subobjective 3.A: Develop methodology for calculation of genome-enhanced breeding values using SNP genotypes.
Subobjective 3.B: Develop methodology for accurate genetic predictions for new traits such as fertility and health.
Objective 4. Investigate economic value of traits and correlations among them to most efficiently combine evaluations to select for healthy dairy animals capable of producing quality milk at a low cost in many environments.
1b.Approach (from AD-416)
Objective 1: Extensive data on selected single nucleotide polymorphisms (SNPs) will be stored in a database, and intensive checks for accuracy will be conducted. Subobjective 1.A: A subset of SNPs will be selected for use in parentage verification and determination. Pedigree verification will be performed by comparing SNP genotypes of animals with those of recorded parents. Subobjective 1.B: Data for health and management traits will be obtained from dairy records processing centers. A system for submission and editing of data for new traits will be developed to allow routine data processing.
Objective 2: Reports will be developed to describe industry progress and various statistics from the national genetic evaluation system for dairy animals, including statistics for Dairy Herd Information programs; breed reports for cow longevity and culling rate; summaries for reproductive traits; crossbreeding summaries and comparison tables for breed performance; heifer and cow inventories by breed composition; evaluation averages, distributions, and changes; genetic trends; progeny-test profiles; and selection intensity changes. Need for separate rankings for a grazing environment will be investigated.
Objective 3: Test-day model methodology will be investigated. After patent issues with Cornell University are resolved, a test-day system will be implemented that provides parity-specific evaluations that account for maturity rate as well as evaluations for lactation persistency. Subobjective 3.A: Prediction of genetic merit using SNP information will be combined with results from the national dairy cattle genetic evaluation system to create an integrated prediction of genetic merit. Subobjective 3.B: Quality of available health data will be determined. Variance components will be estimated for individual and composite traits using threshold sire models. Methodology for genetic evaluation of health traits will be developed. Relationships among health and other traits of economic value will be examined. Environmental and genetic factors that affect gestation length of U.S. dairy cattle will be documented. Methods to improve accuracy of male-fertility evaluations from field data will be examined; effect of genetic and phenotypic factors on bull fertility will be studied. Methods and data for genetic evaluation of components of female fertility will be investigated.
Objective 4: Selection goals that improve dairy farm profit most rapidly will be determined by economic analysis. Costs associated with additional health and management variables will be examined to determine if national genetic evaluations for those traits are needed. Optimal indexes for specific target populations will be determined. Interactions of genotype with environment will be investigated. Tools for making breed comparisons will be developed.
Previously developed genomic predictions were transitioned from a research project to a production system, and the United States became the first country to replace official traditional genetic evaluations with genomic evaluations based on direct examination of DNA in January 2009. Numerous changes were made to the USDA genetic evaluation program to enable efficient management of genomic information, incorporate it in official USDA evaluations, and distribute those evaluations to stakeholders. Artificial-insemination and breed organizations now can use an online query to designate animals to be genotyped, determine if the animal has already been nominated, and check for the reason if a genotype was rejected; four commercial laboratories provide genotypes that are stored in the USDA national dairy database, and the most recent international evaluations are combined with genomic and traditional data into a single evaluation that includes all available information. The evaluation system is continuing to be streamlined to provide genomic evaluations that meet industry needs with available resources. The programs and edited genotypes were also used to compute Canadian national evaluations in August 2009; USDA and Canadian researchers cooperated in developing international evaluation methods to combine genomic information from all countries. Other research included:.
1)visualization of results from genomic predictions;.
2)derivation of factors to estimate daily fat, protein, and somatic cell score from one milking of cows milked twice daily;.
3)development of best prediction procedures for lactation yields that account for regional and seasonal differences;.
4)characterization and usage of sexed semen from U.S. field data and determination of the effect of sexed semen on U.S. Holstein conception rates;.
5)comparison of former and current service-sire fertility evaluations;.
6)characterization of milk ELISA scores for Johne's disease in U.S. dairy cows, investigation of factors that affect those scores; and estimation of genetic parameters and transmitting abilities for ELISA scores;.
7)documentation of trends in the international flow of Holstein genes; and.
8)characterization of somatic cell counts in dairy goat milk.
Official USDA genetic evaluations for dairy cattle include genomic information. The dairy industry can make better breeding and culling decisions, especially for young animals, if it has easy access to highly accurate estimates of genetic merit that include genomic data. To transition previously developed genomic predictions from a research project to a production system, numerous changes were made to the USDA genetic evaluation program to enable efficient management of genomic information, incorporate it in official USDA evaluations, and distribute those evaluations to stakeholders. Artificial-insemination and breed organizations now can use an online query to designate animals to be genotyped, determine if the animal has already been nominated, and check for the reason if a genotype was rejected; four commercial laboratories provide genotypes that are stored in the USDA national dairy database, and the most recent international evaluations are combined with genomic and traditional data into a single evaluation that includes all available information. Genomic information began to be included in official USDA genetic evaluations of dairy cattle that were released to the dairy industry in January 2009, and the evaluation system continues to be streamlined to provide genomic evaluations that meet industry needs with available resources. The United States was the first country to replace traditional genetic evaluations with genomic evaluations based on direct examination of DNA, and the programs and edited genotypes developed by USDA scientists were also used to compute Canadian national evaluations in August 2009; USDA and Canadian researchers cooperated in developing international evaluation methods to combine genomic information from all countries. Because the dairy industry now can select earlier which animals to use as parents of future generations, future efficiency and health of the national dairy herd will be improved.
|Number of New CRADAS||1|
|Number of Web Sites Managed||1|
Cole, J.B., Null, D.J. 2009. Genetic Evaluation of Lactation Persistency for Five Breeds of Dairy Cattle. Journal of Dairy Science. 92(5):2248-2258.
Wiggans, G.R., Tsuruta, S., Misztal, I. 2008. Technical Note: Adaptation of an Animal-Model Method for Approximation of Reliabilities to a Sire-Maternal Grandsire Model. Journal of Dairy Science. 91(10):4058-4061.
Norman, H.D., Wright, J.R., Weigel, K.A. 2009. Alternatives for Examining Daughter Performance of Progeny-Test Bulls between Official Evaluations. Journal of Dairy Science. 92(5):2348-2355.
Norman, H.D., Wright, J.R., Kuhn, M.T., Hubbard, S.M., Cole, J.B., Van Raden, P.M. 2009. Genetic and Environmental Factors That Impact Gestation Length in Dairy Cattle. Journal of Dairy Science. 92(5):2259-2269.
Van Raden, P.M. 2008. Efficient Methods to Compute Genomic Predictions. Journal of Dairy Science. 91(11):4414-4423.
Cole, J.B., Null, D.J., Van Raden, P.M. 2009. Best Prediction of Yields for Long Lactations. Journal of Dairy Science. 92(4):1796-1810.
Appuhamy, A.D., Cassell, B.G., Cole, J.B. 2009. Phenotypic and Genetic Relationships of Common Health Disorders with Milk and Fat Yield Persistencies from Producer-Recorded Health Data and Test Day Yields. Journal of Dairy Science. 92(4):1785-1795.
Van Raden, P.M., Van Tassell, C.P., Wiggans, G.R., Sonstegard, T.S., Schnabel, R.D., Taylor, J.F., Schenkel, F.S. 2009. Invited Review: Reliability of Genomic Predictions for North American Holstein Bulls. Journal of Dairy Science. 92(1):16-24.
De Vries, A., Cole, J.B. 2009. Profitable Dairy Cow Traits for Hot Climatic Conditions. In: Klopcic, M., Reents, R., Philipsson, J., and Kuipers, A., editors. Breeding for Robustness in Cattle. Wageningen, The Netherlands: Wageningen Academic Publishers. p. 227-248.
Miller, R.H., Kuhn, M.T., Norman, H.D., Wright, J.R. 2008. Death Losses for Lactating Cows in Herds Enrolled in Dairy Herd Improvement Test Plans. Journal of Dairy Science. 91(9):3710-3715.
Miller, R.H., Norman, H.D., Wright, J.R., Cole, J.B. 2008. Impact of Genetic Merit for Milk Somatic Cell Score of Sires and Maternal Grandsires on Herd Life of Their Daughters. Journal of Dairy Science. 92(5):2224-2228.
Cole, J.B., Van Raden, P.M., O'Connell, J.R., Van Tassell, C.P., Sonstegard, T.S., Schnabel, R.D., Taylor, J.F., Wiggans, G.R. 2009. Distribution and Location of Genetic Effects for Dairy Traits. Journal of Dairy Science. 92(6):2931-2946.
Wiggans, G.R., Sonstegard, T.S., Van Raden, P.M., Matukumalli, L.K., Schnabel, R.D., Taylor, J.F., Schenkel, F.S., Van Tassell, C.P. 2009. Selection of single-nucleotide polymorphisms and quality of genotypes used in genomic evaluation of dairy cattle in the United States and Canada. Journal of Dairy Science. 92(7):3431-3436.
Norman, H.D., Wright, J.R., Hubbard, S.M., Miller, R.H., Hutchison, J.L. 2009. Reproductive status of Holstein and Jersey cows in the United States. Journal of Dairy Science. 92(7):3517-3528.