2008 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.
Genotypes derived from DNA of 5,285 Holstein bulls and 75 Holstein cows were used in estimating genetic effects for nearly 40,000 single-nucleotide polymorphisms. Based on those effects, genomic predictions for yield (milk, fat, and protein), somatic cell score (indicator for mastitis resistance), productive life (longevity), daughter pregnancy rate (cow fertility), calving ease, final score (conformation), and net merit (a genetic-economic index) were developed. Two different evaluations were developed to predict the genetic merit of an animal's daughters and sons separately. Genomic predictions for genotyped bulls and cows (mostly calves) were distributed in April and July 2008 to owners and to organizations that paid for genotyping to aid in selection decisions. A new procedure to rank bull fertility phenotypically (sire conception rate) was developed to improve accuracy of the current procedure (estimated relative conception rate) and to broaden the data upon which bull fertility was evaluated. Factors related to the cow that is being inseminated that distort bull fertility measures were identified and removed to improve prediction of bull fertility. Other research included.
1)development and implementation of interim evaluations to evaluate daughter performance of progeny-test bulls between official evaluations;.
2)derivation of factors to estimate daily yield from single milkings for Holsteins milked two or three times daily;.
3)enhancement of a data-exchange format and national database for producer-recorded health event data from on-farm management software;.
4)determination of factors that affect abortion frequency in U.S. dairy herds;.
5)investigation of the impact of selection for decreased somatic cell score on productive life and culling for mastitis;.
6)characterization of reproductive trends of U.S. dairy herds;.
7)investigation of the impact of selection for increased daughter fertility on productive life and culling for reproduction; and.
8)documentation of the breed composition of the U.S. dairy cattle herd. For National Program 101 (Food Animal Production), progress on genomic predictions and genetic evaluations (including data collection and adjustment) relates to Component I (Understanding, Improving, and Effectively Using Animal Genetic and Genomic Resources) by enabling identification of functional genes and their interactions and development and implementation of genome-enabled genetic improvement programs; progress on measuring and ranking bull fertility and on characterizing reproductive traits relates to Component II (Enhancing Animal Adaptation, Well-Being, and Efficiency in Diverse Production Systems) through development of tools to help reduce reproductive losses.
Development of a new procedure to rank bull fertility. To improve accuracy of the current procedure (estimated relative conception rate) for measuring bull fertility and to broaden the data upon which bull fertility was evaluated, "sire conception rate," a new and more accurate measure, was developed through an extensive 4-year research effort. First, factors were identified that were related to the bull that provided the unit of semen and that helped to improve the prediction of whether that unit of semen resulted in a pregnancy. Second, factors were identified that were related to the cow receiving the unit of semen and that distorted the fertility measure for the bull providing the semen (nuisance variables); those nuisance variables were removed to allow obtaining the best measure of the bull's success in impregnating the cow. Sire conception rates were provided to the dairy industry for the first time in August 2008. Because differences in bull fertility greatly affect the value of semen purchases, the more accurate measure will allow producers to improve herd reproduction and lessen reproductive losses. This accomplishment addressed National Program 101 (Food Animal Production), Component II (Enhancing Animal Adaptation, Well-Being, and Efficiency in Diverse Production Systems), Problem Statement b (Reducing Reproductive Losses).
Development of interim evaluations for bulls in progeny testing. The change in August 2007 from quarterly to triannual official U.S. genetic evaluations to coincide with international evaluations caused a delay in receiving estimates of genetic merit for progeny-test bulls. At the request of the dairy industry, an unofficial "interim" evaluation was developed for progeny-test bulls based on lactation data from herds with bull daughters that calved in recent months. The interim evaluations can provide information accurate enough for semen collection and storage (banking) for bulls of potentially superior genetic merit. The dairy industry approved release of the interim evaluations 3 times a year between official evaluations, and the first release to the industry was in November 2007. Each week of earlier delivery of bull evaluations for milk yield is worth about $11 million annually as a result of better genetics. This accomplishment addressed National Program 101 (Food Animal Production), Component I (Understanding, Improving, and Effectively Using Animal Genetic and Genomic Resources), Problem Statement d (Develop and Implement Genome-Enabled Genetic Improvement Programs).
Development of genomic predictions for dairy cattle. To improve accuracy of genetic evaluations of dairy cattle for economically important traits, estimates of genetic merit based on genotype were developed for economically important traits: yield (milk, fat, and protein), somatic cell score (indicator for mastitis resistance), productive life (longevity), daughter pregnancy rate (cow fertility), calving ease, final score (conformation), and net merit (a genetic-economic index) and combined with traditional genetic evaluations. Two different evaluations were developed to predict the genetic merit of an animal's daughters and sons separately. Genomic predictions for genotyped bulls and cows (mostly calves) were distributed in April and July 2008 to owners and to organizations that paid for genotyping. The availability of high-accuracy estimates of genetic merit at an early age in an animal’s life allows more accurate decisions when selecting parents of the next generation as well as increases genetic gains by shortening generation intervals. The evaluations will be used for breeding decisions that affect milk production of future generations of dairy animals and thus future efficiency of the national dairy herd and future prices of dairy products. This accomplishment addressed National Program 101 (Food Animal Production), Component I (Understanding, Improving, and Effectively Using Animal Genetic and Genomic Resources), Problem Statements b (Identify Functional Genes and Their Interactions) and d (Develop and Implement Genome-Enabled Genetic Improvement Programs).
5.Significant Activities that Support Special Target Populations
|Number of the New MTAs (providing only)||4|
|Number of Web Sites Managed||1|
|Number of Non-Peer Reviewed Presentations and Proceedings||2|
|Number of Newspaper Articles and Other Presentations for Non-Science Audiences||1|
Appuhamy, J., Cassell, B.G., Dechow, C.D., Cole, J.B. 2007. Phenotypic Relationships of Common Health Disorders in Dairy Cows to Lactation Persistency Estimated from Daily Milk Weights. Journal of Dairy Science. 90(9):4424-4434.
Bohmanova, J., Misztal, I., Tsuruta, S., Norman, H.D., Lawlor, T.J. 2008. Short Communication: Genotype by Environment Interaction Due to Heat Stress. Journal of Dairy Science. 91(2):840-846.
Dechow, C.D., Norman, H.D., Zwald, N.R., Cowan, C.M., Meland, O.M. 2008. Relationship between individual herd-heritability estimates and sire misidentification rate. Journal of Dairy Science. 91(4):1640-1647.
Dechow, C.D., Norman, H.D., Pelensky, C.A. 2008. Short Communication: Variance estimates among herds stratified by individual herd heritability. Journal of Dairy Science. 91(4):1648-1651.
Kuhn, M.T., Hutchison, J.L. 2008. Prediction of dairy bull fertility from field data: Use of multiple services and identification and utilization of factors affecting bull fertility. Journal of Dairy Science. 91(6):2481-2492.
Kuhn, M.T., Hutchison, J.L., Norman, H.D. 2008. Modeling Nuisance Variables for Prediction of Service Sire Fertility. Journal of Dairy Science. 91(7):2823-2835.
Powell, R.L., Sanders, A.H., Norman, H.D. 2008. Investigation of country bias in international genetic evaluations using full-brother information. Journal of Dairy Science. 91(7):2885-2892.
Wiggans, G.R., Cole, J.B., Thornton, L.L. 2008. Multiparity Evaluation of Calving Ease and Stillbirth with Separate Genetic Effects by Parity. Journal of Dairy Science. 91(8):3173-3178.
Mark, T., Fikse, W.F., Sullivan, P.G., Van Raden, P.M. 2007. Prediction of Correlations and International Breeding Values for Missing Traits. Journal of Dairy Science. 90(10):4805-4813.