2011 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.
Five new lethal recessive defects causing embryo loss were discovered from the absence of homozygous haplotypes in genomic data. Genotypes from a 2,900 (3K) marker panel were included as a data source for genomic evaluations, and evaluations for animals with 3K genotypes became official in December 2010. Multiple marker sets were included in the same evaluation by imputing all genotypes to the highest density. Accuracy of imputation was improved by correcting the locations of several markers on the bovine map using information provided by collaborators at the Universities of Maryland, Missouri, and Guelph. A new version of the computer program for haplotyping and imputation was developed and used to increase the proportion of correctly imputed genotypes. Holstein and Jersey genomic reliabilities were discounted further below theoretical reliabilities to match observed reliabilities from the most recent genomic validation; Brown Swiss reliabilities were not discounted further because published and observed reliabilities from the validation study were similar. Genomic relationships, pedigree relationships, and predictions of breed composition were compared for 3 breeds. Approximate multitrait methods were used to add missing genetics evaluations for heifer and cow conception rates rather than use parent averages, which are less accurate. The adjustment of yield trait evaluations of cows to match properties of bull evaluations was applied for all cows rather than just genotyped animals. Other research included:.
1)genomic imputation and evaluation using high-density Holstein genotypes;.
2)investigation of the impact of including foreign data in genomic evaluations of dairy cattle;.
3)documentation of changes in the use of young bulls;.
4)determination of consequences for U.S. Dairy Herd Improvement herds of changing national standards for somatic cell count;.
5)investigation of cow culling to help meet compliance for somatic cell standards;.
6)determination of association of high and low parent average with daughter performance for yield, somatic cell score, and productive life in individual herds;.
7)estimation of heritability of rectal temperature and genetic correlations with production and reproduction traits in dairy cattle;.
8)investigation of effects of dam's dry period length on heifer development;.
9)determination of prevalence, transmission and impact of bovine leukosis in Michigan dairies; 10) verification of factors to estimate daily milk yield from one milking of cows milked twice daily; 11) determination of opportunities for improving milk production efficiency in dairy cattle; and 12) visualization of data structure.
Official national genomic evaluations for dairy cattle with genotypes based on a low-density marker panel. Because of recent availability of a low-density marker panel at a low cost, the number of animals with genomic information has increased greatly, which provided an opportunity to improve accuracy of genetic evaluations. Methods developed last year to combine genomic information from low-density genotypes with previous higher density information were implemented for national genetic evaluations of yield and fitness traits of Holsteins, Jerseys, and Brown Swiss and made official in December 2010. The availability of genomic evaluations for animals with low-density genotypes has increased the accuracy of their estimated genetic merit compared with their traditional evaluations. For young animals with low-density genotypes, gain in accuracy over parent average was about 80% of the gain realized with higher density genotypes. Low-density genotypes also provide a low cost alternative to traditional parentage verification.
Impact of changing national standards for somatic cell count in milk. Consideration of changes for U.S. standards for bulk-tank somatic cell count are underway because of a European Union announcement that its standards will be enforced for any herds supplying imports. For herds participating in Dairy Herd Improvement testing or shipping milk to four Federal Milk Orders, noncompliance was determined to be 0.9 and 1.0%, respectively, based on U.S. standards of 750,000 cells/mL and 7.8 and 16.1% for European Union standards at 400,000 cells/mL. With no change in herd management, proposed changes in U.S. standards would increase noncompliance in Dairy Herd Improvement and Milk Order herds up to 14.1 and 23.3%, respectively. Because the alternative standards being considered are substantially more stringent than the current U.S. standard, U.S. producers will need to place more emphasis on preventing and combating mastitis and doing more directed culling to improve milk quality.
Comparison of genomic inbreeding and relationships of dairy cattle with pedigree measures. Pedigree relationships were the foundation of animal breeding and genetic selection, but genomic relationships are replacing pedigree relationships in many national evaluation systems. Methods to combine genomic and pedigree relationships among Holsteins, Jerseys, and Brown Swiss were compared by estimating adjustments for averages and regressions of genomic on pedigree relationships. Adjustments for base population allele frequencies and adjustments to make pedigree relationships match genomic relationships more closely in multibreed populations were also determined. Results showed that genomic inbreeding accurately detected pedigree inbreeding and that breed identity can be determined more accurately using all markers than marker subsets. The results provide a basis for future multibreed genomic evaluations.
Adjustment of genetic evaluations of cows to improve accuracy of genomic predictions. Upward bias in traditional evaluations of cows with high genetic merit was adversely affecting accuracy of genomic predictions when those cows were added to the reference population for estimating marker effects. Initially, only evaluations of genotyped cows were adjusted to have the same average and variance as bulls. However, evaluations of genotyped cows then were not comparable to those of nongenotyped cows. Later the method was revised and extended to all cows so that genotyped and nongenotyped cows could be compared more fairly. The efficiency of selection programs will improve because cows will be ranked more accurately, which will benefit breeding organizations and dairy producers.
Five new lethal recessive defects that reduce dairy cow fertility. Lethal recessive defects that cause embryo loss are difficult to detect without genomic data even with very large sets of phenotypic and pedigree data because of too few observations per estimated mating interaction. Based on genomic testing, a method was developed to discover lethal defects by detecting the absence of haplotypes (a set of single nucleotide polymorphisms associated on a single chromosome) that had high population frequency but were never homozygous. Haplotype testing revealed that effect on sire conception rate for those 5 new (3 in Holsteins, 1 in Jerseys, and 1 in Brown Swiss) as well as 2 previously known defects were negative and consistent with a lethal recessive. Once animals have been genotyped, dairy farmers could avoid mating carrier animals without further testing expense using the new haplotype test, thereby saving time, increasing profitability, and reducing those defects in the population.
Wiggans, G.R., Gengler, N. 2011. Selection: Evaluation and methods. In: Fuquay, J.W, Fox, P.F., and McSweeney, P.L.H., editors. Encyclopedia of Dairy Sciences. 2nd edition. San Diego, CA: Academic Press. p. 649-655.
Norman, H.D., Hubbard, S.M., Van Raden, P.M. 2010. Dairy Cattle: Breeding and genetics. Encyclopedia of Animal Science, 2nd edition. Pond, W.G., and Bell, A.W. (editors). Taylor and Francis, New York, NY. pp. 262-265.
Norman, H.D., Wright, J.R., Miller, R.H. 2011. Potential consequences of selection on gestation length on Holstein performance. Journal of Dairy Science. 94(2):1005-1010.
Van Raden, P.M., O'Connell, J.R., Wiggans, G.R., Weigel, K.A. 2011. Genomic evaluations with many more genotypes. Genetic Selection Evolution. 43:10.
Cole, J.B., Null, D.J., De Vries, A. 2011. Short communication: Best prediction of 305-day lactation yields with regional and seasonal effects. Journal of Dairy Science. 94(3):1601-1604.
Olson, K.M., Van Raden, P.M., Tooker, M.E., Cooper, T.A. 2011. Differences among methods to validate genomic evaluations for dairy cattle. Journal of Dairy Science. 94(5):2613-2620.
Aguilar, I., Misztal, I., Tsuruta, S., Wiggans, G.R., Lawlor, T.J. 2011. Multiple trait genomic evaluation of conception rate in Holsteins. Journal of Dairy Science. 94(5):2621-2624.
Cole, J.B., Van Raden, P.M. 2011. Use of Haplotypes to Estimate Mendelian Sampling Effects and Selection Limits. Journal of Animal Breeding and Genetics. 128(6):446-455.