Genetic trends in dairy cattle over the next 25 years … where are we headed and how

1. Genetic trends in dairy cattle over the next 25 years … where are we headed and how will we get there

2. National Dairy Genetic Evaluation Program PDCA DHI NAAB AIPL CDCB Universities AIPL Animal Improvement Programs Lab., USDA CDCB Council on Dairy Cattle Breeding DHI Dairy Herd Improvement (milk recording organizations) NAAB National Association of Animal Breeders (AI) PDCA Purebred Dairy Cattle Association (breed registries)

3. DHI statistics (2007) • 4.4 million cows • 98% fat recorded • 95% protein recorded • 94% somatic cell count recorded • 23,500 herds • 184 cows per herd • 23,560 pounds milk per cow • 3.69% fat • 3.09% (true) protein

4. Traits evaluated • Yield (milk, fat, protein volume; component percentages) • Type/conformation • Productive life/longevity • Somatic cell score (SCS)/mastitis resistance • Fertility • Daughter pregnancy rate (DPR; cow) • Estimated relative conception rate (bull) • Calving ease/dystocia (service sire, daughter)

5. Evaluation methods • Animal model (linear)Heritability • Yield (milk, fat, protein) 25–40% • Type (Ayrshire, Brown Swiss, 7–54% Guernsey, Jersey) • Productive life 8.5% • SCS 12% • DPR 4% • Sire-maternal grandsire model(threshold) • Service sire calving ease 8.6% • Daughter calving ease 3.6%

6. Dairy cattle breeding • Long generation interval – 5 years • High value of individuals – $2,000 per cow • Intensive management – milking 2–3 times per day • Bull semen suitable for dilution – 500 doses per collection day)

7. U.S. progeny-test bulls (2006) • Major and marketing-only AI organizations plus breeder proven • Breeds • Ayrshire – 13 • Brown Swiss – 30 • Guernsey – 12 • Holstein – 1,493 • Jersey – 151 • Milking Shorthorn – 8 • 260 new bulls returned to service per year

8. Genetic-economic indexes

9. Index changes

10. International reach • Semen and embryos marketed internationally • Interbull Evaluation Centre (Sweden) ranks all bulls for each participating country • Correlations between countries of <1 accommodated • Some foreign bulls used as sires of sons • U.S. and Canadian semen used widely in South America • Red breeds more popular in Europe than in North America

11. PTA milk prediction

12. Net merit prediction

13. PTA DPR prediction (curvilinear)

14. PTA DPR prediction (linear)

15. Holstein milk yield

16. Goals beyond increased yield • Improve fertility • Increase herdlife • Improve disease resistance • Reduce calving difficulty • Improve efficiency

17. Options for increasing progress • Crossbreeding • Increased selection intensity • Adoption of new technologies

18. Crossbreds • Increasing interest • Way to increase fertility • Scandinavian Red breeds proposed • Hybrid vigor observed

19. All-breed animal model • Purebreds and crossbreds together • Unknown parents grouped by breed • Variance adjustments by breed • Age adjusted to 36 months, not maturity

20. Genomics • Genotype calves • Calculate genomic evaluation • Select intensively • Reduce cost of finding top bulls • Increase rate of genetic progress

21. Getting started • Select animals to genotype • Assign identification to animals • Collect tissue samples • Extract DNA • Check DNA quality and standardize concentration • Begin 3-day genotyping process

22. Genomic evaluation workflow • Check genotypes for inheritance errors • Calculate genomic relationships • Infer missing genotypes • Estimate single-nucleotide polymorphism (SNP) effects

23. Evaluation workflow–cont. • Combine genomic information with parent average • Based on gain from genomics over parent average for animals with genotypes • Apply to all traits • Distribute results

24. First genomic evaluation • 750 animals nominated for genotyping • Over 5,285 predictor bulls from United States and Canada • Embryo flushes • AI organization that arranged for genotyping have first choice • More information at http://aipl.arsusda.gov/reference/changes/eval0804.html

25. Reliabilities and squared correlations

26. Marker effects for net merit

27. SNP density comparison

28. Conclusions • Genomic predictions significantly better than parent average (P < .0001) for all 26 traits tested • Gains in reliability equivalent on average to 11 daughters with records • Analysis used 3,576 historical bulls • Current data includes 5,285 proven bulls • Larger populations require more SNPs

29. Current status • Field test results distributed for 750 nominated animals • Extension to Jersey and Brown Swiss in progress • Transition to commercial genotyping labs • Extension to cows planned for June

30. SNP project outcomes • Genome-wide selection • Parentage verification and traceability panels • Enhanced mapping for quantitative trait loci and gene discovery

31. Future plans • Evaluations of animals not genotyped updated using genomic information (3 times per year) • Genomic evaluations calculated and released more frequently (monthly? weekly?) • Bull evaluations made public when bull enrolled with NAAB • Cow evaluations made public immediately at USDA web site • January 2009 target for public release

32. Genomic selection (New Zealand) • Identify top 30,000 bull calves annually based on parent average • Genotype by 6 days old with 768 SNP • Genotype top 500 bull calves with 50K SNP chip • Keep top 100 bull calves

33. Genomic selection (NZ)–cont. • At 1 year, limited progeny test to check for undesirable recessives • At 2 years, market as part of DNA team • When progeny tested, graduate best to progeny-proven team

34. Research topics • Differential inclusion of X-chromosome effects to predict bulls versus cows • Contribution of cows to accuracy of genomic prediction • Benefit of genotyping more predictor bulls • Optimum methods for combining genomic and current evaluation

35. Research topics–cont. • Practicality of screening and parentage verification with low-cost, low-SNP number assay • Potential of freely sharing enough SNP for accurate parentage discovery • Computational methods to improve accuracy, such as haplotyping

36. Summary • Genomic prediction has great promise • Extensive changes in bull acquisition and marketing and in cow selection expected • Routine genotyping and validation will become industry rather than research responsibilities

37. Where do we go from here • Economic indexes adjusted as conditions change • Traits added as their collection becomes feasible and value demonstrated • Dairies increase in size and technological sophistication • Selection adapts the cow to meet human needs

38. Senior research staff