1. H. Duane Norman Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD duane.norman@ars.usda.gov California Dairy Herd Improvement Association (1) 2008 Sire Fertility & Genomics

2. H.D. Norman 2008 California Dairy Herd Improvement Association (2) Service-sire fertility – history l Estimated relative conception rate (ERCR) w 70-day nonreturn rate (NRR) w Source: − Dairy Records Management Systems, 1986−2005 − USDA, 2006−2008 l Western Bull Fertility Analysis w 75-d confirmed conception rate (CR) w Source: AgriTech Analytics, 2003−present

3. H.D. Norman 2008 California Dairy Herd Improvement Association (3) Sire conception rate (SCR) l New USDA fertility evaluation w Initiated Aug. 2008 l Based on confirmed Conception Rate l Why is SCR most accurate? w Inseminations from ~ 80% of DHI herds in US w Most services (not just first) w More effects accounted for

4. H.D. Norman 2008 California Dairy Herd Improvement Association (4) Data included l Only AI inseminations with confirmed pregnancy l Service numbers 1–7 for cows in lactations 1–5 l Inseminations between 30 and 365 days in milk l Minimum standardized (ME) milk yield w >10,000 lb for Holsteins w >8,000 lb for Brown Swiss w >6,000 lb for all other breeds

5. H.D. Norman 2008 California Dairy Herd Improvement Association (5) Data included (cont.) l Most recent 4 yr. of inseminations l The 6 traditional dairy breeds w Ayrshire w Brown Swiss w Guernsey w Holstein w Jersey w Milking Shorthorn

6. H.D. Norman 2008 California Dairy Herd Improvement Association (6) Data excluded l Embryo-transfer donors l Services with sexed semen l Heifer services l If services within 10 d of each other, only the later of the 2 used

7. H.D. Norman 2008 California Dairy Herd Improvement Association (7) Data excluded (cont.) l Herd with ≥50% of milking cows without recorded breeding l Herd with average CR 90% l Service sire <0.8 yr old l Services just prior to submission deadline (<70 d)

8. H.D. Norman 2008 California Dairy Herd Improvement Association (8) Data sources l 3 dairy records processing centers contributed >99% of data w AgriTech Analytics: California w AgSource Cooperative Service: Wisconsin w Dairy Records Management Systems: North Carolina l 46 States and Puerto Rico

9. H.D. Norman 2008 California Dairy Herd Improvement Association (9) Development of SCR l 4-year research effort prior to implementation – primarily by Dr. Melvin Kuhn l Bull variables (expanded service-sire effects) l Cow variables (nuisance variables)

10. H.D. Norman 2008 California Dairy Herd Improvement Association (10) Bull variables l Inbreeding coefficient of: w Service sire w Embryo l Bull age l Combined AI organization x mating year l Bull

11. H.D. Norman 2008 California Dairy Herd Improvement Association (11) Cow variables l Combined herd, mating year, cow parity, and cow registry status l Combined mating month, year, and State l Cow parity l Service number l Short interval between matings l Cow age l Cow standardized milk yield l Cow’s permanent environment l Cow’s genetics

12. H.D. Norman 2008 California Dairy Herd Improvement Association (12) SCR model Hoard’s Dairyman “The most complex model that I know of to evaluate animal performance” — Bennet Cassell, VPISU, 2008

13. H.D. Norman 2008 California Dairy Herd Improvement Association (13) Accuracy of SCR l Reliability (Rel.) = n/(n + 260) w n = number of inseminations w Constant 260 was needed based of variance components estimated for this model l Confidence interval (CI) = w 0.02313 = true standard deviation w 1.282 =standard normal variate from normal distribution for an 80% CI

14. H.D. Norman 2008 California Dairy Herd Improvement Association (14) Relationship of Rel. and 80% CI InseminationsRel. (%)80% CI 200 43± 2.2 300 54± 2.0 500 66± 1.7 1,000 79± 1.3 2,000 88± 1.0 5,000 95± 0.7 10,000 97± 0.5 15,000 98± 0.4 20,000 99± 0.3

15. H.D. Norman 2008 California Dairy Herd Improvement Association (15) SCR published l Released 3 times a year with USDA genetic evaluation runs w January w April w August l Eligible AI bulls w Active AI w Progeny test

16. H.D. Norman 2008 California Dairy Herd Improvement Association (16) SCR published (cont.) l Overall matings w Holstein≥300 in ≥10 herds w Ayrshire, Brown Swiss, ≥200 in ≥5 herds Guernsey, Jersey l Matings during current 12 mo w Holsteins, Jersey≥100 w Ayrshires, Brown Swiss,≥30 Guernsey

17. H.D. Norman 2008 California Dairy Herd Improvement Association (17) Interpretation of SCR l Predictor of bull fertility w Indicates Conception Rate w Reported as a percentage l Average bulls SCR is 0.0% l Standard deviation for SCR is 2.4%, 2/3 of bulls between -2.4% and +2.4%

18. H.D. Norman 2008 California Dairy Herd Improvement Association (18) Examples l Bull with SCR of +3.0% should provide a 3% higher CR than an average bull (SCR of 0.0), and 6% higher CR than a bull with SCR of −3.0% l Bull with SCR of +3.0% expected to provide a CR of 33% in herd that has been averaging 30% and has been using “average” fertility bulls

19. H.D. Norman 2008 California Dairy Herd Improvement Association (19) Herd & service sire fertility l Relationship between fertility of herd and bull SCR when examined together l Herd-years stratified into 3 equally sized groups by CR w ≤27.3% Low fertility w 27.4 to 33.9% Medium fertility w ≥34.0% High fertility l Bulls stratified into 3 equally sized groups by SCR w ≤−0.9% Low fertility w −0.8 to +1.0% Medium fertility w ≥+1.1%High fertility

20. H.D. Norman 2008 California Dairy Herd Improvement Association (20) Herd CR (August 2008) Service-sire fertility Herd fertility LowMediumHigh Low20.327.435.3 Medium22.630.038.7 High24.832.441.4 Difference 4.5 5.0 6.1

21. H.D. Norman 2008 California Dairy Herd Improvement Association (21) Conclusions l SCR more accurate because it uses more inseminations w More DHI herds w Extra services (2–7) w More complete model

22. H. Duane Norman Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD duane.norman@ars.usda.gov California Dairy Herd Improvement Association (22) 2008 Genomics, genomics, genomics You 9 What?

23. H.D. Norman 2008 California Dairy Herd Improvement Association (23) Genomic evaluations – history l Illumina BovineSNP50 BeadChip developed (December 2007) l Unofficial genomic evaluations for Holsteins initiated (April 2008); computed every 2 mo. w Owner letters and computer files distributed by AIPL l Unofficial genomic evaluations for Jerseys (Oct. 2008)

24. H.D. Norman 2008 California Dairy Herd Improvement Association (24) Genomic eval. – history (cont.) l Brown Swiss genomics tested; negotiations started to exchange Brown Swiss genotypes with Switzerland (Oct. 2008) l Unofficial genomic evaluations for Brown Swiss (Dec. 2008) l Over 22,000 animals genotyped (Feb. 2009) l Genomic evaluations become official (Jan. 2009) w Owner letters and computer files distributed by breed associations and NAAB

25. H.D. Norman 2008 California Dairy Herd Improvement Association (25) Genomic evaluations: what’s it about? l DNA extracted from blood, hair, or semen l ~40,000 genetic markers (SNPs) tested simultaneously (about 1/2 cent per test) l Value of each SNP determined by examining how each SNP impacts “tested animal” performance l The payoff is to genotype young animals and apply the prediction equations l Genomic evaluation combines SNP effects with traditional PA or PTA

26. H.D. Norman 2008 California Dairy Herd Improvement Association (26) Genomic vs. traditional PTA l Genotype is additional source of information (like parents, progeny, and animal records) l For each animal, the genomic test is used to calculate genomic evaluations for all 29 traits l Genomic evaluation interpreted the same as traditional PTA l Expected to increase genetic improvement by 50% with decreased generation interval. Also, genomics contributes ~15 daughter equivalents to a bull

27. H.D. Norman 2008 California Dairy Herd Improvement Association (27) Genomic evaluations – Jan. 2009 l Genomic evaluations became official l Genotyped ancestors contribute their evaluations to descendents, not the reverse l Evaluations of all genotyped females are public l Evaluations of genotyped males either enrolled with NAAB or ≥24 mo. are public l Young-bull genomic evaluations may be shared among AI organizations or disclosed by owner

28. H.D. Norman 2008 California Dairy Herd Improvement Association (28) Genomic eval. – producer impact l Young-bull genomic evaluations have accuracy approaching 1st-crop daughter evaluations (60-70% Reliability) l AI organizations have started marketing genomically evaluated 2-year-old bulls l AI organizations are requiring genotypes on potential bull dams l Progeny-test programs are changing

29. H.D. Norman 2008 California Dairy Herd Improvement Association (29) Genomic evaluations – schedule l Genomic evaluations provided at each of the 3 annual traditional genetic runs: January, April, and August l Genomic evaluations on new bulls provided once or twice between traditional runs w We re-estimate SNP predictors when large numbers of predictor animals added

30. H.D. Norman 2008 California Dairy Herd Improvement Association (30) Genomic eval. – increase accuracy? l Genotyping more predictor bulls (most active-AI bulls expected to be genotyped soon) l Should reach 1,500 Brown Swiss through foreign collaboration l Aggressive genotyped in domestic Jerseys underway, foreign collaboration is likely l Investigate across-breed analysis to see if Holstein data helps accuracy for Jerseys and Brown Swiss

31. H.D. Norman 2008 California Dairy Herd Improvement Association (31) How animals get genotyped l Participating AI organizations have 5-year exclusive right to evaluate bulls genomically l Each AI organization genotypes 1st-choice flushes, thus avoiding duplicate genotyping l Web-based system being developed to show activity w Should help avoid expensive duplication l Breed associations developing cow genotyping service

32. H.D. Norman 2008 California Dairy Herd Improvement Association (32) On horizon: Low-cost genotyping l Developing a new genomic test, inexpensive enough to use for most animals l 384 SNPs proposed for new genomic test l Will provide parentage verification/discovery l Will provides a genetic estimate accurate enough for 1st-stage screening

33. H.D. Norman 2008 California Dairy Herd Improvement Association (33) Implications for dairy industry l Rapid acceptance and use of genomic evaluations l Young-bull acquisition and marketing now based on genomic evaluations l Diversity of bull dams needs considered l Industry groups taking responsibility for genotyping and validation

34. H.D. Norman 2008 California Dairy Herd Improvement Association (34) International implications l All major dairy countries reviewing genomic l Interbull discussing how genomic evaluations should be integrated l Balance needed between treating genotypes as proprietary versus open sharing l Some importing countries might change rules to allow young genomic-tested bull use

35. H. Duane Norman Animal Improvement Programs Laboratory Agricultural Research Service, USDA, Beltsville, MD duane.norman@ars.usda.gov California Dairy Herd Improvement Association (35) 2008 Fertility & genomics Over- load !