Genetic Evaluation of Calving Traits in US Holsteins

1. Genetic Evaluation of Calving Traits in US Holsteins

2. Introduction • A national evaluation was implemented for calving ease (CE) in August 2002 and for stillbirth (SB) for Holstein in August 2006. • A calving ability index (CA$) which includes SB and calving ease (CE) was developed. • Some challenges with the CE and SB evaluations remain

3. Calving Ease Definition • Reported on a five-point scale: 1 = No problem 2 = Slight problem 3 = Needed assistance 4 = Considerable force 5 = Extreme difficulty • Scores of 4 and 5 are combined

4. Stillbirth Definition • Reported on a three-point scale: • Scores of 2 and 3 are combined

5. 0 1 2 3 Total 1 1,287,290 4,343,140 158,250 20,418 5,809,098 2 203,738 482,720 49,858 2,537 738,853 3 183,951 375,203 70,522 3,353 633,029 4 59,614 108,037 37,851 1,740 207,242 5 23,690 38,929 32,196 1,272 96,087 Total 1,758,283 5,348,029 348,677 29,320 7,484,309 Distribution of Stillbirth and Calving Ease Scores Stillbirth Score Calving Ease Score

6. Stillbirth Records by Lactation

7. Detecting Stillbirth Data Errors

8. Data and Edits • 7 million SB records were available for Holstein cows calving since 1980 • Herds needed ≥10 calving records with SB scores of 2 or 3 for inclusion • Herd-years were required to include ≥20 records • Only single births were used (no twins)

9. Sire-MGS Threshold Model • Implemented for calving ease (Aug 2002) and stillbirth (Aug 2006) • Sire effects allow for corrective matings in heifers to avoid large calves • MGS effects control against selection for small animals which would have difficulty calving

10. Genetic Evaluation Model • A sire-maternal grandsire (MGS) threshold model was used: • Fixed: year-season, parity-sex, sire and MGS birth year • Random: herd-year, sire, MGS • (Co)variance components were estimated by Gibbs sampling • Heritabilities are 3.0% (direct) and 6.5% (MGS)

11. Trait Definition • PTA are expressed as the expected percentage of stillbirths • Direct SB measures the effect of the calf itself • Maternal SB measures the effect of a particular cow (daughter) • A base of 8% was used for both traits: • Direct: bulls born 1996–2000 • Maternal: bulls born 1991–1995

12. Phenotypic Trend for Stillbirths

13. Genetic Trend for Stillbirths

14. Distribution of PTA

15. Distribution of Reliabilities

16. Dystocia and Stillbirth • Meyer et al. (2001) make a strong argument for the inclusion of dystocia in models for SB • Difficulty of interpretation - formidable educational challenge • Interbull trait harmonization - none of the March 2006 test run participants included dystocia in their models • Changes in sire and MGS solutions on the underlying scale between models were small

17. Evaluation Conclusions • Reliabilities for SB averaged 45% versus 60% for CE • Phenotypic and genetic trends from 1980 to 2005 were both small • An industry-wide effort is underway to improve recording of calf livability

18. Index Data • 7 million SB records were available for Holstein cows calving since 1980 • Calvings with unknown MGS were eliminated for VCE • Records with sire and MGS among the 2,600 most-frequently appearing bulls were selected

19. Data (cont’d) • Herds needed ≥10 calving records with SB scores of 2 or 3 in the database to be included • Herd-years were required to include ≥20 records and only single births were used • Inclusion of all records for a cow was not guaranteed • The final dataset included 2,083,979 calving records from 5,765 herds and 33,304 herd-years

20. Sampling • Six datasets of ~250,000 records each were created by randomly sampling herd codes without replacement • Datasets ranged from 239,192 to 286,794 observations, and all averaged 7% stillbirths • A common pedigree file was used to facilitate comparisons between sire and MGS solutions

21. Bayesian (co)variance components estimates

22. Heritabilities • Calving Ease (Direct) 8.6% • Calving Ease (MGS) 3.6% • Stillbirth (Direct) 3.0% • Stillbirth (MGS) 6.5%

23. Genetic Correlations Among SB and CE

24. Economic Assumptions • Newborn calf value • Expenses per difficult birth (CE ≥4)

25. Calving Ability Index • CA$ has a genetic correlation of 0.85 with the combined direct and maternal CE values in 2003 NM$ and 0.77 with maternal CE in TPI • Calving traits receive 6% of the total emphasis in NM$ (August 2006 revision)

26. Breeds Other Than Holstein • Brown Swiss economic values are −6 for SCE and −8 for DCE • Separate SB evaluations are not available • CE values include the correlated response in SB • Other breeds will be assigned CA$ of 0

27. Calving Ease Genetic CorrelationsService sire above diagonal, daughter below

28. Stillbirth Genetic CorrelationsService sire above diagonal, daughter below

29. Brown Swiss Calving Ease Service sire correlations above diagonal, daughter below

30. Index Conclusions • A routine evaluation for stillbirth in US Holsteins was implemented in August 2006 • Direct and maternal stillbirth were included in NM$ for Holsteins starting in August 2006 • August 2006 data were included in the September 2006 Interbull test run • The US will participate in routine Interbull evaluations beginning in November 2006

31. Recent Calving Ease Research

32. Abnormal Herd-Years • Many herd-years have abnormal distributions of scores • Two recent approaches to problem • Eliminate HY based on GoF tests • Collapse categories when mode > 1 • Both strategies improve prediction of later evaluations by earlier

33. An Illustration • Herds with unusual distributions of data affect evaluations of bulls • Worst case is when large share of records for a bull are in one “bad” herd • Herd reporting changes over time

34. Test Edits - c2GoF statistics • Based on multinomial distributions • Independent of herd size

35. Percentage of Score by Parity In All (AN) and GoF Excluded (AG) Herds 100 Parity 1 - AN 90 80 Parity 1 - AG 70 Parity 2 - AN 60 Counts by Herd-Parity (%) 50 Parity 2 - AG 40 30 20 10 0 1 2 3 4 5 Calving Ease Score

36. Collapse Categories • The mode for CE scores in a herd is expected to be 1, but was higher for nearly 10% of data • Data from herd-years with a mode of 4 or 5 (1.2%) were deleted • A mode of 3 is assumed to indicate that the scorer normalized the data (middle score of 3 for an 'average' birth)

37. Collapse Categories • Herds with a mode of 2 or 3: scores up to the mode were changed to 1, and scores greater than the mode were decreased accordingly • Herd-years with a mode of 3: scores 1-3 all become 1, scores of 4 are changed to 2, and scores of 5 are changed to 3 • Combining categories lowered the portion of difficult calvings and increased the impact of the subsequent goodness-of-fit test • Overall, 6.4% of data were excluded

38. Conclusions • Exclusion of herds with poor distributions improves prediction of future evaluations across birth years • Correlations across all data increased from .66 to .68 • Herds with poor score distributions were excluded uniformly across herd size • Exclusion of herds results in loss of evaluations for some bulls

39. Separate Parity Effects • First and later parities currently modelled as a single trait • cblup90iod only accepts one threshold trait • Options for bivariate analysis • Gibbs sampling (thrgibbs1) • Linearization (airemlf90) • RR on parity (cblup90iod)

40. Results • RR on a 0-1 parity effect does not account for heterogeneous variances • GS and AIREML solutions were similar • GS required more processing time than is desirable for routine national evaluations • The impact of the approximation necessary to linearize the scores is not known • Implementation of a bivariate analysis is desirable, but challenging

41. Acknowledgments • Jeff Berger, Iowa State University • John Clay, Dairy Records Management Systems • Ignacy Misztal and Shogo Tsuruta, University of Georgia • National Association of Animal Breeders