1. 2007 Paul VanRaden, George Wiggans, Jeff O’Connell, John Cole, Animal Improvement Programs Laboratory Tad Sonstegard, and Curt Van Tassell Bovine Functional Genomics Laboratory USDA Agricultural Research Service, Beltsville, MD, USA Paul.VanRaden@ars.usda.gov Paul.VanRaden@ars.usda.gov 2009 Use of Genomics for Selecting Sires

2. Select Sires conference, March 2009 (2)Paul VanRaden 2009 Genomic Methods  Direct genomic evaluation Sum of effects for 38,416 genetic markers Not published  Combined genomic evaluation Include phenotypes of non-genotyped ancestors Selection index includes 3 PTAs per animal Traditional, direct genomic, and subset PTA  Transferred genomic evaluation Propagate from genotyped animals to non- genotyped descendants by selection index Propagation to ancestors being developed

3. Select Sires conference, March 2009 (3)Paul VanRaden 2009 January Evaluation  HO, JE genomic PTAs official in Jan. Genomic from Dec 1, domestic Dec 18 Traditional PTAs sent to Interbull MACE used if foreign daughters included Genomic PTA used for most bulls (80%) Traditional used if many new daughters Genomic PTA transferred to descendants (to ancestors in future)  Brown Swiss not yet official

4. Select Sires conference, March 2009 (4)Paul VanRaden 2009 February Evaluation  Official only for new genotypes Animals genotyped during Dec and Jan Active bulls not updated officially Unofficial PTAs provided in March for proven bulls  March evaluation Added 96 bulls accidentally left out of Feb Tested fast reliability approximation  Brown Swiss now have >800 genotyped Traded with Switzerland in March 2009

5. Select Sires conference, March 2009 (5)Paul VanRaden 2009 April Evaluation (Plans)  Genomic PTAs all official Compute domestic, then genomic Redo last step after MACE arrives:  Selection index recalculation Replace previous with current MACE SNP effects and subset PTA same Similar to young bull calving ease Suggested by CDN researchers

6. Select Sires conference, March 2009 (6)Paul VanRaden 2009 August Evaluation (Plans)  Interbull converts genomic PTAs Young bulls only Proven bulls next year (2010) AIPL must compute domestic and genomic earlier to meet deadline  Decrease yield heritability to make PAs and cow PTAs less biased

7. Select Sires conference, March 2009 (7)Paul VanRaden 2009 Genomic Tested Bulls Available Jan 2009 Age (yrs)ReliabilityNet Merit Freddie469918 Al167914 Russell165854 Alan168841 O-Man1099778

8. Select Sires conference, March 2009 (8)Paul VanRaden 2009 Net Merit of Top 20 Bulls from 2009 data based on selection in 2004 BullsSelectionNet Merit young Parent average $395 Genomic$516 proven Traditional$381 Genomic$463

9. Select Sires conference, March 2009 (9)Paul VanRaden 2009 Changes in Net Merit means for top 20 bulls (2009 – 2004) BullsSelectionChange young Parent average -$278 Genomic-$130 proven Traditional-$96 Genomic-$30

10. Select Sires conference, March 2009 (10)Paul VanRaden 2009 Average regressions across all traits Predict 2009 from 2004 data, expected = 1.00 BullsSelectionRegression young Parent average 0.85 Genomic0.92 proven Traditional1.03 Genomic1.05

11. Select Sires conference, March 2009 (11)Paul VanRaden 2009 Net Merit regressions Predict 2009 from 2004 data, expected = 1.00 BullsSelectionRegression young Parent average 0.63 Genomic0.74 proven Traditional0.91 Genomic1.10

12. Select Sires conference, March 2009 (12)Paul VanRaden 2009 Genomic vs. traditional – protein PTA

13. Select Sires conference, March 2009 (13)Paul VanRaden 2009 Genomic vs. traditional – net merit

14. Select Sires conference, March 2009 (14)Paul VanRaden 2009 Genomic vs. trad. – protein reliability

15. Select Sires conference, March 2009 (15)Paul VanRaden 2009 Genomic vs. trad. – net merit reliability

16. Select Sires conference, March 2009 (16)Paul VanRaden 2009 Expected Change in Net Merit  SD = 163 * √(REL G – REL T ) = $91 for young bulls (.66 -.35) = $33 for proven bulls (.88 -.84)  Daughter equivalents for NM$ 10 from parent average 25 from genomics 35 total for young animals

17. Select Sires conference, March 2009 (17)Paul VanRaden 2009 Net Merit by Chromosome Freddie - highest Net Merit bull

18. Select Sires conference, March 2009 (18)Paul VanRaden 2009 Net Merit by Chromosome O Man – Sire of Freddie

19. Select Sires conference, March 2009 (19)Paul VanRaden 2009 Net Merit by Chromosome Die-Hard - maternal grandsire

20. Select Sires conference, March 2009 (20)Paul VanRaden 2009 Net Merit by Chromosome Planet – high Net Merit bull

21. Select Sires conference, March 2009 (21)Paul VanRaden 2009 Adoption of Genomic Testing US young bulls purchased by AI companies Birth Year Bulls Sampled Bulls Tested Genomic Tested % 2008*19316686 2007*145589662 2006165771743 2005164281850 2004163874245 * 2007-2008 counts are incomplete

22. Select Sires conference, March 2009 (22)Paul VanRaden 2009 Genetic Progress  Assume 60% REL for net merit Sires mostly 1-3 instead of 6 years old Dams of sons mostly heifers with 60% REL instead of cows with phenotype and genotype (66% REL)  Progress could increase by >50% 0.37 vs. 0.23 genetic SD per year Reduce generation interval more than accuracy

23. Select Sires conference, March 2009 (23)Paul VanRaden 2009 Worldwide Dairy Genotyping as of January 2009 CountriesAnimals United States and Canada22,344 France8,500 Netherlands, New Zealand 1 6,000 New Zealand and Ireland4,500 Germany3,000 Australia2,000 Denmark, Finland, Sweden2,000 1 Using a customized Illumina 50K chip (different markers)

24. Select Sires conference, March 2009 (24)Paul VanRaden 2009 Foreign DNA in North American Data Proven bulls, Young bulls, and Females CtryoldyngfemCtryoldyngfem NLD2513453GBR771 DEU223164DNK550 ITA14175LUX008 AUS12300BEL310 HUN6292CHE400 FRA12192NZL400 CZE3150FIN100

25. Select Sires conference, March 2009 (25)Paul VanRaden 2009 Country Borders  Most phenotypic data collected and stored within country  Genomic data allows simple, accurate prediction across borders Need traditional EBV or PA for foreign animals, but not available for young bulls, cows, or heifers May need full foreign pedigrees Genomic evaluations official on USA scale for many foreign animals (not just CAN)

26. Select Sires conference, March 2009 (26)Paul VanRaden 2009 Simulation Results World Holstein Population  40,360 older bulls to predict 9,850 younger bulls in Interbull file  50,000 or 100,000 SNP; 5,000 QTL  Reliability vs. parent average REL Genomic REL = corr 2 (EBV, true BV) 81% vs 30% observed using 50K 83% vs 30% observed using 100K

27. Select Sires conference, March 2009 (27)Paul VanRaden 2009 International Evaluation  Traditional genetic evaluations MACE instead of merging phenotypes Small benefits expected from data merger Proven bulls only, not cows or young bulls  Parentage testing, genetic recessives, pedigrees done by breed associations  Genomics: what role for Interbull? Benefits of sharing genotypes are large

28. Select Sires conference, March 2009 (28)Paul VanRaden 2009 Genotype Exchange Options  Give away for free (not likely)  Genotype own bulls, then trade? Trade an equal number or all bulls? Country A has 5000 and B has 1000 Proportional to population size?  Trade among organization pairs or create central genomic database?  Service fee for young animals to pay for ancestor genotyping?

29. Select Sires conference, March 2009 (29)Paul VanRaden 2009 Share Young Bull, Cow Genotypes?  May be marketed in >1 country  Exchange of young animals and females more important as their REL increases with genomics  Helps to synchronize databases  Could lead to joint evaluation

30. Select Sires conference, March 2009 (30)Paul VanRaden 2009 Problems of Not Sharing  Genetic progress not as fast as with full access to genotypes  Severe limits on researcher access to genotypes (secrecy)  Genomics may lead to natural monopoly, similar to railroads Small companies / countries can’t afford to buy sufficient genotypes

31. Select Sires conference, March 2009 (31)Paul VanRaden 2009 Genomic MACE Interbull Genomics Task Force  Residuals correlated across countries Repeated tests of the same major gene, or SNP effects estimated from common bulls Let c ij = proportion of common bulls Let g i = DE gen / (DE dau + DE gen ) Corr(e i, e j ) = c ij * Corr(a i, a j ) * √(g i * g j )  Avoids double counting genomic information from multiple countries i, j  New deregression formulas needed

32. Select Sires conference, March 2009 (32)Paul VanRaden 2009 Low Density SNP Chip  Choose 384 marker subset SNP that best predict net merit Parentage markers to be shared  Use for initial screening of cows 40% benefit of full set for 10% cost Could get larger benefits using haplotyping (Habier et al., 2008)

33. Select Sires conference, March 2009 (33)Paul VanRaden 2009 Marker Effects for Net Merit

34. Select Sires conference, March 2009 (34)Paul VanRaden 2009 Genomic vs. Expected Future Inbreeding BullEFIGFI Blackstar7.9 Elevation7.67.4 Chief7.16.8 Emory7.06.9 RC Matt7.06.7 Juror7.06.7

35. Select Sires conference, March 2009 (35)Paul VanRaden 2009 Genomic vs. Pedigree Inbreeding BullPedigree FGenomic F O Man4.515.8 Ramos2.311.5 Shottle5.611.9 Planet6.718.8 Earnit6.212.8 Nifty3.111.7 Correlation =.68

36. Select Sires conference, March 2009 (36)Paul VanRaden 2009 Pedigree Relationship Matrix 1HO9167 O-Style PGSPGDMGSMGDSireDamBull Manfred 1.053.090.105.571.098.334 Jezebel.0901.037.051.099.563.075.319 Teamster.090.0511.035.120.071.578.324 Dima.105.099.1201.042.102.581.342 O-Man.571.563.071.1021.045.086.566 Deva.098.075.578.581.0861.060.573 O-Style.334.319.324.342.566.5731.043

37. Select Sires conference, March 2009 (37)Paul VanRaden 2009 Genomic Relationship Matrix 1HO9167 O-Style PGSPGDMGSMGDSireDamBull Manfred 1.201.058.050.093.609.054.344 Jezebel.0581.131.008.135.618.079.357 Teamster.050.0081.110.100.014.613.292 Dima.093.135.1001.139.131.610.401 O-Man.609.618.014.1311.166.080.626 Deva.054.079.613.610.0801.148.613 O-Style.344.357.292.401.626.6131.157

38. Select Sires conference, March 2009 (38)Paul VanRaden 2009 Difference (Genomic – Pedigree) 1HO9167 O-Style PGSPGDMGSMGDSireDamBull Manfred.149-.032-.040-.012.038-.043.010 Jezebel -.032.095-.043.036.055.004.038 Teamster -.040-.043.075-.021-.057.035-.032 Dima -.012.036-.021.097.029.059 O-Man.038.055-.057.029.121-.006.060 Deva -.043.004.035.029-.006.087.040 O-Style.010.038-.032.059.060.040.114

39. Select Sires conference, March 2009 (39)Paul VanRaden 2009 Genotyped Animals (n=22,344) In North America as of February 2009

40. Select Sires conference, March 2009 (40)Paul VanRaden 2009 Experimental Design - Update Holstein, Jersey, and Brown Swiss breeds HOLJERBSW Predictor: Bulls born <20004,4221,149225 Cows with data947212 Total5,3691,361225 Predicted: Bulls born >20002,035388118 Data from 2004 used to predict independent data from 2009

41. Select Sires conference, March 2009 (41)Paul VanRaden 2009 Reliability Gain 1 by Breed Yield traits and NM$ of young bulls TraitHOJEBS Net merit2483 Milk2660 Fat32115 Protein2421 Fat %503610 Protein %38295 1 Gain above parent average reliability ~35%

42. Select Sires conference, March 2009 (42)Paul VanRaden 2009 Reliability Gain by Breed Health and type traits of young bulls TraitHOJEBS Productive life3272 Somatic cell score23316 Dtr pregnancy rate287- Final score202- Udder depth37203 Foot angle2511- Trait average2913N/A

43. Select Sires conference, March 2009 (43)Paul VanRaden 2009 Value of Genotyping More Animals Actual and predicted gains for 27 traits and for Net Merit BullsReliability Gain PredictorPredictedNM$27 trait avg 21302611317 3576175923 442220352429 618473303130 Cows: 947 1916

44. Select Sires conference, March 2009 (44)Paul VanRaden 2009 Conclusions - 1  High accuracy requires very many genotypes and phenotypes 100X more markers allows MAS across rather than within families 5X more bulls allows estimation of much smaller QTL effects (HO)  Most traits are very quantitative (few major genes)

45. Select Sires conference, March 2009 (45)Paul VanRaden 2009 Conclusions - 2  Reliability increases by tracing actual genes inherited instead of expected average from parents  Genomic reliability > traditional 30-40% with traditional parent average 60-70% using 8,100 genotyped Holsteins 81-83% from 40,000 simulated bulls Gains smaller for USA JER and BSW breeds  Trading, sharing, profit is needed

46. Select Sires conference, March 2009 (46)Paul VanRaden 2009 Acknowledgments  Genotyping and DNA extraction: USDA Bovine Functional Genomics Lab, U. Missouri, U. Alberta, GeneSeek, Genetics & IVF Institute, Genetic Visions, and Illumina  Computing: AIPL staff (Mel Tooker, Leigh Walton, Jay Megonigal)  Funding: National Research Initiative grants – 2006-35205-16888, 2006-35205-16701 Agriculture Research Service Holstein and Jersey breed associations Contributors to Cooperative Dairy DNA Repository (CDDR)