1. 2007 Paul VanRaden, Mel Tooker, and Melvin Kuhn Animal Improvement Programs Laboratory, USDA Agricultural Research Service, Beltsville, MD, USA paul@aipl.arsusda.gov 2007 Research Plans for Genomics, Crossbreeding, Fertility, etc.

2. Genex / CRI, June 2007 (2) P.M. VanRaden 2007 AIPL 5-Year Plan 2007-2012  Objectives Collect genotypes, new phenotypes Document current status and effects of management on dairy traits Improve accuracy of predictions by including SNP data, refining models Estimate economic values of traits to maximize lifetime profit

3. Genex / CRI, June 2007 (3) P.M. VanRaden 2007 Genomic Goals  Predict young bulls and cows more accurately  Compare actual DNA inherited  Use exact relationship matrix G instead of expected values in A  Trace chromosome segments  Locate genes with large effects

4. Genex / CRI, June 2007 (4) P.M. VanRaden 2007 How Related are Relatives?  Example: Full sibs are expected to share 50% of their DNA on average may actually share 45% or 55% of their DNA because each inherits a different mixture of chromosome segments from the two parents.  Combine genotype and pedigree data to determine exact fractions

5. Genex / CRI, June 2007 (5) P.M. VanRaden 2007 Genomic Relationships  Measures of genetic similarity A = Expected % genes identical by descent from pedigree (Wright, 1922) G = Actual % of DNA shared (using genotype data) T = % genes shared that affect a given trait (using genotype and phenotype)  Best measure depends on use

6. Genex / CRI, June 2007 (6) P.M. VanRaden 2007 QTL Relationship Matrix (T)  Three bulls each +50 PTA protein.  Are their QTL alleles the same? Possibly, but probably not. Bull A could have 10 positive genes. Bull B could have 10 positive genes, not on same chromosomes as bull A. Bull C could have 20 positive and 10 negative genes.

7. Genex / CRI, June 2007 (7) P.M. VanRaden 2007 Genes in Common at One Locus If Full Sib 1 inherits: If Full Sib 2 inherits: w,yw,zx,yx,z w,y2110 w,z1201 x,y1021 x,z0112 w = gene from sire of sire x = gene from dam of sire y = gene from sire of dam z = gene from dam of dam

8. Genex / CRI, June 2007 (8) P.M. VanRaden 2007 Alleles Shared by Sibs Indep- endent Loci Percentage of alleles shared Full sibsHalf sibs MeanSDMeanSD 15035.42517.7 55015.8257.9 105011.2255.6 50 5.0252.5 100503.5251.8 Infinite500.0250.0

9. Genex / CRI, June 2007 (9) P.M. VanRaden 2007 Unrelated Individuals?  No known common ancestors  Many unknown common ancestors born before the known pedigree  G = Z Z’ / number of loci  Elements of Z are –p and (1 – p), where p is allele frequency  Relationships in base = 0 +/- LD

10. Genex / CRI, June 2007 (10) P.M. VanRaden 2007 Traditional Pedigree Sire of Sire Sire Dam of Sire Animal Sire of Dam Dam Dam of Dam

11. Genex / CRI, June 2007 (11) P.M. VanRaden 2007 Genomic Pedigree

12. Genex / CRI, June 2007 (12) P.M. VanRaden 2007 Example of a SNP haplotype caacgtat caacggat SNP atccgaat atccgcat … …… … SNP tctaggat tctcggat SNP … …Chr1 Chr2 Haplotype is a set of single nucleotide polymorphisms (SNPs) associated on a single chromosome. Identification of a few alleles of a haplotype block can identify other polymorphic sites in the region. Haplotype 1tca gacHaplotype 2

13. Genex / CRI, June 2007 (13) P.M. VanRaden 2007 SNP Pedigree atagatcgatcg ctgtagcttagg agggcgcgcagt cgatctagatcg cggtagatcagt agagatcgatct atggcgcgaacg ctatcgctcagg ctgtagcgatcg agatctagatcg agagatcgcagt atgtcgctcacg ctgtctagatcg atgtcgcgcagt

14. Genex / CRI, June 2007 (14) P.M. VanRaden 2007 Haplotype Pedigree atagatcgatcg ctgtagcttagg agggcgcgcagt cgatctagatcg cggtagatcagt agagatcgatct atggcgcgaacg ctatcgctcagg ctgtagcgatcg agatctagatcg agagatcgcagt atgtcgctcacg ctgtctagatcg atgtcgcgcagt

15. Genex / CRI, June 2007 (15) P.M. VanRaden 2007 Genotype Pedigree Count number of copies of second allele 121101011112 111011120202 101121121111 122021121111 101101111100 011111012011 121120011012 0 = homozygous for first allele 1 = heterozygous 2 = homozygous for second allele

16. Genex / CRI, June 2007 (16) P.M. VanRaden 2007 Reliability from Full Sibs Marker and QTL positions identical, sib REL = 99% Reliability Obtained From: Full Sibs A 60 QTLs G 30,000 QTLs G 1.250 10.454.494.470 100.495.907.624 Infinite.5001.000 A = traditional additive relationships, G = genomic relationships

17. Genex / CRI, June 2007 (17) P.M. VanRaden 2007 Bulls to Genotype 58,533 SNP Project  Choose HO bulls with semen at BFGL  Genotype 1777 proven bulls Born 1994-1996 with >75% REL NM Plus 172 ancestor bulls born 1952-1993  Predict 500 bulls sampled later Born 2001 with >75% REL NM  Include other bulls in gap years? Born 1997-2000 (proven) or >2002 (waiting)

18. Genex / CRI, June 2007 (18) P.M. VanRaden 2007 Birth Years of Bulls to Genotype Data cutoff

19. Genex / CRI, June 2007 (19) P.M. VanRaden 2007 Contributors of DNA 500 CDDR bulls to predict, born in 2001 AI OrganizationCode Number of bulls chosen CRI / Genex1126 Select Sires7107 Alta Genetics1167 Accelerated1444 ABS Global29120 Semex20032

20. Genex / CRI, June 2007 (20) P.M. VanRaden 2007 Potential Results Simulation of 50,000 SNPs  QTLs normally distributed, n = 100  Reliability vs parent average REL 58% vs 36% if QTLs are between SNPs 71% vs 36% if QTLs are located at SNPs (not likely) Higher REL if major loci and Bayesian methods used, lower if many loci (>100) affect trait

21. Genex / CRI, June 2007 (21) P.M. VanRaden 2007 Reliability from Genotyping  Daughter equivalents DE Total = DE PA + DE Prog + DE Y + DE G DE G is additional DE from genotype REL = DE total / (DE Total + k)  Gains in reliability DE G could be about 15 for Net Merit More for traits with low heritability Less for traits with high heritability

22. Genex / CRI, June 2007 (22) P.M. VanRaden 2007 Genomic Computer Programs  Simulate SNPs and QTLs Compare SNP numbers, size of QTLs  Calculate genomic EBVs Use selection index, G instead of A Use iteration on data for SNP effects  Form haplotypes from genotypes Not programmed yet

23. Genex / CRI, June 2007 (23) P.M. VanRaden 2007 Computing Times  Inversion including G matrix Animals 2 x markers to form G matrix Animals 3 to invert selection index 10 hours for 3000 bulls, 50,000 SNPs  Iteration on genotype data Markers x animals x iterations 16 hours for 1000 iterations

24. Genex / CRI, June 2007 (24) P.M. VanRaden 2007 Distribution of Marker Effects

25. Genex / CRI, June 2007 (25) P.M. VanRaden 2007 Linear vs Non-linear Models

26. Genex / CRI, June 2007 (26) P.M. VanRaden 2007 All-Breed Model: Goals  Evaluate crossbred animals without biasing purebred evaluations  Accurately estimate breed differences  Compare crossbreeding strategies  Compute national evaluations and examine changes  Display results without confusion

27. Genex / CRI, June 2007 (27) P.M. VanRaden 2007 Methods  All-breed animal model Purebreds and crossbreds together Relationship matrix among all Unknown parents grouped by breed Variance adjustments by breed Age adjust to 36 months, not mature  Within-breed-of-sire model examined but not used

28. Genex / CRI, June 2007 (28) P.M. VanRaden 2007 Data  Numbers of cows of all breeds 22.6 million for milk and fat 16.1 million for protein 22.5 million for productive life 19.9 million for daughter pregnancy rate 10.5 million for somatic cell score  Type traits are still collected and evaluated in separate breed files

29. Genex / CRI, June 2007 (29) P.M. VanRaden 2007 Purebred and Crossbred Data USA milk yield records Breed% of totalCows born 2003 Holstein90.5642,354 Jersey6.445,151 Brown Swiss.85,960 Guernsey.42,563 Ayrshire.31,926 F1 Crossbred1.28,647

30. Genex / CRI, June 2007 (30) P.M. VanRaden 2007 Crossbred Cows with 1 st parity records Fresh year F1 (%) F1 cows Back- cross Het > 0 XX cows 20061.4101533422153656099 20051.286472495126214465 20041.178631983111913947 2003.96248149290513111 2002.74689146773382564

31. Genex / CRI, June 2007 (31) P.M. VanRaden 2007 Number of Cows with Records Number of Cows with Records (with > 50% heterosis; March 2007) DamSire Breed BreedAYBSGUJEMSXXHO AY —29 22148431796 BS 20—5029442132619 GU 4696—28832163256 JE 181357155—116563718 MS 281521071—5965 XX 48915443083568323—8859 HO 1843139931721351931858675—

32. Genex / CRI, June 2007 (32) P.M. VanRaden 2007 Number of Cows with Records Number of Cows with Records (with > 50% heterosis; March 2007) Sire Breed Dam Breed# Sire Breed Dam Breed# BS SM25 HO DL47 DL HO109 HO LD195 MO HO73 HO MI60 NO HO38 HO NR21 NR HO23 HO RE22 SR HO118 HO SM16

33. Genex / CRI, June 2007 (33) P.M. VanRaden 2007 Crossbred Daughters Added for sires in top 10 NM$ within breed Sire breed Daughters Sire NameFeb ‘07Added LegacyAY15733 AgendaBS3521 ExciteBS14457 Q ImpulsJE24120 StetsonMS3631

34. Genex / CRI, June 2007 (34) P.M. VanRaden 2007 Heterosis for Yield Traits Heterosis for Yield Traits Percent of Parent Breed Average MilkFatProtein Breed HO Sire HO Dam HO Sire HO Dam HO Sire HO Dam Ayrshire 2.4-2.02.7-1.82.9-2.4 Brown Swiss 5.6 3.24.8 4.54.7 3.8 Guernsey 5.2 2.47.1 4.45.5 4.0 Jersey 7.5 1.66.6 4.57.2 4.1 M. Shorthrn 2.8 0.33.2 1.33.6 1.2 Heterosis3.44.44.1

35. Genex / CRI, June 2007 (35) P.M. VanRaden 2007 All-Breed Analyses  Crossbred animals Now have PTAs, only 3% did before if in breed association grading-up programs Reliable PTAs from both parents  Purebred animals Information from crossbred relatives More herdmates (other breeds, crossbreds)  Routinely used in other populations New Zealand (1994), Netherlands (1997) USA goats (1989), calving ease (2005)

36. Genex / CRI, June 2007 (36) P.M. VanRaden 2007 Unknown Parent Groups  Look up PTAs of known parents  Estimate averages for unknowns  Group unknown parents by Birth year Breed Path (dams of cows, sires of cows, parents of bulls) Origin (domestic vs other countries)

37. Genex / CRI, June 2007 (37) P.M. VanRaden 2007 All- vs Within-Breed Evaluations Correlations of PTA Milk Breed 99% REL bulls Recent bulls Recent cows Holstein >.999.994.989 Jersey.997.988.972 Brown Swiss.990.960.942 Guernsey.991.988.969 Ayrshire.990.963.943 Milking Shorthorn.997.986.947

38. Genex / CRI, June 2007 (38) P.M. VanRaden 2007 Display of PTAs  Genetic base Convert all-breed base to within-breed bases (or vice versa) PTA brd = (PTA all – mean brd ) SD brd /SD HO PTA all = PTA brd (SD HO /SD brd ) + mean brd  Heterosis and inbreeding Both effects removed in the animal model Heterosis added to crossbred animal PTA Expected Future Inbreeding (EFI) and merit differ with mate breed

39. Genex / CRI, June 2007 (39) P.M. VanRaden 2007 All-Breed PTAs – March Test Run  Genetic correlations mostly same JE increase.02 for PL and.01 for SCS BS decrease.01 for fat and SCS AY increase.01 for PL  USA bulls in top 100 differ little Numbers are averages across all scales JE improve for SCS, fat (26 vs 25) JE decline for milk, protein (59 vs 62) BS decline for yield (10 vs 15) HO improve for yield (17 vs 16)

40. Genex / CRI, June 2007 (40) P.M. VanRaden 2007 Jersey and Swiss PTAs  Base cow means changed little  Base cow SD changed little  Top bulls for protein dropped by ~9 lbs, bottom bulls dropped by ~4 lbs in both breeds  Unknown parent grouping, heterosis may be responsible

41. Genex / CRI, June 2007 (41) P.M. VanRaden 2007 All-breed Trend Validation  85 tests, 6 were significant (.05) None significant for milk or SCS 1 of 15 for fat and for protein 2 of 15 for PL and for DPR  Increase in DPR repeatability made trend more negative, helped tests

42. Genex / CRI, June 2007 (42) P.M. VanRaden 2007 Daughter Pregnancy Rate Genetic trend on all-breed base

43. Genex / CRI, June 2007 (43) P.M. VanRaden 2007 Assumed Effects – Other Traits Transmitting ability differences from Holstein SizeUdderF&L Calving Difficulty Still- birth Jersey −10.4−1.4−2.1−7.1−1.5 B. Swiss 0.00.70.3−3.2−0.7 Guernsey −7.3−0.5−1.3−4.61.1 Ayrshire −5.8−1.6−0.9−3.5−1.2 M. Short. −4.20.1−0.6−0.1−2.4 Heterosis 0.90.0

44. Genex / CRI, June 2007 (44) P.M. VanRaden 2007 Merit of F 1 Holstein Crossbreds 2006 Merit Indexes Second Breed NM$CM$FM$ Ayrshire −304 −261−364 Brown Swiss 55 139−78 Guernsey −408−405−503 Jersey 31153−158 M. Shorthorn −498−461−547 Compared to 2005 genetic base for Holstein

45. Genex / CRI, June 2007 (45) P.M. VanRaden 2007 Later Generation Crosses Holstein backcross or multi-breed NM$CM$ FM$ HO x (BS x HO) +28+70−39 HO x (JE x HO) +16+77−79 BS x (JE x HO) −32+109−251 JE x (BS x HO) −44+116−292 HO x (BS x JE) +44+147−118 Compared to 2005 genetic base for Holstein

46. Genex / CRI, June 2007 (46) P.M. VanRaden 2007 Butterfat yield of three breed crosses was greater than from their F 1 crossbred dams. Three breed crosses averaged 14,927 pounds of milk and 641 pounds of butterfat as 2-year-olds in 1947. USDA Yearbook of Agriculture 1947 Three-Breed Crosses

47. Genex / CRI, June 2007 (47) P.M. VanRaden 2007 Crossbreeding Conclusions  All-breed model accounts for: Breed effects and general heterosis Unequal variances within breed  Implemented in May 2007 PTA converted back to within-breed bases, crossbreds to breed of sire PTA changes larger in breeds with fewer animals

48. Genex / CRI, June 2007 (48) P.M. VanRaden 2007 Cow Fertility Research  Daughter Pregnancy Rate works well, except that Other traits are evaluated by Interbull Other countries don’t use DPR in their indexes, and their calving interval data comes too late  Synchronization changes traits

49. Genex / CRI, June 2007 (49) P.M. VanRaden 2007 Emphasis on Fertility, Longevity (% of total merit) CtryFertLongCtryFertLong USA917DNK86 DEU125AUS98 NLD816NZL76 FRA13 GBR715 CAN57SWE155 ITA8IRL2218

50. Genex / CRI, June 2007 (50) P.M. VanRaden 2007 Days Open Genetic Correlations Jorjani, 2005 Interbull Bulletin DFSESPGBRIRLNLDNZLUSA DFS.91.75.93.76.91 ESP.91.89.82.90.83.93 GBR.91.89.84.96.84.85 IRL.75.82.84.80.70.80 NLD.93.90.96.80.83.88 NZL.76.83.84.85.83.73 USA.91.93.85.80.88.73 DFS = Denmark-Finland-Sweden

51. Genex / CRI, June 2007 (51) P.M. VanRaden 2007 DPR Results – March Test Run Holstein genetic correlations EvalModel BELDFSESPGBRIRLITANLDNZL Mar All breed 8689938376908662 Feb Within breed 85…938372868560 Diff +1…00+4 +1+2 March model also included an increase in repeatability

52. Genex / CRI, June 2007 (52) P.M. VanRaden 2007 Daughter Conception Rate Genetic Correlations Jorjani, 2005 Interbull Bulletin CANDEUDFSFRAISRNLD CAN.90.80.78.72.70 DEU.90.72.92.65.47 DFS.80.72.75.96.62 FRA.78.92.75.70.42 ISR.72.65.96.70.64 NLD.70.47.62.42.64 DFS = Denmark-Finland-Sweden

53. Genex / CRI, June 2007 (53) P.M. VanRaden 2007 Days to 1 st Insemination Genetic Correlations Interbull, May 2007 CHEDFSITANLDNZL CHE.95.87.90.61 DFS.95.90.91.57 ITA.87.90.86.70 NLD.90.91.86.55 NZL.61.57.70.55 DFS = Denmark-Finland-Sweden

54. Genex / CRI, June 2007 (54) P.M. VanRaden 2007 Fertility Trait Indexes % relative emphasis TraitUSANLDITACANDNK 1 DEUFRA Days 1 st Insem. 6933192515 Non− Return 3141206570100 Days Open 1002661 Heifer fertility 1015 1 Time from first to last insemination replaces non−return rate

55. Genex / CRI, June 2007 (55) P.M. VanRaden 2007 Predict Longevity from Fertility  Which cow fertility trait contributes most to longevity? Days to first insemination (DFI), or Non−return rate (NR)  Combined longevity includes 23% DFI and 12% NR in CAN Only DFI in NLD Correlations =.33 DFI,.11 NR in USA

56. Genex / CRI, June 2007 (56) P.M. VanRaden 2007 DPR - Top 100 bulls Born in last 12 years, March 2007 test run Country with most daughters ScaleDFSESPGBRIRLITANLDNZLUSA BEL14410616544 DFS293116317273 ESP15510415528 GBR187137411307 IRL12310 15580 ITA1838338552 NLD184104122383 NZL100100970 USA1748326537 Total142338044168046434

57. Genex / CRI, June 2007 (57) P.M. VanRaden 2007 Calving Interval Correlations with other traits in the same country CtryBirthMilkFatProtLongSCS DNK−.40−.31−.28−.32.34−.18 ESP−.08−.38−.29−.35.38−.16 GBR−.27−.36 −.42.30−.13 IRL−.20−.40−.35−.37.49 NLD−.41−.52−.43−.50.06−.13 NZL−.11−.32−.05−.21.59−.10 USA−.04−.21 −.17.48−.12

58. Genex / CRI, June 2007 (58) P.M. VanRaden 2007 Conception Rate (Trait 4 correlations with other traits) CtryBirthMilkFatProtLongSCS CAN−.06−.07−.09.09−.04 DEU.06−.01−.03−.02.17−.04 DNK−.41−.43−.37−.47.23−.17 FRA.09.00−.02.00.28−.08 ISR−.06−.07−.16−.27.38−.15 NLD−.41−.39−.37−.48.08−.04

59. Genex / CRI, June 2007 (59) P.M. VanRaden 2007 Calving to First Insemination (Trait 2 correlations with other traits) CtryBirthMilkFatProtLongSCS CAN−.01−.26−.16−.21.32−.12 DNK−.34−.42−.36−.40.25−.22 NLD−.33−.49−.46−.50.04−.15 NZL−.08−.29−.05−.19.49−.10

60. Genex / CRI, June 2007 (60) P.M. VanRaden 2007 Heifer Fertility (Trait 1 correlations with other traits) CtryBirthMilkFatProtLongSCS CAN−.09−.11−.09−.14.14−.10 DNK−.27−.23−.19−.27.03−.05 GBR−.43−.48−.22−.44.13−.12

61. Genex / CRI, June 2007 (61) P.M. VanRaden 2007 Cow Fertility Conclusions  Fertility and longevity receive a total of 8% to 40% of selection  Fertility definitions not uniform  Days to 1 st insemination is more important than conception rate?  Selection for fertility reduces costs and increases longevity

62. Genex / CRI, June 2007 (62) P.M. VanRaden 2007 Bull Fertility Research Dr. Melvin Kuhn I. Multiple services and an expanded service sire (SSR) term II. “Type” of model: Linear, Threshold III. Unconfirmed breedings: outcome not known with certainty IV. Edits and Modeling of nuisance variables

63. Genex / CRI, June 2007 (63) P.M. VanRaden 2007 Service Sire Effects  SSR inbreeding  Inbreeding of the Mating  SSR age at mating  Stud and Stud*year  Additive genetic effect (very low heritability)

64. Genex / CRI, June 2007 (64) P.M. VanRaden 2007 Results: Correlations Services MethodPredictorAll1 st only SimulationExpanded87.2 81.0 SSR only83.0 71.4 Split-herdExpanded56.1 45.5 SSR only44.0 37.5 Future yrExpanded32.1 29.4 SSR only29.3 23.6 Expd Stud*yr: 38.1 Expd, no Stud*yr: 31.6

65. Genex / CRI, June 2007 (65) P.M. VanRaden 2007 Linear/Threshold Model Conclusions to date:  Little, if any, difference in predictions between the 2 models  Use of a good estimate of std. dev. of the predictor in thr model probability calculations may improve thr model evaluations  Threshold/Linear model is, at most and if anything at all, only a minor issue  Linear model will likely be implemented because it is computationally faster, more reliable, and simpler

66. Genex / CRI, June 2007 (66) P.M. VanRaden 2007 Sexed Semen (S) Matings  22,843 S-matings reported as of April 2007  92% are Holstein, most of remainder are Jersey  61% are on heifers (not eligible for ERCR)  69% are 1 st services  4,040 ERCR-eligible Holstein S-matings  398 bulls  Only 2 bulls with at least 300 ERCR-eligible S-matings

67. Genex / CRI, June 2007 (67) P.M. VanRaden 2007 Bull Fertility Summary  Research on use of multiple services and an expanded service sire term is complete  Linear/Thr model is, at most, of minor importance only for this trait; will likely implement linear model  Expect to delete unconfirmed matings and treat those with positive preg ck as successes but impact will be evaluated  Implementation expected January 2008

68. Genex / CRI, June 2007 (68) P.M. VanRaden 2007 Test Day Model - Potential Benefits  Increased accuracy of evaluations Account for lactation curve differences Account for genetic differences by parity Evaluate persistency, rate of maturity Include milk-only records if multi-trait Possible earlier selection of bull dams Promote as state-of-the-art system  Management effects more accurate Could provide to DRPCs and herd owners