1. John B. Cole Animal Genomics and Improvement Laboratory Agricultural Research Service, USDA Beltsville, MD john.cole@ars.usda.gov Genetic improvement programs for US dairy cattle

2. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (2) Cole Typical US dairies Top: Large freestall barn in the state of Florida. Bottom: 7,000 G (~26,500 l) milk tankers. Photo courtesy of North Florida Holsteins. Small dairy farm in western Maryland. Photo courtesy of ARS.

3. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (3) Cole U.S. dairy population and milk yield

4. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (4) Cole U.S. DHI dairy statistics (2011) l 9.1 million U.S. cows l ~75% bred AI l 47% milk recorded through Dairy Herd Information (DHI) w 4.4 million cows − 86% Holstein − 8% crossbred − 5% Jersey − <1% Ayrshire, Brown Swiss, Guernsey, Milking Shorthorn, Red & White w 20,000 herds w 220 cows/herd w 10,300 kg/cow

5. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (5) Cole Genetic evaluation advances YearAdvanceGain, % 1862USDA established 1895USDA begins collecting dairy records 1926Daughter-dam comparison100 1962Herdmate comparison50 1973Records in progress10 1974Modified contemporary comparison5 1977Protein evaluated4 1989Animal model4 1994Net merit, productive life, and somatic cell score 50 2008Genomic selection>50

6. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (6) Cole Animal model l 1989 to present l Introduced by Wiggans and VanRaden l Advantages w Information from all relatives w Adjustment for genetic merit of mates w Uniform procedures for males and females w Best prediction (BLUP) w Crossbreds included (2007) w Genomic information added (2008)

7. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (7) Cole Traits evaluated YearTraitYearTrait 1926Milk & fat yields2000Calving ease 1 1978Conformation (type)2003Daughter pregnancy rate 1978Protein yield2006Stillbirth rate 1994Productive life2006Bull conception rate 2 1994Somatic cell score (mastitis) 2009Cow and heifer conception rates 1 Sire calving ease evaluated by Iowa State University (1978–99) 2 Estimated relative conception rate evaluated by DRMS in Raleigh, NC (1986–2005)

8. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (8) Cole Evaluation methods for traits l Animal model (linear) w Yield (milk, fat, protein) w Type (AY, BS, GU, JE) w Productive life w Somatic cell score w Daughter pregnancy rate w Heifer conception rate w Cow conception rate l Sire–maternal grandsire model (threshold) w Service sire calving ease w Daughter calving ease w Service sire stillbirth rate w Daughter stillbirth rate Heritability 8.6% 3.6% 3.0% 6.5% 25 – 40% 7 – 54% 8.5% 12% 4% 1% 1.6%

9. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (9) Cole Conformation (type) traits l Stature l Strength l Body depth l Dairy form l Rump angle l Thurl width l Rear legs (side) l Rear legs (rear) l Foot angle l Feet and legs score l Fore udder attachment l Rear udder height l Rear udder width l Udder cleft l Udder depth l Front teat placement l Rear teat placement l Teat length

10. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (10) Cole Holstein milk (kg) Phenotypic base = 11,828 kg Cows Sires 79 kg/yr

11. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (11) Cole Holstein productive life (mo) Phenotypic base = 27.2 mo Sires Cows 0.2 mo/yr

12. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (12) Cole Holstein somatic cell score (log 2 ) Sires Cows 0.02/yr Phenotypic base = 3.0

13. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (13) Cole Holstein daughter pregnancy rate (%) Phenotypic base = 22.6% Sires Cows 0.1%/yr

14. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (14) Cole Holstein calving ease (%) Daughte r Service-sire phenotypic base = 7.9% Daughter phenotypic base = 7.5% Service sire 0.18%/yr 0.01%/yr

15. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (15) Cole Trait Relative emphasis on traits in index (%) PD$ 1971 MFP$ 1976 CY$ 1984 NM$ 1994 NM$ 2000 NM$ 2003 NM$ 2006 NM$ 2010 NM$ 2014 Milk5227–265000 Fat484645252122231922 Protein…2753433633231620 PL………201411172219 SCS………–6–9 –10-7 UDC…………77678 FLC…………44343 BDC…………–4–3–4–6-5 DPR……………79117 HCR…………… … … …2 CCR…………… … … …1 SCE……………–2……… DCE……………–2… … … CA$………………655 Index changes over time Source: AGIL, ARS, USDA (http://aipl.arsusda.gov/reference/nmcalc-2014.htm).

16. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (16) Cole Trait Relative value (%) Net merit Cheese merit Fluid merit Grazing merit Milk (lb)-923 Fat (lb)22192320 Protein (lb)2024018 Productive life (PL, mo)19162010 Somatic cell score (SCS, log 2 )-7 -3-6 Udder composite (UC)8688 Feet/legs composite (FLC)3233 Body size composite (BSC)-5-4-5-4 Daughter pregnancy rate (DPR, %)76719 Heifer conception rate (HCR, %)2123 Cow conception rate (CCR, %)1125 Calving ability (CA$, $)5455 Genetic-economic indices (2014) Source: AGIL, ARS, USDA (http://aipl.arsusda.gov/reference/nmcalc-2014.htm).

17. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (17) Cole Traditional evaluation summary l Evaluation procedures have improved l Fitness traits have been added l Effective selection has produced substantial annual genetic improvement l Indices enable selection for overall economic merit l Fertility evaluations prevent continued decline

18. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (18) Cole Traditional dairy breeds in the US The six traditional US dairy breeds. Photo courtesy of Bonnie Mohr.

19. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (19) Cole Genomic evaluation system l Provides timely evaluations of young bulls for purchasing decisions l Increases accuracy of evaluations of bull dams l Assists in selection of service sires, particularly for low-reliability traits l High demand for semen from genomically evaluated 2-year-old bulls

20. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (20) Cole Genomic data flow DNA samples genotypes genomic evaluations nominations, pedigree data genotype quality reports genomic evaluations DNA samples genotypes DNA samples Dairy Herd Improvement (DHI) producer Council on Dairy Cattle Breeding (CDCB) DNA laboratory AI organization, breed association AI organization, breed association

21. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (21) Cole Collaboration with industry l Council on Dairy Cattle Breeding (CDCB) responsible for receiving data and for computing and delivering US genetic evaluations for dairy cattle l AIP responsible for research and development to improve the evaluation system l CDCB (Bowie) and AIP (Beltsville) are located near one another Dr. Jo ão D ü rr is CDCB’s CEO

22. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (22) Cole Council on Dairy Cattle Breeding l 3 board members from each organization l Total of 12 voting members l 2 nonvoting industry members CDCB PDCANAABDRPCDHIA Purebred Dairy Cattle Association National Association of Animal Breeders Dairy Records Processing Centers Dairy Herd Information Association

23. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (23) Cole 012345 Genomic prediction of progeny test Select parents, transfer embryos to recipients Calves born and DNA tested Calves born from DNA- selected parents Bull receives progeny test Reduce generation interval from 5 to 2 years

24. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (24) Cole Evaluation flow l Animal nominated for genomic evaluation by breed association or AI organization l Hair or other DNA source sent to genotyping lab l DNA extracted and placed on chip for 3-day genotyping process l Genotypes sent from genotyping lab to AIPL for accuracy review

25. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (25) Cole Laboratory quality control l Each SNP evaluated for w Call rate w Portion heterozygous w Parent-progeny conflicts l Clustering investigated if SNP exceeds limits l Number of failing SNPs indicates genotype quality l Target of <10 SNPs in each category

26. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (26) Cole Evaluation flow (continued) l Genotype calls modified as necessary l Genotypes loaded into database l Nominators receive reports of parentage and other conflicts l Pedigree or animal assignments corrected l Genotypes extracted and imputed to 45K l SNP effects estimated

27. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (27) Cole Imputation l Based on splitting genotype into individual chromosomes (maternal and paternal contributions) l Missing SNPs assigned by tracking inheritance from ancestors and descendants l Imputed dams increase predictor population l Genotypes from all chips merged by imputing SNPs not present

28. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (28) Cole Evaluation flow (continued) l Final evaluations calculated l Evaluations released to dairy industry w Download from CDCB FTP site with separate files for each nominator w Monthly release for new animals w All genomic evaluations updated 3 times each year with traditional evaluations w Weekly evaluations are now available

29. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (29) Cole Genomic evaluation results Source: https://www.cdcb.us/Report_Data/Marker_Effects/marker_effects.cfm?Breed=HO&Trait=Net_Merit

30. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (30) Cole Information sources for evaluations l Traditional evaluations of genotyped bulls and cows used to estimate SNP effects l Combined final evaluation w Sum of SNP effects for an animal’s alleles w Polygenetic effect w Traditional evaluation l Pedigree data used and validated by genotypes

31. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (31) Cole Genotypes are abundant

32. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (32) Cole SNP used for genomic evaluations l 61,013 SNP used after culling on w MAF w Parent-progeny conflicts w Percentage heterozygous (departure from HWE) l SNP for HH1, BLAD, DUMPS, CVM, polled, red, and mulefoot included w JH1 included for Jerseys l Some SNP eliminated because incorrect location  haplotype non-inheritance

33. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (33) Cole SNP count for different chips ChipSNP (no.)ChipSNP (no.) 50K54,001ZMD56,955 50K v254,609ELD9,072 3K2,900LD26,912 HD777,962GP326,151 Affy648,875ZL217,557 LD6,909ZM260,914 GGP8,762GH2139,480 GHD77,068G7K7,083 GP219,809GP430,112 ZLD11,410ZL418,815 Source: Council on Dairy Cattle Breeding.

34. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (34) Cole 2016 genotypes by breed and sex BreedFemaleMale All animals Female: male Ayrshire 3,6411,6935,33468:32 Brown Swiss4,27816,75721,03520:80 Guernsey1,8356562,49174:26 Holstein894,471182,8661,077,37783:17 Jersey119,68921,031140,72085:15 Milking Shorthorn12142646:54 Crossbred380 100:00 All1,023,964223,0171,246,981 Source: Council on Dairy Cattle Breeding (https://www.cdcb.us/Genotype/cur_freq.html).

35. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (35) Cole Growth in US predictor population BullsCows 1,2 Breed Jan. 2016 12-mo gain Jan. 2016 12-mo gain Ayrshire 7524113359 Brown Swiss6,3632411,580429 Holstein28,9222,163190,02178,917 Jersey4,71226442,71716,247 1 Predictor cows must have domestic records. 2 Counts include 3k genotypes, which are not included in the predictor population. Source: Council on Dairy Cattle Breeding (https://www.cdcb.us/Genotype/cur_density.html).

36. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (36) Cole TraitBias* Reliability (%) Reliability gain (% points) Milk (kg)−80.369.230.3 Fat (kg)−1.468.429.5 Protein (kg)−0.960.922.6 Fat (%)0.093.754.8 Protein (%)0.086.348.0 Productive life (mo)−0.773.741.6 Somatic cell score 0.064.929.3 Daughter pregnancy rate (%) 0.253.520.9 Sire calving ease 0.645.819.6 Daughter calving ease−1.844.222.4 Sire stillbirth rate 0.228.2 5.9 Daughter stillbirth rate0.137.617.9 *2013 deregressed value – 2009 genomic evaluation Holstein prediction accuracy

37. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (37) Cole Holstein prediction accuracy *2013 deregressed value – 2009 genomic evaluation TraitBias* Reliability (%) Reliability gain (% points) Final score0.158.822.7 Stature−0.268.530.6 Dairy form−0.271.834.5 Rump angle0.070.234.7 Rump width−0.265.028.1 Feed and legs0.244.012.8 Fore udder attachment −0.270.433.1 Rear udder height −0.159.422.2 Udder depth −0.375.337.7 Udder cleft−0.262.125.1 Front teat placement −0.269.932.6 Teat length−0.166.729.4

38. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (38) Cole Parent ages of marketed Holstein bulls

39. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (39) Cole Active AI bulls that were genomic bulls

40. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (40) Cole Genetic merit of marketed Holstein bulls Average gain: $19.77/year Average gain: $52.00/year Average gain: $85.60/year

41. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (41) Cole Genetic choices l Before genomics: w Proven bulls with daughter records (PTA) w Young bulls with parent average (PA) l After genomics: w Young animals with DNA test (GPTA) w Reliability of GPTA ~70% compared to PA ~35% and PTA ~85% for Holstein NM$

42. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (42) Cole Stability of genomic evaluations l 642 Holstein bulls w Dec. 2012 NM$ compared with Dec. 2014 NM$ w First traditional evaluation in Aug. 2014 w  50 daughters by Dec. 2014 l Top 100 bulls in 2012 w Average rank change of 9.6 w Maximum drop of 119 w Maximum rise of 56 l All 642 bulls w Correlation of 0.94 between 2012 and 2014 w Regression of 0.92

43. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (43) Cole Genomics is not the only innovation Photos courtesy of Albert de Vries. The Swedish Agricultural University dairy research center has a state-of-the-art facility equipped with the latest DeLaval technology.

44. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (44) Cole Application to more traits l Animal’s genotype good for all traits l Traditional evaluations required for accurate estimates of SNP effects l Traditional evaluations not currently available for heat tolerance or feed efficiency l Research populations could provide data for traits that are expensive to measure l Will resulting evaluations work in target population?

45. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (45) Cole Some new traits studied recently ● Claw health (Van der Linde et al., 2010) ● Dairy cattle health (Parker Gaddis et al., 2013) ● Embryonic development (Cochran et al., 2013) ● Immune response (Thompson-Crispi et al., 2013) ● Methane production (de Haas et al., 2011) ● Milk fatty acid composition (Soyeurt et al., 2011) ● Persistency of lactation (Cole et al., 2009) ● Rectal temperature (Dikmen et al., 2013) ● Residual feed intake (Connor et al., 2013)

46. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (46) Cole Parentage validation and discovery l Parent-progeny conflicts detected w Animal checked against all other genotypes w Reported to breeds and requesters w Correct sire usually detected l Maternal grandsire (MGS) checking w SNP at a time checking w Haplotype checking more accurate l Breeds moving to accept SNPs in place of microsatellites

47. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (47) Cole Haplotypes affecting fertility l Rapid discovery of new recessive defects w Large numbers of genotyped animals w Affordable DNA sequencing l Determination of haplotype location w Significant number of homozygous animals expected, but none observed w Narrow suspect region with fine mapping w Use sequence data to find causative mutation

48. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (48) Cole Name BTA chromo- some Location* (Mbp) Carrier frequency (%)Earliest known ancestor HH1563.2*3.8Pawnee Farm Arlinda Chief HH2194.9 – 96.63.3Willowholme Mark Anthony HH3895.4*5.9Glendell Arlinda Chief, Gray View Skyliner HH411.3*0.7Besne Buck HH5992.4 – 93.94.4Thornlea Texal Supreme JH11515.7*24.2Observer Chocolate Soldier JH2268.8 – 9.42.6Liberators Basilius BH1742.8 – 47.013.3West Lawn Stretch Improver BH21910.6 – 11.715.6Rancho Rustic My Design AH11765.9*26.0Selwood Betty’s Commander Haplotypes affecting fertility *Causative mutation known

49. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (49) Cole Recessive Haplo- type BTA chromo- some Tested animals (no.) Concord- ance (%) New carriers (no.) BrachyspinaHH021??? BLADHHB 1*11,78299.9314 CVMHHC 3*13,226—2,716 DUMPSHHD 1*3,242100.03 Mule footHHM15*8797.7120 PolledHHP1345—2,050 Red coat color HHR18*4,137—5,927 SDMBHD11*10894.4108 SMABHM24*56898.1111 WeaverBHW416396.332 Haplotypes tracking known recessives *Causative mutation known

50. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (50) Cole Impact on breeders l Haplotype and gene tests in selection and mating programs l Trend towards a small number of elite breeders that are investing heavily in genomics l About 30% of young males genotyped directly by breeders since April 2013 l Prices for top genomic heifers can be very high (e.g., $265,000 or R$1,060,000)

51. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (51) Cole Impact on dairy producers l General w Reduced generation interval w Increased rate of genetic gain w More inbreeding/homozygosity?

52. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (52) Cole Impact on dairy producers (continued) l Sires w Higher average genetic merit of available bulls w More rapid increase in genetic merit for all traits w Larger choice of bulls in terms of traits and semen price w Greater use of young bulls

53. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (53) Cole Why genomics works for dairy cattle l Extensive historical data available l Well-developed genetic evaluation program l Widespread use of AI sires l Progeny-test programs l High-value animals worth the cost of genotyping l Long generation interval that can be reduced substantially by genomics

54. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (54) Cole Key issues for the dairy industry l Inbreeding and genetic diversity (including across breeds) l Sequencing, new genes, and mutations l Novel traits, resource populations (feed efficiency, health, milk properties)

55. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (55) Cole Conclusions l Genomic evaluation has dramatically changed dairy cattle breeding l Rate of gain is increasing primarily because of a large reduction in generation interval l Genomic research is ongoing w Detect causative genetic variants w Find more haplotypes affecting fertility w Improve accuracy through more SNPs, more predictor animals, and more traits

56. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (56) Cole Acknowledgments l Appropriated project 1265-31000-096-00, "Improving Genetic Predictions in Dairy Animals Using Phenotypic and Genomic Information", ARS, USDA l CNPq “Science Without Borders” project 301025/2014-2 l Kristen Gaddis, Dan Null, Paul VanRaden, and George Wiggans l Council on Dairy Cattle Breeding

57. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (57) Cole Disclaimer Mention of trade names or commercial products in this presentation is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture.

58. Embrapa Pecuária Sul, Bagé, RS, Brasil 4 February 2016 (58) Cole Questions?