1. G.R. Wiggans Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD george.wiggans@ars.usda.gov 2010 G.R. WiggansDCRC 2010 Conference (1) Genomic Evaluations: Past, Present, and Future

2. G.R. Wiggans 2010 DCRC 2010 Conference (2) Genetic Improvement l Driven by genetic evaluation program l Yield, fitness, type and calving traits evaluated l Widespread use of AI sires l Progeny test programs l Genomics w Increases rate of improvement by reducing generation interval

3. G.R. Wiggans 2010 DCRC 2010 Conference (3) Past l Parentage verification using w Blood groups w Microsatellites l Search for major genes l Marker assisted selection w Little value

4. G.R. Wiggans 2010 DCRC 2010 Conference (4) History of genomic evaluations l Dec. 2007BovineSNP50 BeadChip available l Apr. 2008First unofficial evaluation released l Jan. 2009Genomic evaluations official for Holstein and Jersey l Aug. 2009Official for Brown Swiss l Sept. 2010Unofficial evaluations from 3K chip released l Dec. 20103K genomic evaluations to be official

5. G.R. Wiggans 2010 DCRC 2010 Conference (5) Bovine Genome Sequence

6. G.R. Wiggans 2010 DCRC 2010 Conference (6) Background: Genetic Markers l A segment of DNA at a unique physical location in the genome that varies sufficiently between individuals that its inheritance can be tracked through families. l A marker is not required to be part of a gene.

7. G.R. Wiggans 2010 DCRC 2010 Conference (7) Genetic Markers l Allow inheritance to be followed in a region across generations l Single nucleotide polymorphisms (SNP) are the markers of choice l Need lots! w 3 million in the genome

8. G.R. Wiggans 2010 DCRC 2010 Conference (8) Cattle SNP Collaboration - iBMAC l Develop 60,000 Bead Illumina iSelect® assay w USDA-ARS Beltsville Agricultural Research Center: Bovine Functional Genomics Laboratory and Animal Improvement Programs Laboratory w University of Missouri w University of Alberta w USDA-ARS US Meat Animal Research Center l Starting 60,800 beads – 54,000 useable SNP

9. G.R. Wiggans 2010 DCRC 2010 Conference (9)

10. G.R. Wiggans 2010 DCRC 2010 Conference (10) Participants  Illumina  Marylinn Munson  Cindy Lawley  Christian Haudenschild  BARC  Curt Van Tassell  Lakshmi Matukumalli  Tad Sonstegard  Missouri  Jerry Taylor  Bob Schnabel  Stephanie McKay  Alberta  Steve Moore  USMARC – Clay Center  Tim Smith  Mark Allan 10  USDA/NRI/CSREES  2006-35616-16697  2006-35205-16888  2006-35205-16701  USDA/ARS  1265-31000-081D  1265-31000-090D  5438-31000-073D  Merial  Stewart Bauck  NAAB  Godon Doak  ABS Global  Accelerated Genetics  Alta Genetics  CRI/Genex  Select Sires  Semex Alliance  Taurus Service iBMAC Consortium Funding Agencies

11. G.R. Wiggans 2010 DCRC 2010 Conference (11) Collaboration l Consortium including universities, government and industry contributed to developing chip l Full sharing of genotypes with Canada w CDN calculates genomic evaluations on Canadian base l Trading of Brown Swiss genotypes with Switzerland, Germany, and Austria l Collaborations with other countries being negotiated

12. G.R. Wiggans 2010 DCRC 2010 Conference (12) What’s genomics? l Study of the effects of an animal’s genes as a whole l Genomic evaluations based on DNA markers l Single nucleotide polymorphism (SNP) markers abundant and cheap to read l Genotypes from Illumina BovineSNP50, 3K and HD BeadChips l 3 possible genotypes across 2 chromosomes at each SNP (AA, AB, BB) or (2, 1, 0)

13. G.R. Wiggans 2010 DCRC 2010 Conference (13) What’s whole-genome selection? l Many markers used to track inheritance of chromosomal segments l Impact of each segment on each trait is estimated l Estimates combined with traditional predicted transmitting abilities (PTA) to produce genomic PTA l Animals can be selected shortly after birth

14. G.R. Wiggans 2010 DCRC 2010 Conference (14) What’s a SNP? l Place on chromosome where animals differ in nucleotides (A, C, T, or G) l Usually not part of gene that controls trait (quantitative trait locus; QTL) l With enough SNP, association between SNP and QTL alleles enables useful evaluations l SNP chosen to be distributed evenly and have both alleles well represented in population

15. G.R. Wiggans 2010 DCRC 2010 Conference (15) Source of genomic evaluations l DNA extracted from blood, hair, semen, nasal swab, or ear punch l 43,382 SNP evaluated l SNP effect is difference in PTA from having 1 more A allele (BB to AB, or AB to AA)

16. G.R. Wiggans 2010 DCRC 2010 Conference (16) Present

17. G.R. Wiggans 2010 DCRC 2010 Conference (17) Steps to prepare genotypes l Nominate animal for genotyping l Collect DNA containing sample w Blood may not be suitable for twins l Send to laboratory for extraction l Transfer DNA to BeadChip for 3-day genotyping process

18. G.R. Wiggans 2010 DCRC 2010 Conference (18) Steps to prepare genotypes (cont.) l Read red/green intensities from chip l Call genotypes from clusters l Send genotypes to AIPL l Check genotypes for duplicates, parent- progeny conflicts, breed, and wrong sex

19. G.R. Wiggans 2010 DCRC 2010 Conference (19) Before clustering adjustment 86% call rate

20. G.R. Wiggans 2010 DCRC 2010 Conference (20) After clustering adjustment 100% call rate

21. G.R. Wiggans 2010 DCRC 2010 Conference (21) What can go wrong l Sample doesn’t provide adequate DNA quality or quantity l Genotype has many SNP that can’t be determined (90% call rate required) l Parent-progeny conflicts w Pedigree error w Sample ID error w Laboratory error w Unrelated animal qualifies as parent or progeny

22. G.R. Wiggans 2010 DCRC 2010 Conference (22) Parent-progeny conflict Parent 10212002101201211001020120100 Progeny 10202010100200221001120120220

23. G.R. Wiggans 2010 DCRC 2010 Conference (23) Parent-Progeny conflicts l For animal w Pedigree wrong w Genotype unreliable (3K) l For SNP w SNP unreliable w Clustering needs adjustment

24. G.R. Wiggans 2010 DCRC 2010 Conference (24) Parent-Progeny conflict resolution l Animal checked against all other genotypes l Usually true sire is found when there is a conflict w Requester must confirm new parent l Conflict declared when parent-progeny relationship detected that is not in pedigree w Split embryo duplicate of parent w Sample ID error on genomic parent/progeny

25. G.R. Wiggans 2010 DCRC 2010 Conference (25) Genotype extraction l For animals with > 1 genotype, missing values filled in from other genotypes l For split embryos and clones, all assigned the same genotype l SNP level parent-progeny conflicts resolved by setting SNP with fewest confirmations to missing

26. G.R. Wiggans 2010 DCRC 2010 Conference (26) Chips l BovineSNP50 w Version 1 54,001 SNP w Version 2 54,609 SNP w 43,382 used in evaluations l 3K w 2900 SNP w 2706 used in evaluations l HD w 777,963 SNP w Not yet in use, > 300 in database

27. G.R. Wiggans 2010 DCRC 2010 Conference (27) 3K chip l 2900 SNP mostly from SNP50 chip w 14 Y Chr SNP included for sex validation w Evenly spaced across 30 Chr l Developed to reduce cost of genotyping l 2706 SNP used after removing poor performers l Rapid adoption, 3,807 animal genotypes submitted for Nov. genomic evaluation

28. G.R. Wiggans 2010 DCRC 2010 Conference (28) Imputation l Based on splitting the genotype into individual chromosomes (maternal & paternal contributions) l Missing SNP approximated by tracking inheritance from ancestors and descendents l Imputed Dams increase predictor population l 3K & 50K genotypes merged by imputing SNP not on 3K

29. G.R. Wiggans 2010 DCRC 2010 Conference (29) Genotyped Holsteins Date Young animals** All animals Bulls*Cows* Bulls Heifers 04-09 7,600 2,711 9,690 1,94321,944 01-10 8,974 4,348 14,061 6,03133,414 02-10 9,378 5,086 15,328 7,62037,412 04-10 9,770 7,415 16,007 8,63041,822 05-10 9,958 7,940 16,594 9,77244,264 06-10 9,958 8,122 17,507 10,71346,300 07-10 9,963 8,18618,18711,30947,645 08-1010,430 9,37218,65211,02149,475 09-1010,611 9,45319,38913,33352,786 10-1010,616 9,78720,18415,28855,877 11-1010,61910,17520,83617,09558,727 *Traditional evaluation **No traditional evaluation

30. G.R. Wiggans 2010 DCRC 2010 Conference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enotype for Elevation l Chromosome 1

31. G.R. Wiggans 2010 DCRC 2010 Conference (31) 10212221010210210111021101121122112110022020002220 20002020220000022002022220220200002002022222200002 02222000002202000020022002000000222200022220000000 00002022202200200022202022222000220222222222000020 02202022202000200022000000002202220000002200202000 22220020200200202022202222222202220200020220220222 20202220202020220002200222022002220000022020000200 20020002002222200022220202002220022202000020200000 02222202020000200200222200020220222200220002222022 00222202020002202202222002220022000200220200000220 02202220000220000220002222020022220002200200202022 02000222000222002220220220000022022002002002022000 20002222022002220020220200222202220000020220002020 02020200022002200000220222002022202000220020002000 22002002000200220222220022022000200002000200002022 00202202002000022200002220020002002220000220220020 02200220220202020202020002220200022020020220222022 00002020200002020200022222200222200020022022220000 020220020200202022022020200002000200220220002200 Genotype for inbred bull (Megastar) l Chromosome 24 Double grandson of Aerostar

32. G.R. Wiggans 2010 DCRC 2010 Conference (32) X Chromosome Bull 202220200002022220002020222020202 Cow 1201201212222010111022210210212022

33. G.R. Wiggans 2010 DCRC 2010 Conference (33) Data and evaluation flow Animal Improvement Programs Laboratory, USDA AI organizations, breed associations Dairy producers DNA laboratories samples genotypes nominations evaluations

34. G.R. Wiggans 2010 DCRC 2010 Conference (34) Adjustment of Cow Evaluations l Traditional cow evaluations inflated compared to bull evaluations l US industry wanted cow’s own performance to influence genomic evaluations. Most countries use only bull evaluations for SNP effect estimation l Information from genotyped cows did not increasing reliability of yield traits l Cow contributions adjusted to be comparable to those from bulls

35. G.R. Wiggans 2010 DCRC 2010 Conference (35) Holstein prediction accuracy Trait a Bias b bREL (%)REL gain (%) Milk (kg)−4.00.9167.529.4 Fat (kg)−0.90.9673.135.0 Protein (kg) 0.60.8863.725.6 Fat (%) 0.01.0285.747.6 Protein (%) 0.00.9077.939.8 PL (months)−1.51.0464.233.2 SCS 0.00.8860.426.5 DPR (%)−0.21.0846.817.0 Sire CE 1.00.7940.913.8 Daughter CE−1.00.9344.318.1 Sire SB 2.10.8729.8 7.2 Daughter SB 0.30.8929.3 2.7 a CE = calving ease and SB = stillbirth. b 2010 deregressed value – 2006 genomic evaluation.

36. G.R. Wiggans 2010 DCRC 2010 Conference (36) Reliabilities for young bulls GPTATraditional PA

37. G.R. Wiggans 2010 DCRC 2010 Conference (37) Holstein Protein SNP Effects

38. G.R. Wiggans 2010 DCRC 2010 Conference (38) Use of genomic evaluations l Determine which young bulls to bring into AI service l Use to select mating sires l Pick bull dams l Market semen from 2-year-old bulls

39. G.R. Wiggans 2010 DCRC 2010 Conference (39) Use of 3K genomic evaluations l Sort heifers for breeding w Flush w Sexed semen w Beef bull l Confirm parentage to avoid inbreeding l Predict inbreeding depression better l Precision mating considering genomics (future)

40. G.R. Wiggans 2010 DCRC 2010 Conference (40) Updates between trad. evaluations l Genomic evaluations calculated every month l Evaluations not released for animals that already have an official evaluation l Evaluations of new animals distributed to owners w Females by breed associations w Males by NAAB

41. G.R. Wiggans 2010 DCRC 2010 Conference (41) Impact on producers l Young-bull evaluations with accuracy of early 1st­ crop evaluations l AI organizations marketing genomically evaluated 2-year-olds l Bull dams likely to be required to be genotyped l Rate of genetic improvement likely to increase by up to 50% l Progeny-test programs changing

42. G.R. Wiggans 2010 DCRC 2010 Conference (42) International implications l All major dairy countries investigating genomic selection l Interbull working on how genomic evaluations should be integrated l European collaboration to share genotypes l Large number of predictor animals increases prediction accuracy l Importing countries changing rules to allow for genomically evaluated young bulls

43. G.R. Wiggans 2010 DCRC 2010 Conference (43) Future

44. G.R. Wiggans 2010 DCRC 2010 Conference (44) Increase in accuracy l Genotyped bulls get traditional evaluation when 5 years old l Possible genotyping of 10,000 bulls with semen in CDDR l Collaboration with more countries l Use of more SNP from HD chips l Full sequencing

45. G.R. Wiggans 2010 DCRC 2010 Conference (45) Application to more traits l Animal’s genotype is 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?

46. G.R. Wiggans 2010 DCRC 2010 Conference (46) Summary l Extraordinarily rapid implementation of genomic evaluations l Young-bull acquisition and marketing now based on genomic evaluations l Genotyping of many females because of 3K chip

47. G.R. Wiggans 2010 DCRC 2010 Conference (47)