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John B. Cole
Animal Improvement Programs Laboratory
Agricultural Research Service, USDA
Beltsville, MD 20705-2350, USA
joh...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (2) Cole
History
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (3) Cole
Why genomics works in dairy
 Extensive ...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (4) Cole
History of genomic evaluations
 Dec. 20...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (5) Cole
Current sources of data
AIPL CDCB
NAAB
P...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (6) Cole
Sources of genomic data
Genomic
Evaluati...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (7) Cole
Successes
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (8) Cole
Many animals have been genotyped
0
30000...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (9) Cole
Calculation of genomic evaluations
 Der...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (10) Cole
Genetic merit of Jersey bulls
0
100
200...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (11) Cole
What is a SNP genotype worth?
For the p...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (12) Cole
And for daughter pregnancy rate (h2=0.0...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (13) Cole
Holstein prediction accuracy
Traita Bia...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (14) Cole
Many chips are available
 BovineSNP50
...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (15) Cole
Genotypes and haplotypes
 Genotypes in...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (16) Cole
O-Style Haplotypes Chromosome 15
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (17) Cole
Haplotyping program – findhap.f90
 Beg...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (18) Cole
Recessive defect discovery
 Check for ...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (19) Cole
We’re working on new tools
Cole, J.B., ...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (20) Cole
Impact on producers
 Young-bull evalua...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (21) Cole
Challenges
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (22) Cole
Input costs are rising quickly
0
0.5
1
...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (23) Cole
 Expected value of Mendelian sampling ...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (24) Cole
 Bulls born in 2008, progeny tested in...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (25) Cole
 1-Step to incorporate genotypes
 Fle...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (26) Cole
Inbreeding continues to increase
Cole, ...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (27) Cole
Genomic vs. Pedigree Inbreeding
Bull Pe...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (28) Cole
Loss-of-function mutations
 At least 1...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (29) Cole
Unknown phenotypes
 Susceptibility to ...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (30) Cole
Across-breed evaluations
 Method 1 est...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (31) Cole
Across-breed evaluations - conclusions
...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (32) Cole
The IP land grab
Provisional US patent ...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (33) Cole
Conclusions
 Genomic selection has bee...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (34) Cole
Acknowledgments
 Genotyping and DNA ex...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (35) Cole
CDDR Contributors
 National Associatio...
National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (36) Cole
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Challenges and successes in dairy cattle genomics

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Presentation on the status of genomics in dairy cattle presented to the National Swine Improvement Federation in Kansas City, MO, in November 2012.

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Challenges and successes in dairy cattle genomics

  1. 1. John B. Cole Animal Improvement Programs Laboratory Agricultural Research Service, USDA Beltsville, MD 20705-2350, USA john.cole@ars.usda.gov Challenges and successes in dairy cattle genomics
  2. 2. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (2) Cole History
  3. 3. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (3) Cole Why genomics works in dairy  Extensive historical data available  Well-developed genetic evaluation program  Widespread use of AI sires  Progeny test programs  High valued animals, worth the cost of genotyping  Long generation interval which can be reduced substantially by genomics
  4. 4. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (4) Cole History of genomic evaluations  Dec. 2007 BovineSNP50 BeadChip available  Apr. 2008 First unofficial evaluation released  Jan. 2009 Genomic evaluations official for Holstein and Jersey  Aug. 2009 Official for Brown Swiss  Sept. 2010 Unofficial evaluations from 3K chip released  Dec. 2010 3K genomic evaluations to be official  Sept. 2011 Infinium BovineLD BeadChip available
  5. 5. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (5) Cole Current sources of data AIPL CDCB NAAB PDCA DHI Universities AIPL Animal Improvement Programs Lab., USDA CDCB Council on Dairy Cattle Breeding DHI Dairy Herd Improvement (milk recording organizations) NAAB National Association of Animal Breeders (AI) PDCA Purebred Dairy Cattle Association (breed registries)
  6. 6. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (6) Cole Sources of genomic data Genomic Evaluation Lab Requester (Ex: AI, breeds) Dairy producers DNA laboratories samples
  7. 7. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (7) Cole Successes
  8. 8. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (8) Cole Many animals have been genotyped 0 30000 60000 90000 120000 150000 180000 1004 1008 1012 1104 1108 1112 1204 1208 Bulls Cows Evaluation Date (YYMM) Genotypes
  9. 9. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (9) Cole Calculation of genomic evaluations  Deregressed values derived from traditional evaluations of predictor animals  Allele substitutions random effects estimated for 45,187 SNP  Polygenic effect estimated for genetic variation not captured by SNP  Selection Index combination of genomic and traditional not included in genomic  Applied to yield, fitness, calving, and type traits
  10. 10. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (10) Cole Genetic merit of Jersey bulls 0 100 200 300 400 500 600 2006 2007 2008 2009 2010 Active Genotyped Breeding Year NetMerit($)
  11. 11. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (11) Cole What is a SNP genotype worth? For the protein yield (h2=0.30), the SNP genotype provides information equivalent to an additional 34 daughters Pedigree is equivalent to information on about 7 daughters
  12. 12. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (12) Cole And for daughter pregnancy rate (h2=0.04), SNP = 131 daughters What is a SNP genotype worth?
  13. 13. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (13) Cole Holstein prediction accuracy Traita Biasb b REL (%) REL gain (%) Milk (kg) −64.3 0.92 67.1 28.6 Fat (kg) −2.7 0.91 69.8 31.3 Protein (kg) 0.7 0.85 61.5 23.0 Fat (%) 0.0 1.00 86.5 48.0 Protein (%) 0.0 0.90 79.0 40.4 PL (months) −1.8 0.98 53.0 21.8 SCS 0.0 0.88 61.2 27.0 DPR (%) 0.0 0.92 51.2 21.7 Sire CE 0.8 0.73 31.0 10.4 Daughter CE −1.1 0.81 38.4 19.9 Sire SB 1.5 0.92 21.8 3.7 Daughter SB − 0.2 0.83 30.3 13.2 a PL=productive life, CE = calving ease and SB = stillbirth. b 2011 deregressed value – 2007 genomic evaluation.
  14. 14. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (14) Cole Many chips are available  BovineSNP50  Version 1 54,001 SNP  Version 2 54,609 SNP  45,187 used in evaluations  HD  777,962 SNP  Only 50K SNP used,  >1700 in database  LD  6,909 SNP  Replaced 3K HD 50KV2 LD
  15. 15. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (15) Cole Genotypes and haplotypes  Genotypes indicate how many copies of each allele were inherited  Haplotypes indicate which alleles are on which chromosome  Observed genotypes partitioned into the two unknown haplotypes  Pedigree haplotyping uses relatives  Population haplotyping finds matching allele patterns
  16. 16. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (16) Cole O-Style Haplotypes Chromosome 15
  17. 17. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (17) Cole Haplotyping program – findhap.f90  Begin with population haplotyping  Divide chromosomes into segments, ~250 to 75 SNP / segment  List haplotypes by genotype match  Similar to fastPhase, IMPUTE  End with pedigree haplotyping  Detect crossover, fix noninheritance  Impute nongenotyped ancestors
  18. 18. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (18) Cole Recessive defect discovery  Check for homozygous haplotypes  7 to 90 expected but none observed  5 of top 11 are potentially lethal  936 to 52,449 carrier sire-by-carrier MGS fertility records  3.1% to 3.7% lower conception rates  Some slightly higher stillbirth rates  Confirmed Brachyspina same way
  19. 19. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (19) Cole We’re working on new tools Cole, J.B., and Null, D.J. 2012. AIPL Research Report GENOMIC2: Use of chromosomal predicted transmitting abilities. Available: http://aipl.arsusda.gov/reference/chromosomal_pta_query.html.
  20. 20. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (20) Cole Impact on producers  Young-bull evaluations with accuracy of early 1st-crop evaluations  AI organizations marketing genomically evaluated 2- year-olds  Genotype usually required for cow to be bull dam  Rate of genetic improvement likely to increase by up to 50%  Studs reducing progeny-test programs
  21. 21. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (21) Cole Challenges
  22. 22. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (22) Cole Input costs are rising quickly 0 0.5 1 1.5 2 2.5 3 1 2 3 4 5 6 7 8 9 10 11 12 2010 2011 2012 M:FP = price of a kg of milk / price of a kg of a 16% protein ration Month Milk:FeedPriceRatio July 2012 Grain Costs Soybeans: $15.60/bu (€0.46/kg) Corn: $ 7.36/bu (€0.23/kg)
  23. 23. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (23) Cole  Expected value of Mendelian sampling no longer equal to 0  Key assumption of animal models  References:  Patry, Ducrocq 2011 GSE 43:30  Vitezica et al 2011 Genet Res (Camb) pp. 1–10. Bias from Pre-Selection
  24. 24. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (24) Cole  Bulls born in 2008, progeny tested in 2009, with daughter records in 2012, were pre-selected:  3,434 genotyped vs. 1,096 sampled  Now >10 genotyped per 1 marketed  Potential for bias:  178 genotyped progeny  32 sons progeny tested Pre-Selection Bias Now Beginning
  25. 25. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (25) Cole  1-Step to incorporate genotypes  Flexible models, many recent studies  Foreign data not yet included  Multi-step GEBV, then insert in AM  Same trait (Ducrocq and Liu, 2009)  Or correlated trait (Mantysaari and Stranden, 2010; Stoop et al, 2011)  Foreign genotyped bulls included Methods to Reduce Bias
  26. 26. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (26) Cole Inbreeding continues to increase Cole, J.B., and P.M. VanRaden. 2011. Use of haplotyes to estimate Mendelian sampling effects and selection limits. J. Anim. Breed. Genet. 128(6):448-455.
  27. 27. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (27) Cole Genomic vs. Pedigree Inbreeding Bull Pedigree F Genomic F O Man 4.5 15.8 Ramos 2.3 11.5 Shottle 5.6 11.9 Planet 6.7 18.8 Earnit 6.2 12.8 Nifty 3.1 11.7 Correlation = .68
  28. 28. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (28) Cole Loss-of-function mutations  At least 100 LoF per human genome surveyed (MacArthur et al., 2010)  Of those genes ~20 are completely inactivated  Previously uncharacterized LoF variants likely to have phenotypic effects  How can mating programs deal with this?
  29. 29. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (29) Cole Unknown phenotypes  Susceptibility to disease  e.g., Johne’s is difficult to diagnose,  Differential response to management  Conversion efficiency of different rations  Response to superovulation  Resistance to heat stress
  30. 30. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (30) Cole Across-breed evaluations  Method 1 estimated SNP effects within breed then applied those effects to the other breeds  Method 2 (across-breed) used a common set of SNP effects from the combined breed genotypes and phenotypes  Method 3 (multi-breed) used a correlated SNP effects using a multi-trait method
  31. 31. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (31) Cole Across-breed evaluations - conclusions  Using another breeds SNP estimates did not help  Across-breed method increased the predictive ability, however the traditional GPTA accounted for more variation than the across-breed GPTA  Multi-breed increased the predictive ability and the multi-breed GPTA accounted for more variation than the traditional GPTA
  32. 32. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (32) Cole The IP land grab Provisional US patent filed on 20 NOV 2010 after the 9WCGALP in Leipzig – no disclosure at that time! This MS with similar ideas was submitted 22 SEP 2010 and published on 12 APR 2011. Why share?
  33. 33. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (33) Cole Conclusions  Genomic selection has been very successful in the dairy industry.  The technology is widely used, and is increasing the rate of genetic progress.  Several challenges remain, particularly pre-selection bias and across-breed genomics.
  34. 34. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (34) Cole 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)  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)
  35. 35. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (35) Cole CDDR Contributors  National Association of Animal Breeders (NAAB, Columbia, MO)  ABS Global (DeForest, WI)  Accelerated Genetics (Baraboo, WI)  Alta (Balzac, AB, Canada)  Genex (Shawano, WI)  New Generation Genetics (Fort Atkinson, WI)  Select Sires (Plain City, OH)  Semex Alliance (Guelph, ON, Canada)  Taurus-Service (Mehoopany, PA)
  36. 36. National Swine Improvement Federation, Kansas City, MO, 29 November 2012 (36) Cole Questions?

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