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Reliability of Genomic Predictions for North American Dairy Bulls

Reliability of Genomic Predictions for North American Dairy Bulls. Sequencing and Genotyping. Cattle genome sequenced in 2004 30 chromosome pairs (including X,Y) 3 billion letters from each parent Illumina BovineSNP50 BeadChip 58,000 genetic markers in 2007

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Reliability of Genomic Predictions for North American Dairy Bulls

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  1. Reliability of Genomic Predictions for North American Dairy Bulls

  2. Sequencing and Genotyping • Cattle genome sequenced in 2004 • 30 chromosome pairs (including X,Y) • 3 billion letters from each parent • Illumina BovineSNP50 BeadChip • 58,000 genetic markers in 2007 • 38,416 used in genomic predictions • Current cost <$250 per animal

  3. Experimental Design • Compute genomic evaluations and parent averages from 2003 data • 3576 older Holstein bulls born 1952-1998 • Compare ability to predict daughter deviations in 2008 data • 1759 younger bulls born 1999-2002 • Test results for 27 traits: 5 yield, 5 health, 16 conformation, and Net Merit

  4. Genotyped Animals (n=6005)As of April 2008

  5. Genomic Methods • Direct genomic evaluation • Inversion for linear prediction, REL • Iteration for nonlinear prediction • Combined genomic evaluation • 3 x 3 selection index combining direct genomic PTA, traditional PA or PTA, and subset PA or PTA by REL

  6. Marker Effects for Net Merit

  7. Significance Tests for Net Merit

  8. Major Gene on Chromosome 18Net Merit, Productive Life, Calving Ease, Stature, Strength, Rump Width

  9. Marker Effects for Milk

  10. Marker Effects for Final Score

  11. Linear and Nonlinear Predictions • Linear model • Infinitesimal alleles model in which all loci have non-zero effects • Nonlinear models • Model A: infinitesimal alleles with a heavy-tailed prior • Model B: finite locus model with normally-distributed marker effects • Model AB: finite locus model with a heavy-tailed prior

  12. Nonlinear and Linear Regressions for marker allele effects

  13. R2 for linear and nonlinear predictions

  14. R2 vs. Reliability • Adjust the observed genomic R2 • Daughter deviations contain error • Divide by REL of 2008 deviations • Parents are selected • Add difference of PA R2 from expected • Adjust theoretical genomic REL • Genotypes contain a few errors • QTLs are located between SNPs

  15. R2 and Reliabilities for Traditional and Genomic Predictions

  16. R2 and Reliabilities for Traditional and Genomic Predictions

  17. Reliability Gains for Proven Bulls • Bulls included in test had: • >10 daughters in August 2003 • >10% increase in reliability by 2008 • Numbers of bulls in test ranged from 104 to 735 across traits • Predicted the change in evaluation • Significant increase in R2 (P < .001) for 26 of 27 traits

  18. Net Merit by Chromosome for O ManTop bull for Net Merit

  19. SNPs on X Chromosome • Each animal has two evaluations: • Expected genetic merit of daughters • Expected genetic merit of sons • Difference is sum of effects on X • SD = .1 σG, smaller than expected • Correlation with sire’s daughter vs. son PTA difference was significant (P<.0001), regression close to 1.0

  20. X, Y, Pseudo-autosomal SNPs 35 SNPs 35 SNPs 0 SNPs 487 SNPs

  21. Clones and Identical Twins21HO2121, 21HO2125, 21HO2100, CAN6139300, CAN6139303

  22. Value of Genotyping More SNP9,604 (10K), 19,208 (20K), and 38,416 (40K) SNP

  23. Value of Genotyping More Bulls

  24. Simulated ResultsWorld Holstein Population • 15,197 older and 5,987 younger bulls in Interbull file • 40,000 SNPs and 10,000 QTLs • Provided timing, memory test • Reliability vs parent average REL • REL = corr2 (EBV, true BV) • 80% vs 34% expected for young bulls • 72% vs 30% observed in simulation

  25. Brown Swiss Results • Nearly all proven bulls genotyped • Data from 225 bulls born before 1999 • Predict 118 bulls born during or after 1999 • Gains in young bull reliability • Expected to be 1% to 3% • Actual gains were about 2% for yield • Little or no gain for other traits • Cooperation with Europe is needed

  26. Jersey Genotypes • Same experimental design • DNA available for 766 bulls • Total of 594 genotyped as of June • Results not available yet • Gains in reliability expected to be proportional to number of bulls genotyped

  27. Expected vs Observed ReliabilityHolsteins • Reliability for predictee bulls • Traditional PA: 27% average across traits • Genomic: 63% expected vs. 50% observed • Observed range 78% (fat pct) to 31% (SCE) • PTA regressions .8 to .9 of expected • Multiply genomic daughter equivalents by .7 to make expected closer to observed • For example, 16 * .7 = 11 • Include polygenic effect, less than 5%

  28. Genetic ProgressHolsteins • Assume 60% REL for net merit • Sires mostly 2 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

  29. Genetic Evaluation Advancesand increases in genetic progress

  30. How Related are Relatives?Correction • Example: Full sibs • Share 50% ± 5% of their DNA on average (in cattle) • SD 3.5% reported previously was low • For any diploid species, general formula is 50% ± 50% / [2(C + L)].5, where C is number of chromosomes and L is genome length in Morgans

  31. Conclusions • Genomic predictions significantly better than parent average (P < .0001) for all 26 traits tested • Gains in reliability equivalent on average to 11 daughters with records • Analysis used 3576 historical bulls • April data included 5285 proven bulls • High REL requires many genotypes

  32. Acknowledgments • Genotyping and DNA extraction: • BFGL, U. Missouri, U. Alberta, GeneSeek, GIFV, and Illumina • Computing: • AIPL staff (Mel Tooker, Leigh Walton, etc.) • Funding: • National Research Initiative grants • 2006-35205-16888, 2006-35205-16701 • Agriculture Research Service • Contributors to Cooperative Dairy DNA Repository (CDDR)

  33. CDDR Contributors • National Association of Animal Breeders (NAAB, Columbia, MO) • ABS Global (DeForest, WI) • Accelerated Genetics (Baraboo, WI) • Alta (Balzac, AB) • Genex (Shawano, WI) • New Generation Genetics (Fort Atkinson, WI) • Select Sires (Plain City, OH) • Semex Alliance (Guelph, ON) • Taurus-Service (Mehoopany, PA)

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