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Using Haplotypes in Breeding Programs

Using Haplotypes in Breeding Programs. What is imputation?. Prediction of unknown genotypes from observed genotypes Pedigree haplotyping Matching allele patterns Genotypes indicate how many copies of each allele were inherited Haplotypes indicate which alleles are on which chromosome.

francis-mcneil
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Using Haplotypes in Breeding Programs

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  1. Using Haplotypes in Breeding Programs

  2. What is imputation? • Prediction of unknown genotypes from observed genotypes • Pedigree haplotyping • Matching allele patterns • Genotypes indicate how many copies of each allele were inherited • Haplotypes indicate which alleles are on which chromosome

  3. Why impute haplotypes? • Predict dam from progeny SNP • Predict unknown SNP from known • Measure 3,000, predict 50,000 SNP • Measure 50,000, predict 850,000 • Measure each haplotype at highest density only a few times • Increase reliabilities

  4. How does imputation work? • Identify haplotypes in population using many markers • Track haplotypes with fewer markers • e.g., track a 20 SNP block with 4 SNP • 4 SNP: 2202 • 20 SNP: 20220200020020020002

  5. How well does haplotyping work? • Half of young animals assigned 3K • Proven bulls, cows all had 50K • Dams imputed using 50K and 3K • Half of ALL animals assigned 3K • Could 3K CDDR genotypes help? • 10,000 proven bulls yet to genotype • Should cows with 3K be predictors?

  6. Correlations of 3K and PA with 50K Half ofyoung animals had 3K PTA, half had 50K PTA

  7. Using 3K as reference genotypes Half ofALL animal NM$ were from 3K, half 50K

  8. What about the HD chip? • In simulation, reliability averaged 84.0% for 500K SNP versus 82.6% for 50K SNP • Haplotypes can fill in almost all missing SNP when moving from 50K to 500K

  9. Selection limits and Mendelian sampling • Genotypes for 43,385 SNP using the Illumina BovineSNP50 • Haplotypes imputed with findhap.f90 (VanRaden et al., 2010) • 1,455 Brown Swiss bulls and cows • 40,351 Holstein bulls and cows • 4,064 Jersey bulls and cows • Results shown for net merit

  10. How far can we go with selection?

  11. How much sampling variance is there?

  12. Why are HO different from BS and JE? BS & JE: No QTL HO: Multiple QTL for NM$ ― DGAT1 on BTA 14, AIPL marker on BTA 18

  13. What can we conclude? • Higher densities probably less valuable than additional animals • Imputation can accurately fill in missing SNP when moving from lower to higher densities • Selection limits and sampling variances differ among breeds

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