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Use of Haplotypes to Predict Selection Limits and Mendelian Sampling

Use of Haplotypes to Predict Selection Limits and Mendelian Sampling. Introduction. Mendelian sampling is the difference between an individual's PTA and its PA Sustained genetic gain under selection depends on Mendelian sampling variance (Woolliams et al., 1999)

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Use of Haplotypes to Predict Selection Limits and Mendelian Sampling

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  1. Use of Haplotypes to Predict Selection Limits and Mendelian Sampling

  2. Introduction • Mendelian sampling is the difference between an individual's PTA and its PA • Sustained genetic gain under selection depends on Mendelian sampling variance (Woolliams et al., 1999) • Increased reliabilities from genomic selection due to better estimates of Mendelian sampling (Hayes et al., 2009)

  3. Introduction (cont’d) • You do not benefit substantially from genomic selection until you have a large enough pool of genotyped animals to provide good estimates of marker effects • Good marker effects are essential for reliable prediction of Mendelian sampling

  4. Objectives • Describe the predicted Mendelian sampling (MS) variation in Brown Swiss, Holstein, and Jersey cattle • Calculate selection limits based on haplotypes present in the genotyped population • Examine adjustments to breeding values for changes in heterozygosity

  5. Materials • 43,382 SNP from the Illumina BovineSNP50 • SNP solutions from the June, 2010 evaluation • Three breeds • 1,455 Brown Swiss males and females • 40,351 Holstein males and females • 4,064 Jersey males and females • Three traits • Daughter pregnancy rate (DPR) • Milk yield (Milk) • Lifetime net merit (NM$)

  6. Methods • Haplotypes imputed with findhap.f90 (VanRaden et al., 2010) • Calculations and simulations performed with SAS 9.2 • Plots produced with R 2.10.1 and ggplot2 0.8.7 (Wickham, 2009) • Operating system is 64-bit RedHat Enterprise Linux 5

  7. Predicted Mendelian sampling • Lower bound assumes all SNP on a chromosome are unlinked • Upper bound assumes all SNP on a chromosome are perfectly linked • “I have discovered a truly marvelous proof…this slide is too narrow to contain it” • Also could be calculated from linkage disequilibrium blocks

  8. Distribution of Mendelian sampling variance

  9. Predicted Mendelian sampling variance

  10. Why are Holsteins so different? • There are many more HO haplotypes represented • There are multiple QTL affecting NM$ in HO

  11. Sampling variance over time — DPR BS HO JE

  12. Sampling variance over time — Milk BS HO JE

  13. Sampling variance over time — NM$ BS HO JE

  14. Correlations with inbreeding

  15. Selection limits • Lower bound found by summing the best chromosomes • Upper bound found by summing the best alleles at each locus • NM$ was adjusted to account for changes in heterozygosity

  16. Calculated selection limits

  17. Adjusting for heterozygosity • Chromosomal EBV for NM$ were adjusted by adding or subtracting 6% of an additive genetic standard deviation ($11.88) per 1% change in heterozygosity (Smith et al., 1998) • Only 4 chromosomes (BTA 6, 10, 14, and 16) differed between the adjusted and unadjusted groups

  18. What’s the best cow we can make? A “Supercow” constructed from the best haplotypes in the Holstein population would have an EBV(NM$) of $7515

  19. Conclusions • Selection limits and sampling variances differ among breeds • Sampling variance has decreased slightly over time • The top animals in each breed are well below predicted selection limits • Adjustment for heterozygosity had little effect on breeding values for NM$

  20. Questions?

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