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Haplotypes and imputed genotypes in diverse human populations

Haplotypes and imputed genotypes in diverse human populations. Noah Rosenberg April 29, 2009. Human Genome Diversity Cell Line Panel. 525,910 single-nucleotide polymorphisms in 29 populations. M Jakobsson et al. (2008) Nature 451:998-1003. Overview.

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Haplotypes and imputed genotypes in diverse human populations

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  1. Haplotypes and imputed genotypes in diverse human populations Noah Rosenberg April 29, 2009

  2. Human Genome Diversity Cell Line Panel 525,910 single-nucleotide polymorphisms in 29 populations M Jakobsson et al. (2008) Nature 451:998-1003

  3. Overview • How do we measure and compare haplotype diversity across populations? • Imputation in diverse populations

  4. Which populations and genomic sites have more haplotype diversity? Population 1 Population 2

  5. Which populations and genomic sites have more haplotype diversity? Population 1 Population 2

  6. Which populations and genomic sites have more haplotype diversity? Population 1 Population 2 P Scheet, M Stephens (2006) AJHG 78:629-644

  7. Which populations and genomic sites have more haplotype diversity? Population 1 Blue

  8. Which populations and genomic sites have more haplotype diversity? Population 1 Blue Green

  9. Which populations and genomic sites have more haplotype diversity? Population 1 Blue Green Orange

  10. Which populations and genomic sites have more haplotype diversity? Population 1 Blue Green Orange Pink

  11. Which populations and genomic sites have more haplotype diversity? Population 1 Blue Green Orange Pink Yellow

  12. Which populations and genomic sites have more haplotype diversity?

  13. Which populations and genomic sites have more haplotype diversity? Population 1 Less diversity Population 2 More diversity

  14. Haplotype cluster frequencies for a “typical” genomic region M Jakobsson et al. (2008) Nature 451:998-1003

  15. More haplotype diversity in Africa C Asia Europe America Oceania East Asia Africa Middle East M Jakobsson et al. (2008) Nature 451:998-1003

  16. Less haplotype homozygosity and more haplotype diversity in Africa M Jakobsson et al. (2008) Nature 451:998-1003

  17. Genetic diversity declines with distance from Africa Haplotype heterozygosity

  18. Haplotype clusters recover population structure Europe Middle East Central/South Asia America East Asia Oceania Africa M Jakobsson et al. (2008) Nature 451:998-1003

  19. Haplotype clusters recover population structure M Jakobsson et al. (2008) Nature 451:998-1003

  20. Low haplotype diversity in the lactase region in Europe C Asia Europe America Oceania East Asia Africa Middle East M Jakobsson et al. (2008) Nature 451:998-1003

  21. Lactase region Haplotype cluster homozygosity as a test for selection Random region M Jakobsson et al. (2008) Nature 451:998-1003

  22. Haplotype diversity – summary • Haplotype clusters can be used to encode haplotypes pointwise for measurement of diversity • Haplotype cluster diversity is greatest in Africa • Low haplotype cluster diversity can potentially be used to detect selection

  23. Overview • Measuring haplotype diversity using haplotype clusters • Imputation in diverse populations

  24. Reference panel Imputed genotypes can be tested for disease association Genotyped positions Study sample Genotypes can be imputed using a reference panel – but imperfectly

  25. Evaluating imputation accuracy in worldwide populations • 443 individuals in 29 populations from the Human Genome Diversity Panel • Genotypes at >500,000 SNPs (Jakobsson et al. Nature 451:998-1003, 2008) • 420 HapMap reference haplotypes of ~2,000,000 SNPs, omitting offspring in trios • Randomly hide 15% genotypes in HGDP individuals and impute with MACH • Measure the proportion of alleles imputed correctly

  26. Imputation accuracy is predicted by haplotype diversity Imputation accuracy L Huang et al. (2008) AJHG 84:235-250

  27. Imputation accuracy is greatest with a close reference panel L Huang et al. (2008) AJHG 84:235-250

  28. Highest-accuracy reference panels match geographic locations Africa Europe/ W Asia E Asia/ Oceania/ Americas L Huang et al. (2008) AJHG 84:235-250

  29. Imputation accuracy can be increased using HapMap mixtures • Instead of imputing based on separate HapMap panels, impute from mixtures • Choose mixtures to have optimal size given specified ratios L Huang et al. (2008) AJHG 84:235-250

  30. Imputation accuracy can be increased using HapMap mixtures L Huang et al. (2008) AJHG 84:235-250

  31. Summary – imputation accuracy • Strategies to improve imputation studies • -Increased sample size • -Improved imputation algorithms • -Improved use of reference panels • -Development of additional reference panels • -Improved haplotyping • -Use of additional data from relatives

  32. Imputation – summary • Imputation error and sample size inflation are greatest in Africa • Several strategies may be available for improving imputation, including use of mixtures

  33. Rosenberg lab James Degnan Mike DeGiorgio Lucy Huang Mattias Jakobsson Trevor Pemberton Paul Scheet Zach Szpiech Jenna VanLiere Chaolong Wang Collaborators Goncalo Abecasis (Michigan) Raph Gibbs (NIA) John Hardy (UCL) Yun Li (Michigan) Sonja Scholz (NIA) Andy Singleton (NIA) Funding Alfred P. Sloan Foundation Burroughs Wellcome Fund National Institutes of Health U of M Rackham Graduate School [M DeGiorgio] U of M Center for Genetics in Health and Medicine [M Jakobsson]

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