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Meiotic gene conversion in humans: rate, sex ratio, and GC bias

Meiotic gene conversion in humans: rate, sex ratio, and GC bias. Amy L. Williams. June 19, 2013 University of Chicago. Gene conversion defined. Meiosis: produces haploid germ cells with recombinations Gene conversion: short segment copied into given chromosome from other homolog.

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Meiotic gene conversion in humans: rate, sex ratio, and GC bias

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  1. Meiotic gene conversion in humans: rate, sex ratio, and GC bias Amy L. Williams June 19, 2013University of Chicago

  2. Gene conversion defined • Meiosis: produces haploid germ cells with recombinations • Gene conversion: short segment copied into given chromosome from other homolog Two types of recombination: Meiosis Crossover GeneConversion

  3. Study question 1: gene conversion rate? • Number of gene conversions per meiosis? • 4-15× # crossovers? Jeffreys and May (2004) • Length of gene conversion tracts? • 55-290 bp? Jeffreys and May (2004)

  4. Study question 1: gene conversion rate? • Number of gene conversions per meiosis? • 4-15× # crossovers? Jeffreys and May (2004) • Length of gene conversion tracts? • 55-290 bp? Jeffreys and May (2004) • Per base-pair rate? Fraction of genome affected • R = (number × tract length) / genome length • 2.2×10-6 to 4.4×10-5? Jeffreys and May (2004)

  5. Study question 2: male vs. female rate? • Gender differences in rate? • Crossovers: female rate 1.78× male (deCODE)

  6. Study question 3 & 4: GC bias? Localization? • GC bias observed in allelic transmissions? • Crossover hot spots influence location? • Locations of gene conversions independent in a given meiosis? Myers et al., Science 2005

  7. Summary: study questions • Genome-wide de novo gene conversion rate? • Different rate between males/females? • Extent of GC bias in tracts? • Localization: Hotspots? Tracts independent?

  8. Outline • Background / study questions • Study design and methods • Results • SNP chip data • Sequence data

  9. Approaches to identify gene conversions • Linkage disequilibrium based • Can give rate estimate • Averaged over human history, both genders • Sperm-based • Many meiotic products: per-individual estimates • Single molecule: genome-wide assays difficult • Pedigree-based • De novo, per-gender events observable • Data for many samples required

  10. Study design: SNP chip data for pedigrees • Primary analysis: pedigree SNPchip data • Challenge: small tracts • Tracts covered by ≤ 1 SNP • Not all tracts covered, but stillobtain overall rate • Chip data give per base-pair rate • R = # gene conversions / # informative sites

  11. Datasets for analysis • Mexican American pedigrees • Data source 1: San Antonio Family Studies • 2,490 genotyped samples, 80 pedigrees • SNP chip genotypes (Illumina 1M, 660k) • Can estimate de novo gene conversion rate

  12. Datasets for analysis • Mexican American pedigrees • Data source 1: San Antonio Family Studies • 2,490 genotyped samples, 80 pedigrees • SNP chip genotypes (Illumina 1M, 660k) • Can estimate de novo gene conversion rate • Data source 2: T2D-GENES Consortium • 607 sequenced samples, 20 pedigrees • Whole genome sequence (Complete Genomics) • Can examine tract length, distribution, etc. • Though need deep data on single family to do so

  13. Study design: SNP chip data for pedigrees • Pedigree-based haplotypes/phasereveal recombinations • Heterozygous sites: informative for recombination • Phasing method: Hapi • Phases nuclear families • Williams et al., Genome Biol. 2010

  14. Family-based phase reveals recombinations • Hapi output: paternal haplotype transmissions Crossover: Haplotype 1 Haplotype 2

  15. Family-based phase reveals recombinations • Hapi output: paternal haplotype transmissions Crossover: Gene Conversion: Haplotype 1 Haplotype 2

  16. Other pedigree phasing methods • Most pedigree phasing methods slow • Runtime complexity for phasing ~O(m 22n) • n = # non-founders • m = # markers • Example: nuclear family with 11 children • 4,194,304 states per marker • Can merge exponential class of states • Many states extremely unlikely to be optimal

  17. Hapi: efficient phasing of nuclear families • Hapi: state space reduction improves efficiency • Merges exponential class of states • Omits states that cannot yield optimal solution • Applied to family with 11 children • Average per marker states: 4.2, maximum 48

  18. Hapi: efficient phasing of nuclear families • Hapi: state space reduction improves efficiency • Merges exponential class of states • Omits states that cannot yield optimal solution • Applied to family with 11 children • Average per marker states: 4.2, maximum 48 * Superlink failed to analyze 11 child family; 8/11 children used

  19. Hapi: efficient phasing of nuclear families • Hapi: state space reduction improves efficiency • Merges exponential class of states • Omits states that cannot yield optimal solution • Applied to family with 11 children • Average per marker states: 4.2, maximum 48 * Superlink failed to analyze 11 child family; 8/11 children used

  20. Applying Hapi to multi-generational pedigrees • Hapi currently applies to nuclear families • For 3-generation pedigrees analyzed for gene conversions, omit sites with phase conflicts • Will not bias results, but data are reduced

  21. Applying Hapi to multi-generational pedigrees • Hapi currently applies to nuclear families • For 3-generation pedigrees analyzed for gene conversions, omit sites with phase conflicts • Will not bias results, but data are reduced • Extension to Hapi possible to efficiently analyzearbitrarily large pedigrees • Most San Antonio Family Studies pedigrees too large to be phased in practical time

  22. Approach to identifying gene conversions • Perform QC, phase 3-generation pedigrees • Find gene conversions in 2ndgeneration:single SNPdouble crossovers • Confirm: • Gene converted allele in 3rdgeneration • Other allele in 2nd generation sibling(s) • False positive only if ≥ 2 genotyping errors

  23. Outline • Background / study questions • Study design and methods • Results • SNP chip data • Sequence data

  24. Current analysis dataset • Analyzed SNP chip data for 16 pedigrees • Data for both parents, 3+ children, 1+ grandchild • 190 samples • 42 meioses (21 paternal, 21 maternal) • 4.15×106 informative sites

  25. Result 1: 33 putative gene conversions, rate • Rate:7.95×10-6/bp/generation • Within range of Jeffreysand May (2004) • Close to LD-based estimates Female Male

  26. Result 1: 33 putative gene conversions, rate • Rate:7.95×10-6/bp/generation • Within range of Jeffreysand May (2004) • Close to LD-based estimates Female Are these real gene conversions? Male

  27. T2D-GENES sequence confirms events • 19 sites sequenced by T2D-GENES Consortium • 18/19 gene conversion genotypes verified • Differing site looks like sequencing artifact • 2nd generation recipient has genotype mismatch3rd generation grandchild shows same genotype • If sequence data correct,gene conversion ingrandchild

  28. Result 2: gene conversion rates by gender • More female gene conversions than male • Females transmit 1.54× males • Difference (yet) not significant – larger sample coming • Different rates expected based on crossovers • Female crossover rate 1.78× male (deCODE)

  29. Result 3: gene conversions localize in hotspots 2.71% of genome in ≥10 cM/Mb hotspots

  30. Result 3: gene conversions localize in hotspots 2.71% of genome in ≥10 cM/Mb hotspots 10/33 gene conversions with ≥10 cM/Mb: P=1.1×10-8

  31. Result 4: observe extreme GC bias • 31 GC informative sites • A/C, A/GT/C, T/G • GC transmission in 74% of cases(95% CI 59% – 90%) • GC bias likely (P=5.3×10-3)

  32. Outline • Background / study questions • Study design and methods • Results • SNP chip data • Sequence data

  33. Sequencenearchip-identifiedgeneconversions • Sequence available for 11/33 putative sites

  34. Sequencenearchip-identifiedgeneconversions • Sequence available for 11/33 putative sites • Shortest resolution for tract length ≤ 143 bp

  35. Sequencenearchip-identifiedgeneconversions • Sequence available for 11/33 putative sites • Clustered gene conversions in 4 sequences

  36. Sequencenearchip-identifiedgeneconversions • Sequence available for 11/33 putative sites • Clustered gene conversions in 4 sequences Boxed regions confirmed by Sanger sequencing

  37. Relationship to complex crossover? Haplotype 1 Haplotype 2

  38. Conclusions • Estimate of de novo gene conversion rate • 7.95×10-6/bp/generation • Females: 1.54× gene conversions vs. males • Enriched in hotspots: similar mechanism to crossover • GC vs AT allele transmitted ~3:1 – GC bias • Complex/clustered gene conversions observed in sequence data • Suggests unique correlation within short region

  39. Acknowledgements The T2D-GENES Consortium (NIDDK)San Antonio Family Studies (NIDDK, NIMH) NHGRI NRSA Fellowship Tom Dyer Giulio Genovese Kati Truax Nick Patterson John Blangero David Reich

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