meiotic gene conversion in humans: rate, sex ratio, and gc bias
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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. - PowerPoint PPT PresentationTRANSCRIPT
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Meiotic gene conversion in humans: rate, sex ratio, and GC bias
Amy L. Williams
June 19, 2013
University of Chicago
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Gene conversion defined
• Meiosis: produces haploid germ cells with recombinations
• Gene conversion: short segment copied into given chromosome from other homolog
MeiosisCrossover
GeneConversion
Two types ofrecombination:
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• 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)
Study question 1: gene conversion rate?
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• 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)
Study question 1: gene conversion rate?
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Study question 2: male vs. female rate?
• Gender differences in rate?– Crossovers: female rate 1.78× male (deCODE)
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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
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Summary: study questions
1. Genome-wide de novo gene conversion rate?
2. Different rate between males/females?
3. Extent of GC bias in tracts?
4. Localization: Hotspots? Tracts independent?
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Outline
• Background / study questions
• Study design and methods
• Results– SNP chip data– Sequence data
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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
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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 still
obtain overall rate
• Chip data give per base-pair rate– R = # gene conversions / # informative sites
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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
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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
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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
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Family-based phase reveals recombinations
• Hapi output: paternal haplotype transmissions
Crossover:
Haplotype 2Haplotype 1
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Family-based phase reveals recombinations
• Hapi output: paternal haplotype transmissions
Crossover: Gene Conversion:
Haplotype 2Haplotype 1
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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
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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
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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 48Program
All families (N=103)Runtime Speedup
Hapi 3.1 s -
Merlin 1,005 s 323×
Allegro v2 7,661 s 2,462×
Superlink 1,393 s* 448×
* Superlink failed to analyze 11 child family; 8/11 children used
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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 48Program
All families (N=103) ≤ 3 children (N=86)Runtime Speedup Runtime Speedup
Hapi 3.1 s - 2.2 s -
Merlin 1,005 s 323× 8.7 s 3.8×
Allegro v2 7,661 s 2,462× 14.5 s 6.4×
Superlink 1,393 s* 448× 38.8 s 17.2×
* Superlink failed to analyze 11 child family; 8/11 children used
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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
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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
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Approach to identifying gene conversions
1. Perform QC, phase 3-generation pedigrees2. Find gene conversions in 2nd generation:
single SNP double crossovers3. Confirm:
– Gene converted allele in 3rd generation– Other allele in 2nd generation sibling(s)
• False positive only if ≥ 2 genotyping errors
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Outline
• Background / study questions
• Study design and methods
• Results– SNP chip data– Sequence data
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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
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• Rate: 7.95×10-6/bp/generation– Within range of Jeffreys and May (2004)– Close to LD-based estimates
Result 1: 33 putative gene conversions, rate
MaleFemale
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• Rate: 7.95×10-6/bp/generation– Within range of Jeffreys and May (2004)– Close to LD-based estimates
Result 1: 33 putative gene conversions, rate
MaleFemale Are these real gene
conversions?
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• 19 sites sequenced by T2D-GENES Consortium– 18/19 gene conversion genotypes verified
• Differing site looks like sequencing artifact– 2nd generation recipient has genotype mismatch
3rd generation grandchild shows same genotype– If sequence data correct,
gene conversion ingrandchild
T2D-GENES sequence confirms events
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• 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)
Result 2: gene conversion rates by gender
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Result 3: gene conversions localize in hotspots
2.71% of genome in ≥10 cM/Mb hotspots
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Result 3: gene conversions localize in hotspots
10/33 gene conversions with ≥10 cM/Mb:
P=1.1×10-8
2.71% of genome in ≥10 cM/Mb hotspots
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Result 4: observe extreme GC bias
• 31 GC informative sites– A/C, A/G
T/C, T/G
• GC transmission in 74% of cases(95% CI 59% – 90%)– GC bias likely (P=5.3×10-3)
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Outline
• Background / study questions
• Study design and methods
• Results– SNP chip data– Sequence data
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Sequence near chip-identified gene conversions
• Sequence available for 11/33 putative sites
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Sequence near chip-identified gene conversions
• Sequence available for 11/33 putative sites
• Shortest resolution for tract length ≤ 143 bp
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Sequence near chip-identified gene conversions
• Sequence available for 11/33 putative sites
• Clustered gene conversions in 4 sequences
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Sequence near chip-identified gene conversions
• Sequence available for 11/33 putative sites
• Clustered gene conversions in 4 sequences
Boxed regions confirmed by Sanger sequencing
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Relationship to complex crossover?
Haplotype 2Haplotype 1
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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
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The T2D-GENES Consortium (NIDDK)San Antonio Family Studies (NIDDK, NIMH)
NHGRI NRSA Fellowship
Acknowledgements
Nick Patterson David ReichJohn Blangero
Giulio GenoveseTom Dyer Kati Truax