The genetic architecture of recombination rate variation in a natural population.
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Genome-wide association study vs. regional heritability analysis to detect genetic variants underlying individual recombination rate variation in a wild population of Soay sheep.
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The genetic architecture of recombination rate variation in a natural population.
- 1. The genetic architecture of recombination rate variation in a natural population. Susan E. Johnston, Jon Slate, Josephine M. Pemberton @SuseJohnston
- 2. Why recombine? An evolutionary perspective. • Recombination can be beneficial. – Can prevent accumulation of deleterious mutations. – Can increase genetic variance for fitness. • Recombination can be costly. – May reduce genome integrity – Can break up co-adapted gene complexes. • Empirical studies have been limited by genetic resources. Charlesworth & Barton (1996), Felsenstein (1974), Burt (2000), Inoue & Lupski (2002)
- 3. Understanding recombination rates in the genomics era • Recombination rates vary from local to global level. • Recombination rate may co-vary with fitness. • Individual recombination rate can be heritable. – Genetic variants have associated with variation – PRDM9, RNF212, etc. • But little understanding on if, how and why RR varies at an individual level in natural populations. h2 = 0.30 h2 = 0.46 h2 = 0.22 biologyfishman David Illig Aimeric Blaud Kong et al (2004) Nat. Genet. Baudat et al (2010) Science Kong et al (2008) Science Kong et al (2010) Nature
- 4. St Kilda • Wild population of Neolithic domestic sheep studied since 1985. • Extensive life history, pedigree and phenotype information for ~ 7,000 individuals. • 39,101 polymorphic SNPs typed in 5652 pedigreed sheep Soay sheep (Ovis aries) @SoaySheep
- 5. Pedigree and SNP information can be integrated to find meiotic crossovers.
- 6. Father Mother Focal ID Offspring Mate gamete CRIMAP v2.504 Green et al. (1990) Pedigree and SNP information can be integrated to find meiotic crossovers. gamete karyotype 34 crossover events Y
- 7. Father Mother Focal ID Offspring Mate gamete CRIMAP v2.504 Green et al. (1990) Pedigree and SNP information can be integrated to find meiotic crossovers. 3330 individual recombination counts in 813 unique focal individuals.
- 8. Is recombination rate heritable? Is recombination rate driven by particular genetic variants? Questions
- 9. Estimating heritability: an animal model approach. Fixed effects Sex, Age, Condition Genomic inbreeding coefficient Random effects Individual identity Year of Birth Year of Gamete Transfer Mother identity Modelled using ASReml-R (Butler et al. 2009) Genomic inbreeding/relatedness determined using GCTA (Yang et al. 2010) Additive genetic effect (heritability) Genomic relationship matrix using 39K SNP markers REML generalised linear mixed model: *Only Sex and Additive genetic effect were significant.
- 10. Sex h2 VP Female 0.16 (0.02) 31.7 (1.06) Male 0.12 (0.03) 25.2 (1.16) Males have 7.38 more crossovers per gamete. Females have higher phenotypic variance and heritability.
- 11. Is recombination rate heritable? Is recombination rate driven by particular genetic variants? Questions
- 12. 1. Genome-wide association study N = 1197 (227) A region on chromosome 6 has a trans-acting, sex-limited effect on recombination rate. N = 2134 (586) RNF212
- 13. biologyfishman David Illig Aimeric Blaud Candidate gene: ring finger protein 212 (RNF212) • Locus associated with individual recombination rate variation in humans, cattle and mice. • Sexually antagonistic effect on recombination in humans. • Strong candidate for sex-limited effect on recombination rate. Kong et al (2014) Nat. Genet. Sandor et al (2012) PLoS Genetics Reynolds et al (2013) Nat. Genet.
- 14. Effect sizes at RNF212 in Soay sheep Autosomalcrossovercount The most significant SNP explains 35% of heritable variation in females. SNP ID: oar3_OAR6_116402578 Autosomalcrossovercount
- 15. • Majority of heritable variation remains unexplained. – Common phenomenon in GWAS studies. • GWAS is a single locus approach – Reduced power to detect rare variants… – …and variants of small effect sizes. • One solution: Regional heritability. – Determine variance explained by defined regions. – Incorporates the effects of multiple haplotypes. Single vs. multimarker approaches Wood et al. (2014) Nat. Genet. Yang et al (2011) Nat. Genet Nagamine et al (2012) PLoS One Santure et al (2013) Mol Ecol Berenos et al (2015) Mol Ecol
- 16. 2. Regional heritability analysis. Regional additive genetic variance Genomic additive genetic variance Additive genetic effect Yang et al (2011) Nat. Genet Nagamine et al (2012) PLoS One Examined variance explained within sliding windows of 20 SNPs (~800kb windows)
- 17. 2. Regional heritability analysis. Regional additive genetic variance Genomic additive genetic variance Additive genetic effect Yang et al (2011) Nat. Genet Nagamine et al (2012) PLoS One Examined variance explained within sliding windows of 20 SNPs (~800kb windows)
- 18. 2. Regional heritability analysis. Regional additive genetic variance Genomic additive genetic variance Additive genetic effect Yang et al (2011) Nat. Genet Nagamine et al (2012) PLoS One Examined variance explained within sliding windows of 20 SNPs (~800kb windows)
- 19. N = 2134 (586) N = 1197 (227) N = 3330 (813) RNF212 region explains 47% of heritable variation in females. No regions identified in males. Region with meiotic recombinant protein REC8 REC8 region explains 26% of heritable variation in both sexes.
- 20. N = 2134 (586) N = 1197 (227) N = 3330 (813) RNF212 region explains 47% of heritable variation in females. No regions identified in males. REC8 region explains 26% of heritable variation in both sexes. The approach may increase chances of finding new variants… …but power is likely to be limited in smaller sample sizes. Region with meiotic recombinant protein REC8
- 21. Conclusions • Recombination rate is heritable and has a sexually dimorphic genetic architecture in Soay sheep. • Multi-locus approaches may improve variant detection – But “missing heritability” issue indicates quantitative genetic framework still relevant. • Is recombination rate under selection in the wild? – Ongoing work!
- 22. ACKNOWLEDGEMENTS: St Kilda Photographs: Arpat Ozgul, Tom Black, Gina Prior, Owen Jones. Josephine Pemberton Jon Slate Camillo Bérénos Jisca Huisman Jarrod Hadfield Craig Walling Bill Hill John Hickey Phil Ellis Jill Pilkington Ian Stevenson Lynsey Bunnefeld Many Soay sheep project volunteers Wellcome Trust Genotyping Facility, Edinburgh.