1. Recombination based population genomics Jaume Bertranpetit Marta Melé Francesc Calafell Asif Javed Laxmi Parida

2. Recall: IRiS Identification of Recombinations in Sequences IRiS is a computational method developed with biological insight detects evidence of historical recombinations minimizes number of recombinations in Ancestral Recombinational Graph (ARG)

3. Recotypes recombination edge mutation edge extant sequence Two chromosomes share a recombination if the junction is co-inherited.

4. Recotypes Two chromosomes share a recombination if the junction is co-inherited. r1 ab

5. Recotypes Two chromosomes share a recombination if the junction is co-inherited. r1 r2 abc

6. Recotypes Two chromosomes share a recombination if the junction is co-inherited. r1 r2 abc r1r2… a10 b10 c01 …

7. Validity of inferred recombinations Comparison with sperm typing Computer simulated recombinations

8. in vitro Chr 1 near MS32 minisatellite Jeffreys et al. 2005 80 UK semen donor of North European origin - Sperm typing - LDhat and Phase (200 SNPs) IRiS LDhat Phase sperm typing HapMap 2 CEU population similar SNP density

9. in silico HapMap 3 X chromosome data Select 2 chromosomes at random. Pick a random breakpoint. Create a new chromosome. Check if it is unique, add to the dataset. Run IRiS on the dataset to see if the breakpoint is detected. Chromosomes

10. in silico HapMap 3 X chromosome data Select 2 chromosomes at random. Pick a random breakpoint. Create a new chromosome. Check if it is unique, add to the dataset. Run IRiS on the dataset to see if the breakpoint is detected. Chromosomes

11. in silico HapMap 3 X chromosome data Select 2 chromosomes at random. Pick a random breakpoint. Create a new chromosome. Check if it is unique, add to the dataset. Run IRiS on the dataset to see if the breakpoint is detected. Chromosomes

12. in silico HapMap 3 X chromosome data Select 2 chromosomes at random. Pick a random breakpoint. Create a new chromosome. Check if it is unique, add to the dataset. Run IRiS on the dataset to see if the breakpoint is detected. Chromosomes

13. in silico HapMap 3 X chromosome data Select 2 chromosomes at random. Pick a random breakpoint. Create a new chromosome. Check if it is unique, add to the dataset. Run IRiS on the dataset to see if the breakpoint is detected. Chromosomes

14. in silico HapMap 3 X chromosome data Select 2 chromosomes at random. Pick a random breakpoint. Create a new chromosome. Check if it is unique, add to the dataset. Run IRiS on the dataset to see if the breakpoint is detected. Chromosomes IRiS recombination detected?

15. in silico HapMap 3 X chromosome data Select 2 chromosomes at random. Pick a random breakpoint. Create a new chromosome. Check if it is unique, add to the dataset. Run IRiS on the dataset to see if the breakpoint is detected. Chromosomes IRiS recombination detected? 69% recombinations detected All detected recombinations detect the correct sequence No false positives

16. Recombinomics Strong population structure Agreement with traditional methods  FST vs. recombinational distance More informative than SNPs  STRUCTURE  PCA

17. Regions 18 regions selected from HapMap 3 X-chromosome in males (to avoid phasing errors) 50 KB away from known CNV and SD (to avoid genotyping errors) 50 KB away from genes (to avoid selection) at least 80 SNPs 438888424240 2125217440 Chromosomes: LWK(43), MKK (88), YRI (88), ASW (42), GIH (42), CHB (40), CHD (21), JPT(25), MEX(21), CEU (74), TSI (40)

18. Analysis For each region IRiS inferred recotypes for each chromosome  5166 recombinations were inferred  3459 co-occurred in at least two chromosomes r1r2r3r4r5r6…r3459 LK10110000 LK21011000 : LK43101000 MK10100111 : TI400000010 Chromosome Recombination

19. Analysis For each region IRiS inferred recotypes for each chromosome  5166 recombinations were inferred  3459 co-occurred in at least two chromosomes r1r2r3r4r5r6…r3459 LK10110000 LK21011000 : LK43101000 MK10100111 : TI400000010 Chromosome Recombination Recotype

20. Agreement with LDhat number of recombinations inferred by IRiS recombination rate inferred by LDhat Spearman correlation = 0.711 pvalue <10 -30 Each point represents a short haplotype segment in HapMap CEU population

21. Agreement with LDhat number of recombinations inferred by IRiS recombination rate inferred by LDhat Spearman correlation = 0.711 pvalue <10 -30 Each point represents a short haplotype segment in HapMap CEU population Correlation in hotspots  2 = 38.39 pvalue<6x10 -10

22. Recombinational distance between populations Two populations genetically closer will share a higher number of recombinations Recombinational distance Correlation between FST distance and recombinational distance for the 18 region [0.35 – 0.75 ] with pvalues < 0.025 = R A + R B -R AB R AB D AB MDS All regions combined stress=6.1% 1 -

23. PCA of population data r1r2r3r4r5r6…r3459 LK10110000 LK21011000 : LK43101000 MK10100111 : TI400000010 Recall recotypes

24. PCA of population data r1r2r3r4r5r6…r3459 LK10110000 LK21011000 : LK43101000 MK10100111 : TI400000010 Recall recotypes r1r2r3r4r5r6…r3459 LK14749010 MK14705724 : TI0171001

25. PCA of population data r1r2r3r4r5r6…r3459 LK14749010 MK14705724 : TI0171001 The first two PCs capture 66.4% of the variance

26. PCA of recotypes  more on this later

27. Recotypes vs. SNPs Due to ascertainment bias gene diversity does not reflect population structure Percentage of variance SNPsRecotypes Across groups9%6% Within groups4%1% Within populations 87%93% Normalized comparison linearly scaled to [0,1] using 21 samples per population in agreement with Lewontin 72 results similar to Conrad 07

28. from SNPs to haplotypes to recotypes (a STRUCTURE comparison ) K=2 SNPs haplotypes recotypes

29. from SNPs to haplotypes to recotypes (a STRUCTURE comparison ) K=3 SNPs haplotypes recotypes

30. from SNPs to haplotypes to recotypes (a STRUCTURE comparison ) K=4 SNPs haplotypes recotypes

31. from SNPs to haplotypes to recotypes (a STRUCTURE comparison ) K=5 SNPs haplotypes recotypes

32. Africa within global genetic variation Avg. Number of recombinations in 21 random chromsomes Out of Africa hypothesis Founder’s effect minority African specific component Structure k=4

33. Genetic variation within Africa Maasai specific minor component Structure k=5  Subsaharan Maasai are distinct among Africans. Parra 98  African-American exhibit stronger recombinational affinity with African populations than European populations. (Parra 98)

34. Genetic variation outside Africa Structure k=5  Outside Africa, Gujarati and Japanese exhibit the highest and lowest number of recombinations respectively.  Gujarati Indians show intermediate position between Europeans and East Asians. Avg. Number of recombinations in 21 random chromsomes

35. Venturing outside the X-chromosome Benefits  The bigger picture  More regions and hence more information Challenges  Higher number of recombinations makes the picture murkier  Phasing errors

36. Regions 81 regions selected from HapMap 3 50 KB away from known CNV and SD (to avoid genotyping errors) 50 KB away from genes (to avoid selection) at least 200 SNPs 25 samples per population (each sample has two chromosomes)

37. Analysis For each region IRiS inferred recotypes for each chromosome  34140 recombinations were inferred merged For each sample the two recotypes were merged. SNPsrecotypes PCA plots

38. Quantifying population structure PCA and by k nearest neighbors is used to predict population of every sample AfricansNon- Africans MKK LKK YRIASW GIHE. AsianMEXEuropean CHB+CHDJPTCEUTSI (4,3)(4,3) (0,7)(0,7) (3,13)(8,13) Perfectly classified classified with errors Misclassification by (recotypes, SNPs)

39. East Asian population Recotypes are more informative of underlying population structure. SNPsrecotypes PCA plots

40. in conclusion … Recotypes show strong agreement with in silico and in vetro recombination rates estimates are highly informative of the underlying population structure provide a novel approach to study the recombinational dynamics