bioRxiv doi: http://dx.doi.org/10.1101/008367

Modeling human population separation history using physically phased genomes

Shiya Song, Elzbieta Sliwerska, Sarah Emery, Jeffrey M Kidd

Phased haplotype sequences are a key component in many population genetic analyses since variation in haplotypes reflects the action of recombination, selection, and changes in population size. In humans, haplotypes are typically estimated from unphased sequence or genotyping data using statistical models applied to large reference panels. To assess the importance of correct haplotype phase on population history inference, we performed fosmid pool sequencing and resolved phased haplotypes of five individuals from diverse African populations (including Yoruba, Esan, Gambia, Massai and Mende). We physically phased 98% of heterozygous SNPs into haplotype-resolved blocks, obtaining a block N50 of 1 Mbp. We combined these data with additional phased genomes from San, Mbuti, Gujarati and CEPH European populations and analyzed population size and separation history using the Pairwise Sequentially Markovian Coalescent (PSMC) and Multiple Sequentially Markovian Coalescent (MSMC) models. We find that statistically phased haplotypes yield an earlier split-time estimation compared with experimentally phased haplotypes. To better interpret patterns of cross-population coalescence, we implemented an approximate Bayesian computation (ABC) approach to estimate population split times and migration rates by fitting the distribution of coalescent times inferred between two haplotypes, one from each population, to a standard Isolation-with-Migration model. We inferred that the separation between hunter-gather populations and other populations happened around 120,000 to 140,000 years ago with gene flow continuing until 30,000 to 40,000 years ago; separation between west African and out of African populations happened around 70,000 to 80,000 years ago, while the separation between Massai and out of African populations happened around 50,000 years ago.

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