title: Modeling Human Population Separation History Using Physically Phased Genomes.
abstract: 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, Maasai, 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 Centre de'Etude du Polymorphism Humain European populations and analyzed population size and separation history using the pairwise sequentially Markovian coalescent and multiple sequentially Markovian coalescent models. We find that statistically phased haplotypes yield a more recent split-time estimation compared with experimentally phased haplotypes. To better interpret patterns of cross-population coalescence, we implemented an approximate Bayesian computation 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-gatherer populations and other populations happened ∼120-140 KYA, with gene flow continuing until 30-40 KYA; separation between west-African and out-of-African populations happened ∼70-80 KYA; while the separation between Maasai and out-of-African populations happened ∼50 KYA.
authors.affiliation: Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan 48109.
authors.forename: Shiya
authors.initials: S
authors.lastname: Song
authors.affiliation: Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan 48109.
authors.forename: Elzbieta
authors.initials: E
authors.lastname: Sliwerska
authors.affiliation: Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan 48109.
authors.forename: Sarah
authors.initials: S
authors.lastname: Emery
authors.affiliation: Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan 48109 jmkidd@umich.edu.|Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan 48109.
authors.forename: Jeffrey M
authors.initials: JM
authors.lastname: Kidd
mesh_terms: D001499:Bayes Theorem; D044383:Black People / Q000235:genetics; D005828:Genetics, Population / Q000379:methods*; D015894:Genome, Human; D005838:Genotype; D006239:Haplotypes; D006801:Humans; D008297:Male; D008957:Models, Genetic; D020641:Polymorphism, Single Nucleotide
keywords: MSMC; PSMC; approximate Bayesian computation; fosmid pool sequencing; haplotype; population split time