Inferring human population sizes, divergence times and rates of gene flow from mitochondrial, X and Y chromosome resequencing data - PubMed (original) (raw)

. 2007 Dec;177(4):2195-207.

doi: 10.1534/genetics.107.077495.

Sarah B Kingan, Maya M Pilkington, Jason A Wilder, Murray P Cox, Himla Soodyall, Beverly Strassmann, Giovanni Destro-Bisol, Peter de Knijff, Andrea Novelletto, Jonathan Friedlaender, Michael F Hammer

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Inferring human population sizes, divergence times and rates of gene flow from mitochondrial, X and Y chromosome resequencing data

Daniel Garrigan et al. Genetics. 2007 Dec.

Abstract

We estimate parameters of a general isolation-with-migration model using resequence data from mitochondrial DNA (mtDNA), the Y chromosome, and two loci on the X chromosome in samples of 25-50 individuals from each of 10 human populations. Application of a coalescent-based Markov chain Monte Carlo technique allows simultaneous inference of divergence times, rates of gene flow, as well as changes in effective population size. Results from comparisons between sub-Saharan African and Eurasian populations estimate that 1500 individuals founded the ancestral Eurasian population approximately 40 thousand years ago (KYA). Furthermore, these small Eurasian founding populations appear to have grown much more dramatically than either African or Oceanian populations. Analyses of sub-Saharan African populations provide little evidence for a history of population bottlenecks and suggest that they began diverging from one another upward of 50 KYA. We surmise that ancestral African populations had already been geographically structured prior to the founding of ancestral Eurasian populations. African populations are shown to experience low levels of mitochondrial DNA gene flow, but high levels of Y chromosome gene flow. In particular, Y chromosome gene flow appears to be asymmetric, i.e., from the Bantu-speaking population into other African populations. Conversely, mitochondrial gene flow is more extensive between non-African populations, but appears to be absent between European and Asian populations.

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Figures

F<sc>igure</sc> 1.—

Figure 1.—

Map showing the geographical locations of the 10 human populations sampled for DNA resequencing in this study.

F<sc>igure</sc> 2.—

Figure 2.—

A schematic of the isolation-with-migration (IM) model. The IM model includes two populations that diverge from one another at time T from a common ancestral population of size _N_A. After time T, the ancestral population splits into two daughter populations, one of size _sN_A and the other of size (1 − s)_N_A. The populations are allowed to grow (or shrink) exponentially until the current generation. Over the course of these T generations, gene flow can occur between the two populations and can occur at different rates in each direction.

F<sc>igure</sc> 3.—

Figure 3.—

Posterior probability distributions for the divergence time parameter in the IM model in 13 pairwise population comparisons. Each curve represents an independent run of the MCMC algorithm. The timescale shown at the bottom is in thousands of years before the present.

F<sc>igure</sc> 4.—

Figure 4.—

Comparison between the distributions of _F_ST values predicted between African and non-African populations (A), under the inferred parameters of the IM model, and those observed at 50 autosomal loci resequenced by V

oight

et al. (2005). (B) The predicted and observed distributions of _F_ST between European and Asian populations. The predicted and observed distributions of Tajima's D statistic are also given for the African population (C) and the Asian population (D).

F<sc>igure</sc> 5.—

Figure 5.—

A schematic to illustrate the effect of gene flow with unsampled populations. In A, although populations 2 and 3 are more closely related, population 2 only exchanges genes with the more distantly related population 1. If only populations 1 and 3 are sampled (solid circles), this combination of factors may result in a misleading signal of asymmetrical gene flow between populations 1 and 3. However, if gene flow can occur between all populations (sampled or unsampled), as in the linear stepping stone model in B, no such misleading pattern of asymmetrical gene flow is expected.

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