How strong was the bottleneck associated to the peopling of the Americas? New insights from multilocus sequence data

Abstract In spite of many genetic studies that contributed for a deep knowledge about the peopling of the Americas, no consensus has emerged about important parameters such as the effective size of the Native Americans founder population. Previous estimates based on genomic datasets may have been biased by the use of admixed individuals from Latino populations, while other recent studies using samples from Native American individuals relied on approximated analytical approaches. In this study we use resequencing data for nine independent regions in a set of Native American and Siberian individuals and a full-likelihood approach based on isolation-with-migration scenarios accounting for recent flow between Asian and Native American populations. Our results suggest that, in agreement with previous studies, the effective size of the Native American population was small, most likely in the order of a few hundred individuals, with point estimates close to 250 individuals, even though credible intervals include a number as large as ~4,000 individuals. Recognizing the size of the genetic bottleneck during the peopling of the Americas is important for determining the extent of genetic markers needed to characterize Native American populations in genome-wide studies and to evaluate the adaptive potential of genetic variants in this population.

Bayesian Analysis of Evolutionary Divergence with Genomic Data under Diverse Demographic Models.

We present a new Bayesian method for estimating demographic and phylogenetic history using population genomic data. Several key innovations are introduced that allow the study of diverse models within an Isolation-with-Migration framework. The new method implements a 2-step analysis, with an initial Markov chain Monte Carlo (MCMC) phase that samples simple coalescent trees, followed by the calculation of the joint posterior density for the parameters of a demographic model. In step 1, the MCMC sampling phase, the method uses a reduced state space, consisting of coalescent trees without migration paths, and a simple importance sampling distribution without the demography of interest. Once obtained, a single sample of trees can be used in step 2 to calculate the joint posterior density for model parameters under multiple diverse demographic models, without having to repeat MCMC runs. Because migration paths are not included in the state space of the MCMC phase, but rather are handled by analytic integration in step 2 of the analysis, the method is scalable to a large number of loci with excellent MCMC mixing properties. With an implementation of the new method in the computer program MIST, we demonstrate the method's accuracy, scalability, and other advantages using simulated data and DNA sequences of two common chimpanzee subspecies: Pan troglodytes (P. t.) troglodytes and P. t. verus.