Reconstructing past history from whole-genomes: an ABC approach handling recombining data.

Abstract

International audienceIn population genetics, a key interest is to reconstruct the demographic history of a population using its genetic data. This history can be characterized by multiple events such as migration of individuals, admixture with another population, or changes in population size. With the availability of large-scale genomic data numerous methods have arisen for untangling complicated histories or retrieving a detailed picture of a population at different time periods.Although genomes are known to be extremely informative about demography, there are many ways to extract this information. We present an approach designed for inferring past population sizes for an intermediate number of fully sequenced genomes. It relies on Approximate Bayesian Computation (ABC), a simulation-based statistical framework for generic model comparison and parameter inference. We demonstrated how the specificities of DNA sequencing data (namely haplotypic information, long range genetic correlation and genotyping errors) can be handled using ABC and fast genetic simulators, and further infer histories of successive bottleneck and expansions in human populations