Population genomics from pool sequencing

Abstract

Next generation sequencing of pooled samples is an effective approach for studies of variability and differentiation in populations. In this paper we provide a comprehensive set of estimators of the most common statistics in population genetics based on the frequency spectrum, namely the Watterson estimator θW, nucleotide pairwise diversity Π, Tajima's D, Fu and Li's D and F, Fay and Wu's H, McDonald-Kreitman and HKA tests and FST, corrected for sequencing errors and ascertainment bias. In a simulation study, we show that pool and individual θ estimates are highly correlated and discuss how the performance of the statistics vary with read depth and sample size in different evolutionary scenarios. As an application, we reanalyse sequences from Drosophila mauritiana and from an evolution experiment in Drosophila melanogaster. These methods are useful for population genetic projects with limited budget, study of communities of individuals that are hard to isolate, or autopolyploid species.