RT Journal Article
SR Electronic
T1 Measuring genetic differentiation from Pool-seq data
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 282400
DO 10.1101/282400
A1 Valentin Hivert
A1 Raphël Leblois
A1 Eric J. Petit
A1 Mathieu Gautier
A1 Renaud Vitalis
YR 2018
UL http://biorxiv.org/content/early/2018/07/12/282400.abstract
AB The advent of high throughput sequencing and genotyping technologies enables the comparison of patterns of polymorphisms at a very large number of markers. While the characterization of genetic structure from individual sequencing data remains expensive for many non-model species, it has been shown that sequencing pools of individual DNAs (Pool-seq) represents an attractive and cost-effective alternative. However, analyzing sequence read counts from a DNA pool instead of individual genotypes raises statistical challenges in deriving correct estimates of genetic differentiation. In this article, we provide a method-of-moments estimator of FST for Pool-seq data, based on an analysis-of-variance framework. We show, by means of simulations, that this new estimator is unbiased, and outperforms previously proposed estimators. We evaluate the robustness of our estimator to model misspecification, such as sequencing errors and uneven contributions of individual DNAs to the pools. Finally, by reanalyzing published Pool-seq data of different ecotypes of the prickly sculpin Cottus asper, we show how the use of an unbiased FST estimator may question the interpretation of population structure inferred from previous analyses.