Estimates of introgression as a function of pairwise distances

Abstract

Background: Research over the last 10 years highlights the increasing importance of hybridization between species as a major force structuring the evolution of genomes and potentially providing raw material for adaptation by natural and/or sexual selection. Fueled by research in a few model systems where phenotypic hybrids are easily identified, research into hybridization and introgression (the flow of genes between species) has exploded with the advent of whole-genome sequencing and emerging methods to detect the signature of hybridization at the whole-genome or chromosome level. Amongst these are a general class of methods that utilize patterns of single-nucleotide polymorphisms (SNPs) across a tree as markers of hybridization. These methods have been applied to a variety of genomic systems ranging from butterflies to Neanderthals to detect introgression, however, when employed at a fine genomic scale these methods do not perform well to quantify introgression in small sample windows. Results: We introduce a novel method to detect introgression by combining two widely used statistics: pairwise nucleotide diversity d xy and Patterson's D. The resulting statistic, the distance fraction (d f ), accounts for genetic distance across possible topologies and is designed to simultaneously detect and quantify introgression. We also relate our new method to the recently published f d and incorporate these statistics into the powerful genomics R-package PopGenome, freely available on GitHub (pievos101/PopGenome) and the Comprehensive R Archive Network (CRAN). The supplemental material contains a wide range of simulation studies and a detailed manual how to perform the statistics within the PopGenome framework. Conclusion: We present a new distance based statistic d f that avoids the pitfalls of Patterson's D when applied to small genomic regions and accurately quantifies the fraction of introgression (f) for a wide range of simulation scenarios.