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 polymorphism (SNP) polymorphisms across a tree as markers of hybridization. These methods have been applied to a variety of genomic systems ranging from butterflies to Neanderthal's 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 Basic distance fraction (Bd 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 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 Bd f that avoids the pitfalls of Patterson's D when applied to small genomic regions and more accurately quantifies the fraction of introgression (f ) for a wide range of simulation scenarios.

Genome scans for selection and introgression based on k‐nearest neighbour techniques

“…When the gene flow is recent, D 3 has overall lower AUC values than the kNN‐based approaches (Figure 6a), whereas D 3 and | D 3 | outperform the kNN techniques when the gene flow occurred further in the past ( t GF > 0.1). This stability against the time of gene flow was also previously mentioned by Pfeifer and Kapan (2019). These authors used a similar concept to D 3 , which was realized on a four‐taxon system.…”

“…In the introgression cases, we compare the kNN‐based methods to the D 3 approach (Hahn & Hibbins, 2019), which follows a similar logic as the d f method introduced by Pfeifer & Kapan (2019), but without the use of an outgroup. We also show the absolute value of D 3 , denoted as | D 3 |.…”

“…Several approaches have been proposed for this purpose. The most widely applied one is the ABBA‐BABA family of methods, which is based on a four‐taxon system where the fourth taxon serves as the outgroup (Durand, Patterson, Reich, & Slatkin, 2011; Green et al., 2010; Martin, Davey, & Jiggins, 2014; Pfeifer & Kapan, 2019). Since an outgroup is not always available, approaches based on fewer taxa have also been introduced (Geneva, Muirhead, Kingan, & Garrigan, 2015; Hahn & Hibbins, 2019; Hibbins & Hahn, 2019).…”

Evolutionary History of the Marchantia polymorpha Complex

“…As a means to distinguish between ILS and introgression, we applied three variants of the ABBA-BABA test – Pattersons D statistic ( Durand et al, 2011 ), Martins f statistic ( Martin et al, 2013 ) and Bd-fraction ( Pfeifer and Kapan, 2017 ) – using the R package “PopGenome” ( Pfeifer et al, 2014 ). Local ancestry inference was conducted using Loter ( Dias-Alves et al, 2018 ), with default settings and three ancestral populations (subsp.…”

Genome Scans for Selection and Introgression based on k-nearest Neighbor Techniques

“…There has been an explosion of available methods in this area in recent years. Currently, the most widely applied methods are the ABBA-BABA family of methods which are based on a four-taxon system (Durand et al, 2011;Green et al, 2010;Martin et al, 2014;Pfeifer and Kapan, 2019), where the fourth taxon acts as the outgroup. Since an outgroup is not always available, several other approaches based on fewer taxa were also introduced (Geneva et al, 2015;Hahn and Hibbins, 2019;Hibbins and Hahn, 2019).…”