Evaluating the Use of ABBA–BABA Statistics to Locate Introgressed Loci

Abstract

Several methods have been proposed to test for introgression across genomes. One method tests for a genome-wide excess of shared derived alleles between taxa using Patterson’s D statistic, but does not establish which loci show such an excess or whether the excess is due to introgression or ancestral population structure. Several recent studies have extended the use of D by applying the statistic to small genomic regions, rather than genome-wide. Here, we use simulations and whole-genome data from Heliconius butterflies to investigate the behavior of D in small genomic regions. We find that D is unreliable in this situation as it gives inflated values when effective population size is low, causing D outliers to cluster in genomic regions of reduced diversity. As an alternative, we propose a related statistic truef^d, a modified version of a statistic originally developed to estimate the genome-wide fraction of admixture. truef^d is not subject to the same biases as D, and is better at identifying introgressed loci. Finally, we show that both D and truef^d outliers tend to cluster in regions of low absolute divergence (dXY), which can confound a recently proposed test for differentiating introgression from shared ancestral variation at individual loci.

Gene Flow between Divergent Cereal- and Grass-Specific Lineages of the Rice Blast Fungus Magnaporthe oryzae

“…For three lineages P1, P2, and P3 and an outgroup with genealogical relationships (((P1,P2),P3),O), and under conditions of no gene flow, shared derived alleles between P2 and P3 (ABBA alleles) and shared derived alleles between P1 and P3 (BABA alleles) can be produced only by incomplete lineage sorting and should be equally infrequent (34,35). Differences in numbers of ABBA and BABA alleles are interpreted as gene flow assuming no recurrent mutation and no deep ancestral population structure within lineages.…”

“…Differences in numbers of ABBA and BABA alleles are interpreted as gene flow assuming no recurrent mutation and no deep ancestral population structure within lineages. We computed D, which measures the imbalance between numbers of ABBA and BABA sites and is used to test for admixture in ((P1,P2),P3) triplets, with D Ͼ 0 implying gene flow between P2 and P3 and D Ͻ 0 implying gene flow between P1 and P3 (34,35). We also made use of the heterogeneity in divergence time between members of ((P1,P2),P3) triplets to examine gene flow across three time periods (33), according to the following principles: (i) triplets including the most recently diverged lineages as P1 and P2 (i.e., the Triticum and Lolium lineages, the two Eleusine lineages, or the Oryza and Setaria lineages) carried information about gene flow across relatively recent times, (ii) triplets including as P1 and P2 two lineages from the same main group of lineages (i.e., Eragrostis/Eleusine1/ Eleusine2/Triticum/Lolium or Brachiaria2/Setaria/Oryza, excluding (P1,P2) pairs already used in principle 1) carried information about gene flow across intermediate times, and (iii) triplets including as P1 and P2 two lineages from different main groups of lineages (i.e., Eragrostis/Eleusine1/Eleusine2/Triticum/Lolium and Brachiaria2/Setaria/Oryza) and Stenotaphrum or Brachiaria1 as P3 carried information about gene flow across a relatively long time period (Fig.…”

Introgression and gene family contraction drive the evolution of lifestyle and host shifts of hypocrealean fungi

“…Recently, it has been used as a convenient statistic for studying locus-specific introgression of genetic material controlling coloration in Heliconius butterflies (Zhang et al 2015). D -statistic analysis requires four species including two sister species, a third species potentially involved in introgression and an outgroup species (Martin et al 2014). Most investigations of introgression focus on animals and plants, such as horse, butterfly and tomato, that have sexual reproduction during their life-cycles (Pease and Rosenzweig 2015; Zhang et al 2015).…”

Evidence for archaic adaptive introgression in humans

“…There are several statistical methods available for identifying introgression from genome-wide data 1, 42, 43, 44 . The most well known is Patterson’s D 1, 42, 43 , a statistic that measures the excess sharing of derived alleles between each of two populations in a pair (ingroup populations) and an outgroup population (Supplementary information S1 (box)).…”

“…Identifying specific genes or segments of the genome that are introgressed is even more challenging, because the simple re-sampling methods for evaluating the significance of Patterson’s D statistic are inapplicable to shorter genomic regions 44 . Inferences regarding specific regions must instead rely on demographic models that include assumptions about parameters such as divergence times, effective population sizes, and recombination rates.…”