Evaluating the use of ABBA-BABA statistics to locate introgressed loci

Simon H. Martin*, John W. Davey, Chris D. Jiggins

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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 ƒ(d), a modified version of a statistic originally developed to estimate the genome-wide fraction of admixture. ƒ(d) is not subject to the same biases as D, and is better at identifying introgressed loci. Finally, we show that both D and ƒ(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.

Original languageEnglish
Pages (from-to)244-257
Number of pages14
JournalMolecular Biology and Evolution
Volume32
Issue number1
Early online date22 Sep 2014
DOIs
Publication statusPublished - 1 Jan 2015

Keywords

  • ABBA-BABA
  • gene flow
  • heliconius
  • introgression
  • population structure
  • simulation

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