A Statistical Approach for Distinguishing Hybridization and Incomplete Lineage Sorting

Abstract

The extent and evolutionary significance of hybridization is difficult to evaluate because of the difficulty in distinguishing hybridization from incomplete lineage sorting. Here we present a novel parametric approach for statistically distinguishing hybridization from incomplete lineage sorting based on minimum genetic distances of a nonrecombining locus. It is based on the idea that the expected minimum genetic distance between sequences from two species is smaller for some hybridization events than for incomplete lineage sorting scenarios. When applied to empirical data sets, distributions can be generated for the minimum interspecies distances expected under incomplete lineage sorting using coalescent simulations. If the observed distance between sequences from two species is smaller than its predicted distribution, incomplete lineage sorting can be rejected and hybridization inferred. We demonstrate the power of the method using simulations and illustrate its application on New Zealand alpine buttercups (Ranunculus). The method is robust and complements existing approaches. Thus it should allow biologists to assess with greater accuracy the importance of hybridization in evolution.