Interspecific hybridization causes long‐term phylogenetic discordance between nuclear and mitochondrial genomes in freshwater fishes

Citations Over TimeTop 10% of 2017 papers

Abstract

Classification, phylogeography and the testing of evolutionary hypotheses rely on correct estimation of species phylogeny. Early molecular phylogenies often relied on mtDNA alone, which acts as a single linkage group with one history. Over the last decade, the use of multiple nuclear sequences has often revealed conflict among gene trees. This observation can be attributed to hybridization, lineage sorting, paralogy or selection. Here, we use 54 groups of fishes from 48 studies to estimate the degree of concordance between mitochondrial and nuclear gene trees in two ecological grades of fishes: marine and freshwater. We test the hypothesis that freshwater fish phylogenies should, on average, show more discordance because of their higher propensity for hybridization in the past. In keeping with this idea, concordance between mitochondrial and nuclear gene trees (as measured by proportion of components shared) is on average 50% higher in marine fishes. We discuss why this difference almost certainly results from introgression caused by greater historical hybridization among lineages in freshwater groups, and further emphasize the need to use multiple nuclear genes, and identify conflict among them, in estimation of species phylogeny.

Related Papers

• → A Bayesian Implementation of the Multispecies Coalescent Model with Introgression for Phylogenomic Analysis(2019)180 cited
• → Reconciling the Mitonuclear Compatibility Species Concept with Rampant Mitochondrial Introgression(2019)91 cited
• → Impact of Ghost Introgression on Coalescent-Based Species Tree Inference and Estimation of Divergence Time(2022)27 cited
• → Impact of Ghost Introgression on Coalescent-based Species Tree Inference and Estimation of Divergence Time(2022)4 cited
• → A Bayesian implementation of the multispecies coalescent model with introgression for comparative genomic analysis(2019)3 cited