Data from: Are 100 enough? Inferring acanthomorph teleost phylogeny using Anchored Hybrid Enrichment

Background: The past decade has witnessed remarkable progress towards resolution of the Tree of Life. However, despite the increased use of genomic scale datasets, some phylogenetic relationships remain difficult to resolve. Here we employ anchored phylogenomics to capture 107 nuclear loci in 29 species of acanthomorph teleost fishes, with 25 of these species sampled from the recently delimited clade Ovalentaria. Previous studies employing multilocus nuclear exon datasets have not been able to resolve the nodes at the base of the Ovalentaria tree with confidence. Here we test whether a phylogenomic approach will provide better support for these nodes, and if not, why this may be. Results: After using a novel method to account for paralogous loci, we estimated phylogenies with maximum likelihood and species tree methods using DNA sequence alignments of over 80,000 base pairs. Several key relationships within Ovalentaria are well resolved, including 1) the sister taxon relationship between Cichlidae and Pholidichthys, 2) a clade containing blennies, grammas, clingfishes, and jawfishes, and 3) monophyly of Atherinomorpha (topminnows, flyingfishes, and silversides). However, many nodes in the phylogeny associated with the early diversification of Ovalentaria are poorly resolved in several analyses. Through the use of rarefaction curves we show that limited phylogenetic resolution among the earliest nodes in the Ovalentaria phylogeny does not appear to be due to a deficiency of data, as average global node support ceases to increase when only 1/3rd of the sampled loci are used in analyses. Instead this lack of resolution may be driven by model misspecification as a Bayesian mixed model analysis of the amino acid dataset provided good support for parts of the base of the Ovalentaria tree.Conclusions: Although it does not appear that the limited phylogenetic resolution among the earliest nodes in the Ovalentaria phylogeny is due to a deficiency of data, it may be that both stochastic and systematic error resulting from model misspecification play a role in the poor resolution at the base of the Ovalentaria tree as a Bayesian approach was able to resolve some of the deeper nodes, where the other methods failed.