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.