Data for: Gene tree estimation error with ultraconserved elements: An empirical study on Pseudapis bees

Summarizing individual gene trees to species phylogenies using two-step
coalescent methods is now a standard strategy in the field of
phylogenomics. However, practical implementations of summary methods
suffer from gene tree estimation error, which is caused by various
biological and analytical factors. Greatly understudied is the choice of
gene tree inference method and downstream effects on species tree
estimation for empirical data sets. To better understand the impact of
this method choice on gene and species tree accuracy, we compare gene
trees estimated through four widely used programs under different
model-selection criteria: PhyloBayes, MrBayes, IQ-Tree and RAxML. We study
their performance in the phylogenomic framework of > 800
ultraconserved elements from the bee subfamily Nomiinae (Halictidae). Our
taxon sampling focuses on the genus Pseudapis, a distinct lineage with
diverse morphological features, but contentious morphology-based taxonomic
classifications and no molecular phylogenetic guidance. We approximate
topological accuracy of gene trees by assessing their ability to recover
two uncontroversial, monophyletic groups, and compare branch lengths of
individual trees using the stemminess metric (the relative length of
internal branches). We further examine different strategies of removing
uninformative loci and the collapsing of weakly supported nodes into
polytomies. We then summarize gene trees with ASTRAL and compare resulting
species phylogenies, including comparisons to concatenation-based
estimates. Gene trees obtained with the reversible jump model search in
MrBayes were most concordant on average and all Bayesian methods yielded
gene trees with better stemminess values. The only gene tree estimation
approach whose ASTRAL summary trees consistently produced the most likely
correct topology, however, was IQ-Tree with automated model designation
(MFP). We discuss these findings and provide practical advice on gene tree
estimation for summary methods. Lastly, we establish the first
phylogeny-informed classification for Pseudapis s. l. and map the
distribution of distinct morphological features of the group.