Larger, unfiltered datasets are more effective at resolving phylogenetic conflict: Introns, exons, and UCEs resolve ambiguities in Golden-backed frogs (Anura: Ranidae; genus Hylarana).

Using FrogCap, a recently-developed sequence-capture protocol, we obtained >12,000 highly informative exons, introns, and ultraconserved elements (UCEs), which we used to illustrate variation in evolutionary histories of these classes of markers, and to resolve long-standing systematic problems in Southeast Asian Golden-backed frogs of the genus-complex Hylarana. We also performed a comprehensive suite of analyses to assess the relative performance of different genetic markers, data filtering strategies, tree inference methods, and different measures of branch support. To reduce gene tree estimation error, we filtered the data using different thresholds of taxon completeness (missing data) and parsimony informative sites (PIS). We then estimated species trees using concatenated datasets and Maximum Likelihood (IQ-TREE) in addition to summary (ASTRAL-III), distance-based (ASTRID), and site-based (SVDQuartets) multispecies coalescent methods. Topological congruence and branch support were examined using traditional bootstrap, local posterior probabilities, gene concordance factors, quartet frequencies, and quartet scores. Our results did not yield a single concordant topology. Instead, introns, exons, and UCEs clearly possessed different phylogenetic signals, resulting in conflicting, yet strongly-supported phylogenetic estimates. However, a combined analysis comprising the most informative introns, exons, and UCEs converged on a similar topology across all analyses, with the exception of SVDQuartets. Bootstrap values were consistently high despite high levels of incongruence and high proportions of gene trees supporting conflicting topologies. Although low bootstrap values did indicate low heuristic support, high bootstrap support did not necessarily reflect congruence or support for the correct topology. This study reiterates findings of some previous studies, which demonstrated that traditional bootstrap values can produce positively misleading measures of support in large phylogenomic datasets. We also showed a remarkably strong positive relationship between branch length and topological congruence across all datasets, implying that very short internodes remain a challenge to resolve, even with orders of magnitude more data than ever before. Overall, our results demonstrate that more data from unfiltered or combined datasets produced superior results. Although data filtering reduced gene tree incongruence, decreased amounts of data also biased phylogenetic estimation. A point of diminishing returns was evident, at which higher congruence (from more stringent filtering) at the expense of amount of data led to topological error as assessed by comparison to more complete datasets across different genomic markers. Additionally, we showed that applying a parameter-rich model to a partitioned analysis of concatenated data produces better results compared to unpartitioned, or even partitioned analysis using model selection. Despite some lingering uncertainties, a combined analysis of our genomic data and sequences supplemented from GenBank (on the basis of a few gene regions) revealed highly supported novel systematic arrangements. Based on these new findings, we transfer Amnirana nicobariensis into the genus Indosylvirana; and I. milleti and Hylarana celebensis to the genus Papurana. We also provisionally place H. attigua in the genus Papurana pending verification from positively identified (voucher substantiated) samples.