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Phylogenomic data sets are illuminating many areas of the Tree of Life. However, the large size of these data sets alone may be insufficient to resolve problematic nodes in the most rapid evolutionary radiations, because inferences in zones of extraordinarily low phylogenetic signal can be sensitive to the model and method of inference, as well as the information content of loci employed. We used a data set of $&gt;$3950 ultraconserved element (UCE) loci from a classic mammalian radiation, ground-dwelling squirrels of the tribe Marmotini (Sciuridae: Xerinae), to assess sensitivity of phylogenetic estimates to varying per-locus information content across four different inference methods (RAxML, ASTRAL, NJst, and SVDquartets). Persistent discordance was found in topology and bootstrap support between concatenation- and coalescent-based inferences; among methods within the coalescent framework; and within all methods in response to different filtering scenarios. Contrary to some recent empirical UCE-based studies, filtering by information content did not promote complete among-method concordance. Nevertheless, filtering did improve concordance relative to randomly selected locus sets, largely via improved consistency of two-step summary methods (particularly NJst) under conditions of higher average per-locus variation (and thus increasing gene tree precision). The benefits of phylogenomic data set filtering are variable among classes of inference methods and across different evolutionary scenarios, reiterating the complexities of resolving rapid radiations, even with robust taxon and character sampling.

Impacts of Inference Method and Data set Filtering on Phylogenomic Resolution in a Rapid Radiation of Ground Squirrels (Xerinae: Marmotini)