4.6 Article

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

期刊

SYSTEMATIC BIOLOGY
卷 68, 期 2, 页码 298-316

出版社

OXFORD UNIV PRESS
DOI: 10.1093/sysbio/syy064

关键词

Coalescent; concatenation; gene tree estimation error; incomplete lineage sorting; UCEs

资金

  1. National Science Foundation [NSF 1258010]
  2. Smithsonian Institution (Peter Buck Predoctoral Fellowship)
  3. American Museum of Natural History (Theodore Roosevelt Memorial Research Grant)
  4. American Society of Mammalogists
  5. American Society of Mammalogists (ASM Fellowship)
  6. University of New Mexico Department of Biology
  7. University of New Mexico Graduate and Professional Student Association

向作者/读者索取更多资源

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 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.

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