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Dryad

UCE alignments and phylogenetic trees

Cite this dataset

Blair, Christopher et al. (2021). UCE alignments and phylogenetic trees [Dataset]. Dryad. https://doi.org/10.5061/dryad.gb5mkkwqp

Abstract

Genomic data continue to advance our understanding of species limits and biogeographic patterns. However, there is still no consensus regarding appropriate methods of phylogenomic analysis that make the best use of these heterogeneous data sets. In this study, we used thousands of ultraconserved element (UCE) loci from alligator lizards in the genus Gerrhonotus to compare and contrast species trees inferred using multiple contemporary methods and provide a timeframe for biological diversification across the Mexican Transition Zone (MTZ). Concatenated maximum likelihood (ML) and Bayesian analyses provide highly congruent results, with differences limited to poorly supported nodes. Similar topologies were inferred from coalescent analyses in BPP and SVDquartets, albeit with lower support for some nodes. All divergence times fell within the Miocene, linking speciation to local Neogene vicariance and/or global cooling trends following the mid-Miocene Climatic Optimum. We detected a high level of genomic divergence for a morphologically distinct species restricted to the arid mountains of northeastern Mexico, and erected a new genus to better reflect evolutionary history. In sum, our results further advocate leveraging the strengths and weaknesses of concatenation and coalescent methods, provide evidence for old divergences for alligator lizards, and indicate that the MTZ continues to harbor substantial unrecognized diversity.

Usage notes

Please find both individual and concatenated UCE alignments. We are also submitting tree files resulting from each of the phylogenetic analyses.

Funding

National Science Foundation, Award: DEB-1929679

National Science Foundation, Award: DEB-1257785

National Science Foundation, Award: DEB-1258205

Universidad Nacional Autónoma de México, Award: IN216619

Consejo Nacional de Humanidades, Ciencias y Tecnologías, Award: A1-S-37838