Redefining Possible: Combining Phylogenomic and Supersparse Data in Frogs
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Department of Ecology and Evolutionary Biology, University of ArizonaIssue Date
2023-05-04
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Oxford University PressCitation
Daniel M Portik, Jeffrey W Streicher, David C Blackburn, Daniel S Moen, Carl R Hutter, John J Wiens, Redefining Possible: Combining Phylogenomic and Supersparse Data in Frogs, Molecular Biology and Evolution, Volume 40, Issue 5, May 2023, msad109, https://doi.org/10.1093/molbev/msad109Journal
Molecular Biology and EvolutionRights
© The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/).Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
The data available for reconstructing molecular phylogenies have become wildly disparate. Phylogenomic studies can generate data for thousands of genetic markers for dozens of species, but for hundreds of other taxa, data may be available from only a few genes. Can these two types of data be integrated to combine the advantages of both, addressing the relationships of hundreds of species with thousands of genes? Here, we show that this is possible, using data from frogs. We generated a phylogenomic data set for 138 ingroup species and 3,784 nuclear markers (ultraconserved elements [UCEs]), including new UCE data from 70 species. We also assembled a supermatrix data set, including data from 97% of frog genera (441 total), with 1–307 genes per taxon. We then produced a combined phylogenomic–supermatrix data set (a “gigamatrix”) containing 441 ingroup taxa and 4,091 markers but with 86% missing data overall. Likelihood analysis of the gigamatrix yielded a generally well-supported tree among families, largely consistent with trees from the phylogenomic data alone. All terminal taxa were placed in the expected families, even though 42.5% of these taxa each had >99.5% missing data and 70.2% had >90% missing data. Our results show that missing data need not be an impediment to successfully combining very large phylogenomic and supermatrix data sets, and they open the door to new studies that simultaneously maximize sampling of genes and taxa. © The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.Note
Open access articleISSN
0737-4038PubMed ID
37140129Version
Final Published Versionae974a485f413a2113503eed53cd6c53
10.1093/molbev/msad109
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Except where otherwise noted, this item's license is described as © The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/).
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