Efficient Inference of Macrophylogenies: Insights from the Avian Tree of Life

The exponential growth of molecular sequence data over the past decade has enabled the construction of numerous clade-specific phylogenies encompassing hundreds or thousands of taxa. These independent studies often include overlapping data, presenting a unique opportunity to build macrophylogenies (phylogenies sampling > 1,000 taxa) for entire classes across the Tree of Life. However, the inference of large trees remains constrained by logistical, computational, and methodological challenges. The Avian Tree of Life provides an ideal model for evaluating strategies to robustly infer macrophylogenies from intersecting datasets derived from smaller studies. In this study, we leveraged a comprehensive resource of sequence capture datasets to evaluate the phylogenetic accuracy and computational costs of four methodological approaches: (1) supermatrix approaches using concatenation, including the "fast" maximum likelihood (ML) methods, (2) filtering datasets to reduce heterogeneity, (3) supertree estimation based on published phylogenomic trees, and (4) a "divide-and-conquer" strategy, wherein smaller ML trees were estimated and subsequently combined using a supertree approach. Additionally, we examined the impact of these methods on divergence time estimation using a dataset that includes newly vetted fossil calibrations for the Avian Tree of Life. Our findings highlight the advantages of recently developed fast tree search approaches initiated with parsimony starting trees, which offer a reasonable compromise between computational efficiency and phylogenetic accuracy, facilitating inference of macrophylogenies.

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Publication Details

Journal
Systematic Biology
Published
2025-11-08
DOI
https://doi.org/10.1093/sysbio/syaf080
Citations
2
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
1.61
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article

Efficient Inference of Macrophylogenies: Insights from the Avian Tree of Life

Travis C. Glenn, Michael J. Braun, Peter A. Hosner, Leo Joseph et al.
2 citations
Systematic Biology
Genomics and Phylogenetic Studies
1.61
article

Efficient Inference of Macrophylogenies: Insights from the Avian Tree of Life

Travis C. Glenn, Michael J. Braun, Peter A. Hosner, Leo Joseph, Kevin Winker, Michael Harvey, Brant C. Faircloth, Carl H. Oliveros, Daniel T. Ksepka, Gregory Thom, John E. McCormack, Michael J. Andersen, Rebecca T. Kimball, Daniel J. Field, Elizabeth P. Derryberry, Robb T. Brumfield, Brett W. Benz, Gustavo A. Bravo, F. Keith Barker, Noor D. White, Robert G. Moyle, Tyler S Imfeld, Brian Tilston Smith, R. Terry Chesser, Edward L. Braun, Jenna M. McCullough, Joseph D. Manthey, Min Zhao
article en
2 citations

Abstract

The exponential growth of molecular sequence data over the past decade has enabled the construction of numerous clade-specific phylogenies encompassing hundreds or thousands of taxa. These independent studies often include overlapping data, presenting a unique opportunity to build macrophylogenies (phylogenies sampling > 1,000 taxa) for entire classes across the Tree of Life. However, the inference of large trees remains constrained by logistical, computational, and methodological challenges. The Avian Tree of Life provides an ideal model for evaluating strategies to robustly infer macrophylogenies from intersecting datasets derived from smaller studies. In this study, we leveraged a comprehensive resource of sequence capture datasets to evaluate the phylogenetic accuracy and computational costs of four methodological approaches: (1) supermatrix approaches using concatenation, including the "fast" maximum likelihood (ML) methods, (2) filtering datasets to reduce heterogeneity, (3) supertree estimation based on published phylogenomic trees, and (4) a "divide-and-conquer" strategy, wherein smaller ML trees were estimated and subsequently combined using a supertree approach. Additionally, we examined the impact of these methods on divergence time estimation using a dataset that includes newly vetted fossil calibrations for the Avian Tree of Life. Our findings highlight the advantages of recently developed fast tree search approaches initiated with parsimony starting trees, which offer a reasonable compromise between computational efficiency and phylogenetic accuracy, facilitating inference of macrophylogenies.

Systematic Biology
Louisiana State University (US), Texas Tech University (US), Science Museum of Minnesota (US), United States Geological Survey (US), National Institutes of Health (US), University of Minnesota (US), Houston Museum of Natural Science (US), American Museum of Natural History (US), National Museum of Natural History (US), Harvard University (US), University of Alaska Fairbanks (US), University of Kentucky (US), University of Kansas (US), The University of Texas at El Paso (US), University of Georgia (US), University of New Mexico (US), Xavier University (US), University of Cambridge (GB), University of Michigan (US), Alexander von Humboldt Biological Resources Research Institute (CO), University of Florida (US), Alexander von Humboldt Foundation (DE), New Mexico Museum of Natural History and Science (US), Natural History Museum Aarhus (DK), Bruce Museum (US), Circle Park (US), Institute of Zoology (KZ), National Eye Institute (US), Washington DC VA Medical Center (US), Australian National Wildlife Collection (AU), Department of Earth Sciences (RU), Eastern Ecological Science Center, University of Maryland, College Park (US), Occidental College (US), University of Tennessee at Knoxville (US), Virginia Tech (US)
Openalex Percentile: Top 14%
Genomics and Phylogenetic Studies
1.61
DOISourceOpenAlex
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