Modeling Site Heterogeneity with Posterior Mean Site Frequency Profiles Accelerates Accurate Phylogenomic Estimation
Abstract
Proteins have distinct structural and functional constraints at different sites that lead to site-specific preferences for particular amino acid residues as the sequences evolve. Heterogeneity in the amino acid substitution process between sites is not modeled by commonly used empirical amino acid exchange matrices. Such model misspecification can lead to artefacts in phylogenetic estimation such as long-branch attraction. Although sophisticated site-heterogeneous mixture models have been developed to address this problem in both Bayesian and maximum likelihood (ML) frameworks, their formidable computational time and memory usage severely limits their use in large phylogenomic analyses. Here we propose a posterior mean site frequency (PMSF) method as a rapid and efficient approximation to full empirical profile mixture models for ML analysis. The PMSF approach assigns a conditional mean amino acid frequency profile to each site calculated based on a mixture model fitted to the data using a preliminary guide tree. These PMSF profiles can then be used for in-depth tree-searching in place of the full mixture model. Compared with widely used empirical mixture models with $k$ classes, our implementation of PMSF in IQ-TREE (http://www.iqtree.org) speeds up the computation by approximately $k$/1.5-fold and requires a small fraction of the RAM. Furthermore, this speedup allows, for the first time, full nonparametric bootstrap analyses to be conducted under complex site-heterogeneous models on large concatenated data matrices. Our simulations and empirical data analyses demonstrate that PMSF can effectively ameliorate long-branch attraction artefacts. In some empirical and simulation settings PMSF provided more accurate estimates of phylogenies than the mixture models from which they derive.
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Previous studies analysing the test datasets without partitioning have found support for the accepted topology under a variety of site-heterogeneous models.
“Previous studies analysing the test datasets used here, but without partitioning, have found support for the accepted topology under a variety of site-heterogeneous models22,56,60.”
From Evidence for sponges as sister to all other animals from partitioned phylogenomics with mixture models and recoding (2021) · cites this paper as [56]
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- Authors
- Wang, H.-C., Minh, B. Q., Susko, E., & Roger, A. J.
- Affiliations
- Dalhousie University (CA)
- Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, University of Vienna and Medical University of Vienna, Austria
- Corresponding author
- Roger, Andrew J
- Venue
- Systematic Biology
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-08-07
- Volume
- 67
- Issue
- 2
- Pages
- 216-235
- ISSN
- 1063-5157 (ISSN-L)
- 1076-836X
- OpenAlex
- W2744971808
- Cited by
- 466
- References
- 8
- Citations by year
- 2026: 58 · 2025: 49 · 2024: 76 · 2023: 52 · 2022: 67 · 2021: 56 · 2020: 50 · 2019: 33 · 2018: 21 · 2017: 4
- FWCI
- 12.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Systematic Biology (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Natural Sciences and Engineering Research Council of Canada
- Austrian Science Fund (FWF I-2805-B29)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA and protein synthesis mechanisms
- Physical Sciences › Earth and Planetary Sciences › Paleontology › Evolution and Paleontology Studies
- Keywords
- site heterogeneity, amino acid substitution models, long-branch attraction, IQ-TREE, nonparametric bootstrap, computational efficiency, protein sequence evolution
- MeSH terms
- Classification, Computer Simulation, Models, Genetic, Phylogeny, Statistics, Nonparametric, Evolution, Molecular, Amino Acid Substitution
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