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Cited by 1,516Genomics and Phylogenetic StudiesRNA and protein synthesis mechanismsBayesian Methods and Mixture Models

A Bayesian Mixture Model for Across-Site Heterogeneities in the Amino-Acid Replacement Process

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Lartillot, Nicolas, Philippe, Hervé·2004·Molecular Biology and Evolution
DOI 10.1093/molbev/msh112
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Abstract

Most current models of sequence evolution assume that all sites of a protein evolve under the same substitution process, characterized by a 20 x 20 substitution matrix. Here, we propose to relax this assumption by developing a Bayesian mixture model that allows the amino-acid replacement pattern at different sites of a protein alignment to be described by distinct substitution processes. Our model, named CAT, assumes the existence of distinct processes (or classes) differing by their equilibrium frequencies over the 20 residues. Through the use of a Dirichlet process prior, the total number of classes and their respective amino-acid profiles, as well as the affiliations of each site to a given class, are all free variables of the model. In this way, the CAT model is able to adapt to the complexity actually present in the data, and it yields an estimate of the substitutional heterogeneity through the posterior mean number of classes. We show that a significant level of heterogeneity is present in the substitution patterns of proteins, and that the standard one-matrix model fails to account for this heterogeneity. By evaluating the Bayes factor, we demonstrate that the standard model is outperformed by CAT on all of the data sets which we analyzed. Altogether, these results suggest that the complexity of the pattern of substitution of real sequences is better captured by the CAT model, offering the possibility of studying its impact on phylogenetic reconstruction and its connections with structure-function determinants.

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  • At least two additional sources of uncertainty not studied here are uncertainty introduced by the birth-death time prior and its failure to accommodate diversified sampling of species in phylogenies, and uncertainty due to the substitution model, which may have an important effect when estimating branch lengths in ancient phylogenies.

    “The situation is compounded by at least two additional sources of uncertainty that we did not study here: uncertainty introduced by the birth-death time prior, and its failure to accommodate diversified sampling of species in phylogenies [65], and uncertainty due to the substitution model, which may have an important effect when estimating branch lengths in ancient phylogenies [66, 67].”

    From Uncertainty in the Timing of Origin of Animals and the Limits of Precision in Molecular Timescales (2015) · cites this paper as [66]

  • Redmond and McLysaght's criticisms of Whelan and Halanych are without basis because Redmond and McLysaght did not perform analyses with the CAT models of PhyloBayes.

    “the criticisms of RM about Whelan and Halanych 9 , a study that compared the CAT models of PhyloBayes 10 to partitioning, are without basis as RM did not perform analyses with the CAT models of PhyloBayes.”

    From Available data do not rule out Ctenophora as the sister group to all other Metazoa (2023) · cites this paper as [10]

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Research works printed but not linked: 4

  1. [8]8. Dayhoff, M., R. V. Eck, and C. M. Park. 1972. A model of evolutionary change in proteins. Pp. 88-89 In M. Dayhoff, ed., Atlas of Protein Sequence and Structure, National Biomedical Research Foundation, Washington, D.C.
  2. [9]9. Dayhoff, M., R. Schwartz, and B. Orcutt. 1978. A model of evolutionary change in proteins. Pp. 345-352 In M. Dayhoff, ed., Atlas of Protein Sequence and Structure, National Biomedical Research Foundation, Washington, D.C.
  3. [29]29. ---. 1961. Theory of Probability. Oxford University Press.
  4. [39]39. Lopez, P. 1997. Analyse phyloge ´ne ´tique de grands alignements de prote ´ines: vers une classification des sites? Master degree dissertation, Universite ´Paris XI, Paris, France.

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Authors
Lartillot, N., & Philippe, H.
Affiliations
Canadian Institute for Advanced Research (CA)
Corresponding author
Lartillot, Nicolas
ORCID
Lartillot, Nicolas
Venue
Molecular Biology and Evolution
Publisher
Oxford University Press (OUP)
Published
2004-06
Volume
21
Issue
6
Pages
1095-1109
ISSN
  • 0737-4038 (ISSN-L)
  • 1537-1719
DOI
10.1093/molbev/msh112
OpenAlex
W2147307434
Cited by
1,516
References
58
Citations by year
2026: 42 · 2025: 53 · 2024: 90 · 2023: 62 · 2022: 78 · 2021: 90 · 2020: 78 · 2019: 98 · 2018: 106 · 2017: 82 · 2016: 79 · 2015: 81 · 2014: 107 · 2013: 76 · 2012: 65
FWCI
6.59
Type
journal article
Language
en
Open access
Locations
  • Molecular Biology and Evolution (publishedVersion)
  • PubMed (publishedVersion)
  • HAL (submittedVersion, cc-by)
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 › Computer Science › Artificial Intelligence › Bayesian Methods and Mixture Models
Keywords
cat model, Bayesian mixture models, Dirichlet process prior, protein sequence evolution, substitution matrices, phylogenetic inference
MeSH terms
Amino Acid Sequence, Bayes Theorem, Models, Genetic, Phylogeny, Sequence Alignment, Evolution, Molecular, Amino Acid Substitution

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