Literature DB >> 18319244

A mixed branch length model of heterotachy improves phylogenetic accuracy.

Bryan Kolaczkowski1, Joseph W Thornton.   

Abstract

Evolutionary relationships are typically inferred from molecular sequence data using a statistical model of the evolutionary process. When the model accurately reflects the underlying process, probabilistic phylogenetic methods recover the correct relationships with high accuracy. There is ample evidence, however, that models commonly used today do not adequately reflect real-world evolutionary dynamics. Virtually all contemporary models assume that relatively fast-evolving sites are fast across the entire tree, whereas slower sites always evolve at relatively slower rates. Many molecular sequences, however, exhibit site-specific changes in evolutionary rates, called "heterotachy." Here we examine the accuracy of 2 phylogenetic methods for incorporating heterotachy, the mixed branch length model--which incorporates site-specific rate changes by summing likelihoods over multiple sets of branch lengths on the same tree--and the covarion model, which uses a hidden Markov process to allow sites to switch between variable and invariable as they evolve. Under a variety of simple heterogeneous simulation conditions, the mixed model was dramatically more accurate than homotachous models, which were subject to topological biases as well as biases in branch length estimates. When data were simulated with strong versions of the types of heterotachy observed in real molecular sequences, the mixed branch length model was more accurate than homotachous techniques. Analyses of empirical data sets confirmed that the mixed branch length model can improve phylogenetic accuracy under conditions that cause homotachous models to fail. In contrast, the covarion model did not improve phylogenetic accuracy compared with homotachous models and was sometimes substantially less accurate. We conclude that a mixed branch length approach, although not the solution to all phylogenetic errors, is a valuable strategy for improving the accuracy of inferred trees.

Mesh:

Year:  2008        PMID: 18319244      PMCID: PMC3299401          DOI: 10.1093/molbev/msn042

Source DB:  PubMed          Journal:  Mol Biol Evol        ISSN: 0737-4038            Impact factor:   16.240


  66 in total

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Authors:  J Castresana
Journal:  Mol Biol Evol       Date:  2000-04       Impact factor: 16.240

2.  Maximum-likelihood phylogenetic analysis under a covarion-like model.

Authors:  N Galtier
Journal:  Mol Biol Evol       Date:  2001-05       Impact factor: 16.240

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Journal:  Syst Biol       Date:  2002-06       Impact factor: 15.683

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Journal:  Mol Biol Evol       Date:  2005-02-09       Impact factor: 16.240

5.  Modeling compositional heterogeneity.

Authors:  Peter G Foster
Journal:  Syst Biol       Date:  2004-06       Impact factor: 15.683

6.  An improved statistical method for detecting heterotachy in nucleotide sequences.

Authors:  Guy Baele; Jeroen Raes; Yves Van de Peer; Stijn Vansteelandt
Journal:  Mol Biol Evol       Date:  2006-05-03       Impact factor: 16.240

7.  Pitfalls of heterogeneous processes for phylogenetic reconstruction.

Authors:  Daniel Stefankovic; Eric Vigoda
Journal:  Syst Biol       Date:  2007-02       Impact factor: 15.683

8.  Phylogenetic mixtures on a single tree can mimic a tree of another topology.

Authors:  Frederick A Matsen; Mike Steel
Journal:  Syst Biol       Date:  2007-10       Impact factor: 15.683

9.  Inferring pattern and process: maximum-likelihood implementation of a nonhomogeneous model of DNA sequence evolution for phylogenetic analysis.

Authors:  N Galtier; M Gouy
Journal:  Mol Biol Evol       Date:  1998-07       Impact factor: 16.240

10.  Heterotachy in mammalian promoter evolution.

Authors:  Martin S Taylor; Chikatoshi Kai; Jun Kawai; Piero Carninci; Yoshihide Hayashizaki; Colin A M Semple
Journal:  PLoS Genet       Date:  2006-04-28       Impact factor: 5.917

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  33 in total

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Authors:  Richard Gouy; Denis Baurain; Hervé Philippe
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2015-09-26       Impact factor: 6.237

2.  Modelling heterotachy in phylogenetic inference by reversible-jump Markov chain Monte Carlo.

Authors:  Mark Pagel; Andrew Meade
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2008-12-27       Impact factor: 6.237

Review 3.  Statistics and truth in phylogenomics.

Authors:  Sudhir Kumar; Alan J Filipski; Fabia U Battistuzzi; Sergei L Kosakovsky Pond; Koichiro Tamura
Journal:  Mol Biol Evol       Date:  2011-08-26       Impact factor: 16.240

4.  Phylogenomic resolution of scorpions reveals multilevel discordance with morphological phylogenetic signal.

Authors:  Prashant P Sharma; Rosa Fernández; Lauren A Esposito; Edmundo González-Santillán; Lionel Monod
Journal:  Proc Biol Sci       Date:  2015-04-07       Impact factor: 5.349

5.  mtProtEvol: the resource presenting molecular evolution analysis of proteins involved in the function of Vertebrate mitochondria.

Authors:  Anastasia A Kuzminkova; Anastasia D Sokol; Kristina E Ushakova; Konstantin Yu Popadin; Konstantin V Gunbin
Journal:  BMC Evol Biol       Date:  2019-02-26       Impact factor: 3.260

6.  Phylogenetic tree reconstruction accuracy and model fit when proportions of variable sites change across the tree.

Authors:  Liat Shavit Grievink; David Penny; Michael D Hendy; Barbara R Holland
Journal:  Syst Biol       Date:  2010-03-01       Impact factor: 15.683

7.  Mitochondrial genome evolution in fire ants (Hymenoptera: Formicidae).

Authors:  Dietrich Gotzek; Jessica Clarke; DeWayne Shoemaker
Journal:  BMC Evol Biol       Date:  2010-10-07       Impact factor: 3.260

8.  Pervasive cryptic epistasis in molecular evolution.

Authors:  Mark Lunzer; G Brian Golding; Antony M Dean
Journal:  PLoS Genet       Date:  2010-10-21       Impact factor: 5.917

9.  PROCOV: maximum likelihood estimation of protein phylogeny under covarion models and site-specific covarion pattern analysis.

Authors:  Huai-Chun Wang; Edward Susko; Andrew J Roger
Journal:  BMC Evol Biol       Date:  2009-09-08       Impact factor: 3.260

10.  Long-branch attraction bias and inconsistency in Bayesian phylogenetics.

Authors:  Bryan Kolaczkowski; Joseph W Thornton
Journal:  PLoS One       Date:  2009-12-09       Impact factor: 3.240

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