Literature DB >> 12411592

A novel use of equilibrium frequencies in models of sequence evolution.

Nick Goldman1, Simon Whelan.   

Abstract

Current mathematical models of amino acid sequence evolution are often applied in variants that match their expected amino acid frequencies to those observed in a data set under analysis. This has been achieved by setting the instantaneous rate of replacement of a residue i by another residue j proportional to the observed frequency of the resulting residue j. We describe a more general method that maintains the match between expected and observed frequencies but permits replacement rates to be proportional to the frequencies of both the replaced and resulting residues, raised to powers other than 1. Analysis of a database of amino acid alignments shows that the description of the evolutionary process in a majority (approximately 70% of 182 alignments) is significantly improved by use of the new method, and a variety of analyses indicate that parameter estimation with the new method is well-behaved. Improved evolutionary models increase our understanding of the process of molecular evolution and are often expected to lead to improved phylogenetic inferences, and so it seems justified to consider our new variants of existing standard models when performing evolutionary analyses of amino acid sequences. Similar methods can be used with nucleotide substitution models, but we have not found these to give corresponding significant improvements to our ability to describe the processes of nucleotide sequence evolution.

Mesh:

Year:  2002        PMID: 12411592     DOI: 10.1093/oxfordjournals.molbev.a004007

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


  17 in total

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Authors:  Rolf Olsen; William F Loomis
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2.  Solving the protein sequence metric problem.

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Journal:  Proc Natl Acad Sci U S A       Date:  2005-04-25       Impact factor: 11.205

3.  Efficient methods for estimating amino acid replacement rates.

Authors:  Lars Arvestad
Journal:  J Mol Evol       Date:  2006-04-28       Impact factor: 2.395

4.  Bayesian comparisons of codon substitution models.

Authors:  Nicolas Rodrigue; Nicolas Lartillot; Hervé Philippe
Journal:  Genetics       Date:  2008-09-14       Impact factor: 4.562

5.  Selective pressure to increase charge in immunodominant epitopes of the H3 hemagglutinin influenza protein.

Authors:  Keyao Pan; Jinxue Long; Haoxin Sun; Gregory J Tobin; Peter L Nara; Michael W Deem
Journal:  J Mol Evol       Date:  2010-11-18       Impact factor: 2.395

6.  High diversity at PRDM9 in chimpanzees and bonobos.

Authors:  Linn Fenna Groeneveld; Rebeca Atencia; Rosa M Garriga; Linda Vigilant
Journal:  PLoS One       Date:  2012-07-02       Impact factor: 3.240

7.  CodonPhyML: fast maximum likelihood phylogeny estimation under codon substitution models.

Authors:  Manuel Gil; Marcelo Serrano Zanetti; Stefan Zoller; Maria Anisimova
Journal:  Mol Biol Evol       Date:  2013-02-23       Impact factor: 16.240

8.  Markovian and non-Markovian protein sequence evolution: aggregated Markov process models.

Authors:  Carolin Kosiol; Nick Goldman
Journal:  J Mol Biol       Date:  2011-06-21       Impact factor: 5.469

9.  Addressing inter-gene heterogeneity in maximum likelihood phylogenomic analysis: yeasts revisited.

Authors:  Jaqueline Hess; Nick Goldman
Journal:  PLoS One       Date:  2011-08-05       Impact factor: 3.240

10.  Efficient context-dependent model building based on clustering posterior distributions for non-coding sequences.

Authors:  Guy Baele; Yves Van de Peer; Stijn Vansteelandt
Journal:  BMC Evol Biol       Date:  2009-04-30       Impact factor: 3.260

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