Literature DB >> 16698770

Observations of amino acid gain and loss during protein evolution are explained by statistical bias.

Richard A Goldstein1, David D Pollock.   

Abstract

The authors of a recent manuscript in "Nature" claim to have discovered "universal trends" of amino acid gain and loss in protein evolution. Here, we show that this universal trend can be simply explained by a bias that is unavoidable with the 3-taxon trees used in the original analysis. We demonstrate that a rigorously reversible equilibrium model, when analyzed with the same methods as the "Nature" manuscript, yields identical (and in this case, clearly erroneous) conclusions. A main source of the bias is the division of the sequence data into "informative" and "noninformative" sites, which favors the observation of certain transitions.

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Year:  2006        PMID: 16698770      PMCID: PMC2943954          DOI: 10.1093/molbev/msl010

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


  16 in total

1.  Assessing an unknown evolutionary process: effect of increasing site-specific knowledge through taxon addition.

Authors:  D D Pollock; W J Bruno
Journal:  Mol Biol Evol       Date:  2000-12       Impact factor: 16.240

2.  Modeling evolution at the protein level using an adjustable amino acid fitness model.

Authors:  M W Dimmic; D P Mindell; R A Goldstein
Journal:  Pac Symp Biocomput       Date:  2000

3.  Dimerization in aminergic G-protein-coupled receptors: application of a hidden-site class model of evolution.

Authors:  Orkun S Soyer; Matthew W Dimmic; Richard R Neubig; Richard A Goldstein
Journal:  Biochemistry       Date:  2003-12-16       Impact factor: 3.162

4.  The rapid generation of mutation data matrices from protein sequences.

Authors:  D T Jones; W R Taylor; J M Thornton
Journal:  Comput Appl Biosci       Date:  1992-06

5.  Environment-specific amino acid substitution tables: tertiary templates and prediction of protein folds.

Authors:  J Overington; D Donnelly; M S Johnson; A Sali; T L Blundell
Journal:  Protein Sci       Date:  1992-02       Impact factor: 6.725

6.  Use of amino acid environment-dependent substitution tables and conformational propensities in structure prediction from aligned sequences of homologous proteins. II. Secondary structures.

Authors:  H Wako; T L Blundell
Journal:  J Mol Biol       Date:  1994-05-20       Impact factor: 5.469

7.  Context-dependent optimal substitution matrices.

Authors:  J M Koshi; R A Goldstein
Journal:  Protein Eng       Date:  1995-07

8.  A codon-based model of nucleotide substitution for protein-coding DNA sequences.

Authors:  N Goldman; Z Yang
Journal:  Mol Biol Evol       Date:  1994-09       Impact factor: 16.240

9.  Apparent trends of amino Acid gain and loss in protein evolution due to nearly neutral variation.

Authors:  John H McDonald
Journal:  Mol Biol Evol       Date:  2005-09-29       Impact factor: 16.240

10.  Ancestral sequence reconstruction in primate mitochondrial DNA: compositional bias and effect on functional inference.

Authors:  Neeraja M Krishnan; Hervé Seligmann; Caro-Beth Stewart; A P Jason De Koning; David D Pollock
Journal:  Mol Biol Evol       Date:  2004-06-30       Impact factor: 16.240

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  11 in total

1.  Sequence space and the ongoing expansion of the protein universe.

Authors:  Inna S Povolotskaya; Fyodor A Kondrashov
Journal:  Nature       Date:  2010-05-19       Impact factor: 49.962

2.  Evaluation of Ancestral Sequence Reconstruction Methods to Infer Nonstationary Patterns of Nucleotide Substitution.

Authors:  Tomotaka Matsumoto; Hiroshi Akashi; Ziheng Yang
Journal:  Genetics       Date:  2015-05-06       Impact factor: 4.562

Review 3.  Redox Regulation via Glutaredoxin-1 and Protein S-Glutathionylation.

Authors:  Reiko Matsui; Beatriz Ferran; Albin Oh; Dominique Croteau; Di Shao; Jingyan Han; David Richard Pimentel; Markus Michael Bachschmid
Journal:  Antioxid Redox Signal       Date:  2020-01-23       Impact factor: 8.401

4.  The universal trend of amino acid gain-loss is caused by CpG hypermutability.

Authors:  Kazuharu Misawa; Naoyuki Kamatani; Reiko F Kikuno
Journal:  J Mol Evol       Date:  2008-09-23       Impact factor: 2.395

5.  Universal and taxon-specific trends in protein sequences as a function of age.

Authors:  Jennifer E James; Sara M Willis; Paul G Nelson; Catherine Weibel; Luke J Kosinski; Joanna Masel
Journal:  Elife       Date:  2021-01-08       Impact factor: 8.140

6.  Evolution of proteomes: fundamental signatures and global trends in amino acid compositions.

Authors:  Fredj Tekaia; Edouard Yeramian
Journal:  BMC Genomics       Date:  2006-12-05       Impact factor: 3.969

7.  Why do eukaryotic proteins contain more intrinsically disordered regions?

Authors:  Walter Basile; Marco Salvatore; Claudio Bassot; Arne Elofsson
Journal:  PLoS Comput Biol       Date:  2019-07-22       Impact factor: 4.475

8.  Evidence from glycine transfer RNA of a frozen accident at the dawn of the genetic code.

Authors:  Harold S Bernhardt; Warren P Tate
Journal:  Biol Direct       Date:  2008-12-17       Impact factor: 4.540

9.  A universal trend among proteomes indicates an oily last common ancestor.

Authors:  Ranjan V Mannige; Charles L Brooks; Eugene I Shakhnovich
Journal:  PLoS Comput Biol       Date:  2012-12-27       Impact factor: 4.475

10.  Effect of the assignment of ancestral CpG state on the estimation of nucleotide substitution rates in mammals.

Authors:  Daniel J Gaffney; Peter D Keightley
Journal:  BMC Evol Biol       Date:  2008-09-30       Impact factor: 3.260

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