Literature DB >> 14597178

Detecting excess radical replacements in phylogenetic trees.

Tal Pupko1, Roded Sharan, Masami Hasegawa, Ron Shamir, Dan Graur.   

Abstract

There are a few instances in which positive Darwinian selection has been convincingly demonstrated at the molecular level. In this study, we present a novel test for detecting excess of radical amino-acid replacements. Such excess is usually indicative of positive Darwinian selection, but may also be due to relaxed functional constraints or model misspecification. In our test, each amino-acid replacement is characterized in terms of a physicochemical distance, i.e., the degree of dissimilarity between the exchanged amino-acid residues. By using phylogenetic trees based on protein sequences, our test identifies statistically significant deviations of the mean physicochemical distance from the random expectation, either along a taxonomic lineage or across a subtree. The mean inferred distance is calculated as the average physicochemical distance over all possible ancestral sequence reconstructions weighted by their likelihood. Our method substantially improves over previous approaches by taking into account the stochastic process, tree phylogeny, among-site rate variation, and alternative ancestral reconstructions. We provide a fast linear time algorithm for applying this test to all branches and all subtrees of a given phylogenetic tree. We validate this approach by applying it to two well-studied datasets: the MHC class I glycoproteins serving as a positive control, and the house-keeping gene carbonic anhydrase I serving as a negative control.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 14597178     DOI: 10.1016/s0378-1119(03)00802-3

Source DB:  PubMed          Journal:  Gene        ISSN: 0378-1119            Impact factor:   3.688


  10 in total

1.  Characterizing molecular adaptation: a hierarchical approach to assess the selective influence of amino acid properties.

Authors:  Saheli Datta; Raquel Prado; Abel Rodríguez; Ananías A Escalante
Journal:  Bioinformatics       Date:  2010-09-16       Impact factor: 6.937

2.  Enhanced synonymous site divergence in positively selected vertebrate antimicrobial peptide genes.

Authors:  Jacob A Tennessen
Journal:  J Mol Evol       Date:  2005-09-12       Impact factor: 2.395

3.  The exchangeability of amino acids in proteins.

Authors:  Lev Y Yampolsky; Arlin Stoltzfus
Journal:  Genetics       Date:  2005-06-08       Impact factor: 4.562

4.  The site-wise log-likelihood score is a good predictor of genes under positive selection.

Authors:  Huai-Chun Wang; Edward Susko; Andrew J Roger
Journal:  J Mol Evol       Date:  2013-04-18       Impact factor: 2.395

5.  Evolution of BK virus based on complete genome data.

Authors:  Yuriko Nishimoto; Tomokazu Takasaka; Masami Hasegawa; Huai-Ying Zheng; Qin Chen; Chie Sugimoto; Tadaichi Kitamura; Yoshiaki Yogo
Journal:  J Mol Evol       Date:  2006-07-28       Impact factor: 2.395

6.  Evolutionary patterns of amino acid substitutions in 12 Drosophila genomes.

Authors:  Lev Y Yampolsky; Michael A Bouzinier
Journal:  BMC Genomics       Date:  2010-12-02       Impact factor: 3.969

7.  Reduced selective constraint in endosymbionts: elevation in radical amino acid replacements occurs genome-wide.

Authors:  Jennifer J Wernegreen
Journal:  PLoS One       Date:  2011-12-14       Impact factor: 3.240

8.  Fast and robust characterization of time-heterogeneous sequence evolutionary processes using substitution mapping.

Authors:  Jonathan Romiguier; Emeric Figuet; Nicolas Galtier; Emmanuel J P Douzery; Bastien Boussau; Julien Y Dutheil; Vincent Ranwez
Journal:  PLoS One       Date:  2012-03-27       Impact factor: 3.240

9.  Adaptive evolution of the chrysanthemyl diphosphate synthase gene involved in irregular monoterpene metabolism.

Authors:  Ping-Li Liu; Jun-Nan Wan; Yan-Ping Guo; Song Ge; Guang-Yuan Rao
Journal:  BMC Evol Biol       Date:  2012-11-08       Impact factor: 3.260

10.  Evidence for the Selective Basis of Transition-to-Transversion Substitution Bias in Two RNA Viruses.

Authors:  Daniel M Lyons; Adam S Lauring
Journal:  Mol Biol Evol       Date:  2017-12-01       Impact factor: 16.240

  10 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.