Literature DB >> 18696030

Detecting site-specific biochemical constraints through substitution mapping.

Julien Dutheil1.   

Abstract

The neutral theory of molecular evolution states that most mutations are deleterious or neutral. It results that the evolutionary rate of a given position in an alignment is a function of the level of constraint acting on this position. Inferring evolutionary rates from a set of aligned sequences is hence a powerful method to detect functionally and/or structurally important positions in a protein. Some positions, however, may be constrained while having a high substitution rate, providing these substitutions do not affect the biochemical property under constraint. Here, I introduce a new evolutionary rate measure accounting for the evolution of specific biochemical properties (e.g., volume, polarity, and charge). I then present a new statistical method based on the comparison of two rate measures: a site is said to be constrained for property X if it shows an unexpectedly high conservation of X knowing its total evolutionary rate. Compared to single-rate methods, the two-rate method offers several advantages: it (i) allows assessment of the significance of the constraint, (ii) provides information on the type of constraint acting on each position, and (iii) detects positions that are not proposed by previous methods. I apply this method to a 200-sequence data set of triosephosphate isomerase and report significant cases of positions constrained for polarity, volume, or charge. The three-dimensional localization of these positions shows that they are of potential interest to the molecular evolutionist and to the biochemist.

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Year:  2008        PMID: 18696030     DOI: 10.1007/s00239-008-9139-8

Source DB:  PubMed          Journal:  J Mol Evol        ISSN: 0022-2844            Impact factor:   2.395


  25 in total

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Authors:  Fabian Glaser; Tal Pupko; Inbal Paz; Rachel E Bell; Dalit Bechor-Shental; Eric Martz; Nir Ben-Tal
Journal:  Bioinformatics       Date:  2003-01       Impact factor: 6.937

5.  Structure of yeast triosephosphate isomerase at 1.9-A resolution.

Authors:  E Lolis; T Alber; R C Davenport; D Rose; F C Hartman; G A Petsko
Journal:  Biochemistry       Date:  1990-07-17       Impact factor: 3.162

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Authors:  N Goldman; J L Thorne; D T Jones
Journal:  Genetics       Date:  1998-05       Impact factor: 4.562

7.  Likelihood models for detecting positively selected amino acid sites and applications to the HIV-1 envelope gene.

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Journal:  Genetics       Date:  1998-03       Impact factor: 4.562

8.  A new method of inference of ancestral nucleotide and amino acid sequences.

Authors:  Z Yang; S Kumar; M Nei
Journal:  Genetics       Date:  1995-12       Impact factor: 4.562

9.  Detecting site-specific physicochemical selective pressures: applications to the Class I HLA of the human major histocompatibility complex and the SRK of the plant sporophytic self-incompatibility system.

Authors:  Raazesh Sainudiin; Wendy Shuk Wan Wong; Krithika Yogeeswaran; June B Nasrallah; Ziheng Yang; Rasmus Nielsen
Journal:  J Mol Evol       Date:  2005-03       Impact factor: 2.395

10.  Bio++: a set of C++ libraries for sequence analysis, phylogenetics, molecular evolution and population genetics.

Authors:  Julien Dutheil; Sylvain Gaillard; Eric Bazin; Sylvain Glémin; Vincent Ranwez; Nicolas Galtier; Khalid Belkhir
Journal:  BMC Bioinformatics       Date:  2006-04-04       Impact factor: 3.169

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  6 in total

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Journal:  BMC Evol Biol       Date:  2011-11-21       Impact factor: 3.260

4.  Comparison of methods for calculating conditional expectations of sufficient statistics for continuous time Markov chains.

Authors:  Paula Tataru; Asger Hobolth
Journal:  BMC Bioinformatics       Date:  2011-12-05       Impact factor: 3.169

5.  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

6.  Drug resistance missense mutations in cancer are subject to evolutionary constraints.

Authors:  Ran Friedman
Journal:  PLoS One       Date:  2013-12-20       Impact factor: 3.240

  6 in total

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