Literature DB >> 20847216

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

Saheli Datta1, Raquel Prado, Abel Rodríguez, Ananías A Escalante.   

Abstract

MOTIVATION: A number of methods for detecting positive selection in protein coding DNA sequences are based on whether each site/region has a non-synonymous to synonymous substitution rates ratio ω greater than one. However, a site/region may show a relatively large number of non-synonymous mutations that conserve a particular property. Recent methods have proposed to consider as evidence for molecular adaptations how conserving, or radically different, non-synonymous mutations are with respect to some key amino acid properties. While such methods have been useful in providing a qualitative assessment of molecular adaptation, they rely on independent statistical analyses for each amino acid property and typically do not properly adjust for multiple comparisons when selection needs to be assessed at several sites.
RESULTS: We consider a Bayesian hierarchical model that allows us to jointly determine if a set of amino acid properties are being conserved or radically changed while simultaneously adjusting for multiple comparisons at the codon level. We illustrate how this model can be used to characterize molecular adaptation in two datasets: an alignment from six class I alleles of the human major histocompatibility complex and a sperm lysin alignment from 25 abalone species. We compare the results obtained with the proposed hierarchical models to those obtained with alternative methods. Our analyses indicate that a more complete quantitative and qualitative characterization of molecular adaptation is achieved by taking into account changes in amino acid properties. AVAILABILITY: The R code for implementing the hierarchical models is freely available at http://www.ams.ucsc.edu/∼raquel/software/.

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Year:  2010        PMID: 20847216      PMCID: PMC2971574          DOI: 10.1093/bioinformatics/btq532

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  35 in total

1.  A method for detecting positive selection at single amino acid sites.

Authors:  Y Suzuki; T Gojobori
Journal:  Mol Biol Evol       Date:  1999-10       Impact factor: 16.240

2.  Codon-substitution models for heterogeneous selection pressure at amino acid sites.

Authors:  Z Yang; R Nielsen; N Goldman; A M Pedersen
Journal:  Genetics       Date:  2000-05       Impact factor: 4.562

3.  Positive Darwinian selection drives the evolution of several female reproductive proteins in mammals.

Authors:  W J Swanson; Z Yang; M F Wolfner; C F Aquadro
Journal:  Proc Natl Acad Sci U S A       Date:  2001-02-20       Impact factor: 11.205

4.  Accommodating phylogenetic uncertainty in evolutionary studies.

Authors:  J P Huelsenbeck; B Rannala; J P Masly
Journal:  Science       Date:  2000-06-30       Impact factor: 47.728

5.  Codon-substitution models to detect adaptive evolution that account for heterogeneous selective pressures among site classes.

Authors:  Ziheng Yang; Willie J Swanson
Journal:  Mol Biol Evol       Date:  2002-01       Impact factor: 16.240

6.  Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages.

Authors:  Ziheng Yang; Rasmus Nielsen
Journal:  Mol Biol Evol       Date:  2002-06       Impact factor: 16.240

7.  Maximum-likelihood analysis of molecular adaptation in abalone sperm lysin reveals variable selective pressures among lineages and sites.

Authors:  Z Yang; W J Swanson; V D Vacquier
Journal:  Mol Biol Evol       Date:  2000-10       Impact factor: 16.240

8.  Ratios of radical to conservative amino acid replacement are affected by mutational and compositional factors and may not be indicative of positive Darwinian selection.

Authors:  Tal Dagan; Yael Talmor; Dan Graur
Journal:  Mol Biol Evol       Date:  2002-07       Impact factor: 16.240

9.  The crystal structure of lysin, a fertilization protein.

Authors:  A Shaw; D E McRee; V D Vacquier; C D Stout
Journal:  Science       Date:  1993-12-17       Impact factor: 47.728

10.  Estimating the influence of selection on the variable amino acid sites of the cytochrome B protein functional domains.

Authors:  D A McClellan; K G McCracken
Journal:  Mol Biol Evol       Date:  2001-06       Impact factor: 16.240

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  2 in total

1.  Bayesian factor models in characterizing molecular adaptation.

Authors:  Saheli Datta; Raquel Prado; Abel Rodríguez
Journal:  J Appl Stat       Date:  2013-04-03       Impact factor: 1.404

2.  Bayesian semiparametric regression models to characterize molecular evolution.

Authors:  Saheli Datta; Abel Rodriguez; Raquel Prado
Journal:  BMC Bioinformatics       Date:  2012-10-30       Impact factor: 3.169

  2 in total

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