Literature DB >> 17347158

Assessing the determinants of evolutionary rates in the presence of noise.

Joshua B Plotkin1, Hunter B Fraser.   

Abstract

Although protein sequences are known to evolve at vastly different rates, little is known about what determines their rate of evolution. However, a recent study using principal component regression (PCR) has concluded that evolutionary rates in yeast are primarily governed by a single determinant related to translation frequency. Here, we demonstrate that noise in biological data can confound PCRs, leading to spurious conclusions. When equalizing noise levels across 7 predictor variables used in previous studies, we find no evidence that protein evolution is dominated by a single determinant. Our results indicate that a variety of factors--including expression level, gene dispensability, and protein-protein interactions--may independently affect evolutionary rates in yeast. More accurate measurements or more sophisticated statistical techniques will be required to determine which one, if any, of these factors dominates protein evolution.

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Year:  2007        PMID: 17347158     DOI: 10.1093/molbev/msm044

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


  29 in total

1.  Young proteins experience more variable selection pressures than old proteins.

Authors:  Anchal Vishnoi; Sergey Kryazhimskiy; Georgii A Bazykin; Sridhar Hannenhalli; Joshua B Plotkin
Journal:  Genome Res       Date:  2010-10-04       Impact factor: 9.043

Review 2.  Three independent determinants of protein evolutionary rate.

Authors:  Sun Shim Choi; Sridhar Hannenhalli
Journal:  J Mol Evol       Date:  2013-02-12       Impact factor: 2.395

Review 3.  Signatures of protein biophysics in coding sequence evolution.

Authors:  Claus O Wilke; D Allan Drummond
Journal:  Curr Opin Struct Biol       Date:  2010-04-13       Impact factor: 6.809

4.  Genome-wide survey of natural selection on functional, structural, and network properties of polymorphic sites in Saccharomyces paradoxus.

Authors:  Anchal Vishnoi; Praveen Sethupathy; Daniel Simola; Joshua B Plotkin; Sridhar Hannenhalli
Journal:  Mol Biol Evol       Date:  2011-04-03       Impact factor: 16.240

5.  Gene promoter evolution targets the center of the human protein interaction network.

Authors:  Jordi Planas; Josep M Serrat
Journal:  PLoS One       Date:  2010-07-08       Impact factor: 3.240

6.  Protein evolution in yeast transcription factor subnetworks.

Authors:  Yong Wang; Eric A Franzosa; Xiang-Sun Zhang; Yu Xia
Journal:  Nucleic Acids Res       Date:  2010-05-13       Impact factor: 16.971

7.  Integrated assessment of genomic correlates of protein evolutionary rate.

Authors:  Yu Xia; Eric A Franzosa; Mark B Gerstein
Journal:  PLoS Comput Biol       Date:  2009-06-12       Impact factor: 4.475

8.  Why is the correlation between gene importance and gene evolutionary rate so weak?

Authors:  Zhi Wang; Jianzhi Zhang
Journal:  PLoS Genet       Date:  2009-01-09       Impact factor: 5.917

9.  Evolutionary rate patterns of the Gibberellin pathway genes.

Authors:  Yan-hua Yang; Fu-min Zhang; Song Ge
Journal:  BMC Evol Biol       Date:  2009-08-18       Impact factor: 3.260

10.  Determinants of exon-level evolutionary rates in Arabidopsis species.

Authors:  Gideon C-T Wu; Feng-Chi Chen
Journal:  Evol Bioinform Online       Date:  2012-07-04       Impact factor: 1.625

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