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

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.

[1]  Anders Blomberg,et al.  High-resolution yeast phenomics resolves different physiological features in the saline response , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[2]  A. E. Hirsh,et al.  Adjusting for selection on synonymous sites in estimates of evolutionary distance. , 2005, Molecular biology and evolution.

[3]  P. Bork,et al.  Functional organization of the yeast proteome by systematic analysis of protein complexes , 2002, Nature.

[4]  T. Ideker,et al.  Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae , 2006, Journal of biology.

[5]  P. Green,et al.  Ancient conserved regions in new gene sequences and the protein databases. , 1993, Science.

[6]  Laurence D. Hurst,et al.  Do essential genes evolve slowly? , 1999, Current Biology.

[7]  V. Ingram,et al.  Gene Evolution and the Hæmoglobins , 1961, Nature.

[8]  Z. Weng,et al.  Structure, function, and evolution of transient and obligate protein-protein interactions. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[9]  C. Pál,et al.  Highly expressed genes in yeast evolve slowly. , 2001, Genetics.

[10]  C. Wilke,et al.  A single determinant dominates the rate of yeast protein evolution. , 2006, Molecular biology and evolution.

[11]  J. McInerney,et al.  The causes of protein evolutionary rate variation. , 2006, Trends in ecology & evolution.

[12]  P. Kemmeren,et al.  Protein interaction verification and functional annotation by integrated analysis of genome-scale data. , 2002, Molecular cell.

[13]  Eduardo P C Rocha,et al.  An analysis of determinants of amino acids substitution rates in bacterial proteins. , 2004, Molecular biology and evolution.

[14]  E. Lander,et al.  Remodeling of yeast genome expression in response to environmental changes. , 2001, Molecular biology of the cell.

[15]  Laurent Duret,et al.  Synonymous Codon Usage, Accuracy of Translation, and Gene Length in Caenorhabditis elegans , 2001, Journal of Molecular Evolution.

[16]  Ronald W. Davis,et al.  Mechanisms of Haploinsufficiency Revealed by Genome-Wide Profiling in Yeast , 2005, Genetics.

[17]  T. Ohta Slightly Deleterious Mutant Substitutions in Evolution , 1973, Nature.

[18]  Lan V. Zhang,et al.  Evidence for dynamically organized modularity in the yeast protein–protein interaction network , 2004, Nature.

[19]  C. Pál,et al.  Genomic function: Rate of evolution and gene dispensability. , 2003, Nature.

[20]  A. E. Hirsh,et al.  Functional genomic analysis of the rates of protein evolution. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[21]  Richard E. Dickerson,et al.  The structure of cytochromec and the rates of molecular evolution , 2005, Journal of Molecular Evolution.

[22]  C. Pál,et al.  An integrated view of protein evolution , 2006, Nature Reviews Genetics.

[23]  Eduardo P C Rocha,et al.  The quest for the universals of protein evolution. , 2006, Trends in genetics : TIG.

[24]  A. E. Hirsh,et al.  Evolutionary Rate in the Protein Interaction Network , 2002, Science.

[25]  Michael R. Green,et al.  Dissecting the Regulatory Circuitry of a Eukaryotic Genome , 1998, Cell.

[26]  Gary D Bader,et al.  Systematic identification of protein complexes in Saccharomyces cerevisiae by mass spectrometry , 2002, Nature.

[27]  E. O’Shea,et al.  Global analysis of protein expression in yeast , 2003, Nature.

[28]  A. E. Hirsh,et al.  Protein dispensability and rate of evolution , 2001, Nature.

[29]  C. Adami,et al.  Apparent dependence of protein evolutionary rate on number of interactions is linked to biases in protein–protein interactions data sets , 2003, BMC Evolutionary Biology.

[30]  Eugene V Koonin,et al.  Evolutionary systems biology: links between gene evolution and function. , 2006, Current opinion in biotechnology.

[31]  Ker-Chau Li,et al.  Slicing Regression: A Link-Free Regression Method , 1991 .

[32]  Donald A. Jackson STOPPING RULES IN PRINCIPAL COMPONENTS ANALYSIS: A COMPARISON OF HEURISTICAL AND STATISTICAL APPROACHES' , 1993 .

[33]  B. Snel,et al.  Comparative assessment of large-scale data sets of protein–protein interactions , 2002, Nature.

[34]  L. Orgel,et al.  Biochemical Evolution , 1971, Nature.

[35]  Matthew W. Hahn,et al.  Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks. , 2005, Molecular biology and evolution.

[36]  C. Wilke,et al.  Why highly expressed proteins evolve slowly. , 2005, Proceedings of the National Academy of Sciences of the United States of America.