How Do Variable Substitution Rates Influence Ka and Ks Calculations?

The ratio of nonsynonymous substitution rate (Ka) to synonymous substitution rate (Ks) is widely used as an indicator of selective pressure at sequence level among different species, and diverse mutation models have been incorporated into several computing methods. We have previously developed a new γ-MYN method by capturing a key dynamic evolution trait of DNA nucleotide sequences, in consideration of varying mutation rates across sites. We now report a further improvement of NG, LWL, MLWL, LPB, MLPB, and YN methods based on an introduction of gamma distribution to illustrate the variation of raw mutation rate over sites. The novelty comes in two ways: (1) we incorporate an optimal gamma distribution shape parameter a into γ-NG, γ-LWL, γ-MLWL, γ-LPB, γ-MLPB, and γ-YN methods; (2) we investigate how variable substitution rates affect the methods that adopt different models as well as the interplay among four evolutional features with respect to Ka/Ks computations. Our results suggest that variable substitution rates over sites under negative selection exhibit an opposite effect on ω estimates compared with those under positive selection. We believe that the sensitivity of our new methods has been improved than that of their original methods under diverse conditions and it is advantageous to introduce novel parameters for Ka/Ks computation.

[1]  H. Kishino,et al.  Dating of the human-ape splitting by a molecular clock of mitochondrial DNA , 2005, Journal of Molecular Evolution.

[2]  N. Bianchi,et al.  Evolution of the Zfx and Zfy genes: rates and interdependence between the genes. , 1993, Molecular biology and evolution.

[3]  T. Jukes CHAPTER 24 – Evolution of Protein Molecules , 1969 .

[4]  大沢 省三,et al.  Evolution of life : fossils, molecules, and culture , 1991 .

[5]  Han Liang,et al.  SWAKK: a web server for detecting positive selection in proteins using a sliding window substitution rate analysis , 2006, Nucleic Acids Res..

[6]  M. Gouy,et al.  Molecular phylogeny of Rodentia, Lagomorpha, Primates, Artiodactyla, and Carnivora and molecular clocks. , 1990, Proceedings of the National Academy of Sciences of the United States of America.

[7]  Jun Yu,et al.  Evaluation of Six Methods for Estimating Synonymous and Nonsynonymous Substitution Rates , 2006, Genom. Proteom. Bioinform..

[8]  J. Wakeley,et al.  Substitution-rate variation among sites and the estimation of transition bias. , 1994, Molecular biology and evolution.

[9]  D. Liberles,et al.  A simple covarion‐based approach to analyse nucleotide substitution rates , 2002 .

[10]  Mario A. Fares SWAPSC: sliding window analysis procedure to detect selective constraints , 2004, Bioinform..

[11]  Jun Li,et al.  Correlation Between Ka/Ks and Ks is Related to Substitution Model and Evolutionary Lineage , 2009, Journal of Molecular Evolution.

[12]  S. Muse,et al.  Estimating synonymous and nonsynonymous substitution rates. , 1996, Molecular biology and evolution.

[13]  Adam Eyre-Walker,et al.  Molecular Evolution by Wen-Hsiung Li. Published by Sinauer Associates, Sunderland, MA, USA. ISBN: 0-87893-463-4 (cloth). , 1997 .

[14]  Nick Goldman,et al.  Variation in evolutionary processes at different codon positions. , 2006, Molecular biology and evolution.

[15]  S. Jeffery Evolution of Protein Molecules , 1979 .

[16]  H. Munro,et al.  Mammalian protein metabolism , 1964 .

[17]  Santiago F. Elena,et al.  A Sliding Window-Based Method to Detect Selective Constraints in Protein-Coding Genes and Its Application to RNA Viruses , 2002, Journal of Molecular Evolution.

[18]  M. Nei,et al.  Estimation of the number of nucleotide substitutions in the control region of mitochondrial DNA in humans and chimpanzees. , 1993, Molecular biology and evolution.

[19]  D. Labie,et al.  Molecular Evolution , 1991, Nature.

[20]  A. Wilson,et al.  Sequence Evolution of Mitochondrial DNA in Humans and Chimpanzees: Control Region and a Protein-Coding Region , 1991 .

[21]  Wen-Hsiung Li Unbiased estimation of the rates of synonymous and nonsynonymous substitution , 2006, Journal of Molecular Evolution.

[22]  Z. Yang,et al.  Maximum-likelihood estimation of phylogeny from DNA sequences when substitution rates differ over sites. , 1993, Molecular biology and evolution.

[23]  L. Jin,et al.  Limitations of the evolutionary parsimony method of phylogenetic analysis. , 1990, Molecular biology and evolution.

[24]  Ziheng Yang PAML 4: phylogenetic analysis by maximum likelihood. , 2007, Molecular biology and evolution.

[25]  W. Messier,et al.  Episodic adaptive evolution of primate lysozymes , 1997, Nature.

[26]  Jun Li,et al.  BMC Evolutionary Biology BioMed Central Methodology article Topology testing of phylogenies using least squares methods , 2006 .

[27]  Arne Elofsson,et al.  Tertiary Windowing to Detect Positive Diversifying Selection , 2005, Journal of Molecular Evolution.

[28]  Yoshiyuki Suzuki,et al.  Three-dimensional window analysis for detecting positive selection at structural regions of proteins. , 2004, Molecular biology and evolution.

[29]  M. Nei,et al.  Simple methods for estimating the numbers of synonymous and nonsynonymous nucleotide substitutions. , 1986, Molecular biology and evolution.

[30]  N. Goldman,et al.  Codon-substitution models for heterogeneous selection pressure at amino acid sites. , 2000, Genetics.

[31]  J. Wakeley Substitution rate variation among sites in hypervariable region 1 of human mitochondrial DNA , 1993, Journal of Molecular Evolution.

[32]  Ziheng Yang Maximum likelihood phylogenetic estimation from DNA sequences with variable rates over sites: Approximate methods , 1994, Journal of Molecular Evolution.

[33]  C. Luo,et al.  A new method for estimating synonymous and nonsynonymous rates of nucleotide substitution considering the relative likelihood of nucleotide and codon changes. , 1985, Molecular biology and evolution.

[34]  Jun Li,et al.  KaKs_Calculator: Calculating Ka and Ks Through Model Selection and Model Averaging , 2007, Genom. Proteom. Bioinform..

[35]  A. Oskooi Molecular Evolution and Phylogenetics , 2008 .

[36]  Z. Yang,et al.  Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models. , 2000, Molecular biology and evolution.

[37]  N. Goldman,et al.  Comparison of models for nucleotide substitution used in maximum-likelihood phylogenetic estimation. , 1994, Molecular biology and evolution.

[38]  Jun Yu,et al.  γ-MYN: a new algorithm for estimating Ka and Ks with consideration of variable substitution rates , 2009, Biology Direct.

[39]  Wen-Hsiung Li,et al.  Comparison of three methods for estimating rates of synonymous and nonsynonymous nucleotide substitutions. , 2004, Molecular biology and evolution.

[40]  M. Kimura A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences , 1980, Journal of Molecular Evolution.