Molecular Biology and Evolution

MBE Advance Access originally published online on May 4, 2007
Molecular Biology and Evolution 2007 24(8):1586-1591; doi:10.1093/molbev/msm088

This Article Abstract FREE Full Text (PDF) All Versions of this Article: 24/8/1586    most recent msm088v1 Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to My Personal Archive Download to citation manager Request Permissions Google Scholar Articles by Yang, Z. Search for Related Content PubMed PubMed Citation Articles by Yang, Z. Social Bookmarking          What's this?

© The Author 2007. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org

Letters

PAML 4: Phylogenetic Analysis by Maximum Likelihood

Ziheng Yang^*

^* Department of Biology, Galton Laboratory, University College London, London, United Kingdom

E-mail: z.yang{at}ucl.ac.uk.

	Abstract

TOP Abstract Introduction Major Applications of the... Acknowledgements References

 
PAML, currently in version 4, is a package of programs for phylogenetic analyses of DNA and protein sequences using maximum likelihood (ML). The programs may be used to compare and test phylogenetic trees, but their main strengths lie in the rich repertoire of evolutionary models implemented, which can be used to estimate parameters in models of sequence evolution and to test interesting biological hypotheses. Uses of the programs include estimation of synonymous and nonsynonymous rates (d_N and d_S) between two protein-coding DNA sequences, inference of positive Darwinian selection through phylogenetic comparison of protein-coding genes, reconstruction of ancestral genes and proteins for molecular restoration studies of extinct life forms, combined analysis of heterogeneous data sets from multiple gene loci, and estimation of species divergence times incorporating uncertainties in fossil calibrations. This note discusses some of the major applications of the package, which includes example data sets to demonstrate their use. The package is written in ANSI C, and runs under Windows, Mac OSX, and UNIX systems. It is available at http://abacus.gene.ucl.ac.uk/software/paml.html.

Key Words: codon models • likelihood • PAML • phylogenetic analysis • software

	Introduction

TOP Abstract Introduction Major Applications of the... Acknowledgements References

 
Phylogenetic methods for comparative analysis of DNA and protein sequences are becoming ever more important with the rapid accumulation of molecular sequence data, spearheaded by numerous genome projects. It is now common for phylogeny reconstruction to be conducted using large data sets involving hundreds or even thousands of genes. Similarly, phylogenetic methods are widely used to estimate the evolutionary rates of genes and genomes to detect footprints of natural selection, and the evolutionary information is used to interpret genomic data (Yang 2005). For example, both evolutionary conservation indicating negative purifying selection and accelerated evolution driven by positive Darwinian selection have been employed to detect functionally significant regions of the genome (e.g., Thomas et al. 2003; Nielsen et al. 2005; Sawyer et al. 2005).

PAML is a package of programs for phylogenetic analyses of DNA and protein sequences using maximum likelihood (ML). The package includes the following programs: BASEML, BASEMLG, CODEML, EVOLVER, PAMP, YN00, MCMCTREE, and CHI2. Tree-search algorithms implemented in BASEML and CODEML are primitive. However, the programs may be used to evaluate a collection of trees obtained using other programs such as PHYLIP (Felsenstein 2005), PAUP (Swofford 2000), MRBAYES (Huelsenbeck and Ronquist 2001) and MEGA (Kumar, Tamura, and Nei 2005). The strength of PAML is in its rich collection of sophisticated substitution models, useful when our focus is on understanding the process of sequence evolution. Examples of analyses that can be performed using the package include

• Comparison and tests of phylogenetic trees (BASEML and CODEML);
  
• Estimation of parameters in sophisticated substitution models, including models of variable rates among sites and models for combined analysis of multiple genes (BASEML and CODEML);
  
• Likelihood ratio tests (LRTs) of hypotheses through comparison of nested statistical models (BASEML, CODEML, CHI2);
  
• Estimation of synonymous and nonsynonymous substitution rates and detection of positive Darwinian selection in protein-coding DNA sequences (YN00 and CODEML);
  
• Estimation of empirical amino acid substitution matrices (CODEML);
  
• Estimation of species divergence times under global and local clock models using likelihood (BASEML and CODEML) and Bayesian (MCMCTREE) methods;
  
• Reconstruction of ancestral sequences using nucleotide, amino acid, and codon models (BASEML and CODEML);
  
• Generation of nucleotide, codon, and amino acid sequence alignments by Monte Carlo simulation (EVOLVER).
  

This article provides an overview of a few major applications of PAML programs, with an emphasis on models and analyses in common use but unavailable elsewhere. Example data files used in publications that described those methods are included in the package, to illustrate the file formats and the interpretation of results (see table 1). New users of the programs are advised to use the examples to duplicate published results before analyzing their own data.

View this table: [in this window] [in a new window]   Table 1 Example Data Sets Included in the Package to Demonstrate the Analyses

 

	Major Applications of the Software Package

TOP Abstract Introduction Major Applications of the... Acknowledgements References

 
Comparison and Tests of Trees
The programs BASEML and CODEML can take a set of user trees and evaluate their log likelihood values under a variety of nucleotide, amino acid, and codon substitution models. When more than one tree is specified, the programs automatically calculates the bootstrap proportions for trees using the RELL method (Kishino and Hasegawa 1989), as well as p values using the K-H test (Kishino and Hasegawa 1989) and S-H test (Shimodaira and Hasegawa 1999). See Goldman, Anderson, and Rodrigo (2000) for a critical review of those methods.

In particular, a number of likelihood models are implemented in BASEML and CODEML for combined analysis of heterogeneous data sets from multiple gene loci (Yang 1996). These models allow estimation of common parameters of interest (such as species divergence times or species phylogenies), while allowing other parameters (such as the substitution rate, transition/transversion rate ratio, and base compositions) to differ among loci to accommodate the idiosyncrasies in the evolutionary process at different loci. Application of such models in the ML method has been discussed by Yang (1996), Pupko et al. (2002), Shapiro, Rambaut, and Drummond (2006), and Bofkin and Goldman (2007). Similar models are implemented in the Bayesian framework by Suchard et al. (2003) and Nylander et al. (2004). The use of statistical likelihood in those methods allows one locus to borrow information from other loci in combined analysis of heterogeneous data sets, and the method combines the strengths of the supermatrix and supertree methods while avoiding their drawbacks.

Estimation of Synonymous and Nonsynonymous Rates Between Two Protein-Coding DNA Sequences
In analysis of protein-coding genes, we have the advantage of being able to distinguish the synonymous or silent substitutions (nucleotide substitutions that do not change the encoded amino acid) from the nonsynonymous or replacement substitutions (those that do change the amino acid). Because natural selection operates mainly on the protein level, synonymous and nonsynonymous mutations are under very different selective pressures and are fixed at very different rates. Thus comparison of synonymous and nonsynonymous substitution rates can reveal the direction and strength of natural selection acting on the protein (Kimura 1977; Miyata and Yasunaga 1980).

The YN00 program implements a number of counting methods for estimating d_N and d_S between two sequences, including NG86 (Nei and Gojobori 1986), LWL85 (Li, Wu, and Luo 1985), LPB (Li 1993; Pamilo and Bianchi 1993), and LWL85m, a modified version of LWL85 (Yang 2006, p. 55). NG86 assumes no transition-transversion rate difference and no codon usage bias, while LWL85, LPB, and LWL85m all account for the transition-transversion rate difference to some extent but assume no codon usage bias. The counting method of Yang and Nielsen (2000) is implemented in YN00 as well, which accommodates both the transition-transversion rate difference and unequal codon frequencies. The ML method of Goldman and Yang (1994) is implemented in CODEML, which can be applied under different model assumptions. It can also be used to calculate ML estimates of a few new distances defined by Yang (2006; section 2.5.4). These include d_3B, the distance at the third codon position before the operation of natural selection on the protein level, which is very similar to d₄, the sequence distance at the so-called 4-fold degenerate sites. Usually a third codon position is considered to be a 4-fold site if the first and second positions are identical across sequences and if the encoded amino acid does not depend on the third position (e.g., Adachi and Hasegawa 1996). This definition has the drawback that the number of 4-fold sites used in the calculation decreases with sequence divergence. In CODEML, d₄ is calculated from the codon model and avoids this drawback (Yang 2006, p. 64).

Detection of Adaptive Molecular Evolution Under Models of Codon Substitution
A number of codon substitution models have been implemented in CODEML as extensions of the basic model of Goldman and Yang (1994; see also Muse and Gaut 1994). Several reviews have been published that discuss applications of those models to detect positive selection (Yang and Bielawski 2000; Nielsen 2001; Yang 2002, 2006, Chapter 8).

The main feature of codon-substitution models, compared with models of nucleotide or amino acid substitution, is that the codon triplet is considered the unit of evolution (Goldman and Yang 1994). The version of the model in common use (e.g., Yang 1998; Yang and Nielsen 1998) ignores chemical differences between amino acids and uses the same nonsynonymous/synonymous rate ratio ( = d_N/d_S) for all nonsynonymous substitutions. This assumption may be unrealistic but simplifies the interpretation of the model. The ratio measures the direction and magnitude of selection on amino acid changes, with values of < 1, = 1, and > 1 indicating negative purifying selection, neutral evolution, and positive selection, respectively. However, straightforward use of the ratio to detect positive selection, by calculating d_N and d_S between two sequences, is rarely effective, because the ratio averaged over all sites is seldom greater than 1. Much effort has been taken recently to develop models useful for detecting positive selection that affects specific lineages or individual sites.

The branch models use different ratio parameters for different branches on the phylogeny (Yang 1998; Yang and Nielsen 1998). They may be used to detect positive selection acting on particular lineages, without averaging the ratio throughout the phylogenetic tree. The branch models are useful for detecting positive selection after gene duplications, where one copy of the duplicates may have acquired a new function and may have thus evolved at accelerated rates.

The site models treats the ratio for any site (codon) in the gene as a random variable from a statistical distribution, thus allowing to vary among codons (Nielsen and Yang 1998; Yang et al. 2000). Positive selection is defined as presence of some codons at which > 1. An LRT is constructed to compare a null model that does not allow for any codons with > 1 against a more general model that does. Real data analyses and computer simulations (Anisimova, Bielawski, and Yang 2001, 2002; Anisimova, Nielsen, and Yang 2003; Wong et al. 2004) suggest that two pairs of site models are particularly effective (table 2). The first pair include M1a (neutral) and M2a (selection) (Nielsen and Yang 1998; Wong et al. 2004; Yang, Wong, and Nielsen 2005), while the second pair include M7 (beta) and M8 (beta&) (Yang et al. 2000). The LRT statistic, or twice the log likelihood difference between the two compared models (2), may be compared against , with critical values to be 5.99 and 9.21 at 5% and 1% significance levels, respectively. When the LRT suggests positive selection, the Bayes empirical Bayes (BEB) method can be used to calculate the posterior probabilities that each codon is from the site class of positive selection under models M2a and M8 (Yang, Wong, and Nielsen 2005). The BEB is an improvement of the early Naïve empirical Bayesian (NEB) method (Nielsen and Yang 1998), and accounts for sampling errors in the ML estimates of parameters in the model.

View this table: [in this window] [in a new window]   Table 2 Parameters in Site Models

 
The branch-site models aim to detect positive selection that affects only a few sites on prespecified lineages (Yang and Nielsen 2002). The branches under test for positive selection are called the foreground branches, while all other branches on the tree are the background branches. The version of the model in common use now is called branch-site model A and is illustrated in table 3 (Yang, Wong, and Nielsen 2005; Zhang, Nielsen, and Yang 2005). In the LRT, branch-site model A is the alternative model, while the simpler null model is model A but with ₂ = 1 fixed. Because the value ₂ = 1 is at the boundary of the space of model A, the test statistic 2 should be compared with the 50:50 mixture of point mass 0 and (with critical values to be 2.71 and 5.41 at the 5% and 1% significance levels, respectively) (Self and Liang 1987). Some authors (e.g., Zhang, Nielsen, and Yang 2005) also suggested the use of (with critical values to be 3.84 and 5.99), to guide against violations of model assumptions. The BEB method is implemented to calculate posterior probabilities for site classes under model A if the LRT suggests presence of codons under positive selection on the foreground branch.

View this table: [in this window] [in a new window]   Table 3 Parameters in Branch-Site Model A

 
The branch-site test requires a priori specification of the foreground branches. When multiple branches on the tree are tested for positive selection using the same data set, a correction for multiple testing is required (Anisimova and Yang 2007). A simple and slightly conservative procedure is Bonferroni's correction, which means that the individual test for any branch is considered significant at the level only if the p-value is </m, where m is the number of branches being tested using the same data.

Reconstruction of Ancestral Sequences
The programs BASEML and CODEML implement the empirical Bayes (EB) method for reconstructing genes or proteins in extinct ancestors on a phylogeny (Yang, Kumar, and Nei 1995; Koshi and Goldstein 1996). The general methodology is the same as the NEB for detecting positively selected sites discussed above. Ancestral reconstruction can be conducted under nucleotide-, amino acid-, or codon-based models. Compared with the parsimony algorithm (Fitch 1971; Hartigan 1973), the EB approach takes into account differences in the branch lengths and in the relative substitution rates between characters (nucleotides, amino acids, or codons). Both marginal and joint reconstructions are implemented. The marginal reconstruction assigns a character state to a single node on the tree and may be more suitable when the gene or protein sequence in an extinct ancestor is desired, as in restoration studies (Chang, Kazmi, and Sakmar 2002; Thornton 2004). The joint reconstruction assigns a set of character states to all ancestral nodes on the tree and is more appropriate when one counts changes at every site (Pupko et al. 2000). The EB approach replaces parameters in the model such as branch lengths and substitution parameters by their ML estimates. An alternative method, the hierarchical (full) Bayesian approach, accommodates sampling errors in the parameter estimates by averaging the parameters over a prior (Huelsenbeck and Bollback 2001). This difference between methods may be important in small data sets that lack information to estimate the parameters reliably.

Ancestral reconstruction provides an intuitive way of exploring the data. It has been used in numerous analyses, for example, to estimate selective pressures along lineages (Messier and Stewart 1997; Zhang, Kumar, and Nei 1997) or at individual sites (Suzuki and Gojobori 1999). However, the intuitive simplicity of the idea invites its misuse. Most studies making use of ancestral reconstructions ignore the fact that the ancestral sequences are inferred pseudo-data instead of real observed data, and that using only the optimal character states while ignoring the suboptimal states can lead to systematic biases (Eyre-Walker 1998; Yang 2006, section 4.4).

Estimation of Species Divergence Times
The programs BASEML and CODEML implement the likelihood method of Yoder and Yang (2000; see also Yang and Yoder 2003) for estimating species divergence times under local-clock models. This, like the quartet-dating method of Rambaut and Bromham (1998), assigns rates to different branches on the tree and then estimates both branch rates and divergence times from the sequence data. The method allows analysis of data from multiple loci, taking into account differences in their evolutionary dynamics, and can use multiple fossil calibrations in the same analysis. However, the assignment of rates to branches in the method is somewhat arbitrary. A rate-smoothing procedure was implemented to help assign rates to branches automatically (Yang 2004), which may be considered an improved version of Sanderson's (2002) penalized likelihood method.

A problem with current likelihood approaches to divergence time estimation is that fossil calibrations are assumed to provide known node ages without errors. The methods thus fail to account for uncertainties in fossil calibrations. Attempts to incorporate fossil uncertainties in the likelihood framework have not been very successful (see Yang 2006, section 7.3).

The program MCMCTREE used to implement the Bayesian method of phylogeny reconstruction of Yang and Rannala (1997; see also Rannala and Yang 1996). It was very slow and was decommissioned after the release of MRBAYES (Huelsenbeck and Ronquist 2001; Ronquist and Huelsenbeck 2003). The program now implements the MCMC algorithm for dating species divergences of Yang and Rannala (2006) and Rannala and Yang (2007). This is similar to the MULTIDIVTIME program (Thorne, Kishino, and Painter 1998; Kishino, Thorne, and Bruno 2001) and can be used to analyze data of multiple gene loci, incorporating multiple fossil calibrations and allowing the evolutionary rate to drift over time. A difference that may be important is that MULTIDIVTIME uses "hard" lower and upper bounds on node ages to specify fossil calibration information, while MCMCTREE uses "soft" bounds or arbitrary statistical distributions. A detailed discussion between the two programs is provided by Yang (2006, pp. 245–257).

Simulating Molecular Evolution
The program EVOLVER can be used to simulate DNA and protein sequences under various nucleotide, amino acid, and codon substitution models. Simulation is useful for learning about a complicated model or method of data analysis, and for comparing different analytical methods. For example, a number of simulation studies have been conducted to compare different tree reconstruction methods. In a simulation, the true model and the true values of parameters are under the control of the investigator, and they can be varied to examine their effects on method performance. See Yang (2006, Chapter 10) for a description of techniques for simulating molecular evolution.

Software Platform and Availability
The programs in the PAML package are written in ANSI C. Executables are compiled for Windows and Mac OSX, and C source codes are provided for UNIX systems. The program is distributed free of charge for academic use at its web site: http://abacus.gene.ucl.ac.uk/software/paml.html.

	Acknowledgements

TOP Abstract Introduction Major Applications of the... Acknowledgements References

 
I am grateful to a number of users of the program package for comments and suggestions, although it is impossible to mention their names here. Development of the software has been supported by grants from the Biotechnological and Biological Sciences Research Council (BBSRC) and the Natural Environment Research Councils (NERC).

	Footnotes

 
Sudhir Kumar, Associate Editor

	References

TOP Abstract Introduction Major Applications of the... Acknowledgements References

 

Adachi J, Hasegawa M. Model of amino acid substitution in proteins encoded by mitochondrial DNA. J Mol Evol. (1996) 42:459–468.[Web of Science][Medline]

Anisimova M, Bielawski JP, Yang Z. The accuracy and power of likelihood ratio tests to detect positive selection at amino acid sites. Mol Biol Evol. (2001) 18:1585–1592.[Abstract/Free Full Text]

Anisimova M, Bielawski JP, Yang Z. Accuracy and power of Bayes prediction of amino acid sites under positive selection. Mol Biol Evol. (2002) 19:950–958.[Abstract/Free Full Text]

Anisimova M, Nielsen R, Yang Z. Effect of recombination on the accuracy of the likelihood method for detecting positive selection at amino acid sites. Genetics (2003) 164:1229–1236.[Abstract/Free Full Text]

Anisimova A, Yang Z. Multiple hypothesis testing to detect lineages under positive selection that affects only a few sites. Mol Biol Evol. (2007) 24:1219–1228.[Abstract/Free Full Text]

Bofkin L, Goldman N. Variation in evolutionary processes at different codon positions. Mol Biol Evol. (2007) 24:513–521.[Abstract/Free Full Text]

Cao Y, Janke A, Waddell PJ, Westerman M, Takenaka O, Murata S, Okada N, Paabo S, Hasegawa M. Conflict among individual mitochondrial proteins in resolving the phylogeny of eutherian orders. J Mol Evol. (1998) 47:307–322.[CrossRef][Web of Science][Medline]

Chang BS, Kazmi MA, Sakmar TP. Synthetic gene technology: applications to ancestral gene reconstruction and structure-function studies of receptors. Methods Enzymol. (2002) 343:274–294.[Web of Science][Medline]

Eyre-Walker A. Problems with parsimony in sequences of biased base composition. J Mol Evol. (1998) 47:686–690.[CrossRef][Web of Science][Medline]

Felsenstein J. Phylip: phylogenetic inference program Version 3.6 (2005) Seattle: University of Washington.

Fitch WM. Toward defining the course of evolution: minimum change for a specific tree topology. Syst Zool. (1971) 20:406–416.[Abstract]

Goldman N, Anderson JP, Rodrigo AG. Likelihood-based tests of topologies in phylogenetics. Syst Biol. (2000) 49:652–670.[Abstract/Free Full Text]

Goldman N, Yang Z. A codon-based model of nucleotide substitution for protein-coding DNA sequences. Mol Biol Evol. (1994) 11:725–736.[Abstract]

Hartigan JA. Minimum evolution fits to a given tree. Biometrics (1973) 29:53–65.[CrossRef][Web of Science]

Huelsenbeck JP, Bollback JP. Empirical and hierarchical Bayesian estimation of ancestral states. Syst Biol. (2001) 50:351–366.[Web of Science][Medline]

Huelsenbeck JP, Ronquist F. MrBayes: Bayesian inference of phylogenetic trees. Bioinformatics (2001) 17:754–755.[Abstract/Free Full Text]

Kimura M. Prepondence of synonymous changes as evidence for the neutral theory of molecular evolution. Nature (1977) 267:275–276.[CrossRef][Medline]

Kishino H, Hasegawa M. Evaluation of the maximum likelihood estimate of the evolutionary tree topologies from DNA sequence data, and the branching order in hominoidea. J Mol Evol. (1989) 29:170–179.[CrossRef][Web of Science][Medline]

Kishino H, Thorne JL, Bruno WJ. Performance of a divergence time estimation method under a probabilistic model of rate evolution. Mol Biol Evol. (2001) 18:352–361.[Abstract/Free Full Text]

Koshi JM, Goldstein RA. Probabilistic reconstruction of ancestral protein sequences. J Mol Evol. (1996) 42:313–320.[CrossRef][Web of Science][Medline]

Kumar S, Tamura K, Nei M. MEGA3: integrated software for molecular evolutionary genetics analysis and sequence alignment. Brief Bioinform. (2005) 5:150–163.[CrossRef][Web of Science]

Lee Y-H, Ota T, Vacquier VD. Positive selection is a general phenomenon in the evolution of abalone sperm lysin. Mol Biol Evol. (1995) 12:231–238.[Abstract]

Li W-H. Unbiased estimation of the rates of synonymous and nonsynonymous substitution. J Mol Evol. (1993) 36:96–99.[CrossRef][Web of Science][Medline]

Li W-H, Wu C-I, Luo C-C. A new method for estimating synonymous and nonsynonymous rates of nucleotide substitutions considering the relative likelihood of nucleotide and codon changes. Mol Biol Evol. (1985) 2:150–174.[Abstract]

Messier W, Stewart C-B. Episodic adaptive evolution of primate lysozymes. Nature (1997) 385:151–154.[CrossRef][Medline]

Miyata T, Yasunaga T. Molecular evolution of mRNA: a method for estimating evolutionary rates of synonymous and amino acid substitutions from homologous nucleotide sequences and its applications. J Mol Evol. (1980) 16:23–36.[CrossRef][Web of Science][Medline]

Muse SV, Gaut BS. A likelihood approach for comparing synonymous and nonsynonymous nucleotide substitution rates, with application to the chloroplast genome. Mol Biol Evol. (1994) 11:715–724.[Abstract]

Nei M, Gojobori T. Simple methods for estimating the numbers of synonymous and nonsynonymous nucleotide substitutions. Mol Biol Evol. (1986) 3:418–426.[Abstract]

Nielsen R. Statistical tests of selective neutrality in the age of genomics. Heredity (2001) 86:641–647.[CrossRef][Web of Science][Medline]

Nielsen R, Bustamante C, Clark AG, (13 co-authors). A scan for positively selected genes in the genomes of humans and chimpanzees. PLoS Biol. (2005) 3:e170.[CrossRef][Medline]

Nielsen R, Yang Z. Likelihood models for detecting positively selected amino acid sites and applications to the HIV-1 envelope gene. Genetics (1998) 148:929–936.[Abstract/Free Full Text]

Nylander JAA, Ronquist F, Huelsenbeck JP, Nieves-Aldrey JL. Bayesian phylogenetic analysis of combined data. Syst Biol. (2004) 53:47–67.[Abstract/Free Full Text]

Pamilo P, Bianchi NO. Evolution of the Zfx and Zfy genes - rates and interdependence between the genes. Mol Biol Evol. (1993) 10:271–281.[Abstract]

Pupko T, Huchon D, Cao Y, Okada N, Hasegawa M. Combining multiple data sets in a likelihood analysis: which models are the best? Mol Biol Evol. (2002) 19:2294–2307.[Abstract/Free Full Text]

Pupko T, Pe'er I, Shamir R, Graur D. A fast algorithm for joint reconstruction of ancestral amino acid sequences. Mol Biol Evol. (2000) 17:890–896.[Abstract/Free Full Text]

Rambaut A, Bromham L. Estimating divergence dates from molecular sequences. Mol Biol Evol. (1998) 15:442–448.[Abstract]

Rannala B, Yang Z. Inferring speciation times under an episodic molecular clock. Syst Biol. (2007).

Ronquist F, Huelsenbeck JP. MrBayes. 3: Bayesian phylogenetic inference under mixed models. Bioinformatics (2003) 19:1572–1574.[Abstract/Free Full Text]

Sanderson MJ. Estimating absolute rates of molecular evolution and divergence times: a penalized likelihood approach. Mol Biol Evol. (2002) 19:101–109.[Abstract/Free Full Text]

Sawyer SL, Wu LI, Emerman M, Malik HS. Positive selection of primate TRIM5 identifies a critical species-specific retroviral restriction domain. Proc Natl Acad Sci USA (2005) 102:2832–2837.[Abstract/Free Full Text]

Self SG, Liang K-Y. Asymptotic properties of maximum likelihood estimators and likelihood ratio tests under nonstandard conditions. J Am Stat Assoc. (1987) 82:605–610.[CrossRef][Web of Science]

Shapiro B, Rambaut A, Drummond AJ. Choosing appropriate substitution models for the phylogenetic analysis of protein-coding sequences. Mol Biol Evol. (2006) 23:7–9.[Abstract/Free Full Text]

Shimodaira H, Hasegawa M. Multiple comparisons of log-likelihoods with applications to phylogenetic inference. Mol Biol Evol. (1999) 16:1114–1116.[Web of Science]

Stewart C-B, Schilling JW, Wilson AC. Adaptive evolution in the stomach lysozymes of foregut fermenters. Nature (1987) 330:401–404.[CrossRef][Medline]

Suchard MA, Kitchen CM, Sinsheimer JS, Weiss RE. Hierarchical phylogenetic models for analyzing multipartite sequence data. Syst Biol. (2003) 52:649–664.[Abstract/Free Full Text]

Suzuki Y, Gojobori T. A method for detecting positive selection at single amino acid sites. Mol Biol Evol. (1999) 16:1315–1328.[Abstract]

Swofford DL. PAUP*: phylogenetic analysis by parsimony, version 4. In: Sinauer Associates (2000) Massachusetts: Sanderland.

Thomas JW, Touchman JW, Blakesley RW, et al, (71 co-authors). Comparative analyses of multi-species sequences from targeted genomic regions. Nature (2003) 424:788–793.[CrossRef][Medline]

Thorne JL, Kishino H, Painter IS. Estimating the rate of evolution of the rate of molecular evolution. Mol Biol Evol. (1998) 15:1647–1657.[Abstract]

Thornton J. Resurrecting ancient genes: experimental analysis of extinct molecules. Nat Rev Genet. (2004) 5:366–375.[CrossRef][Web of Science][Medline]

Wong WSW, Yang Z, Goldman N, Nielsen R. Accuracy and power of statistical methods for detecting adaptive evolution in protein coding sequences and for identifying positively selected sites. Genetics (2004) 168:1041–1051.[Abstract/Free Full Text]

Yang Z. Maximum-likelihood models for combined analyses of multiple sequence data. J Mol Evol. (1996) 42:587–596.[CrossRef][Web of Science][Medline]

Yang Z. Likelihood ratio tests for detecting positive selection and application to primate lysozyme evolution. Mol Biol Evol. (1998) 15:568–573.[Abstract]

Yang Z. Inference of selection from multiple species alignments. Curr Opinion Genet Devel. (2002) 12:688–694.[CrossRef][Web of Science][Medline]

Yang Z. A heuristic rate smoothing procedure for maximum likelihood estimation of species divergence times. Acta Zool Sinica. (2004) 50:645–656.

Yang Z. The power of phylogenetic comparison in revealing protein function. Proc Natl Acad Sci USA (2005) 102:3179–3180.[Free Full Text]

Yang Z. Computational molecular evolution (2006) Oxford: Oxford University Press.

Yang Z, Bielawski JP. Statistical methods for detecting molecular adaptation. Trends Ecol Evol. (2000) 15:496–503.[CrossRef][Medline]

Yang Z, Kumar S, Nei M. A new method of inference of ancestral nucleotide and amino acid sequences. Genetics (1995) 141:1641–1650.[Abstract]

Yang Z, Nielsen R. Synonymous and nonsynonymous rate variation in nuclear genes of mammals. J Mol Evol. (1998) 46:409–418.[CrossRef][Web of Science][Medline]

Yang Z, Nielsen R. Estimating synonymous and nonsynonymous substitution rates under realistic evolutionary models. Mol Biol Evol. (2000) 17:32–43.[Abstract/Free Full Text]

Yang Z, Nielsen R. Codon-substitution models for detecting molecular adaptation at individual sites along specific lineages. Mol Biol Evol. (2002) 19:908–917.[Abstract/Free Full Text]

Yang Z, Rannala B. Bayesian estimation of species divergence times under a molecular clock using multiple fossil calibrations with soft bounds. Mol Biol Evol. (2006) 23:212–226.[Abstract/Free Full Text]

Yang Z, Swanson WJ. Codon-substitution models to detect adaptive evolution that account for heterogeneous selective pressures among site classes. Mol Biol Evol. (2002) 19:49–57.[Abstract/Free Full Text]

Yang Z, Wong WSW, Nielsen R. Bayes empirical Bayes inference of amino acid sites under positive selection. Mol Biol Evol. (2005) 22:1107–1118.[Abstract/Free Full Text]

Yang Z, Yoder AD. Comparison of likelihood and Bayesian methods for estimating divergence times using multiple gene loci and calibration points, with application to a radiation of cute-looking mouse lemur species. Syst Biol. (2003) 52:705–716.[Abstract/Free Full Text]

Yang Z, Nielsen R, Goldman N, Pedersen A-MK. Codon-substitution models for heterogeneous selection pressure at amino acid sites. Genetics (2000) 155:431–449.[Abstract/Free Full Text]

Yoder AD, Yang Z. Estimation of primate speciation dates using local molecular clocks. Mol Biol Evol. (2000) 17:1081–1090.[Abstract/Free Full Text]

Zhang J, Kumar S, Nei M. Small-sample tests of episodic adaptive evolution: a case study of primate lysozymes. Mol Biol Evol. (1997) 14:1335–1338.[Web of Science][Medline]

Zhang J, Nielsen R, Yang Z. Evaluation of an improved branch-site likelihood method for detecting positive selection at the molecular level. Mol Biol Evol. (2005) 22:2472–2479.[Abstract/Free Full Text]

Accepted for publication April 25, 2007.

CiteULike    Connotea    Del.icio.us    What's this?

This article has been cited by other articles:

				T. R. Gregory, C. B. Andrews, J. A. McGuire, and C. C. Witt The smallest avian genomes are found in hummingbirds Proc R Soc B, November 7, 2009; 276(1674): 3753 - 3757. [Abstract] [Full Text] [PDF]

				P.-C. Liao, T.-P. Lin, W.-C. Lan, J.-D. Chung, and S.-Y. Hwang Duplication of the class I cytosolic small heat shock protein gene and potential functional divergence revealed by sequence variations flanking the {alpha}-crystallin domain in the genus Rhododendron (Ericaceae) Ann. Bot., November 3, 2009; (2009) mcp272v1. [Abstract] [Full Text] [PDF]

				R. Carter and G. Drouin The Evolutionary Rates of Eukaryotic RNA Polymerases and of Their Transcription Factors Are Affected by the Level of Concerted Evolution of the Genes They Transcribe Mol. Biol. Evol., November 1, 2009; 26(11): 2515 - 2520. [Abstract] [Full Text] [PDF]

				A. M. Runck, H. Moriyama, and J. F. Storz Evolution of Duplicated {beta}-Globin Genes and the Structural Basis of Hemoglobin Isoform Differentiation in Mus Mol. Biol. Evol., November 1, 2009; 26(11): 2521 - 2532. [Abstract] [Full Text] [PDF]

				M. Giannakis, H. K. Backhed, S. L. Chen, J. J. Faith, M. Wu, J. L. Guruge, L. Engstrand, and J. I. Gordon Response of Gastric Epithelial Progenitors to Helicobacter pylori Isolates Obtained from Swedish Patients with Chronic Atrophic Gastritis J. Biol. Chem., October 30, 2009; 284(44): 30383 - 30394. [Abstract] [Full Text] [PDF]

				T. Tada, A. Altun, and S. Yokoyama Evolutionary replacement of UV vision by violet vision in fish PNAS, October 13, 2009; 106(41): 17457 - 17462. [Abstract] [Full Text] [PDF]

				F. H. Leendertz, M. Deckers, W. Schempp, F. Lankester, C. Boesch, L. Mugisha, A. Dolan, D. Gatherer, D. J. McGeoch, and B. Ehlers Novel cytomegaloviruses in free-ranging and captive great apes: phylogenetic evidence for bidirectional horizontal transmission J. Gen. Virol., October 1, 2009; 90(10): 2386 - 2394. [Abstract] [Full Text] [PDF]

				R. Schwarz, P. N. Seibel, S. Rahmann, C. Schoen, M. Huenerberg, C. Muller-Reible, T. Dandekar, R. Karchin, J. Schultz, and T. Muller Detecting species-site dependencies in large multiple sequence alignments Nucleic Acids Res., October 1, 2009; 37(18): 5959 - 5968. [Abstract] [Full Text] [PDF]

				Y.-Y. Shen, P. Shi, Y.-B. Sun, and Y.-P. Zhang Relaxation of selective constraints on avian mitochondrial DNA following the degeneration of flight ability Genome Res., October 1, 2009; 19(10): 1760 - 1765. [Abstract] [Full Text] [PDF]

				H. M. Sallam, E. R. Seiffert, M. E. Steiper, and E. L. Simons Fossil and molecular evidence constrain scenarios for the early evolutionary and biogeographic history of hystricognathous rodents PNAS, September 29, 2009; 106(39): 16722 - 16727. [Abstract] [Full Text] [PDF]

				M. Matsuno,, V. Compagnon, G. A. Schoch, M. Schmitt, D. Debayle, J.-E. Bassard, B. Pollet, A. Hehn, D. Heintz, P. Ullmann, et al. Evolution of a Novel Phenolic Pathway for Pollen Development Science, September 25, 2009; 325(5948): 1688 - 1692. [Abstract] [Full Text] [PDF]

				L. N. Gillman, D. J. Keeling, H. A. Ross, and S. D. Wright Latitude, elevation and the tempo of molecular evolution in mammals Proc R Soc B, September 22, 2009; 276(1671): 3353 - 3359. [Abstract] [Full Text] [PDF]

				A. Caro-Quintero, G. P. Rodriguez-Castano, and K. T. Konstantinidis Genomic Insights into the Convergence and Pathogenicity Factors of Campylobacter jejuni and Campylobacter coli Species J. Bacteriol., September 15, 2009; 191(18): 5824 - 5831. [Abstract] [Full Text] [PDF]

				Z. Yang, R. Nielsen, and N. Goldman In defense of statistical methods for detecting positive selection PNAS, September 8, 2009; 106(36): E95 - E95. [Full Text] [PDF]

				J. P. McCutcheon, B. R. McDonald, and N. A. Moran Convergent evolution of metabolic roles in bacterial co-symbionts of insects PNAS, September 8, 2009; 106(36): 15394 - 15399. [Abstract] [Full Text] [PDF]

				J. B. W. Wolf, A. Kunstner, K. Nam, M. Jakobsson, and H. Ellegren Nonlinear Dynamics of Nonsynonymous (dN) and Synonymous (dS) Substitution Rates Affects Inference of Selection Gen Biol Evol, September 4, 2009; 2009(0): 308 - 319. [Abstract] [Full Text] [PDF]

				R. Reinheimer and E. A. Kellogg Evolution of AGL6-like MADS Box Genes in Grasses (Poaceae): Ovule Expression Is Ancient and Palea Expression Is New PLANT CELL, September 1, 2009; 21(9): 2591 - 2605. [Abstract] [Full Text] [PDF]

				S.-K. Oh, C. Young, M. Lee, R. Oliva, T. O. Bozkurt, L. M. Cano, J. Win, J. I.B. Bos, H.-Y. Liu, M. van Damme, et al. In Planta Expression Screens of Phytophthora infestans RXLR Effectors Reveal Diverse Phenotypes, Including Activation of the Solanum bulbocastanum Disease Resistance Protein Rpi-blb2 PLANT CELL, September 1, 2009; 21(9): 2928 - 2947. [Abstract] [Full Text] [PDF]

				J. Gonzalez, J. M. Macpherson, and D. A. Petrov A Recent Adaptive Transposable Element Insertion Near Highly Conserved Developmental Loci in Drosophila melanogaster Mol. Biol. Evol., September 1, 2009; 26(9): 1949 - 1961. [Abstract] [Full Text] [PDF]

				D. Dong, G. He, S. Zhang, and Z. Zhang Evolution of Olfactory Receptor Genes in Primates Dominated by Birth-and-Death Process Gen Biol Evol, August 20, 2009; 2009(0): 258 - 264. [Abstract] [Full Text] [PDF]

				D. San Mauro, D. J. Gower, T. Massingham, M. Wilkinson, R. Zardoya, and J. A. Cotton Experimental Design in Caecilian Systematics: Phylogenetic Information of Mitochondrial Genomes and Nuclear rag1 Syst Biol, August 18, 2009; (2009) syp043v1. [Abstract] [Full Text] [PDF]

				K. T. Konstantinidis, J. Braff, D. M. Karl, and E. F. DeLong Comparative Metagenomic Analysis of a Microbial Community Residing at a Depth of 4,000 Meters at Station ALOHA in the North Pacific Subtropical Gyre Appl. Envir. Microbiol., August 15, 2009; 75(16): 5345 - 5355. [Abstract] [Full Text] [PDF]

				P.-A. Christin, E. Samaritani, B. Petitpierre, N. Salamin, and G. Besnard Evolutionary Insights on C4 Photosynthetic Subtypes in Grasses from Genomics and Phylogenetics Gen Biol Evol, August 13, 2009; 2009(0): 221 - 230. [Abstract] [Full Text] [PDF]

				A. Monier, A. Pagarete, C. de Vargas, M. J. Allen, B. Read, J.-M. Claverie, and H. Ogata Horizontal gene transfer of an entire metabolic pathway between a eukaryotic alga and its DNA virus Genome Res., August 1, 2009; 19(8): 1441 - 1449. [Abstract] [Full Text] [PDF]

				W. Hao and G. B. Golding Does Gene Translocation Accelerate the Evolution of Laterally Transferred Genes? Genetics, August 1, 2009; 182(4): 1365 - 1375. [Abstract] [Full Text] [PDF]

				A. Heger, C. P. Ponting, and I. Holmes Accurate Estimation of Gene Evolutionary Rates Using XRATE, with an Application to Transmembrane Proteins Mol. Biol. Evol., August 1, 2009; 26(8): 1715 - 1721. [Abstract] [Full Text] [PDF]

				L. Viljakainen, J. D. Evans, M. Hasselmann, O. Rueppell, S. Tingek, and P. Pamilo Rapid Evolution of Immune Proteins in Social Insects Mol. Biol. Evol., August 1, 2009; 26(8): 1791 - 1801. [Abstract] [Full Text] [PDF]

				G. Besnard, A. M. Muasya, F. Russier, E. H. Roalson, N. Salamin, and P.-A. Christin Phylogenomics of C4 Photosynthesis in Sedges (Cyperaceae): Multiple Appearances and Genetic Convergence Mol. Biol. Evol., August 1, 2009; 26(8): 1909 - 1919. [Abstract] [Full Text] [PDF]

				J. Martin-Coello, H. Dopazo, L. Arbiza, J. Ausio, E. R.S. Roldan, and M. Gomendio Sexual selection drives weak positive selection in protamine genes and high promoter divergence, enhancing sperm competitiveness Proc R Soc B, July 7, 2009; 276(1666): 2427 - 2436. [Abstract] [Full Text] [PDF]

				T. Lefebure and M. J. Stanhope Pervasive, genome-wide positive selection leading to functional divergence in the bacterial genus Campylobacter Genome Res., July 1, 2009; 19(7): 1224 - 1232. [Abstract] [Full Text] [PDF]

				F. Cheung, M. Trick, N. Drou, Y. P. Lim, J.-Y. Park, S.-J. Kwon, J.-A Kim, R. Scott, J. C. Pires, A. H. Paterson, et al. Comparative Analysis between Homoeologous Genome Segments of Brassica napus and Its Progenitor Species Reveals Extensive Sequence-Level Divergence PLANT CELL, July 1, 2009; 21(7): 1912 - 1928. [Abstract] [Full Text] [PDF]

				S. Fang, C.-T. Ting, C.-R. Lee, K.-H. Chu, C.-C. Wang, and S.-C. Tsaur Molecular Evolution and Functional Diversification of Fatty Acid Desaturases after Recurrent Gene Duplication in Drosophila Mol. Biol. Evol., July 1, 2009; 26(7): 1447 - 1456. [Abstract] [Full Text] [PDF]

				N. Svetec, P. Pavlidis, and W. Stephan Recent Strong Positive Selection on Drosophila melanogaster HDAC6, a Gene Encoding a Stress Surveillance Factor, as Revealed by Population Genomic Analysis Mol. Biol. Evol., July 1, 2009; 26(7): 1549 - 1556. [Abstract] [Full Text] [PDF]

				T.-K. Seo and H. Kishino Statistical Comparison of Nucleotide, Amino Acid, and Codon Substitution Models for Evolutionary Analysis of Protein-Coding Sequences Syst Biol, June 29, 2009; (2009) syp015v1. [Abstract] [Full Text] [PDF]

				C. Lemaitre, M. D. V. Braga, C. Gautier, M.-F. Sagot, E. Tannier, and G. A. B. Marais Footprints of Inversions at Present and Past Pseudoautosomal Boundaries in Human Sex Chromosomes Gen Biol Evol, June 22, 2009; 2009(0): 56 - 66. [Abstract] [Full Text] [PDF]

				S. D. Liberles, L. F. Horowitz, D. Kuang, J. J. Contos, K. L. Wilson, J. Siltberg-Liberles, D. A. Liberles, and L. B. Buck Formyl peptide receptors are candidate chemosensory receptors in the vomeronasal organ PNAS, June 16, 2009; 106(24): 9842 - 9847. [Abstract] [Full Text] [PDF]

				T. D. O'Connor and N. I. Mundy Genotype-phenotype associations: substitution models to detect evolutionary associations between phenotypic variables and genotypic evolutionary rate Bioinformatics, June 15, 2009; 25(12): i94 - i100. [Abstract] [Full Text] [PDF]

				K. Livingstone and S. Anderson Patterns of Variation in the Evolution of Carotenoid Biosynthetic Pathway Enzymes of Higher Plants J. Hered., June 11, 2009; (2009) esp026v1. [Abstract] [Full Text] [PDF]

				H. Zhao, S. J. Rossiter, E. C. Teeling, C. Li, J. A. Cotton, and S. Zhang The evolution of color vision in nocturnal mammals PNAS, June 2, 2009; 106(22): 8980 - 8985. [Abstract] [Full Text] [PDF]

				C. L. McGrath, C. Casola, and M. W. Hahn Minimal Effect of Ectopic Gene Conversion Among Recent Duplicates in Four Mammalian Genomes Genetics, June 1, 2009; 182(2): 615 - 622. [Abstract] [Full Text] [PDF]

				H. Ikeda, N. Fujii, and H. Setoguchi Molecular Evolution of Phytochromes in Cardamine nipponica (Brassicaceae) Suggests the Involvement of PHYE in Local Adaptation Genetics, June 1, 2009; 182(2): 603 - 614. [Abstract] [Full Text] [PDF]

				K. K. Kojima and N. Okada mRNA Retrotransposition Coupled with 5' Inversion as a Possible Source of New Genes Mol. Biol. Evol., June 1, 2009; 26(6): 1405 - 1420. [Abstract] [Full Text] [PDF]

				Y. I. Wolf, P. S. Novichkov, G. P. Karev, E. V. Koonin, and D. J. Lipman Inaugural Article: The universal distribution of evolutionary rates of genes and distinct characteristics of eukaryotic genes of different apparent ages PNAS, May 5, 2009; 106(18): 7273 - 7280. [Abstract] [Full Text] [PDF]

				P. J. Norman, L. Abi-Rached, K. Gendzekhadze, J. A. Hammond, A. K. Moesta, D. Sharma, T. Graef, K. L. McQueen, L. A. Guethlein, C. V.F. Carrington, et al. Meiotic recombination generates rich diversity in NK cell receptor genes, alleles, and haplotypes Genome Res., May 1, 2009; 19(5): 757 - 769. [Abstract] [Full Text] [PDF]

				M. V. Han, J. P. Demuth, C. L. McGrath, C. Casola, and M. W. Hahn Adaptive evolution of young gene duplicates in mammals Genome Res., May 1, 2009; 19(5): 859 - 867. [Abstract] [Full Text] [PDF]

				G. D. Findlay, M. J. MacCoss, and W. J. Swanson Proteomic discovery of previously unannotated, rapidly evolving seminal fluid genes in Drosophila Genome Res., May 1, 2009; 19(5): 886 - 896. [Abstract] [Full Text] [PDF]

				M. J. Schreiber, E. C. Holmes, S. H. Ong, H. S. H. Soh, W. Liu, L. Tanner, P. P. K. Aw, H. C. Tan, L. C. Ng, Y. S. Leo, et al. Genomic Epidemiology of a Dengue Virus Epidemic in Urban Singapore J. Virol., May 1, 2009; 83(9): 4163 - 4173. [Abstract] [Full Text] [PDF]

				M. D. Vibranovski, Y. Zhang, and M. Long General gene movement off the X chromosome in the Drosophila genus Genome Res., May 1, 2009; 19(5): 897 - 903. [Abstract] [Full Text] [PDF]

				N. Lewis-Rogers, M. L. Bendall, and K. A. Crandall Phylogenetic Relationships and Molecular Adaptation Dynamics of Human Rhinoviruses Mol. Biol. Evol., May 1, 2009; 26(5): 969 - 981. [Abstract] [Full Text] [PDF]

				J. I. Lucas-Lledo and M. Lynch Evolution of Mutation Rates: Phylogenomic Analysis of the Photolyase/Cryptochrome Family Mol. Biol. Evol., May 1, 2009; 26(5): 1143 - 1153. [Abstract] [Full Text] [PDF]

				S. Mukherjee, N. Sarkar-Roy, D. K. Wagener, and P. P. Majumder Signatures of natural selection are not uniform across genes of innate immune system, but purifying selection is the dominant signature PNAS, April 28, 2009; 106(17): 7073 - 7078. [Abstract] [Full Text] [PDF]

				M. Nozawa, Y. Suzuki, and M. Nei Reliabilities of identifying positive selection by the branch-site and the site-prediction methods PNAS, April 21, 2009; 106(16): 6700 - 6705. [Abstract] [Full Text] [PDF]

				J. A. Hodgson, K. N. Sterner, L. J. Matthews, A. S. Burrell, R. A. Jani, R. L. Raaum, C.-B. Stewart, and T. R. Disotell Successive radiations, not stasis, in the South American primate fauna PNAS, April 7, 2009; 106(14): 5534 - 5539. [Abstract] [Full Text] [PDF]

				J. Keay and J. W. Thornton Hormone-Activated Estrogen Receptors in Annelid Invertebrates: Implications for Evolution and Endocrine Disruption Endocrinology, April 1, 2009; 150(4): 1731 - 1738. [Abstract] [Full Text] [PDF]

				N. Mine, J. Guglielmini, M. Wilbaux, and L. Van Melderen The Decay of the Chromosomally Encoded ccdO157 Toxin-Antitoxin System in the Escherichia coli Species Genetics, April 1, 2009; 181(4): 1557 - 1566. [Abstract] [Full Text] [PDF]

				T. Miyake, N. Takebayashi, and D. E. Wolf Possible Diversifying Selection in the Imprinted Gene, MEDEA, in Arabidopsis Mol. Biol. Evol., April 1, 2009; 26(4): 843 - 857. [Abstract] [Full Text] [PDF]

				J. D. O'Brien, V. N. Minin, and M. A. Suchard Learning to Count: Robust Estimates for Labeled Distances between Molecular Sequences Mol. Biol. Evol., April 1, 2009; 26(4): 801 - 814. [Abstract] [Full Text] [PDF]

				S. Subramanian Temporal Trails of Natural Selection in Human Mitogenomes Mol. Biol. Evol., April 1, 2009; 26(4): 715 - 717. [Abstract] [Full Text] [PDF]

				G. Wlasiuk, S. Khan, W. M. Switzer, and M. W. Nachman A History of Recurrent Positive Selection at the Toll-Like Receptor 5 in Primates Mol. Biol. Evol., April 1, 2009; 26(4): 937 - 949. [Abstract] [Full Text] [PDF]

				H. Schaefer, C. Heibl, and S. S Renner Gourds afloat: a dated phylogeny reveals an Asian origin of the gourd family (Cucurbitaceae) and numerous oversea dispersal events Proc R Soc B, March 7, 2009; 276(1658): 843 - 851. [Abstract] [Full Text] [PDF]

				G. J. Binford, M. R. Bodner, M. H.J. Cordes, K. L. Baldwin, M. R. Rynerson, S. N. Burns, and P. A. Zobel-Thropp Molecular Evolution, Functional Variation, and Proposed Nomenclature of the Gene Family That Includes Sphingomyelinase D in Sicariid Spider Venoms Mol. Biol. Evol., March 1, 2009; 26(3): 547 - 566. [Abstract] [Full Text] [PDF]

				M. Toll-Riera, N. Bosch, N. Bellora, R. Castelo, L. Armengol, X. Estivill, and M. Mar Alba Origin of Primate Orphan Genes: A Comparative Genomics Approach Mol. Biol. Evol., March 1, 2009; 26(3): 603 - 612. [Abstract] [Full Text] [PDF]

				Z. Wang, L. Yuan, S. J. Rossiter, X. Zuo, B. Ru, H. Zhong, N. Han, G. Jones, P. D. Jepson, and S. Zhang Adaptive Evolution of 5'HoxD Genes in the Origin and Diversification of the Cetacean Flipper Mol. Biol. Evol., March 1, 2009; 26(3): 613 - 622. [Abstract] [Full Text] [PDF]

				M. A. Minge, J. D Silberman, R. J.S Orr, T. Cavalier-Smith, K. Shalchian-Tabrizi, F. Burki, A. Skjaeveland, and K. S Jakobsen Evolutionary position of breviate amoebae and the primary eukaryote divergence Proc R Soc B, February 22, 2009; 276(1657): 597 - 604. [Abstract] [Full Text] [PDF]

				S. Prabhakar, A. Visel, J. A. Akiyama, M. Shoukry, K. D. Lewis, A. Holt, I. Plajzer-Frick, H. Morrison, D. R. FitzPatrick, V. Afzal, et al. Response to Comment on "Human-Specific Gain of Function in a Developmental Enhancer" Science, February 6, 2009; 323(5915): 714d - 714d. [Abstract] [Full Text] [PDF]

				M. Wallis Prolactin in the Afrotheria: characterization of genes encoding prolactin in elephant (Loxodonta africana), hyrax (Procavia capensis) and tenrec (Echinops telfairi) J. Endocrinol., February 1, 2009; 200(2): 233 - 240. [Abstract] [Full Text] [PDF]

				R. S. Baucom, J. C. Estill, J. Leebens-Mack, and J. L. Bennetzen Natural selection on gene function drives the evolution of LTR retrotransposon families in the rice genome Genome Res., February 1, 2009; 19(2): 243 - 254. [Abstract] [Full Text] [PDF]

				A. J. Vilella, J. Severin, A. Ureta-Vidal, L. Heng, R. Durbin, and E. Birney EnsemblCompara GeneTrees: Complete, duplication-aware phylogenetic trees in vertebrates Genome Res., February 1, 2009; 19(2): 327 - 335. [Abstract] [Full Text] [PDF]

				M. Anisimova and C. Kosiol Investigating Protein-Coding Sequence Evolution with Probabilistic Codon Substitution Models Mol. Biol. Evol., February 1, 2009; 26(2): 255 - 271. [Abstract] [Full Text] [PDF]

				P.-A. Christin, B. Petitpierre, N. Salamin, L. Buchi, and G. Besnard Evolution of C4 Phosphoenolpyruvate Carboxykinase in Grasses, from Genotype to Phenotype Mol. Biol. Evol., February 1, 2009; 26(2): 357 - 365. [Abstract] [Full Text] [PDF]

				P. S. Novichkov, Y. I. Wolf, I. Dubchak, and E. V. Koonin Trends in Prokaryotic Evolution Revealed by Comparison of Closely Related Bacterial and Archaeal Genomes J. Bacteriol., January 1, 2009; 191(1): 65 - 73. [Abstract] [Full Text] [PDF]

				W. Delport, K. Scheffler, and C. Seoighe Models of coding sequence evolution Brief Bioinform, January 1, 2009; 10(1): 97 - 109. [Abstract] [Full Text] [PDF]

				M. Aguade Nucleotide and Copy-Number Polymorphism at the Odorant Receptor Genes Or22a and Or22b in Drosophila melanogaster Mol. Biol. Evol., January 1, 2009; 26(1): 61 - 70. [Abstract] [Full Text] [PDF]

				E. Proux, R. A. Studer, S. Moretti, and M. Robinson-Rechavi Selectome: a database of positive selection Nucleic Acids Res., January 1, 2009; 37(suppl_1): D404 - D407. [Abstract] [Full Text] [PDF]

				N. K. Mimouni, R. B. Lyngso, S. Griffiths-Jones, and J. Hein An Analysis of Structural Influences on Selection in RNA Genes Mol. Biol. Evol., January 1, 2009; 26(1): 209 - 216. [Abstract] [Full Text] [PDF]

				A. Stamatakis and M. Ott Efficient computation of the phylogenetic likelihood function on multi-gene alignments and multi-core architectures Phil Trans R Soc B, December 27, 2008; 363(1512): 3977 - 3984. [Abstract] [Full Text] [PDF]

				S. Whelan The genetic code can cause systematic bias in simple phylogenetic models Phil Trans R Soc B, December 27, 2008; 363(1512): 4003 - 4011. [Abstract] [Full Text] [PDF]

				Z. Yang Empirical evaluation of a prior for Bayesian phylogenetic inference Phil Trans R Soc B, December 27, 2008; 363(1512): 4031 - 4039. [Abstract] [Full Text] [PDF]

				M. Albu, X. J. Min, D. Hickey, and B. Golding Uncorrected Nucleotide Bias in mtDNA Can Mimic the Effects of Positive Darwinian Selection Mol. Biol. Evol., December 1, 2008; 25(12): 2521 - 2524. [Abstract] [Full Text] [PDF]

				M. M. Guisinger, J. V. Kuehl, J. L. Boore, and R. K. Jansen Genome-wide analyses of Geraniaceae plastid DNA reveal unprecedented patterns of increased nucleotide substitutions PNAS, November 25, 2008; 105(47): 18424 - 18429. [Abstract] [Full Text] [PDF]

				H. Bourhy, J.-M. Reynes, E. J. Dunham, L. Dacheux, F. Larrous, V. T. Q. Huong, G. Xu, J. Yan, M. E. G. Miranda, and E. C. Holmes The origin and phylogeography of dog rabies virus J. Gen. Virol., November 1, 2008; 89(11): 2673 - 2681. [Abstract] [Full Text] [PDF]

				P.-A. Christin, N. Salamin, A. M. Muasya, E. H. Roalson, F. Russier, and G. Besnard Evolutionary Switch and Genetic Convergence on rbcL following the Evolution of C4 Photosynthesis Mol. Biol. Evol., November 1, 2008; 25(11): 2361 - 2368. [Abstract] [Full Text] [PDF]

				R. C. Karn, N. L. Clark, E. D. Nguyen, and W. J. Swanson Adaptive Evolution in Rodent Seminal Vesicle Secretion Proteins Mol. Biol. Evol., November 1, 2008; 25(11): 2301 - 2310. [Abstract] [Full Text] [PDF]

				G. Jayawardane, G. C. Russell, J. Thomson, D. Deane, H. Cox, D. Gatherer, M. Ackermann, D. M. Haig, and J. P. Stewart A captured viral interleukin 10 gene with cellular exon structure J. Gen. Virol., October 1, 2008; 89(10): 2447 - 2455. [Abstract] [Full Text] [PDF]

				D. C. S. G. Oliveira, R. Raychoudhury, D. V. Lavrov, and J. H. Werren Rapidly Evolving Mitochondrial Genome and Directional Selection in Mitochondrial Genes in the Parasitic Wasp Nasonia (Hymenoptera: Pteromalidae) Mol. Biol. Evol., October 1, 2008; 25(10): 2167 - 2180. [Abstract] [Full Text] [PDF]

				V. J. Lynch, A. Tanzer, Y. Wang, F. C. Leung, B. Gellersen, D. Emera, and G. P. Wagner Adaptive changes in the transcription factor HoxA-11 are essential for the evolution of pregnancy in mammals PNAS, September 30, 2008; 105(39): 14928 - 14933. [Abstract] [Full Text] [PDF]

				E. Borenstein, M. Kupiec, M. W. Feldman, and E. Ruppin Large-scale reconstruction and phylogenetic analysis of metabolic environments PNAS, September 23, 2008; 105(38): 14482 - 14487. [Abstract] [Full Text] [PDF]

				G. Li, J. Wang, S. J. Rossiter, G. Jones, J. A. Cotton, and S. Zhang The hearing gene Prestin reunites echolocating bats PNAS, September 16, 2008; 105(37): 13959 - 13964. [Abstract] [Full Text] [PDF]

				S. Yokoyama, T. Tada, H. Zhang, and L. Britt From the Cover: Elucidation of phenotypic adaptations: Molecular analyses of dim-light vision proteins in vertebrates PNAS, September 9, 2008; 105(36): 13480 - 13485. [Abstract] [Full Text] [PDF]

				C. Fan, Y. Zhang, Y. Yu, S. Rounsley, M. Long, and R. A. Wing The Subtelomere of Oryza sativa Chromosome 3 Short Arm as a Hot Bed of New Gene Origination in Rice Mol Plant, September 1, 2008; 1(5): 839 - 850. [Abstract] [Full Text] [PDF]

This Article Abstract FREE Full Text (PDF) All Versions of this Article: 24/8/1586    most recent msm088v1 Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to My Personal Archive Download to citation manager Request Permissions Google Scholar Articles by Yang, Z. Search for Related Content PubMed PubMed Citation Articles by Yang, Z. Social Bookmarking          What's this?

Online ISSN 1537-1719 - Print ISSN 0737-4038

Copyright © 2009 Society for Molecular Biology and Evolution

Oxford Journals Oxford University Press

• Site Map
• Privacy Policy
• Frequently Asked Questions

Other Oxford University Press sites: Oxford University Press Oxford Journals China Oxford Journals Japan American National Biography Booksellers' Information Service Children's Fiction and Poetry Children's Reference Corporate & Special Sales Dictionaries Dictionary of National Biography Digital Reference English Language Teaching Higher Education Textbooks Humanities International Education Unit Law Medicine Music Online Products Oxford English Dictionary Reference Rights and Permissions Science School Books Social Sciences Very Short Introductions World's Classics