INTRODUCTION While Darwin's theory of evolution by natural selection is accepted by biologists for morphological traits, the importance of selection in molecular evolution has been much debated. The neutral theory (Kimura, 1983) maintains that most observed molecular vari- ation (both diversity within species and divergence between species) is due to random fixation of mutations with fitness effects so small that random drift rather than natural selection dominates their fate. Population geneticists have developed a number of tests of neutrality (see Wayne and Simonsen, 1998, for a review). Those tests often easily reject the strictly neutral model when applied to real data. However, they are often unable to distinguish different forms of natural selection, or to demonstrate molecular adaptation. Up to now, the most convincing evidence of adaptive molecular evolution appears to have come from comparison of synonymous (silent) and non-synonymous (aminoacid -changing) substitution rate

Phylogenetic reconstruction is a fast-growing field that is enriched by different statistical approaches and by findings and applications in a broad range of biological areas. Fundamental to these are the mathematical models used to describe the patterns of DNA base substitution and amino acid replacement. These may become some of the basic models for comparative genome research. We discuss these models, including the analysis of observed DNA base and amino acid mutation patterns, the concept of site heterogeneity, and the incorporation of structural biology data, all of which have become particularly important in recent years. We also describe the use of such models in phylogenetic reconstruction and statistical methods for the comparison of different models. PCR has deeply transformed and boosted phylogenetic studies. At the same time, the statistical analysis of evolutionary relationships among species has recently revealed important biotechnological uses. For example, the understanding of viral quasispecies variation allows us to trace routes of infectious disease transmission. The analysis of the host–

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† These authors contributed equally Keywords: positive selection; purifying selection; evolutionary conservation; HIV-1 protease. Bioinformatics Advance Access published January 12, 2005 Bioinfor matics © Oxford University Press 2005; all rights reserved. Summary: We present an algorithmic tool for the identification of biologically significant amino acids in proteins of known three dimensional structure. We estimate the degree of purifying selection and positive Darwinian selection at each site and project these estimates onto the molecular surface of the protein. Thus, patches of functional residues (undergoing either positive or purifying selection), which may be discontinuous in the linear sequence, are revealed. We test for the statistical significance of the site-specific scores in order to obtain reliable and valid estimates. Availability: The Selecton web server is available at:

this paper can resolve this problem. The excess of nonsynonymous substitutions over synonymous substitutions is an indicator of positive selection, so that estimation of nonsynonymous (d N ) and synonymous (d s ) substitution rates, is very important. For calculating d N and d s , the codon-based model of Goldman and Yang [7] is employed in this study. The model is formulated at the codon level instead of the nucleotide or amino acid level and is thus more realistic compared to other evolutionary models. In this model, substitutions between sense codons are described by a continuous-time Markov process. The three stop codons are not allowed in the gene sequence and are thus not considered in the Markov model. The Markov process is described by a rate matrix Q = {q ij }, where q ij Dt represents the probability that codon i changes to codon j in a small time interval Dt. By using the rate matrix Q, we can describe the codon substitution matrix P(t), whose element p ij (t) gives the probability that codon i replaces codon j after time interval t. According to Markov process theory, we have

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The complete genomic analysis of Arabidopsis thaliana has shown that a major fraction of the genome consists of paralogous genes that probably originated through one or more ancient large-scale gene or genome duplication events. However, the number and timing of these duplications still remains unclear, and several different hypotheses have been put forward recently. Here, we reanalyzed duplicated blocks found in the Arabidopsis genome described previously and determined their date of divergence based on silent substitution estimations between the paralogous genes and, where possible, by phylogenetic reconstruction. We show that methods based on averaging protein distances of heterogeneous classes of duplicated genes lead to unreliable conclusions and that a large fraction of blocks duplicated much more recently than assumed previously. We found clear evidence for one large-scale gene or even complete genome duplication event somewhere between 70 to 90 million years ago. Traces pointing to a much older (probably more than 200 million years) large-scale gene duplication event could be detected. However, for now it is impossible to conclude whether these old duplicates are the result of one or more large-scale gene duplication events.

Biologically significant sites in a protein may be identified by contrasting the rates of synonymous (K s ) and non-synonymous (K a ) substitutions. This enables the inference of site-specific positive Darwinian selection and purifying selection. We present here Selecton version 2.2 (http://selecton. bioinfo.tau.ac.il), a web server which automatically calculates the ratio between K a and K s (u) at each site of the protein. This ratio is graphically displayed on each site using a color-coding scheme, indicat- ing either positive selection, purifying selection or lack of selection. Selecton implements an assembly of different evolutionary models, which allow for statistical testing of the hypothesis that a protein has undergone positive selection. Specifically, the recently developed mechanistic- empirical model is introduced, which takes into account the physicochemical properties of amino acids. Advanced options were introduced to allow maximal fine tuning of the server to the user’s specific needs, including calculation of statistical support of the u values, an advanced graphic display of the protein’s 3-dimensional structure, use of different genetic codes and inputting of a pre-built phylogenetic tree. Selecton version 2.2 is an effective, user-friendly and freely available web server which implements up-to-date methods for computing site-specific selection forces, and the visualization of these forces on the protein’s sequence and structure.

This paper applies the likelihood

Drosophila genomes