MEGA2: molecular evolutionary genetics analysis software.

We have developed a new software package, Molecular Evolutionary Genetics Analysis version 2 (MEGA2), for exploring and analyzing aligned DNA or protein sequences from an evolutionary perspective. MEGA2 vastly extends the capabilities of MEGA version 1 by: (1) facilitating analyses of large datasets; (2) enabling creation and analyses of groups of sequences; (3) enabling specification of domains and genes; (4) expanding the repertoire of statistical methods for molecular evolutionary studies; and (5) adding new modules for visual representation of input data and output results on the Microsoft Windows platform. AVAILABILITY: http://www.megasoftware.net. CONTACT: s.kumar@asu.edu     

proseq: A software for preparation and evolutionary analysis of DNA sequence data sets

proseq is an integrated user‐friendly windows based program for convenient sequence editing and evolutionary analysis. It is designed to simplify preparation and analysis of DNA sequence data sets in population genetic, phylogenetic and molecular ecology studies. Sequence editor features include editing of chromatogram files, contig assembly, sequence alignment, translation and other utilities. Analysis features include calculation of genetic diversity, divergence, population subdivision and gene flow with permutation‐based significance testing and various tests of neutrality. A tool for coalescent simulations implements models with intragenic recombination, population subdivision and population growth.     

Computer analysis of DNA and protein sequences.

Some recent trends in the development of theoretical methods for DNA and protein sequence analysis are reviewed, with particular emphasis on the design of new databases, motif searches, sequence alignment algorithms and applications of neural networks.     

MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods

Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.     

An evolutionary model for maximum likelihood alignment of DNA sequences

Summary Most algorithms for the alignment of biological sequences are not derived from an evolutionary model. Consequently, these alignment algorithms lack a strong statistical basis. A maximum likelihood method for the alignment of two DNA sequences is presented. This method is based upon a statistical model of DNA sequence evolution for which we have obtained explicit transition probabilities. The evolutionary model can also be used as the basis of procedures that estimate the evolutionary parameters relevant to a pair of unaligned DNA sequences. A parameter-estimation approach which takes into account all possible alignments between two sequences is introduced; the danger of estimating evolutionary parameters from a single alignment is discussed.     

MEGA3: Integrated software for Molecular Evolutionary Genetics Analysis and sequence alignment

With its theoretical basis firmly established in molecular evolutionary and population genetics, the comparative DNA and protein sequence analysis plays a central role in reconstructing the evolutionary histories of species and multigene families, estimating rates of molecular evolution, and inferring the nature and extent of selective forces shaping the evolution of genes and genomes. The scope of these investigations has now expanded greatly owing to the development of high-throughput sequencing techniques and novel statistical and computational methods. These methods require easy-to-use computer programs. One such effort has been to produce Molecular Evolutionary Genetics Analysis (MEGA) software, with its focus on facilitating the exploration and analysis of the DNA and protein sequence variation from an evolutionary perspective. Currently in its third major release, MEGA3 contains facilities for automatic and manual sequence alignment, web-based mining of databases, inference of the phylogenetic trees, estimation of evolutionary distances and testing evolutionary hypotheses. This paper provides an overview of the statistical methods, computational tools, and visual exploration modules for data input and the results obtainable in MEGA.     

champuru 1.0: a computer software for unraveling mixtures of two DNA sequences of unequal lengths

champuru is an interactive, user‐friendly web software that facilitates the deconvolution of mixed chromatograms obtained when sequencing directly mixtures of two DNA templates of unequal lengths. The program takes as input two strings of characters describing the forward and reverse chromatograms as obtained by direct sequencing and returns, most often after several iterations aimed at correcting basecalling errors, the sequences of the two templates present in the mixture. champuru was written in perl , with a web interface accessible online at http://134.157.186.185/champuru/champuru.htm .     

A two-stage evolutionary approach for effective classification of hypersensitive DNA sequences

Hypersensitive (HS) sites in genomic sequences are reliable markers of DNA regulatory regions that control gene expression. Annotation of regulatory regions is important in understanding phenotypical differences among cells and diseases linked to pathologies in protein expression. Several computational techniques are devoted to mapping out regulatory regions in DNA by initially identifying HS sequences. Statistical learning techniques like Support Vector Machines (SVM), for instance, are employed to classify DNA sequences as HS or non-HS. This paper proposes a method to automate the basic steps in designing an SVM that improves the accuracy of such classification. The method proceeds in two stages and makes use of evolutionary algorithms. An evolutionary algorithm first designs optimal sequence motifs to associate explicit discriminating feature vectors with input DNA sequences. A second evolutionary algorithm then designs SVM kernel functions and parameters that optimally separate the HS and non-HS classes. Results show that this two-stage method significantly improves SVM classification accuracy. The method promises to be generally useful in automating the analysis of biological sequences, and we post its source code on our website.     

TOPALi: software for automatic identification of recombinant sequences within DNA multiple alignments

SUMMARY: TOPALi is a new Java graphical analysis application that allows the user to identify recombinant sequences within a DNA multiple alignment (either automatically or via manual investigation). TOPALi allows a choice of three statistical methods to predict the positions of breakpoints due to past recombination. The breakpoint predictions are then used to identify putative recombinant sequences and their relationships to other sequences. In addition to its sophisticated interface, TOPALi can import many sequence formats, estimate and display phylogenetic trees and allow interactive analysis and/or automatic HTML report generation. AVAILABILITY: TOPALi is freely available from http://www.bioss.ac.uk/software.html     

A rate-independent technique for analysis of nucleic acid sequences: evolutionary parsimony

The method of evolutionary parsimony--or operator invariants--is a technique of nucleic acid sequence analysis related to parsimony analysis and explicitly designed for determining evolutionary relationships among four distantly related taxa. The method is independent of substitution rates because it is derived from consideration of the group properties of substitution operators rather than from an analysis of the probabilities of substitution in branches of a tree. In both parsimony and evolutionary parsimony, three patterns of nucleotide substitution are associated one-to-one with the three topologically linked trees for four taxa. In evolutionary parsimony, the three quantities are operator invariants. These invariants are the remnants of substitutions that have occurred in the interior branch of the tree and are analogous to the substitutions assigned to the central branch by parsimony. The two invariants associated with the incorrect trees must equal zero (statistically), whereas only the correct tree can have a nonzero invariant. The chi 2-test is used to ascertain the nonzero invariant and the statistically favored tree. Examples, obtained using data calculated with evolutionary rates and branchings designed to camouflage the true tree, show that the method accurately predicts the tree, even when substitution rates differ greatly in neighboring peripheral branches (conditions under which parsimony will consistently fail). As the number of substitutions in peripheral branches becomes fewer, the parsimony and the evolutionary-parsimony solutions converge. The method is robust and easy to use.      

CURVATURE: software for the analysis of curved DNA

Software is presented to plot the sequence-dependent spatialtrajectory of the DNA double helix and/or distribution of curvaturealong the DNA molecule. The nearest-neighbor wedge model isimplemented to calculate overall DNA path using local helixparameters: helix twist angle, wedge (deflection) angle anddirection (of deflection) angle. The procedures described provedto be very convenient as tools for investigation of a relationshipbetween overall DNA curvature and its gel electrophoretic mobility.All parameters of the model had been estimated from experimentaldata. Using these wedge parameters the program takes, as input,any DNA sequence and calculates the likely degree of curvatureat each point along the molecule. This information is displayedboth graphically and in the form of simplified representationsof curved double helices. The Software, CURVATURE, can thusbe used to investigate possible roles of curvature in modulationof gene expression and for location of curved portions of DNA,which may play an important role in sequence-specific protein-DNAinteractions.     

Antheprot: An interactive graphics software for analyzing protein structures from sequences

ANTHEPROT is a fully interactive program devoted to the analysis of protein structures using a graphics workstation. It presents four options: The first option can predict secondary structures using five methods, and hydrophobicity, solvent accessibility, flexibility and antigenicity profiles using eighteen scales. The user may introduce his own scales. The results displayed on the screen can be easily analyzed. The second option is for representing results concerning up to eight proteins by one method. To compare these proteins, it is possible to align the profiles or the predicted secondary structure according to various motifs. The secondary structure deduced from crystallographic data may also be introduced. The third option is designed to compare the primary structure of two proteins and to visualize on the screen regions that exhibit similarity. Six different comparison matrices may be used, but the user can also introduce his own matrices. The last option is for studying the proteolytic peptides resulting from a chemical or enzymatic digestion of a given protein. It is possible to analyze the protein cleavage using eleven chemical reagents or enzymes. The results are displayed on the screen as RP-HPLC chromatogram.     

Advantages of a mechanistic codon substitution model for evolutionary analysis of protein-coding sequences

BACKGROUND: A mechanistic codon substitution model, in which each codon substitution rate is proportional to the product of a codon mutation rate and the average fixation probability depending on the type of amino acid replacement, has advantages over nucleotide, amino acid, and empirical codon substitution models in evolutionary analysis of protein-coding sequences. It can approximate a wide range of codon substitution processes. If no selection pressure on amino acids is taken into account, it will become equivalent to a nucleotide substitution model. If mutation rates are assumed not to depend on the codon type, then it will become essentially equivalent to an amino acid substitution model. Mutation at the nucleotide level and selection at the amino acid level can be separately evaluated. RESULTS: The present scheme for single nucleotide mutations is equivalent to the general time-reversible model, but multiple nucleotide changes in infinitesimal time are allowed. Selective constraints on the respective types of amino acid replacements are tailored to each gene in a linear function of a given estimate of selective constraints. Their good estimates are those calculated by maximizing the respective likelihoods of empirical amino acid or codon substitution frequency matrices. Akaike and Bayesian information criteria indicate that the present model performs far better than the other substitution models for all five phylogenetic trees of highly-divergent to highly-homologous sequences of chloroplast, mitochondrial, and nuclear genes. It is also shown that multiple nucleotide changes in infinitesimal time are significant in long branches, although they may be caused by compensatory substitutions or other mechanisms. The variation of selective constraint over sites fits the datasets significantly better than variable mutation rates, except for 10 slow-evolving nuclear genes of 10 mammals. An critical finding for phylogenetic analysis is that assuming variable mutation rates over sites lead to the overestimation of branch lengths.