The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSIBLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.

/pdf/gapped-blast-and-psi-blast-a-new-generation-of-protein-2ybl67x5yx.pdf

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

The sensitivity of the commonly used progressive multiple sequence alignment method has been greatly improved for the alignment of divergent protein sequences. Firstly, individual weights are assigned to each sequence in a partial alignment in order to down-weight near-duplicate sequences and up-weight the most divergent ones. Secondly, amino acid substitution matrices are varied at different alignment stages according to the divergence of the sequences to be aligned. Thirdly, residue-specific gap penalties and locally reduced gap penalties in hydrophilic regions encourage new gaps in potential loop regions rather than regular secondary structure. Fourthly, positions in early alignments where gaps have been opened receive locally reduced gap penalties to encourage the opening up of new gaps at these positions. These modifications are incorporated into a new program, CLUSTAL W which is freely available.

/pdf/clustal-w-improving-the-sensitivity-of-progressive-multiple-2na2s9sq2h.pdf

Clustal w: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice

A new method called the neighbor-joining method is proposed for reconstructing phylogenetic trees from evolutionary distance data. The principle of this method is to find pairs of operational taxonomic units (OTUs [= neighbors]) that minimize the total branch length at each stage of clustering of OTUs starting with a starlike tree. The branch lengths as well as the topology of a parsimonious tree can quickly be obtained by using this method. Using computer simulation, we studied the efficiency of this method in obtaining the correct unrooted tree in comparison with that of five other tree-making methods: the unweighted pair group method of analysis, Farris's method, Sattath and Tversky's method, Li's method, and Tateno et al.'s modified Farris method. The new, neighbor-joining method and Sattath and Tversky's method are shown to be generally better than the other methods.

/pdf/the-neighbor-joining-method-a-new-method-for-reconstructing-j5gk4xv4lj.pdf

The neighbor-joining method: a new method for reconstructing phylogenetic trees.

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.

/pdf/mega5-molecular-evolutionary-genetics-analysis-using-maximum-2fhrdnt1zl.pdf

MEGA5: Molecular Evolutionary Genetics Analysis using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods

Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%. IQ-TREE is freely available at http://www.cibiv.at/software/iqtree.

IQ-TREE: A fast and effective stochastic algorithm for estimating maximum likelihood phylogenies

Fitch, W. M. (Dept. of Physiological Chemistry, Univ. of Wisconsin, Madison, Wisconsin, 53706), 1971. Toward defining the course of evolution: minimum change for a specific tree topology. Syst. Zool., 20:406-416.-A method is presented that is asserted to provide all hypothetical ancestral character states that are consistent with describing the descent of the present-day character states in a minimum number of changes of state using a predetermined phylogenetic relationship among the taxa represented. The character states used as examples are the four messenger RNA nucleotides encoding the amino acid sequences of proteins, but the method is general. [Evolution; parsimonious trees.] It has been a goal of those attempting to deduce phylogenetic relationships from information on biological characteristics to find the ancestral relationship(s) that would permit one to account for the descent of those characteristics in a manner requiring a minimum number of evolutionary steps or changes. The result could be called the most parsimonious evolutionary tree and might be expected to have a high degree of correspondence to the true phylogeny (Camin and Sokal, 1965). It's justification lies in the most efficient use of the information available and does not presuppose that evolution follows a most parsimonious course. There are no known algorithms for finding the most parsimonious tree(s) apart from the brute force method of examining nearly every possible tree.' This is impractical for trees involving a dozen or more taxonomic units. Most numerical taxonomic procedures (Sokal and Sneath, 1963; Farris, 1969, 1970; Fitch and Margoliash, 1967) provide dendrograms that would be among the more parsimonious solutions; one just cannot be sure that a more parsimonious tree structure does not exist. Farris (1970) has explicitly considered the parsimony principle as a part of 'An elegant beginning to an attack on the problem has recently been published by Farris (1969) who developed a method which estimates the reliability of various characters and then weights the characters on the basis of that reliability. his method which, like the present method, has its roots in the Wagner tree (Wagner,

https://www.jstor.org/stable/pdfplus/2412116.pdf

Toward Defining the Course of Evolution: Minimum Change for a Specific Tree Topology

https://science.sciencemag.org/content/sci/155/3760/279.full.pdf

Construction of Phylogenetic Trees

Fitch, W. M. (Dept. Physiological Chem., U. Wisconsin, Madison 53706) 1970. Distinguishing homologous from analogaus proteins. Syst. Zool., 19:99-113.-This work provides a means by which it is possible to determine whether two groups of related proteins have a common ancestor or are of independent origin. A set of 16 random amino acid sequences were shown to be unrelated by this method. A set of 16 real but presumably unrelated proteins gave a similar result. A set of 24 model proteins which was composed of two independently evolving groups, converging toward the same chemical goal, was correctly shown to be convergently related, with the probability that the result was due to chance being <10'. A set of 24 cytochromes composed of 5 fungi and 19 metazoans was shown to be divergently related, with the probability that the result was due to chance being < 10-'. A process was described which leads to the absolute minimum of nucleotide replacements required to account for the divergent descent of a set of genes given a particular topology for the tree depicting their ancestral relations. It was also shown that the convergent processes could realistically lead to amino acid sequences which would produce positive tests for relatedness, not only by a chemical criterion, but by a genetic (nucleotide sequence) criterion as well. Finally, a realistic case is indicated where truly homologous traits, behaving in a perfectly expectable way, may nevertheless lead to a ludicrous phylogeny. The demonstration that two proteins are related has been attempted using two different criteria. One criterion is to show that their chemical structures are very similar. An early example of this approach was the observation of the relatedness of the oxygen carrying proteins, myoglobin and hemoglobin (Watson and Kendrew, 1961). More recent is the relatedness of two enzymes in carbohydrate metabolism, lysozyme and alpha-lactalbumin (Brew, Vanaman and Hill, 1967). The other criterion is to show that underlying genetic structures of the proteins are more alike than one would expect by chance. This is now possible because our knowledge of the genetic code permits us to determine how many nucleotide positions, at the minimum, must differ in the genes encoding the two presumptively homologous proteins. One then compares the answer obtained to the number of differences one would expect for unrelated proteins. An example of this approach is the observation of the relatedness of plant and bacterial ferredoxins (Matsubara, Jukes and Cantor, 1969) for which added evidence has been produced (Fitch, 1970a). But regardless of the approach, the impulse, too powerful to resist, is to conclude that a particular pair of proteins had a common genic ancestor if they meet whichever criterion the observer uses. Now two proteins may appear similar because they descend with divergence from a common ancestral gene (i.e., are homologous in a time-honoured meaning dating back at the least to Darwin's Origin of Species) or because they descend with convergence from separate ancestral genes (i.e., are analogous). And, if a common genic ancestor is to be the conclusion, a genetic criterion should be superior to a chemical criterion. This is because analogous gene products, although they have no common ancestor, do serve similar functions and may well be expected to have similar chemical structures and thereby be confused with homologous gene products. This danger can only be increased by using a chemical, as opposed to a genetic, criterion.

Distinguishing Homologous From Analogous Proteins

George Gaylord Simpson said in his classic Tempo and Mode in Evolution (1) that paleontologists enjoy special advantages over geneticists on two evolutionary topics. One general topic, suggested by the word "tempo," has to do with "evolutionary rates. . ., their acceleration and deceleration, the conditions of exceptionally slow or rapid evolutions, and phenomena suggestive of inertia and momentum." A group of related problems, implied by the word "mode," involves "the study of the way, manner, or pattern of evolution, a study in which tempo is a basic factor, but which embraces considerably more than tempo" (pp. xvii-xviii). Simpson's book was self-consciously written in the wake of Theodosius Dobzhansky's Genetics and the Origin of Species (2). The title of Dobzhansky's book suggested its theme: the role of genetics in explaining "the origin of species"-i.e., a synthesis of Darwin's theory of evolution by natural selection and the maturing science of genetics. In the introduction to his book, Simpson averred that an essential part of his study was an "attempted synthesis of paleontology and genetics," an effort that pervaded the whole book, but was particularly the subject of the first two chapters, which accounted for nearly half the book's pages. Darwin believed that evolutionary change occurs by natural selection of small individual differences appearing every generation within any species. Singly the changes effected by selection are small but, given enough time, great changes can take place. Two of Darwin's most dedicated supporters, Thomas Huxley and Francis Galton, argued instead that evolution occurs by selection of discontinuous variations, or sports; evolution proceeds rapidly by discrete leaps. According to Huxley, if natural selection operates only upon gradual differences among individuals, the gaps between existing species and in the paleontological record could not be explained. For Galton, evolution was not a smooth and uniform process, but proceeded by "jerks," some of which imply considerable organic change. This controversy was continued in the latter part of the nineteenth century by the biometricians Karl Pearson and W. F. R. Weldon, who believed, like Darwin, in the primary importance of common individual differences, and by the geneticist William Bateson, who maintained the primary importance of discontinuous variations. The rediscovery of Mendelian inheritance in 1900 provided what might have been common grounds to resolve the conflict. Instead, the dispute between biometricians and geneticists extended to continental Europe and to the United States. Bateson was the champion of the Mendelians, many of whom accepted the mutation theory proposed by De Vries, and denied that natural selection played a major role in evolution. The biometricians for their part argued that Mendelian characters were sports of little importance to the evolutionary process.

/pdf/tempo-and-mode-in-evolution-4vmduy3ymm.pdf

Walter M. Fitch

Papers

Toward Defining the Course of Evolution: Minimum Change for a Specific Tree Topology

Construction of Phylogenetic Trees

Distinguishing Homologous From Analogous Proteins

Tempo and mode in evolution.

Homology: a personal view on some of the problems