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Journal ArticleDOI

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

01 Jul 1987-Molecular Biology and Evolution (Oxford University Press)-Vol. 4, Iss: 4, pp 406-425
TL;DR: The neighbor-joining method and Sattath and Tversky's method are shown to be generally better than the other methods for reconstructing phylogenetic trees from evolutionary distance data.
Abstract: 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.

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Citations
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Journal ArticleDOI
TL;DR: The sensitivity of the commonly used progressive multiple sequence alignment method has been greatly improved and modifications are incorporated into a new program, CLUSTAL W, which is freely available.
Abstract: 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.

63,427 citations

Journal ArticleDOI
TL;DR: The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models, inferring ancestral states and sequences, and estimating evolutionary rates site-by-site.
Abstract: 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.

39,110 citations


Cites methods from "The neighbor-joining method: a new ..."

  • ...MEGA5 automatically infers the evolutionary tree by the NeighborJoining (NJ) algorithm that uses a matrix of pairwise distances estimated under the Jones–Thornton–Taylor (JTT) model for amino acid sequences or the Tamura and Nei (1993) model for nucleotide sequences (Saitou and Nei 1987; Jones et al. 1992; Tamura and Nei 1993; Tamura et al. 2004)....

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  • ...…or generated automatically by applying NJ and BIONJ algorithms to a matrix of pairwise distances estimated using a maximum composite likelihood approach for nucleotide sequences and a JTT model for amino acid sequences (Saitou and Nei 1987; Jones et al. 1992; Gascuel 1997; Tamura et al. 2004)....

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  • ...…the NeighborJoining (NJ) algorithm that uses a matrix of pairwise distances estimated under the Jones–Thornton–Taylor (JTT) model for amino acid sequences or the Tamura and Nei (1993) model for nucleotide sequences (Saitou and Nei 1987; Jones et al. 1992; Tamura and Nei 1993; Tamura et al. 2004)....

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  • ...The initial tree for the ML search can be supplied by the user (Newick format) or generated automatically by applying NJ and BIONJ algorithms to a matrix of pairwise distances estimated using a maximum composite likelihood approach for nucleotide sequences and a JTT model for amino acid sequences (Saitou and Nei 1987; Jones et al. 1992; Gascuel 1997; Tamura et al. 2004)....

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Journal ArticleDOI
TL;DR: MUSCLE is a new computer program for creating multiple alignments of protein sequences that includes fast distance estimation using kmer counting, progressive alignment using a new profile function the authors call the log-expectation score, and refinement using tree-dependent restricted partitioning.
Abstract: We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the logexpectation score, and refinement using treedependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.

37,524 citations


Cites methods from "The neighbor-joining method: a new ..."

  • ...Distance matrices are clustered using UPGMA (11), which we ®nd to give slightly improved results over neighbor-joining (12), despite the expectation that neighbor-joining will give a more reliable estimate of the evolutionary tree....

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Journal ArticleDOI
TL;DR: The latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine, has been optimized for use on 64-bit computing systems for analyzing larger datasets.
Abstract: We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.

33,048 citations


Cites methods from "The neighbor-joining method: a new ..."

  • ...For the Neighbor-Joining (NJ) method (Saitou and Nei 1987), memory usage increased at a polynomial rate as the number of sequences was increased....

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Journal ArticleDOI
TL;DR: Version 4 of MEGA software expands on the existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses.
Abstract: We announce the release of the fourth version of MEGA software, which expands on the existing facilities for editing DNA sequence data from autosequencers, mining Web-databases, performing automatic and manual sequence alignment, analyzing sequence alignments to estimate evolutionary distances, inferring phylogenetic trees, and testing evolutionary hypotheses. Version 4 includes a unique facility to generate captions, written in figure legend format, in order to provide natural language descriptions of the models and methods used in the analyses. This facility aims to promote a better understanding of the underlying assumptions used in analyses, and of the results generated. Another new feature is the Maximum Composite Likelihood (MCL) method for estimating evolutionary distances between all pairs of sequences simultaneously, with and without incorporating rate variation among sites and substitution pattern heterogeneities among lineages. This MCL method also can be used to estimate transition/transversion bias and nucleotide substitution pattern without knowledge of the phylogenetic tree. This new version is a native 32-bit Windows application with multi-threading and multi-user supports, and it is also available to run in a Linux desktop environment (via the Wine compatibility layer) and on Intel-based Macintosh computers under the Parallels program. The current version of MEGA is available free of charge at (http://www.megasoftware.net).

29,021 citations


Cites methods from "The neighbor-joining method: a new ..."

  • ...the Neighbor-Joining method ( Saitou and Nei 1987 ), as the use of the MCL distances leads to a...

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  • ...…from https://academic.oup.com/mbe/article-abstract/24/8/1596/1105236 by Zhejiang University user on 26 June 2018 Neighbor-Joining method (Saitou and Nei 1987), as the use of the MCL distances leads to a much higher accuracy (Tamura, Nei, and Kumar 2004)....

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References
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Journal ArticleDOI
TL;DR: The metric presented in this paper makes possible the comparison of the many nonbinary phylogenetic trees appearing in the literature, and provides an objective procedure for comparing the different methods for constructing phylogenetics trees.
Abstract: A metric on general phylogenetic trees is presented. This extends the work of most previous authors, who constructed metrics for binary trees. The metric presented in this paper makes possible the comparison of the many nonbinary phylogenetic trees appearing in the literature. This provides an objective procedure for comparing the different methods for constructing phylogenetic trees. The metric is based on elementary operations which transform one tree into another. Various results obtained in applying these operations are given. They enable the distance between any pair of trees to be calculated efficiently. This generalizes previous work by Bourque to the case where interior vertices can be labeled, and labels may contain more than one element or may be empty.

2,519 citations

Journal ArticleDOI
TL;DR: The distance Wagner procedure is applicable to data matrices of immunological distance, such as that of Sarich (1969a), in which between-OTU comparisons are evaluated but for which no attributes of the OTUs themselves are directly observable.
Abstract: 1. The distance Wagner procedure, presented here, is a modification of the original Wagner algorithm of Kluge and Farris (1969). Unlike previous techniques for calculating most parsimonious trees, it does not require a character-state matrix for the OTUs, but depends only upon an OTU × OTU matrix of phenetic differences. For this reason, the distance Wagner procedure is applicable to data matrices of immunological distance, such as that of Sarich (1969a), in which between-OTU comparisons are evaluated but for which no attributes of the OTUs themselves are directly observable. The distance Wagner procedure has the advantage over other available techniques for processing such data that it is free of the assumption of homogeneity of evolutionary rates over phyletic lines. 2. The estimated evolutionary trees produced by the distance Wagner procedure are undirected. Their roots may be estimated either by assuming the evolutionary rates of the two most divergent phyletic lines on the tree to be equal, or by con...

1,218 citations


"The neighbor-joining method: a new ..." refers methods in this paper

  • ...Some examples are the distance Wagner (DW) method (Farris 1972), modified Farris (MF) methods (Tateno et al. 1982; Faith 1985), and the neighborliness methods of Sattath and Tversky (ST method; 1977) and Fitch ( 198 1)....

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Journal ArticleDOI
TL;DR: A comparison of the accuracies and efficiencies of four different methods for constructing phylogenetic trees from molecular data was examined by using computer simulation, and it is shown that the agreement between patristic and observed genetic distances is not a good indicator of the goodness of the tree obtained.
Abstract: The accuracies and efficiencies of four different methods for constructing phylogenetic trees from molecular data were examined by using computer simulation. The methods examined are UPGMA, Fitch and Margoliash's (1967) (F/M) method, Farris' (1972) method, and the modified Farris method (Tateno, Nei, and Tajima, this paper). In the computer simulation, eight OTUs (32 OTUs in one case) were assumed to evolve according to a given model tree, and the evolutionary change of a sequence of 300 nucleotides was followed. The nucleotide substitution in this sequence was assumed to occur following the Poisson distribution, negative binomial distribution or a model of temporally varying rate. Estimates of nucleotide substitutions (genetic distances) were then computed for all pairs of the nucleotide sequences that were generated at the end of the evolution considered, and from these estimates a phylogenetic tree was reconstructed and compared with the true model tree. The results of this comparison indicate that when the coefficient of variation of branch length is large the Farris and modified Farris methods tend to be better than UPGMA and the F/M method for obtaining a good topology. For estimating the number of nucleotide substitutions for each branch of the tree, however, the modified Farris method shows a better performance than the Farris method. When the coefficient of variation of branch length is small, however, UPGMA shows the best performance among the four methods examined. Nevertheless, any tree-making method is likely to make errors in obtaining the correct topology with a high probability, unless all branch lengths of the true tree are sufficiently long. It is also shown that the agreement between patristic and observed genetic distances is not a good indicator of the goodness of the tree obtained.

887 citations

Journal ArticleDOI

673 citations

Journal ArticleDOI
TL;DR: A computer program, ADDTREE, for the construction of additive trees is described and applied to several sets of data, and some empirical and theoretical advantages of tree representations over spatial representations of proximity data are illustrated.
Abstract: Similarity data can be represented by additive trees. In this model, objects are represented by the external nodes of a tree, and the dissimilarity between objects is the length of the path joining them. The additive tree is less restrictive than the ultrametric tree, commonly known as the hierarchical clustering scheme. The two representations are characterized and compared. A computer program, ADDTREE, for the construction of additive trees is described and applied to several sets of data. A comparison of these results to the results of multidimensional scaling illustrates some empirical and theoretical advantages of tree representations over spatial representations of proximity data.

594 citations