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      A large-scale phylogeny of Amphibia including over 2800 species, and a revised classification of extant frogs, salamanders, and caecilians.

      Molecular Phylogenetics and Evolution
      Animals, Anura, classification, genetics, Bayes Theorem, Cell Nucleus, DNA, Mitochondrial, Likelihood Functions, Phylogeny, Sequence Analysis, DNA, Urodela

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          Abstract

          The extant amphibians are one of the most diverse radiations of terrestrial vertebrates (>6800 species). Despite much recent focus on their conservation, diversification, and systematics, no previous phylogeny for the group has contained more than 522 species. However, numerous studies with limited taxon sampling have generated large amounts of partially overlapping sequence data for many species. Here, we combine these data and produce a novel estimate of extant amphibian phylogeny, containing 2871 species (∼40% of the known extant species) from 432 genera (∼85% of the ∼500 currently recognized extant genera). Each sampled species contains up to 12,712 bp from 12 genes (three mitochondrial, nine nuclear), with an average of 2563 bp per species. This data set provides strong support for many groups recognized in previous studies, but it also suggests non-monophyly for several currently recognized families, particularly in hyloid frogs (e.g., Ceratophryidae, Cycloramphidae, Leptodactylidae, Strabomantidae). To correct these and other problems, we provide a revised classification of extant amphibians for taxa traditionally delimited at the family and subfamily levels. This new taxonomy includes several families not recognized in current classifications (e.g., Alsodidae, Batrachylidae, Rhinodermatidae, Odontophrynidae, Telmatobiidae), but which are strongly supported and important for avoiding non-monophyly of current families. Finally, this study provides further evidence that the supermatrix approach provides an effective strategy for inferring large-scale phylogenies using the combined results of previous studies, despite many taxa having extensive missing data. Copyright © 2011 Elsevier Inc. All rights reserved.

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          MUSCLE: multiple sequence alignment with high accuracy and high throughput.

          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 log-expectation score, and refinement using tree-dependent 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.
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            Clustal W and Clustal X version 2.0.

            The Clustal W and Clustal X multiple sequence alignment programs have been completely rewritten in C++. This will facilitate the further development of the alignment algorithms in the future and has allowed proper porting of the programs to the latest versions of Linux, Macintosh and Windows operating systems. The programs can be run on-line from the EBI web server: http://www.ebi.ac.uk/tools/clustalw2. The source code and executables for Windows, Linux and Macintosh computers are available from the EBI ftp site ftp://ftp.ebi.ac.uk/pub/software/clustalw2/
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              RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models.

              RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies with maximum likelihood (ML). Low-level technical optimizations, a modification of the search algorithm, and the use of the GTR+CAT approximation as replacement for GTR+Gamma yield a program that is between 2.7 and 52 times faster than the previous version of RAxML. A large-scale performance comparison with GARLI, PHYML, IQPNNI and MrBayes on real data containing 1000 up to 6722 taxa shows that RAxML requires at least 5.6 times less main memory and yields better trees in similar times than the best competing program (GARLI) on datasets up to 2500 taxa. On datasets > or =4000 taxa it also runs 2-3 times faster than GARLI. RAxML has been parallelized with MPI to conduct parallel multiple bootstraps and inferences on distinct starting trees. The program has been used to compute ML trees on two of the largest alignments to date containing 25,057 (1463 bp) and 2182 (51,089 bp) taxa, respectively. icwww.epfl.ch/~stamatak
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                Author and article information

                Journal
                21723399
                10.1016/j.ympev.2011.06.012

                Chemistry
                Animals,Anura,classification,genetics,Bayes Theorem,Cell Nucleus,DNA, Mitochondrial,Likelihood Functions,Phylogeny,Sequence Analysis, DNA,Urodela

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