Deconstructing the crustacean squat lobster genus

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Abstract

Unravelling the evolutionary history of taxa requires solid delimitation of the traits characterising these. This can be challenging especially in groups with a highly complex taxonomy. The squat lobster family Munididae contains more than 450 species distributed among 21 genera, Munida being the most speciose (~300 species). Previous phylogenetic studies, based on a small part of the diversity of the group, have suggested polyphyletic origins for Munida and the paraphyly of Munididae. Here, we use an integrative approach based on multi-locus phylogenies (two mitochondrial and three nuclear markers) paired with 120 morphological characters, to resolve taxonomic and evolutionary relationships within Munididae. Our study covers ~60% of the family’s known diversity (over 800 specimens of 291 species belonging to 19 of the 21 genera collected from the Atlantic, Indian and Pacific oceans). Using this information, we confirm the validity of most genera, proposing new ones in cases where the genetic analyses are compatible with morphological characters. Four well-defined munidid clades were recovered, suggesting that new genera should be erected in the currently recognised Munididae (three for the genus Agononida and eleven in Munida), and the genus Grimothea is resurrected. A key to all genera of the family is presented. Molecular clock estimates and ancestral biogeographic area reconstructions complement the taxonomic profiles and suggest some explosive diversification within Munididae during the Cretaceous and the Palaeogene. Further anagenetic events and narrow sympatry accounting for changes in distribution indicate a more limited dispersal capacity than previously considered. Our study unravels how diversification may occur in deep waters and further highlights the importance of the integrative approach in accurately delineating species in understanding the history of a family and the factors driving the evolution. ZooBank LSID: urn:lsid:zoobank.org:pub:16A61C4A-8D96-4372-820F-8EBDF179B43C

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MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

Fredrik Ronquist, Maxim Teslenko, Paul van der Mark … (2012)

Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.

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MAFFT: a novel method for rapid multiple sequence alignment based on fast Fourier transform.

K Katoh (2002)

A multiple sequence alignment program, MAFFT, has been developed. The CPU time is drastically reduced as compared with existing methods. MAFFT includes two novel techniques. (i) Homo logous regions are rapidly identified by the fast Fourier transform (FFT), in which an amino acid sequence is converted to a sequence composed of volume and polarity values of each amino acid residue. (ii) We propose a simplified scoring system that performs well for reducing CPU time and increasing the accuracy of alignments even for sequences having large insertions or extensions as well as distantly related sequences of similar length. Two different heuristics, the progressive method (FFT-NS-2) and the iterative refinement method (FFT-NS-i), are implemented in MAFFT. The performances of FFT-NS-2 and FFT-NS-i were compared with other methods by computer simulations and benchmark tests; the CPU time of FFT-NS-2 is drastically reduced as compared with CLUSTALW with comparable accuracy. FFT-NS-i is over 100 times faster than T-COFFEE, when the number of input sequences exceeds 60, without sacrificing the accuracy.

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New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

Stéphane Guindon, Jean-François Dufayard, Vincent Lefort … (2010)

PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.