A new species of Pareas (Squamata, Pareidae) from southern Vietnam

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Abstract

Abstract We describe a new species of pareid snake from the Di Linh Plateau in Lam Dong Province of southern Vietnam based on morphological and molecular evidence. Pareas temporalis sp. nov. is distinguished from its congeners by having the combination of yellow-brown body colouration; hexagonal-shaped frontal, with lateral sides parallel to the body axis; 16–17 temporals, with 4–5 anterior temporals; loreal and prefrontal not contacting eye; 2–3 preoculars; two suboculars; 2–3 postoculars; 8–9 supralabials; 8–9 infralabials; 15–15–15 dorsal scale rows, all keeled, three vertebral scale rows enlarged; 191 (+1 preventral) ventrals, smooth; 92 subcaudals, all divided; undivided anal scale; two postocular stripes; and a solid dark brown vertebral stripe extending from rear of nuchal collar along the entire length of body and tail. Phylogenetic analyses of mitochondrial DNA data recovered the new species to be nested within the P. carinatus complex and to be the sister taxon to P. nuchalis from Borneo.

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MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

Kazutaka Katoh, Daron Standley (2013)

We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.

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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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Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7

Andrew Rambaut, Alexei J. Drummond, Dong Xie … (2018)

Abstract Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We present the software package Tracer (version 1.7) for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference. Tracer provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more. Tracer is open-source and available at http://beast.community/tracer.