Morphological and phylogenetic evidence for recognition of two new species of Hyphoderma (Basidiomycota) from southern China, with a key to all Chinese Hyphoderma

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Abstract

Wood-inhabiting fungi play crucial roles as decomposers in forest ecosystems and, in this study, two new wood-inhabiting corticioid fungi, Hyphoderma puerense and H. tenuissimum spp. nov., are proposed, based on a combination of morphological features and molecular evidence. Hyphoderma puerense is characterised by effused basidiomata with smooth to floccose hymenial surface, a monomitic hyphal system with clamped generative hyphae and ellipsoid basidiospores. Hyphoderma tenuissimum is characterised by resupinate basidiomata with tuberculate to minutely-grandinioid hymenial surface, septate cystidia and cylindrical to allantoid basidiospores. Sequences of ITS and nLSU rRNA markers of the studied samples were generated and phylogenetic analyses were performed with Maximum Likelihood, maximum parsimony and Bayesian Inference methods. These analyses showed that the two new species clustered into Hyphoderma, in which H. puerense grouped with H. moniliforme and H. tenuissimum formed a singleton lineage. In addition, an identification key to Chinese Hyphoderma is provided.

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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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AMPLIFICATION AND DIRECT SEQUENCING OF FUNGAL RIBOSOMAL RNA GENES FOR PHYLOGENETICS

T.J White, T. Bruns, S. Lee … (1990)

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MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization

Kazutaka Katoh, John Rozewicki, Kazunori Yamada (2017)

Abstract This article describes several features in the MAFFT online service for multiple sequence alignment (MSA). As a result of recent advances in sequencing technologies, huge numbers of biological sequences are available and the need for MSAs with large numbers of sequences is increasing. To extract biologically relevant information from such data, sophistication of algorithms is necessary but not sufficient. Intuitive and interactive tools for experimental biologists to semiautomatically handle large data are becoming important. We are working on development of MAFFT toward these two directions. Here, we explain (i) the Web interface for recently developed options for large data and (ii) interactive usage to refine sequence data sets and MSAs.