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      The Enigmatic Thelebolaceae (Thelebolales, Leotiomycetes): One New Genus Solomyces and Five New Species

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          Abstract

          The family Thelebolaceae belongs to the order Thelebolales, class Leotiomycetes, and contains 22 genera. In this study, we introduce a new genus Solomyces gen. nov. in the family Thelebolaceae, which is supported by morphological observation and multilocus-based [internal transcribed spacers (ITS) + LSU and ITS + LSU+ MCM7+ EF1A+ RPB2] phylogenetic analysis. Maximum-likelihood and Bayesian phylogenetic inference analyses indicated that Solomyces is a distinct genus within this family. The new genus is compared against related Thelebolaceae genera, and its description and illustration are provided. This genus comprises one new species and one unnamed species (including two strains). We also report the addition of four new species – Pseudogymnoascus shaanxiensis, Pseudogymnoascus guizhouensis, Pseudogymnoascus sinensis, and Geomyces obovatus – in the family Thelebolaceae and present their morphological and phylogenetic characterizations.

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

          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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            IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

            Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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              MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

              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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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                29 October 2020
                2020
                : 11
                : 572596
                Affiliations
                [1] 1Institute of Fungus Resources, Department of Ecology, College of Life Sciences, Guizhou University , Guiyang, China
                [2] 2Department of Microbiology, Guiyang College of Traditional Chinese Medicine , Guiyang, China
                [3] 3Key Laboratory of Plant Resource Conservation and Germplasm Innovation in Mountainous Region (Ministry of Education), Guizhou University , Guiyang, China
                [4] 4Engineering Research Center of Industrial Microbiology, Ministry of Education, Fujian Normal University , Fuzhou, China
                Author notes

                Edited by: Gustavo Henrique Goldman, University of São Paulo, Brazil

                Reviewed by: Hiran A. Ariyawansa, National Taiwan University, Taiwan; Donald Henry Pfister, Harvard University, United States

                *Correspondence: Yanfeng Han, swallow1128@ 123456126.com

                This article was submitted to Fungi and Their Interactions, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2020.572596
                7658094
                33193172
                715dec26-8536-48a6-801c-45d59bc96540
                Copyright © 2020 Zhang, Dong, Chen, Mou, Lu, Han, Huang and Liang.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 15 June 2020
                : 29 September 2020
                Page count
                Figures: 7, Tables: 2, Equations: 0, References: 52, Pages: 15, Words: 0
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                taxonomy,phylogeny,thelebolales,new genus,new species
                Microbiology & Virology
                taxonomy, phylogeny, thelebolales, new genus, new species

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