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      Morphological and phylogenetic analyses reveal two new species of Sporocadaceae from Hainan, China

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          Abstract

          Species of Sporocadaceae have often been reported as plant pathogens, endophytes or saprophytes and are commonly isolated from a wide range of plant hosts. The isolated fungi were studied through a complete examination, based on multilocus phylogenies from combined datasets of ITS/ tub2/ tef1, in conjunction with morphological characteristics. Nine strains were isolated from Ficus microcarpa , Ilex chinensis and Schima superba in China which represented four species, viz., Monochaetia schimae sp. nov., Neopestalotiopsis haikouensis sp. nov., Neopestalotiopsis piceana and Pestalotiopsis licualicola . Neopestalotiopsis piceana was a new country record for China and first host record from Ficus macrocarpa . Pestalotiopsis licualicola was first report from Ilex chinensis in China.

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          Sudhir Kumar, Glen Stecher, Koichiro Tamura (2016)
          We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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            RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

            Alexandros Stamatakis (2014)
            Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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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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                Author and article information

                Contributors
                Jiwen Xia:
                ORCID: https://orcid.org/0000-0002-7436-7249
                Journal
                Journal ID (nlm-ta): MycoKeys
                Journal ID (iso-abbrev): MycoKeys
                Journal ID (publisher-id): 11
                Journal ID (index): urn:lsid:arphahub.com:pub:C004A564-9D6A-5F9F-B058-6A3815DFE9C3
                Title: MycoKeys
                Publisher: Pensoft Publishers
                ISSN (Print): 1314-4057
                ISSN (Electronic): 1314-4049
                Publication date Collection: 2022
                Publication date (Electronic): 14 April 2022
                Volume: 88
                Pages: 171-192
                Affiliations
                [1 ] Shandong Provincial Key Laboratory for Biology of Vegetable Diseases and Insect Pests, College of Plant Protection, Shandong Agricultural University, Taian, 271018, China Shandong Agricultural University Taian China
                Author notes
                Corresponding author: Jiwen Xia ( xiajiwen1@ 123456126.com )

                Academic editor: Nalin Wijayawardene

                Author information
                https://orcid.org/0000-0002-7436-7249
                Article
                Publisher ID: 82229
                DOI: 10.3897/mycokeys.88.82229
                PMC ID: 9023435
                PubMed ID: 35585932
                SO-VID: a9ab37fc-7c6b-4516-9517-c8706cd70d03
                Copyright © Zhaoxue Zhang, Rongyu Liu, Shubin Liu, Taichang Mu, Xiuguo Zhang, Jiwen Xia
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 17 February 2022
                Date accepted : 29 March 2022
                Funding
                This work was supported by the National Natural Science Foundation of China (nos. 31900014, U2002203, 31750001).
                Categories
                Subject: Research Article
                Subject: Anamorphic Fungi
                Subject: Sordariomycetes
                Subject: Molecular Systematics
                Subject: Phylogeny
                Subject: Taxonomy
                Subject: Asia

                Keywords: monochaetia ,multigene phylogeny, neopestalotiopsis , pestalotiopsis
                Data availability:
                Keywords: monochaetia , multigene phylogeny, neopestalotiopsis , pestalotiopsis

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