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      Phylogeny, Divergence Time Estimation and Biogeography of the Genus Onnia (Basidiomycota, Hymenochaetaceae)

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          Abstract

          Species of Onnia are important tree pathogens and play a crucial role in forest ecosystems. The species diversity and distribution of Onnia have been studied, however, its evolutionary history is poorly understood. In this study, we reconstructed the phylogeny of Onnia using internal transcribed spacers (ITS) and large subunit (LSU) rDNA sequence data. Molecular clock analyses developed the divergence times of Onnia based on a dataset (ITS + LSU rDNA + rpb1 + rpb2 + tef1α). Reconstruct Ancestral State in Phylogenies (RASP) was used to reconstruct the historical biogeography for the genus Onnia with a Dispersal Extinction Cladogenesis (DEC) model. Here, we provide a robust phylogeny of Onnia, with a description of a new species, Onnia himalayana from Yunnan Province, China. Molecular clock analyses suggested that the common ancestor of Onnia and Porodaedalea emerged in the Paleogene period with full support and a mean stem age of 56.9 Mya (95% highest posterior density of 35.9–81.6 Mya), and most species occurred in the Neogene period. Biogeographic studies suggest that Asia, especially in the Hengduan-Himalayan region, is probably the ancestral area. Five dispersals and two vicariances indicate that species of Onnia were rapidly diversified. Speciation occurred in the Old World and New World due to geographic separation. This study is the first inference of the divergence times, biogeography, and speciation of the genus Onnia.

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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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            RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

            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

              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
                07 July 2022
                2022
                : 13
                : 907961
                Affiliations
                [1] 1School of Ecology and Nature Conservation, Institute of Microbiology, Beijing Forestry University , Beijing, China
                [2] 2College of Life Sciences, Shandong Normal University , Jinan, China
                Author notes

                Edited by: Bálint Dima, Eötvös Loránd University, Hungary

                Reviewed by: Young Woon Lim, Seoul National University, South Korea; Hai-Sheng Yuan, Institute of Applied Ecology (CAS), China

                *Correspondence: Fang Wu, fangwubjfu2014@ 123456bjfu.edu.cn

                This article was submitted to Evolutionary and Genomic Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2022.907961
                9301299
                35875515
                bed30d2b-937d-43fe-9c8b-79429db24dc8
                Copyright © 2022 Zhao, Zhou, Liu, Wu and Dai.

                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
                : 30 March 2022
                : 06 June 2022
                Page count
                Figures: 5, Tables: 2, Equations: 0, References: 78, Pages: 12, Words: 7318
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                hymenochaetaceae,molecular dating,reconstruct ancestral state,new taxa,biogeographic patterns

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