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      The numbers of fungi: contributions from traditional taxonomic studies and challenges of metabarcoding

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          Abstract

          The global diversity of fungi has been estimated using several different approaches. There is somewhere between 2–11 million estimated species, but the number of formally described taxa is around 150,000, a tiny fraction of the total. In this paper, we examine 12 ascomycete genera as case studies to establish trends in fungal species descriptions, and introduce new species in each genus. To highlight the importance of traditional morpho-molecular methods in publishing new species, we introduce novel taxa in 12 genera that are considered to have low species discovery. We discuss whether the species are likely to be rare or due to a lack of extensive sampling and classification. The genera are Apiospora, Bambusicola, Beltrania, Capronia, Distoseptispora, Endocalyx, Neocatenulostroma, Neodeightonia, Paraconiothyrium, Peroneutypa, Phaeoacremonium and Vanakripa. We discuss host-specificity in selected genera and compare the number of species epithets in each genus with the number of ITS (barcode) sequences deposited in GenBank and UNITE. We furthermore discuss the relationship between the divergence times of these genera with those of their hosts. We hypothesize whether there might be more species in these genera and discuss hosts and habitats that should be investigated for novel species discovery.

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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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            Posterior Summarization in Bayesian Phylogenetics Using Tracer 1.7

            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.
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              jModelTest 2: more models, new heuristics and parallel computing.

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                Journal
                Fungal Diversity
                Fungal Diversity
                Springer Science and Business Media LLC
                1560-2745
                1878-9129
                May 2022
                April 28 2022
                May 2022
                : 114
                : 1
                : 327-386
                Article
                10.1007/s13225-022-00502-3
                960b8c58-bb06-4dff-aa58-213f4b0372de
                © 2022

                https://creativecommons.org/licenses/by/4.0

                https://creativecommons.org/licenses/by/4.0

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