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      Brazilian Atlantic Forest and Pampa Biomes in the spotlight: an overview of Aspergillus, Penicillium, and Talaromyces (Eurotiales) species and the description of Penicillium nordestinense sp. nov.

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          Abstract

          ABSTRACT The knowledge of the geographical distribution of fungi is essential to promote the understanding of global and national fungal diversity patterns. In this study, we provide a literature-based checklist of Aspergillus, Penicillium, and Talaromyces species recorded in the biomes of the Brazilian Atlantic Forest and the Brazilian Pampa. Only Penicillium digitatum was reported for the Pampa biome. For the Atlantic Forest, a total of 169 species (68 Aspergillus, 79 Penicillium, and 22 Talaromyces) are reported, of which 20 are typified with specimens from this biome, including the novel species Penicillium nordestinense (section Lanata-Divaricata) that is described in this study. Penicillium nordestinense is phylogenetically related to the invalidly described species Penicillium setosum, and this species is validated here. Soil was the most common substrate from where species were reported. Several reported species are well known in biotechnological processes. Penicilliopsis zonata and Sclerocleista ornata, species previously treated in Aspergillus, are recorded. This checklist reflects the limited knowledge of fungal species in tropical environments, such as the Brazilian Atlantic Forest and Pampa biomes. This information is a good framework for understanding the Brazilian diversity of Aspergillus, Penicillium, and Talaromyces and provides data for future fungal biogeographical studies in tropical environments.

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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

                Journal
                abb
                Acta Botanica Brasilica
                Acta Bot. Bras.
                Sociedade Botânica do Brasil (Alta Floresta, MT, Brazil )
                0102-3306
                1677-941X
                2022
                : 36
                : e2021abb0390
                Affiliations
                [2] Goiânia Goiás orgnameUniversidade Federal de Goiás orgdiv1Departamento de Biociências e Tecnologia orgdiv2Instituto de Patologia Tropical e Saúde Pública Brazil
                [1] Recife Pernambuco orgnameUniversidade Federal de Pernambuco orgdiv1Centro de Biociências orgdiv2Departamento de Micologia Professor Chaves Batista Brazil
                [3] Uppsalalaan orgnameWesterdijk Fungal Biodiversity Institute The Netherlands
                Article
                S0102-33062022000100143 S0102-3306(22)03600000143
                10.1590/0102-33062021abb0390
                fe478c3a-7850-4443-a27c-756d9971bc09

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                : 07 June 2022
                : 29 December 2021
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 167, Pages: 0
                Product

                SciELO Brazil

                Categories
                Original Article

                Aspergillaceae,biodiversity,conservation hotspot,Trichocomaceae,ascomycetes

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