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      Re-Evaluating Botryosphaeriales: Ancestral State Reconstructions of Selected Characters and Evolution of Nutritional Modes

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          Abstract

          Botryosphaeriales (Dothideomycetes, Ascomycota) occur in a wide range of habitats as endophytes, saprobes, and pathogens. The order Botryosphaeriales has not been subjected to evaluation since 2019 by Phillips and co-authors using phylogenetic and evolutionary analyses. Subsequently, many studies introduced novel taxa into the order and revised several families separately. In addition, no ancestral character studies have been conducted for this order. Therefore, in this study, we re-evaluated the character evolution and taxonomic placements of Botryosphaeriales species based on ancestral character evolution, divergence time estimation, and phylogenetic relationships, including all the novel taxa that have been introduced so far. Maximum likelihood, maximum parsimony, and Bayesian inference analyses were conducted on a combined LSU and ITS sequence alignment. Ancestral state reconstruction was carried out for conidial colour, septation, and nutritional mode. Divergence times estimates revealed that Botryosphaeriales originated around 109 Mya in the early epoch of the Cretaceous period. All six families in Botryosphaeriales evolved in the late epoch of the Cretaceous period (66–100 Mya), during which Angiosperms also appeared, rapidly diversified and became dominant on land. Families of Botryosphaeriales diversified during the Paleogene and Neogene periods in the Cenozoic era. The order comprises the families Aplosporellaceae, Botryosphaeriaceae, Melanopsaceae, Phyllostictaceae, Planistromellaceae and Saccharataceae. Furthermore, current study assessed two hypotheses; the first one being “All Botryosphaeriales species originated as endophytes and then switched into saprobes when their hosts died or into pathogens when their hosts were under stress”; the second hypothesis states that “There is a link between the conidial colour and nutritional mode in botryosphaerialean taxa”. Ancestral state reconstruction and nutritional mode analyses revealed a pathogenic/saprobic nutritional mode as the ancestral character. However, we could not provide strong evidence for the first hypothesis mainly due to the significantly low number of studies reporting the endophytic botryosphaerialean taxa. Results also showed that hyaline and aseptate conidia were ancestral characters in Botryosphaeriales and supported the relationship between conidial pigmentation and the pathogenicity of Botryosphaeriales species.

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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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              MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization

              Abstract This article describes several features in the MAFFT online service for multiple sequence alignment (MSA). As a result of recent advances in sequencing technologies, huge numbers of biological sequences are available and the need for MSAs with large numbers of sequences is increasing. To extract biologically relevant information from such data, sophistication of algorithms is necessary but not sufficient. Intuitive and interactive tools for experimental biologists to semiautomatically handle large data are becoming important. We are working on development of MAFFT toward these two directions. Here, we explain (i) the Web interface for recently developed options for large data and (ii) interactive usage to refine sequence data sets and MSAs.
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                Author and article information

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                Journal
                JFOUCU
                Journal of Fungi
                JoF
                MDPI AG
                2309-608X
                February 2023
                January 29 2023
                : 9
                : 2
                : 184
                Article
                10.3390/jof9020184
                2d630119-87fd-4618-ae54-552665784676
                © 2023

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

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