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      A taxonomic revision of the sponge-associated genus Thoracactis Gravier, 1918 (Anthozoa: Zoantharia) based on an integrated approach

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          Abstract

          The integrated approach of molecular phylogenetic and morphological analyses has revolutionized the systematics and our understanding of the evolutionary relationships of marine taxa. One such group is the hexacorallian order Zoantharia Rafinesque, 1815. The monotypic genus Thoracactis Gravier, 1918 has been little investigated since its placement within the order Zoantharia more than 100 years ago. Here, we examined museum specimens collected from the Cape Verde Islands (eastern Atlantic) and newly collected specimens from Brazil (southwestern Atlantic), using a combined molecular and morphological approach. Our results conclusively show Thoracactis to be referable to the family Parazoanthidae. Morphological data show that Thoracactis topsenti Gravier, 1918, the type species of this monotypic genus, has a cyclically transitional arrangement of its sphincter muscle, and this arrangement has previously been reported from the Parazoanthidae. Thoracactis can be distinguished from other hexasterophoran glass-sponge-associated genera (Churabana Kise, Montenegro & Reimer, 2022, Parachurabana Kise, 2023, and Vitrumanthus Kise, Montenegro & Reimer, 2022) by a combination of morphological, ecological and molecular phylogenetic data. In addition, molecular phylogenetic analyses clearly indicate that Thoracactis topsenti is placed within Parazoanthidae. These results are yet another demonstration of the utility of comprehensive combined approaches. From now, research attention should focus on the revision of remaining taxonomic questions within the family Epizoanthidae, with the goal of a comprehensively revised suborder Macrocnemina within reach.

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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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            New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0.

            PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.
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              RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference

              Abstract Motivation Phylogenies are important for fundamental biological research, but also have numerous applications in biotechnology, agriculture and medicine. Finding the optimal tree under the popular maximum likelihood (ML) criterion is known to be NP-hard. Thus, highly optimized and scalable codes are needed to analyze constantly growing empirical datasets. Results We present RAxML-NG, a from-scratch re-implementation of the established greedy tree search algorithm of RAxML/ExaML. RAxML-NG offers improved accuracy, flexibility, speed, scalability, and usability compared with RAxML/ExaML. On taxon-rich datasets, RAxML-NG typically finds higher-scoring trees than IQTree, an increasingly popular recent tool for ML-based phylogenetic inference (although IQ-Tree shows better stability). Finally, RAxML-NG introduces several new features, such as the detection of terraces in tree space and the recently introduced transfer bootstrap support metric. Availability and implementation The code is available under GNU GPL at https://github.com/amkozlov/raxml-ng . RAxML-NG web service (maintained by Vital-IT) is available at https://raxml-ng.vital-it.ch/ . Supplementary information Supplementary data are available at Bioinformatics online.
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                Author and article information

                Journal
                Contributions to Zoology
                Contrib. Zool.
                Brill
                1383-4517
                1875-9866
                April 05 2024
                April 05 2024
                : 1-23
                Affiliations
                [1 ]Environmental Management Research Institute, https://dx.doi.org/119882National Institute of Advanced Industrial Science and Technology, aist, 16–1 Onogawa, Tsukuba, Ibaraki 305- 8569, Japan
                [2 ]Molecular Invertebrate Systematics and Ecology Laboratory, Graduate School of Engineering and Science, University of the Ryukyus, 1 Senbaru, Nishihara, Okinawa 903-0213, Japan
                [3 ]Minderoo-uwa Deep-Sea Research Centre, School of Biological Sciences and Oceans Institute, The University of Western Australia, 35 Stirling Highway, Perth, WA 6009, Australia
                [4 ]Department of Biological Oceanography, Oceanographic Institute – University of São Paulo, Praça do Oceanográfico 191, cep 05508-120, São Paulo, SP, Brazil
                [5 ]Marine Evolution and Ecology Group, Naturalis Biodiversity Center, PO Box 9517, 2300 RA Leiden, The Netherlands
                [6 ]Groningen Institute for Evolutionary Life Sciences, University of Groningen, P.O. Box 11103, 9700 CC Groningen, The Netherlands
                [7 ]Tropical Biosphere Research Center, University of the Ryukyus, 1 Senbaru, Nishihara, Okinawa 903–0213, Japan
                Article
                10.1163/18759866-bja10059
                03422d3a-65f4-4744-9957-7f51a2431d26
                © 2024

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

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