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      Achnanthidium tinea sp. nov. – a new monoraphid diatom (Bacillariophyceae) species, described on the basis of molecular and morphological approaches

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          Abstract

          A new monoraphid diatom species Achnanthidium tinea Tseplik, Kulikovskiy, Kociolek & Maltsev, sp. nov. is described from Indonesia. The species is described on the basis of molecular and morphological analyses. According to molecular data the new species belongs to the clade that includes strains of Achnanthidium minutissimum , Achnanthidium saprophilum and Achnanthidium digitatum . Morphologically, the new species differs quite significantly from other species of the same genus because of linear-elliptic valves with almost parallel sides and strongly radiate striae and a butterfly-shaped fascia on the raphe valve. The morphology and phylogeny of the new species are discussed, and thoughts on the current state of the taxonomy of the genus Achnanthidium are expressed. Our work shows the importance of using molecular data in diatom systematics and also demonstrates the need to investigate rarely studied regions of our planet.

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          Sudhir Kumar, Glen Stecher, Koichiro Tamura (2016)
          We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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            A rapid bootstrap algorithm for the RAxML Web servers.

            Alexandros Stamatakis, Paul Hoover, Jacques Rougemont … (2008)
            Despite recent advances achieved by application of high-performance computing methods and novel algorithmic techniques to maximum likelihood (ML)-based inference programs, the major computational bottleneck still consists in the computation of bootstrap support values. Conducting a probably insufficient number of 100 bootstrap (BS) analyses with current ML programs on large datasets-either with respect to the number of taxa or base pairs-can easily require a month of run time. Therefore, we have developed, implemented, and thoroughly tested rapid bootstrap heuristics in RAxML (Randomized Axelerated Maximum Likelihood) that are more than an order of magnitude faster than current algorithms. These new heuristics can contribute to resolving the computational bottleneck and improve current methodology in phylogenetic analyses. Computational experiments to assess the performance and relative accuracy of these heuristics were conducted on 22 diverse DNA and AA (amino acid), single gene as well as multigene, real-world alignments containing 125 up to 7764 sequences. The standard BS (SBS) and rapid BS (RBS) values drawn on the best-scoring ML tree are highly correlated and show almost identical average support values. The weighted RF (Robinson-Foulds) distance between SBS- and RBS-based consensus trees was smaller than 6% in all cases (average 4%). More importantly, RBS inferences are between 8 and 20 times faster (average 14.73) than SBS analyses with RAxML and between 18 and 495 times faster than BS analyses with competing programs, such as PHYML or GARLI. Moreover, this performance improvement increases with alignment size. Finally, we have set up two freely accessible Web servers for this significantly improved version of RAxML that provide access to the 200-CPU cluster of the Vital-IT unit at the Swiss Institute of Bioinformatics and the 128-CPU cluster of the CIPRES project at the San Diego Supercomputer Center. These Web servers offer the possibility to conduct large-scale phylogenetic inferences to a large part of the community that does not have access to, or the expertise to use, high-performance computing resources.
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              Parallelization of the MAFFT multiple sequence alignment program

              Kazutaka Katoh, Hiroyuki Toh (2010)
              Summary: Multiple sequence alignment (MSA) is an important step in comparative sequence analyses. Parallelization is a key technique for reducing the time required for large-scale sequence analyses. The three calculation stages, all-to-all comparison, progressive alignment and iterative refinement, of the MAFFT MSA program were parallelized using the POSIX Threads library. Two natural parallelization strategies (best-first and simple hill-climbing) were implemented for the iterative refinement stage. Based on comparisons of the objective scores and benchmark scores between the two approaches, we selected a simple hill-climbing approach as the default. Availability: The parallelized version of MAFFT is available at http://mafft.cbrc.jp/alignment/software/. This version currently supports the Linux operating system only. Contact: kazutaka.katoh@aist.go.jp Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                Anton M. Glushchenko:
                ORCID: https://orcid.org/0000-0002-2832-1872
                Sergei I. Genkal
                Journal
                Journal ID (nlm-ta): PhytoKeys
                Journal ID (iso-abbrev): PhytoKeys
                Journal ID (publisher-id): 3
                Journal ID (index): urn:lsid:arphahub.com:pub:F7FCE910-8E78-573F-9C77-7788555F8AAD
                Title: PhytoKeys
                Publisher: Pensoft Publishers
                ISSN (Print): 1314-2011
                ISSN (Electronic): 1314-2003
                Publication date Collection: 2021
                Publication date (Electronic): 12 March 2021
                Volume: 174
                Pages: 147-163
                Affiliations
                [1 ] K.A. Timiryazev Institute of Plant Physiology RAS, IPP RAS, 35 Botanicheskaya St., Moscow, 127276, Russia
                [2 ] Papanin Institute for Biology of Inland Waters, Russian Academy of Sciences, Yaroslavl, Nekouz, Borok, 152742, Russia
                [3 ] University of Colorado Museum of Natural History, Broadway, Boulder, CO 80302, USA
                [4 ] Department of Ecology and Evolutionary Biology, University of Colorado, Boulder, Colorado, 80309, USA
                Author notes
                Corresponding author: Maxim S. Kulikovskiy ( max-kulikovsky@ 123456yandex.ru )

                Academic editor: K. Manoylov

                Author information
                https://orcid.org/0000-0002-2832-1872
                https://orcid.org/0000-0001-9824-7164
                Article
                Publisher ID: 60337
                DOI: 10.3897/phytokeys.174.60337
                PMC ID: 7979678
                SO-VID: 11413025-0f8e-4a02-ad95-8a9cdc9f94e8
                Copyright © Natalia D. Tseplik, Yevhen I. Maltsev, Anton M. Glushchenko, Irina V. Kuznetsova, Sergei I. Genkal, John Patrick Kociolek, Maxim S. Kulikovskiy
                License:

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Date received : 03 November 2020
                Date accepted : 21 December 2020
                Funding
                Funded by: Russian Science Foundation 501100006769 http://doi.org/10.13039/501100006769
                Categories
                Subject: Research Article
                Subject: Bacillariophyceae
                Subject: Biodiversity & Conservation
                Subject: Asia

                ScienceOpen disciplines: Plant science & Botany
                Keywords: achnanthidium , bacillariophyceae ,indonesia,molecular investigations,new species
                Data availability:
                ScienceOpen disciplines: Plant science & Botany
                Keywords: achnanthidium , bacillariophyceae , indonesia, molecular investigations, new species

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