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      Using RDNA sequences to define dinoflagellate species

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          Abstract

          Dinoflagellate species are traditionally defined using morphological characters, but molecular evidence accumulated over the past several decades indicates many morphologically-based descriptions are inaccurate. This recognition led to an increasing reliance on DNA sequence data, particularly rDNA gene segments, in defining species. The validity of this approach assumes the divergence in rDNA or other selected genes parallels speciation events. Another concern is whether single gene rDNA phylogenies by themselves are adequate for delineating species or if multigene phylogenies are required instead. Currently, few studies have directly assessed the relative utility of multigene versus rDNA-based phylogenies for distinguishing species. To address this, the current study examined D1-D3 and ITS/5.8S rDNA gene regions, a multi-gene phylogeny, and morphological characters in Gambierdiscus and other related dinoflagellate genera to determine if they produce congruent phylogenies and identify the same species. Data for the analyses were obtained from previous sequencing efforts and publicly available dinoflagellate transcriptomic libraries as well from the additional nine well-characterized Gambierdiscus species transcriptomic libraries generated in this study. The D1-D3 and ITS/5.8S phylogenies successfully identified the described Gambierdiscus and Alexandrium species. Additionally, the data showed that the D1-D3 and multigene phylogenies were equally capable of identifying the same species. The multigene phylogenies, however, showed different relationships among species and are likely to prove more accurate at determining phylogenetic relationships above the species level. These data indicated that D1-D3 and ITS/5.8S rDNA region phylogenies are generally successful for identifying species of Gambierdiscus, and likely those of other dinoflagellates. To assess how broadly general this finding is likely to be, rDNA molecular phylogenies from over 473 manuscripts representing 232 genera and 863 described species of dinoflagellates were reviewed. Results showed the D1-D3 rDNA and ITS phylogenies in combination are capable of identifying 97% of dinoflagellate species including all the species belonging to the genera Alexandrium, Ostreopsis and Gambierdiscus, although it should be noted that multi-gene phylogenies are preferred for inferring relationships among these species. A protocol is presented for determining when D1-D3, confirmed by ITS/5.8S rDNA sequence data, would take precedence over morphological features when describing new dinoflagellate species. This protocol addresses situations such as: a) when a new species is both morphologically and molecularly distinct from other known species; b) when a new species and closely related species are morphologically indistinguishable, but genetically distinct; and c) how to handle potentially cryptic species and cases where morphotypes are clearly distinct but have the same rDNA sequence. The protocol also addresses other molecular, morphological, and genetic approaches required to resolve species boundaries in the small minority of species where the D1-D3/ITS region phylogenies fail.

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          Most cited references125

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

            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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              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.

                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: Project administrationRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: InvestigationRole: MethodologyRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: ValidationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                25 February 2022
                2022
                : 17
                : 2
                : e0264143
                Affiliations
                [1 ] Joint Institute for Food Safety and Applied Nutrition (JIFSAN), University of Maryland—College Park, College Park, MD, United States of America
                [2 ] Cell Biology and Molecular Genetics, University of Maryland—College Park, College Park, MD, United States of America
                [3 ] CSS, Inc. Under Contract to National Oceanic and Atmospheric Administration (NOAA), National Ocean Service, National Centers for Coastal Ocean Science, Beaufort Laboratory, Beaufort, North Carolina, United States of America
                [4 ] National Oceanic and Atmospheric Administration, National Ocean Service, National Centers for Coastal Ocean Science, Beaufort Laboratory, Beaufort, North Carolina, United States of America
                IRIG-CEA Grenoble, FRANCE
                Author notes

                Competing Interests: The authors have read the journal’s policy and have the following competing interests: R. Wayne Litaker is a paid contractor for the National Oceanic and Atmospheric Administration (NOAA).

                Author information
                https://orcid.org/0000-0003-1677-7431
                Article
                PONE-D-22-00500
                10.1371/journal.pone.0264143
                8880924
                35213572
                c562b8f1-8299-432a-943c-1fb3aa729a0e

                This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 14 January 2022
                : 3 February 2022
                Page count
                Figures: 6, Tables: 3, Pages: 33
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: DEB1541529
                Award Recipient :
                This project was supported in part by the National Science Foundation (NSF) in the form of a grant to CFD and BMO [DEB1541529] and the Maryland Agricultural Experiment Station (MAES) in the form of funds to CFD. This project was also supported in part by the joint collaboration between the University of Maryland and the Food and Drug Administration through Joint Institute for Food Safety and Applied Nutrition (JIFSAN) in the form of support to BMO. This project was also supported by the National Oceanic and Atmospheric Administration (NOAA), National Ocean Service, National Centers for Coastal Ocean Science in the form of program funds to CH and WL. The NOAA provided support in the form of a salary to WL. The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Systematics
                Phylogenetics
                Biology and Life Sciences
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Computer and Information Sciences
                Data Management
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Biology and Life Sciences
                Organisms
                Eukaryota
                Protists
                Dinoflagellates
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Processes
                Speciation
                Species Delimitation
                Biology and Life Sciences
                Evolutionary Biology
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
                Biology and Life Sciences
                Taxonomy
                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
                Computer and Information Sciences
                Data Management
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                Evolutionary Systematics
                Phylogenetics
                Phylogenetic Analysis
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                Computational Biology
                Genome Analysis
                Transcriptome Analysis
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                Transcriptome Analysis
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                Computer and Information Sciences
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                Evolutionary Systematics
                Phylogenetics
                Animal Phylogenetics
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                Custom metadata
                Sequence reads were deposited in the National Center for Biotechnological Information, Short Read Archive (NCBI, SRA) as BioSamples SAMN14442098 to SAMN14442113 under BioProject PRJNA614967 (see S3 Table for specifics). The LSU D1-D3 rDNA sequences isolated from each of the transcriptomes assembled in this study are available at Genbank under Accessions: MT248299- MT248319. The ITS1 rDNA sequences also isolated from the transcriptomes are available at Genbank under Accessions: MZ964947- MZ964963.

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