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      Phylogenomics provides a robust topology of the major cnidarian lineages and insights on the origins of key organismal traits

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          Abstract

          Background

          The phylogeny of Cnidaria has been a source of debate for decades, during which nearly all-possible relationships among the major lineages have been proposed. The ecological success of Cnidaria is predicated on several fascinating organismal innovations including stinging cells, symbiosis, colonial body plans and elaborate life histories. However, understanding the origins and subsequent diversification of these traits remains difficult due to persistent uncertainty surrounding the evolutionary relationships within Cnidaria. While recent phylogenomic studies have advanced our knowledge of the cnidarian tree of life, no analysis to date has included genome-scale data for each major cnidarian lineage.

          Results

          Here we describe a well-supported hypothesis for cnidarian phylogeny based on phylogenomic analyses of new and existing genome-scale data that includes representatives of all cnidarian classes. Our results are robust to alternative modes of phylogenetic estimation and phylogenomic dataset construction. We show that two popular phylogenomic matrix construction pipelines yield profoundly different datasets, both in the identities and in the functional classes of the loci they include, but resolve the same topology. We then leverage our phylogenetic resolution of Cnidaria to understand the character histories of several critical organismal traits. Ancestral state reconstruction analyses based on our phylogeny establish several notable organismal transitions in the evolutionary history of Cnidaria and depict the ancestral cnidarian as a solitary, non-symbiotic polyp that lacked a medusa stage. In addition, Bayes factor tests strongly suggest that symbiosis has evolved multiple times independently across the cnidarian radiation.

          Conclusions

          Cnidaria have experienced more than 600 million years of independent evolution and in the process generated an array of organismal innovations. Our results add significant clarification on the cnidarian tree of life and the histories of some of these innovations. Further, we confirm the existence of Acraspeda (staurozoans plus scyphozoans and cubozoans), thus reviving an evolutionary hypothesis put forward more than a century ago.

          Electronic supplementary material

          The online version of this article (10.1186/s12862-018-1142-0) contains supplementary material, which is available to authorized users.

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          Most cited references126

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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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            Basic local alignment search tool.

            A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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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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                Author and article information

                Contributors
                ehsan.kayal@gmail.com
                bastian.bentlage@gmail.com
                sabrina.pankey@unh.edu
                ohdera.aki@mac.com
                momedinamunoz@gmail.com
                david.plachetzki@unh.edu
                collinsa@si.edu
                joseph.ryan@whitney.ufl.edu
                Journal
                BMC Evol Biol
                BMC Evol. Biol
                BMC Evolutionary Biology
                BioMed Central (London )
                1471-2148
                13 April 2018
                13 April 2018
                2018
                : 18
                : 68
                Affiliations
                [1 ]ISNI 0000 0001 2192 7591, GRID grid.453560.1, Department of Invertebrate Zoology, , National Museum of Natural History, Smithsonian Institution, ; Washington, DC, USA
                [2 ]UPMC, CNRS, FR2424, ABiMS, Station Biologique, 29680 Roscoff, France
                [3 ]Marine Laboratory, University of Guam, UOG Station, Mangilao, GU 96923 USA
                [4 ]ISNI 0000 0001 2097 4281, GRID grid.29857.31, Department of Biology, , Pennsylvania State University, ; University Park, PA USA
                [5 ]ISNI 0000 0001 2192 7145, GRID grid.167436.1, Department of Molecular, , Cellular and Biomedical Sciences, University of New Hampshire, ; Durham, NH USA
                [6 ]ISNI 0000 0001 2192 7591, GRID grid.453560.1, National Systematics Laboratory, NOAA Fisheries, National Museum of Natural History, Smithsonian Institution, ; Washington, DC, USA
                [7 ]ISNI 0000 0004 1936 8091, GRID grid.15276.37, Whitney Laboratory for Marine Bioscience, , University of Florida, ; St Augustine, FL USA
                [8 ]ISNI 0000 0004 1936 8091, GRID grid.15276.37, Department of Biology, , University of Florida, ; Gainesville, FL USA
                Author information
                http://orcid.org/0000-0002-7061-9613
                http://orcid.org/0000-0003-4417-905X
                http://orcid.org/0000-0001-8367-0293
                http://orcid.org/0000-0002-6255-7117
                http://orcid.org/0000-0002-3664-9691
                http://orcid.org/0000-0001-5478-0522
                Article
                1142
                10.1186/s12862-018-1142-0
                5932825
                29390964
                0a48eca7-bfc0-4f21-a7b5-fe8c5e33642d
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 12 July 2017
                : 16 February 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000014, Smithsonian Institution;
                Funded by: FundRef http://dx.doi.org/10.13039/100000076, Directorate for Biological Sciences;
                Award ID: OIA-1457769
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100005825, National Institute of Food and Agriculture;
                Award ID: Hatch Project 00654
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2018

                Evolutionary Biology
                cnidaria,genome-scale dataset,phylogenomic analysis,acraspeda,staurozoa,life history evolution

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