22
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      An integrative systematic framework helps to reconstruct skeletal evolution of glass sponges (Porifera, Hexactinellida)

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Glass sponges (Class Hexactinellida) are important components of deep-sea ecosystems and are of interest from geological and materials science perspectives. The reconstruction of their phylogeny with molecular data has only recently begun and shows a better agreement with morphology-based systematics than is typical for other sponge groups, likely because of a greater number of informative morphological characters. However, inconsistencies remain that have far-reaching implications for hypotheses about the evolution of their major skeletal construction types (body plans). Furthermore, less than half of all described extant genera have been sampled for molecular systematics, and several taxa important for understanding skeletal evolution are still missing. Increased taxon sampling for molecular phylogenetics of this group is therefore urgently needed. However, due to their remote habitat and often poorly preserved museum material, sequencing all 126 currently recognized extant genera will be difficult to achieve. Utilizing morphological data to incorporate unsequenced taxa into an integrative systematics framework therefore holds great promise, but it is unclear which methodological approach best suits this task.

          Results

          Here, we increase the taxon sampling of four previously established molecular markers (18S, 28S, and 16S ribosomal DNA, as well as cytochrome oxidase subunit I) by 12 genera, for the first time including representatives of the order Aulocalycoida and the type genus of Dactylocalycidae, taxa that are key to understanding hexactinellid body plan evolution. Phylogenetic analyses suggest that Aulocalycoida is diphyletic and provide further support for the paraphyly of order Hexactinosida; hence these orders are abolished from the Linnean classification. We further assembled morphological character matrices to integrate so far unsequenced genera into phylogenetic analyses in maximum parsimony (MP), maximum likelihood (ML), Bayesian, and morphology-based binning frameworks. We find that of these four approaches, total-evidence analysis using MP gave the most plausible results concerning congruence with existing phylogenetic and taxonomic hypotheses, whereas the other methods, especially ML and binning, performed more poorly. We use our total-evidence phylogeny of all extant glass sponge genera for ancestral state reconstruction of morphological characters in MP and ML frameworks, gaining new insights into the evolution of major hexactinellid body plans and other characters such as different spicule types.

          Conclusions

          Our study demonstrates how a comprehensive, albeit in some parts provisional, phylogeny of a larger taxon can be achieved with an integrative approach utilizing molecular and morphological data, and how this can be used as a basis for understanding phenotypic evolution. The datasets and associated trees presented here are intended as a resource and starting point for future work on glass sponge evolution.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12983-017-0191-3) contains supplementary material, which is available to authorized users.

          Related collections

          Most cited references85

          • Record: found
          • Abstract: found
          • Article: not found

          How many bootstrap replicates are necessary?

          Phylogenetic bootstrapping (BS) is a standard technique for inferring confidence values on phylogenetic trees that is based on reconstructing many trees from minor variations of the input data, trees called replicates. BS is used with all phylogenetic reconstruction approaches, but we focus here on one of the most popular, maximum likelihood (ML). Because ML inference is so computationally demanding, it has proved too expensive to date to assess the impact of the number of replicates used in BS on the relative accuracy of the support values. For the same reason, a rather small number (typically 100) of BS replicates are computed in real-world studies. Stamatakis et al. recently introduced a BS algorithm that is 1 to 2 orders of magnitude faster than previous techniques, while yielding qualitatively comparable support values, making an experimental study possible. In this article, we propose stopping criteria--that is, thresholds computed at runtime to determine when enough replicates have been generated--and we report on the first large-scale experimental study to assess the effect of the number of replicates on the quality of support values, including the performance of our proposed criteria. We run our tests on 17 diverse real-world DNA--single-gene as well as multi-gene--datasets, which include 125-2,554 taxa. We find that our stopping criteria typically stop computations after 100-500 replicates (although the most conservative criterion may continue for several thousand replicates) while producing support values that correlate at better than 99.5% with the reference values on the best ML trees. Significantly, we also find that the stopping criteria can recommend very different numbers of replicates for different datasets of comparable sizes. Our results are thus twofold: (i) they give the first experimental assessment of the effect of the number of BS replicates on the quality of support values returned through BS, and (ii) they validate our proposals for stopping criteria. Practitioners will no longer have to enter a guess nor worry about the quality of support values; moreover, with most counts of replicates in the 100-500 range, robust BS under ML inference becomes computationally practical for most datasets. The complete test suite is available at http://lcbb.epfl.ch/BS.tar.bz2, and BS with our stopping criteria is included in the latest release of RAxML v7.2.5, available at http://wwwkramer.in.tum.de/exelixis/software.html.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Phylogenomics revives traditional views on deep animal relationships.

            The origin of many of the defining features of animal body plans, such as symmetry, nervous system, and the mesoderm, remains shrouded in mystery because of major uncertainty regarding the emergence order of the early branching taxa: the sponge groups, ctenophores, placozoans, cnidarians, and bilaterians. The "phylogenomic" approach [1] has recently provided a robust picture for intrabilaterian relationships [2, 3] but not yet for more early branching metazoan clades. We have assembled a comprehensive 128 gene data set including newly generated sequence data from ctenophores, cnidarians, and all four main sponge groups. The resulting phylogeny yields two significant conclusions reviving old views that have been challenged in the molecular era: (1) that the sponges (Porifera) are monophyletic and not paraphyletic as repeatedly proposed [4-9], thus undermining the idea that ancestral metazoans had a sponge-like body plan; (2) that the most likely position for the ctenophores is together with the cnidarians in a "coelenterate" clade. The Porifera and the Placozoa branch basally with respect to a moderately supported "eumetazoan" clade containing the three taxa with nervous system and muscle cells (Cnidaria, Ctenophora, and Bilateria). This new phylogeny provides a stimulating framework for exploring the important changes that shaped the body plans of the early diverging phyla.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Bayesian Analysis Using a Simple Likelihood Model Outperforms Parsimony for Estimation of Phylogeny from Discrete Morphological Data

              Despite the introduction of likelihood-based methods for estimating phylogenetic trees from phenotypic data, parsimony remains the most widely-used optimality criterion for building trees from discrete morphological data. However, it has been known for decades that there are regions of solution space in which parsimony is a poor estimator of tree topology. Numerous software implementations of likelihood-based models for the estimation of phylogeny from discrete morphological data exist, especially for the Mk model of discrete character evolution. Here we explore the efficacy of Bayesian estimation of phylogeny, using the Mk model, under conditions that are commonly encountered in paleontological studies. Using simulated data, we describe the relative performances of parsimony and the Mk model under a range of realistic conditions that include common scenarios of missing data and rate heterogeneity.
                Bookmark

                Author and article information

                Contributors
                m.dohrmann@lrz.uni-muenchen.de
                ckelley@hawaii.edu
                michelle.kelly@niwa.co.nz
                apis@twarda.pan.pl
                john.hooper@qm.qld.gov.au
                hmreiswig@shaw.ca
                Journal
                Front Zool
                Front. Zool
                Frontiers in Zoology
                BioMed Central (London )
                1742-9994
                21 March 2017
                21 March 2017
                2017
                : 14
                : 18
                Affiliations
                [1 ]ISNI 0000 0004 1936 973X, GRID grid.5252.0, Department of Earth & Environmental Sciences, Palaeontology & Geobiology, Molecular Geo- & Palaeobiology Lab, , Ludwig-Maximilians-University Munich, ; Richard-Wagner-Str. 10, 80333 Munich, Germany
                [2 ]ISNI 0000 0001 2188 0957, GRID grid.410445.0, Hawaii Undersea Research Laboratory, , University of Hawaii at Manoa, ; 1000 Pope Rd, MSB 229, Honolulu, 96822 HI USA
                [3 ]Coasts and Oceans National Centre, National Institute of Water and Atmospheric Research (NIWA) Ltd, Private Bag 99940, Newmarket, Auckland, 1149 New Zealand
                [4 ]ISNI 0000 0001 1958 0162, GRID grid.413454.3, Institute of Paleobiology, , Polish Academy of Sciences, ; ul. Twarda 51/55, 00-818 Warszawa, Poland
                [5 ]ISNI 0000 0001 2215 0059, GRID grid.452644.5, Biodiversity & Geosciences Program, , Queensland Museum, ; South Brisbane, QLD 4101 Australia
                [6 ]ISNI 0000 0004 0437 5432, GRID grid.1022.1, Eskitis Institute for Drug Discovery, , Griffith University, ; Nathan, QLD 4111 Australia
                [7 ]ISNI 0000 0001 0757 3272, GRID grid.452733.4, Natural History Section, , Royal British Columbia Museum, ; 675 Belleville Street, Victoria, BC V8W 9W2 Canada
                [8 ]ISNI 0000 0004 1936 9465, GRID grid.143640.4, Department of Biology, , University of Victoria, ; 3800 Finnerty Road, Victoria, BC V8P 4H9 Canada
                Article
                191
                10.1186/s12983-017-0191-3
                5359874
                28331531
                5a232ba4-d790-4c7b-9daf-a99dcee000d8
                © The Author(s). 2017

                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
                : 19 May 2016
                : 20 January 2017
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: DO 1742/1-1, 2
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                Animal science & Zoology
                ancestral state reconstruction,character evolution,classification,hexactinellida,integrative systematics,phylogeny,porifera,total evidence

                Comments

                Comment on this article