2
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Anchored Phylogenomics, Evolution and Systematics of Elateridae: Are All Bioluminescent Elateroidea Derived Click Beetles?

      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

          Simple Summary

          In the era of phylogenomics, new molecular sequencing and computational techniques can aid in resolving phylogenetic relationships that were previously intractable by morphological or limited molecular data. In this study, we used anchored hybrid enrichment—designed to recover DNA sequences from hundreds of single-copy orthologous genes—to resolve the phylogeny of the Elateridae (click-beetles) and establish their placement within superfamily Elateroidea. The resulting data were compatible with published transcriptomes, allowing for integrating our dataset with previously published data. Using a wide range of analyses on these molecular data, we tested hypotheses long-debated in the morphological literature and also the robustness of our phylogenetic inferences. Our results placed the bioluminescent lampyroids (fireflies and relatives) within the click-beetles, challenging the current classification of Elateridae, Lampyridae, Phengodidae, and Rhagophthalmidae. However, despite the large amount of molecular data analyzed, a few nodes with conflicting phylogenetic signals could not be unambiguously resolved. Overall, we recovered well-resolved tree topologies that will serve as a framework for further systematic and evolutionary studies of click-beetles. This work further demonstrates that the click-beetle lineage contains not only pest wireworms, but also many species that benefit agriculture.

          Abstract

          Click-beetles (Coleoptera: Elateridae) are an abundant, diverse, and economically important beetle family that includes bioluminescent species. To date, molecular phylogenies have sampled relatively few taxa and genes, incompletely resolving subfamily level relationships. We present a novel probe set for anchored hybrid enrichment of 2260 single-copy orthologous genes in Elateroidea. Using these probes, we undertook the largest phylogenomic study of Elateroidea to date (99 Elateroidea, including 86 Elateridae, plus 5 non-elateroid outgroups). We sequenced specimens from 88 taxa to test the monophyly of families, subfamilies and tribes. Maximum likelihood and coalescent phylogenetic analyses produced well-resolved topologies. Notably, the included non-elaterid bioluminescent families (Lampyridae + Phengodidae + Rhagophthalmidae) form a clade within the otherwise monophyletic Elateridae, and Sinopyrophoridae may not warrant recognition as a family. All analyses recovered the elaterid subfamilies Elaterinae, Agrypninae, Cardiophorinae, Negastriinae, Pityobiinae, and Tetralobinae as monophyletic. Our results were conflicting on whether the hypnoidines are sister to Dendrometrinae or Cardiophorinae + Negastriinae. Moreover, we show that fossils with the eucnemid-type frons and elongate cylindrical shape may belong to Eucnemidae, Elateridae: Thylacosterninae, ancestral hard-bodied cantharoids or related extinct groups. Proposed taxonomic changes include recognition of Plastocerini as a tribe in Dendrometrinae and Hypnoidinae stat. nov. as a subfamily within Elateridae.

          Related collections

          Most cited references 85

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

            Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              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/.
                Bookmark

                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Biology (Basel)
                Biology (Basel)
                biology
                Biology
                MDPI
                2079-7737
                21 May 2021
                June 2021
                : 10
                : 6
                Affiliations
                [1 ]Agriculture and Agri-Food Canada, 960 Carling Avenue, Ottawa, ON K1A 0C6, Canada; adam.brunke@ 123456canada.ca (A.J.B.); julie.chapados@ 123456canada.ca (J.T.C.); jackson.eyres@ 123456canada.ca (J.E.); robin.richter@ 123456canada.ca (R.R.); karine.savard@ 123456canada.ca (K.S.); jeremy.dettman@ 123456canada.ca (J.R.D.)
                [2 ]Department of Zoology, Faculty of Science, Palacky University, 17. listopadu 50, 771 46 Olomouc, Czech Republic; robin.kundrata@ 123456upol.cz
                [3 ]Australian National Insect Collection, National Collections Australia, CSIRO, Canberra, ACT 2601, Australia; hermes.escalona@ 123456csiro.au (H.E.E.); Adam.Slipinski@ 123456csiro.au (A.Ś.)
                [4 ]Center for Biodiversity Research, Department of Biological Sciences, University of Memphis, Memphis, TN 38152, USA; dmckenna@ 123456memphis.edu
                Author notes
                Article
                biology-10-00451
                10.3390/biology10060451
                8224040
                34063961
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                Categories
                Article

                Comments

                Comment on this article