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      An integrative phylogenomic approach to elucidate the evolutionary history and divergence times of Neuropterida (Insecta: Holometabola)

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          Abstract

          Background

          The latest advancements in DNA sequencing technologies have facilitated the resolution of the phylogeny of insects, yet parts of the tree of Holometabola remain unresolved. The phylogeny of Neuropterida has been extensively studied, but no strong consensus exists concerning the phylogenetic relationships within the order Neuroptera. Here, we assembled a novel transcriptomic dataset to address previously unresolved issues in the phylogeny of Neuropterida and to infer divergence times within the group. We tested the robustness of our phylogenetic estimates by comparing summary coalescent and concatenation-based phylogenetic approaches and by employing different quartet-based measures of phylogenomic incongruence, combined with data permutations.

          Results

          Our results suggest that the order Raphidioptera is sister to Neuroptera + Megaloptera. Coniopterygidae is inferred as sister to all remaining neuropteran families suggesting that larval cryptonephry could be a ground plan feature of Neuroptera. A clade that includes Nevrorthidae, Osmylidae, and Sisyridae (i.e. Osmyloidea) is inferred as sister to all other Neuroptera except Coniopterygidae, and Dilaridae is placed as sister to all remaining neuropteran families. Ithonidae is inferred as the sister group of monophyletic Myrmeleontiformia. The phylogenetic affinities of Chrysopidae and Hemerobiidae were dependent on the data type analyzed, and quartet-based analyses showed only weak support for the placement of Hemerobiidae as sister to Ithonidae + Myrmeleontiformia. Our molecular dating analyses suggest that most families of Neuropterida started to diversify in the Jurassic and our ancestral character state reconstructions suggest a primarily terrestrial environment of the larvae of Neuropterida and Neuroptera.

          Conclusion

          Our extensive phylogenomic analyses consolidate several key aspects in the backbone phylogeny of Neuropterida, such as the basal placement of Coniopterygidae within Neuroptera and the monophyly of Osmyloidea. Furthermore, they provide new insights into the timing of diversification of Neuropterida. Despite the vast amount of analyzed molecular data, we found that certain nodes in the tree of Neuroptera are not robustly resolved. Therefore, we emphasize the importance of integrating the results of morphological analyses with those of sequence-based phylogenomics. We also suggest that comparative analyses of genomic meta-characters should be incorporated into future phylogenomic studies of Neuropterida.

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          ModelFinder: Fast Model Selection for Accurate Phylogenetic Estimates

          Model-based molecular phylogenetics plays an important role in comparisons of genomic data, and model selection is a key step in all such analyses. We present ModelFinder, a fast model-selection method that greatly improves the accuracy of phylogenetic estimates. The improvement is achieved by incorporating a model of rate-heterogeneity across sites not previously considered in this context, and by allowing concurrent searches of model-space and tree-space.
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            ETE 3: Reconstruction, Analysis, and Visualization of Phylogenomic Data

            The Environment for Tree Exploration (ETE) is a computational framework that simplifies the reconstruction, analysis, and visualization of phylogenetic trees and multiple sequence alignments. Here, we present ETE v3, featuring numerous improvements in the underlying library of methods, and providing a novel set of standalone tools to perform common tasks in comparative genomics and phylogenetics. The new features include (i) building gene-based and supermatrix-based phylogenies using a single command, (ii) testing and visualizing evolutionary models, (iii) calculating distances between trees of different size or including duplications, and (iv) providing seamless integration with the NCBI taxonomy database. ETE is freely available at http://etetoolkit.org
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              The genome of the model beetle and pest Tribolium castaneum.

              Tribolium castaneum is a member of the most species-rich eukaryotic order, a powerful model organism for the study of generalized insect development, and an important pest of stored agricultural products. We describe its genome sequence here. This omnivorous beetle has evolved the ability to interact with a diverse chemical environment, as shown by large expansions in odorant and gustatory receptors, as well as P450 and other detoxification enzymes. Development in Tribolium is more representative of other insects than is Drosophila, a fact reflected in gene content and function. For example, Tribolium has retained more ancestral genes involved in cell-cell communication than Drosophila, some being expressed in the growth zone crucial for axial elongation in short-germ development. Systemic RNA interference in T. castaneum functions differently from that in Caenorhabditis elegans, but nevertheless offers similar power for the elucidation of gene function and identification of targets for selective insect control.
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                Author and article information

                Contributors
                alexvasilikop@gmail.com
                b.misof@leibniz-zfmk.de
                Journal
                BMC Evol Biol
                BMC Evol. Biol
                BMC Evolutionary Biology
                BioMed Central (London )
                1471-2148
                3 June 2020
                3 June 2020
                2020
                : 20
                : 64
                Affiliations
                [1 ]GRID grid.452935.c, ISNI 0000 0001 2216 5875, Centre for Molecular Biodiversity Research, , Zoological Research Museum Alexander Koenig, ; 53113 Bonn, Germany
                [2 ]GRID grid.5963.9, Department of Evolutionary Biology and Ecology, , Institute of Biology I (Zoology), Albert-Ludwigs-Universität Freiburg, ; 79104 Freiburg, Germany
                [3 ]GRID grid.1016.6, Australian National Insect Collection, National Research Collections Australia, , Commonwealth Scientific and Industrial Research Organisation (CSIRO), ; Canberra, ACT 2601 Australia
                [4 ]GRID grid.83440.3b, ISNI 0000000121901201, Department of Genetics, Evolution and Environment, , University College London, ; London, WC1E 6BT UK
                [5 ]GRID grid.9613.d, ISNI 0000 0001 1939 2794, Institut für Zoologie und Evolutionsforschung, , Friedrich-Schiller-Universität Jena, ; 07743 Jena, Germany
                [6 ]GRID grid.462257.0, ISNI 0000 0004 0493 4732, Natural History Department, , Hessisches Landesmuseum Darmstadt, ; 64283 Darmstadt, Germany
                [7 ]GRID grid.10388.32, ISNI 0000 0001 2240 3300, Steinmann-Institut für Geologie, Mineralogie und Paläontologie, , Rheinische Friedrich-Wilhelms-Universität Bonn, ; 53115 Bonn, Germany
                [8 ]GRID grid.452935.c, ISNI 0000 0001 2216 5875, Centre for Taxonomy and Evolutionary Research, Arthropoda Department, , Zoological Research Museum Alexander Koenig, ; 53113 Bonn, Germany
                [9 ]GRID grid.10420.37, ISNI 0000 0001 2286 1424, Department of Evolutionary Biology, , University of Vienna, ; 1090 Vienna, Austria
                [10 ]GRID grid.22935.3f, ISNI 0000 0004 0530 8290, Department of Entomology, , China Agricultural University, ; 100193 Beijing, People’s Republic of China
                [11 ]LOEWE Centre for Translational Biodiversity Genomics (LOEWE-TBG), 60325 Frankfurt, Germany
                [12 ]GRID grid.7872.a, ISNI 0000000123318773, School of Biological, Earth and Environmental Sciences, , University College Cork, ; Distillery Fields, North Mall, T23 N73K Cork, Ireland
                [13 ]GRID grid.22937.3d, ISNI 0000 0000 9259 8492, Institute of Specific Prophylaxis and Tropical Medicine, Medical Parasitology, , Medical University of Vienna (MUW), ; 1090 Vienna, Austria
                [14 ]GRID grid.425585.b, ISNI 0000 0001 2259 6528, Zoological Department II, , Natural History Museum of Vienna, ; 1010 Vienna, Austria
                Author information
                http://orcid.org/0000-0002-2579-0112
                https://orcid.org/0000-0003-4253-1849
                Article
                1631
                10.1186/s12862-020-01631-6
                7268685
                32493355
                529bd8c4-86d2-4782-b0e7-2474109a5537
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

                History
                : 22 October 2019
                : 19 May 2020
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001809, National Natural Science Foundation of China;
                Award ID: 31972871
                Award ID: 31672322
                Award Recipient :
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2020

                Evolutionary Biology
                megaloptera,neuroptera,raphidioptera,endopterygota,transcriptomics,rna-seq,multi-species coalescent,supermatrices,four-cluster likelihood mapping

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