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      Phylogenomics indicates Amazonia as the major source of Neotropical swarm-founding social wasp diversity

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          Abstract

          The Neotropical realm harbours unparalleled species richness and hence has challenged biologists to explain the cause of its high biotic diversity. Empirical studies to shed light on the processes underlying biological diversification in the Neotropics are focused mainly on vertebrates and plants, with little attention to the hyperdiverse insect fauna. Here, we use phylogenomic data from ultraconserved element (UCE) loci to reconstruct for the first time the evolutionary history of Neotropical swarm-founding social wasps (Hymenoptera, Vespidae, Epiponini). Using maximum likelihood, Bayesian, and species tree approaches we recovered a highly resolved phylogeny for epiponine wasps. Additionally, we estimated divergence dates, diversification rates, and the biogeographic history for these insects in order to test whether the group followed a ‘museum’ (speciation events occurred gradually over many millions of years) or ‘cradle’ (lineages evolved rapidly over a short time period) model of diversification. The origin of many genera and all sampled extant Epiponini species occurred during the Miocene and Plio-Pleistocene. Moreover, we detected no major shifts in the estimated diversification rate during the evolutionary history of Epiponini, suggesting a relatively gradual accumulation of lineages with low extinction rates. Several lines of evidence suggest that the Amazonian region played a major role in the evolution of Epiponini wasps. This spatio-temporal diversification pattern, most likely concurrent with climatic and landscape changes in the Neotropics during the Miocene and Pliocene, establishes the Amazonian region as the major source of Neotropical swarm-founding social wasp diversity.

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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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            MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

            We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.
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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
                (View ORCID Profile)
                (View ORCID Profile)
                Journal
                Proceedings of the Royal Society B: Biological Sciences
                Proc. R. Soc. B.
                The Royal Society
                0962-8452
                1471-2954
                June 10 2020
                June 03 2020
                June 10 2020
                : 287
                : 1928
                : 20200480
                Affiliations
                [1 ]Department of Entomology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20560-0188, USA
                [2 ]Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras - Universidade de São Paulo (FFCLRP/USP), Av. Bandeirantes, 3900, 14040-901 Ribeirão Preto, SP, Brazil
                [3 ]Computational Sciences, The Jackson Laboratory, 600 Main Street, Bar Harbor, ME 04609, USA
                Article
                10.1098/rspb.2020.0480
                0c78a716-03a2-4381-a19e-1cfed362ea50
                © 2020

                https://royalsociety.org/-/media/journals/author/Licence-to-Publish-20062019-final.pdf

                https://royalsociety.org/journals/ethics-policies/data-sharing-mining/

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