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      Key innovations and the diversification of Hymenoptera

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          Abstract

          The order Hymenoptera (wasps, ants, sawflies, and bees) represents one of the most diverse animal lineages, but whether specific key innovations have contributed to its diversification is still unknown. We assembled the largest time-calibrated phylogeny of Hymenoptera to date and investigated the origin and possible correlation of particular morphological and behavioral innovations with diversification in the order: the wasp waist of Apocrita; the stinger of Aculeata; parasitoidism, a specialized form of carnivory; and secondary phytophagy, a reversal to plant-feeding. Here, we show that parasitoidism has been the dominant strategy since the Late Triassic in Hymenoptera, but was not an immediate driver of diversification. Instead, transitions to secondary phytophagy (from parasitoidism) had a major influence on diversification rate in Hymenoptera. Support for the stinger and the wasp waist as key innovations remains equivocal, but these traits may have laid the anatomical and behavioral foundations for adaptations more directly associated with diversification.

          Abstract

          Hymenoptera is an incredibly diverse order, with numerous behavioral and morphological innovations. Here, the authors compile a time-calibrated Hymenoptera phylogeny and find that secondary transitions to phytophagy, plant feeding, are associated with significant increases in diversification rate in this group.

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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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            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%.
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              MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

              Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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                Author and article information

                Contributors
                bonnie.blaimer@mfn.berlin
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                3 March 2023
                3 March 2023
                2023
                : 14
                : 1212
                Affiliations
                [1 ]GRID grid.422371.1, ISNI 0000 0001 2293 9957, Museum für Naturkunde, Leibniz Institute for Evolution and Biodiversity Science, , Center for Integrative Biodiversity Discovery, ; Invalidenstraße 43, Berlin, 10115 Germany
                [2 ]GRID grid.1214.6, ISNI 0000 0000 8716 3312, National Museum of Natural History, , Smithsonian Institution, ; 10th & Constitution Ave. NW, Washington, DC USA
                [3 ]GRID grid.121334.6, ISNI 0000 0001 2097 0141, CBGP, INRAe, CIRAD, IRD, Montpellier SupAgro, , Université de Montpellier, ; Montpellier, France
                [4 ]GRID grid.1214.6, ISNI 0000 0000 8716 3312, Systematic Entomology Laboratory, USDA-ARS, c/o NMNH, , Smithsonian Institution, ; 10th & Constitution Ave. NW, Washington, DC USA
                [5 ]GRID grid.167436.1, ISNI 0000 0001 2192 7145, Department of Biological Sciences, , University of New Hampshire, ; Durham, NH USA
                [6 ]GRID grid.421466.3, ISNI 0000 0004 0627 8572, Florida State Collection of Arthropods, , Division of Plant Industry, Florida Department of Agriculture and Consumer Services, ; 1911 SW 34th St, Gainesville, FL 32608 USA
                Author information
                http://orcid.org/0000-0002-8961-9998
                http://orcid.org/0000-0002-2634-3066
                http://orcid.org/0000-0001-8932-4199
                http://orcid.org/0000-0002-5760-1371
                http://orcid.org/0000-0002-1516-0360
                http://orcid.org/0000-0001-9719-0215
                http://orcid.org/0000-0001-8614-6665
                http://orcid.org/0000-0001-8502-9061
                http://orcid.org/0000-0002-1048-6345
                http://orcid.org/0000-0003-0468-940X
                http://orcid.org/0000-0003-1900-3861
                Article
                36868
                10.1038/s41467-023-36868-4
                9984522
                36869077
                54f8e632-5f0d-42b8-9fe3-ef243e2a3939
                © The Author(s) 2023

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 25 March 2022
                : 21 February 2023
                Funding
                Funded by: Smithsonian Institute for Biodiversity Genomics and Global Genome Initiative
                Funded by: Global Genome Initiative Peter Buck Postdoctoral Fellowship (Smithsonian Institution)
                Funded by: INRAe SPE department
                Funded by: FundRef https://doi.org/10.13039/100007917, United States Department of Agriculture | Agricultural Research Service (USDA Agricultural Research Service);
                Funded by: FundRef https://doi.org/10.13039/100011508, Florida Department of Agriculture and Consumer Services (FDACS);
                Funded by: FundRef https://doi.org/10.13039/100000001, National Science Foundation (NSF);
                Award ID: DEB-1555905
                Award Recipient :
                Categories
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                © The Author(s) 2023

                Uncategorized
                evolution,zoology,comparative genomics,phylogenomics
                Uncategorized
                evolution, zoology, comparative genomics, phylogenomics

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