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      Toward a Stable Global Noctuidae (Lepidoptera) Taxonomy

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          Abstract

          Noctuidae are one of the world’s most diverse, ecologically successful, and economically important animal lineages with over 12,000 species in ~1,150 genera. We inferred a phylogeny using eight protein-coding genes for the global fauna, greatly expanding upon previous attempts to stabilize Noctuidae higher classification by sampling 341 genera (nearly half represented by their type species) representing 70/76 widely recognized family-group taxa: 20/21 subfamilies, 32/35 tribes, and 18/20 subtribes. We evaluated 17 subfamily-level taxa in detail, discussing adult and larval morphology, life histories, and taxonomic implications of our results. We significantly alter concepts of Acontiinae, Condicinae, Eustrotiinae, Metoponiinae, and Stiriinae. Our results supported recognition of two new subfamilies: Cobubathinae Wagner & Keegan, 2021 subf. nov. and Cropiinae Keegan & Wagner, 2021 subf. nov. Other nomenclatural changes we made are as follows. We moved: ‘Acontia’ viridifera (Hampson, 1910), ‘Azenia’ virida Barnes and McDunnough, 1916, Aleptinoides, Austrazenia, Chalcoecia, Megalodes, and Trogotorna to Chamaecleini in Acontiinae; Apaustis to, and reinstated Emmelia as a valid genus in Acontiinae; Allophyes and Meganephria to Cuculliinae; ‘Plagiomimicus’ navia (Harvey, 1875), Airamia, Alvaradoia, Hypoperigea, Neotarache, and Mesotrosta to Condicinae; Axenus, Azenia, Metaponpneumata, Sexserrata, and Tristyla to Metoponiinae; ‘Paramiana’ canoa (Barnes, 1907) to Noctuinae; Aucha, Cobubatha, and Tripudia to Cobubathinae; Anycteola and Supralathosea to Oncocnemidinae; Cropia to Cropiinae; Desmoloma to Dyopsinae; Eviridemas and Gloanna to Bryophilinae; Fota and Stilbia to Stiriinae; and Copibryophila, Homolagoa, and Tyta to Noctuidae incertae sedis. We conclude with discussion of instances where current understanding of noctuid biogeography and life histories were changed by our results.

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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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            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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              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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                Author and article information

                Contributors
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                Journal
                Insect Systematics and Diversity
                Oxford University Press (OUP)
                2399-3421
                May 01 2021
                May 01 2021
                May 01 2021
                May 01 2021
                May 03 2021
                : 5
                : 3
                Affiliations
                [1 ]Department of Ecology and Evolutionary Biology, University of Connecticut, 75 N. Eagleville Road, Unit 3043, Storrs, CT 06269-3043, USA
                [2 ]Department of Biology, Lund University, Sölvegatan 37, 223 62 Lund, Sweden
                [3 ]Centrum für Naturkunde (CeNak), Hamburg University, Martin-Luther-King-Platz 3, 20146, Hamburg, Germany
                [4 ]Canadian Food Inspection Agency, Ottawa Plant Laboratory, Entomology Laboratory, Building 18, 960 Carling Avenue, Ottawa, ON K1A 0C6, Canada
                [5 ]Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD, UK
                [6 ]Canadian National Collection of Insects, Arachnids and Nematodes, Agriculture and Agri-Food Canada, K.W. Neatby Bldg., 960 Carling Avenue, Ottawa, ON K1A 0C6, Canada
                [7 ]Systematic Entomology Laboratory, USDA-ARS, National Museum of Natural History, 10th Street and Constitution Avenue, NW Washington, DC 20560, USA
                Article
                10.1093/isd/ixab005
                16d0d022-14d2-4fe2-8ad3-702f2a9381e8
                © 2021

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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