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      Evaluating DNA Barcoding for Species Identification and Discovery in European Gracillariid Moths

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          Abstract

          Gracillariidae is the most species-rich leaf-mining moth family with over 2,000 described species worldwide. In Europe, there are 263 valid named species recognized, many of which are difficult to identify using morphology only. Here we explore the use of DNA barcodes as a tool for identification and species discovery in European gracillariids. We present a barcode library including 6,791 COI sequences representing 242 of the 263 (92%) resident species. Our results indicate high congruence between morphology and barcodes with 91.3% (221/242) of European species forming monophyletic clades that can be identified accurately using barcodes alone. The remaining 8.7% represent cases of non-monophyly making their identification uncertain using barcodes. Species discrimination based on the Barcode Index Number system (BIN) was successful for 93% of species with 7% of species sharing BINs. We discovered as many as 21 undescribed candidate species, of which six were confirmed from an integrative approach; the other 15 require additional material and study to confirm preliminary evidence. Most of these new candidate species are found in mountainous regions of Mediterranean countries, the South-Eastern Alps and the Balkans, with nine candidate species found only on islands. In addition, 13 species were classified as deep conspecific lineages, comprising a total of 27 BINs with no intraspecific morphological differences found, and no known ecological differentiation. Double-digest restriction-site associated DNA sequencing (ddRAD) analysis showed strong mitonuclear discrepancy in four out of five species studied. This discordance is not explained by Wolbachia-mediated genetic sweeps. Finally, 26 species were classified as “unassessed species splits” containing 71 BINs and some involving geographical isolation or ecological specialization that will require further study to test whether they represent new cryptic species.

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          MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

          The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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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 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

              Abstract IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.
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                Author and article information

                Journal
                Frontiers in Ecology and Evolution
                Front. Ecol. Evol.
                Frontiers Media SA
                2296-701X
                February 18 2021
                February 18 2021
                : 9
                Article
                10.3389/fevo.2021.626752
                2bd16937-f2a6-47c4-854f-b4acb8e98049
                © 2021

                Free to read

                https://creativecommons.org/licenses/by/4.0/

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