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      A Mitochondrial Genome Phylogeny of Cleridae (Coleoptera, Cleroidea)

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      Insects
      MDPI AG

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          Abstract

          The predaceous beetle family Cleridae includes a large and widely distributed rapid radiation, which is vital for the ecosystem. Despite its important role, a number of problems remain to be solved regarding the phylogenetic inter-relationships, the timing of divergence, and the mitochondrial biology. Mitochondrial genomes have been widely used to reconstruct phylogenies of various insect groups, but never introduced to Cleridae until now. Here, we generated 18 mitochondrial genomes to address these issues, which are all novel to the family. In addition to phylogenomic analysis, we have leveraged our new sources to study the mitochondrial biology in terms of nucleotide composition, codon usage and substitutional rate, to understand how these vital cellular components may have contributed to the divergence of the Cleridae. Our results recovered Korynetinae sister to the remaining clerids, and the calde of Clerinae+Hydnocerinae is indicated more related to Tillinae. A time-calibrated phylogeny estimated the earliest divergence time of Cleridae was soon after the origin of the family, not later than 160.18 Mya (95% HPD: 158.18–162.07 Mya) during the mid-Jurassic. This is the first mitochondrial genome-based phylogenetic study of the Cleridae that covers nearly all subfamily members, which provides an alternative evidence for reconstructing the phylogenetic relationships.

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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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            MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

            We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.
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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
                Journal
                Insects
                Insects
                MDPI AG
                2075-4450
                February 2022
                January 24 2022
                : 13
                : 2
                : 118
                Article
                10.3390/insects13020118
                35206692
                e40fa91d-fd45-4ae3-8a2f-470179370e8f
                © 2022

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

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