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      Mitochondrial genomes of twelve species of hyperdiverse Trigonopterus weevils

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          Abstract

          Mitochondrial genomes of twelve species of Trigonopterus weevils are presented, ten of them complete. We describe their gene order and molecular features and test their potential for reconstructing the phylogeny of this hyperdiverse genus comprising > 1,000 species. The complete mitochondrial genomes examined herein ranged from 16,501 bp to 21,007 bp in length, with an average AT content of 64.2% to 69.7%. Composition frequencies and skews were generally lower across species for atp6, cox1-3, and cob genes, while atp8 and genes coded on the minus strand showed much higher divergence at both nucleotide and amino acid levels. Most variation within genes was found at the codon level with high variation at third codon sites across species, and with lesser degree at the coding strand level. Two large non-coding regions were found, CR1 (between rrnS and trnI genes) and CR2 (between trnI and trnQ), but both with large variability in length; this peculiar structure of the non-coding region may be a derived character of Curculionoidea. The nad1 and cob genes exhibited an unusually high interspecific length variation of up to 24 bp near the 3′ end. This pattern was probably caused by a single evolutionary event since both genes are only separated by trnS2 and length variation is extremely rare in mitochondrial protein coding genes. We inferred phylogenetic trees using protein coding gene sequences implementing both maximum likelihood and Bayesian approaches, each for both nucleotide and amino acid sequences. While some clades could be retrieved from all reconstructions with high confidence, there were also a number of differences and relatively low support for some basal nodes. The best partition scheme of the 13 protein coding sequences obtained by IQTREE suggested that phylogenetic signal is more accurate by splitting sequence variation at the codon site level as well as coding strand, rather than at the gene level. This result corroborated the different patterns found in Trigonopterus regarding to A+T frequencies and AT and GC skews that also greatly diverge at the codon site and coding strand levels.

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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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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              MUSCLE: multiple sequence alignment with high accuracy and high throughput.

              We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                peerj
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                13 October 2020
                2020
                : 8
                : e10017
                Affiliations
                [1 ]State Museum of Natural History Karlsruhe , Karlsruhe, Germany
                [2 ]Museum Zoologicum Bogoriense, Research Center for Biology, Indonesian Institute of Sciences (LIPI) , Cibinong, Indonesia
                [3 ]Diversidad Animal y Microbiana, Instituto Mediterráneo de Estudios Avanzados IMEDEA (CSIC-UIB) , Esporles, Balearic Islands, Spain
                Article
                10017
                10.7717/peerj.10017
                7566755
                33083123
                3603e02c-9c7d-4c99-a7ef-1c8644180f25
                ©2020 Narakusumo et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits using, remixing, and building upon the work non-commercially, as long as it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 24 April 2020
                : 1 September 2020
                Funding
                Funded by: The German Academic Exchange Service DAAD
                Award ID: 91654661
                Funded by: The German Research Foundation DFG
                Award ID: RI 1817/3-4
                Funded by: DIPA KSK Pengembangan Database KEHATI PDII LIPI 2018
                Funded by: LIPI and UC Berkeley (NSF Award)
                Award ID: #1457845
                This work was funded by the German Academic Exchange Service DAAD (91654661 to Raden P. Narakusumo), and the German Research Foundation DFG (RI 1817/3-4 to Alexander Riedel). Part of the fieldwork for this study was funded by DIPA KSK Pengembangan Database KEHATI PDII LIPI 2018 and the collaborative project between LIPI and UC Berkeley (NSF Award #1457845). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Entomology
                Genomics
                Zoology

                cryptorhynchinae,curculionidae,mitochondrial genomes,next generation sequencing,phylogenetic analysis

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