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      Comparative analysis of codon usage patterns and phylogenetic implications of five mitochondrial genomes of the genus Japanagallia Ishihara, 1955 (Hemiptera, Cicadellidae, Megophthalminae)

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          Abstract

          Japanagallia is a genus of Cicadomorpha in the family of leafhoppers that are plant piercing-sucking insects, and it is difficult to distinguish by morphological characteristics. So far, only one complete mitochondrial genome data has been reported for the genus Japanagallia. Therefore, in order to better understand this group, we assembled and annotated the complete mitochondrial genomes of five Japanagallia species, and analyzed their codon usage patterns. Nucleotide composition analysis showed that AT content was higher than GC content, and the protein-coding sequences preferred to end with A/T at the third codon position. Relative synonymous codon usage analysis revealed most over-represented codon ends with A or T. Parity plot analysis revealed the codon usage bias of mitochondrial genes was influenced by both natural selection and mutation pressure. In the neutrality plot, the slopes of regression lines were < 0.5, suggesting that natural selection was playing a major role while mutation pressure was of minor importance. The effective number of codons showed that the codon usage bias between genes and genomes was low. Correspondence analysis revealed that the codon usage pattern differed among 13 protein-coding genes. Phylogenetic analyses based on three datasets using two methods (maximum likelihood and Bayesian inference), restored the Megophthalminae monophyly with high support values (bootstrap support values (BS) = 100, Bayesian posterior probability (PP) = 1). In the obtained topology, the seven Japanagallia species were clustered into a monophyletic group and formed a sister group with Durgade. In conclusion, our study can provide a reference for the future research on organism evolution, identification and phylogeny relationships of Japanagallia species .

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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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            Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

            S Altschul (1997)
            The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSI-BLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.
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              Geneious Basic: An integrated and extendable desktop software platform for the organization and analysis of sequence data

              Summary: The two main functions of bioinformatics are the organization and analysis of biological data using computational resources. Geneious Basic has been designed to be an easy-to-use and flexible desktop software application framework for the organization and analysis of biological data, with a focus on molecular sequences and related data types. It integrates numerous industry-standard discovery analysis tools, with interactive visualizations to generate publication-ready images. One key contribution to researchers in the life sciences is the Geneious public application programming interface (API) that affords the ability to leverage the existing framework of the Geneious Basic software platform for virtually unlimited extension and customization. The result is an increase in the speed and quality of development of computation tools for the life sciences, due to the functionality and graphical user interface available to the developer through the public API. Geneious Basic represents an ideal platform for the bioinformatics community to leverage existing components and to integrate their own specific requirements for the discovery, analysis and visualization of biological data. Availability and implementation: Binaries and public API freely available for download at http://www.geneious.com/basic, implemented in Java and supported on Linux, Apple OSX and MS Windows. The software is also available from the Bio-Linux package repository at http://nebc.nerc.ac.uk/news/geneiousonbl. Contact: peter@biomatters.com
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                25 September 2023
                2023
                : 11
                : e16058
                Affiliations
                [1 ]Institute of Entomology, Guizhou University, The Provincial Key Laboratory for Agricultural Pest Management Mountainous Region , Guiyang, Guizhou, China
                [2 ]College of Biology and Food Engineering, Chuzhou University , Chuzhou, Anhui, China
                [3 ]Cellular and Molecular Life Sciences, Department of Biology , Brussels, Belgium
                [4 ]Laboratory of Agrozoology, Dep. of Crop Protection, Ghent University , Ghent, Belgium
                [5 ]Engineering Research Center of Medical Biotechnology, School of Biology and Engineering, Guizhou Medical University , Guiyang, Guizhou, China
                Article
                16058
                10.7717/peerj.16058
                10538298
                37780390
                39a41e9a-8d01-4efa-9b12-4c8d486c7949
                ©2023 Li et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that 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
                : 9 May 2023
                : 17 August 2023
                Funding
                Funded by: The National Natural Science Foundation of China
                Award ID: No. 32160119
                Funded by: The National Natural Science Foundation of China
                Award ID: No. 32000329
                Funded by: The Program of Excellent Innovation Talents, Guizhou Province, China
                Award ID: No. 20206003
                Funded by: Opening Foundation of Shaanxi University of Technology
                Award ID: SLGPT2019KF03-01
                This work was supported by the National Natural Science Foundation of China (No. 32160119); the National Natural Science Foundation of China (No. 32000329); the Program of Excellent Innovation Talents, Guizhou Province, China (No. 20206003); and the Opening Foundation of Shaanxi University of Technology (No. SLGPT2019KF03-01). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Agricultural Science
                Entomology
                Genomics
                Molecular Biology
                Zoology

                codon usage,evolution,japanagallia,mitogenome,phylogeny
                codon usage, evolution, japanagallia, mitogenome, phylogeny

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