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      De novo assembly and functional annotation of blood transcriptome of loggerhead turtle, and in silico characterization of peroxiredoxins and thioredoxins

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          Abstract

          The aim of this study was to generate and analyze the atlas of the loggerhead turtle blood transcriptome by RNA-seq, as well as identify and characterize thioredoxin (Tnxs) and peroxiredoxin (Prdxs) antioxidant enzymes of the greatest interest in the control of peroxide levels and other biological functions. The transcriptome of loggerhead turtle was sequenced using the Illumina Hiseq 2000 platform and de novo assembly was performed using the Trinity pipeline. The assembly comprised 515,597 contigs with an N50 of 2,631 bp. Contigs were analyzed with CD-Hit obtaining 374,545 unigenes, of which 165,676 had ORFs encoding putative proteins longer than 100 amino acids. A total of 52,147 (31.5%) of these transcripts had significant homology matches in at least one of the five databases used. From the enrichment of GO terms, 180 proteins with antioxidant activity were identified, among these 28 Prdxs and 50 putative Tnxs. The putative proteins of loggerhead turtles encoded by the genes Prdx1, Prdx3, Prdx5, Prdx6, Txn and Txnip were predicted and characterized in silico. When comparing Prdxs and Txns of loggerhead turtle with homologous human proteins, they showed 18 (9%), 52 (18%) 94 (43%), 36 (16%), 35 (33%) and 74 (19%) amino acid mutations respectively. However, they showed high conservation in active sites and structural motifs (98%), with few specific modifications. Of these, Prdx1, Prdx3, Prdx5, Prdx6, Txn and Txnip presented 0, 25, 18, three, six and two deleterious changes. This study provides a high quality blood transcriptome and functional annotation of loggerhead sea turtles.

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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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            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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              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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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                18 November 2021
                2021
                : 9
                : e12395
                Affiliations
                [1 ]Department of Natural and Environmental Sciences, Faculty of Science and Engineering, Genetics, Molecular Biology and Bioinformatic Research Group—GENBIMOL, Universidad Jorge Tadeo Lozano , Bogotá, D.C., Colombia
                [2 ]Faculty of Sciences, Department of Biology, Pontificia Universidad Javeriana , Bogotá, D.C., Colombia
                [3 ]Grupo de Bioinformática y Biología de Sistemas, Universidad Nacional de Colombia , Bogotá, Colombia
                [4 ]Institute of Environmental Studies and Services. IDEASA Research Group—IDEASA, Sergio Arboleda University , Bogotá, D.C., Colombia
                [5 ]Molecular Biology CORE (CDB), Hospital Clínic de Barcelona , Barcelona, Spain
                [6 ]Evolutionary Genomics Group, Research Program on Biomedical Informatics (GRIB), Hospital del Mar Research Institute (IMIM), Universitat Pompeu Fabra , Barcelona, Spain
                [7 ]Catalan Institution for Research and Advanced Studies (ICREA) , Barcelona, Spain
                [8 ]Computational Biology Branch, NCBI, NLM, NIH , Bethesda, MD, United States of America
                Article
                12395
                10.7717/peerj.12395
                8606161
                69cbf37c-d9f7-4967-8552-7bd272c5c075
                ©2021 Hernández-Fernández 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
                : 14 January 2021
                : 6 October 2021
                Funding
                Funded by: The Office of Research, Creation and Innovation of the Universidad Jorge Tadeo Lozano (Project 340-07-10)
                Award ID: No. 12201530
                This work was supported by the Office of Research, Creation and Innovation of the Universidad Jorge Tadeo Lozano, No. 12201530 (Project 340-07-10). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Bioinformatics
                Genomics
                Marine Biology
                Molecular Biology
                Ecotoxicology

                caretta caretta,transcriptome,peroxiredoxin,thioredoxin,kegg pathway,blood,rna-seq,3d modelling

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