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      De novo transcriptome based on next-generation sequencing reveals candidate genes with sex-specific expression in Arapaima gigas (Schinz, 1822), an ancient Amazonian freshwater fish

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          Abstract

          Background

          The Arapaima ( Arapaima gigas) is one of the world's largest freshwater bony fish, and is found in the rivers of the Amazon basin. This species is a potential aquaculture resource, although reproductive management in captivity is limited in particular due to the lack of external sexual dimorphism. In this study, using the 454 Roche platform (pyrosequencing) techniques, we evaluated a major portion of the transcriptome of this important Amazonian species.

          Results

          Four libraries obtained from the liver and skin tissue of juvenile specimens (representing males and females separately) were sequenced, yielding 5,453,919 high-quality reads. The de novo transcriptome assembly resulted in 175,792 contigs, with 51,057 significant blast hits. A total of 38,586 transcripts were mapped by Gene Ontology using Blast2GO. We identified 20,219 genes in the total transcriptome (9,551 in the liver and 16,818 in the skin). The gene expression analyses indicated 105 genes in the liver and 204 in the skin with differentiated expression profiles, with 95 being over-expressed in the females and 214 in the males. The log2 Fold Change and heatmap based on Reads Per Kilobase per Million mapped reads (RPKM) revealed that the gene expression in the skin is highly differentiated between male and female arapaima, while the levels of expression in the liver are similar between the sexes.

          Conclusion

          Transcriptome analysis based on pyrosequencing proved to be a reliable tool for the identification of genes with differentiated expression profiles between male and female arapaima. These results provide useful insights into the molecular pathways of sexual dimorphism in this important Amazonian species, and for comparative analyses with other teleosts.

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          Most cited references72

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            Assembly algorithms for next-generation sequencing data.

            The emergence of next-generation sequencing platforms led to resurgence of research in whole-genome shotgun assembly algorithms and software. DNA sequencing data from the Roche 454, Illumina/Solexa, and ABI SOLiD platforms typically present shorter read lengths, higher coverage, and different error profiles compared with Sanger sequencing data. Since 2005, several assembly software packages have been created or revised specifically for de novo assembly of next-generation sequencing data. This review summarizes and compares the published descriptions of packages named SSAKE, SHARCGS, VCAKE, Newbler, Celera Assembler, Euler, Velvet, ABySS, AllPaths, and SOAPdenovo. More generally, it compares the two standard methods known as the de Bruijn graph approach and the overlap/layout/consensus approach to assembly. Copyright 2010 Elsevier Inc. All rights reserved.
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              The evolutionary dynamics of repetitive DNA in eukaryotes.

              Repetitive DNA sequences form a large portion of the genomes of eukaryotes. The 'selfish DNA' hypothesis proposes that they are maintained by their ability to replicate within the genome. The behaviour of repetitive sequences can result in mutations that cause genetic diseases, and confer significant fitness losses on the organism. Features of the organization of repetitive sequences in eukaryotic genomes, and their distribution in natural populations, reflect the evolutionary forces acting on selfish DNA.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: SupervisionRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: MethodologyRole: Visualization
                Role: Data curationRole: Formal analysisRole: Funding acquisitionRole: Methodology
                Role: Funding acquisitionRole: Methodology
                Role: Data curationRole: Formal analysisRole: MethodologyRole: Software
                Role: Methodology
                Role: Funding acquisition
                Role: ConceptualizationRole: Funding acquisitionRole: Project administrationRole: Supervision
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                29 October 2018
                2018
                : 13
                : 10
                : e0206379
                Affiliations
                [1 ] Laboratório de Genética e Biologia Molecular, Instituto de Estudos Costeiros (IECOS), Universidade Federal do Pará, Campus de Bragança, Pará, Brazil
                [2 ] Centro de Inovações Tecnológicas (CIT), Instituto Evandro Chagas (IEC), Ananindeua, Pará, Brazil
                Ohio State University, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-3349-5508
                Article
                PONE-D-18-07622
                10.1371/journal.pone.0206379
                6205615
                30372461
                60763e05-10bc-48e6-a551-23e561f8948a
                © 2018 Watanabe et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 March 2018
                : 11 October 2018
                Page count
                Figures: 3, Tables: 2, Pages: 22
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100003593, Conselho Nacional de Desenvolvimento Científico e Tecnológico;
                Award ID: 550939/2010-5
                Award Recipient :
                The study was funded by the Center of Technological Innovation (CIT), Evandro Chagas Institute (IEC) and National Council of Scientific and Technological Development (CNPq) (Bionorte Project: 550939/2010-5). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Genetics
                Gene Expression
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Transcriptome Analysis
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Transcriptome Analysis
                Medicine and Health Sciences
                Oncology
                Cancers and Neoplasms
                Skin Tumors
                Medicine and Health Sciences
                Dermatology
                Skin Neoplasms
                Skin Tumors
                Medicine and Health Sciences
                Gastroenterology and Hepatology
                Liver Diseases
                Fatty Liver
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Gene Ontologies
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Gene Ontologies
                Biology and Life Sciences
                Anatomy
                Liver
                Medicine and Health Sciences
                Anatomy
                Liver
                Biology and Life Sciences
                Biochemistry
                Proteins
                Serum Proteins
                Biology and Life Sciences
                Cell Biology
                Cellular Structures and Organelles
                Cell Membranes
                Membrane Proteins
                Custom metadata
                All relevant data are within the paper and its Supporting Information files. Raw reads data that support the findings of this study are available in the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) database: (Bioproject: PRJNA353913/ Acession number: SRX2375194, SRX2375196, SRX2375197, and SRX2375191.

                Uncategorized
                Uncategorized

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