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Transcriptome Analysis of the Innate Immunity-Related Complement System in Spleen Tissue of Ctenopharyngodon idella Infected with Aeromonas hydrophila

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      Abstract

      The grass carp ( Ctenopharyngodon idella) is an important commercial farmed herbivorous fish species in China, but is susceptible to Aeromonas hydrophila infections. In the present study, we performed de novo RNA-Seq sequencing of spleen tissue from specimens of a disease-resistant family, which were given intra-peritoneal injections containing PBS with or without a dose of A. hydrophila. The fish were sampled from the control group at 0 h, and from the experimental group at 4, 8, 12, 24, 48 and 72 h. 122.18 million clean reads were obtained from the normalized cDNA libraries; these were assembled into 425,260 contigs and then 191,795 transcripts. Of those, 52,668 transcripts were annotated with the NCBI Nr database, and 41,347 of the annotated transcripts were assigned into 90 functional groups. 20,569 unigenes were classified into six main categories, including 38 secondary KEGG pathways. 2,992 unigenes were used in the analysis of differentially expressed genes (DEGs). 89 of the putative DEGs were related to the immune system and 41 of them were involved in the complement and coagulation cascades pathway. This study provides insights into the complement and complement-related pathways involved in innate immunity, through expression profile analysis of the genomic resources in C. idella. We conclude that complement and complement-related genes play important roles during defense against A. hydrophila infection. The immune response is activated at 4 h after the bacterial injections, indicating that the complement pathways are activated at the early stage of bacterial infection. The study has improved our understanding of the immune response mechanisms in C. idella to bacterial pathogens.

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      Most cited references 42

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      Mapping and quantifying mammalian transcriptomes by RNA-Seq.

      We have mapped and quantified mouse transcriptomes by deeply sequencing them and recording how frequently each gene is represented in the sequence sample (RNA-Seq). This provides a digital measure of the presence and prevalence of transcripts from known and previously unknown genes. We report reference measurements composed of 41-52 million mapped 25-base-pair reads for poly(A)-selected RNA from adult mouse brain, liver and skeletal muscle tissues. We used RNA standards to quantify transcript prevalence and to test the linear range of transcript detection, which spanned five orders of magnitude. Although >90% of uniquely mapped reads fell within known exons, the remaining data suggest new and revised gene models, including changed or additional promoters, exons and 3' untranscribed regions, as well as new candidate microRNA precursors. RNA splice events, which are not readily measured by standard gene expression microarray or serial analysis of gene expression methods, were detected directly by mapping splice-crossing sequence reads. We observed 1.45 x 10(5) distinct splices, and alternative splices were prominent, with 3,500 different genes expressing one or more alternate internal splices.
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        Velvet: algorithms for de novo short read assembly using de Bruijn graphs.

        We have developed a new set of algorithms, collectively called "Velvet," to manipulate de Bruijn graphs for genomic sequence assembly. A de Bruijn graph is a compact representation based on short words (k-mers) that is ideal for high coverage, very short read (25-50 bp) data sets. Applying Velvet to very short reads and paired-ends information only, one can produce contigs of significant length, up to 50-kb N50 length in simulations of prokaryotic data and 3-kb N50 on simulated mammalian BACs. When applied to real Solexa data sets without read pairs, Velvet generated contigs of approximately 8 kb in a prokaryote and 2 kb in a mammalian BAC, in close agreement with our simulated results without read-pair information. Velvet represents a new approach to assembly that can leverage very short reads in combination with read pairs to produce useful assemblies.
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          Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research.

          We present here Blast2GO (B2G), a research tool designed with the main purpose of enabling Gene Ontology (GO) based data mining on sequence data for which no GO annotation is yet available. B2G joints in one application GO annotation based on similarity searches with statistical analysis and highlighted visualization on directed acyclic graphs. This tool offers a suitable platform for functional genomics research in non-model species. B2G is an intuitive and interactive desktop application that allows monitoring and comprehension of the whole annotation and analysis process. Blast2GO is freely available via Java Web Start at http://www.blast2go.de. http://www.blast2go.de -> Evaluation.
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            Author and article information

            Affiliations
            [1 ]Key Laboratory of Exploration and Utilization of Aquatic Genetic Resources, Shanghai Ocean University, Ministry of Education, Shanghai 201306, PR China
            [2 ]National Pathogen Collection Center for Aquatic Animals, College of Fisheries and Life Science, Shanghai Ocean University, 999 Huchenghuan Road, Shanghai 201306, PR China
            Chinese Academy of Fishery Sciences, CHINA
            Author notes

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

            Conceived and designed the experiments: YFD JLL LQL. Performed the experiments: YFD XYX. Analyzed the data: YFD. Contributed reagents/materials/analysis tools: YFD YBS MYH MZ LSL. Wrote the paper: YFD JLL.

            Contributors
            Role: Editor
            Journal
            PLoS One
            PLoS ONE
            plos
            plosone
            PLoS ONE
            Public Library of Science (San Francisco, CA USA )
            1932-6203
            6 July 2016
            2016
            : 11
            : 7
            27383749
            4934786
            10.1371/journal.pone.0157413
            PONE-D-16-13569
            (Editor)
            © 2016 Dang 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.

            Counts
            Figures: 9, Tables: 5, Pages: 22
            Product
            Funding
            Funded by: The China's Agricultural Reseach System
            Award ID: CARS-46-04
            Award Recipient :
            Funded by: The National Key Technology R and D Program of China
            Award ID: 2012BAD26B02
            Award Recipient :
            The work was supported by the following: the China's Agricultural Research System (CARS-46-04), Jiale Li; and the National Key Technology R&D Program of China (2012BAD26B02), Jiale Li.
            Categories
            Research Article
            Biology and Life Sciences
            Physiology
            Immune Physiology
            Complement System
            Medicine and Health Sciences
            Physiology
            Immune Physiology
            Complement System
            Biology and Life Sciences
            Immunology
            Immune System
            Complement System
            Medicine and Health Sciences
            Immunology
            Immune System
            Complement System
            Biology and Life Sciences
            Immunology
            Immune System Proteins
            Complement System
            Medicine and Health Sciences
            Immunology
            Immune System Proteins
            Complement System
            Biology and Life Sciences
            Biochemistry
            Proteins
            Immune System Proteins
            Complement System
            Biology and Life Sciences
            Immunology
            Immune System
            Medicine and Health Sciences
            Immunology
            Immune System
            Biology and Life Sciences
            Organisms
            Bacteria
            Aeromonas
            Aeromonas Hydrophila
            Biology and Life Sciences
            Microbiology
            Medical Microbiology
            Microbial Pathogens
            Bacterial Pathogens
            Aeromonas Hydrophila
            Medicine and Health Sciences
            Pathology and Laboratory Medicine
            Pathogens
            Microbial Pathogens
            Bacterial Pathogens
            Aeromonas Hydrophila
            Biology and Life Sciences
            Organisms
            Animals
            Vertebrates
            Fishes
            Osteichthyes
            Carps
            Biology and Life Sciences
            Genetics
            Gene Expression
            Biology and Life Sciences
            Organisms
            Plants
            Grasses
            Research and Analysis Methods
            Database and Informatics Methods
            Biological Databases
            Sequence Databases
            Biology and Life Sciences
            Molecular Biology
            Molecular Biology Techniques
            Sequencing Techniques
            Sequence Analysis
            Sequence Databases
            Research and Analysis Methods
            Molecular Biology Techniques
            Sequencing Techniques
            Sequence Analysis
            Sequence Databases
            Research and analysis methods
            Extraction techniques
            RNA extraction
            Custom metadata
            All transcriptome data files are available from the NCBI Sequence Read Archive database (accession number SRP060308).

            Uncategorized

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