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Integration of RNAi and RNA-seq Reveals the Immune Responses of Epinephelus coioides to sigX Gene of Pseudomonas plecoglossicida

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      Abstract

      Pseudomonas plecoglossicida is an important pathogen for aquaculture and causes high mortality in various marine fishes. Expression of sigX was found significantly up-regulated at 18°C than at 28°C, which was verified by quantitative real-time PCR (qRT-PCR). RNAi significantly reduced the content of sigX mRNA of P. plecoglossicida, whether in in vitro or in the spleen at all sampling time points. Compared with the wild-type strain, the infection of sigX-RNAi strain resulted in the onset time delay, and 20% reduction in mortality of Epinephelus coioides, as well as alleviates in the symptoms of E. coioides spleen. Compared with wild-type strain, the gene silence of sigX in P. plecoglossicida resulted in a significant change in transcriptome of infected E. coioides. The result of gene ontology and KEGG analysis on E. coioides showed that genes of serine-type endopeptidase and chemokine signaling pathway, coagulation and complement system, and intestinal immune network for IgA production pathway were mostly affected by sigX of P. plecoglossicida. Meanwhile, the immune genes were associated with different number of miRNA and lncRNA, and some miRNAs were associated with more than one gene at the same time. The results indicated that sigX was a virulent gene of P. plecoglossicida. The up-regulation of the immune pathways made E. coioides more likely to kill sigX-RNAi strain than the wild-type strain of P. plecoglossicida, while the immune genes were regulated by miRNA and lncRNA by a complex mode.

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      Fast gapped-read alignment with Bowtie 2.

      As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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        edgeR: a Bioconductor package for differential expression analysis of digital gene expression data

        Summary: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. Availability: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org). Contact: mrobinson@wehi.edu.au
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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            Author and article information

            Affiliations
            1Fisheries College, Key Laboratory of Healthy Mariculture for the East China Sea, Ministry of Agriculture, Jimei University , Xiamen, China
            2State Key Laboratory of Large Yellow Croaker Breeding , Ningde, China
            Author notes

            Edited by: Gerardo R. Vasta, University of Maryland, Baltimore, United States

            Reviewed by: Hai-peng Liu, Xiamen University, China; Hao-Ching Wang, Taipei Medical University, Taiwan

            *Correspondence: Qingpi Yan, yanqp@ 123456jmu.edu.cn

            Specialty section: This article was submitted to Comparative Immunology, a section of the journal Frontiers in Immunology

            Contributors
            Journal
            Front Immunol
            Front Immunol
            Front. Immunol.
            Frontiers in Immunology
            Frontiers Media S.A.
            1664-3224
            16 July 2018
            2018
            : 9
            6054955
            10.3389/fimmu.2018.01624
            Copyright © 2018 Sun, Luo, Zhao, Huang, Qin, Su and Yan.

            This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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            Figures: 5, Tables: 0, Equations: 0, References: 40, Pages: 11, Words: 6169
            Categories
            Immunology
            Original Research

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