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      Temporal changes in transcriptome profile provide insights of White Spot Syndrome Virus infection in Litopenaeus vannamei

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          Abstract

          Shrimp aquaculture is severely affected by WSSV. Despite an increasing effort to understand host/virus interaction by characterizing changes in gene expression (GE) following WSSV infection, the majority of published studies have focussed on a single time-point, providing limited insight on the development of host-pathogen interaction over the infection cycle. Using RNA-seq, we contrasted GE in gills of Litopenaeus vannamei at 1.5, 18 and 56 hours-post-infection (hpi), between WSSV-challenged and control shrimps. Time course analysis revealed 5097 differentially expressed genes: 63 DEGs were viral genes and their expression in WSSV group either peaked at 18 hpi (and decreased at 56 hpi) or increased linearly up to 56 hpi, suggesting a different role played by these genes during the course of infection. The remaining DEGs showed that WSSV altered the expression of metabolic, immune, apoptotic and cytoskeletal genes and was able to inhibit NF-κB and JAK/STAT pathways. Interestingly, GE changes were not consistent through the course of infection but were dynamic with time, suggesting the complexity of host-pathogen interaction. These data offer novel insights into the cellular functions that are affected during the course of infection and ultimately provide a valuable resource towards our understanding of the host-pathogen dynamics and its variation with time.

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          Next maSigPro: updating maSigPro bioconductor package for RNA-seq time series

          Motivation: The widespread adoption of RNA-seq to quantitatively measure gene expression has increased the scope of sequencing experimental designs to include time-course experiments. maSigPro is an R package specifically suited for the analysis of time-course gene expression data, which was developed originally for microarrays and hence was limited in its application to count data. Results: We have updated maSigPro to support RNA-seq time series analysis by introducing generalized linear models in the algorithm to support the modeling of count data while maintaining the traditional functionalities of the package. We show a good performance of the maSigPro-GLM method in several simulated time-course scenarios and in a real experimental dataset. Availability and implementation: The package is freely available under the LGPL license from the Bioconductor Web site (http://bioconductor.org). Contact: mj.nueda@ua.es or aconesa@cipf.es
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            Structure and mechanism of ABC transporter proteins.

            ATP-binding cassette (ABC) transporters are ubiquitous membrane proteins that couple the transport of diverse substrates across cellular membranes to the hydrolysis of ATP. The crystal structures of four ABC transporters have recently been determined. They reveal similar arrangements of the conserved ATP-hydrolyzing nucleotide-binding domains, but unrelated architectures of the transmembrane domains, with the notable exception of a common 'coupling helix' that is essential for transmitting conformational changes. The structures suggest a mechanism that rationalizes ATP-driven transport: While binding of ATP appears to trigger an outward-facing conformation, dissociation of the hydrolysis products may promote an inward-facing conformation. This basic scheme can, in principle, explain nutrient import by ABC importers and drug extrusion by ABC exporters.
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              Penaeid shrimp genome provides insights into benthic adaptation and frequent molting

              Crustacea, the subphylum of Arthropoda which dominates the aquatic environment, is of major importance in ecology and fisheries. Here we report the genome sequence of the Pacific white shrimp Litopenaeus vannamei, covering ~1.66 Gb (scaffold N50 605.56 Kb) with 25,596 protein-coding genes and a high proportion of simple sequence repeats (>23.93%). The expansion of genes related to vision and locomotion is probably central to its benthic adaptation. Frequent molting of the shrimp may be explained by an intensified ecdysone signal pathway through gene expansion and positive selection. As an important aquaculture organism, L. vannamei has been subjected to high selection pressure during the past 30 years of breeding, and this has had a considerable impact on its genome. Decoding the L. vannamei genome not only provides an insight into the genetic underpinnings of specific biological processes, but also provides valuable information for enhancing crustacean aquaculture.
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                Author and article information

                Contributors
                luca.peruzza@soton.ac.uk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                18 September 2019
                18 September 2019
                2019
                : 9
                : 13509
                Affiliations
                [1 ]ISNI 0000 0004 1936 9297, GRID grid.5491.9, School of Ocean and Earth Science, , University of Southampton, ; Hampshire, SO14 3ZH United Kingdom
                [2 ]ISNI 0000 0004 1755 9599, GRID grid.464531.1, Genetics and Biotechnology Unit, , Central Institute of Brackishwater Aquaculture, ; 75 Santhome High Road, R.A. Puram, Chennai, 600004 Tamil Nadu India
                Author information
                http://orcid.org/0000-0001-5001-8653
                Article
                49836
                10.1038/s41598-019-49836-0
                6751192
                31534145
                a1b730e6-12e4-41ad-9121-c878043cb1fb
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 10 April 2019
                : 30 August 2019
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100000268, RCUK | Biotechnology and Biological Sciences Research Council (BBSRC);
                Award ID: BB/N005058/1
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000269, RCUK | Economic and Social Research Council (ESRC);
                Award ID: BB / N005058/1
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100001407, Department of Biotechnology, Ministry of Science and Technology (DBT);
                Funded by: UK Aid (Grant number: BB/N005058/1)
                Categories
                Article
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                © The Author(s) 2019

                Uncategorized
                viral infection,transcriptomics,animal physiology
                Uncategorized
                viral infection, transcriptomics, animal physiology

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