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      Genomic analysis of host – Peste des petits ruminants vaccine viral transcriptome uncovers transcription factors modulating immune regulatory pathways

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          Abstract

          Peste des petits ruminants (PPR), is an acute transboundary viral disease of economic importance, affecting goats and sheep. Mass vaccination programs around the world resulted in the decline of PPR outbreaks. Sungri 96 is a live attenuated vaccine, widely used in Northern India against PPR. This vaccine virus, isolated from goat works efficiently both in sheep and goat. Global gene expression changes under PPR vaccine virus infection are not yet well defined. Therefore, in this study we investigated the host-vaccine virus interactions by infecting the peripheral blood mononuclear cells isolated from goat with PPRV (Sungri 96 vaccine virus), to quantify the global changes in the transcriptomic signature by RNA-sequencing. Viral genome of Sungri 96 vaccine virus was assembled from the PPRV infected transcriptome confirming the infection and demonstrating the feasibility of building a complete non-host genome from the blood transcriptome. Comparison of infected transcriptome with control transcriptome revealed 985 differentially expressed genes. Functional analysis showed enrichment of immune regulatory pathways under PPRV infection. Key genes involved in immune system regulation, spliceosomal and apoptotic pathways were identified to be dysregulated. Network analysis revealed that the protein - protein interaction network among differentially expressed genes is significantly disrupted in infected state. Several genes encoding TFs that govern immune regulatory pathways were identified to co-regulate the differentially expressed genes. These data provide insights into the host - PPRV vaccine virus interactome for the first time. Our findings suggested dysregulation of immune regulatory pathways and genes encoding Transcription Factors (TFs) that govern these pathways in response to viral infection.

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          The online version of this article (doi:10.1186/s13567-015-0153-8) contains supplementary material, which is available to authorized users.

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          Most cited references49

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          The BioGRID Interaction Database: 2011 update

          The Biological General Repository for Interaction Datasets (BioGRID) is a public database that archives and disseminates genetic and protein interaction data from model organisms and humans (http://www.thebiogrid.org). BioGRID currently holds 347 966 interactions (170 162 genetic, 177 804 protein) curated from both high-throughput data sets and individual focused studies, as derived from over 23 000 publications in the primary literature. Complete coverage of the entire literature is maintained for budding yeast (Saccharomyces cerevisiae), fission yeast (Schizosaccharomyces pombe) and thale cress (Arabidopsis thaliana), and efforts to expand curation across multiple metazoan species are underway. The BioGRID houses 48 831 human protein interactions that have been curated from 10 247 publications. Current curation drives are focused on particular areas of biology to enable insights into conserved networks and pathways that are relevant to human health. The BioGRID 3.0 web interface contains new search and display features that enable rapid queries across multiple data types and sources. An automated Interaction Management System (IMS) is used to prioritize, coordinate and track curation across international sites and projects. BioGRID provides interaction data to several model organism databases, resources such as Entrez-Gene and other interaction meta-databases. The entire BioGRID 3.0 data collection may be downloaded in multiple file formats, including PSI MI XML. Source code for BioGRID 3.0 is freely available without any restrictions.
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            Annotation transfer between genomes: protein-protein interologs and protein-DNA regulogs.

            Proteins function mainly through interactions, especially with DNA and other proteins. While some large-scale interaction networks are now available for a number of model organisms, their experimental generation remains difficult. Consequently, interolog mapping--the transfer of interaction annotation from one organism to another using comparative genomics--is of significant value. Here we quantitatively assess the degree to which interologs can be reliably transferred between species as a function of the sequence similarity of the corresponding interacting proteins. Using interaction information from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, and Helicobacter pylori, we find that protein-protein interactions can be transferred when a pair of proteins has a joint sequence identity >80% or a joint E-value <10(-70). (These "joint" quantities are the geometric means of the identities or E-values for the two pairs of interacting proteins.) We generalize our interolog analysis to protein-DNA binding, finding such interactions are conserved at specific thresholds between 30% and 60% sequence identity depending on the protein family. Furthermore, we introduce the concept of a "regulog"--a conserved regulatory relationship between proteins across different species. We map interologs and regulogs from yeast to a number of genomes with limited experimental annotation (e.g., Arabidopsis thaliana) and make these available through an online database at http://interolog.gersteinlab.org. Specifically, we are able to transfer approximately 90,000 potential protein-protein interactions to the worm. We test a number of these in two-hybrid experiments and are able to verify 45 overlaps, which we show to be statistically significant. Copyright 2004 Cold Spring Harbor Laboratory Press
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              NF-κB: roles and regulation in different CD4(+) T-cell subsets.

              The nuclear factor-κB (NF-κB) family of transcription factors plays important roles in various biological processes including apoptosis, stress response, immunity, and inflammation. NF-κB signaling is involved in both immune cell development and function, and it is critical in modulation of the immune response through the transcriptional regulation of cytokine and chemokine expression. An area of great interest in T-cell-mediated adaptive immunity is the ability of naive CD4(+) T cells generated in the thymus to differentiate into various subsets including T-helper 1 (Th1), Th2, Th17, Th9, follicular helper T (Tfh), Th22, and regulatory T (Treg) cells, upon encountering different pathogens and microenvironments. In this review, we discuss the role of NF-κB pathway in the development and functional divergence of the different helper T-cell subsets as well as in regulatory T cells. © 2013 John Wiley & Sons A/S. Published by Blackwell Publishing Ltd.
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                Author and article information

                Contributors
                smanju712@gmail.com
                gandham71@gmail.com
                bpmishra_1@hotmail.com
                binachauhanmishra@hotmail.com
                rush2aditya@gmail.com
                cgjoshi@rediffmail.com
                aktiwari63@yahoo.com
                kaushalvirol@gmail.com
                scjanga@iupui.edu
                Journal
                Vet Res
                Vet. Res
                Veterinary Research
                BioMed Central (London )
                0928-4249
                1297-9716
                24 February 2015
                24 February 2015
                2015
                : 46
                : 15
                Affiliations
                [ ]Division of Veterinary Biotechnology, Indian Veterinary Research Institute, Izatnagar-243122, Bareilly, India
                [ ]School of Informatics and Computing, Indiana University Purdue University, 719 Indiana Ave Ste 319, Walker Plaza Building, Indianapolis, Indiana 46202 USA
                [ ]Department of Animal Biotechnology, College of Veterinary Science & Animal Husbandry, Anand Agricultural University, Anand, Gujarat 388001 India
                [ ]Division of Virology, Indian Veterinary Research Institute (IVRI), Mukteswar Campus, Nainital (Uttaranchal), 263138 India
                [ ]Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, 5021 Health Information and Translational Sciences (HITS), 410 West 10th Street, Indianapolis, Indiana 46202 USA
                [ ]Department of Medical and Molecular Genetics, Indiana University School of Medicine, Medical Research and Library Building, 975 West Walnut Street, Indianapolis, Indiana 46202 USA
                Article
                153
                10.1186/s13567-015-0153-8
                4337102
                25827022
                8316fe34-1ac0-4373-9d86-ebf171ab1568
                © Manjunath et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 8 September 2014
                : 16 January 2015
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                Research
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                © The Author(s) 2015

                Veterinary medicine
                Veterinary medicine

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