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      IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets

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          Abstract

          IslandViewer ( http://www.pathogenomics.sfu.ca/islandviewer/) is a widely-used webserver for the prediction and interactive visualization of genomic islands (GIs, regions of probable horizontal origin) in bacterial and archaeal genomes. GIs disproportionately encode factors that enhance the adaptability and competitiveness of the microbe within a niche, including virulence factors and other medically or environmentally important adaptations. We report here the release of IslandViewer 4, with novel features to accommodate the needs of larger-scale microbial genomics analysis, while expanding GI predictions and improving its flexible visualization interface. A user management web interface as well as an HTTP API for batch analyses are now provided with a secured authentication to facilitate the submission of larger numbers of genomes and the retrieval of results. In addition, IslandViewer's integrated GI predictions from multiple methods have been improved and expanded by integrating the precise Islander method for pre-computed genomes, as well as an updated IslandPath-DIMOB for both pre-computed and user-supplied custom genome analysis. Finally, pre-computed predictions including virulence factors and antimicrobial resistance are now available for 6193 complete bacterial and archaeal strains publicly available in RefSeq. IslandViewer 4 provides key enhancements to facilitate the analysis of GIs and better understand their role in the evolution of successful environmental microbes and pathogens.

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          Genomic islands in pathogenic and environmental microorganisms.

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            IslandViewer: an integrated interface for computational identification and visualization of genomic islands

            Summary: Genomic islands (clusters of genes of probable horizontal origin; GIs) play a critical role in medically important adaptations of bacteria. Recently, several computational methods have been developed to predict GIs that utilize either sequence composition bias or comparative genomics approaches. IslandViewer is a web accessible application that provides the first user-friendly interface for obtaining precomputed GI predictions, or predictions from user-inputted sequence, using the most accurate methods for genomic island prediction: IslandPick, IslandPath-DIMOB and SIGI-HMM. The graphical interface allows easy viewing and downloading of island data in multiple formats, at both the chromosome and gene level, for method-specific, or overlapping, GI predictions. Availability: The IslandViewer web service is available at http://www.pathogenomics.sfu.ca/islandviewer and the source code is freely available under the GNU GPL license. Contact: brinkman@sfu.ca
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              Horizontal Gene Exchange in Environmental Microbiota

              Horizontal gene transfer (HGT) plays an important role in the evolution of life on the Earth. This view is supported by numerous occasions of HGT that are recorded in the genomes of all three domains of living organisms. HGT-mediated rapid evolution is especially noticeable among the Bacteria, which demonstrate formidable adaptability in the face of recent environmental changes imposed by human activities, such as the use of antibiotics, industrial contamination, and intensive agriculture. At the heart of the HGT-driven bacterial evolution and adaptation are highly sophisticated natural genetic engineering tools in the form of a variety of mobile genetic elements (MGEs). The main aim of this review is to give a brief account of the occurrence and diversity of MGEs in natural ecosystems and of the environmental factors that may affect MGE-mediated HGT.
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                Author and article information

                Journal
                Nucleic Acids Res
                Nucleic Acids Res
                nar
                Nucleic Acids Research
                Oxford University Press
                0305-1048
                1362-4962
                03 July 2017
                02 May 2017
                02 May 2017
                : 45
                : Web Server issue
                : W30-W35
                Affiliations
                [1 ]Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
                [2 ]European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
                [3 ]Systems Biology Department, Sandia National Laboratories, Livermore, CA 94551, USA
                [4 ]Big Data Hub, Simon Fraser University, Burnaby, BC V5A 1S6, Canada
                Author notes
                [* ]To whom correspondence should be addressed. Tel: +1 778 782 5646; Fax: +1 778 782 5583; Email: brinkman@ 123456sfu.ca
                Author information
                http://orcid.org/0000-0001-6848-1638
                Article
                gkx343
                10.1093/nar/gkx343
                5570257
                28472413
                20defa0a-6c7b-4aa6-a8a1-204b9fdceeb8
                © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

                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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 18 April 2017
                : 07 April 2017
                : 24 February 2017
                Page count
                Pages: 6
                Categories
                Web Server Issue

                Genetics
                Genetics

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