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      Genomic epidemiology of the commercially important pathogen Renibacterium salmoninarum within the Chilean salmon industry

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          Abstract

          Renibacterium salmoninarum is the causative agent of bacterial kidney disease (BKD), which is a commercially important disease of farmed salmonids. Typing by conventional methods provides limited information on the evolution and spread of this pathogen, as there is a low level of standing variation within the R. salmoninarum population. Here, we apply whole-genome sequencing to 42 R. salmoninarum isolates from Chile, primarily from salmon farms, in order to understand the epidemiology of BKD in this country. The patterns of genomic variation are consistent with multiple introductions to Chile, followed by rapid dissemination over a 30 year period. The estimated dates of introduction broadly coincide with major events in the development of the Chilean aquaculture industry. We find evidence for significant barriers to transmission of BKD in the Chilean salmon production chain that may also be explained by previously undescribed signals of host tropism in R. salmoninarum. Understanding the genomic epidemiology of BKD can inform disease intervention and improve sustainability of the economically important salmon industry. This article contains data hosted by Microreact.

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          Most cited references16

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          SNP-sites: rapid efficient extraction of SNPs from multi-FASTA alignments

          Rapidly decreasing genome sequencing costs have led to a proportionate increase in the number of samples used in prokaryotic population studies. Extracting single nucleotide polymorphisms (SNPs) from a large whole genome alignment is now a routine task, but existing tools have failed to scale efficiently with the increased size of studies. These tools are slow, memory inefficient and are installed through non-standard procedures. We present SNP-sites which can rapidly extract SNPs from a multi-FASTA alignment using modest resources and can output results in multiple formats for downstream analysis. SNPs can be extracted from a 8.3 GB alignment file (1842 taxa, 22 618 sites) in 267 seconds using 59 MB of RAM and 1 CPU core, making it feasible to run on modest computers. It is easy to install through the Debian and Homebrew package managers, and has been successfully tested on more than 20 operating systems. SNP-sites is implemented in C and is available under the open source license GNU GPL version 3.
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            ClonalFrameML: Efficient Inference of Recombination in Whole Bacterial Genomes

            Recombination is an important evolutionary force in bacteria, but it remains challenging to reconstruct the imports that occurred in the ancestry of a genomic sample. Here we present ClonalFrameML, which uses maximum likelihood inference to simultaneously detect recombination in bacterial genomes and account for it in phylogenetic reconstruction. ClonalFrameML can analyse hundreds of genomes in a matter of hours, and we demonstrate its usefulness on simulated and real datasets. We find evidence for recombination hotspots associated with mobile elements in Clostridium difficile ST6 and a previously undescribed 310kb chromosomal replacement in Staphylococcus aureus ST582. ClonalFrameML is freely available at http://clonalframeml.googlecode.com/.
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              Microreact: visualizing and sharing data for genomic epidemiology and phylogeography

              Visualization is frequently used to aid our interpretation of complex datasets. Within microbial genomics, visualizing the relationships between multiple genomes as a tree provides a framework onto which associated data (geographical, temporal, phenotypic and epidemiological) are added to generate hypotheses and to explore the dynamics of the system under investigation. Selected static images are then used within publications to highlight the key findings to a wider audience. However, these images are a very inadequate way of exploring and interpreting the richness of the data. There is, therefore, a need for flexible, interactive software that presents the population genomic outputs and associated data in a user-friendly manner for a wide range of end users, from trained bioinformaticians to front-line epidemiologists and health workers. Here, we present Microreact, a web application for the easy visualization of datasets consisting of any combination of trees, geographical, temporal and associated metadata. Data files can be uploaded to Microreact directly via the web browser or by linking to their location (e.g. from Google Drive/Dropbox or via API), and an integrated visualization via trees, maps, timelines and tables provides interactive querying of the data. The visualization can be shared as a permanent web link among collaborators, or embedded within publications to enable readers to explore and download the data. Microreact can act as an end point for any tool or bioinformatic pipeline that ultimately generates a tree, and provides a simple, yet powerful, visualization method that will aid research and discovery and the open sharing of datasets.
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                Author and article information

                Journal
                Microb Genom
                Microb Genom
                mgen
                mgen
                Microbial Genomics
                Microbiology Society
                2057-5858
                September 2018
                24 July 2018
                24 July 2018
                : 4
                : 9
                : e000201
                Affiliations
                [ 1]Milner Centre for Evolution, Department of Biology and Biochemistry, University of Bath , Bath, UK
                [ 2]Weymouth Laboratory, Centre for Environment, Fisheries and Aquaculture Science (Cefas) , The Nothe, Weymouth, UK
                [ 3]Laboratorio ETECMA , Puerto Montt, Chile
                [ 4]Facultad de Medicina Veterinaria, Universidad San Sebastian , Puerto Montt 5501842, Chile
                [ 5]Laboratorio de Biotecnología, Instituto de Nutrición y Tecnología de los Alimentos (INTA), Universidad de Chile , Santiago, Chile
                [ 6]Centro de Investigaciones Biológicas Aplicadas (CIBA) , Puerto Montt, Chile
                [ 7]Doctorado en Acuicultura, Programa Cooperativo Universidad de Chile, Universidad Católica del Norte, Pontificia Universidad Católica de Valparaíso , Valparaíso, Chile
                Author notes
                *Correspondence: Edward J. Feil, e.feil@ 123456bath.ac.uk
                [†]

                These authors contributed equally to this work.

                Article
                mgen000201
                10.1099/mgen.0.000201
                6202448
                30040063
                a44fca01-6c00-468d-bfaf-e0548dcc50cc
                © 2018 The Authors

                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 work is properly cited.

                History
                : 16 May 2018
                : 04 July 2018
                Funding
                Funded by: Biotechnology and Biological Sciences Research Council
                Award ID: BB/M026388/1
                Funded by: Centre for Environment, Fisheries and Aquaculture Science (GB)
                Award ID: FB002
                Categories
                Research Article
                Microbial Evolution and Epidemiology: Communicable Disease Genomics
                Custom metadata
                0

                aquaculture,epidemiology,whole-genome sequencing,bacterial kidney disease,renibacterium salmoninarum

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