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      Standards for Sequencing Viral Genomes in the Era of High-Throughput Sequencing

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          ABSTRACT

          Thanks to high-throughput sequencing technologies, genome sequencing has become a common component in nearly all aspects of viral research; thus, we are experiencing an explosion in both the number of available genome sequences and the number of institutions producing such data. However, there are currently no common standards used to convey the quality, and therefore utility, of these various genome sequences. Here, we propose five “standard” categories that encompass all stages of viral genome finishing, and we define them using simple criteria that are agnostic to the technology used for sequencing. We also provide genome finishing recommendations for various downstream applications, keeping in mind the cost-benefit trade-offs associated with different levels of finishing. Our goal is to define a common vocabulary that will allow comparison of genome quality across different research groups, sequencing platforms, and assembly techniques.

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          Most cited references18

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          Isolation and characterization of viruses related to the SARS coronavirus from animals in southern China.

          Y Guan (2003)
          A novel coronavirus (SCoV) is the etiological agent of severe acute respiratory syndrome (SARS). SCoV-like viruses were isolated from Himalayan palm civets found in a live-animal market in Guangdong, China. Evidence of virus infection was also detected in other animals (including a raccoon dog, Nyctereutes procyonoides) and in humans working at the same market. All the animal isolates retain a 29-nucleotide sequence that is not found in most human isolates. The detection of SCoV-like viruses in small, live wild mammals in a retail market indicates a route of interspecies transmission, although the natural reservoir is not known.
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            Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform

            Due to the increasing throughput of current DNA sequencing instruments, sample multiplexing is necessary for making economical use of available sequencing capacities. A widely used multiplexing strategy for the Illumina Genome Analyzer utilizes sample-specific indexes, which are embedded in one of the library adapters. However, this and similar multiplex approaches come with a risk of sample misidentification. By introducing indexes into both library adapters (double indexing), we have developed a method that reveals the rate of sample misidentification within current multiplex sequencing experiments. With ~0.3% these rates are orders of magnitude higher than expected and may severely confound applications in cancer genomics and other fields requiring accurate detection of rare variants. We identified the occurrence of mixed clusters on the flow as the predominant source of error. The accuracy of sample identification is further impaired if indexed oligonucleotides are cross-contaminated or if indexed libraries are amplified in bulk. Double-indexing eliminates these problems and increases both the scope and accuracy of multiplex sequencing on the Illumina platform.
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              Pseudomonas Genome Database: improved comparative analysis and population genomics capability for Pseudomonas genomes

              Pseudomonas is a metabolically-diverse genus of bacteria known for its flexibility and leading free living to pathogenic lifestyles in a wide range of hosts. The Pseudomonas Genome Database (http://www.pseudomonas.com) integrates completely-sequenced Pseudomonas genome sequences and their annotations with genome-scale, high-precision computational predictions and manually curated annotation updates. The latest release implements an ability to view sequence polymorphisms in P. aeruginosa PAO1 versus other reference strains, incomplete genomes and single gene sequences. This aids analysis of phenotypic variation between closely related isolates and strains, as well as wider population genomics and evolutionary studies. The wide range of tools for comparing Pseudomonas annotations and sequences now includes a strain-specific access point for viewing high precision computational predictions including updated, more accurate, protein subcellular localization and genomic island predictions. Views link to genome-scale experimental data as well as comparative genomics analyses that incorporate robust genera-geared methods for predicting and clustering orthologs. These analyses can be exploited for identifying putative essential and core Pseudomonas genes or identifying large-scale evolutionary events. The Pseudomonas Genome Database aims to provide a continually updated, high quality source of genome annotations, specifically tailored for Pseudomonas researchers, but using an approach that may be implemented for other genera-level research communities.
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                Author and article information

                Journal
                mBio
                MBio
                mbio
                mbio
                mBio
                mBio
                American Society of Microbiology (1752 N St., N.W., Washington, DC )
                2150-7511
                17 June 2014
                May-Jun 2014
                : 5
                : 3
                : e01360-14
                Affiliations
                [ a ]Center for Genome Sciences, United States Army Medical Research Institute of Infectious Diseases, Fort Detrick, Maryland, USA
                [ b ]Bioinformatics and Analytics Team, Bioscience Division, Los Alamos National Laboratory, Los Alamos, New Mexico, USA
                [ c ]National Security Systems Biology Center, Asymmetric Operations Sector, Johns Hopkins University, Applied Physics Laboratory, Laurel, Maryland, USA
                [ d ]U.S. Food and Drug Administration, Silver Spring, Maryland, USA
                [ e ]Filovirus Animal Nonclinical Group (FANG) Well Characterized Challenge Material Working Group
                [ f ]Department of Microbiology and Immunology, University of Maryland at Baltimore, Baltimore, Maryland, USA
                [ g ]Integrated Research Facility at Fort Detrick, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Fort Detrick, Frederick, Maryland, USA
                [ h ]FAS Center for Systems Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, USA
                [ i ]Broad Institute, Cambridge, Massachusetts, USA
                [ j ]Virology, J. Craig Venter Institute, Rockville, Maryland, USA
                [ k ]The Threat Characterization Consortium, Defense Threat Reduction Agency, Fort Belvoir, Virginia, USA
                [ l ]GoldBelt Raven, LLC, Frederick, Maryland, USA
                Author notes
                Address correspondence to Jason T. Ladner, jason.t.ladner.ctr@ 123456mail.mil , or Gustavo Palacios, gustavo.f.palacios.ctr@ 123456mail.mil .
                Article
                mBio01360-14
                10.1128/mBio.01360-14
                4068259
                24939889
                83a389d9-b314-4a48-bce6-4640f6b36867
                Copyright © 2014 Ladner et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-ShareAlike 3.0 Unported license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                Page count
                Pages: 5
                Categories
                Guest Editorial
                Custom metadata
                May/June 2014

                Life sciences
                Life sciences

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