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      Long-read viral metagenomics captures abundant and microdiverse viral populations and their niche-defining genomic islands

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          Abstract

          Marine viruses impact global biogeochemical cycles via their influence on host community structure and function, yet our understanding of viral ecology is constrained by limitations in host culturing and a lack of reference genomes and ‘universal’ gene markers to facilitate community surveys. Short-read viral metagenomic studies have provided clues to viral function and first estimates of global viral gene abundance and distribution, but their assemblies are confounded by populations with high levels of strain evenness and nucleotide diversity (microdiversity), limiting assembly of some of the most abundant viruses on Earth. Such features also challenge assembly across genomic islands containing niche-defining genes that drive ecological speciation. These populations and features may be successfully captured by single-virus genomics and fosmid-based approaches, at least in abundant taxa, but at considerable cost and technical expertise. Here we established a low-cost, low-input, high throughput alternative sequencing and informatics workflow to improve viral metagenomic assemblies using short-read and long-read technology. The ‘VirION’ (Viral, long-read metagenomics via MinION sequencing) approach was first validated using mock communities where it was found to be as relatively quantitative as short-read methods and provided significant improvements in recovery of viral genomes. We then then applied VirION to the first metagenome from a natural viral community from the Western English Channel. In comparison to a short-read only approach, VirION: (i) increased number and completeness of assembled viral genomes; (ii) captured abundant, highly microdiverse virus populations, and (iii) captured more and longer genomic islands. Together, these findings suggest that VirION provides a high throughput and cost-effective alternative to fosmid and single-virus genomic approaches to more comprehensively explore viral communities in nature.

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          Detecting overlapping protein complexes in protein-protein interaction networks.

          We introduce clustering with overlapping neighborhood expansion (ClusterONE), a method for detecting potentially overlapping protein complexes from protein-protein interaction data. ClusterONE-derived complexes for several yeast data sets showed better correspondence with reference complexes in the Munich Information Center for Protein Sequence (MIPS) catalog and complexes derived from the Saccharomyces Genome Database (SGD) than the results of seven popular methods. The results also showed a high extent of functional homogeneity.
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            Microbial diversity and function in soil: from genes to ecosystems.

            Soils sustain an immense diversity of microbes, which, to a large extent, remains unexplored. A range of novel methods, most of which are based on rRNA and rDNA analyses, have uncovered part of the soil microbial diversity. The next step in the era of microbial ecology is to extract genomic, evolutionary and functional information from bacterial artificial chromosome libraries of the soil community genomes (the metagenome). Sophisticated analyses that apply molecular phylogenetics, DNA microarrays, functional genomics and in situ activity measurements will provide huge amounts of new data, potentially increasing our understanding of the structure and function of soil microbial ecosystems, and the interactions that occur within them. This review summarizes the recent progress in studies of soil microbial communities with focus on novel methods and approaches that provide new insight into the relationship between phylogenetic and functional diversity.
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              Improved data analysis for the MinION nanopore sequencer

              The Oxford Nanopore MinION sequences individual DNA molecules using an array of pores that read nucleotide identities based on ionic current steps. We evaluated and optimized MinION performance using M13 genomic dsDNA. Using expectation-maximization (EM) we obtained robust maximum likelihood (ML) estimates for read insertion, deletion and substitution error rates (4.9%, 7.8%, and 5.1% respectively). We found that 99% of high-quality ‘2D’ MinION reads mapped to reference at a mean identity of 85%. We present a MinION-tailored tool for single nucleotide variant (SNV) detection that uses ML parameter estimates and marginalization over many possible read alignments to achieve precision and recall of up to 99%. By pairing our high-confidence alignment strategy with long MinION reads, we resolved the copy number for a cancer/testis gene family (CT47) within an unresolved region of human chromosome Xq24.
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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                peerj
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                25 April 2019
                2019
                : 7
                : e6800
                Affiliations
                [1 ]Plymouth Marine Laboratory , Plymouth, Devon, United Kingdom
                [2 ]School of Biosciences, University of Exeter , Exeter, Devon, United Kingdom
                [3 ]Department of Microbiology, Ohio State University , Columbus, OH, United States of America
                [4 ]Civil, Environmental and Geodetic Engineering, Ohio State University , Columbus, OH, United States of America
                Article
                6800
                10.7717/peerj.6800
                6487183
                31086738
                dda1f722-5f69-4b26-aa2f-843e6adc5101
                ©2019 Warwick-Dugdale et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 15 November 2018
                : 14 March 2019
                Funding
                Funded by: Bermuda Institute of Ocean Sciences as part of the BIOS-SCOPE program
                Funded by: Royal Society and the Natural Environment Research Council (NERC)
                Award ID: NE/P008534/1
                Award ID: NE/R010935/1
                Funded by: NERC Great Western Four+ (GW4+) Doctoral Training Partnership PhD
                Award ID: NE/L002434/1
                Funded by: Gordon and Betty Moore Foundation
                Award ID: #3790
                Award ID: 5488
                Major support was provided by a fellowship to Ben Temperton from the Bermuda Institute of Ocean Sciences as part of the BIOS-SCOPE program; the Royal Society and the Natural Environment Research Council (NERC) (NE/P008534/1 and NE/R010935/1 to Ben Temperton). Additional support was from a NERC Great Western Four+ (GW4+) Doctoral Training Partnership PhD to Joanna Warwick-Dugdale (NE/L002434/1) and the Gordon and Betty Moore Foundation (awards #3790 and 5488) to Matthew B. Sullivan. There was no additional external funding received for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Bioinformatics
                Genomics
                Marine Biology
                Microbiology
                Virology

                viral metagenomics,virus,virome,metagenome,assembly,viral ecology,long-read sequencing,marine microbiology

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