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      Massive expansion of human gut bacteriophage diversity

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          Summary

          Bacteriophages drive evolutionary change in bacterial communities by creating gene flow networks that fuel ecological adaptions. However, the extent of viral diversity and its prevalence in the human gut remains largely unknown. Here, we introduce the Gut Phage Database, a collection of ∼142,000 non-redundant viral genomes (>10 kb) obtained by mining a dataset of 28,060 globally distributed human gut metagenomes and 2,898 reference genomes of cultured gut bacteria. Host assignment revealed that viral diversity is highest in the Firmicutes phyla and that ∼36% of viral clusters (VCs) are not restricted to a single species, creating gene flow networks across phylogenetically distinct bacterial species. Epidemiological analysis uncovered 280 globally distributed VCs found in at least 5 continents and a highly prevalent phage clade with features reminiscent of p-crAssphage. This high-quality, large-scale catalog of phage genomes will improve future virome studies and enable ecological and evolutionary analysis of human gut bacteriophages.

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          Highlights

          • Database containing 142,809 non-redundant gut phage genomes from 28,060 metagenomes

          • Host assignment reveals phage diversity and host range across gut bacteria isolates

          • Epidemiology analysis unveils 280 viral clusters that are globally distributed

          • The Gubaphage is a clade that infects several members of the Bacteroidales order

          Abstract

          By mining human gut metagenomes and gut bacteria isolates, Camarillo-Guerrero et al. compile high-quality gut bacteriophage genomes into the Gut Phage Database (GPD) and analyze the diversity and worldwide distribution of phage.

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          Most cited references73

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Fast and accurate short read alignment with Burrows–Wheeler transform

            Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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              Basic local alignment search tool.

              A new approach to rapid sequence comparison, basic local alignment search tool (BLAST), directly approximates alignments that optimize a measure of local similarity, the maximal segment pair (MSP) score. Recent mathematical results on the stochastic properties of MSP scores allow an analysis of the performance of this method as well as the statistical significance of alignments it generates. The basic algorithm is simple and robust; it can be implemented in a number of ways and applied in a variety of contexts including straightforward DNA and protein sequence database searches, motif searches, gene identification searches, and in the analysis of multiple regions of similarity in long DNA sequences. In addition to its flexibility and tractability to mathematical analysis, BLAST is an order of magnitude faster than existing sequence comparison tools of comparable sensitivity.
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                Author and article information

                Contributors
                Journal
                Cell
                Cell
                Cell
                Cell Press
                0092-8674
                1097-4172
                18 February 2021
                18 February 2021
                : 184
                : 4
                : 1098-1109.e9
                Affiliations
                [1 ]Host-Microbiota Interactions Laboratory, Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
                [2 ]European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SA, UK
                [3 ]Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton CB10 1SA, UK
                [4 ]Max Planck Tandem Group in Computational Biology, Department of Biological Sciences, Universidad de los Andes, Bogota 111711, Colombia
                Author notes
                []Corresponding author lg15@ 123456sanger.ac.uk
                [∗∗ ]Corresponding author tl2@ 123456sanger.ac.uk
                [5]

                Lead contact

                Article
                S0092-8674(21)00072-6
                10.1016/j.cell.2021.01.029
                7895897
                33606979
                e2e77de8-513e-44aa-93e7-64d2980104b7
                © 2021 The Authors

                This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

                History
                : 18 August 2020
                : 2 November 2020
                : 19 January 2021
                Categories
                Resource

                Cell biology
                virus,phage,human gut,microbiome,database,metagenomics,gut bacteria
                Cell biology
                virus, phage, human gut, microbiome, database, metagenomics, gut bacteria

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