Single-virus genomics reveals hidden cosmopolitan and abundant viruses

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Title: Single-virus genomics reveals hidden cosmopolitan and abundant viruses
Authors: Martinez-Hernandez, Francisco | Fornas, Oscar | Lluesma Gómez, Mónica | Bolduc, Benjamin | Cruz Peña, Maria Jose de la | Martínez Martínez, Joaquín | Anton, Josefa | Gasol, Josep M. | Rosselli, Riccardo | Rodriguez-Valera, Francisco | Sullivan, Matthew B. | Acinas, Silvia G. | Martinez-Garcia, Manuel
Research Group/s: Ecología Microbiana Molecular
Center, Department or Service: Universidad de Alicante. Departamento de Fisiología, Genética y Microbiología
Keywords: Single-virus genomics | Viruses
Knowledge Area: Fisiología | Microbiología
Issue Date: 23-Jun-2017
Publisher: Macmillan Publishers
Citation: Nature Communications. 2017, 8:15892. doi:10.1038/ncomms15892
Abstract: Microbes drive ecosystems under constraints imposed by viruses. However, a lack of virus genome information hinders our ability to answer fundamental, biological questions concerning microbial communities. Here we apply single-virus genomics (SVGs) to assess whether portions of marine viral communities are missed by current techniques. The majority of the here-identified 44 viral single-amplified genomes (vSAGs) are more abundant in global ocean virome data sets than published metagenome-assembled viral genomes or isolates. This indicates that vSAGs likely best represent the dsDNA viral populations dominating the oceans. Species-specific recruitment patterns and virome simulation data suggest that vSAGs are highly microdiverse and that microdiversity hinders the metagenomic assembly, which could explain why their genomes have not been identified before. Altogether, SVGs enable the discovery of some of the likely most abundant and ecologically relevant marine viral species, such as vSAG 37-F6, which were overlooked by other methodologies.
Sponsor: This work has been supported by Spanish Ministry of Economy and Competitiveness (refs CGL2013-40564-R and SAF2013-49267-EXP), Generalitat Valenciana (ref. ACOM/2015/133 and ACIF/2015/332), the USA National Science Foundation (OCE#1536989), the USA Department of Energy (DE-SC0010580), and Gordon and Betty Moore Foundation (grants 3305, 3790, and 5334). The Ohio Supercomputer supported gene-sharing network high performance compute time. Work at BBMO was funded by Spanish project CT2015-70340-R. Work at CRG, BIST and UPF was in part funded by the Spanish Ministry of Economy and Competitiveness, ‘Centro de Excelencia Severo Ochoa 2013-2017’ and the Spanish Ministry of Economy and Competitiveness, ‘Centro de Excelencia Maria de Maeztu 2016-2019’.
URI: http://hdl.handle.net/10045/67518
ISSN: 2041-1723
DOI: 10.1038/ncomms15892
Language: eng
Type: info:eu-repo/semantics/article
Rights: The Author(s) 2017. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
Peer Review: si
Publisher version: http://dx.doi.org/10.1038/ncomms15892
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