Viral dark matter and virus–host interactions resolved from publicly available microbial genomes
Identifieur interne : 001197 ( Main/Curation ); précédent : 001196; suivant : 001198Viral dark matter and virus–host interactions resolved from publicly available microbial genomes
Auteurs : Simon Roux [États-Unis] ; Steven J. Hallam [Canada] ; Tanja Woyke [États-Unis] ; Matthew B. Sullivan [États-Unis]Source :
- eLife [ 2050-084X ] ; ????.
Abstract
The ecological importance of viruses is now widely recognized, yet our limited knowledge of viral sequence space and virus–host interactions precludes accurate prediction of their roles and impacts. In this study, we mined publicly available bacterial and archaeal genomic data sets to identify 12,498 high-confidence viral genomes linked to their microbial hosts. These data augment public data sets 10-fold, provide first viral sequences for 13 new bacterial phyla including ecologically abundant phyla, and help taxonomically identify 7–38% of ‘unknown’ sequence space in viromes. Genome- and network-based classification was largely consistent with accepted viral taxonomy and suggested that (i) 264 new viral genera were identified (doubling known genera) and (ii) cross-taxon genomic recombination is limited. Further analyses provided empirical data on extrachromosomal prophages and coinfection prevalences, as well as evaluation of in silico virus–host linkage predictions. Together these findings illustrate the value of mining viral signal from microbial genomes.
Url:
DOI: 10.7554/eLife.08490
PubMed: 26200428
PubMed Central: 4533152
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PMC:4533152Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>The ecological importance of viruses is now widely recognized, yet our limited knowledge of viral sequence space and virus–host interactions precludes accurate prediction of their roles and impacts. In this study, we mined publicly available bacterial and archaeal genomic data sets to identify 12,498 high-confidence viral genomes linked to their microbial hosts. These data augment public data sets 10-fold, provide first viral sequences for 13 new bacterial phyla including ecologically abundant phyla, and help taxonomically identify 7–38% of ‘unknown’ sequence space in viromes. Genome- and network-based classification was largely consistent with accepted viral taxonomy and suggested that (i) 264 new viral genera were identified (doubling known genera) and (ii) cross-taxon genomic recombination is limited. Further analyses provided empirical data on extrachromosomal prophages and coinfection prevalences, as well as evaluation of in silico virus–host linkage predictions. Together these findings illustrate the value of mining viral signal from microbial genomes.</p>
<p><bold>DOI:</bold>
<ext-link ext-link-type="doi" xlink:href="10.7554/eLife.08490.001">http://dx.doi.org/10.7554/eLife.08490.001</ext-link>
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