![]() The advantages of sequence-independent amplification are simplicity and relative speed and the ability to identify and sequence hundreds of viruses simultaneously thereby allowing detection of new or previously unrecognized viruses that are highly divergent from already described ones ( Bodewes et al., 2014a, c). Common random amplification methods are multiple displacement amplification (MDA) or sequence-independent single-primer amplification (SISPA) ( Hutchison et al., 2005 Spits et al., 2006 Delwart, 2007 Djikeng et al., 2008 Lipkin, 2010 Smits and Osterhaus, 2013). Metagenomic strategies to virus discovery rely on sequence-independent amplification of nucleic acids combined with next generation sequencing platforms instead of targeting specific genomic loci, thereby generating DNA sequences (i.e., reads) that align to various genomic locations for the numerous genomes present in the sample, including non-microbes ( Sharpton, 2014). In addition, these techniques are more and more often being used to generate complete genomes of uncultivated viruses, but also other organisms ( Delwart, 2007 Lipkin, 2010 Iverson et al., 2012 Albertsen et al., 2013 Smits and Osterhaus, 2013 Handley et al., 2014). Nowadays, in order to discover and characterize new or (re-) emerging viruses, metagenome sequencing is increasingly being used to identify viral pathogens. Classically, new viruses were identified by standard molecular detection methods, virus replication in tissue culture or animal experiments. In a proportion of patients and animals suffering from disease, no pathogens can be detected using a range of sensitive diagnostic assays, suggesting the presence of unidentified viruses in human and animal populations ( Bloch and Glaser, 2007 Denno et al., 2012). Human and animal populations are continuously confronted with emerging viral infections ( Delwart, 2007 Lipkin, 2010 Smits and Osterhaus, 2013). Depending on specific characteristics of the target virus and the metagenomic community, different assembly and in silico gap closure strategies were successful in obtaining near complete viral genomes. All methods were tested on 454-generated sequencing datasets containing three recently described RNA viruses with a relatively large genome which were divergent to previously known viruses from the viral families Rhabdoviridae and Coronaviridae. Here we explored different assembly algorithms, remote homology searches, genome-specific sequence motifs, k-mer frequency ranking, and coverage profile binning to detect and obtain viral target genomes from metagenomes. De novo assembly of single viruses from a metagenome is challenging, not only because of the lack of a reference genome, but also because of intrapopulation variation and uneven or insufficient coverage. Often, however, complete viral genomes are not recovered, but rather several distinct contigs derived from a single entity are, some of which have no sequence homology to any known proteins. In silico identification of complete viral genomes from sequence data would allow rapid phylogenetic characterization of these new viruses. Metagenomic approaches are increasingly used in the detection of novel viral pathogens but also to generate complete genomes of uncultivated viruses. ![]() Viral infections remain a serious global health issue.
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