Challenges in the analysis of viral metagenomes

Rose, Rebecca; Constantinides, Bede; Tapinos, Avraam; Robertson, David L; Prosperi, Mattia

Within metagenomes the proportion of viral nucleic acids is typically far lower than that of host or other microbes, limiting the amount of signal available for analysis after sequencing. To (Ruby, Bellare, and Derisi 2013) . Alternatively, PCR amplification may be used to generate an abundance of specific viral sequences present in a sample, a widely used strategy, which was employed in the identification and analysis of MERS coronavirus (Zaki et al. 2012; Cotten et al. 2013 Cotten et al. , 2014 , although effective primer design can be challenging in the presence of high genomic diversity in the target viral species. Conversely, an excess of sequencing coverage can lead to the construction of overly complex and unwieldy de novo assembly graphs in the presence of high genomic diversity, reducing assembly quality. Using in silico normalisation (Crusoe et al. 2015) , excess coverage may be reduced by discarding sequences containing redundant information. This approach increases analytical efficiency when dealing with high coverage sequence data, and we have shown that it can benefit de novo assembly of viral consensus sequences. Another in silico strategy for increasing analytical efficiency by discarding unneeded data is to filter sequences from known abundant organisms through alignment with one or more reference genomes using an aligner or specialist tool (approaches reviewed in Daly et al. 2015) .