Complete viral RNA genome sequencing of ultra-low copy samples by sequence-independent amplification

Malboeuf, Christine M.; Yang, Xiao; Charlebois, Patrick; Qu, James; Berlin, Aaron M.; Casali, Monica; Pesko, Kendra N.; Boutwell, Christian L.; DeVincenzo, John P.; Ebel, Gregory D.; Allen, Todd M.; Zody, Michael C.; Henn, Matthew R.; Levin, Joshua Z.

Our method has several advantages over standard RT-PCR based methods. It does not require prior viral sequence knowledge for primer design enabling the study of viruses with limited sequence data. The lack of viral-specific primers allows for identification of viral recombinants that might not be found with standard RT-PCR methods. Our method is capable of amplifying viral RNA genomes that are not successful by traditional RT-PCR methods. For HIV clinical sample B, four RT-PCR attempts were not successful in capturing the CDS, but in all six attempts with our method 97-100% of the CDS was captured (Table 1) . Furthermore, this method is easily applicable to multiple sample types. We applied the method to HIV, RSV and WNV samples without the need for optimization. Developing a robust RT-PCR process with viral specific primers can require a significant effort, up to several months (unpublished results), so that our method potentially speeds up viral genome sequencing projects. This method works with a highly variable virus such as HIV-capturing the entire CDS of the genome starting from only 100 viral genomes (Table 1 ). In addition, the process from viral RNA to dsDNA requires only 4.5 hours. Furthermore if this method were coupled with Nextera Illumina library construction (45) , one could generate an Illumina library in less than a single day. Although the Nextera method is very fast, the transposase-based method of Illumina library construction may introduce GC-bias compared with standard methods (46) . As only 5 million reads were necessary to assemble complete viral genomes, MiSeq or Ion Torrent sequencing (47) could be used. This would allow a researcher to go from sample to sequence data in less than a week. Finally, the Ovation RNA-Seq method is available in automated format allowing for high-throughput processing of clinical samples. As only 5 million reads are needed per sample, one could pool up to 96 samples per lane of HiSeq2000.