Improved detection of artifactual viral minority variants in high-throughput sequencing data

High-throughput sequencing (HTS) of viral samples provides important information on the presence of viral minority variants. However, detection and accurate quantification is limited by the capacity to distinguish biological from artificial variation. In this study, errors related to the Illumina Hiseq2000 library generation and HTS process were investigated by determining minority variant frequencies in an influenza A/WSN/1933(H1N1) virus reversegenetics plasmid pool. Errors related to amplification and sequencing were determined using the same plasmid pool, by generation of infectious virus using reverse genetics followed by in duplo reverse-transcriptase PCR (RT-PCR) amplification and HTS in the same sequence run. Results showed that after 'best practice' quality control (QC), within the plasmid pool, 1 minority variant with a frequency >0.5% was identified, while 84 and 139 were identified in the RT-PCR amplified samples, indicating RT-PCR amplification artificially increased variation. Detailed analysis showed that artifactual minority variants could be identified by two major technical characteristics: their predominant presence in a single read orientation and uneven distribution of mismatches over the length of the reads. We demonstrate that by addi