Amplicon-Based, Next-Generation Sequencing Approaches to Characterize Single Nucleotide Polymorphisms of Orthohantavirus Species

Abstract

Whole-genome sequencing (WGS) of viruses from patient or environmental samples can provide tremendous insight into the epidemiology, drug resistance or evolution of a virus. However, we face two common hurdles in obtaining robust sequence information; the low copy number of viral genomes in specimens and the error introduced by WGS techniques. To optimize detection and minimize error in WGS of hantaviruses, we tested four amplification approaches and different amplicon pooling methods for library preparation and examined these preparations using two sequencing platforms, Illumina MiSeq and Oxford Nanopore Technologies MinION. First, we tested and optimized primers used for whole segment PCR or one kilobase amplicon amplification for even coverage using RNA isolated from the supernatant of virus-infected cells. Once optimized we assessed two sources of total RNA, virus-infected cells and supernatant from the virus-infected cells, with four variations of primer pooling for amplicons, and six different amplification approaches. We show that 99–100% genome coverage was obtained using a one-step RT-PCR reaction with one forward and reverse primer. Using a two-step RT-PCR with three distinct tiling approaches for the three genomic segments (vRNAs), we optimized primer pooling approaches for PCR amplification to achieve a greater number of aligned reads, average depth of genome, and genome coverage. The single nucleotide polymorphisms identified from MiSeq and MinION sequencing suggested intrinsic mutation frequencies of ~10−5-10−7 per genome and 10−4-10−5 per genome, respectively. We noted no difference in the coverage or accuracy when comparing WGS results with amplicons amplified from RNA extracted from infected cells or supernatant of these infected cells. Our results show that high-throughput diagnostics requiring the identification of hantavirus species or strains can be performed using MiSeq or MinION using a one-step approach. However, the two-step MiSeq approach outperformed the MinION in coverage depth and accuracy, and hence would be superior for assessment of genomes for epidemiology or evolutionary questions using the methods developed herein.