Prompt detection and effective control of porcine reproductive and respiratory syndrome virus (PRRSV) during outbreaks is important given its immense adverse impact on the swine industry. However, the diagnostic process can be challenging due to the high genetic diversity and high mutation rate of PRRSV. A diagnostic method that can provide more detailed genetic information about pathogens is urgently needed. In this study, we evaluated the ability of Oxford Nanopore MinION direct RNA sequencing to generate a PRRSV whole genome sequence and detect and discriminate virus at the strain-level. A nearly full length PRRSV genome was successfully generated from raw sequence reads, achieving an accuracy of 96% after consensus genome generation. Direct RNA sequencing reliably detected the PRRSV strain present with an accuracy of 99.9% using as few as 5 raw sequencing reads and successfully differentiated multiple co-infecting strains present in a sample. In addition, PRRSV strain information was obtained from clinical samples containing 104 to 106 viral copies or more within 6 hours of sequencing. Overall, direct viral RNA sequencing followed by bioinformatic analysis proves to be a promising approach for identification of the viral strain or strains involved in clinical infections, allowing for more precise prevention and control strategies during PRRSV outbreaks.
Keywords: MinION; PRRSV; analytical sensitivity; bioinformatics; co-infection; direct RNA sequencing; quantitation; strain level detection; whole genome sequencing.