Recent studies have shown significant changes in the whole-genome characteristics of both PRRSV-1 and PRRSV-2 in China, which may compromise the accuracy of previous detection methods. Herein, based on the current whole-genome characteristics and a comprehensive sequence database of Chinese PRRSV-1 and PRRSV-2, we identified conserved and specific genes for both viruses and designed corresponding primers and probes. After systematic optimization and evaluation, we developed a duplex real-time RT-qPCR for simultaneously identifying and differentiating PRRSV-1 and PRRSV-2, along with two simplex quantitative RT-PCRs for viral load measurement. To assess the performance of the duplex real-time RT-qPCR, a comprehensive sample repository was established to refine its positive criterion, evaluate its specificity and inclusivity, and compare its detection capacity with that of three commercial kits. The evaluation demonstrated that a positive result for both PRRSV-1 and PRRSV-2 channels was defined as an S-shaped amplification curve with a Ct value ≤ 36.0, while a suspected positive result was characterized by an S-shaped amplification curve with a Ct value greater than 36.0 but not exceeding 37.5. Samples exhibiting a Ct value exceeding 37.5 were classified as negative. Moreover, the method successfully detected diverse PRRSV-1 and PRRSV-2 strains, accurately differentiated between the two types of viruses, and exhibited higher inclusivity for PRRSV-1 and better differentiation capability between PRRSV-1 and PRRSV-2 than three commercial kits. For the two simplex quantitative RT-PCRs, validation using sera from pigs infected with multiple PRRSV-1 and PRRSV-2 strains showed that no viral RNA was detected at 0 dpi, while the expected viral load was successfully quantified between 3 and 21 dpi. Overall, the three developed methods can serve as effective tools for the detection, discrimination, and quantification of PRRSV-1 and PRRSV-2 strains circulating in China.

Keywords: PRRSV; detection and quantification; differential diagnosis; genomic variation; real-time RT-qPCR.