Validation of multiplex PCR sequencing assay of SIV

Abstract

Abstract Background The generation of accurate and reproducible viral sequence data is necessary to understand the diversity present in populations of RNA viruses isolated from clinical samples. While various sequencing methods are available, they often require high quality templates and high viral titer to ensure reliable data. Methods We modified a multiplex PCR and sequencing approach to characterize populations of simian immunodeficiency virus (SIV) isolated from nonhuman primates. We chose this approach with the aim of reducing the number of required input templates while maintaining fidelity and sensitivity. We conducted replicate sequencing experiments using different numbers of quantified viral RNA (vRNA) or viral cDNA as input material. We performed assays with clonal SIVmac239 to detect false positives, and we mixed SIVmac239 and a variant with 24 point mutations (SIVmac239-24X) to measure variant detection sensitivity. Results We found that utilizing a starting material of quantified viral cDNA templates had a lower rate of false positives and increased reproducibility when compared to that of quantified vRNA templates. This study identifies the importance of rigorously validating deep sequencing methods and including replicate samples when using a new method to characterize low frequency variants in a population with a small number of templates. Conclusions Because the need to generate reproducible and accurate sequencing data from diverse viruses from low titer samples, we modified a multiplex PCR and sequencing approach to characterize SIV from populations from non-human primates. We found that increasing starting template numbers increased the reproducibility and decreased the number of false positives identified, and this was further seen when cDNA was used as a starting material. Ultimately, we highlight the importance of vigorously validating methods to prevent overinterpretation of low frequency variants in a sample.

Keywords

• SIV
• Multiplex PCR
• Deep sequencing
• SNV detection