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Porcine Reproductive and Respiratory Virus (PRRSV) and Porcine Circovirus Type 2 (PCV2) are both viruses which cause significant economic and production losses to the swine industry around the world. The gold standard for monitoring these viruses is real-time PCR. Sequencing assays are also used to keep track of the epidemiology of these viruses. The work presented in this thesis aims to examine the repeatability of these types of assays with various concentrations of virus and within common diagnostic sample types. The repeatability of real-time PCR assays for PRRSV and PCV2 was examined using clinical specimens of various sample types which were submitted to the Iowa State University (ISU) Veterinary Diagnostic Laboratory (VDL). This was accomplished by creating a dilution series for each virus and for each of the specimen types: viral isolate, lung homogenate, serum, and oral fluids. These samples were diluted to targeted Cq ranges of 31-32, 32-33, 33-34, 34-35, 35-36, 36-37, 37-38, 38-39, 39-40. The dilutions were performed into negative material of the same sample matrix as the clinical specimen. The nucleic acids were then extracted in triplicate. Ten PRRSV RT-qPCR assays were performed from each extract for each sample matrix, and 15 qPCR reactions from each for PCV2. The repeatability was then determined as a percentage of the positive results from each group. Repeatability was also evaluated based on the cutoff of 40 or 37 cycles for PRRSV, and 40 or 35 cycles for PCV2. The repeatability of a sequencing assay for PRRSV open reading frame (ORF) 5 was also evaluated in this work. A similar methodology used to examine the real-time assays was used to evaluate the sequencing assay. The samples were diluted to different targeted Cq range of 29-30, 30-31, 31-32, 32-33, 33-34, 34-35, 35-36, 36-37. Five amplification PCRs were performed from each extract. Amplification product was then sequenced via Sanger sequencing. The sequencing

Repeatability of diagnostic real-time PCR and sequencing at various concentrations within different sample matrices