Accurate Strand-Specific Quantification of Viral RNA

The presence of full-length complements of viral genomic RNA is a hallmark of RNA virus replication within an infected cell. As such, methods for detecting and measuring specific strands of viral RNA in infected cells and tissues are important in the study of RNA viruses. Strand-specific quantitative real-time PCR (ssqPCR) assays are increasingly being used for this purpose, but the accuracy of these assays depends on the assumption that the amount of cDNA measured during the quantitative PCR (qPCR) step accurately reflects amounts of a specific viral RNA strand present in the RT reaction. To specifically test this assumption, we developed multiple ssqPCR assays for the positive-strand RNA virus o'nyong-nyong (ONNV) that were based upon the most prevalent ssqPCR assay design types in the literature. We then compared various parameters of the ONNV-specific assays. We found that an assay employing standard unmodified virus-specific primers failed to discern the difference between cDNAs generated from virus specific primers and those generated through false priming. Further, we were unable to accurately measure levels of ONNV (−) strand RNA with this assay when higher levels of cDNA generated from the (+) strand were present. Taken together, these results suggest that assays of this type do not accurately quantify levels of the anti-genomic strand present during RNA virus infectious cycles. However, an assay permitting the use of a tag-specific primer was able to distinguish cDNAs transcribed from ONNV (−) strand RNA from other cDNAs present, thus allowing accurate quantification of the anti-genomic strand. We also report the sensitivities of two different detection strategies and chemistries, SYBR® Green and DNA hydrolysis probes, used with our tagged ONNV-specific ssqPCR assays. Finally, we describe development, design and validation of ssqPCR assays for chikungunya virus (CHIKV), the recent cause of large outbreaks of disease in the Indian Ocean region

Gene Expression Signature in Peripheral Blood Detects Thoracic Aortic Aneurysm

BACKGROUND: Thoracic aortic aneurysm (TAA) is usually asymptomatic and associated with high mortality. Adverse clinical outcome of TAA is preventable by elective surgical repair; however, identifying at-risk individuals is difficult. We hypothesized that gene expression patterns in peripheral blood cells may correlate with TAA disease status. Our goal was to identify a distinct gene expression signature in peripheral blood that may identify individuals at risk for TAA. METHODS AND FINDINGS: Whole genome gene expression profiles from 94 peripheral blood samples (collected from 58 individuals with TAA and 36 controls) were analyzed. Significance Analysis of Microarray (SAM) identified potential signature genes characterizing TAA vs. normal, ascending vs. descending TAA, and sporadic vs. familial TAA. Using a training set containing 36 TAA patients and 25 controls, a 41-gene classification model was constructed for detecting TAA status and an overall accuracy of 78+/-6% was achieved. Testing this classifier on an independent validation set containing 22 TAA samples and 11 controls yielded an overall classification accuracy of 78%. These 41 classifier genes were further validated by TaqMan real-time PCR assays. Classification based on the TaqMan data replicated the microarray results and achieved 80% classification accuracy on the testing set. CONCLUSIONS: This study identified informative gene expression signatures in peripheral blood cells that can characterize TAA status and subtypes of TAA. Moreover, a 41-gene classifier based on expression signature can identify TAA patients with high accuracy. The transcriptional programs in peripheral blood leading to the identification of these markers also provide insights into the mechanism of development of aortic aneurysms and highlight potential targets for therapeutic intervention. The classifier genes identified in this study, and validated by TaqMan real-time PCR, define a set of promising potential diagnostic markers, setting the stage for a blood-based gene expression test to facilitate early detection of TAA