Exploring in-silico prediction for the development of a RT-qPCR-high resolution melting assay for the broad detection of emaraviruses.

High-resolution melting (HRM) has shown to be reliable for the detection, discrimination, and diagnosis of several diseases of plants, animals, and humans. The aim of this research was to explore the ability to predict HRM outputs when coupled to reverse transcription quantitative polymerase chain reaction (RT-qPCR). This research used the species in the Emaravirus genus as model to framework the development of genus-specific RT-qPCR-HRM assays. A pair of degenerate genus-specific primers were designed for use in endpoint RT-PCR and RT-qPCR-HRM detection of emaraviruses. Eleven species of RNA viruses infecting economically important crops are classified within the genus Emaravirus, family Fimoviridae. There are at least fifteen other non-classified species that may be added. Some of these viruses are spreading rapidly and cause economically important diseases on several crops, raising a need for a sensitive diagnostic technique for taxonomic and quarantine purposes. RT-PCR and RT-qPCR-HRM were able to detect seven emaravirus species in-vitro with sensitivity up to one fg of cDNA. Specific parameters for prediction in-silico of the melting temperatures of each expected emaravirus amplicon are provided and compared to the data obtained in-vitro. A very distinct isolate of the High Plains wheat mosaic virus was also detected. The prediction in-silico of fluorescence of high-resolution DNA melting curves of predicted RT-PCR products using uMelt speeded the design and development of RT-qPCR-HRM assay. This approach avoided rounds of HRM tests in-vitro when searching for the optimal regions that provides accurate diagnosis. The resultant assay provided sensitive detection and reliable diagnosis for potentially any emaravirus, including new species or strains.