In-silico prediction of RT-qPCR-high resolution melting for broad detection of emaraviruses

Abstract

Twenty-four species of RNA viruses contain members infecting economically important crops that are classified within the genus Emaravirus, family Fimoviridae. There are at least two 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. High-resolution melting (HRM) has shown to be reliable for the detection, discrimination, and diagnosis of several diseases of plants, animals, and humans. This research aimed to explore the ability to predict HRM outputs coupled to reverse transcription-quantitative polymerase chain reaction (RT-qPCR). To approach this goal a pair of degenerate genus-specific primers were designed for endpoint RT-PCR and RT-qPCR-HRM and the species in the genus Emaravirus were selected to framework the development of the assays. Both nucleic acid amplification methods were able to detect in-vitro several members of seven Emaravirus species with sensitivity up to one fg of cDNA. Specific parameters for in-silico prediction of the melting temperatures of each expected emaravirus amplicon are compared to the data obtained in-vitro. A very distinct isolate of the High Plains wheat mosaic virus was also detected. The high-resolution DNA melting curves of the RT-PCR products predicted in-silico using uMeltSM allowed saving time while designing and developing the RT-qPCR-HRM assay since the approach avoided extensive searching for optimal HRM assay regions and rounds of HRM tests in-vitro for optimization. The resultant assay provides sensitive detection and reliable diagnosis for potentially any emaravirus, including new species or strains.