Early blight (EB) disease, caused mainly by Alternaria solani, is an economic threat to potato and tomato production worldwide. Thus, accurate and sensitive detection of the fungal pathogen of this disease in plants at the early infection stage is important for forecasting EB epidemics. In this study, we developed an RNA-based method that enables highly accurate and sensitive A. solani detection in a whole potato leaf at a single spore level based on quantitative real-time polymerase chain reaction (qPCR). We discovered jg1677, a highly expressed gene whose full-length coding sequence is very specific for A. solani, by analyzing A. solani transcripts isolated from enhanced high throughput transcriptome of infected potato leaves by A. solani and using the National Center for Biotechnology Information’s basic local alignment search tool. The specificity of the primers derived from jg1677 was determined using 22 isolates of common potato pathogens, including seven Alternaria isolates. Detecting jg1677 transcripts with qPCR is 1,295 times more sensitive than detecting genomic DNA. In addition, the expression pattern of jg1677 at different infection stages was determined by qPCR. What is more, jg1677 was expressed relatively stable between 15 and 35°C in infected leaves, and its expression was virtually unaffected in isolated leaves left at room temperature for 24 h. Our work provides a much more sensitive and accurate method compared to conditional DNA-based ones, permitting a very early diagnosis of EB and lowering the risk of EB epidemics.

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