Quantitative Detection and Monitoring of Colletotrichum siamense in Rubber Trees Using Real-Time PCR

Abstract

Colletotrichum siamense is one of the most important pathogens of rubber trees in Asia. The proper detection and quantification of C. siamense populations in rubber trees are of importance for monitoring the epidemics of the disease. In this study, we developed an internal transcribed spacer-based real-time PCR method to efficiently detect C. siamense infecting rubber trees, which reliably detected as little as 100 fg of genomic DNA, 100 copies of target DNA, and 20 conidia. The real-time PCR protocol recognized all C. siamense isolates collected from three provinces in China, whereas no amplification was observed with the rubber tree and its other pathogens. Detection and quantification of C. siamense were performed in artificially and naturally infected rubber leaves. We could still detect C. siamense in plant mixes, of which only 0.0001% of the tissue was infected. An accumulation of C. siamense DNA was observed during the whole infection process at all three leaf phenological stages, suggesting that the real-time PCR method can be used to monitor C. siamense development in rubber trees. Finally, the method allowed the detection of C. siamense in naturally infected and symptomless leaves of rubber trees in the fields. Compared with earlier detection methods, the real-time PCR method is more specific and more sensitive, and it will be of great use for studies aiming to gain a better understanding of the epidemiology of Colletotrichum leaf disease, as well as the prediction of disease risk and proposals to control it.