数字聚合酶链反应
生物
实时聚合酶链反应
聚合酶链反应
烟草疫霉
病菌
分子生物学
计算生物学
疫霉菌
遗传学
基因
植物
作者
Josefa Blaya,Eva Lloret,Ana B Santísima‐Trinidad,Margarita Ros,Juan Antonio Pascual
摘要
Currently, real-time polymerase chain reaction (qPCR) is the technique most often used to quantify pathogen presence. Digital PCR (dPCR) is a new technique with the potential to have a substantial impact on plant pathology research owing to its reproducibility, sensitivity and low susceptibility to inhibitors. In this study, we evaluated the feasibility of using dPCR and qPCR to quantify Phytophthora nicotianae in several background matrices, including host tissues (stems and roots) and soil samples.In spite of the low dynamic range of dPCR (3 logs compared with 7 logs for qPCR), this technique proved to have very high precision applicable at very low copy numbers. The dPCR was able to detect accurately the pathogen in all type of samples in a broad concentration range. Moreover, dPCR seems to be less susceptible to inhibitors than qPCR in plant samples. Linear regression analysis showed a high correlation between the results obtained with the two techniques in soil, stem and root samples, with R(2) = 0.873, 0.999 and 0.995 respectively.These results suggest that dPCR is a promising alternative for quantifying soil-borne pathogens in environmental samples, even in early stages of the disease.
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