New species of Phytophthora such as Phytophthora ramorum, P. kernoviae and P. quercina together with P. citricola are plant pathogens which impact on forest health, natural ecosystem stability and international trade. A real-time multiplex PCR approach based on TaqMan PCR was developed to simultaneously identify and detect these four Phytophthora species. Specific primers and probes labelled with FAM (P. ramorum), Yakima Yellow(P. kernoviae), Rox (P. citricola) and Cy5 (P. quercina) were designed in different regions of the ras-related protein (Ypt1) gene. A new set of Black Hole Quenchers (BHQ), which dissipate energy as heat rather than fluorescence, were utilized. The method proved to be highly specific in tests with target DNA from 72 Phytophthora isolates (35 species). For all pathogens, the detection limit was 100 fg of target DNA and was not improved utilizing a nested approach to provide a first round of amplification with Phytophthora spp.-specific primers. Cycle threshold (Ct)values were linearly correlated with the concentration of the target DNA (correlation coefficients ranged from 0.947 to 0.996) and were not affected by the presence of plant extracts, indicating the appropriateness of the method for qualitative and quantitative analyses. Two universal primers and a TaqMan probe were also developed to evaluate the quality and quantity of extracted DNA and to avoid false negatives. The reliability of the entire procedure was assessed using both artificially and naturally infected leaves of a range of plant species. The method, combined with a rapid procedure for DNA extraction, proved to be rapid, reliable, sensitive and cost effective as multiple pathogens were detected within the same plant extract by using different primer/probe combinations.

Detection and quantification of P. ramorum, P. kernoviae, P. citricola and P. quercina in symptomatic leaves by multiplex real-time PCR / Schena, L; Hughes, Kjd; Cooke, Del. - In: MOLECULAR PLANT PATHOLOGY. - ISSN 1464-6722. - 7:(2006), pp. 365-379.

Detection and quantification of P. ramorum, P. kernoviae, P. citricola and P. quercina in symptomatic leaves by multiplex real-time PCR

SCHENA L
;
2006-01-01

Abstract

New species of Phytophthora such as Phytophthora ramorum, P. kernoviae and P. quercina together with P. citricola are plant pathogens which impact on forest health, natural ecosystem stability and international trade. A real-time multiplex PCR approach based on TaqMan PCR was developed to simultaneously identify and detect these four Phytophthora species. Specific primers and probes labelled with FAM (P. ramorum), Yakima Yellow(P. kernoviae), Rox (P. citricola) and Cy5 (P. quercina) were designed in different regions of the ras-related protein (Ypt1) gene. A new set of Black Hole Quenchers (BHQ), which dissipate energy as heat rather than fluorescence, were utilized. The method proved to be highly specific in tests with target DNA from 72 Phytophthora isolates (35 species). For all pathogens, the detection limit was 100 fg of target DNA and was not improved utilizing a nested approach to provide a first round of amplification with Phytophthora spp.-specific primers. Cycle threshold (Ct)values were linearly correlated with the concentration of the target DNA (correlation coefficients ranged from 0.947 to 0.996) and were not affected by the presence of plant extracts, indicating the appropriateness of the method for qualitative and quantitative analyses. Two universal primers and a TaqMan probe were also developed to evaluate the quality and quantity of extracted DNA and to avoid false negatives. The reliability of the entire procedure was assessed using both artificially and naturally infected leaves of a range of plant species. The method, combined with a rapid procedure for DNA extraction, proved to be rapid, reliable, sensitive and cost effective as multiple pathogens were detected within the same plant extract by using different primer/probe combinations.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/5497
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