Submitted to: Phytopathology
Publication Type: Abstract Only
Publication Acceptance Date: May 2, 2009
Publication Date: June 2, 2009
Citation: Schroeder, K.L., Okubara, P.A., Paulitz, T.C. 2009. Application of real-time PCR for quantification of soilborne pathogens. Phytopathology 99: S186. Technical Abstract: Soilborne pathogens can be particularly difficult to quantify. Unlike foliar diseases, symptoms caused by soilborne pathogens such as Pythium and Rhizoctonia spp. are not readily observable, making it difficult to estimate pathogen populations. Pythium and Rhizoctonia present an additional problem in cereal production systems. Rather than the diseases being caused by a single species of each genus, multiple species may be present in the same field and even on the same plant. In eastern Washington, the species prevalence and diversity of each of these pathogens can vary greatly from one region to another. Due to limitations of traditional agar media-based quantification methods, real-time PCR assays were developed for multiple species of Pythium and Rhizoctonia. Soils were collected over a large geographic region of eastern Washington in 2005, 2006, and 2007. Total DNA was extracted from these soils and species-specific primers for three species of Rhizoctonia and three to nine species of Pythium were used with a Roche LightCycler to quantify pathogen DNA in these soils. The prevalence of Pythium species is favored by higher precipitation zones. The diversity can also very greatly with as many as nine or as few as one species being detected in a single soil sample. Conversely, R. solani AG-8 is quantified in low amounts in the higher precipitation zones and favors areas with less than 300 mm of annual precipitation. Rhizoctonia oryzae is less affected by precipitation, being prevalent in most regions. This work has also revealed correlations between the presence of certain species of these necrotrophic root pathogens with specific host plants. For example, R. solani AG-2-1 is favored by rotations with brassica crops. Using these real-time PCR assays, disease risk models are being created to develop this procedure into a preplant tool for improved disease management.