Author
Duressa, DeChassa | |
Rauscher, Gilda | |
Mou, Beiquan | |
Hayes, Ryan | |
KOIKE, STEVEN - University Of California - Cooperative Extension Service | |
MARUTHACHALAM, KARUNAKARAN - University Of California | |
SUBBARAO, KRISHNA - University Of California | |
Klosterman, Steven |
Submitted to: Phytopathology
Publication Type: Abstract Only Publication Acceptance Date: 6/1/2011 Publication Date: 6/1/2011 Citation: Duressa, D.O., Rauscher, G.M., Mou, B., Hayes, R.J., Koike, S.T., Maruthachalam, K., Subbarao, K.V., Klosterman, S.J. 2011. Development of a qPCR assay for quantification of verticillium dahliae in spinach seed.Phytopathology. 101:S46. Interpretive Summary: Technical Abstract: Verticillium wilt, caused by the soilborne fungus Verticillium dahliae, is an important disease of lettuce and other specialty crops in the Salinas Valley of California. Although spinach is not affected by Verticillium wilt in commercial production, spinach seed infected with V. dahliae from locations in the U.S. Pacific Northwest and Europe and planted in Salinas Valley increases inoculum density and potentially introduces exotic strains that may contribute to Verticillium wilt epidemics. A sensitive, rapid and reliable method for quantification of the fungi in seed may help to curtail the spread of V. dahliae via spinach seed. The objective of this research is to develop a qPCR assay to detect and quantify V. dahliae in spinach seed. We employed Cyber Green detection methodology for qPCR, and conducted parallel NP10 plate assays to determine actual seed infection in multiple seed lots. The qPCR assay reliably detected V. dahliae in spinach seed, showing a sensitivity of detection of 20 infected seeds per 1000 (2% infection level). In two seed lots examined at infection levels ranging from approximately 0.5% to 75%, the relationship between percentage of seed infected and seed pathogen DNA content was highly significant (R2 > 0.97, p < 0.001). We are currently testing several seedlots to determine threshold qPCR parameters that can be used as a guide to predict the percent seed infected from seed pathogen DNA content. |