Skip to main content
ARS Home » Midwest Area » St. Paul, Minnesota » Cereal Disease Lab » Research » Publications at this Location » Publication #285467

Research Project: CEREAL RUST FUNGI: GENETICS, POPULATION BIOLOGY, AND HOST-PATHOGEN INTERACTIONS

Location: Cereal Disease Lab

Title: Evaluation of a SNP-based qPCR identification system for the Ug99 race group using field collections of Puccinia graminis f. sp. tritici in South Africa

Author
item VISSER, BOTMA - University Of The Free State
item Szabo, Les
item TEREFE, T - Agricultural Research Council Of South Africa
item PRETORIUS, ZACHARY - University Of The Free State

Submitted to: Meeting Abstract
Publication Type: Abstract Only
Publication Acceptance Date: 8/28/2012
Publication Date: 8/28/2012
Citation: Visser, B., Szabo, L.J., Terefe, T., Pretorius, Z. 2012. Evaluation of a SNP-based qPCR identification system for the Ug99 race group using field collections of Puccinia graminis f. sp. tritici in South Africa. Meeting Abstract. p. 239.

Interpretive Summary:

Technical Abstract: Annual surveys aim to monitor the distribution and composition of the local stem rust population within South Africa. The number of isolates that are processed is limited due to physical and financial constraints and the problem of non-viable spores. An accurate DNA based identification method would increase and expedite the number of isolates that are screened. A two-stage SNP based qPCR identification system for individual members of the Ug99 race group was recently developed by the USDA-ARS Cereal Disease Laboratory. The first stage distinguishes between Ug99 lineage and non-Ug99 linage isolates, while the second allows for the accurate identification of individual Ug99 races. Since four of the eight described Ug99 variants have been detected within Southern Africa, the efficiency of this identification system was evaluated using field samples of stem rust collected during recent surveys in South Africa. Using infected wheat stem tissue as DNA source, randomly selected isolates were identified with qPCR and their identities compared to those determined by traditional race analysis. Preliminary results have indicated an excellent correlation between the two methods.