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United States Department of Agriculture

Agricultural Research Service

Title: Alternative approaches for measuring oat crown rust to improve resistance mapping

Authors
item Bonman, John
item Jackson, Eric
item Acevedo, Maricelis

Submitted to: Plant and Animal Genome Conference
Publication Type: Proceedings
Publication Acceptance Date: October 1, 2007
Publication Date: N/A

Technical Abstract: Precise and accurate disease assessment can improve mapping of QTL conferring resistance. We have used two new methods to assess crown rust resistance in the Ogle/TAM O-301 oat mapping population: 1) single-race field trials in isolation chambers and 2) a molecular assay to measure the development of Puccinia coronata within oat tissue by estimating fungal DNA content via quantitative PCR (q-PCR). The field technique uses isolation chambers to promote uniform disease development in adult plants with single crown rust isolates. The method eliminates confounding effects of multiple races within an experiment and with it we have identified loci that were found using more laborious multiple location trials. With q-PCR differences between resistant, partially resistant, and susceptible genotypes were more distinct when compared to either visual estimations or digital image analysis of the same tissues. q-PCR enabled mapping of a major gene locus more precisely than either visual disease assessment or analysis of digital images (i.e. lower standard deviation of the distance between a fixed marker and the r gene). Furthermore, the method allowed detection of resistance QTL more precisely than visual assessment (sharper peak and better correspondence to two-point linkage analysis) and identified QTL that were not discernable with other assessment methods. Recently, the efficiency of the q-PCR method has been improved by simultaneously measuring fungal DNA relative to host DNA. These new methods have improved characterization and mapping of resistance in the Ogle/TAM O 301 population and will be verified further in additional oat populations.

Last Modified: 4/18/2014