Abstract

The increased occurrence of triazole fungicide resistant strains of Blumeria graminis f. sp. hordei (Bgh) is an economic concern for the barley industry in Australia and elsewhere. High levels of resistance to triazoles in the field are caused by two separate point mutations in the Cyp51 gene, Y136F and S509T. Early detection of these mutations arising in pathogen field populations is important as this allows time for changes in fungicide practices to be adopted, thus mitigating potential yield losses due to fungicide failure and preventing the resistance from becoming dominant. A digital PCR (dPCR) assay has been developed for the detection and quantification of the Y136F and S509T mutations in the Bgh Cyp51 gene. Mutation levels were quantifiable as low as 0.2% in genomic DNA extractions and field samples. This assay was applied to the high throughput screening of Bgh field and bait trial samples from barley growing regions across Australia in the 2015 and 2016 growing seasons and identified the S509T mutation for the first time in the Eastern states of Australia. This is the first report on the use of digital PCR technology for fungicide resistance detection and monitoring in agriculture. Here we describe the potential application of dPCR for the screening of fungicide resistance mutations in a network of specifically designed bait trials. The combination of these two tools constitute an early warning system for the development of fungicide resistance that allows for the timely adjustment of management practices.

Highlights

  • The management of fungicide resistance has become a major preoccupation of fungicide manufacturers, regulatory authorities and growers in the last two to three decades

  • We determined that digital PCR (dPCR) can accurately and sensitively measure the level of two mutations in the Cyp51 gene that confer resistance to demethylase inhibitor (DMI) fungicides (Y136F and S509T) in Blumeria graminis f. sp. hordei (Bgh) samples collected from the field

  • Our system of dPCR combined with baiting trials is an especially powerful tool for two reasons: (i) the use of baiting trials allows for enrichment of the mutant population and dPCR can quantify mutations down to 0.2%; allowing us to identify cases of resistance quickly with unprecedented sensitivity and accuracy; and (ii) baiting trials do not portray an accurate measure of mutation field frequency, these results can quickly pinpoint resistance hot spots and allow us to target field sampling, saving on time and resources

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Summary

Introduction

The management of fungicide resistance has become a major preoccupation of fungicide manufacturers, regulatory authorities and growers in the last two to three decades. A substantial body of research has evaluated the methods that can be used to prevent or delay the evolution of a resistant population of a pathogen (van den Bosch et al, 2011, 2014) These methods include the withdrawal or substitution of the affected fungicide class with another, mixing or alternating two or more modes of action and the use of genetically resistant crops or rotations. Methods for identifying resistance in the field involved collecting samples from diseased crops, isolating the fungus in pure culture and conducting fungicide sensitivity bioassays (Ishii and Hollomon, 2015). These phenotyping methods are time consuming, labor intensive and the efficiency of detecting resistance is low because results are based on a limited number of isolates

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