Thierry C. Marcel

Monitoring virulent strains within pathogen populations is crucial to improve host resistance deployment strategies. Such monitoring increasingly involves field pathogenomics studies of molecular polymorphisms in pathogen genomes based on high‐throughput screening technologies. However, it is not always straightforward to predict virulence phenotypes from these polymorphisms, and in planta phenotyping remains necessary. We developed a method for ‘bulk phenotyping on checkerboard microcanopies of wheat near‐isogenic lines’ (BPC) for estimating the frequency of virulence against a resistance gene in mixed populations of the fungal pathogen Zymoseptoria tritici , the causal agent of Septoria tritici blotch (STB) in wheat, without the need for strain‐by‐strain pathogen phenotyping. Our method involves the uniform inoculation of a microcanopy of two wheat lines—one with the target resistance gene and the other without it—with a multistrain mixture of isolates representative of the population to be characterized, followed by the differential quantification of infection points (lesions). Using Stb16q , a wheat resistance gene that has recently broken down in Europe, we found a robust correlation between the ratio of the mean number of lesions on each wheat line and the frequency of virulent strains in the inoculum. Using pairs of virulent and avirulent strains, as well as synthetic populations consisting of 10 virulent strains and 10 avirulent strains mixed in different proportions, we validated the principle of the method and established standard curves at virulence frequencies close to those observed in natural conditions. We discuss the potential of this method for virulence monitoring in combination with molecular methods.

Puccinia triticina is a highly damaging wheat pathogen. The efficacy of leaf rust control by genetic resistance is mitigated by the adaptive capacity of the pathogen, expressed as changes in its virulence combinations (pathotypes). An extensive P . triticina population survey has been carried out in France over the last 30 years, describing the evolutionary dynamics of this pathogen in response to cultivar deployment. We analysed the data set for the 2006–2016 period to determine the relationship between the Lr genes in the cultivars and virulence in the pathotypes. Rust populations were dominated by a small number of pathotypes, with variations in most of the virulence frequencies related to the corresponding Lr gene frequencies in the cultivated landscape. Furthermore, the emergence and spread of a new virulence matched the introduction and use of the corresponding Lr gene ( Lr28 ), confirming that the deployment of qualitative resistance genes is an essential driver of evolution in P . triticina populations. However, principal component analysis (PCA) revealed that certain pathotype–cultivar associations cannot be explained solely by the distribution of Lr genes in the landscape. This conclusion is supported by the predominance of a few pathotypes on some cultivars, with the persistence of several other compatible pathotypes at low frequencies. Specific interactions are not, therefore, sufficient to explain the distribution of virulence in rust populations. The hypothesis that quantitative interactions between P . triticina populations and bread wheat cultivars—based on differences in aggressiveness—is also a driver of changes in pathotype frequencies deserves further investigation.