Fungal plant pathogens, such as Zymoseptoria tritici (formerly known as Mycosphaerella graminicola), secrete repertoires of effectors to facilitate infection or trigger host defence mechanisms. The discovery and functional characterization of effectors provides valuable knowledge that can contribute to the design of new and effective disease management strategies. Here, we combined bioinformatics approaches with expression profiling during pathogenesis to identify candidate effectors of Z. tritici. In addition, a genetic approach was conducted to map quantitative trait loci (QTLs) carrying putative effectors, enabling the validation of both complementary strategies for effector discovery. In planta expression profiling revealed that candidate effectors were up-regulated in successive waves corresponding to consecutive stages of pathogenesis, contrary to candidates identified by QTL mapping that were, overall, expressed at low levels. Functional analyses of two top candidate effectors (SSP15 and SSP18) showed their dispensability for Z. tritici pathogenesis. These analyses reveal that generally adopted criteria, such as protein size, cysteine residues and expression during pathogenesis, may preclude an unbiased effector discovery. Indeed, genetic mapping of genomic regions involved in specificity render alternative effector candidates that do not match the aforementioned criteria, but should nevertheless be considered as promising new leads for effectors that are crucial for the Z. tritici-wheat pathosystem.
Keywords: QTL mapping; Zymoseptoria tritici; bioinformatics; effectors; knock-out; septoria tritici blotch; wheat.
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