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.
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