Transcriptome profiling in susceptible and tolerant rubber tree clones in response to cassiicolin Cas1, a necrotrophic effector from Corynespora cassiicola.

Corynespora cassiicola, a fungal plant pathogen with a large host range, causes important damages in rubber tree (Hevea brasiliensis), in Asia and Africa. A small secreted protein named cassiicolin was previously identified as a necrotrophic effector required for the virulence of C. cassiicola in specific rubber tree clones. The objective of this study was to decipher the cassiicolin-mediated molecular mechanisms involved in this compatible interaction. We comparatively analyzed the RNA-Seq transcriptomic profiles of leaves treated or not with the purified cassiicolin Cas1, in two rubber clones: PB260 (susceptible) and RRIM600 (tolerant). The reads were mapped against a synthetic transcriptome composed of all available transcriptomic references from the two clones. Genes differentially expressed in response to cassiicolin Cas1 were identified, in each clone, at two different time-points. After de novo annotation of the synthetic transcriptome, we analyzed GO enrichment of the differentially expressed genes in order to elucidate the main functional pathways impacted by cassiicolin. Cassiicolin induced qualitatively similar transcriptional modifications in both the susceptible and the tolerant clones, with a strong negative impact on photosynthesis, and the activation of defense responses via redox signaling, production of pathogenesis-related protein, or activation of the secondary metabolism. In the tolerant clone, transcriptional reprogramming occurred earlier but remained moderate. By contrast, the susceptible clone displayed a late but huge transcriptional burst, characterized by massive induction of phosphorylation events and all the features of a hypersensitive response. These results confirm that cassiicolin Cas1 is a necrotrophic effector triggering a hypersensitive response in susceptible rubber clones, in agreement with the necrotrophic-effector-triggered susceptibility model.