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• W4386227181 abstract "Plant defense responses involve several biological processes that allow plants to fight against pathogenic attacks. How these different processes are orchestrated within organs and depend on specific cell types is poorly known. Here, using scRNA-seq technology on three independent biological replicates, we identified several cell populations representing the core transcriptional responses of wild-type Arabidopsis leaves inoculated with the bacterial pathogen Pseudomonas syringae DC3000. Among these populations, we retrieved major cell types of the leaves (mesophyll, guard, epidermal, companion and vascular S cells) to which we could associate characteristic transcriptional reprogramming and regulators, thereby specifying different cell-type responses to the pathogen. Further analyses of transcriptional dynamics, based on inference of cell trajectories, indicated that the different cell types, in addition to their characteristic defense responses, can also share similar modules of gene reprogramming, uncovering a ubiquitous antagonism between immune and susceptible processes. Moreover, it appears that the defense responses of vascular S cells, epidermal cells and mesophyll cells can evolve along two separate paths, one converging towards an identical cell fate, mostly characterized by lignification and detoxification functions. As this divergence does not correspond to the differentiation between immune and susceptible cells, we speculate that this might reflect the discrimination between cell-autonomous and non-cell-autonomous responses. Altogether our data provide an upgraded framework to describe, explore and explain the specialization and the coordination of plant cell responses upon pathogenic challenge." @default.
• W4386227181 created "2023-08-29" @default.
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• W4386227181 date "2023-09-01" @default.
• W4386227181 modified "2023-10-12" @default.
• W4386227181 title "Cell specialization and coordination in Arabidopsis leaves upon pathogenic attack revealed by scRNA-seq." @default.
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• W4386227181 doi "https://doi.org/10.1016/j.xplc.2023.100676" @default.
• W4386227181 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/37644724" @default.
• W4386227181 hasPublicationYear "2023" @default.
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