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Cell specialization and coordination in Arabidopsis leaves upon pathogenic attack revealed by scRNAseq

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DataCite Commons2025-05-16 更新2025-04-16 收录
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https://entrepot.recherche.data.gouv.fr/citation?persistentId=doi:10.57745/CKVGIN
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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 scRNAseq technology, we identified 18 distinct cell populations in wild-type Arabidopsis leaves inoculated with the hemibiotrophic pathogen Pseudomonas syringae DC3000. Among those, we retrieved major cell types of the leaves (mesophyl, guard, epidermial, companion and vascular S cells) to which we could associate characteristic transcriptional reprogramming, 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, allowing for instance vascular S cells, epidermal cells and mesophyl cells to converge towards an identical cell fate, mostly characterized by lignification and detoxification functions. Moreover, it appeared that defense responses of these three cell types can evolve along a second separate path. 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. this dataset contains the output of the CellRanger count command for the three samples of the project. They are the input for the analytical script provided at https://github.com/Bastien-mva/pipeline_seurat_monocle
提供机构:
Recherche Data Gouv
创建时间:
2023-07-17
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