Rapid plant immune responses in the appropriate cells are needed for effective defense against pathogens.Although transcriptome analysis is often used to describe overall immune responses,collection of transcriptome d...Rapid plant immune responses in the appropriate cells are needed for effective defense against pathogens.Although transcriptome analysis is often used to describe overall immune responses,collection of transcriptome data with sufficient resolution in both space and time is challenging.We reanalyzed public Arabidopsis time-course transcriptome data obtained after low-dose inoculation with a Pseudomonas syringae strain expressing the effector AvrRpt2,which induces effector-triggered immunity in Arabidopsis.Double-peak time-course patterns are prevalent among thousands of upregulated genes.We implemented a multicompartment modeling approach to decompose the double-peak pattern into two single-peak patterns for each gene.The decomposed peaks reveal an“echoing”pattern:the peak times of the first and second peaks correlate well across most upregulated genes.We demonstrated that the two peaks likely represent responses of two distinct cell populations that respond either cell autonomously or indirectly to AvrRpt2.Thus,the peak decomposition has extracted spatial information from the time-course data.The echoing pattern also indicates a conserved transcriptome response with different initiation times between the two cell populations despite different elicitor types.A gene set highly overlapping with the conserved gene set is also upregulated with similar kinetics during pattern-triggered immunity.Activation of a WRKY network via different entry-point WRKYs can explain the similar but not identical transcriptome responses elicited by different elicitor types.We discuss potential benefits of the properties of the WRKY activation network as an immune signaling network in light of pressure from rapidly evolving pathogens.展开更多
基金supported by grants from the National Science Foundation(grant nos.MCB-0918908 and MCB-1518058 to F.K.and C.L.M.and IOS1645460 to F.K.)a grant from the United States Department of Agriculture-National Institute of Food and Agriculture to F.K.(grant no.2020-67013-31187)a grant from Ajinomoto Co.,Inc.to F.K.We thank the Minnesota Supercomputing Institute for their computing resources.We thank Tatsuya Nobori for information on the gene symbols in his snRNA-seq data.
文摘Rapid plant immune responses in the appropriate cells are needed for effective defense against pathogens.Although transcriptome analysis is often used to describe overall immune responses,collection of transcriptome data with sufficient resolution in both space and time is challenging.We reanalyzed public Arabidopsis time-course transcriptome data obtained after low-dose inoculation with a Pseudomonas syringae strain expressing the effector AvrRpt2,which induces effector-triggered immunity in Arabidopsis.Double-peak time-course patterns are prevalent among thousands of upregulated genes.We implemented a multicompartment modeling approach to decompose the double-peak pattern into two single-peak patterns for each gene.The decomposed peaks reveal an“echoing”pattern:the peak times of the first and second peaks correlate well across most upregulated genes.We demonstrated that the two peaks likely represent responses of two distinct cell populations that respond either cell autonomously or indirectly to AvrRpt2.Thus,the peak decomposition has extracted spatial information from the time-course data.The echoing pattern also indicates a conserved transcriptome response with different initiation times between the two cell populations despite different elicitor types.A gene set highly overlapping with the conserved gene set is also upregulated with similar kinetics during pattern-triggered immunity.Activation of a WRKY network via different entry-point WRKYs can explain the similar but not identical transcriptome responses elicited by different elicitor types.We discuss potential benefits of the properties of the WRKY activation network as an immune signaling network in light of pressure from rapidly evolving pathogens.
