bioRxivPlant BiologyPreprint
Transcriptional Dynamics of the Salicylic Acid Response and its Interplay with the Jasmonic Acid Pathway
R. Hickman, M. Pereira Mendes, M. C. Van Verk, A. J. H. Van Dijken, J. Di Sora, K. Denby, C. C. M. J. Pieterse, S. C. M. Van Wees
Abstract
The phytohormone salicylic acid (SA) is a central regulator of plant immunity. Antagonistic and synergistic actions between SA and other defense-associated hormones like jasmonic acid (JA) play key roles in determining the outcome of the plant immune response. To obtain a deeper understanding of SA-mediated transcriptional reprogramming and SA/JA crosstalk, we generated a high-resolution time series of gene expression from Arabidopsis leaves treated with SA alone and a combination of SA and methyl JA (MeJA), sampled at 14 time points over a 16-h period. We found that approximately one-third of the Arabidopsis genome was differentially expressed in response to SA, and temporal changes in gene expression could be partitioned into 45 distinct clusters of process-specific coregulated genes, linked to specific cis-regulatory elements and binding of transcription factors (TFs). Integration of our expression data with information on TF-DNA binding allowed us to generate a dynamic gene regulatory network model of the SA response, recovering known regulators and identifying novel ones. We found that 12% of SA-responsive genes and 69% of the MeJA-responsive genes exhibited antagonistic or synergistic expression levels in the combination treatment. Multi-condition co-clustering of the single- and combined-hormone expression profiles predicted underlying regulatory mechanisms in signal integration. Finally, we identified the TFs ANAC061 and ANAC090 as negative regulators of SA pathway genes and defense against biotrophic pathogens. Collectively, our data provide an unprecedented level of detail about transcriptional changes during the SA response and SA/JA crosstalk, serving as a valuable resource for systems-level network studies and functional plant defense studies.
- organism: Arabidopsis
- assay: bulk RNA-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: cell type annotation
- approach: statistical model
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