Abstract

Cross-regulation between hormone response pathways is indispensable for plant growth because it enables plants to respond to diverse environmental information. Hundreds of transcription factors are involved, reprogramming gene expression. Determining how these transcription factors influence dynamic gene expression patterns can provide base information to manipulate plant-environment interactions. We have comprehensively characterized transcription factor activity during plant hormone responses and generated dynamic transcriptional regulatory models to explain how signals are integrated from multiple pathways. We analysed transcriptome dynamics of seedlings following stimulation of six hormone pathways and identified the target genes of 14 key hormone transcription factors. Using these data we identified hub genes targeted by multiple transcription factors and characterized their properties in hormone transcriptional networks. We then reconstructed hormone signalling pathway models by integrating dynamic gene expression data with target gene information from hundreds of transcription factors and thousands of protein-protein interactions. Using these we identified transcriptional regulatory properties that are common and unique across hormones. We also identified a group of kinases that may act as core cross-regulatory hubs between hormone signalling pathways.

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