Résumé
Transcriptional networks operate dynamically in vivo, but capturing and modeling these systems is an experimental and computational challenge. Here, we focus on the new biology revealed by nitrogen (N) regulatory networks in plants, presenting the dimension of how N-signals operate over time, dose and in interaction with other key nutrients. Our exploration of the 4th dimension in system biology – time – uncovered a time-dependent cascade of cis-regulatory elements and transcription factors, triggering major transcriptional response and genome-wide reprogramming of N regulatory networks. We used a machine learning model to uncover gene regulatory networks (GRNs) that predict a hierarchy of transcription factors in a time regulatory cascade associated with N-signaling.We further exploited systems biology approaches to study the genome-wide effects of N-dosage and nutrient interactions. In now classic experiments on plant nutrition from 1962, Murashige and Skoog (MS) showed that specific combinations of N-dose (nitrogen) with P (phosphorus) and K (potassium) could lead to an increase in biomass under low N input, “for unknown reasons”. We uncovered the molecular basis for this response using RNA-seq in Arabidopsis. Using an ANCOVA model, we showed that 10% of the Arabidopsis genome is controlled by N-dose interacting with PK signals in both leaf and root organs. This analysis has identified key transcription factor “hubs”, focusing on N-dose and N-PK interaction markers that control root foraging strategies and N-dependent changes in biomass.In conclusion, our research in the systems biology of nitrogen networks has uncovered critical network “hubs” implicated in mediating N-responses over time, dose and PK interactions. We explore the role of these components in nitrogen use efficiency in plants, and their potential benefits for reducing energy and environmental costs of N-fertilizer use in agriculture.