Abstract
Nitrogen use efficiency (NUE) is a critical agronomic trait for sustainable cereal production, yet its underlying regulatory networks remain poorly understood. We employed a multi-omics integration framework combining transcriptomics, proteomics, and metabolomics data from rice, maize, and wheat under low and high nitrogen conditions. Using Bayesian network inference and graph-linked embedding, we reconstructed regulatory networks and identified key hub genes and metabolites associated with NUE. Our analysis revealed conserved modules involving nitrogen assimilation, amino acid metabolism, and carbon-nitrogen balance, with transcription factors such as NAC and bZIP families playing central roles. Integration of public ChIP-seq data further validated regulatory interactions. Cross-species comparison highlighted both common and species-specific regulatory elements. The study demonstrates that multi-omics integration can uncover complex regulatory networks and provides a roadmap for breeding nitrogen-efficient cereals.