A multi-layered regulatory model uncovers the central role of OsPRR37 in coordinating multiple agronomic traits

Background: The plant circadian clock is crucial for regulating developmental and metabolic processes, enabling crops to adapt to environmental changes and maintain high productivity. In rice, the clock gene OsPRR37 plays a pivotal role in photoperiod sensitivity and the regulation of yield-related traits. However, the complete regulatory network of OsPRR37 remains largely unexplored. Results: This study utilized an integrated multi-omics approach, combining transcriptome profiling, DNA affinity purification sequencing (DAP-seq), and protein–protein interaction (PPI) mapping to construct a multi-layered regulatory model of OsPRR37 . CRISPR/Cas9 knockout lines showed significant changes in flowering time, plant height, panicle architecture, and spikelet number. Transcriptome analysis associated OsPRR37 with pathways related to photosynthesis, carbohydrate metabolism, and stress responses. Comparative analysis of knockout and overexpression datasets identified 454 candidate target genes exhibiting inverse expression patterns, including regulators of flowering and chlorophyll biosynthesis. DAP-seq revealed 1,679 high-confidence DNA-binding sites, with nine genes identified as direct targets, six of which contained conserved motifs associated with cytokinin signaling, inflorescence architecture, and meristem determinacy. PPI mapping through a yeast two-hybrid screen identified 26 interacting proteins, including OsGlyRS3 and OsSnRK1A, which are involved in flowering, sugar signaling, chloroplast development, and hormone metabolism. Structural modeling suggested that OsGlyRS3 may stabilize OsPRR37 protein complexes, while OsSnRK1A could modulate its DNA-binding capacity under sugar-deficient conditions. Conclusions: The findings establish OsPRR37 as a central regulatory hub that coordinates flowering, energy metabolism, chloroplast function, and stress adaptation through a hierarchical network comprising a Modulatory Layer of protein interactors, a Direct Target Layer of DNA-bound genes, an Indirect Coherent Layer of transcriptional cascades, and a Diffuse Response Layer encompassing broad metabolic outputs. This model provides a comprehensive framework for understanding how OsPRR37 integrates circadian signals to control multiple agronomic traits and offers valuable targets for breeding climate-resilient, high-yielding rice varieties.