Metabolic Atlas and Multi‐Omics Analysis of Maize Pericarp: Coordinated Regulatory Mechanism of Morphogenesis and Flavonoid Metabolism

The maize pericarp serves not only as a physical protective barrier of the seed but also as a critical functional interface involved in environmental response and physiological regulation. Systematic analysis of the metabolic basis of nutritional components and related metabolites in the maize pericarp is of great importance for quality improvement, nutrient fortification, and understanding crop adaptation to environmental changes. However, due to limitations in analytical techniques, current knowledge of the maize pericarp metabolome remains limited. In this study, UHPLC–MS/MS was employed to analyze the pericarp metabolome. A total of 12 and 9 classes of metabolites were identified in positive ion mode (POS) and negative ion mode (NEG), respectively, from which 52 significantly different metabolites were screened. Based on the core differential metabolites, a metabolic atlas of the pericarp was constructed, successfully classifying the tested population into three distinct subgroups with markedly different metabolic characteristics. By constructing an association network between metabolic and morphological phenotypes, we found that surface roughness parameters were most extensively linked with metabolites: both average roughness (Ra) and root mean square roughness (Rq) were significantly positively correlated with l ‐histidine, whereas roughness skewness (Rsk) was significantly negatively correlated with flavonoids, proline, and other metabolites. These results suggest that micrometer‐scale morphological traits may be closely associated with the composition of secondary metabolites. Furthermore, genome‐wide association study (GWAS) identified a candidate gene, Zm00001d053872 , that may be associated with coordinated variation in pericarp roughness and flavonoid metabolism. This study established a quantitative analysis method for pericarp characteristics based on a metabolic atlas and deciphered the synergistic regulatory network between pericarp morphology and metabolism through a multi‐omics integration strategy, providing a theoretical basis for the genetic improvement of seed quality and pericarp‐related agronomic traits.