Hierarchical regulation of carbon-nitrogen allocation and kernel quality in maize: progress, challenges, and prospects for molecular breeding

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Maize ( Zea mays L.) is the cornerstone of global food security and serves as a major source of feed and industrial raw materials. However, synergistic improvement of kernel oil, starch and protein is restricted by inherent metabolic trade-offs. While the cause of these trade-offs is often attributed to competitive resources, they also reflect the complexity of interlinked regulatory pathways. This review presents a hypothesis-driven framework based on the ‘push-protect’ approach as a testable method for enhancing maize source-sink performance and kernel quality. The framework combines optimization of plant architecture to increase source capacity with a proposed SnRK1α-C200S substitution designed to test whether sink activity can be maintained under oxidative stress. To date, the C200S mutation has only been validated in vitro using Arabidopsis and thus in planta validation of its role in maize kernels is required. Additionally, this framework suggests that enhancing metabolic resource allocation from the source end by increasing photosynthetic supply (push), and protecting metabolic resources from degradation during stress responses at the sink end through a targeted metabolic-editing strategy (protect) may be viable routes for achieving increased yield and nutritional quality. The effectiveness of this framework across environments, especially in the field, has not been evaluated. Practical use of this framework would require detailed assessments of physiological limitations such as source-sink imbalances and metabolic constraints. As such, the hierarchy regarding how energy limitation impacts competition among oil, starch and protein synthesis provides a useful organizing model to direct future research efforts. By linking carbohydrate supply with metabolic signal perception, the model offers a conceptual basis for examining possible improvements in kernel nutritional quality and yield stability. Therefore, this review integrates previously unconnected physiological, genetic, biochemical, bioinformatics and breeding-based data into a single coherent set of testable priorities for molecular maize breeding.