Abstract
As global agricultural production faces increasingly severe challenges from diseases, research on disease-resistance genes in corn, an important food crop, becomes particularly significant. This paper explores several research directions for optimizing disease resistance gene editing targets in corn, including the application of artificial intelligence technology in target identification and validation, prediction and assessment of off-target effects, enhancement of editing efficiency, and the integration of diversity and adaptability studies. The paper also emphasizes the importance of interdisciplinary collaboration and data-driven dynamic adjustments in improving the precision and efficiency of gene editing. These research directions promote gene editing technologies' development and provide a scientific basis and practical guidance for disease-resistant breeding in corn. By integrating the latest research findings, this paper aims to explore the optimization pathways for disease-resistance gene editing targets in corn, thereby providing references for improving agricultural productivity and ensuring food security.
