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Ginkgo biloba L. is a relic tree species that integrates medicinal, edible, ornamental, and scientific research value, offering substantial economic and social benefits. However, market demand for new cultivars with superior ornamental characteristics, high bioactive compound content, and enhanced stress tolerance is becoming increasingly urgent, and conventional breeding approaches can no longer adequately meet these needs. The rapid advancement of omics technologies has provided novel perspectives and a rich data foundation for deciphering the molecular mechanisms underlying key traits in G. biloba from multiple dimensions. This review systematically summarizes the progress and application of omics technologies in studies on G. biloba morphogenesis, sex determination and differentiation, biosynthesis of pharmacologically active compounds (flavonoids and terpene lactones), and stress resistance. To address the limitations of current omics-based research on G. biloba traits, this paper proposes a multidisciplinary framework integrating systems biology, precision phenomics, and machine learning modeling, aiming to propel molecular design breeding in G. biloba and provide strategic reference for its precision genetic improvement as well as the quality and efficiency enhancement of the entire industrial chain.
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