Abstract: Rice (Oryza sativa L.) is a staple food crop for more than half of the global population, and the abundant genetic variations contained in its germplasm resources serve as the core material basis for genetic improvement and variety breeding. With the continuous advances in genome sequencing technology, remarkable progress has been made in rice genomics research. However, three prominent bottlenecks still exist: insufficient integrity of the Oryza genus genome, the lack of a standard rice pan-genome, and a serious disconnection between genomic data and breeding applications. This paper systematically reviewed the application progress of genomic data in four major areas of rice germplasm resources research, including the iterative upgrading of rice reference genome and pan-genome resources and the construction of database systems, the application scenarios of different sequencing technologies and challenges in data analysis, the mainstream methodological system for genetic diversity analysis, and the application and limitations of genome-wide association study (GWAS) in mining elite genes. The study found that rice genomic resources evolved from a single linear reference genome to a multi-dimensional pan-genome; next-generation sequencing remained the mainstream technology for large-scale population resequencing; genomics methods became the core means of genetic diversity research; and GWAS technology successfully mined a large number of key genes for important agronomic traits. Nevertheless, problems such as the scarcity of wild rice genomic resources, the lack of standardization in analytical pipelines, the limited ability to detect selection signals of polygenic genes, and the omission of structural variations in traditional SNP-GWAS remained unresolved. Moreover, the low efficiency of transforming genomic data into breeding applications was currently the biggest shortcoming. Based on this, this paper proposed that future research should focus on three key directions: Constructing a unified pan-genome system for the Oryza genus, developing a new generation of GWAS technology, and establishing a breeding-oriented intelligent genomic big data platform. This review aimed to provide theoretical references and technical pathways for the efficient utilization of rice germplasm resources and precise genetic improvement.