Rice Genomics and Genetics 2025, Vol.16, No.2, 106-115 http://cropscipublisher.com/index.php/rgg 106 Review and Progress Open Access Functional Genomics of Rice: Recent Discoveries and Future Prospects Yanfu Wang, Danyan Ding Institute of Life Sciences, Jiyang College of Zhejiang A&F University, Zhuji, 311800, Zhejiang, China Corresponding email: 723822780@qq.com Rice Genomics and Genetics, 2025, Vol.16, No.2 doi: 10.5376/rgg.2025.16.0010 Received: 23 Feb., 2025 Accepted: 08 Apr., 2025 Published: 25 Apr., 2025 Copyright © 2025 Wang and Ding, This is an open access article published under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Preferred citation for this article: Wang Y.F., and Ding D.Y., 2025, Functional genomics of rice: recent discoveries and future prospects, Rice Genomics and Genetics, 16(2): 106-115 (doi: 10.5376/rgg.2025.16.0010) Abstract Rice (Oryza sativa L.) serves as a crucial staple food for over half of the global population and stands as a model organism for monocotyledon genomics research. Recent advancements in functional genomics have significantly enhanced the understanding of the genetic and molecular mechanisms underlying key agronomic traits in rice. Over the past decade, more than 2 000 genes associated with important traits such as yield, stress resistance, and nutrient use efficiency have been cloned and characterized. The development of comprehensive genomic resources, including large mutant libraries, global expression profiles, and extensive resequencing data, has accelerated gene discovery and functional analysis. The integration of these resources into platforms like the funRiceGenes database has facilitated the systematic characterization of rice genes, enabling more targeted breeding strategies. Furthermore, innovative tools such as the CRISPR Applicable Functional Redundancy Inspector (CAFRI-Rice) are addressing challenges like functional redundancy, thereby streamlining functional genomics research. The focus will be on leveraging these genomic insights to develop Green Super Rice varieties that combine high yield with sustainability, addressing the pressing need for increased food production in the face of global challenges. Keywords Rice (Oryza sativaL.); Functional genomics; Gene cloning; Agronomic traits; Genomic resources 1 Introduction Rice (Oryza sativa L.) is not only the staple food of more than half of the world's population, but also one of the most widely used research objects in plant science. Why study rice? In addition to its economic value, it is also because, as a representative of monocotyledons, it has rich genetic resources and clear genomic information. In the past decade, there has been a lot of research in this area. As soon as high-throughput sequencing technology came on the stage, researchers had new tools to explore genes related to key agronomic traits such as yield, stress resistance, and nutrient absorption. Now, more than 2 000 such genes have been identified (Jiang et al., 2012; Li et al., 2018). Of course, genetic information alone is not enough. What really drives progress is the accumulation of resources and the maturity of technical means. For example, various large mutant libraries, full-length cDNA sequences, and expression profile data of different tissues and developmental stages have been established, which directly accelerated the pace of gene cloning and functional verification. The emergence of projects such as RICE2020 shows the extensive international cooperation in promoting rice genetic research (Zhang et al., 2008). With the support of these technologies and resources, functional genomics has begun to play an increasingly important role in rice breeding. After all, the purpose is still the same - to select key genes that can improve rice yield, quality or environmental adaptability and turn them into usable tools. Here, high-throughput phenotyping platforms and mutagenesis technologies (such as T-DNA insertion or activation tagging) are particularly important because they directly connect the "causal chain" between genes and traits (Yang et al., 2013; Moin et al., 2017). This understanding not only stays in the laboratory, but also begins to truly serve breeding practice, such as developing new rice varieties that are more efficient, resistant to stress and suitable for sustainable agriculture (Huang et al., 2013).
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