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. 2025 Apr 7;18(4):651-668.
doi: 10.1016/j.molp.2025.03.007. Epub 2025 Mar 13.

Large-scale genomic and phenomic analyses of modern cultivars empower future rice breeding design

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Free article

Large-scale genomic and phenomic analyses of modern cultivars empower future rice breeding design

Xiaoding Ma et al. Mol Plant. .
Free article

Abstract

Modern cultivated rice plays a pivotal role in global food security. China accounts for nearly 30% of the world's rice production and has developed numerous cultivated varieties over the past decades that are well adapted to diverse growing regions. However, the genomic bases underlying the phenotypes of these modern cultivars remain poorly characterized, limiting the exploitation of this vast resource for breeding specialized, regionally adapted cultivars. In this study, we constructed a comprehensive genetic variation map of modern rice using resequencing datasets from 6044 representative cultivars from five major rice-growing regions in China. Our genomic and phenotypic analyses of this diversity panel revealed regional preferences for specific genomic backgrounds and traits, such as heading date, biotic/abiotic stress resistance, and grain shape, which are crucial for adaptation to local conditions and consumer preferences. We identified 3131 quantitative trait loci associated with 53 phenotypes across 212 datasets under various environmental conditions through genome-wide association studies. Notably, we cloned and functionally verified a novel gene related to grain length, OsGL3.6. By integrating multiple datasets, we developed RiceAtlas, a versatile multi-scale toolkit for rice breeding design. We successfully utilized the RiceAtlas breeding design function to rapidly improve the grain shape of the Suigeng4 cultivar. These valuable resources enhance our understanding of the adaptability and breeding requirements of modern rice and can facilitate advances in future rice-breeding initiatives.

Keywords: breeding design; genomic bases; modern rice cultivars; rice-growing regions.

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