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全基因组关联分析为水稻代谢的自然变异提供了遗传和生化方面的见解。

Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism.

机构信息

1] National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China. [2].

National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China.

出版信息

Nat Genet. 2014 Jul;46(7):714-21. doi: 10.1038/ng.3007. Epub 2014 Jun 8.

Abstract

Plant metabolites are important to world food security in terms of maintaining sustainable yield and providing food with enriched phytonutrients. Here we report comprehensive profiling of 840 metabolites and a further metabolic genome-wide association study based on ∼6.4 million SNPs obtained from 529 diverse accessions of Oryza sativa. We identified hundreds of common variants influencing numerous secondary metabolites with large effects at high resolution. We observed substantial heterogeneity in the natural variation of metabolites and their underlying genetic architectures among different subspecies of rice. Data mining identified 36 candidate genes modulating levels of metabolites that are of potential physiological and nutritional importance. As a proof of concept, we functionally identified or annotated five candidate genes influencing metabolic traits. Our study provides insights into the genetic and biochemical bases of rice metabolome variation and can be used as a powerful complementary tool to classical phenotypic trait mapping for rice improvement.

摘要

植物代谢物对于维护可持续产量和提供富含植物营养素的食物,对世界粮食安全很重要。在这里,我们报告了对 840 种代谢物的全面分析,并基于来自 529 种不同的水稻品种的约 640 万个 SNP 进行了进一步的代谢全基因组关联研究。我们发现了数百个常见的变体,这些变体影响了许多次生代谢物,其在高分辨率下具有较大的影响。我们观察到在不同亚种的水稻中,代谢物的自然变异及其潜在的遗传结构存在很大的异质性。数据挖掘鉴定出 36 个候选基因,这些基因调节对生理和营养具有潜在重要性的代谢物水平。作为概念验证,我们对影响代谢特征的五个候选基因进行了功能鉴定或注释。我们的研究提供了对水稻代谢组变异的遗传和生化基础的深入了解,并可以作为经典表型特征图谱的有力补充工具,用于水稻改良。

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