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代谢产物的关联作图

已有 6221 次阅读 2015-3-20 16:13 |个人分类:关联作图|系统分类:科研笔记

2014 Jul;46(7):714-21. doi: 10.1038/ng.3007. Epub 2014 Jun 8.
Genome-wide association analyses provide genetic and biochemical insights into natural variation in rice metabolism.
Author information
  • 11] National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan, China. [2].

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

  • 3College of Life Science and Technology, Huazhong Agricultural University, Wuhan, China.

  • 4Key Laboratory of Horticultural Plant Biology (Ministry of Education), Huazhong Agricultural University, Wuhan, China.

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.

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关于作图,高通量基因型鉴定方法的出现及成本的降低,使得作图的关键在于表型。代谢产物的含量当然也可以算是一种表型。传统的表型,例如株高,产量等,获得表型数据的方法比较复杂,在基因型不是问题的时代,能够高通量获取的表型也许会成为优先选择的目标。类似的研究也应该可以利用RIL来开展。




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