Department of Plant Sciences, University of California Davis, Davis, California, United States of America.
PLoS Genet. 2010 Nov 4;6(11):e1001198. doi: 10.1371/journal.pgen.1001198.
Discovering links between the genotype of an organism and its metabolite levels can increase our understanding of metabolism, its controls, and the indirect effects of metabolism on other quantitative traits. Recent technological advances in both DNA sequencing and metabolite profiling allow the use of broad-spectrum, untargeted metabolite profiling to generate phenotypic data for genome-wide association studies that investigate quantitative genetic control of metabolism within species. We conducted a genome-wide association study of natural variation in plant metabolism using the results of untargeted metabolite analyses performed on a collection of wild Arabidopsis thaliana accessions. Testing 327 metabolites against >200,000 single nucleotide polymorphisms identified numerous genotype-metabolite associations distributed non-randomly within the genome. These clusters of genotype-metabolite associations (hotspots) included regions of the A. thaliana genome previously identified as subject to recent strong positive selection (selective sweeps) and regions showing trans-linkage to these putative sweeps, suggesting that these selective forces have impacted genome-wide control of A. thaliana metabolism. Comparing the metabolic variation detected within this collection of wild accessions to a laboratory-derived population of recombinant inbred lines (derived from two of the accessions used in this study) showed that the higher level of genetic variation present within the wild accessions did not correspond to higher variance in metabolic phenotypes, suggesting that evolutionary constraints limit metabolic variation. While a major goal of genome-wide association studies is to develop catalogues of intraspecific variation, the results of multiple independent experiments performed for this study showed that the genotype-metabolite associations identified are sensitive to environmental fluctuations. Thus, studies of intraspecific variation conducted via genome-wide association will require analyses of genotype by environment interaction. Interestingly, the network structure of metabolite linkages was also sensitive to environmental differences, suggesting that key aspects of network architecture are malleable.
发现生物体的基因型与其代谢物水平之间的联系，可以增进我们对代谢、代谢控制以及代谢对其他数量性状的间接影响的理解。近年来，DNA 测序和代谢物分析技术的进步，使得人们可以利用广谱、非靶向的代谢物分析，为全基因组关联研究生成表型数据，以研究物种内代谢的数量遗传控制。我们利用对野生拟南芥（Arabidopsis thaliana）品系集合进行的非靶向代谢物分析结果，进行了一个植物代谢的全基因组关联研究。针对 >200,000 个单核苷酸多态性，对 327 种代谢物进行了测试，鉴定出了许多分布在基因组中非随机的基因型-代谢物关联。这些基因型-代谢物关联的聚类（热点）包括先前被鉴定为受到近期强烈正向选择（选择压力）影响的 A. thaliana 基因组区域，以及与这些假定的选择压力发生连锁的区域，这表明这些选择压力已经影响到 A. thaliana 代谢的全基因组控制。将该野生品系集合中检测到的代谢变化与源自两个研究品系的重组自交系（recombinant inbred lines）的实验室衍生群体进行比较，表明野生品系中存在的更高遗传变异水平并不对应于代谢表型的更高方差，这表明进化约束限制了代谢变异。尽管全基因组关联研究的主要目标是开发种内变异目录，但这项研究中进行的多项独立实验的结果表明，鉴定出的基因型-代谢物关联对环境波动敏感。因此，通过全基因组关联进行的种内变异研究需要进行基因型与环境互作分析。有趣的是，代谢物关联的网络结构也对环境差异敏感，这表明网络结构的关键方面是可塑的。
