Lu Yaping, Liu Yemao, Niu Xiaohui, Yang Qingyong, Hu Xuehai, Zhang Hong-Yu, Xia Jingbo
Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University Wuhan, China.
Front Plant Sci. 2015 Nov 27;6:1027. doi: 10.3389/fpls.2015.01027. eCollection 2015.
In the post-GWAS (Genome-Wide Association Scan) era, the interpretation of GWAS results is crucial to screen for highly relevant phenotype-genotype association pairs. Based on the single genotype-phenotype association test and a pathway enrichment analysis, we propose a Metabolite-pathway-based Phenome-Wide Association Scan (M-PheWAS) to analyze the key metabolite-SNP pairs in rice and determine the regulatory relationship by assessing similarities in the changes of enzymes and downstream products in a pathway. Two SNPs, sf0315305925 and sf0315308337, were selected using this approach, and their molecular function and regulatory relationship with Enzyme EC:5.5.1.6 and with flavonoids, a significant downstream regulatory metabolite product, were demonstrated. Moreover, a total of 105 crucial SNPs were screened using M-PheWAS, which may be important for metabolite associations.
在后全基因组关联扫描(GWAS)时代,解读GWAS结果对于筛选高度相关的表型-基因型关联对至关重要。基于单基因型-表型关联测试和通路富集分析,我们提出了一种基于代谢物-通路的全表型关联扫描(M-PheWAS)方法,用于分析水稻中关键的代谢物-SNP对,并通过评估通路中酶和下游产物变化的相似性来确定调控关系。利用该方法筛选出了两个SNP,即sf0315305925和sf0315308337,并证明了它们与酶EC:5.5.1.6以及重要的下游调控代谢物产物黄酮类化合物的分子功能和调控关系。此外,使用M-PheWAS共筛选出105个关键SNP,这些SNP可能对代谢物关联具有重要意义。