Pino Del Carpio Dunia, Basnet Ram Kumar, Arends Danny, Lin Ke, De Vos Ric C H, Muth Dorota, Kodde Jan, Boutilier Kim, Bucher Johan, Wang Xiaowu, Jansen Ritsert, Bonnema Guusje
Wageningen UR Plant Breeding, Wageningen University & Research Centre, Wageningen, The Netherlands.
Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Haren, The Netherlands.
PLoS One. 2014 Sep 15;9(9):e107123. doi: 10.1371/journal.pone.0107123. eCollection 2014.
Brassica rapa studies towards metabolic variation have largely been focused on the profiling of the diversity of metabolic compounds in specific crop types or regional varieties, but none aimed to identify genes with regulatory function in metabolite composition. Here we followed a genetical genomics approach to identify regulatory genes for six biosynthetic pathways of health-related phytochemicals, i.e carotenoids, tocopherols, folates, glucosinolates, flavonoids and phenylpropanoids. Leaves from six weeks-old plants of a Brassica rapa doubled haploid population, consisting of 92 genotypes, were profiled for their secondary metabolite composition, using both targeted and LC-MS-based untargeted metabolomics approaches. Furthermore, the same population was profiled for transcript variation using a microarray containing EST sequences mainly derived from three Brassica species: B. napus, B. rapa and B. oleracea. The biochemical pathway analysis was based on the network analyses of both metabolite QTLs (mQTLs) and transcript QTLs (eQTLs). Co-localization of mQTLs and eQTLs lead to the identification of candidate regulatory genes involved in the biosynthesis of carotenoids, tocopherols and glucosinolates. We subsequently focused on the well-characterized glucosinolate pathway and revealed two hotspots of co-localization of eQTLs with mQTLs in linkage groups A03 and A09. Our results indicate that such a large-scale genetical genomics approach combining transcriptomics and metabolomics data can provide new insights into the genetic regulation of metabolite composition of Brassica vegetables.
对白菜代谢变异的研究主要集中在特定作物类型或区域品种中代谢化合物多样性的分析上,但尚无研究旨在鉴定在代谢物组成中具有调控功能的基因。在此,我们采用遗传基因组学方法,鉴定了与健康相关的植物化学物质的六种生物合成途径的调控基因,即类胡萝卜素、生育酚、叶酸、芥子油苷、黄酮类化合物和苯丙烷类化合物。利用靶向和基于液相色谱-质谱联用的非靶向代谢组学方法,对由92个基因型组成的白菜双单倍体群体中六周龄植株的叶片进行了次生代谢物组成分析。此外,使用一个主要来源于三种芸苔属物种(甘蓝型油菜、白菜和甘蓝)的EST序列微阵列,对同一群体的转录本变异进行了分析。生化途径分析基于代谢物QTL(mQTL)和转录本QTL(eQTL)的网络分析。mQTL和eQTL的共定位导致了参与类胡萝卜素、生育酚和芥子油苷生物合成的候选调控基因的鉴定。我们随后聚焦于特征明确的芥子油苷途径,揭示了在A03和A09连锁群中eQTL与mQTL共定位的两个热点。我们的结果表明,这种结合转录组学和代谢组学数据的大规模遗传基因组学方法,可以为白菜类蔬菜代谢物组成的遗传调控提供新的见解。