Laboratory of Plant Physiology, Wageningen University, 6708 PB Wageningen, The Netherlands.
Plant Physiol. 2012 Mar;158(3):1306-18. doi: 10.1104/pp.111.188441. Epub 2012 Jan 5.
Recent advances in -omics technologies such as transcriptomics, metabolomics, and proteomics along with genotypic profiling have permitted dissection of the genetics of complex traits represented by molecular phenotypes in nonmodel species. To identify the genetic factors underlying variation in primary metabolism in potato (Solanum tuberosum), we have profiled primary metabolite content in a diploid potato mapping population, derived from crosses between S. tuberosum and wild relatives, using gas chromatography-time of flight-mass spectrometry. In total, 139 polar metabolites were detected, of which we identified metabolite quantitative trait loci for approximately 72% of the detected compounds. In order to obtain an insight into the relationships between metabolic traits and classical phenotypic traits, we also analyzed statistical associations between them. The combined analysis of genetic information through quantitative trait locus coincidence and the application of statistical learning methods provide information on putative indicators associated with the alterations in metabolic networks that affect complex phenotypic traits.
近年来，转录组学、代谢组学和蛋白质组学等组学技术的进步，以及基因型分析，使得对非模式物种中分子表型所代表的复杂性状的遗传学进行剖析成为可能。为了鉴定马铃薯（Solanum tuberosum）中初级代谢物变异的遗传因素，我们使用气相色谱-飞行时间-质谱联用技术，对源自马铃薯与野生近缘种杂交的二倍体马铃薯作图群体的初级代谢物含量进行了分析。共检测到 139 种极性代谢物，其中约 72%的检测化合物的代谢物数量性状位点被我们鉴定出来。为了深入了解代谢性状与经典表型性状之间的关系，我们还分析了它们之间的统计相关性。通过数量性状位点一致性的遗传信息综合分析和统计学习方法的应用，为与影响复杂表型性状的代谢网络变化相关的假定指标提供了信息。
