Max-Planck-Institute of Molecular Plant Physiology.
Max-Planck-Institute of Molecular Plant Physiology; Center of Plant Systems Biology and Biotechnology.
J Vis Exp. 2021 Jul 27(173). doi: 10.3791/62732.
Both gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) are widely used metabolomics approaches to detect and quantify hundreds of thousands of metabolite features. However, the application of these techniques to a large number of samples is subject to more complex interactions, particularly for genome-wide association studies (GWAS). This protocol describes an optimized metabolic workflow, which combines an efficient and fast sample preparation with the analysis of a large number of samples for legume crop species. This slightly modified extraction method was initially developed for the analysis of plant and animal tissues and is based on extraction in methyl tert-butyl ether: methanol solvent to allow the capture of polar and lipid metabolites. In addition, we provide a step-by-step guide for reducing analytical variations, which are essential for the high-throughput evaluation of metabolic variance in GWAS.
气相色谱-质谱联用（GC-MS）和液相色谱-质谱联用（LC-MS）都是广泛用于检测和定量成千上万种代谢物特征的代谢组学方法。然而，这些技术在大量样本中的应用受到更复杂的相互作用的限制，特别是对于全基因组关联研究（GWAS）。本方案描述了一种优化的代谢工作流程，它将高效快速的样品制备与大量样本的分析相结合，适用于豆科作物物种。这种经过略微修改的提取方法最初是为分析植物和动物组织而开发的，它基于在甲基叔丁基醚：甲醇溶剂中的提取，以允许捕获极性和脂类代谢物。此外，我们提供了减少分析变异的分步指南，这对于高通量评估 GWAS 中的代谢变异至关重要。
