title: Seed metabolomic study reveals significant metabolite variations and correlations among different soybean cultivars.
abstract: Soybean [Glycine max (L.) Merr.] is one of the world's major crops, and soybean seeds are a rich and important resource for proteins and oils. While "omics" studies, such as genomics, transcriptomics, and proteomics, have been widely applied in soybean molecular research, fewer metabolomic studies have been conducted for large-scale detection of low molecular weight metabolites, especially in soybean seeds. In this study, we investigated the seed metabolomes of 29 common soybean cultivars through combined gas chromatography-mass spectrometry and ultra-performance liquid chromatography-tandem mass spectrometry. One hundred sixty-nine named metabolites were identified and subsequently used to construct a metabolic network of mature soybean seed. Among the 169 detected metabolites, 104 were found to be significantly variable in their levels across tested cultivars. Metabolite markers that could be used to distinguish genetically related soybean cultivars were also identified, and metabolite-metabolite correlation analysis revealed some significant associations within the same or among different metabolite groups. Findings from this work may potentially provide the basis for further studies on both soybean seed metabolism and metabolic engineering to improve soybean seed quality and yield.
authors.affiliation: National Center for the Molecular Characterization of Genetically Modified Organisms, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai, 200240, China; Department of Plant and Crop Sciences, School of Biosciences, University of Nottingham, Sutton Bonington Campus, Loughborough, Leicestershire, LE12 5RD, UK.
authors.forename: Hong
authors.initials: H
authors.lastname: Lin
authors.forename: Jun
authors.initials: J
authors.lastname: Rao
authors.forename: Jianxin
authors.initials: J
authors.lastname: Shi
authors.forename: Chaoyang
authors.initials: C
authors.lastname: Hu
authors.forename: Fang
authors.initials: F
authors.lastname: Cheng
authors.forename: Zoe A
authors.initials: ZA
authors.lastname: Wilson
authors.forename: Dabing
authors.initials: D
authors.lastname: Zhang
authors.forename: Sheng
authors.initials: S
authors.lastname: Quan
mesh_terms: D002853:Chromatography, Liquid; D008401:Gas Chromatography-Mass Spectrometry; D055432:Metabolomics; D025341:Principal Component Analysis; D012639:Seeds / Q000378:metabolism*; D013025:Glycine max / Q000145:classification / Q000196:embryology / Q000378:metabolism*; D053719:Tandem Mass Spectrometry
keywords: Gas chromatography-mass spectrometry (GC-MS); metabolic network; metabolite-metabolite correlation; metabolomics; soybean; ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS)