Metabolomic analysis of tomato seed germination

Rashid H. Kazmi, Leo A.J. Willems, Ronny V.L. Joosen, Noorullah Khan, Wilco Ligterink*, Henk W.M. Hilhorst

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

26 Citations (Scopus)


Introduction: Seed germination is inherently related to seed metabolism, which changes throughout its maturation, desiccation and germination processes. The metabolite content of a seed and its ability to germinate are determined by underlying genetic architecture and environmental effects during development. Objective: This study aimed to assess an integrative approach to explore genetics modulating seed metabolism in different developmental stages and the link between seed metabolic- and germination traits. Methods: We have utilized gas chromatography-time-of-flight/mass spectrometry (GC-TOF/MS) metabolite profiling to characterize tomato seeds during dry and imbibed stages. We describe, for the first time in tomato, the use of a so-called generalized genetical genomics (GGG) model to study the interaction between genetics, environment and seed metabolism using 100 tomato recombinant inbred lines (RILs) derived from a cross between Solanum lycopersicum and Solanum pimpinellifolium. Results: QTLs were found for over two-thirds of the metabolites within several QTL hotspots. The transition from dry to 6 h imbibed seeds was associated with programmed metabolic switches. Significant correlations varied among individual metabolites and the obtained clusters were significantly enriched for metabolites involved in specific biochemical pathways. Conclusions: Extensive genetic variation in metabolite abundance was uncovered. Numerous identified genetic regions that coordinate groups of metabolites were detected and these will contain plausible candidate genes. The combined analysis of germination phenotypes and metabolite profiles provides a strong indication for the hypothesis that metabolic composition is related to germination phenotypes and thus to seed performance.

Original languageEnglish
Article number145
Number of pages17
Issue number12
Publication statusPublished - 23 Oct 2017


  • Canonical correlation analysis (CCA)
  • Generalized genetical genomics (GGG)
  • Metabolomics
  • mQTL analysis
  • Seed performance
  • Solanum lycopersicum
  • Solanum pimpinellifolium
  • Tomato


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