Mapping the Arabidopsis Metabolic Landscape by Untargeted Metabolomics at Different Environmental Conditions

Si Wu, Takayuki Tohge, Álvaro Cuadros-Inostroza, Hao Tong, Hezi Tenenboim, Rik Kooke, Michaël Méret, Joost B. Keurentjes, Zoran Nikoloski, Alisdair R. Fernie, Lothar Willmitzer, Yariv Brotman

Research output: Contribution to journalArticlepeer-review

84 Scopus citations

Abstract

Metabolic genome-wide association studies (mGWAS), whereupon metabolite levels are regarded as traits, can help unravel the genetic basis of metabolic networks. A total of 309 Arabidopsis accessions were grown under two independent environmental conditions (control and stress) and subjected to untargeted LC–MS-based metabolomic profiling; levels of the obtained hydrophilic metabolites were used in GWAS. Our two-condition-based GWAS for more than 3000 semi-polar metabolites resulted in the detection of 123 highly resolved metabolite quantitative trait loci (p ≤ 1.0E-08), 24.39% of which were environment-specific. Interestingly, differently from natural variation in Arabidopsis primary metabolites, which tends to be controlled by a large number of small-effect loci, we found several major large-effect loci alongside a vast number of small-effect loci controlling variation of secondary metabolites. The two-condition-based GWAS was followed by integration with network-derived metabolite–transcript correlations using a time-course stress experiment. Through this integrative approach, we selected 70 key candidate associations between structural genes and metabolites, and experimentally validated eight novel associations, two of them showing differential genetic regulation in the two environments studied. We demonstrate the power of combining large-scale untargeted metabolomics-based GWAS with time-course-derived networks both performed under different abiotic environments for identifying metabolite–gene associations, providing novel global insights into the metabolic landscape of Arabidopsis. By combining large-scale untargeted metabolomics-based GWAS and network analysis with environmental stress-driven perturbations of metabolic homeostasis, this system-wide study provides new global insights into the metabolic landscape of Arabidopsis, using a strategy that could readily be extended to other plant species.

Original languageEnglish
Pages (from-to)118-134
Number of pages17
JournalMolecular Plant
Volume11
Issue number1
DOIs
StatePublished - 1 Jan 2018

Keywords

  • GWAS
  • different environments
  • network analysis
  • secondary metabolism
  • untargeted metabolomics

ASJC Scopus subject areas

  • Molecular Biology
  • Plant Science

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