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Pairing omics to decode the diversity of plant specialized metabolism

  • Felicia C. Wolters
  • , Elena Del Pup
  • , Kumar Saurabh Singh
  • , Klaas Bouwmeester
  • , M. Eric Schranz
  • , Justin J. J. van der Hooft*
  • , Marnix H. Medema*
  • *Corresponding author for this work

Research output: Contribution to journal › (Systematic) Review article › peer-review

Abstract

Plants have evolved complex bouquets of specialized natural products that are utilized in medicine, agriculture, and industry. Untargeted natural product discovery has benefitted from growing plant omics data resources. Yet, plant genome complexity limits the identification and curation of biosynthetic pathways via single omics. Pairing multi-omics types within experiments provides multiple layers of evidence for biosynthetic pathway mining. The extraction of paired biological information facilitates connecting genes to transcripts and metabolites, especially when captured across time points, conditions and chemotypes. Experimental design requires specific adaptations to enable effective paired-omics analysis. Ultimately, metadata standards are required to support the integration of paired and unpaired public datasets and to accelerate collaborative efforts for natural product discovery in the plant research community.
Original languageEnglish
Article number102657
Number of pages9
JournalCurrent Opinion in Plant Biology
Volume82
DOIs
Publication statusPublished - 1 Dec 2024

Keywords

  • Multi-omics
  • Plant science
  • Specialized metabolism
  • Paired omics
  • Multi-omics integration
  • GENE-CLUSTER
  • METABOLOMICS
  • PATHWAY
  • IDENTIFICATION
  • PREDICTION
  • NETWORKS
  • DATABASE
  • DEFENSE

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