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Plant-pathogen interactions: making the case for multi-omics analysis of complex pathosystems.

Sadegh Balotf1, Richard Wilson2, Roghayeh Hemmati3

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|October 28, 2025
PubMed
Summary

Single-omics studies limit understanding of plant-pathogen interactions. Multi-omics approaches, integrating diverse data, offer a comprehensive view, becoming essential for dissecting complex plant disease dynamics.

Keywords:
GenomicsMetabolomicsMulti-omicsPlant-pathogen interactionsProteomicsTranscriptomics

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Area of Science:

  • Plant science
  • Molecular biology
  • Biotechnology

Background:

  • Single-omics approaches (genomics, transcriptomics, proteomics, metabolomics) provide limited insights into complex plant-pathogen interactions.
  • Understanding host-pathogen molecular dynamics requires a systems-level perspective often missing in isolated omics studies.

Purpose of the Study:

  • To highlight the limitations of single-omics in plant-pathogen research.
  • To emphasize the value and necessity of multi-omics strategies for a comprehensive understanding.
  • To discuss computational tools, challenges, and future directions in integrating omics data.

Main Methods:

  • Review of current literature on plant-pathogen interactions and omics methodologies.
  • Discussion of computational tools for multi-omics data integration and visualization.
  • Analysis of challenges and future prospects, including AI and single-cell omics.

Main Results:

  • Single-omics studies are insufficient for capturing the complexity of plant-pathogen molecular interactions.
  • Multi-omics strategies provide a more holistic view of host-pathogen molecular networks and defense pathways.
  • Despite accessibility, multi-omics integration is underutilized in plant science.

Conclusions:

  • Multi-omics approaches are indispensable for a systems-level understanding of plant-pathogen interactions.
  • Technological advancements are making multi-omics more accessible and affordable.
  • Future research should focus on overcoming integration challenges and leveraging AI and single-cell omics.