Communications Biology· 2026Q1
Transcriptomic biomarkers reveal jasmonic and salicylic acid states under field herbivory in Arabidopsis thaliana
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- Q1SCImago
- 2026year
Short summary
Machine-learning biomarkers derived from transcriptomic data can independently quantify salicylic acid (SA) and jasmonic acid (JA) response states in Arabidopsis thaliana, revealing dynamic hormonal responses shaped by herbivore presence in field conditions.
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Key points
- Identified 43 distinct transcriptomic signatures corresponding to specific combinations of SA and JA concentrations.
- Developed machine-learning biomarkers capable of independently quantifying SA and JA response states from transcriptomes.
- Demonstrated that field herbivory dynamically shapes SA/JA response states based on herbivore abundance and co-occurrence.
- Provides a method to decode hormonal responses to biotic environments from field transcriptomes.
AI-generated from the title and abstract; the full text is not read.
Abstract
Abstract Plants coordinate defence against pathogens and herbivores through the crosstalk between salicylic acid (SA) and jasmonic acid (JA) signalling pathways. However, little is known about how plants integrate the phytohormone concentration profiles to shape defence states in complex field environments. Here we show that systematically varying combinatorial SA and JA concentrations in Arabidopsis thaliana reveals 43 distinct combination-specific transcriptional signatures beyond SA–JA antagonism. Leveraging these data, we developed and validated machine-learning-based transcriptomic biomarkers that enabled independent quantification of SA and JA response states. By applying these biomarkers to field-grown A. thaliana , we revealed that SA/JA response states were dynamically shaped by abundant and co-occurrence of herbivores on individual plants. Our study provides a strategy to decode hormonal responses to biotic environments from field transcriptomes, bridging the gap between molecular signalling and ecological dynamics.
The authors' abstract, as published at the source. Communications Biology, 2026 · DOI ↗
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Field: Insect Science
Insect ScienceAgricultural and Biological Sciences