Integrative transcriptome meta-analysis distinguishes compatibility and incompatibility in rice-Xanthomonas interaction.

Authors

Gokulan Cg, Kamal K Malukani, Namami Gaur, Sreekanth M, Hitendra K Patel, Ramesh V Sonti

Published in

Journal of experimental botany. Nov 03, 2026. Epub Nov 03, 2026.

Abstract

Diseases caused by the Xanthomonas oryzae pathovars are important constraints for global rice productivity. Despite being a well-studied pathosystem, the transcriptional mechanisms distinguishing resistance from susceptibility remain incompletely understood. Here, we present a systems-level meta-analysis of more than a hundred publicly available rice-Xanthomonas transcriptome datasets. Using appropriate analysis pipelines, stringent filtering criteria and metadata integration, we identified rice functions that distinguish disease resistance and susceptibility with temporal resolution. Compatible interactions were characterized by early activation of abscisic-acid biosynthetic and signaling genes, and extensive transcriptional plasticity associated with susceptibility gene activation. In contrast, incompatible interactions displayed a restrained transcriptome reprogramming, enrichment of phenylpropanoid and aromatic-amino-acid biosynthetic pathways, and enrichment of an AP2/ERF-GCC-box regulatory module. Transient over-expression of three conserved infection-responsive genes, OsJAZ11, OsSYP131b, and OsMYB45, modestly enhanced defense gene expression and reduced lesion length caused by X. oryzae pv. oryzae in rice leaves, thus providing a proof-of-concept relevance of the candidates to rice-Xoo interaction. We also developed RiceXtra, an openly available database hosting the analyzed data (http://tdb.ccmb.res.in/RiceXtra), for exploring gene expression patterns during rice-Xanthomonas interactions. Overall, our study proposes a mechanistic framework connecting hormonal signalling and transcriptional plasticity with disease outcome, offering a foundation for engineering durable disease resistance.

PMID:
42973148
Bibliographic data and abstract were imported from PubMed on 03 Nov 2026.

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