DOI: 10.1093/pcp/pcag080 ISSN: 0032-0781

Post-Translational Modifications of Plant Transcription Factors Regulating Stress Resistance Mechanisms

Xin Xu, Xiaoyu Ji, Yucheng Wang

Abstract

Throughout their life cycle, plants continuously face various environmental stresses such as drought, high salinity, and extreme temperatures. To cope with these environmental challenges, plants have evolved a multi-layered regulatory network centered on transcription factors (TFs), whose functions are dynamically and precisely modulated by post-translational modifications (PTMs). Despite extensive documentation of PTM-TF regulatory modules in plant stress responses, current studies remain largely descriptive and lack a unified conceptual framework and critical assessment. This review systematically summarizes the molecular mechanisms of major PTM types—including phosphorylation, ubiquitination, acetylation, and SUMOylation—in regulating key stress-responsive TFs such as NAC, WRKY, MYB, bZIP, AP2/ERF, and HSF. Specifically, we focus on how PTMs affect the DNA-binding ability, subcellular localization, protein stability, and interaction networks of these TFs, thereby enabling rapid response to and precise integration of stress signals. We further highlight landmark conceptual advances in the field, deconstruct the hierarchical regulatory logic and synergistic/antagonistic crosstalk between different PTMs, construct a unified PTM-transcription factor regulatory network, and reveal its physiological functions in enhancing plant stress tolerance and maintaining the balance between growth and defense. Finally, we provide a systematic overview of the historical development and comparative performance of PTM detection methodologies, synthesize major research trends in the field, define unresolved core scientific questions and technical bottlenecks and discuss the potential of PTM research in crop stress-resistant breeding and highlights the application prospects of cutting-edge technologies such as gene editing and multi-omics integration in deciphering dynamic modification networks.

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