Plant PhysiologyPlant BiologyPeer-reviewed journal article
Rapid systemic responses of Arabidopsis to waterlogging stress
M. A. Pelaez-Vico, A. Tukuli, P. Singh, D. G. Mendoza-Cozatl, T. G. Joshi, R. Mittler
Abstract
Waterlogging stress (WLS) negatively impacts the growth and yield of crops resulting in heavy losses to agricultural production. Previous studies revealed that WLS induces a systemic response in shoots that is partially dependent on the plant hormones ethylene and abscisic acid. However, the role of rapid cell-to-cell signaling pathways, such as the reactive oxygen species (ROS) and calcium waves, in systemic responses of plants to WLS is unknown at present. Here we reveal that an abrupt WLS treatment of Arabidopsis thaliana plants growing in peat moss triggers systemic ROS and calcium wave responses, and that the WLS-triggered ROS wave response of Arabidopsis is dependent on the ROS generating RESPIRATORY BURST OXIDASE HOMOLOG D (RBOHD), calcium-permeable channels GLUTAMATE-LIKE RECEPTOR 3.3 and 3.6 (GLR3.3 and GLR3.6), and aquaporin PLASMA MEMBRANE INTRINSIC PROTEIN 2;1 (PIP2;1) proteins. We further show that WLS is accompanied by a rapid systemic transcriptomic response that is evident as early as 10 min following waterlogging initiation, includes many hypoxia-response transcripts, and is partially dependent on RBOHD. Interestingly, the abrupt WLS of Arabidopsis resulted in the triggering of a rapid hydraulic wave response and the transient opening of stomata on leaves. Taken together, our findings reveal that the initiation of WLS in plants is accompanied by rapid systemic physiological and transcriptomic responses that involve the ROS, calcium, and hydraulic waves. These findings reveal that systemic plant responses to WLS are rapid and at least partially dependent on cell-to-cell signaling mechanisms.
- organism: Arabidopsis
- assay: bulk RNA-seq
- research focus: cell signaling & trafficking
- research focus: development & morphogenesis
- research focus: metabolism & bioenergetics
- approach: experimental assay
- approach: statistical model
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