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Abscisic Acid Modulates Neighbor Proximity-Induced Leaf Hyponasty in Arabidopsis.

Olivier MichaudJohanna KrahmerFlorian GalbierMaud LagierVinicius Costa GalvãoYetkin Çaka InceMartine TrévisanJana KneřováPatrick J DickinsonJulian M HibberdSamuel C ZeemanChristian Fankhauser
Published in: Plant physiology (2022)
Leaves of shade-avoiding plants such as Arabidopsis (Arabidopsis thaliana) change their growth pattern and position in response to low red to far-red ratios (LRFRs) encountered in dense plant communities. Under LRFR, transcription factors of the phytochrome interacting factor (PIF) family are de-repressed. PIFs induce auxin production, which is required for promoting leaf hyponasty, thereby favoring access to unfiltered sunlight. Abscisic acid (ABA) has also been implicated in the control of leaf hyponasty, with gene expression patterns suggesting that LRFR regulates the ABA response. Here, we show that LRFR leads to a rapid increase in ABA levels in leaves. Changes in ABA levels depend on PIFs, which regulate the expression of genes encoding isoforms of the enzyme catalyzing a rate-limiting step in ABA biosynthesis. Interestingly, ABA biosynthesis and signaling mutants have more erect leaves than wild-type Arabidopsis under white light but respond less to LRFR. Consistent with this, ABA application decreases leaf angle under white light; however, this response is inhibited under LRFR. Tissue-specific interference with ABA signaling indicates that an ABA response is required in different cell types for LRFR-induced hyponasty. Collectively, our data indicate that LRFR triggers rapid PIF-mediated ABA production. ABA plays a different role in controlling hyponasty under white light than under LRFR. Moreover, ABA exerts its activity in multiple cell types to control leaf position.
Keyphrases
  • arabidopsis thaliana
  • transcription factor
  • gene expression
  • dna binding
  • single cell
  • wild type
  • cell wall
  • stem cells
  • cell therapy
  • high glucose
  • mesenchymal stem cells
  • endothelial cells
  • big data
  • binding protein