Corolla movement is a typical plant movement behavior that enables plants to optimize pollination and adapt to environmental changes. Nevertheless, its molecular mechanism remains poorly understood. In the present study, we conduct a comprehensive transcriptome analysis of Mirabilis jalapa (Nyctaginaceae) corolla at five stages (AG-EG) to elucidate the regulatory networks underlying movement. The results showed that the differentially expressed genes (DEGs) were mainly associated with cellular processes, catalytic activity, MAPK signaling, plant hormone signal transduction, and photosynthesis-related pathways, highlighting their involvement in corolla dynamics. Transcriptome profiling further demonstrated that auxin, ethylene, and abscisic acid signaling pathways were key hormonal regulators of corolla movement. Moreover, Ca2+ transport genes (CNGCs and CMLs) and respiratory burst oxidase homologs (RBOHs) were significantly enriched, indicating that Ca2+–ROS signaling oscillations also play an important role in driving differential cell expansion and turgor changes. Transcription factor analysis also revealed the upregulation of WRKY2, WRKY22, and WRKY33, suggesting that WRKYs act as the critical transcriptional regulators linking ROS–Ca2+ signals with downstream gene expression. The reliability of RNA-Seq data was confirmed by RT-qPCR, which showed high consistency with transcriptome profiles. These findings suggested that corolla movement in M. jalapa is carried through the integration of hormonal pathways, Ca2+–ROS signaling, and WRKY-mediated transcriptional regulation. This research provided novel insights into the molecular basis of plant movement and established a foundation for further study on floral dynamics and adaptive strategies in angiosperms.
Building similarity graph...
Analyzing shared references across papers
Loading...
Dingkun Liu
Jinggangshan University
Huiqi Yan
Zhejiang Chinese Medical University
Xuan Wang
Jinggangshan University
Biology
Jinggangshan University
Building similarity graph...
Analyzing shared references across papers
Loading...
Liu et al. (Mon,) studied this question.
synapsesocial.com/papers/69d895046c1944d70ce05f5d — DOI: https://doi.org/10.3390/biology15070585