The transcriptional coactivator ZaGIF2 from Zanthoxylum armatum enhances growth and drought tolerance in plants by synergistically activating GRF activity
摘要
In this study, the transcriptional coactivator ZaGIF2, isolated from Zanthoxylum armatum, enhances plant growth and drought tolerance by synergistically activating GRF transcription factors in plants.
AbstractGrowth-regulating factor-interacting factors (GIFs) are conserved transcriptional coactivators in plants that regulate growth and development by forming complexes with growth-regulating factors (GRFs). However, their functions in woody plants, especially in non-model species, and their specific roles in coordinating growth and stress resistance remain unclear. In this study, a GIF gene, ZaGIF2, was cloned from the economically important species Zanthoxylum armatum var. dintanensis. ZaGIF2 exhibited the highest expression in apical buds with active meristems, and its transcription was significantly induced by naphthaleneacetic acid (NAA), abscisic acid (ABA), and drought stress. The encoded protein was localized to the nucleus. Overexpression of ZaGIF2 in Nicotiana benthamiana and Arabidopsis thaliana simultaneously promoted leaf enlargement and enhanced drought tolerance. Transgenic plants demonstrated improved water retention capacity, reduced oxidative damage, and enhanced osmotic adjustment. Overexpression of ZaGIF2 upregulated the expression of multiple growth-related genes (AtPIF4, AtLBD18, AtTCP14) and drought-responsive genes (DREB2A, P5CS1, RD26, RD29). Mechanistically, the ZaGIF2 protein directly interacted with AtGRF1 and AtGRF3 and significantly enhanced their transcriptional activation activity. Collectively, our findings reveal a novel mechanism in woody plants whereby a GIF protein improves plant growth and drought adaptation by interacting with and enhancing the activity of GRF transcription factors. This study provides important genetic resources and a theoretical foundation for the synergistic improvement of growth and stress resistance traits in forest trees using the conserved GIF–GRF module.