Decoding gibberellin-strigolactone interaction networks in cereal crops toward a next-generation Green Revolution

The agricultural Green Revolution (GR) of the 1950s and 1960s drove unprecedented increases in crop yields through widespread adoption of semi-dwarf cereal varieties with mutations affecting gibberellin (GA) biosynthesis or signaling pathways. Although semi-dwarf plants exhibited strong lodging resistance, their low nitrogen-use efficiency (NUE) demanded excessive inorganic fertilizer inputs, leading to severe and widespread environmental degradation. To boost sustainable agriculture, the "next-generation GR (NGR)" approach has emerged as a promising solution to limit chemical fertilizer use in high-yield crops. Nevertheless, inherent trade-offs between grain yield and NUE remain a major challenge to achieving agricultural sustainability. Strigolactones (SLs), a class of phytohormone discovered in 2008, play multifaceted roles comparable to those of GAs and have demonstrated significant promise for both conventional and modern crop improvement. Recent advances in artificial intelligence (AI)-driven protein engineering suggest that precision pyramiding of favorable alleles from GA and SL biosynthesis and signaling pathways holds a strong potential to revolutionize NGR through optimized phytohormone regulation. This review analyzes the fundamental drivers of GR success, synthesizes current understanding of GA-SL crosstalk in modulating nitrogen-responsive control of plant architecture and branching patterns, and elucidates the coordination between plant growth and metabolism in regulating NUE and grain yield. This knowledge will establish a framework for leveraging beneficial traits while mitigating pleiotropic trade-offs in current cultivars, thereby enabling rapid progress in the NGR breeding programs.