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Open access Jul 2026

Manipulating the Gibberellin Pathway Alters Harvest Index and Cannabinoid Content in Cannabis sativa L.

Cannabis sativa is a multi-purpose crop with a wide range of industrial and medicinal end uses. Despite its long history of cultivation, it has not received the same breeding efforts as many other crops due to regulatory barriers. In particular, it bypassed the Green Revolution, which improved harvest indices of crops via developing semi-dwarf varieties by manipulating endogenous gibberellin signalling pathways. We chemically manipulated gibberellin signalling through the exogenous application of gibberellic acid and the gibberellin biosynthesis inhibitor paclobutrazol. We used multi-omic analysis to determine the effect of these applications on the proteome, transcriptome and secondary metabolite accumulation to assess the potential of gibberellin modulation for improved C. sativa end uses. Paclobutrazol treatments resulted in a semi-dwarf phenotype with an improved high harvest index and enhanced cannabinoid accumulation. Differentially expressed gene and weighted gene co-expression network analysis revealed the importance of source/sink dynamics for harvest index, with the increased expression of sucrose synthases and sugar transporters key to the phenotypic changes induced by gibberellin modulation. At the same time, the availability of hexanoate precursors via the degradation of long-chain fatty acids emerged as a likely constraint on cannabinoid accumulation. This study provides a basis for exploring the manipulation of gibberellin pathways in C. sativa varieties and their relevance to cannabinoid production.

Lennard Garcia-de Heer, Matthew Nolan, J. Mieog et al. · 0 citations
#gene editing Review Open access Aug 2026

Strigolactones: From Fundamental Biology to Applications in Tree Breeding.

This study proposes a research and breeding roadmap progressing from molecular validation to medium- and short-term characterization in model trees and finally to multisite long-term ecological assessment, and presents a multiscale theoretical framework and testable pathways for translating SLs research from model plants to forestry applications.

Zhong-Zheng Ma, Wanxin Li, Qi Guo et al. · 0 citations