GA₃ enhances Rhodiola crenulata rhizome growth

Non-targeted metabolomic analysis of rhizomes of Rhodiola crenulata. This study aimed to elucidate how GA₃ regulates rhizome growth and biosynthesis of bioactive metabolites through source-sink reprogramming and substrate-directed metabolic allocation. Rhizome samples from GA₃-treated (500 ppm, 150 d) and control plants were analyzed using UPLC-MS/MS. A total of 2092 metabolites were identified, which were divided into 17 categories, including lipids, phenylpropanoids, and organic acids. Multivariate and KEGG enrichment analyses showed that GA₃ significantly reprogrammed central carbon and amino acid metabolism, downregulated phenylpropanoid and ABC transporter pathways, and redirected L-tyrosine flux to the biosynthesis of salidroside and tyrosol. These data provide comprehensive metabolomic evidence for the GA₃-mediated "source-sink reprogramming and substrate-directed allocation" model of R. crenulata, which will help understand the hormone-directed coordination between growth and secondary metabolism in medicinal plants.Rhizome Metabolomic AnalysisRhizome samples from both GA and CK treatment groups were collected, with four biological replicates per treatment. The samples were freeze-dried, homogenized into a fine powder, and 50 mg of the resulting lyophilized powder was extracted with 1 mL of 70% aqueous methanol. After centrifugation and filtration, the extracts were subjected to UPLC-MS/MS analysis.Chromatographic separation was performed by injecting 4 µL of each extract into a UPLC system coupled to an ESI-triple quadrupole-linear ion trap (QTRAP) mass spectrometer. Differential metabolites between groups were identified based on the variable importance in projection (VIP) score from the orthogonal projections to latent structures-discriminant analysis (OPLS-DA) model and the fold-change (FC). Metabolites with a VIP≥1 and an absolute FC≥2 (i.e., FC≤0.5 or≥2) were considered statistically significant. Functional annotation and pathway enrichment analysis of these significant metabolites were conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database.