Metabolomics and transcriptomics reveal dynamic flavonoid metabolic responses in Isatis indigotica roots following leaf cutting

The root of Isatis indigotica (Radix Isatidis) is a valuable traditional Chinese medicine rich in bioactive flavonoids, yet the regulatory mechanism by which leaf cutting affects root flavonoid metabolism remains unclear. In this two‑year (2024 and 2025) field experiment, we investigated the dynamic responses of root flavonoids in I. indigotica cultivar “Yulan No. 1” at five time points (0, 4, 8, 12, 16 days) after leaf cutting. Total flavonoid content was lowest at day 0 and highest at day 16 after leaf cutting and measured in both years and showed a consistent trend. Using UPLC‑MS/MS‑based widely-targeted metabolomics on the second‑year samples, 148 flavonoid metabolites were identified, among which 64 were differentially accumulated. K‑means clustering revealed six distinct temporal patterns. Eleven candidate differential metabolites showed strong positive correlations with total flavonoid content, with tenuifone exhibiting the highest correlation. Transcriptome sequencing identified 69 differentially expressed genes involved in flavonoid‑related pathways, including phenylpropanoid and flavonoid biosynthesis. Integrated correlation analysis constructed a metabolite‑gene network, highlighting multiple 4CL and CYP81E genes as candidate genes potentially involved in the flavonoid response. Notably, different isoforms of the same gene family showed opposite correlation directions with the same metabolites, indicating isoform‑specific regulatory complexity. Our findings demonstrate that leaf cutting induces a biphasic, quantitative reprogramming of root flavonoid metabolism with a largely conserved qualitative metabolite profile. This study provides a correlative metabolomic and transcriptomic landscape of leaf-cutting-induced flavonoid accumulation in I. indigotica roots, offering a theoretical basis for quality-oriented cultivation and identifying candidate metabolites and genes for further functional validation.