## 2 Results
### Correlation Analysis of Transcriptome and Metabolome Expression Data  
The enrichment analysis of differentially expressed genes (DEGs) and differential accumulation metabolites (DAMs) between each control group revealed significant enrichments in the \"Biosynthesis of various plant secondary metabolites\", \"Phenylpropanol biosynthesis\", \"Glycolysis/Gluconeogenesis\", as well as amino acid metabolic pathways including \"Arginine and proline metabolism\", \"Tyrosine metabolism\", and \"Cysteine and methionine metabolism\".  
To further investigate the regulatory network of differentially expressed genes, we conducted a correlation analysis between differential metabolites and differentially expressed genes in each comparison group. We then identified the correlations that met the criteria of an absolute value of the Pearson correlation coefficient greater than 0.8 and a \(p\)-value < 0.05. The fold differences of genes and metabolites corresponding to these correlations were visualized using a nine-quadrant plot (Figures 9 and S9). Taking husk and leaf callus control groups as examples, our results demonstrated that genes and metabolites in quadrants 3 and 7 exhibited a positive correlation, indicating that gene expression changes positively regulated the abundance of metabolites. Specifically, there were 2125 differential genes positively regulating 267 differential metabolites. In quadrants 1 and 9, we observed a negative correlation between genes and metabolites, suggesting that gene expression changes negatively regulated the abundance of metabolites. In this case, there were 52 differential genes negatively regulating 192 differential metabolites. Among these findings, terpenoids were found to be regulated by a total of 1274 genes (320 negatively correlated, 955 positively correlated). Additionally, delta-guaiaceae was found to regulate 36 genes (11 negatively correlated, 25 positively correlated). Genes located in quadrants 2, 4, 6, and 8 were not simultaneously up-regulated or down-regulated with their corresponding metabolite counterparts. In quadrant 5, no significant difference was observed in both gene expression and metabolite abundance. The findings suggest the existence of an intricate regulatory mechanism linking variations in metabolite accumulation and gene expression abundance across different tissue sites of _A. sinensis_.  
Figure 8: Schematic representation of DEG pathways involved in the sesquiterpene synthesis pathway. The color scale from green to red represents the expression level of DEGs from low to high. AACT: acetyl-CoA C-acetyltransferase; HMGS: 3-hydroxy-3-methylglutaryl CoA synthase; HMGR: 3-hydroxy-3-methylglutaryl coenzyme A reductase; MVK: mevalonate kinase; PMK: phosphomechanate kinase; MVD: mevalonate diphosphate decarboxylase; DXS: 1-deoxy-D-xylulose 5-phosphate  
synthase; DXR: 1-deoxy-D-xylulose 5-phosphate reductoisomerase; MCT: mesaconate CoA-transferase; CMK: cytidylate kinase; MCS: 2-C-methyl-D-erythriotl-2.4-cyclodextrin diphosphate synthase; HDS: 4-hydroxy-3-methyl but-2-(E)-enyl diphosphate synthase; HDR: 4-hydroxy-3-methyl but-2-(E)-enyl diphosphate reductase; IDI: isopentenyl diphosphate isomerase; FPS: farnesyl-pyrophosphate synthetase; FPP: farnesyl pyrophosphate synthase; SesTPS: sesquiterpene synthase.