The leaves of tea plants (Camellia sinensis) are used to produce tea, which is one of the most popular beverages consumed worldwide. The nutritional value and health benefits of tea are mainly related to three abundant characteristic metabolites; catechins, theanine and caffeine. Weighted gene co-expression network analysis (WGCNA) is a powerful system for investigating correlations between genes, identifying modules among highly correlated genes, and relating modules to phenotypic traits based on gene expression profiling. Currently, relatively little is known about the regulatory mechanisms and correlations between these three secondary metabolic pathways at the omics level in tea. In this study, levels of the three secondary metabolites in ten different tissues of tea plants were determined, 87,319 high-quality unigenes were assembled, and 55,607 differentially expressed genes (DEGs) were identified by pairwise comparison. The resultant co-expression network included 35 co-expression modules, of which 20 modules were significantly associated with the biosynthesis of catechins, theanine and caffeine. Furthermore, we identified several hub genes related to these three metabolic pathways, and analysed their regulatory relationships using RNA-Seq data. The results showed that these hub genes are regulated by genes involved in all three metabolic pathways, and they regulate the biosynthesis of all three metabolites. It is notable that light was identified as an important regulator for the biosynthesis of catechins. Our integrated omics-level WGCNA analysis provides novel insights into the potential regulatory mechanisms of catechins, theanine and caffeine metabolism, and the identified hub genes provide an important reference for further research on the molecular biology of tea plants.