Large scale cell-based transcriptome data treated with Jakyakgamcho-tang in HepG2 cell

Jakyakgamcho-tang (JGT) is the simplest form of herbal medicine composed of Paeoniae Radix (PR) and Glycyrrhizae Radix at Rhizoma (GR), and has been used to treat muscle-related diseases and inflammation. However, the pharmacological effects of JGT may vary depending on the ratio of the constituent herbs and the main preparation conditions of the extraction method. Nevertheless, no gene expression dataset systematically reflecting these various variables has existed to date. In this study, a total of 498 transcriptome profiles were constructed with three concentrations and three replicates of RNA-seq data. It is structured to enable multidimensional analysis of the effects of various preparation conditions on gene expression by combining the ratio of PR:GR (2:1, 1:1, 1:2), solvent (water, 70% ethanol), and extraction method (combined decoction vs. separate decoction) of JGT, targeting three cell lines (HepG2, C2C12, and PC12). All raw and preprocessed data are deposited available through GEO, and standardized metadata and ingredient data are also provided. This dataset provides a foundation for exploring how traditional herbal medicine formulations affect cellular transcriptomic responses and can serve as a baseline for scientific optimization of herbal medicines. Overall design: Whole transcriptomic analysis in HepG2 cells was conducted, comparing cells treated with a vehicle control to those treated with three different concentrations of JGT-E and JGT-W. All experiments were performed in triplicate. We constructed the pharmacological transcriptome data obtained through combinatorial conditions, such as extraction orders (individual herbs extracted or the herb-mixed JGT extracted), combination ratios (two herbs into 2:1, 1:1, and 1:2), two extracting methods (hot water or 70% ethanol).