Multidimensional transcriptome dataset for systematic evaluation of Jakyakgamcho-tang-induced cell signatures.

Area of Science:

• Herbal Medicine
• Pharmacology
• Genomics
• Transcriptomics

Background:

• Jakyakgamcho-tang (JGT) is a simple herbal formulation composed of Paeoniae Radix (PR) and Glycyrrhizae Radix et Rhizoma (GR).
• JGT is traditionally used for muscle-related diseases and inflammation, but its efficacy can be influenced by ingredient ratios and preparation methods.
• Existing research lacks comprehensive gene expression datasets to systematically evaluate these preparation variables.

Purpose of the Study:

• To generate a comprehensive gene expression dataset for Jakyakgamcho-tang (JGT) under varying preparation conditions.
• To enable multidimensional analysis of how JGT preparation factors influence cellular transcriptomic responses.
• To provide a foundation for the scientific optimization of traditional herbal medicine formulations.

Main Methods:

• Generated 513 transcriptome profiles using RNA-seq across three concentrations and three replicates.
• Investigated the effects of PR to GR ratios (2:1, 1:1, 1:2), solvents (water, 70% ethanol), and extraction methods (combined, individual).
• Utilized HepG2, C2C12, and PC12 cell lines for transcriptomic profiling.

Main Results:

• Created a structured dataset of 513 transcriptome profiles reflecting diverse JGT preparation variables.
• The dataset allows for detailed analysis of how ingredient ratios, solvents, and extraction methods impact gene expression.
• All raw and preprocessed data, along with standardized metadata, are publicly available via GEO.

Conclusions:

• This dataset serves as a crucial resource for understanding the transcriptomic effects of traditional herbal formulations like JGT.
• Facilitates scientific investigation into optimizing herbal medicine preparation for enhanced efficacy.
• Supports the advancement of evidence-based approaches in traditional medicine research.