GEPREP: A comprehensive data atlas of RNA-seq-based gene expression profiles of exercise responses

Area of Science:

• Genomics and Exercise Physiology
• Bioinformatics and Data Science

Background:

• Physical activity influences gene expression across various tissues and cells.
• Publicly available RNA-sequencing (RNA-seq) data on exercise responses are abundant but often underutilized due to poor curation.
• A need exists for a well-organized, accessible resource for exercise-related gene expression data.

Purpose of the Study:

• To develop a comprehensive data atlas for RNA-sequencing-based gene expression profiles related to exercise.
• To improve the accessibility and usability of existing exercise genomics data.

Main Methods:

• Collected and curated high-quality RNA-sequencing datasets on exercise responses.
• Manually curated metadata for each sample, ensuring data quality and consistency.
• Uniformly processed data, corrected for batch effects, and organized information on an accessible website.

Main Results:

• The GEPREP atlas contains 69 RNA-seq datasets (26 human, 43 mouse) with 2126 total samples.
• Human samples primarily include skeletal muscle (87.2%) and blood (12.8%).
• Mouse samples cover 9 tissues, with skeletal muscle (35.7%) and brain (27.8%) being the most represented.

Conclusions:

• GEPREP provides a valuable, comprehensive resource for RNA-seq data on exercise-induced gene expression changes.
• The atlas's reliable annotations and user-friendly interface facilitate deeper insights into exercise physiology.
• This resource has the potential to advance research in exercise genomics and personalized health.