MetaMEx

MetaMEx aggregates transcriptomic data to enable meta-analysis of skeletal muscle responses to exercise and inactivity.

Key Features:

• Extensive Dataset Integration: Integrates 66 published human transcriptomic datasets spanning aerobic and resistance exercise, acute and chronic training, and inactivity.
• Meta-Analysis Methodology: Applies meta-analysis techniques to synthesize results across studies and identify consistent gene expression patterns and pathways.
• Gene Ontology and Pathway Analyses: Performs gene ontology and pathway analyses to reveal pathways selectively activated or repressed by inactivity, aerobic versus resistance training, and acute versus chronic exercise.
• Identification of Key Genes: Detects NR4A3 as a gene highly responsive to both exercise and inactivity and implicated in mediating metabolic responses to exercise-like stimuli.
• Differential Response Insights: Characterizes variations in transcriptomic responses to exercise among individuals with metabolic impairments.

Scientific Applications:

• Molecular basis of muscle adaptation: Enables investigation of gene expression changes underlying skeletal muscle adaptation to different exercise modalities and inactivity.
• Intervention development: Informs targeted exercise intervention studies by linking exercise type and duration to transcriptional responses.
• Metabolic regulation research: Supports study of genes such as NR4A3 to elucidate genetic mechanisms of metabolic regulation in muscle.

Methodology:

Integrates 66 published human transcriptomic datasets and applies meta-analysis along with gene ontology and pathway analyses to identify consistent transcriptional responses and key genes such as NR4A3.