Ageing transcriptome meta-analysis reveals similarities and differences between key mammalian tissues.

Area of Science:

• Genomics
• Aging Research
• Bioinformatics

Background:

• Understanding functional changes during aging is crucial.
• Transcriptomic data offers insights into cellular processes.
• Cross-species and cross-tissue comparisons are valuable for identifying conserved aging mechanisms.

Purpose of the Study:

• To identify a conserved transcriptomic signature of aging across species and tissues.
• To functionally characterize age-related gene expression changes.
• To investigate the network properties of aging-associated genes.

Main Methods:

• Meta-analysis of 127 microarray and RNA-Seq datasets from mice, rats, and humans.
• Enrichment analysis and machine learning for functional interpretation.
• Protein-protein interaction and co-expression network analyses.

Main Results:

• Identified a common transcriptomic signature of aging across species and tissues, including specific signatures for brain, heart, and muscle.
• Revealed overexpression of immune and stress response genes and underexpression of metabolic and developmental genes.
• Demonstrated that aging-associated genes, particularly overexpressed ones, are often central in protein-protein interaction networks, while underexpressed genes in the brain are central in co-expression networks.

Conclusions:

• Aging exhibits conserved functional transcriptomic similarities across different tissues and species.
• Age-related gene expression changes are associated with specific network properties, suggesting broad functional consequences.
• The study highlights the importance of network context in understanding the impact of aging on gene expression.