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Age-associated increases in inter-individual gene expression variability across human tissues.

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Aging increases gene expression variability, not just differences, affecting distinct pathways. This study identifies key reference genes for studying human aging transcriptomics.

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Area of Science:

  • Genomics
  • Aging Research
  • Transcriptomics

Background:

  • Aging is characterized by physiological decline, but its transcriptomic underpinnings are not fully understood.
  • Previous research primarily focused on differentially expressed genes (DEGs), overlooking gene expression variability.

Purpose of the Study:

  • To investigate differentially variable genes (DVGs) as a measure of transcriptomic changes during aging.
  • To analyze the contribution of age- and sex-related DVGs to overall gene expression variability.
  • To explore the relationship between gene expression variability, biological pathways, and transcriptional noise.

Main Methods:

  • Utilized the Gene Stability Score (GSS) to identify DVGs across 30 tissue types from the Genotype-Tissue Expression (GTEx) project.
  • Analyzed age- and sex-related DVGs in nearly 1,000 individuals.
  • Performed gene regulatory network analysis and correlated inter-individual instability with cell-to-cell transcriptional noise.

Main Results:

  • Age- and sex-related DVGs constitute approximately 15% of expression variability, with age-related DVGs contributing 7.7%.
  • DVGs and DEGs impact distinct biological pathways.
  • Inter-individual gene expression instability correlates significantly with cell-to-cell transcriptional noise.
  • Gene regulatory network architecture shapes this variability.

Conclusions:

  • Aging involves both coordinated transcriptional programs and increased stochasticity at the individual and cellular levels.
  • Differentially variable genes offer new insights into aging transcriptomics beyond differential expression.
  • Identified robust reference genes (TBP, PUM1, TMEM199) for RT-qPCR in human aging studies.