Multi-tissue transcriptomic aging atlas reveals predictive aging biomarkers in the killifish

Area of Science:

• Gerontology and Molecular Biology
• Comparative Vertebrate Aging Research

Background:

• Aging causes progressive tissue dysfunction, frailty, and mortality.
• Understanding tissue-specific and systemic aging factors requires detailed characterization of aging features like gene expression dynamics.

Purpose of the Study:

• To create a comprehensive resource for studying aging dynamics across multiple tissues in the African turquoise killifish.
• To identify conserved and tissue-specific aging pathways and sex-age interactions.
• To develop transcriptomic clocks for age prediction and evaluate interventions.

Main Methods:

• RNA-sequencing performed on 13 tissues from 6 different ages in a sex-balanced killifish cohort.
• Analysis of gene expression to identify age-altered pathways and sex-age interactions.
• Development of tissue-specific transcriptomic clocks and biomarker identification.

Main Results:

• A comprehensive 'atlas' of aging across 13 killifish tissues was generated.
• Identified evolutionarily conserved, age-altered biological pathways and varying sex-age interaction strengths.
• Discovered a sex-specific aging-related myeloid bias in the head kidney and developed predictive transcriptomic clocks.

Conclusions:

• The African turquoise killifish is a valuable vertebrate model for studying aging across tissues.
• The generated dataset provides a powerful resource for aging research, enabling studies on dietary interventions and sex-specific aging dynamics.
• Tissue-specific transcriptomic clocks offer novel biomarkers for chronological age prediction.