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

Abstract

Aging is associated with progressive tissue dysfunction, leading to frailty and mortality. Characterizing aging features, such as changes in gene expression and dynamics, shared across tissues or specific to each tissue, is crucial for understanding systemic and local factors contributing to the aging process. We performed RNA sequencing on 13 tissues at six different ages in male and female African turquoise killifish, the shortest-lived vertebrate that can be raised in captivity. This comprehensive, sex-balanced 'atlas' dataset revealed varying strength of sex-age interactions across killifish tissues and age-altered genes and biological pathways that are evolutionarily conserved in mice and humans. We discovered a female-biased myeloid shift with age in the killifish hematopoietic organ, developed tissue-specific 'transcriptomic clocks' and identified biomarkers predictive of chronological age. We showed the importance of sex-specific clocks for selected tissues, validated the tissue clocks with an independent transcriptomic dataset and used them to evaluate different lifespan interventions in the killifish. Our work provides a comprehensive resource for studying aging dynamics across tissues in the killifish, a powerful vertebrate aging model.