2026-08-21 ジョージア大学（UGA）
Zebra sharks can live up to 30 years. A new modeling tool can correctly estimate an individual shark’s age to within two years. (Photo courtesy of Ripley’s Aquariums)
＜関連情報＞
- https://news.uga.edu/shark-dna-could-hold-answers-to-aging/
- https://onlinelibrary.wiley.com/doi/10.1111/mec.70326
Genome-Wide DNA Methylation Patterns Predict Age in the Zebra Shark (Stegostoma tigrinum) and Provide Insight Into the Evolution of Vertebrate Aging
Samantha L. Bock, Kady Lyons, Lei Yang, Jennifer Wyffels, Lance Adams, Nienke Klerks, Aaron Jeskie, Ellen Leever, Taylor Hartl, Javier Almunia, Dan Peterson, …
Molecular Ecology Published: 03 April 2026
DOI:https://doi.org/10.1111/mec.70326
ABSTRACT
Epigenomic changes are a hallmark of aging, and DNA methylation (DNAm) has emerged as the most reliable molecular marker of an individual’s age. Genome-wide patterns of age-associated hypo- and hypermethylation have been applied to generate predictive models (i.e., “epigenetic clocks”) capable of estimating chronological age in an increasingly diverse set of species including many mammals, a few birds, a reptile, and several bony fishes. Elasmobranchs (sharks, skates, and rays) are underrepresented in comparative investigations of epigenetic aging despite exhibiting exceptional life history variation, occupying a key basal position in the vertebrate phylogeny, and encompassing a large proportion of threatened species lacking accurate, non-lethal age determination methods. Here, we characterize epigenome-wide aging signals in the zebra shark (Stegostoma tigrinum), a long-lived elasmobranch of conservation concern, from whole-genome enzymatic methyl-sequencing of whole blood. Using a cohort of 51 known-age aquarium-bred individuals, we develop several epigenetic clock models capable of predicting chronological age with a median absolute error of 1.03–1.99 years (3.32%–6.42% of lifespan) based on the methylation status of as few as ten cytosines. We further apply our models to 19 individuals of unknown age originating from the wild. By profiling the broader age-associated methylome we demonstrate that these patterns not only predict age with high accuracy but also exhibit striking similarities in their genomic distributions to those observed in mammals pointing to conservation of the processes underlying epigenetic aging across vertebrates.
