Age prediction of green turtles with an epigenetic clock

Benjamin Mayne, Walter Mustin, Vandanaa Baboolal, Francesca Casella, Katia Ballorain, Mathieu Barret, Mathew A. Vanderklift, Anton D. Tucker, Darren Korbie, Simon Jarman, Oliver Berry

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


Age is a fundamental life history attribute that is used to understand the dynamics of wild animal populations. Unfortunately, most animals do not have a practical or nonlethal method to determine age. This makes it difficult for wildlife managers to carry out population assessments, particularly for elusive and long-lived fauna such as marine turtles. In this study, we present an epigenetic clock that predicts the age of marine turtles from skin biopsies. The model was developed and validated using DNA from known-age green turtles (Chelonia mydas) from two captive populations, and mark-recapture wild turtles with known time intervals between captures. Our method, based on DNA methylation levels at 18 CpG sites, was highly accurate with a median absolute error of 2.1 years (4.7% of maximum age in data set). This is the first epigenetic clock developed for a reptile and illustrates their broad applicability across a broad variety of vertebrate species. It has the potential to transform marine turtle management through a nonlethal and inexpensive method to provide key life history information.

Original languageEnglish
Pages (from-to)2275-2284
Number of pages10
JournalMolecular Ecology Resources
Issue number6
Early online date2022
Publication statusPublished - Aug 2022


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