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Building an ‘epigenetic clock’: utilizing whole genome DNA methylation patterns to predict age in haddock, Melanogrammus aeglefinus


Abstract

Age-based population models are a gold standard approach to estimate stock size and sustainable catch recommendations for effective fisheries management. Traditional ageing by counting annuli on their ear stones (otoliths), is labor-intensive, lethal, and can be inaccurate for long-lived fishes. In this study, we present an accurate, non-lethal epigenetic clock method for predicting age in haddock, Melanogrammus aeglefinus, one of the most valuable commercial fisheries in the north Atlantic Ocean. Pectoral fin tissue (n = 140 individuals) was collected during Fall 2022 and Spring 2023 bottom trawl surveys in the Georges Bank-Gulf of Maine region, and whole-genome bisulfite sequencing was conducted to measure CpG loci DNA methylation levels. The most age-predictive loci were identified using a three-step modeling approach: a Bayesian generalized linear mixed model with length and sex as random factors followed by elastic net regression models with a 70/30 train-test split. The final model used 109 loci to predict age with a mean absolute error of 0.17 years. Hypo- and hyper-methylated age-predictive loci were found throughout the genome and were enriched in intragenic regions with functions related to development, immunity, transcriptional regulation, and signal transduction. This study provides an accurate, cost-effective, and scalable epigenetic tool for fisheries management to predict the age of haddock.

Acknowledgements

We would like to thank the Ecosystems Surveys Branch of the NOAA Fisheries Northeast Fisheries Science Center and the officers and crew of the NOAA Ship Henry B. Bigelow for their assistance in securing biological samples from the Fall 2022 and Spring 2023 Bottom Trawl Surveys.

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Emma L. Strand.

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Strand, E.L., McBride, R., Robillard, E. et al. Building an ‘epigenetic clock’: utilizing whole genome DNA methylation patterns to predict age in haddock, Melanogrammus aeglefinus.
Sci Rep (2026). https://doi.org/10.1038/s41598-026-73271-7

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