Epigenetic Aging Clock for Long-Lived Fish Collected from the Wild

Age information is fundamental in population biology. In fisheries management, robust and effective stock assessment models rely on fecundity and survival rates, and other life history traits that are generally age specific. Current aging methods for most fish species are based on the number of otolith growth rings, a time intensive method that requires lethal sampling and highly specialized expertise. To supplement current otolith-based aging efforts, here we develop a DNA methylation approach for aging Atlantic Halibut. We conducted whole-genome methylation sequencing on 66 wild caught individuals with otolith-derived age estimates. The resulting 14,588 CpG sites were evaluated as predictors of age in an elastic net model. We found a strong positive linear correlation between otolith age and predictions using a subset of 87 CpG sites selected by the elastic net model that had a mean absolute error of less than one year. The enzymatic treatment required for methylation sequencing with short-read technology like Illumina is still cost-prohibitive for routine application of large numbers of individuals. Accordingly, we conducted a successful pilot test to use adaptive nanopore sequencing for rapid, large-scale aging, and developed a framework to process the data for use in an aging framework. Our technique can be used to age Atlantic halibut when non-lethal sampling is needed (e.g., tagging studies) and to supplement otolith aging data for lethally sampled fish. Supplementary Material File (maintext_epigeneticagingestimate.docx) - Download - 702.92 KB Information & Authors Information Version history Copyright This work is licensed under a Non Exclusive No Reuse License.

Authors Metrics & Citations Metrics Article Usage 500views 234downloads Citations Download citation Ellen Weise, Cait Nemeczek, Cornelia den Heyer, et al. Epigenetic Aging Clock for Long-Lived Fish Collected from the Wild. Authorea. 10 January 2025. DOI: https://doi.org/10.22541/au.173649084.49050224/v1 DOI: https://doi.org/10.22541/au.173649084.49050224/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu.