Epigenetic models predict age and aging in plains zebras and other equids

Abstract

Five of the seven extant wild species of the genus Equus are species of significant conservation concern. Effective conservation and management of such threatened wildlife populations depends on the ability to estimate demographic trends and population viability and therefore requires accurate assessment of age structure. However, reliably aging wildlife is challenging as many methods are highly invasive, inaccurate, or both. Epigenetic aging models, which estimate individual age with high accuracy based on genomic methylation patterns, are promising developments in this regard. Importantly, epigenetic aging models developed for one species can potentially predict age with high accuracy in sister taxa. Using blood and biopsy samples from known age plains zebras (Equus quagga), we developed epigenetic clocks (ECs) to predict chronological age, and epigenetic pacemaker (EPM) models to predict biological age. We tested the ability of our blood-based EC to predict ages of Grevy's zebras, Somali asses and domestic horses, from blood samples. Because our samples came from a population with a complex pedigree, we also leveraged information from a previous sequencing effort to measure the association between levels of inbreeding (F and ROH) and the age acceleration as measured by DNA methylation. The resulting models describe the trajectory of epigenetic aging in plains zebras and accurately predict the ages of plains zebras and other equids. We found moderate support for a slight acceleration of aging with increased inbreeding.

DNA methylation aging and transcriptomic studies in horses

“…The data from the three additional equid species are described in a companion paper 55 that focuses on plains zebras ( Equus quagga ). Briefly, both blood ( n = 76 including 42 female samples, aged between 0.16 and 20.2 years, mean age = 5.2 years) and skin biopsy ( n = 24 including 9 female samples, aged between 0.16 and 24.8 years, mean age=5.9 years) samples from plains zebras were obtained from a captive population of zebras maintained in a semi-wild state by the Quagga Project 56 in the Western Cape of South Africa.…”

“…Blood samples from Grevy’s zebra (total n = 5 comprised of 4 males and 1 female, age ranged from 2.3 years to 18.5 years) and Somali wild ass (total n = 7 comprised of 6 males and 1 female, age ranged from 2.4 years to 10.0 years) were opportunistically collected from zoo-based animals during routine health exams 31 , 55 .…”

The Epigenetic Pacemaker is a more sensitive tool than penalized regression for identifying moderators of epigenetic aging

“…We also found that The EPM model generated for individuals exposed to PBB was sensitive to e PBB exposure, which has been linked to negative health outcomes, while the penalized regression epigenetic aging model was not. Additionally, the sensitivity of the EPM to moderators of epigenetic aging has been supported by two two recent studies investigating epigenetic aging in marmots [46] and zebras [47]. In the first of these studies, EPM models showed an association between hibernation and slowed epigenetic aging in marmots and in the second an increased epigenetic age associated with zebra inbreeding; no such associations were observed with penalized regression epigenetic age models.…”

Age is not just a number: how incorrect ageing impacts close-kin mark-recapture estimates of population size

“…We believe the CKMR method has great potential and, in some cases, is an improvement over other methods, but our study confirms that care that needs to be taken when ageing is biased. In such cases epigenetic ageing could be preferable, even though epigenetic ageing can still involve substantial uncertainty (e.g., Larison et al, 2021;Prado et al, 2021) and relies strongly on the quality of the training data (Mayne et al, 2023).…”