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Abstract
Effective conservation and management of threatened wildlife populations require an accurate assessment of age structure to estimate demographic trends and population viability. Epigenetic aging models are promising developments because they estimate individual age with high accuracy, accurately predict age in related species, and do not require invasive sampling or intensive long-term studies. Using blood and biopsy samples from known age plains zebras (Equus quagga), we model epigenetic aging using two approaches: the epigenetic clock (EC) and the epigenetic pacemaker (EPM). The plains zebra EC has the potential for broad application within the genus Equus given that five of the seven extant wild species of the genus are threatened. We test the EC’s ability to predict age in sister taxa, including two endangered species and the more distantly related domestic horse, demonstrating high accuracy in all cases. By comparing chronological and estimated age in plains zebras, we investigate age acceleration as a proxy of health status. An interaction between chronological age and inbreeding is associated with age acceleration estimated by the EPM, suggesting a cumulative effect of inbreeding on biological aging throughout life.
Larison et al. report epigenetic aging models in plains zebras (Equus quagga) using the epigenetic clock and epigenetic pacemaker approaches. Their epigenetic clock allows age to be accurately estimated in endangered sister species, and the pacemaker model identifies an association between inbreeding and accelerating aging.
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1 University of California, Department of Ecology and Evolutionary Biology, Los Angeles, USA (GRID:grid.19006.3e) (ISNI:0000 0000 9632 6718); University of California, Center for Tropical Research, Institute of the Environment and Sustainability, Los Angeles, USA (GRID:grid.19006.3e) (ISNI:0000 0000 9632 6718)
2 University of California, Department of Ecology and Evolutionary Biology, Los Angeles, USA (GRID:grid.19006.3e) (ISNI:0000 0000 9632 6718)
3 University of California, Human Genetics, David Geffen School of Medicine, Los Angeles, USA (GRID:grid.19006.3e) (ISNI:0000 0000 9632 6718)
4 University of California, Department of Population Health and Reproduction, School of Veterinary Medicine, Davis, USA (GRID:grid.27860.3b) (ISNI:0000 0004 1936 9684)
5 University of California, Department of Molecular, Cell and Developmental Biology, Los Angeles, USA (GRID:grid.19006.3e) (ISNI:0000 0000 9632 6718)
6 HudsonAlpha Institute for Biotechnology, Huntsville, USA (GRID:grid.417691.c) (ISNI:0000 0004 0408 3720); Stanford University, Department of Genetics, Stanford, USA (GRID:grid.168010.e) (ISNI:0000000419368956)
7 Quagga Project, Elandsberg Farms, Hermon, South Africa (GRID:grid.168010.e)
8 Zoological Operations, SeaWorld Parks and Entertainment, Orlando, USA (GRID:grid.448661.9) (ISNI:0000 0000 9898 6699)
9 White Oak Conservation, Yulee, USA (GRID:grid.448661.9)
10 University of California, Human Genetics, David Geffen School of Medicine, Los Angeles, USA (GRID:grid.19006.3e) (ISNI:0000 0000 9632 6718); University of California, Los Angeles, Department of Biostatistics, Fielding School of Public Health, Los Angeles, USA (GRID:grid.19006.3e) (ISNI:0000 0000 9632 6718); Altos Labs, San Diego, USA (GRID:grid.19006.3e)