Methylation-based markers for the estimation of age in African Cheetah, Acinonyx jubatus

Age is a key demographic in conservation biology where individual age classes show diffuse differences in terms of important population dynamics metrics such as morbidity and mortality. Furthermore, several traits including reproductive potential show clear senescence with aging. Thus, the ability to estimate the ages for the individuals of a population as part of age class assignment is critical in understanding both the current population structure as well as in modelling and predicting the future survival of species. This study explored the utility of age-related changes in methylation for six candidate genes, EDARADD, ELOVL2, FHL2, GRIA2, ITGA2B, and PENK, to create an age estimation model in captive cheetah. Gene orthologues between humans and cheetah were retrieved containing a hundred CpG’s. Target regions were assayed for differential methylation and fragmentation patterns in fifty samples using mass array technology for a total of seventy-seven CpG clusters. Correlation analyses between CpG methylation and chronological age identified six CpG’s with an age relationship, of which four were hypomethylated and two were hypermethylated. Regression models, fitted for different combinations of CpG’s, indicated that age models using four and six CpG’s were most accurate, with the six CpG model having superior correlation and predictive power (R2 = 0.70, Mean Absolute Error = 25 months). This model was more accurate than previous attempts using methylation sensitive Polymerase Chain Reaction and performed similarly to models created using a candidate gene approach in several other mammal species, making methylation a promising tool of age estimation in cheetah.