Stubbs Thomas M, Bonder Marc Jan, Stark Anne-Katrien, Krueger Felix, von Meyenn Ferdinand, Stegle Oliver, Reik Wolf
Epigenetics Programme, The Babraham Institute, Cambridge, CB22 3AT, UK.
European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, CB10 1SD, UK.
Genome Biol. 2017 Apr 11;18(1):68. doi: 10.1186/s13059-017-1203-5.
DNA methylation changes at a discrete set of sites in the human genome are predictive of chronological and biological age. However, it is not known whether these changes are causative or a consequence of an underlying ageing process. It has also not been shown whether this epigenetic clock is unique to humans or conserved in the more experimentally tractable mouse.
We have generated a comprehensive set of genome-scale base-resolution methylation maps from multiple mouse tissues spanning a wide range of ages. Many CpG sites show significant tissue-independent correlations with age which allowed us to develop a multi-tissue predictor of age in the mouse. Our model, which estimates age based on DNA methylation at 329 unique CpG sites, has a median absolute error of 3.33 weeks and has similar properties to the recently described human epigenetic clock. Using publicly available datasets, we find that the mouse clock is accurate enough to measure effects on biological age, including in the context of interventions. While females and males show no significant differences in predicted DNA methylation age, ovariectomy results in significant age acceleration in females. Furthermore, we identify significant differences in age-acceleration dependent on the lipid content of the diet.
Here we identify and characterise an epigenetic predictor of age in mice, the mouse epigenetic clock. This clock will be instrumental for understanding the biology of ageing and will allow modulation of its ticking rate and resetting the clock in vivo to study the impact on biological age.
人类基因组中一组离散位点的DNA甲基化变化可预测实际年龄和生物学年龄。然而,尚不清楚这些变化是衰老过程的原因还是结果。也未表明这种表观遗传时钟是否为人类所特有,还是在实验上更易于操作的小鼠中保守存在。
我们从多个不同年龄的小鼠组织中生成了一套全面的全基因组碱基分辨率甲基化图谱。许多CpG位点显示出与年龄显著的组织无关相关性,这使我们能够开发一种小鼠年龄的多组织预测模型。我们的模型基于329个独特CpG位点的DNA甲基化来估计年龄,其平均绝对误差为3.33周,并且具有与最近描述的人类表观遗传时钟相似的特性。使用公开可用的数据集,我们发现小鼠时钟足够精确,能够测量对生物学年龄的影响,包括在干预情况下。虽然雌性和雄性在预测的DNA甲基化年龄上没有显著差异,但卵巢切除术会导致雌性显著的年龄加速。此外,我们发现年龄加速存在显著差异,这取决于饮食中的脂质含量。
在这里,我们鉴定并表征了小鼠的一种年龄表观遗传预测指标——小鼠表观遗传时钟。这个时钟将有助于理解衰老生物学,并将允许调节其滴答速率以及在体内重置时钟,以研究对生物学年龄的影响。