Project Summary Epigenetic clocks based on DNA cytosine methylation (DNAme) are currently the most robust biomarkers of aging in mammals. They can accurately estimate the age of diverse biosamples and are responsive to interventions–such as caloric restriction or rapamycin treatment—that are thought to slow aging. Despite their increasing ubiquity in the field, the biology underlying epigenetic clocks is poorly understood. Likewise, their potential as a readout to test pharmaceutical interventions and discover new aging-associated genes is yet unrealized. One of the main limitations to using DNAme clocks at scale is the cost of current methods. Commonly used technologies to assay epigenetic age, such as methylation chip and RRBS, measure hundreds of thousands of CpGs and cost hundreds of dollars per sample. An economical, targeted approach that can measure virtually any epigenetic clock is badly needed to enable larger experiments with epigenetic age as the primary readout. For the F99 phase of this proposal, I have developed a new method called Tagmentation-based Indexing for Methylation SEquencing (TIME-Seq) that enables targeted DNAme clock sequencing of dozens to hundreds of samples simultaneously. I have shown that TIME-Seq is capable of measuring diverse epigenetic clocks at a range of scales and decreases costs 1-2 orders of magnitude. I plan to validate the method via comparison to conventional methods and build novel epigenetic age predictors and biomarkers trained on age-related frailty metrics. In the K00 phase, I will investigate the biology driving epigenetic clocks using aging mouse muscle as a model. I will take a multiomic approach, using TIME-Seq and established genomic methods, to test the hypothesis that heritable loss of silencing at developmental loci, in part, drives ticking of the clocks. This proposal will provide the aging field with a much-needed method for cost-effective and high- throughput epigenetic clock assay, as well as novel biomarkers based on frailty, which can be used in academic research and a clinical context. Ultimately, the method will help us understand how and why it is possible to build DNAme clocks and what they tell us about epigenomic dysfunction during aging.