A novel method to identify regulators of biological aging 
based on high-throughput sequencing of epigenetic clocks.

项目概要 基于 DNA 胞嘧啶甲基化 (DNAme) 的表观遗传时钟是目前最强大的生物标志物 哺乳动物的衰老。他们可以准确估计不同生物样本的年龄并对 热量限制或雷帕霉素治疗等干预措施被认为可以延缓衰老。尽管他们的 随着表观遗传时钟在该领域的日益普及，人们对表观遗传时钟背后的生物学知之甚少。同样，他们的 作为测试药物干预措施和发现新的衰老相关基因的读数的潜力尚未确定 未实现。大规模使用 DNAme 时钟的主要限制之一是当前方法的成本。常见 使用甲基化芯片和RRBS等技术来测定表观遗传年龄，测量了数百个 每个样品需要数千个 CpG，成本为数百美元。一种经济的、有针对性的方法，可以 迫切需要测量几乎任何表观遗传时钟，以便能够以表观遗传年龄为基础进行更大规模的实验。 主要读数。 对于该提案的 F99 阶段，我开发了一种称为基于标记的索引的新方法 用于甲基化测序 (TIME-Seq)，可实现数十到数百个目标 DNAme 时钟测序 样品同时进行。我已经证明 TIME-Seq 能够以一定的速度测量不同的表观遗传时钟 规模范围和成本降低 1-2 个数量级。我计划通过比较来验证该方法 传统方法并建立针对年龄相关衰弱的新型表观遗传年龄预测因子和生物标记物 指标。 在 K00 阶段，我将研究驱动表观遗传时钟的生物学，使用衰老的小鼠肌肉作为 模型。我将采用多组学方法，使用 TIME-Seq 和已建立的基因组方法来测试 假设发育位点沉默的遗传性丧失在一定程度上驱动了时钟的滴答作响。 该提案将为老龄化领域提供一种急需的方法，以实现成本效益高、 吞吐量表观遗传时钟测定，以及基于脆弱性的新型生物标志物，可用于学术 研究和临床背景。最终，该方法将帮助我们理解如何以及为何可以构建 DNAme 时钟及其告诉我们衰老过程中表观基因组功能障碍的信息。

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.