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

项目摘要 基于DNA胞嘧啶甲基化（DNAme）的表观遗传时钟是目前最可靠的生物标志物 哺乳动物的衰老。它们可以准确地估计不同生物样本的年龄，并对 干预措施，如热量限制或雷帕霉素治疗，被认为是减缓衰老。尽管他们 随着表观遗传时钟在该领域的日益普遍，人们对表观遗传时钟的生物学基础知之甚少。同样，他们的 作为检测药物干预和发现新的衰老相关基因的读出器， 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。通常 使用技术来测定表观遗传年龄，如甲基化芯片和RRBS， 数千个CpG，每个样本花费数百美元。一种经济、有针对性的方法， 测量几乎任何表观遗传时钟是迫切需要的，以使更大的实验与表观遗传年龄作为 主要读数。 对于本提案的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），可实现数十至数百个靶向DNAme时钟测序 样品同时我已经证明，TIME-Seq能够以一种特定的速度测量不同的表观遗传时钟。 范围的规模和减少成本1-2个数量级。我计划通过比较来验证该方法， 传统的方法，并建立新的表观遗传年龄预测和生物标志物训练的年龄相关的弱点 指标. 在K 00阶段，我将研究生物学驱动表观遗传时钟使用老化的小鼠肌肉作为一个 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 这一假说认为，在发育基因座沉默的遗传损失，部分驱动时钟滴答作响。 该提案将为老龄化领域提供一种急需的成本效益高的方法， 通量表观遗传时钟分析，以及基于脆弱性的新生物标志物，可用于学术研究。 研究和临床背景。最终，该方法将帮助我们了解如何以及为什么有可能建立 DNA时钟以及它们告诉我们的关于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.