Tagmentation-based Indexing for Methylation Sequencing as a novel method of high-throughput methylation clock measurement

项目总结 尽管表观遗传时钟在表观基因组学研究和人类健康中的重要性，但方法 测量甲基化年龄在很大程度上仍然昂贵，不适用于高通量分析。我们 正在开发一种新的方法，称为基于标记的甲基化测序索引(time-seq)，用于 高性价比的表观遗传时钟位点高通量甲基化测序。Time-Seq将降低成本 在单个步骤(标记)中附加条形码和片段DNA，并使用 生物素核糖核酸诱饵。可行性研究表明，Time-Seq与多路传输和 成功地丰富了时钟站点。我们的第一个目标是优化Time-Seq作为一种高通量的检测方法 测量基于DNA甲基化的生物标记物。我们将通过优化生物素-rna的设计来实现这一点。 诱饵以适应人类和小鼠不同的DNA甲基化时钟。我们还将比较 与已建立的表观遗传时钟分析方法相比，时间序列的重复性和准确性。我们预测 这一时间序列将使甲基化测序实验的规模至少增加两个数量级 通过降低每个样本的成本，使时钟测量更容易实现。此外，我们还将 调整时间顺序，以便在单电池上使用。目前，DNA甲基化时钟测量平均甲基化 组织中许多细胞的年龄，尽管组织中可能只有一小部分细胞类型 贡献了大部分的信号。因此，我们将开发一种单小区时间序列(scTIME-seq)协议 基于组合索引在细胞水平上理解表观遗传老化。此方法将允许 甲基化时钟位点细胞间变异的测量，将为深入了解 衰老。最终，我们的目标是增加获得定向甲基化测序的机会，并将其设想为 研究和个性化医疗中使用的标准工具。

PROJECT SUMMARY Despite the importance of the epigenetic clock in epigenomics research and to human health, methods to measure methylation age remain for the most part expensive and not amenable to high throughput assays. We are developing a new method, called Tagmentation-based Indexing for MEthylation sequencing (TIME-seq), for cost-effective high throughput methylation sequencing of epigenetic clock sites. TIME-seq will reduce costs by attaching barcodes and fragmenting DNA in a single step (tagmentation) and by enriching for clock sites using biotinylated RNA baits. Feasibility studies demonstrate that TIME-seq is compatible with multiplexing and successfully enriches for clock sites. Our first goal is to optimize TIME-seq as a high-throughput assay for measuring DNA methylation-based biomarkers. We will accomplish this by optimizing the design of biotin-RNA baits to accommodate diverse DNA methylation clocks from humans and mice. We will also compare the reproducibility and accuracy of TIME-seq to those of established assays for epigenetic clock analysis. We predict that TIME-seq will allow for an increase in the scale of methylation sequencing experiments by at least two orders of magnitude and make clock measurement more accessible by lowering the cost per sample. Moreover, we will adapt TIME-seq for use on single cells. Currently, DNA methylation clocks measure the average methylation age of many cells in a tissue, despite the possibility that only a small number of cell types within a tissue contribute to the majority of the signal. Therefore, we will develop a single-cell TIME-seq (scTIME-seq) protocol based on combinatorial indexing to understand epigenetic aging at the cellular level. This method will allow for measurement of cell-to-cell variation at methylation clock sites and will provide insight into the mechanisms of aging. Ultimately, we aim to increase access to targeted methylation sequencing, and envision it becoming a standard tool used in research and personalized medicine.