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

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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.