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

> **NIH NIH R21** · HARVARD MEDICAL SCHOOL · 2021 · $626,327

## Abstract

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.

## Key facts

- **NIH application ID:** 10273233
- **Project number:** 1R21HG011850-01
- **Recipient organization:** HARVARD MEDICAL SCHOOL
- **Principal Investigator:** DAVID A. SINCLAIR
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $626,327
- **Award type:** 1
- **Project period:** 2021-09-17 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10273233

## Citation

> US National Institutes of Health, RePORTER application 10273233, Tagmentation-based Indexing for Methylation Sequencing as a novel method of high-throughput methylation clock measurement (1R21HG011850-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10273233. Licensed CC0.

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