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Low Input Genome-Wide DNA Methylation Analysis with Minimal Library Amplification
Wan Kin Au Yeung1, Hiroyuki Sasaki2
1Division of Epigenomics and Development, Medical Institute of Bioregulation, Kyushu University, Fukuoka, Japan. donalday@bioreg.kyushu-u.ac.jp.
Methods in Molecular Biology (Clifton, N.J.)
|July 7, 2022
Summary
This study presents a post-bisulfite adaptor tagging (PBAT) protocol for whole genome bisulfite sequencing (WGBS) using only 200 cells. This method enables efficient genome-wide DNA methylation analysis with minimal cell input.
Area of Science:
- Genomics
- Epigenetics
- Molecular Biology
Background:
- Whole genome bisulfite sequencing (WGBS) is crucial for mapping DNA methylation at base resolution.
- Existing WGBS methods often require substantial cell numbers, limiting their application.
- Post-bisulfite adaptor tagging (PBAT) offers a way to reduce cell input requirements.
Purpose of the Study:
- To describe a refined PBAT protocol for preparing WGBS libraries from a small number of cells (200).
- To introduce a bioinformatic analysis pipeline for PBAT-generated WGBS data.
- To demonstrate the efficiency of the PBAT method for low-input WGBS.
Main Methods:
- Development and optimization of a post-bisulfite adaptor tagging (PBAT) library preparation protocol.
- Application of the PBAT protocol to prepare WGBS libraries from 200 cells.
- Outline of a downstream bioinformatic analysis workflow for PBAT-WGBS data.
- Sequencing of prepared libraries using the Illumina NovaSeq 6000 platform.
Main Results:
- A robust PBAT protocol for WGBS library construction from 200 cells was established.
- The protocol yields sufficient sequencing reads (approx. 800 million) for comprehensive human and mouse genome coverage.
- The generated data allows for approximately 15x genome coverage on Illumina NovaSeq 6000.
Conclusions:
- The described PBAT protocol significantly lowers the cell input requirement for WGBS.
- This advancement expands the utility of WGBS for epigenomic studies using limited cell samples.
- The protocol and associated bioinformatic analysis provide a powerful tool for low-input genome-wide DNA methylation profiling.

