4.4 Article

ATAC-seq Optimization for Cancer Epigenetics Research

Journal

JOVE-JOURNAL OF VISUALIZED EXPERIMENTS
Volume -, Issue 184, Pages -

Publisher

JOURNAL OF VISUALIZED EXPERIMENTS
DOI: 10.3791/64242

Keywords

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Funding

  1. National Institutes of Health [P20GM104360, P20 GM104360]
  2. University of North Dakota School of Medicine and Health Sciences, Department of Biomedical Sciences

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ATAC-seq is a high-throughput sequencing method that utilizes Tn5 transposase to probe DNA accessibility, allowing identification of open chromatin regions and monitoring gene activation. In cancer cells, it is crucial to choose the appropriate cell lysis buffer, titrate Tn5 enzyme, and determine the starting cell volume for successful ATAC-seq library preparation.
The assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) probes deoxyribonucleic acid (DNA) accessibility using the hyperactive Tn5 transposase. Tn5 cuts and ligates adapters for high-throughput sequencing within accessible chromatin regions. In eukaryotic cells, genomic DNA is packaged into chromatin, a complex of DNA, histones, and other proteins, which acts as a physical barrier to the transcriptional machinery. In response to extrinsic signals, transcription factors recruit chromatin remodeling complexes to enable access to the transcriptional machinery for gene activation. Therefore, identifying open chromatin regions is useful when monitoring enhancer and gene promoter activities during biological events such as cancer progression. Since this protocol is easy to use and has a low cell input requirement, ATAC-seq has been widely adopted to define open chromatin regions in various cell types, including cancer cells. For successful data acquisition, several parameters need to be considered when preparing ATAC-seq libraries. Among them, the choice of cell lysis buffer, the titration of the Tn5 enzyme, and the starting volume of cells are crucial for ATAC-seq library preparation in cancer cells. Optimization is essential for generating high-quality data. Here, we provide a detailed description of the ATAC-seq optimization methods for epithelial cell types.

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