What is Single Cell ATAC Sequencing?

30.07.2025

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The basics of single cell ATAC sequencing

ATAC-seq stands for Assay for Transposase-Accessible Chromatin using sequencing. It maps open chromatin regions across the genome.

DNA is often tightly packaged around histones, forming units called nucleosomes. Only 2-3% of total genome is “open”, or “accessible”, allowing regulatory molecules such as transcription factors to bind and regulate gene expression, DNA replication, and repair.

Unlike RNA sequencing, which captures the transcriptome (the set of all mRNA molecules), ATAC-seq focuses on the accessibility of DNA.

Interested in RNA profiling?

Check out "What is Single Cell RNA sequencing" article

Single cell ATAC-seq (scATAC-seq) takes this a step further by profiling chromatin accessibility at the resolution of individual cells. Using a highly specific enzyme called Tn5 transposase, scATAC-seq labels open chromatin regions. By combining this information with cell barcodes, researchers can identify DNA sequences accessible to transposase in each individual cell.

Why is scATAC-seq important?

scATAC-seq data is valuable for:

Understanding the regulatory elements (like enhancers and promoters) that act as on/off switches for gene expression.
Revealing chromatin accessibility profiles unique to each cell type and identifying rare or novel cell populations.
Gaining insights into differences between healthy and diseased states, as changes in chromatin accessibility often precede changes in gene expression.

What is the difference between scRNA-seq and scATAC-seq?

While gene expression analysis (like scRNA-seq) tells you which genes are being transcribed, scATAC-seq reveals how those genes are regulated—helping you identify potential targets for therapeutic intervention.

How does scATAC-seq work?

Preparing samples for scATAC-seq

Cell dissociation for scATAC-seq.

The first step is to obtain a single-cell suspension from your tissue of interest. This involves carefully dissociating the tissue to preserve cell viability, which is crucial for accurate downstream analysis.

Nuclei isolation

After dissociation, cells are lysed gently to release intact nuclei. Careful optimization is essential because the ATAC-seq protocol targets chromatin within the nucleus, and high-quality nuclei are key for reliable results.

Tagmentation with Tn5 Transposase

Tn5 is an enzyme that can simultaneously cut DNA and insert sequencing adapters—a process known as tagmentation. It specifically binds to open chromatin regions. Therefore, only accessible regions of the DNA are tagged.

The adapters inserted by Tn5 allow for the subsequent amplification and sequencing of these open chromatin regions, enabling genome-wide profiling of regulatory landscapes.

How to encode nuclei for scATAC-seq

To distinguish individual cells, unique barcodes are introduced during library preparation. These barcodes tag DNA fragments from each nucleus, allowing for single-cell resolution during sequencing and analysis.

Sequencing the location of Tn5 integrations

The barcoded DNA fragments are then sequenced using high-throughput platforms. The resulting data reveal the precise locations where Tn5 inserted adapters, corresponding to accessible chromatin regions in each cell.

Bioinformatics: Identifying and Calling Peaks

After sequencing, the key data analysis steps include pre-processing the FASTQ data, aligning reads to the reference genome, and identifying “peaks”—regions with high read density that indicate open chromatin.

Bioinformatics pipelines such as CeleSCOPE-scATAC (https://github.com/singleron-RD/scatac), ArchR (Granja et al., 2021) and Signac (Stuart et al., 2021) are used to for scATAC-seq data analysis.

These software packages also help to deconvolute the data to assign peaks to individual cells, cluster cell types, and infer regulatory networks.

A typical scATAC-seq data analysis workflow (Fang et al. 2021. CC BY 4.0)

An example of differential accessibility visualization (Stuart et al. 2021).

Each coloured frequency plot represents the frequency of Tn5 integration across regions of the genome for each of the cell types. A detailed explanation of the analysis workflow can be found at https://doi.org/10.1038/s41467-021-21583-9

Do you need single cell sequencing data for ATAC seq?

While bulk ATAC-seq provides an average chromatin accessibility profile across many cells, single cell ATAC-seq is essential for resolving cell-to-cell heterogeneity. If your research requires understanding regulatory differences between individual cells, scATAC-seq is the method of choice.

Singleron Biotechnologies’ Single Cell ATAC Sequencing Kits and Service

scATAC-seq involves a complex workflow and requires careful optimization. Singleron provides end-to-end services for single cell ATAC-seq, maximising your success rate with precious tissue samples.

Have more questions about scATAC-seq? Ask a scientist.

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References:

Fang, R., Preissl, S., Li, Y. et al. (2021). Comprehensive analysis of single cell ATAC-seq data with SnapATAC. Nat Commun, 12, 1337. https://doi.org/10.1038/s41467-021-21583-9

Granja JM, Corces MR et al. (2021). ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis. Nat Genetics, 53, 403-411. https://doi.org/10.1038/s41588-021-00790-6

Stuart, T., Srivastava, A., Madad, S. et al. (2021). Single-cell chromatin state analysis with Signac. Nat Methods, 18, 1333–1341. https://doi-org/10.1038/s41592-021-01282-5

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A post by Prabhakaran Munusamy

Prabhakaran Munusamy is a Bioinformatics Scientist at Singleron with more than 10 years of experience in genomics and transcriptomics data analysis. Holding a Master's degree in Bioinformatics from McGill University, Canada, he specializes in leveraging high-performance and cloud computing resources to develop robust bioinformatics workflows. With a strong publication record, Prabha is recognized for his analytical mindset, technical expertise, and clear scientific communication. In his free time, Prabha enjoys playing badminton and is among the top players on the Singleron team.