An Overview of Single-Cell Epigenomics Methods

Probe epigenetic dimensions with single-cell resolution using scBS-seq, scCHIP-seq, scATAC-seq, and more

single cell epigenomics methods

Although cells have the same genetic material, they can function differently. Single-cell RNA sequencing has revealed how heterogeneous the transriptome of an individual cell may be with a homogeneous cell population or tissue.  Single-cell genome sequencing has provided insights into genomic variations that occur in physiology and in diseases.

Today we can probe the majority of epigenetic dimensions with single-cell resolution through multiple methods (Table 1). Studying individual cells offers insight into molecular components of the genome and its functional output. Epigenetic marks can affect the cells’ transcriptional output and consequently their function. Therefore understanding the effects of these epigenetic marks on a single-cell resolution can determine variations that occur in cell identity, fate, and function.

Single-Cell Epigenomic Methods

Single-cell bisulfite-sequencing, scBS-seq, allows for methylation profiling of a single cell, which can be used to analyze expression of important genes, sister chromatin exchange, and methylation states of particular genes of interest. Multi-omics data may be collected by combining scBS-seq with scRNA-seq by separating RNA and DNA from the same cell for separate downstream applications. Together this data can provide transcriptome information from the same cell, strengthening the data between DNA methylation and transcriptional output.

Single-cell epigenome methods can be used to profile chromatin states of a single cell. Assays such as scNOMe-seq, ATAC-seq and ChIP-seq have been adapted to identify chromatin states in single cells. However, technical improvements are necessary for each of these methods. scNOME-seq has a high false-discovery rate due to nonspecific signals throughout the genome. scATAC-seq allows for the processing of large number of samples, however, the output data is sparse and limits the analysis of cellular variations at individual regulatory elements. Additionally, ChIP-seq presents issues with specificity and sensitivity due to the use of antibodies during immunoprecipitation.

Learn about the single molecule real-time bisulfite sequencing (SMRT-BS) method for methylation analysis created in an attempt to overcome the short read length and multiplexing limitations of targeted bisulfite sequencing.

All these methods have challenges and limitations, such as low mappability rates, limited capture rates, and high levels of PCR duplicates. Though, advances in these epigenome-based methods have helped overcome some of these issues. The main drawback of the multi-omics approach is that both DNA and RNA are necessary, which is limited in cells and how they are treated. Therefore, multi-omics methods require analyses of hundreds of cells rather than a single-cell.

Future Insights into Cellular Fate

Nonetheless, multi-omics approaches and single-cell sequencing methods provide new insights into genomic variations that may be due to different diseases. Multi-omics approach allows for multiple data to be used for discovering new connection between genomic and cell function.  It can be used to demonstrate the links between epigenetics and to what extent underlying changes in DNA sequencing drives epigenetic changes, in order to better understand cell fate, identity, function and the progression of diseases. As these methods continue to improve they will provide new potential to better understand mechanisms that control cellular fate.

SEE ALSO:   A Researcher’s Guide to Successful DNA Bisulfite Conversion

Table 1. Overview of Single Cell Methods




DNA Accessibility scNOME-seq

Used to map nucleosome positioning and determine chromatin accessibility. Since there is no selectivity for open chromatin, high levels of sequencing are necessary to guarantee coverage of the element of interest.


High throughput method for determining chromatin accessibility, by using Tn5 transposase to insert sequencing adaptors into accessible regions of the genome. Method is limited by the sparseness of data, due to reduced depth, which limits the analysis of cellular variation at individual regulatory elements.


A low throughput method that uses deoxyribonuclease I to identify open chromatin. This method is able to detect an average ̴40,000 DNase I hypersensitive sites per cell however, false discovery rate is high due to non-specific signals throughout the genome.

Chromosomal Organization scHIC

Used to measure the proximity of DNA sequences in 3-D space on the basis of ligation events in fixed nuclei. The false negative rates increases as the domain of interactions diminishes or for proteins with very transient interactions. Resolution is insufficient to interrogate contacts between specific promoters and their enhancers.

Transcription scRNA-seq

High throughput method provides the gene expression profile of individual cells in order to characterize heterogeneous expression of a cell within a seemingly homogeneous cell population. The advantage to this approach is the scalability. This method can be used in tens of hundreds of thousands of cells.

DNA Modification scBS-seq

Used to identify 5mC sites however, current protocols are only able to achieve coverage up to about 40%. Therefore, the loci that are observed will originate from only one chromosomal copy.


Restriction endonuclease, AbaS1, is used to generate recognition sites for 5hmC positions. Conversely, there is an unknown false negative rate which might contribute to a range in the number of 5hmC positions recorded in single cells.


Technique used to detect 5fC by labeling the sites with specific reactivity of maloninitrile and analyzing its C-to-T conversion during amplification and sequencing.

Histone Modification scCHIP-seq

Used to map posttranslational modifications of histones that correlate with chromatin activity states. The issue with scChIP-seq is that there may be problems with the specificity and sensitivity of the antibody used in the assay. The data produced may also be too sparse to provide de novo peak calling.


Source: Kelsey et al., Single-cell epigenomics: Recording the past and predicting the future.  Science. 2017. 358, p. 69-75.

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About Estephany Ferrufino 6 Articles
Estephany Ferrufino received her M.S. in Biology from Hofstra University. Her thesis research was on Octopine Dehydrogenase response to environmental and physiological hypoxia and its possible regulation by Hypoxia-Inducible Factor. When she’s not in the lab you can find her either watching or playing soccer, or hiking with her beautiful Siberian husky.
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