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Chromatin accessibility profiling methods

Nature Reviews Methods Primers volume 1, Article number: 10 (2021) Cite this article

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Abstract

Chromatin accessibility, or the physical access to chromatinized DNA, is a widely studied characteristic of the eukaryotic genome. As active regulatory DNA elements are generally ‘accessible’, the genome-wide profiling of chromatin accessibility can be used to identify candidate regulatory genomic regions in a tissue or cell type. Multiple biochemical methods have been developed to profile chromatin accessibility, both in bulk and at the single-cell level. Depending on the method, enzymatic cleavage, transposition or DNA methyltransferases are used, followed by high-throughput sequencing, providing a view of genome-wide chromatin accessibility. In this Primer, we discuss these biochemical methods, as well as bioinformatics tools for analysing and interpreting the generated data, and insights into the key regulators underlying developmental, evolutionary and disease processes. We outline standards for data quality, reproducibility and deposition used by the genomics community. Although chromatin accessibility profiling is invaluable to study gene regulation, alone it provides only a partial view of this complex process. Orthogonal assays facilitate the interpretation of accessible regions with respect to enhancer–promoter proximity, functional transcription factor binding and regulatory function. We envision that technological improvements including single-molecule, multi-omics and spatial methods will bring further insight into the secrets of genome regulation.

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Fig. 1: Chromatin accessibility profiling in bulk and at single-cell level reveals putative regulatory regions.
Fig. 2: Experimental approaches for measuring chromatin accessibility and nucleosome positioning.
Fig. 3: Overview of common tasks in the analysis of bulk chromatin accessibility data.
Fig. 4: Overview of common tasks in the analysis of scATAC-seq data.
Fig. 5: Schematic overview of future roads and opportunities for chromatin accessibility profiling.

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Acknowledgements

This work was supported by the Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health (NIH) (K.Z.) and the National Science Foundation (NSF; IOS-1856627) (R.J.S). R.J.S. is a Pew Scholar in the Biomedical Sciences, supported by The Pew Charitable Trusts. L.M. was supported by a PhD fellowship from the FWO (no. 1S03317N), A.P.M. by an NSF Postdoctoral Fellowship in Biology (DBI-1905869), C.B. by a European Research Council (ERC) Starting Grant (European Union’s Horizon 2020 research and innovation programme, grant agreement no. 679146), E.E.M.F. by an ERC Advanced grant (DeCRypT) and S.A. by an ERC Consolidator Grant (cis_CONTROL). W.J.G. acknowledges support as a Chan-Zuckerberg Biohub Investigator, and from NIH grants UM1-HG009436, P50-HG007735, UM1-HG009442 and U19-AI057266. The authors thank J. Demeulemeester for insights into the long-read sequencing platforms.

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Authors and Affiliations

  1. Center for Brain & Disease Research, VIB-KU Leuven, Leuven, Belgium

    Liesbeth Minnoye & Stein Aerts

  2. Department of Human Genetics, KU Leuven, Leuven, Belgium

    Liesbeth Minnoye & Stein Aerts

  3. Department of Genetics, Stanford University, Stanford, CA, USA

    Georgi K. Marinov & William J. Greenleaf

  4. CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria

    Thomas Krausgruber & Christoph Bock

  5. Laboratory of Epigenome Biology, Systems Biology Center, Division of Intramural Research, National Heart, Lung and Blood Institute, NIH, Bethesda, MD, USA

    Lixia Pan & Keji Zhao

  6. Department of Genetics, University of Georgia, Athens, GA, USA

    Alexandre P. Marand & Robert J. Schmitz

  7. European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany

    Stefano Secchia & Eileen E. M. Furlong

  8. Institute of Artificial Intelligence and Decision Support, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria

    Christoph Bock

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Contributions

Introduction (S.A., L.M.); Experimentation (G.K.M., L.P., A.P.M., W.J.G., K.Z., R.J.S.); Results (L.M., S.A., G.K.M., W.J.G.); Applications (G.K.M., T.K., A.P.M., R.J.S., C.B., W.J.G.); Reproducibility and data deposition (A.P.M., R.J.S.); Limitations and optimizations (G.K.M., W.J.G.); Outlook (S.S., E.E.M.F.); Overview of the Primer (S.A., L.M.).

Corresponding author

Correspondence to Stein Aerts.

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Competing interests

C.B. is an inventor on a patent describing the ChIPmentation assay. R.J.S. is a co-founder of REquest Genomics, LLC, a company that provides epigenomics services. W.J.G is an inventor on a patent describing Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq), a consultant for 10x Genomics and Guardant Health, and a co-founder of Protillion biosciences. All other authors declare no competing interests.

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Nature Reviews Methods Primers thanks T. Liu, B. Treutlein, L. Zhu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Related links

ENCODE ATAC-seq Data Standards and Processing Pipeline: https://www.encodeproject.org/atac-seq/

FastQC: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/

Supplementary information

Glossary

Nucleosomes

The basic structural unit of DNA packaging, consisting of ~147 bp of DNA wrapped around an octamer of histones.

Cis-regulatory elements

Non-coding DNA regions involved in the regulation of expression of neighbouring genes. The regions contain binding sites for transcription factors.

Accessible chromatin

A permissive state of the chromatin in which nuclear macromolecules are able to physically access and interact with the DNA.

Transcriptional condensates

Membraneless compartments of the genome formed by liquid–liquid phase separation, in which the transcription machinery is concentrated to efficiently activate transcription.

Pioneer factors

Transcription factors that can recognize and bind their target sequence in closed chromatin and trigger opening of the chromatin, allowing binding of other transcription factors.

Tagmentation

Transposases cut DNA into fragments while simultaneously adding adaptor sequences. Used in Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq), as well as for general sequencing library construction to randomly fragment double-stranded DNA.

TF footprinting

Small stretches of nucleotides that are protected from cleavage or tagmentation and represent the location of transcription factor (TF) binding sites. TF footprints can be inferred from the analysis of high-resolution chromatin accessibility data.

Mosaic end adapters

Hyperactive versions of the two inverted 19-bp end sequences of the wild-type Tn5 transposon that, during an Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) experiment, are end-joined to accessible DNA by the transposase.

Nucleosome ladder

A characteristic ‘ladder’ pattern that originates from the cleavage of the linker DNA between nucleosomes, due to the periodic arrangement of nucleosomes.

Combinatorial indexing

A technique that uniquely labels a large number of single molecules or single cells by split-pool barcoding of nucleic acids.

Doublets

Artefactual libraries generated from two cells in single-cell omics experiments. For instance, in droplet-based methods, doublets arise if two cells are captured in a single droplet.

BAM file

An alignment file format that is the compressed binary version of a SAM file, used to represent aligned sequences.

Irreproducible discovery rate

(IDR). A measure of consistency between biological replicates of high-throughput sequencing experiments. Also used to determine highly stable peak calling thresholds based on reproducibility.

Genomic intervals

Consecutive stretches on a genomic sequence, specified as a chromosomal location range or as a cytoband designation.

Fraction of reads in called peaks

(FRiP score). The fraction of all mapped reads that fall into the called peak regions.

Signal proportion of tags

(SPOT score). The fraction of reads that fall in tag-enriched regions identified using the Hotspot algorithm.

Signature

A set of peaks that is differentially accessible between studied samples and can be used to define a studied cell type or state.

Differential peak calling

A process in which peaks with significantly differentially accessibility between samples are identified.

MA plots

Visual representations of genomic data used to compare two samples or two groups of samples. The x axis represents the base mean value of the samples and the y axis the difference between them.

Hierarchical clustering and k-means clustering

Clustering algorithms that group similar objects in a data set into groups called clusters. In k-means clustering, the data are divided into a predefined number (‘k’) of clusters, whereas in hierarchical clustering, a hierarchy of clusters is built without requiring a predefined number of clusters.

Pseudo-time trajectory

A computational reconstructed path of a dynamic biological process, such as differentiation, undergone by the cells in a single-cell omics experiment. Single cells are ordered along the trajectory based on their ‘pseudo-time’, or their inferred progression through the biological process.

Zygotic genome activation

A process by which transcription is turned on after fertilization, making the switch from an unfertilized oocyte with nearly any gene expression to a state where up to thousands of genes are transcribed.

Quantitative trait loci

(QTL). Small regions of the genome at which a genetic variant is associated with a quantitative trait of a cell or an organism, based on statistical association between genetic markers and the measurable trait.

Yoruba HapMap

A resource set up by the Yoruba HapMap project that aims to catalogue the common patterns of human genetic variation and associate SNPs with genotypes across human populations.

Hi-C

(High-throughput chromosome conformation capture). A genome-wide sequencing technique used to investigate 3D chromatin conformation.

Chromatin accessibility QTL

Quantitative trait loci (QTL) associated with chromatin accessibility. Specifically, chromatin accessibility QTL represent an SNP that is correlated significantly with accessibility changes in their encompassing region.

Morphogen gradients

Gradients of signalling molecules within developing tissues and embryos, which illicit different responses across the gradient, leading to diverse outcomes in terms of cell fate decisions, controlling pattern formation during embryogenesis.

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Minnoye, L., Marinov, G.K., Krausgruber, T. et al. Chromatin accessibility profiling methods. Nat Rev Methods Primers 1, 10 (2021). https://doi.org/10.1038/s43586-020-00008-9

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