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Assay for transposase-accessible chromatin sequencing (ATAC-seq) builds on a process called tagmentation: the simultaneous fragmentation and tagging of a genome with sequencing adaptors1. The key component of this process is a mutant hyperactive Tn5 transposase that excises any sufficiently long DNA. During tagmentation, mutant Tn5 transposases, preloaded with DNA adapters, tag genomic DNA for downstream excision and fragmentation. ATAC-seq was initially designed for next-generation sequencing (NGS) preparation but has now been successfully adapted to efficiently identify open chromatin2 and is becoming part of the standard epigenetic analysis.
Adapted from Buenrostro et al. (2015) Curr. Protoc. Mol. Biol. 109, 21.29.1-9.
Methods to assess open chromatin via NGS have been in use for a number of years now (for review, see Meyer and Liu 20143). The main advantage of ATAC-seq over these existing methods is the simplicity of the library preparation protocol: Tn5 insertion followed by two rounds of PCR. After library preparation, the DNA is sequenced with NGS technology, and the number of reads for a region correlates with how open that chromatin is at a single nucleotide resolution.
ATAC-seq requires no sonication or phenol-chloroform extraction like FAIRE-seq; no antibodies like ChIP-seq; and no sensitive enzymatic digestion like MNase-seq or DNase-seq. Unlike similar methods, which can take up to four days to complete, ATAC-seq preparation can be completed in under three hours.
Another consideration in the ATAC-seq protocol is cell number. While the total number of cells defines library complexity, too few cells lead to under-transposition, while too many lead to over-transposition4. It is therefore important to optimize cell number from the beginning: for human studies, 500–50,000 cells are recommended2, but this can vary between species and cell type 4.
ATAC-seq’s most common use is for nucleosome mapping. Schep et al. (2015) developed an algorithm to infer the rotational and translational positions of nucleosomes with single-base resolution from ATAC-seq data5. This identifies subtle changes in nucleosome position between experimental conditions, and correlation with sequence context.
ATAC-seq has also proven useful in transcription factor (TF) occupancy analysis in specific cell types. Because TF binding signals are influenced by many factors (nucleosome position, binding strength, kinetics, etc), and different assays can better detect different sites, ATAC-seq can be used alongside DNAase-seq or FAIRE-seq to provide a complete picture of TF occupancy2. For example, this method has been used to find lineage-specific factors during hematopoesis6. In a similar study, FAIRE-seq and ATAC-seq were used to identify occupied TF binding sites during normal development and oncogenesis in Drosophila7.
Another common application of ATAC-seq is identifying novel enhancers during development8. For example, it has been used to explore the evolution of neural crest cis-regulatory element by comparing human and chimp development9, and to plot enhancer development across 20 species10.
In addition to normal development, ATAC-seq can be used to explore various pathological conditions. Davie et al. (2015) used this method to identify ectopically-active regions during Ras-dependent oncogenesis7.
In coming years, ATAC-seq looks set to become common in single-cell analysis. Though ATAC-seq is not optimized for low cell numbers, modifications to the protocol have been made to accommodate this: microfluidics can be used to separate single nuclei and perform ATAC-seq reactions individually11.
A higher throughput option is combinatorial cellular indexing, which uses barcoding to measure chromatin accessibility in thousands of individual cells. With this approach, there is the possibility to look at over 17,000 cells per experiment12, although this technique is not truly a single-cell analysis.
ATAC-seq will likely be a key component of comprehensive epigenomic workflows. Integration of whole-genome histone modification, DNA methylation, gene expression, and chromatin accessibility is becoming the norm. Single-experimental workflows to examine all these components together are on the horizon. ATAC-seq is well-positioned to fulfill the chromatin accessibility portion of such workflows, due to its ease, speed, reliability, and multiplexing potential.
1. Adey, A. et al. Rapid, low-input, low-bias construction of shotgun fragment libraries by high-density in vitro transposition. Genome Biol. 11, R119 (2010).
2. Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–8 (2013).
3. Meyer, C. A. & Liu, X. S. Identifying and mitigating bias in next-generation sequencing methods for chromatin biology. Nat. Rev. Genet. 15, 709–721 (2014).
4. Buenrostro, J. D., Wu, B., Chang, H. Y. & Greenleaf, W. J. ATAC-seq: A Method for Assaying Chromatin Accessibility Genome-Wide. Curr. Protoc. Mol. Biol. 109, 21.29.1-9 (2015).
5. Schep, A. N. et al. Structured nucleosome fingerprints enable high-resolution mapping of chromatin architecture within regulatory regions. Genome Res. 25, 1757–1770 (2015).
6. Lara-Astiaso, D. et al. Immunogenetics. Chromatin state dynamics during blood formation. Science 345, 943–9 (2014).
7. Davie, K. et al. Discovery of Transcription Factors and Regulatory Regions Driving In Vivo Tumor Development by ATAC-seq and FAIRE-seq Open Chromatin Profiling. PLOS Genet. 11, e1004994 (2015).
8. Kim, T.-K. & Shiekhattar, R. Architectural and Functional Commonalities between Enhancers and Promoters. Cell 162, 948–959 (2015).
9. Prescott, S. L. et al. Enhancer Divergence and cis-Regulatory Evolution in the Human and Chimp Neural Crest. Cell 163, 68–83 (2015).
10. Villar, D. et al. Enhancer Evolution across 20 Mammalian Species. Cell 160, 554–566 (2015).
11. Buenrostro, J. D. et al. Single-cell chromatin accessibility reveals principles of regulatory variation. Nature 523, 486–490 (2015).
12. Cusanovich, D. A. et al. Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing. Science 348, 910–4 (2015).