ATAC-seq
ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) is a technique used in molecular biology to assess genome-wide chromatin accessibility.[1] In 2013, the technique was first described as an alternative advanced method for MNase-seq, FAIRE-Seq and DNase-Seq.[1] ATAC-seq is a faster analysis of the epigenome than DNase-seq or MNase-seq.[2][3][4]
Description
ATAC-seq identifies accessible DNA regions by probing open chromatin with hyperactive mutant Tn5 Transposase that inserts sequencing adapters into open regions of the genome.[2][5] While naturally occurring transposases have a low level of activity, ATAC-seq employs the mutated hyperactive transposase.[6] In a process called "tagmentation", Tn5 transposase cleaves and tags double-stranded DNA with sequencing adaptors.[7][8] The tagged DNA fragments are then purified, PCR-amplified, and sequenced using next-generation sequencing.[8] Sequencing reads can then be used to infer regions of increased accessibility as well as to map regions of transcription factor binding sites and nucleosome positions.[2] The number of reads for a region correlate with how open that chromatin is, at single nucleotide resolution.[2] ATAC-seq requires no sonication or phenol-chloroform extraction like FAIRE-seq;[9] no antibodies like ChIP-seq;[10] and no sensitive enzymatic digestion like MNase-seq or DNase-seq.[11] ATAC-seq preparation can be completed in under three hours.[12]
Applications
![](http://upload.wikimedia.org/wikipedia/commons/thumb/f/fc/ATAC-Seq_application_v2.pdf/page1-220px-ATAC-Seq_application_v2.pdf.jpg)
ATAC-Seq analysis is used to investigate a number of chromatin-accessibility signatures. The most common use is nucleosome mapping experiments,[3] but it can be applied to mapping transcription factor binding sites,[13] adapted to map DNA methylation sites,[14] or combined with sequencing techniques.[15]
The utility of high-resolution enhancer mapping ranges from studying the evolutionary divergence of enhancer usage (e.g. between chimps and humans) during development[16] and uncovering a lineage-specific enhancer map used during blood cell differentiation.[17]
ATAC-Seq has also been applied to defining the genome-wide chromatin accessibility landscape in human cancers,[18] and revealing an overall decrease in chromatin accessibility in macular degeneration.[19] Computational footprinting methods can be performed on ATAC-seq to find cell specific binding sites and transcription factors with cell specific activity.[13]
Single-cell ATAC-seq
Modifications to the ATAC-seq protocol have been made to accommodate single-cell analysis. Microfluidics can be used to separate single nuclei and perform ATAC-seq reactions individually.[12] With this approach, single cells are captured by either a microfluidic device or a liquid deposition system before tagmentation.[12][20] An alternative technique that does not require single cell isolation is combinatorial cellular indexing.[21] This technique uses barcoding to measure chromatin accessibility in thousands of individual cells; it can generate epigenomic profiles from 10,000-100,000 cells per experiment.[22] But combinatorial cellular indexing requires additional, custom-engineered equipment or a large quantity of custom, modified Tn5.[23] Recently, a pooled barcode method called sci-CAR was developed, allowing joint profiling of chromatin accessibility and gene expression of single cells.[24]
Computational analysis of scATAC-seq is based on construction of a count matrix with number of reads per open chromatin regions. Open chromatin regions can be defined, for example, by standard peak calling of pseudo bulk ATAC-seq data. Further steps include data reduction with PCA and clustering of cells.[20] scATAC-seq matrices can be extremely large (hundreds of thousands of regions) and is extremely sparse, i.e. less than 3% of entries are non-zero.[25] Therefore, imputation of count matrix is another crucial step performed by using various methods such as non-negative matrix factorization. As with bulk ATAC-seq, scATAC-seq allows finding regulators like transcription factors controlling gene expression of cells. This can be achieved by looking at the number of reads around TF motifs[26] or footprinting analysis.[25]
References
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- ^ a b c d Buenrostro JD, Wu B, Chang HY, Greenleaf WJ (January 2015). "ATAC-seq: A Method for Assaying Chromatin Accessibility Genome-Wide". Current Protocols in Molecular Biology. 109: 21.29.1–21.29.9. doi:10.1002/0471142727.mb2129s109. PMC 4374986. PMID 25559105.
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- ^ Bajic M, Maher KA, Deal RB (2018). "Identification of Open Chromatin Regions in Plant Genomes Using ATAC-Seq". Plant Chromatin Dynamics. Methods in Molecular Biology. Vol. 1675. pp. 183–201. doi:10.1007/978-1-4939-7318-7_12. ISBN 978-1-4939-7317-0. ISSN 1064-3745. PMC 5693289. PMID 29052193.
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- ^ Adey, Andrew (December 2010). "Rapid, low-input, low-bias construction of shotgun fragment libraries by high-density in vitro transposition". Genome Biology. 11 (12): R119. doi:10.1186/gb-2010-11-12-r119. PMC 3046479. PMID 21143862.
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- ^ Wang J, Zibetti C, Shang P, Sripathi SR, Zhang P, Cano M, et al. (April 2018). "ATAC-Seq analysis reveals a widespread decrease of chromatin accessibility in age-related macular degeneration". Nature Communications. 9 (1): 1364. Bibcode:2018NatCo...9.1364W. doi:10.1038/s41467-018-03856-y. PMC 5893535. PMID 29636475.
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- ^ Lareau CA, Duarte FM, Chew JG, Kartha VK, Burkett ZD, Kohlway AS, Pokholok D, Aryee MJ, et al. (2019). "Droplet-based combinatorial indexing for massive scale single-cell epigenomics". bioRxiv. doi:10.1101/612713.
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- ^ Cao, Junyue; Cusanovich, Darren A.; Ramani, Vijay; Aghamirzaie, Delasa; Pliner, Hannah A.; Hill, Andrew J.; Daza, Riza M.; McFaline-Figueroa, Jose L.; Packer, Jonathan S.; Christiansen, Lena; Steemers, Frank J. (2018-09-28). "Joint profiling of chromatin accessibility and gene expression in thousands of single cells". Science. 361 (6409): 1380–1385. Bibcode:2018Sci...361.1380C. doi:10.1126/science.aau0730. ISSN 0036-8075. PMC 6571013. PMID 30166440.
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External links
- ATAC-seq probes open-chromatin state (figure)
- ATAC-seq: Fast and sensitive epigenomic profiling
- HINT-ATAC: Identification of Transcription Factor Binding Sites using ATAC-seq