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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 (sequencing of micrococcal nuclease sensitive sites), FAIRE-Seq and DNase-Seq.[1] ATAC-seq is a faster and more sensitive analysis of the epigenome than DNase-seq or MNase-seq.[2][3][4]


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] The tagged DNA fragments are then purified, PCR-amplified, and sequenced using next-generation sequencing.[7] 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;[8] no antibodies like ChIP-seq;[9] and no sensitive enzymatic digestion like MNase-seq or DNase-seq.[10] ATAC-seq preparation can be completed in under three hours.[11]


Applications of ATAC-Seq

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,[12] adapted to map DNA methylation sites,[13] or combined with sequencing techniques.[14]

The utility of high-resolution enhancer mapping ranges from studying the evolutionary divergence of enhancer usage (e.g. between chimps and humans) during development[15] and uncovering a lineage-specific enhancer map used during blood cell differentiation.[16]

ATAC-Seq has also been applied to defining the genome-wide chromatin accessibility landscape in human cancers,[17] and revealing an overall decrease in chromatin accessibility in macular degeneration.[18] Computational footprinting methods can be performed on ATAC-seq to find cell specific binding sites and transcription factors with cell specific activity.[19]

Single-cell ATAC-seq[edit]

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.[11] With this approach, single cells are captured by either a microfluidic device or a liquid deposition system before tagmentation.[11][20] An alternative technique that does not require single cell isolation is combinatorial cellular indexing. 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.[21] But combinatorial cellular indexing requires additional, custom-engineered equipment or a large quantity of custom, modified Tn5.[22]

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 a pseudo bulk ATAC-seq data. Further steps include data reduction with PCA and clustering of cells[20]. scATAC-seq matrices can be extremelly large (hundrends of thounds of regions) and is extremelly sparse, i.e. less than 3% of entries are non-zero[23]. Therefore, inputation of count matrix is another crucial step. As with bulk ATAC-seq, scATAC-seq allows finding regulators transcription factors controlling gene expression of cells. This can be achieved by looking at the number of reads around TF motifs[24] or footprinting analysis[23].


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