Wikipedia

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 edit

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 edit

 
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,[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 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.[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 edit

  1. ^ a b Buenrostro JD, Giresi PG, Zaba LC, Chang HY, Greenleaf WJ (December 2013). "Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position". Nature Methods. 10 (12): 1213–8. doi:10.1038/nmeth.2688. PMC 3959825. PMID 24097267.
  2. ^ 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.
  3. ^ a b Schep AN, Buenrostro JD, Denny SK, Schwartz K, Sherlock G, Greenleaf WJ (November 2015). "Structured nucleosome fingerprints enable high-resolution mapping of chromatin architecture within regulatory regions". Genome Research. 25 (11): 1757–70. doi:10.1101/gr.192294.115. PMC 4617971. PMID 26314830.
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