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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, 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

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

^ ^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.
^ ^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.
^ ^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. Bibcode:2015GenRe..25.1757S. doi:10.1101/gr.192294.115. PMC 4617971. PMID 26314830.
^ Song L, Crawford GE (February 2010). "DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells". Cold Spring Harbor Protocols. 2010 (2): pdb.prot5384. doi:10.1101/pdb.prot5384. PMC 3627383. PMID 20150147.
^ 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.
^ Reznikoff WS (2008). "Transposon Tn5". Annual Review of Genetics. 42 (1): 269–86. doi:10.1146/annurev.genet.42.110807.091656. PMID 18680433.
^ 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.
^ ^a ^b Picelli S, Björklund AK, Reinius B, Sagasser S, Winberg G, Sandberg R (December 2014). "Tn5 transposase and tagmentation procedures for massively scaled sequencing projects". Genome Research. 24 (12): 2033–40. doi:10.1101/gr.177881.114. PMC 4248319. PMID 25079858.
^ Simon JM, Giresi PG, Davis IJ, Lieb JD (January 2012). "Using formaldehyde-assisted isolation of regulatory elements (FAIRE) to isolate active regulatory DNA". Nature Protocols. 7 (2): 256–67. doi:10.1038/nprot.2011.444. PMC 3784247. PMID 22262007.
^ Savic D, Partridge EC, Newberry KM, Smith SB, Meadows SK, Roberts BS, et al. (October 2015). "CETCh-seq: CRISPR epitope tagging ChIP-seq of DNA-binding proteins". Genome Research. 25 (10): 1581–9. doi:10.1101/gr.193540.115. PMC 4579343. PMID 26355004.
^ Hoeijmakers WA, Bártfai R (2018). "Characterization of the Nucleosome Landscape by Micrococcal Nuclease-Sequencing (MNase-seq)". Chromatin Immunoprecipitation. Methods in Molecular Biology. Vol. 1689. pp. 83–101. doi:10.1007/978-1-4939-7380-4_8. ISBN 978-1-4939-7379-8. ISSN 1064-3745. PMID 29027167.
^ ^a ^b ^c Buenrostro JD, Wu B, Litzenburger UM, Ruff D, Gonzales ML, Snyder MP, et al. (July 2015). "Single-cell chromatin accessibility reveals principles of regulatory variation". Nature. 523 (7561): 486–90. Bibcode:2015Natur.523..486B. doi:10.1038/nature14590. PMC 4685948. PMID 26083756.
^ ^a ^b Li, Zhijian; Schulz, Marcel H.; Look, Thomas; Begemann, Matthias; Zenke, Martin; Costa, Ivan G. (26 February 2019). "Identification of transcription factor binding sites using ATAC-seq". Genome Biology. 20 (1): 45. doi:10.1186/s13059-019-1642-2. PMC 6391789. PMID 30808370.
^ Spektor R, Tippens ND, Mimoso CA, Soloway PD (June 2019). "methyl-ATAC-seq measures DNA methylation at accessible chromatin". Genome Research. 29 (6): 969–977. doi:10.1101/gr.245399.118. PMC 6581052. PMID 31160376.
^ Hendrickson DG, Soifer I, Wranik BJ, Botstein D, Scott McIsaac R (2018), "Simultaneous Profiling of DNA Accessibility and Gene Expression Dynamics with ATAC-Seq and RNA-Seq", Computational Cell Biology, Methods in Molecular Biology, vol. 1819, Springer New York, pp. 317–333, doi:10.1007/978-1-4939-8618-7_15, ISBN 9781493986170, PMID 30421411
^ Prescott SL, Srinivasan R, Marchetto MC, Grishina I, Narvaiza I, Selleri L, et al. (September 2015). "Enhancer divergence and cis-regulatory evolution in the human and chimp neural crest". Cell. 163 (1): 68–83. doi:10.1016/j.cell.2015.08.036. PMC 4848043. PMID 26365491.
^ Lara-Astiaso D, Weiner A, Lorenzo-Vivas E, Zaretsky I, Jaitin DA, David E, et al. (August 2014). "Immunogenetics. Chromatin state dynamics during blood formation". Science. 345 (6199): 943–9. doi:10.1126/science.1256271. PMC 4412442. PMID 25103404.
^ Corces MR, Granja JM, Shams S, Louie BH, Seoane JA, Zhou W, et al. (October 2018). "The chromatin accessibility landscape of primary human cancers". Science. 362 (6413): eaav1898. Bibcode:2018Sci...362.1898C. doi:10.1126/science.aav1898. PMC 6408149. PMID 30361341.
^ 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.
^ ^a ^b Mezger A, Klemm S, Mann I, Brower K, Mir A, Bostick M, et al. (September 2018). "High-throughput chromatin accessibility profiling at single-cell resolution". Nature Communications. 9 (1): 3647. Bibcode:2018NatCo...9.3647M. doi:10.1038/s41467-018-05887-x. PMC 6128862. PMID 30194434.
^ Cusanovich, Darren (May 2015). "Multiplex single cell profiling of chromatin accessibility by combinatorial cellular indexing". Science. 348 (6237): 910–914. Bibcode:2015Sci...348..910C. doi:10.1126/science.aab1601. PMC 4836442. PMID 25953818.
^ 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.
^ Chen X, Miragaia RJ, Natarajan KN, Teichmann SA (December 2018). "A rapid and robust method for single cell chromatin accessibility profiling". Nature Communications. 9 (1): 5345. Bibcode:2018NatCo...9.5345C. doi:10.1038/s41467-018-07771-0. PMC 6297232. PMID 30559361.
^ 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.
^ ^a ^b Li Z, Kuppe C, Cheng M, Menzel S, Zenke M, Kramann R, et al. (2021). "Chromatin-accessibility estimation from single-cell ATAC-seq data with scOpen". Nature Communications. 12 (1): 865931. Bibcode:2021NatCo..12.6386L. doi:10.1038/s41467-021-26530-2. PMC 8568974. PMID 34737275.
^ Schep AN, Wu B, Buenrostro JD, Greenleaf WJ (October 2017). "chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data". Nature Methods. 14 (10): 975–978. doi:10.1038/nmeth.4401. PMC 5623146. PMID 28825706.

External links

[BuenrostroGiresi2013-1] 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.

[BuenrostroWu2015-2] 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.

[SchepBuenrostro2015-3] 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. Bibcode:2015GenRe..25.1757S. doi:10.1101/gr.192294.115. PMC 4617971. PMID 26314830.

[SongCrawford2010-4] Song L, Crawford GE (February 2010). "DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells". Cold Spring Harbor Protocols. 2010 (2): pdb.prot5384. doi:10.1101/pdb.prot5384. PMC 3627383. PMID 20150147.

[BajicMaher2018-5] 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.

[Reznikoff2008-6] Reznikoff WS (2008). "Transposon Tn5". Annual Review of Genetics. 42 (1): 269–86. doi:10.1146/annurev.genet.42.110807.091656. PMID 18680433.

[7] 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.

[PicelliBjörklund2014-8] Picelli S, Björklund AK, Reinius B, Sagasser S, Winberg G, Sandberg R (December 2014). "Tn5 transposase and tagmentation procedures for massively scaled sequencing projects". Genome Research. 24 (12): 2033–40. doi:10.1101/gr.177881.114. PMC 4248319. PMID 25079858.

[SimonGiresi2012-9] Simon JM, Giresi PG, Davis IJ, Lieb JD (January 2012). "Using formaldehyde-assisted isolation of regulatory elements (FAIRE) to isolate active regulatory DNA". Nature Protocols. 7 (2): 256–67. doi:10.1038/nprot.2011.444. PMC 3784247. PMID 22262007.

[SavicPartridge2015-10] Savic D, Partridge EC, Newberry KM, Smith SB, Meadows SK, Roberts BS, et al. (October 2015). "CETCh-seq: CRISPR epitope tagging ChIP-seq of DNA-binding proteins". Genome Research. 25 (10): 1581–9. doi:10.1101/gr.193540.115. PMC 4579343. PMID 26355004.

[HoeijmakersBártfai2018-11] Hoeijmakers WA, Bártfai R (2018). "Characterization of the Nucleosome Landscape by Micrococcal Nuclease-Sequencing (MNase-seq)". Chromatin Immunoprecipitation. Methods in Molecular Biology. Vol. 1689. pp. 83–101. doi:10.1007/978-1-4939-7380-4_8. ISBN 978-1-4939-7379-8. ISSN 1064-3745. PMID 29027167.

[BuenrostroWuLitzenburger-12] Buenrostro JD, Wu B, Litzenburger UM, Ruff D, Gonzales ML, Snyder MP, et al. (July 2015). "Single-cell chromatin accessibility reveals principles of regulatory variation". Nature. 523 (7561): 486–90. Bibcode:2015Natur.523..486B. doi:10.1038/nature14590. PMC 4685948. PMID 26083756.

[Schulz-13] Li, Zhijian; Schulz, Marcel H.; Look, Thomas; Begemann, Matthias; Zenke, Martin; Costa, Ivan G. (26 February 2019). "Identification of transcription factor binding sites using ATAC-seq". Genome Biology. 20 (1): 45. doi:10.1186/s13059-019-1642-2. PMC 6391789. PMID 30808370.

[14] Spektor R, Tippens ND, Mimoso CA, Soloway PD (June 2019). "methyl-ATAC-seq measures DNA methylation at accessible chromatin". Genome Research. 29 (6): 969–977. doi:10.1101/gr.245399.118. PMC 6581052. PMID 31160376.

[15] Hendrickson DG, Soifer I, Wranik BJ, Botstein D, Scott McIsaac R (2018), "Simultaneous Profiling of DNA Accessibility and Gene Expression Dynamics with ATAC-Seq and RNA-Seq", Computational Cell Biology, Methods in Molecular Biology, vol. 1819, Springer New York, pp. 317–333, doi:10.1007/978-1-4939-8618-7_15, ISBN 9781493986170, PMID 30421411

[PrescottSrinivasan2015-16] Prescott SL, Srinivasan R, Marchetto MC, Grishina I, Narvaiza I, Selleri L, et al. (September 2015). "Enhancer divergence and cis-regulatory evolution in the human and chimp neural crest". Cell. 163 (1): 68–83. doi:10.1016/j.cell.2015.08.036. PMC 4848043. PMID 26365491.

[Lara-AstiasoWeiner2014-17] Lara-Astiaso D, Weiner A, Lorenzo-Vivas E, Zaretsky I, Jaitin DA, David E, et al. (August 2014). "Immunogenetics. Chromatin state dynamics during blood formation". Science. 345 (6199): 943–9. doi:10.1126/science.1256271. PMC 4412442. PMID 25103404.

[CorcesGranja2018-18] Corces MR, Granja JM, Shams S, Louie BH, Seoane JA, Zhou W, et al. (October 2018). "The chromatin accessibility landscape of primary human cancers". Science. 362 (6413): eaav1898. Bibcode:2018Sci...362.1898C. doi:10.1126/science.aav1898. PMC 6408149. PMID 30361341.

[WangZibetti2018-19] 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.

[MezgerKlemm2018-20] Mezger A, Klemm S, Mann I, Brower K, Mir A, Bostick M, et al. (September 2018). "High-throughput chromatin accessibility profiling at single-cell resolution". Nature Communications. 9 (1): 3647. Bibcode:2018NatCo...9.3647M. doi:10.1038/s41467-018-05887-x. PMC 6128862. PMID 30194434.

[21] Cusanovich, Darren (May 2015). "Multiplex single cell profiling of chromatin accessibility by combinatorial cellular indexing". Science. 348 (6237): 910–914. Bibcode:2015Sci...348..910C. doi:10.1126/science.aab1601. PMC 4836442. PMID 25953818.

[LareauDuarte2019-22] 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.

[ChenMiragaia2018-23] Chen X, Miragaia RJ, Natarajan KN, Teichmann SA (December 2018). "A rapid and robust method for single cell chromatin accessibility profiling". Nature Communications. 9 (1): 5345. Bibcode:2018NatCo...9.5345C. doi:10.1038/s41467-018-07771-0. PMC 6297232. PMID 30559361.

[24] 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.

[:0-25] Li Z, Kuppe C, Cheng M, Menzel S, Zenke M, Kramann R, et al. (2021). "Chromatin-accessibility estimation from single-cell ATAC-seq data with scOpen". Nature Communications. 12 (1): 865931. Bibcode:2021NatCo..12.6386L. doi:10.1038/s41467-021-26530-2. PMC 8568974. PMID 34737275.

[26] Schep AN, Wu B, Buenrostro JD, Greenleaf WJ (October 2017). "chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data". Nature Methods. 14 (10): 975–978. doi:10.1038/nmeth.4401. PMC 5623146. PMID 28825706.

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@@ Line 1: / Line 1: @@
+{{short description|Molecular biology technique}}
-'''ATAC-seq''' ('''A'''ssay for '''T'''ransposase-'''A'''ccessible '''C'''hromatin using '''seq'''uencing) is a technique used in [[molecular biology]] to assess genome-wide [[chromatin|chromatin accessibility]].<ref name="BuenrostroGiresi2013">{{cite journal | vauthors = Buenrostro JD, Giresi PG, Zaba LC, Chang HY, Greenleaf WJ | title = Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position | journal = Nature Methods | volume = 10 | issue = 12 | pages = 1213–8 | date = December 2013 | pmid = 24097267 | pmc = 3959825 | doi = 10.1038/nmeth.2688 }}</ref> In 2013, the technique was first described as an alternative advanced method for [[MNase-seq]], [[FAIRE-Seq]] and [[DNase-Seq]].<ref name="BuenrostroGiresi2013" /> ATAC-seq is a faster analysis of the epigenome than DNase-seq or MNase-seq.<ref name="BuenrostroWu2015">{{cite journal | vauthors = Buenrostro JD, Wu B, Chang HY, Greenleaf WJ | title = ATAC-seq: A Method for Assaying Chromatin Accessibility Genome-Wide | journal = Current Protocols in Molecular Biology | volume = 109 | pages = 21.29.1–21.29.9 | date = January 2015 | pmid = 25559105 | pmc = 4374986 | doi = 10.1002/0471142727.mb2129s109 }}</ref><ref name="SchepBuenrostro2015">{{cite journal | vauthors = Schep AN, Buenrostro JD, Denny SK, Schwartz K, Sherlock G, Greenleaf WJ | title = Structured nucleosome fingerprints enable high-resolution mapping of chromatin architecture within regulatory regions | journal = Genome Research | volume = 25 | issue = 11 | pages = 1757–70 | date = November 2015 | pmid = 26314830 | pmc = 4617971 | doi = 10.1101/gr.192294.115 }}</ref><ref name="SongCrawford2010">{{cite journal | vauthors = Song L, Crawford GE | title = DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells | journal = Cold Spring Harbor Protocols | volume = 2010 | issue = 2 | pages = pdb.prot5384 | date = February 2010 | pmid = 20150147 | pmc = 3627383 | doi = 10.1101/pdb.prot5384 }}</ref>
+'''ATAC-seq''' ('''A'''ssay for '''T'''ransposase-'''A'''ccessible '''C'''hromatin using '''seq'''uencing) is a technique used in [[molecular biology]] to assess genome-wide [[chromatin|chromatin accessibility]].<ref name="BuenrostroGiresi2013">{{cite journal | vauthors = Buenrostro JD, Giresi PG, Zaba LC, Chang HY, Greenleaf WJ | title = Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position | journal = Nature Methods | volume = 10 | issue = 12 | pages = 1213–8 | date = December 2013 | pmid = 24097267 | pmc = 3959825 | doi = 10.1038/nmeth.2688 }}</ref> In 2013, the technique was first described as an alternative advanced method for [[MNase-seq]], [[FAIRE-Seq]] and [[DNase-Seq]].<ref name="BuenrostroGiresi2013" /> ATAC-seq is a faster analysis of the epigenome than DNase-seq or MNase-seq.<ref name="BuenrostroWu2015">{{cite journal | vauthors = Buenrostro JD, Wu B, Chang HY, Greenleaf WJ | title = ATAC-seq: A Method for Assaying Chromatin Accessibility Genome-Wide | journal = Current Protocols in Molecular Biology | volume = 109 | pages = 21.29.1–21.29.9 | date = January 2015 | pmid = 25559105 | pmc = 4374986 | doi = 10.1002/0471142727.mb2129s109 }}</ref><ref name="SchepBuenrostro2015">{{cite journal | vauthors = Schep AN, Buenrostro JD, Denny SK, Schwartz K, Sherlock G, Greenleaf WJ | title = Structured nucleosome fingerprints enable high-resolution mapping of chromatin architecture within regulatory regions | journal = Genome Research | volume = 25 | issue = 11 | pages = 1757–70 | date = November 2015 | pmid = 26314830 | pmc = 4617971 | doi = 10.1101/gr.192294.115 | bibcode = 2015GenRe..25.1757S }}</ref><ref name="SongCrawford2010">{{cite journal | vauthors = Song L, Crawford GE | title = DNase-seq: a high-resolution technique for mapping active gene regulatory elements across the genome from mammalian cells | journal = Cold Spring Harbor Protocols | volume = 2010 | issue = 2 | pages = pdb.prot5384 | date = February 2010 | pmid = 20150147 | pmc = 3627383 | doi = 10.1101/pdb.prot5384 }}</ref>
 ==Description==
-ATAC-seq identifies accessible [[DNA]] regions by probing open chromatin with hyperactive mutant [[Transposase#Transposase Tn5|Tn5 Transposase]] that inserts sequencing adapters into open regions of the genome.<ref name="BuenrostroWu2015" /><ref name="BajicMaher2018">{{cite book|last1=Bajic|first1=Marko|last2=Maher|first2=Kelsey A.|last3=Deal|first3=Roger B. | name-list-style = vanc |chapter=Identification of Open Chromatin Regions in Plant Genomes Using ATAC-Seq|volume=1675|year=2018|pages=183–201|issn=1064-3745|doi=10.1007/978-1-4939-7318-7_12|pmid=29052193|pmc=5693289|title=Plant Chromatin Dynamics |series=Methods in Molecular Biology|isbn=978-1-4939-7317-0}}</ref> While naturally occurring transposases have a low level of activity, ATAC-seq employs the mutated hyperactive transposase.<ref name="Reznikoff2008">{{cite journal | vauthors = Reznikoff WS | title = Transposon Tn5 | journal = Annual Review of Genetics | volume = 42 | issue = 1 | pages = 269–86 | year = 2008 | pmid = 18680433 | doi = 10.1146/annurev.genet.42.110807.091656 }}</ref> In a process called "tagmentation", Tn5 transposase cleaves and tags double-stranded DNA with sequencing adaptors.<ref>{{cite journal |last1=Adey |first1=Andrew |title=Rapid, low-input, low-bias construction of shotgun fragment libraries by high-density in vitro transposition |journal=Genome Biology |date=December 2010 |volume=11 |issue=12 |pages=R119 |doi=10.1186/gb-2010-11-12-r119 |pmid=21143862 |pmc= 3046479 }}</ref><ref name="PicelliBjörklund2014">{{cite journal | vauthors = Picelli S, Björklund AK, Reinius B, Sagasser S, Winberg G, Sandberg R | title = Tn5 transposase and tagmentation procedures for massively scaled sequencing projects | journal = Genome Research | volume = 24 | issue = 12 | pages = 2033–40 | date = December 2014 | pmid = 25079858 | pmc = 4248319 | doi = 10.1101/gr.177881.114 }}</ref> The tagged DNA fragments are then purified, [[Polymerase chain reaction|PCR]]-amplified, and sequenced using [[massive parallel sequencing|next-generation sequencing]].<ref name="PicelliBjörklund2014" /> 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.<ref name="BuenrostroWu2015" /> The number of reads for a region correlate with how open that chromatin is, at single nucleotide resolution.<ref name="BuenrostroWu2015" /> ATAC-seq requires no [[sonication]] or [[phenol-chloroform extraction]] like FAIRE-seq;<ref name="SimonGiresi2012">{{cite journal | vauthors = Simon JM, Giresi PG, Davis IJ, Lieb JD | title = Using formaldehyde-assisted isolation of regulatory elements (FAIRE) to isolate active regulatory DNA | journal = Nature Protocols | volume = 7 | issue = 2 | pages = 256–67 | date = January 2012 | pmid = 22262007 | pmc = 3784247 | doi = 10.1038/nprot.2011.444 }}</ref> no antibodies like ChIP-seq;<ref name="SavicPartridge2015">{{cite journal | vauthors = Savic D, Partridge EC, Newberry KM, Smith SB, Meadows SK, Roberts BS, Mackiewicz M, Mendenhall EM, Myers RM | display-authors = 6 | title = CETCh-seq: CRISPR epitope tagging ChIP-seq of DNA-binding proteins | journal = Genome Research | volume = 25 | issue = 10 | pages = 1581–9 | date = October 2015 | pmid = 26355004 | pmc = 4579343 | doi = 10.1101/gr.193540.115 }}</ref> and no sensitive enzymatic digestion like MNase-seq or DNase-seq.<ref name="HoeijmakersBártfai2018">{{cite book|last1=Hoeijmakers|first1=Wieteke Anna Maria|last2=Bártfai |first2=Richárd | name-list-style = vanc |title=Chromatin Immunoprecipitation|chapter=Characterization of the Nucleosome Landscape by Micrococcal Nuclease-Sequencing (MNase-seq)|volume=1689|year=2018|pages=83–101|issn=1064-3745|doi=10.1007/978-1-4939-7380-4_8|pmid=29027167|series=Methods in Molecular Biology|isbn=978-1-4939-7379-8}}</ref> ATAC-seq preparation can be completed in under three hours.<ref name="BuenrostroWuLitzenburger" />
+ATAC-seq identifies accessible [[DNA]] regions by probing open chromatin with hyperactive mutant [[Transposase#Transposase Tn5|Tn5 Transposase]] that inserts sequencing adapters into open regions of the genome.<ref name="BuenrostroWu2015" /><ref name="BajicMaher2018">{{cite book|last1=Bajic|first1=Marko|last2=Maher|first2=Kelsey A.|last3=Deal|first3=Roger B. | name-list-style = vanc |chapter=Identification of Open Chromatin Regions in Plant Genomes Using ATAC-Seq|volume=1675|year=2018|pages=183–201|issn=1064-3745|doi=10.1007/978-1-4939-7318-7_12|pmid=29052193|pmc=5693289|title=Plant Chromatin Dynamics |series=Methods in Molecular Biology|isbn=978-1-4939-7317-0}}</ref> While naturally occurring transposases have a low level of activity, ATAC-seq employs the mutated hyperactive transposase.<ref name="Reznikoff2008">{{cite journal | vauthors = Reznikoff WS | title = Transposon Tn5 | journal = Annual Review of Genetics | volume = 42 | issue = 1 | pages = 269–86 | year = 2008 | pmid = 18680433 | doi = 10.1146/annurev.genet.42.110807.091656 }}</ref> In a process called "tagmentation", Tn5 transposase cleaves and tags double-stranded DNA with sequencing adaptors.<ref>{{cite journal |last1=Adey |first1=Andrew |title=Rapid, low-input, low-bias construction of shotgun fragment libraries by high-density in vitro transposition |journal=Genome Biology |date=December 2010 |volume=11 |issue=12 |pages=R119 |doi=10.1186/gb-2010-11-12-r119 |pmid=21143862 |pmc= 3046479 |doi-access=free }}</ref><ref name="PicelliBjörklund2014">{{cite journal | vauthors = Picelli S, Björklund AK, Reinius B, Sagasser S, Winberg G, Sandberg R | title = Tn5 transposase and tagmentation procedures for massively scaled sequencing projects | journal = Genome Research | volume = 24 | issue = 12 | pages = 2033–40 | date = December 2014 | pmid = 25079858 | pmc = 4248319 | doi = 10.1101/gr.177881.114 }}</ref> The tagged DNA fragments are then purified, [[Polymerase chain reaction|PCR]]-amplified, and sequenced using [[massive parallel sequencing|next-generation sequencing]].<ref name="PicelliBjörklund2014" /> 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.<ref name="BuenrostroWu2015" /> The number of reads for a region correlate with how open that chromatin is, at single nucleotide resolution.<ref name="BuenrostroWu2015" /> ATAC-seq requires no [[sonication]] or [[phenol-chloroform extraction]] like FAIRE-seq;<ref name="SimonGiresi2012">{{cite journal | vauthors = Simon JM, Giresi PG, Davis IJ, Lieb JD | title = Using formaldehyde-assisted isolation of regulatory elements (FAIRE) to isolate active regulatory DNA | journal = Nature Protocols | volume = 7 | issue = 2 | pages = 256–67 | date = January 2012 | pmid = 22262007 | pmc = 3784247 | doi = 10.1038/nprot.2011.444 }}</ref> no antibodies like [[ChIP-seq]];<ref name="SavicPartridge2015">{{cite journal | vauthors = Savic D, Partridge EC, Newberry KM, Smith SB, Meadows SK, Roberts BS, Mackiewicz M, Mendenhall EM, Myers RM | display-authors = 6 | title = CETCh-seq: CRISPR epitope tagging ChIP-seq of DNA-binding proteins | journal = Genome Research | volume = 25 | issue = 10 | pages = 1581–9 | date = October 2015 | pmid = 26355004 | pmc = 4579343 | doi = 10.1101/gr.193540.115 }}</ref> and no sensitive enzymatic digestion like MNase-seq or DNase-seq.<ref name="HoeijmakersBártfai2018">{{cite book|last1=Hoeijmakers|first1=Wieteke Anna Maria|last2=Bártfai |first2=Richárd | name-list-style = vanc |title=Chromatin Immunoprecipitation|chapter=Characterization of the Nucleosome Landscape by Micrococcal Nuclease-Sequencing (MNase-seq)|volume=1689|year=2018|pages=83–101|issn=1064-3745|doi=10.1007/978-1-4939-7380-4_8|pmid=29027167|series=Methods in Molecular Biology|isbn=978-1-4939-7379-8}}</ref> ATAC-seq preparation can be completed in under three hours.<ref name="BuenrostroWuLitzenburger" />
 == Applications ==
 [[File:ATAC-Seq application_v2.pdf|thumb|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,<ref name="SchepBuenrostro2015" /> but it can be applied to mapping [[Transcription factor-binding site|transcription factor binding sites]],<ref name="Schulz">{{cite journal |last1=Li |first1=Zhijian |last2=Schulz |first2=Marcel H. |last3=Look |first3=Thomas |last4=Begemann |first4=Matthias |last5=Zenke |first5=Martin |last6=Costa |first6=Ivan G. |title=Identification of transcription factor binding sites using ATAC-seq |journal=Genome Biology |date=26 February 2019 |volume=20 |issue=1 |pages=45 |doi=10.1186/s13059-019-1642-2 |pmid=30808370 |pmc=6391789 |doi-access=free}}</ref> adapted to map [[DNA methylation]] sites,<ref>{{cite journal | vauthors = Spektor R, Tippens ND, Mimoso CA, Soloway PD | title = methyl-ATAC-seq measures DNA methylation at accessible chromatin | journal = Genome Research | volume = 29 | issue = 6 | pages = 969–977 | date = June 2019 | pmid = 31160376 | pmc = 6581052 | doi = 10.1101/gr.245399.118 }}</ref> or combined with sequencing techniques.<ref>{{Citation|last1=Hendrickson|first1=David G.|title=Simultaneous Profiling of DNA Accessibility and Gene Expression Dynamics with ATAC-Seq and RNA-Seq|volume=1819|date=2018|doi=10.1007/978-1-4939-8618-7_15|pmid=30421411|series=Methods in Molecular Biology|pages=317–333|publisher=Springer New York |isbn=9781493986170 |last2=Soifer |first2=Ilya |last3=Wranik |first3=Bernd J. |last4=Botstein |first4=David |last5=Scott McIsaac |first5=R.| name-list-style = vanc }}</ref>
+ATAC-Seq analysis is used to investigate a number of chromatin-accessibility signatures. The most common use is [[nucleosome]] mapping experiments,<ref name="SchepBuenrostro2015" /> but it can be applied to mapping [[Transcription factor-binding site|transcription factor binding sites]],<ref name="Schulz">{{cite journal |last1=Li |first1=Zhijian |last2=Schulz |first2=Marcel H. |last3=Look |first3=Thomas |last4=Begemann |first4=Matthias |last5=Zenke |first5=Martin |last6=Costa |first6=Ivan G. |title=Identification of transcription factor binding sites using ATAC-seq |journal=Genome Biology |date=26 February 2019 |volume=20 |issue=1 |pages=45 |doi=10.1186/s13059-019-1642-2 |pmid=30808370 |pmc=6391789 |doi-access=free}}</ref> adapted to map [[DNA methylation]] sites,<ref>{{cite journal | vauthors = Spektor R, Tippens ND, Mimoso CA, Soloway PD | title = methyl-ATAC-seq measures DNA methylation at accessible chromatin | journal = Genome Research | volume = 29 | issue = 6 | pages = 969–977 | date = June 2019 | pmid = 31160376 | pmc = 6581052 | doi = 10.1101/gr.245399.118 }}</ref> or combined with sequencing techniques.<ref>{{Citation|last1=Hendrickson|first1=David G.|volume=1819|date=2018|doi=10.1007/978-1-4939-8618-7_15|pmid=30421411|series=Methods in Molecular Biology|pages=317–333|publisher=Springer New York |isbn=9781493986170 |last2=Soifer |first2=Ilya |last3=Wranik |first3=Bernd J. |last4=Botstein |first4=David |last5=Scott McIsaac |first5=R.|title=Computational Cell Biology |chapter=Simultaneous Profiling of DNA Accessibility and Gene Expression Dynamics with ATAC-Seq and RNA-Seq | name-list-style = vanc }}</ref>
 The utility of high-resolution enhancer mapping ranges from studying the evolutionary divergence of enhancer usage (e.g. between chimps and humans) during development<ref name="PrescottSrinivasan2015">{{cite journal | vauthors = Prescott SL, Srinivasan R, Marchetto MC, Grishina I, Narvaiza I, Selleri L, Gage FH, Swigut T, Wysocka J | display-authors = 6 | title = Enhancer divergence and cis-regulatory evolution in the human and chimp neural crest | journal = Cell | volume = 163 | issue = 1 | pages = 68–83 | date = September 2015 | pmid = 26365491 | pmc = 4848043 | doi = 10.1016/j.cell.2015.08.036 }}</ref> and uncovering a lineage-specific enhancer map used during blood cell differentiation.<ref name="Lara-AstiasoWeiner2014">{{cite journal | vauthors = Lara-Astiaso D, Weiner A, Lorenzo-Vivas E, Zaretsky I, Jaitin DA, David E, Keren-Shaul H, Mildner A, Winter D, Jung S, Friedman N, Amit I | display-authors = 6 | title = Immunogenetics. Chromatin state dynamics during blood formation | journal = Science | volume = 345 | issue = 6199 | pages = 943–9 | date = August 2014 | pmid = 25103404 | pmc = 4412442 | doi = 10.1126/science.1256271 }}</ref>
@@ Line 15: / Line 16: @@
 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.<ref name="BuenrostroWuLitzenburger">{{cite journal | vauthors = Buenrostro JD, Wu B, Litzenburger UM, Ruff D, Gonzales ML, Snyder MP, Chang HY, Greenleaf WJ | display-authors = 6 | title = Single-cell chromatin accessibility reveals principles of regulatory variation | journal = Nature | volume = 523 | issue = 7561 | pages = 486–90 | date = July 2015 | pmid = 26083756 | pmc = 4685948 | doi = 10.1038/nature14590 | bibcode = 2015Natur.523..486B }}</ref> With this approach, single cells are captured by either a microfluidic device or a liquid deposition system before tagmentation.<ref name="BuenrostroWuLitzenburger" /><ref name="MezgerKlemm2018">{{cite journal | vauthors = Mezger A, Klemm S, Mann I, Brower K, Mir A, Bostick M, Farmer A, Fordyce P, Linnarsson S, Greenleaf W | display-authors = 6 | title = High-throughput chromatin accessibility profiling at single-cell resolution | journal = Nature Communications | volume = 9 | issue = 1 | pages = 3647 | date = September 2018 | pmid = 30194434 | pmc = 6128862 | doi = 10.1038/s41467-018-05887-x | bibcode = 2018NatCo...9.3647M }}</ref> An alternative technique that does not require single cell isolation is combinatorial cellular indexing.<ref>{{cite journal |last1=Cusanovich |first1=Darren |title=Multiplex single cell profiling of chromatin accessibility by combinatorial cellular indexing |journal=Science |date=May 2015 |volume=348 |issue=6237 |pages=910–914 |doi=10.1126/science.aab1601 |pmid=25953818 |pmc=4836442|bibcode=2015Sci...348..910C }}</ref> This technique uses [[DNA barcoding|barcoding]] to measure chromatin accessibility in thousands of individual cells; it can generate epigenomic profiles from 10,000-100,000 cells per experiment.<ref name="LareauDuarte2019">{{cite journal | vauthors = Lareau CA, Duarte FM, Chew JG, Kartha VK, Burkett ZD, Kohlway AS, Pokholok D, Aryee MJ, Steemers FJ, Lebofsky R, Buenrostro JD | display-authors = 8 |year=2019 |title=Droplet-based combinatorial indexing for massive scale single-cell epigenomics |journal=bioRxiv |doi=10.1101/612713 |doi-access=free }}</ref> But combinatorial cellular indexing requires additional, custom-engineered equipment or a large quantity of custom, modified Tn5.<ref name="ChenMiragaia2018">{{cite journal | vauthors = Chen X, Miragaia RJ, Natarajan KN, Teichmann SA | title = A rapid and robust method for single cell chromatin accessibility profiling | journal = Nature Communications | volume = 9 | issue = 1 | pages = 5345 | date = December 2018 | pmid = 30559361 | pmc = 6297232 | doi = 10.1038/s41467-018-07771-0 | bibcode = 2018NatCo...9.5345C }}</ref> Recently, a pooled barcode method called sci-CAR was developed, allowing joint profiling of chromatin accessibility and gene expression of single cells.<ref>{{Cite journal|last1=Cao|first1=Junyue|last2=Cusanovich|first2=Darren A.|last3=Ramani|first3=Vijay|last4=Aghamirzaie|first4=Delasa|last5=Pliner|first5=Hannah A.|last6=Hill|first6=Andrew J.|last7=Daza|first7=Riza M.|last8=McFaline-Figueroa|first8=Jose L.|last9=Packer|first9=Jonathan S.|last10=Christiansen|first10=Lena|last11=Steemers|first11=Frank J.|date=2018-09-28|title=Joint profiling of chromatin accessibility and gene expression in thousands of single cells|journal=Science|language=en|volume=361|issue=6409|pages=1380–1385|doi=10.1126/science.aau0730|issn=0036-8075|pmid=30166440|pmc=6571013 |bibcode=2018Sci...361.1380C |doi-access=free}}</ref>
-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.<ref name="MezgerKlemm2018" /> 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.<ref name=":0">{{cite journal |last1=Li |first1=Zhijian |last2=Kuppe |first2=Christoph |last3=Cheng |first3=Mingbo |last4=Menzel |first4=Sylvia |last5=Zenke |first5=Martin |last6=Kramann |first6=Rafael |last7=Costa |first7=Ivan G. |name-list-style = vanc | display-authors = 6 |date=2021|title=Chromatin-accessibility estimation from single-cell ATAC-seq data with scOpen|journal=Nature Communications|volume=12 |issue=1 |language=en|pages=865931|doi=10.1038/s41467-021-26530-2|pmid=34737275 |pmc=8568974 |bibcode=2021NatCo..12.6386L |doi-access=free }}</ref> Therefore, imputation of count matrix is another crucial step by using methods 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<ref>{{cite journal | vauthors = Schep AN, Wu B, Buenrostro JD, Greenleaf WJ | title = chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data | journal = Nature Methods | volume = 14 | issue = 10 | pages = 975–978 | date = October 2017 | pmid = 28825706 | pmc = 5623146 | doi = 10.1038/nmeth.4401 }}</ref> or footprinting analysis.<ref name=":0" />
+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.<ref name="MezgerKlemm2018" /> 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.<ref name=":0">{{cite journal |last1=Li |first1=Zhijian |last2=Kuppe |first2=Christoph |last3=Cheng |first3=Mingbo |last4=Menzel |first4=Sylvia |last5=Zenke |first5=Martin |last6=Kramann |first6=Rafael |last7=Costa |first7=Ivan G. |name-list-style = vanc | display-authors = 6 |date=2021|title=Chromatin-accessibility estimation from single-cell ATAC-seq data with scOpen|journal=Nature Communications|volume=12 |issue=1 |language=en|pages=865931|doi=10.1038/s41467-021-26530-2|pmid=34737275 |pmc=8568974 |bibcode=2021NatCo..12.6386L |doi-access=free }}</ref> 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<ref>{{cite journal | vauthors = Schep AN, Wu B, Buenrostro JD, Greenleaf WJ | title = chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data | journal = Nature Methods | volume = 14 | issue = 10 | pages = 975–978 | date = October 2017 | pmid = 28825706 | pmc = 5623146 | doi = 10.1038/nmeth.4401 }}</ref> or footprinting analysis.<ref name=":0" />
 == References ==
 {{Reflist}}
-==External source==
+==External links ==
 * [http://www.nature.com/nmeth/journal/v10/n12/fig_tab/nmeth.2688_F1.html ATAC-seq probes open-chromatin state (figure)]
 * [https://web.archive.org/web/20150901062145/http://greenleaf.stanford.edu/portfolio_details_buenrostro_2013_nature_methods.html ATAC-seq: Fast and sensitive epigenomic profiling]