Skip to main content

TAB-seq and ACE-seq Data Processing for Genome-Wide DNA hydroxymethylation Profiling

  • Protocol
  • First Online:
TET Proteins and DNA Demethylation

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2272))

Abstract

5-Methylcytosine (5mC) is one of the most abundant and well-studied chemical DNA modifications of vertebrate genomes. 5mC plays an essential role in genome regulation including: silencing of retroelements, X chromosome inactivation, and heterochromatin stability. Furthermore, 5mC shapes the activity of cis-regulatory elements crucial for cell fate determination. TET enzymes can oxidize 5mC to form 5-hydroxymethylcytosine (5hmC), thereby adding an additional layer of complexity to the DNA methylation landscape dynamics. The advent of techniques enabling genome-wide 5hmC profiling provided critical insights into its genomic distribution, scope, and function. These methods include immunoprecipitation, chemical labeling and capture-based approaches, as well as single-nucleotide 5hmC profiling techniques such as TET-assisted bisulfite sequencing (TAB-seq) and APOBEC-coupled epigenetic sequencing (ACE-seq). Here we provide a detailed protocol for computational analysis required for the genomic alignment of TAB-seq and ACE-seq data, 5hmC calling, and statistical analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 149.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Schubeler D (2015) Function and information content of DNA methylation. Nature 517:321–326

    Article  CAS  Google Scholar 

  2. Clark SJ, Harrison J, Paul CL et al (1994) High sensitivity mapping of methylated cytosines. Nucleic Acids Res 22:2990–2997

    Article  CAS  Google Scholar 

  3. Lister R, Pelizzola M, Dowen RH et al (2009) Human DNA methylomes at base resolution show widespread epigenomic differences. Nature 462:315–322

    Article  CAS  Google Scholar 

  4. Stadler MB, Murr R, Burger L et al (2011) DNA-binding factors shape the mouse methylome at distal regulatory regions. Nature 480:490–495

    Article  CAS  Google Scholar 

  5. Lister R, Mukamel EA, Nery JR et al (2013) Global epigenomic reconfiguration during mammalian brain development. Science 341:1237905

    Article  Google Scholar 

  6. Bogdanovic O, Smits AH, de la Calle Mustienes E et al (2016) Active DNA demethylation at enhancers during the vertebrate phylotypic period. Nat Genet 48:417–426

    Article  CAS  Google Scholar 

  7. Skvortsova K, Tarbashevich K, Stehling M et al (2019) Retention of paternal DNA methylome in the developing zebrafish germline. Nat Commun 10:3054

    Article  Google Scholar 

  8. Tahiliani M, Koh KP, Shen Y et al (2009) Conversion of 5-methylcytosine to 5-hydroxymethylcytosine in mammalian DNA by MLL partner TET1. Science 324:930–935

    Article  CAS  Google Scholar 

  9. Ito S, Shen L, Dai Q et al (2011) Tet proteins can convert 5-methylcytosine to 5-formylcytosine and 5-carboxylcytosine. Science 333:1300–1303

    Article  CAS  Google Scholar 

  10. Mellen M, Ayata P, Heintz N (2017) 5-hydroxymethylcytosine accumulation in postmitotic neurons results in functional demethylation of expressed genes. Proc Natl Acad Sci U S A 114:E7812–E7821

    Article  CAS  Google Scholar 

  11. Xu Y, Wu F, Tan L et al (2011) Genome-wide regulation of 5hmC, 5mC, and gene expression by Tet1 hydroxylase in mouse embryonic stem cells. Mol Cell 42:451–464

    Article  CAS  Google Scholar 

  12. Wu H, D’Alessio AC, Ito S et al (2011) Genome-wide analysis of 5-hydroxymethylcytosine distribution reveals its dual function in transcriptional regulation in mouse embryonic stem cells. Genes Dev 25:679–684

    Article  CAS  Google Scholar 

  13. Yu M, Hon GC, Szulwach KE et al (2012) Base-resolution analysis of 5-hydroxymethylcytosine in the mammalian genome. Cell 149:1368–1380

    Article  CAS  Google Scholar 

  14. Schutsky EK, DeNizio JE, Hu P et al (2018) Nondestructive, base-resolution sequencing of 5-hydroxymethylcytosine using a DNA deaminase. Nat Biotechnol. https://doi.org/10.1038/nbt.4204

  15. Tanaka K, Okamoto A (2007) Degradation of DNA by bisulfite treatment. Bioorg Med Chem Lett 17:1912–1915

    Article  CAS  Google Scholar 

  16. Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120

    Article  CAS  Google Scholar 

  17. Li H, Handsaker B, Wysoker A et al (2009) The sequence alignment/Map format and SAMtools. Bioinformatics 25:2078–2079

    Article  Google Scholar 

  18. Chen H, Smith AD, Chen T (2016) WALT: fast and accurate read mapping for bisulfite sequencing. Bioinformatics 32:3507–3509

    CAS  PubMed  PubMed Central  Google Scholar 

  19. Robinson JT, Thorvaldsdottir H, Winckler W et al (2011) Integrative genomics viewer. Nat Biotechnol 29:24–26

    Article  CAS  Google Scholar 

  20. Andrews S (2010) FastQC: A quality control tool for high throughput sequence data [Online]. Available online at: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/

  21. Kriaucionis S, Heintz N (2009) The nuclear DNA base 5-hydroxymethylcytosine is present in Purkinje neurons and the brain. Science 324:929–930

    Article  CAS  Google Scholar 

  22. Li X, Liu Y, Salz T et al (2016) Whole-genome analysis of the methylome and hydroxymethylome in normal and malignant lung and liver. Genome Res 26:1730–1741

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Ksenia Skvortsova or Ozren Bogdanovic .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Skvortsova, K., Bogdanovic, O. (2021). TAB-seq and ACE-seq Data Processing for Genome-Wide DNA hydroxymethylation Profiling. In: Bogdanovic, O., Vermeulen, M. (eds) TET Proteins and DNA Demethylation. Methods in Molecular Biology, vol 2272. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1294-1_9

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-1294-1_9

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1293-4

  • Online ISBN: 978-1-0716-1294-1

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics