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Genome-Wide Profiling of DNA Methyltransferases in Mammalian Cells

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CpG Islands

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1766))

Abstract

Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is currently the method of choice to determine binding sites of chromatin-associated factors in a genome-wide manner. Here, we describe a method to investigate the binding preferences of mammalian DNA methyltransferases (DNMT) based on ChIP-seq using biotin-tagging. Stringent ChIP of DNMT proteins based on the strong interaction between biotin and avidin circumvents limitations arising from low antibody specificity and ensures reproducible enrichment. DNMT-bound DNA fragments are ligated to sequencing adaptors, amplified and sequenced on a high-throughput sequencing instrument. Bioinformatic analysis gives valuable information about the binding preferences of DNMTs genome-wide and around promoter regions. This method is unconventional due to the use of genetically engineered cells; however, it allows specific and reliable determination of DNMT binding.

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References

  1. Okano M, Bell DW, Haber DA, Li E (1999) DNA methyltransferases Dnmt3a and Dnmt3b are essential for de novo methylation and mammalian development. Cell 99(3):247–257

    Article  CAS  PubMed  Google Scholar 

  2. Smith ZD, Meissner A (2013) DNA methylation: roles in mammalian development. Nat Rev Genet 14(3):204–220. https://doi.org/10.1038/nrg3354

    Article  CAS  PubMed  Google Scholar 

  3. Suzuki MM, Bird A (2008) DNA methylation landscapes: provocative insights from epigenomics. Nat Rev Genet 9(6):465–476. https://doi.org/10.1038/nrg2341

    Article  CAS  PubMed  Google Scholar 

  4. Landt SG, Marinov GK, Kundaje A, Kheradpour P, Pauli F, Batzoglou S, Bernstein BE, Bickel P, Brown JB, Cayting P, Chen Y, DeSalvo G, Epstein C, Fisher-Aylor KI, Euskirchen G, Gerstein M, Gertz J, Hartemink AJ, Hoffman MM, Iyer VR, Jung YL, Karmakar S, Kellis M, Kharchenko PV, Li Q, Liu T, Liu XS, Ma L, Milosavljevic A, Myers RM, Park PJ, Pazin MJ, Perry MD, Raha D, Reddy TE, Rozowsky J, Shoresh N, Sidow A, Slattery M, Stamatoyannopoulos JA, Tolstorukov MY, White KP, Xi S, Farnham PJ, Lieb JD, Wold BJ, Snyder M (2012) ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Res 22(9):1813–1831. https://doi.org/10.1101/gr.136184.111

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Einhauer A, Jungbauer A (2001) The FLAG peptide, a versatile fusion tag for the purification of recombinant proteins. J Biochem Biophys Methods 49(1–3):455–465

    Article  CAS  PubMed  Google Scholar 

  6. Kolodziej KE, Pourfarzad F, de Boer E, Krpic S, Grosveld F, Strouboulis J (2009) Optimal use of tandem biotin and V5 tags in ChIP assays. BMC Mol Biol 10:6. https://doi.org/10.1186/1471-2199-10-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Wilbanks EG, Larsen DJ, Neches RY, Yao AI, Wu CY, Kjolby RA, Facciotti MT (2012) A workflow for genome-wide mapping of archaeal transcription factors with ChIP-seq. Nucleic Acids Res 40(10):e74. https://doi.org/10.1093/nar/gks063

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Kidder BL, Hu G, Zhao K (2011) ChIP-Seq: technical considerations for obtaining high-quality data. Nat Immunol 12(10):918–922. https://doi.org/10.1038/ni.2117

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. de Boer E, Rodriguez P, Bonte E, Krijgsveld J, Katsantoni E, Heck A, Grosveld F, Strouboulis J (2003) Efficient biotinylation and single-step purification of tagged transcription factors in mammalian cells and transgenic mice. Proc Natl Acad Sci U S A 100(13):7480–7485. https://doi.org/10.1073/pnas.1332608100

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Green NM (1990) Avidin and streptavidin. Methods Enzymol 184:51–67

    Article  CAS  PubMed  Google Scholar 

  11. Baubec T, Colombo DF, Wirbelauer C, Schmidt J, Burger L, Krebs AR, Akalin A, Schubeler D (2015) Genomic profiling of DNA methyltransferases reveals a role for DNMT3B in genic methylation. Nature 520(7546):243–247. https://doi.org/10.1038/nature14176

    Article  CAS  PubMed  Google Scholar 

  12. Lindqvist Y, Schneider G (1996) Protein-biotin interactions. Curr Opin Struct Biol 6(6):798–803

    Article  CAS  PubMed  Google Scholar 

  13. Schatz PJ (1993) Use of peptide libraries to map the substrate specificity of a peptide-modifying enzyme: a 13 residue consensus peptide specifies biotinylation in Escherichia coli. Biotechnology (N Y) 11(10):1138–1143

    CAS  Google Scholar 

  14. Kim J, Cantor AB, Orkin SH, Wang J (2009) Use of in vivo biotinylation to study protein–protein and protein–DNA interactions in mouse embryonic stem cells. Nat Protoc 4:506–517

    Article  CAS  PubMed  Google Scholar 

  15. Flemr M, Buhler M (2015) Single-step generation of conditional knockout mouse embryonic stem cells. Cell Rep 12(4):709–716. https://doi.org/10.1016/j.celrep.2015.06.051

    Article  CAS  PubMed  Google Scholar 

  16. Weber M, Hellmann I, Stadler MB, Ramos L, Paabo S, Rebhan M, Schubeler D (2007) Distribution, silencing potential and evolutionary impact of promoter DNA methylation in the human genome. Nat Genet 39(4):457–466. https://doi.org/10.1038/ng1990

    Article  CAS  PubMed  Google Scholar 

  17. Meyer CA, Liu XS (2014) Identifying and mitigating bias in next-generation sequencing methods for chromatin biology. Nat Rev Genet 15(11):709–721. https://doi.org/10.1038/nrg3788

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. FASTX-Toolkit (2010) http://hannonlab.cshl.edu/fastx_toolkit/

  19. Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10(3):R25. https://doi.org/10.1186/gb-2009-10-3-r25

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Gaidatzis D, Lerch A, Hahne F, Stadler MB (2015) QuasR: quantification and annotation of short reads in R. Bioinformatics 31(7):1130–1132. https://doi.org/10.1093/bioinformatics/btu781

    Article  CAS  PubMed  Google Scholar 

  21. Lawrence M, Huber W, Pages H, Aboyoun P, Carlson M, Gentleman R, Morgan MT, Carey VJ (2013) Software for computing and annotating genomic ranges. PLoS Comput Biol 9(8):e1003118. https://doi.org/10.1371/journal.pcbi.1003118

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Robinson MD, McCarthy DJ, Smyth GK (2010) edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26(1):139–140. https://doi.org/10.1093/bioinformatics/btp616

    Article  CAS  PubMed  Google Scholar 

  23. Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15(12):550. https://doi.org/10.1186/s13059-014-0550-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Gentleman R, Carey V, Huber W, Hahne F (2016) genefilter: methods for filtering genes from high-throughput experiments. https://www.bioconductor.org/packages/release/bioc/html/genefilter.html

  25. Karolchik D, Hinrichs AS, Furey TS, Roskin KM, Sugnet CW, Haussler D, Kent WJ (2004) The UCSC Table Browser data retrieval tool. Nucleic Acids Res 32(Database issue):D493–D496. https://doi.org/10.1093/nar/gkh103

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Gardiner-Garden M, Frommer M (1987) CpG islands in vertebrate genomes. J Mol Biol 196(2):261–282

    Article  CAS  PubMed  Google Scholar 

  27. Takai D, Jones PA (2002) Comprehensive analysis of CpG islands in human chromosomes 21 and 22. Proc Natl Acad Sci U S A 99(6):3740–3745. https://doi.org/10.1073/pnas.052410099

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Hackenberg M, Carpena P, Bernaola-Galvan P, Barturen G, Alganza AM, Oliver JL (2011) WordCluster: detecting clusters of DNA words and genomic elements. Algorithms Mol Biol 6:2. https://doi.org/10.1186/1748-7188-6-2

    Article  PubMed  PubMed Central  Google Scholar 

  29. Stadler MB, Murr R, Burger L, Ivanek R, Lienert F, Scholer A, van Nimwegen E, Wirbelauer C, Oakeley EJ, Gaidatzis D, Tiwari VK, Schubeler D (2011) DNA-binding factors shape the mouse methylome at distal regulatory regions. Nature 480(7378):490–495. https://doi.org/10.1038/nature10716

    Article  CAS  PubMed  Google Scholar 

  30. Baubec T, Ivanek R, Lienert F, Schubeler D (2013) Methylation-dependent and -independent genomic targeting principles of the MBD protein family. Cell 153(2):480–492. https://doi.org/10.1016/j.cell.2013.03.011

    Article  CAS  PubMed  Google Scholar 

  31. Pagès H, Aboyoun P, Gentleman R, DebRoy S (2016) Biostrings: string objects representing biological sequences, and matching algorithms. https://bioconductor.org/packages/release/bioc/html/Biostrings.html

  32. Illingworth RS, Gruenewald-Schneider U, Webb S, Kerr AR, James KD, Turner DJ, Smith C, Harrison DJ, Andrews R, Bird AP (2010) Orphan CpG islands identify numerous conserved promoters in the mammalian genome. PLoS Genet 6(9):e1001134. https://doi.org/10.1371/journal.pgen.1001134

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Akalin A, Franke V, Vlahovicek K, Mason CE, Schubeler D (2015) Genomation: a toolkit to summarize, annotate and visualize genomic intervals. Bioinformatics 31(7):1127–1129. https://doi.org/10.1093/bioinformatics/btu775

    Article  CAS  PubMed  Google Scholar 

  34. mod/mouse/humanENCODE: blacklisted genomic regions for functional genomics analysis (2014) https://sites.google.com/site/anshulkundaje/projects/blacklists

  35. Manzo M, et al (2017) Isoform-specific localization of DNMT3A regulates DNA methylation fidelity at bivalent CpG islands. EMBO J 36:3421–3434

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

We thank Isabel Schwarz and Joël Wirz for carefully reading the manuscript prior to submission. Research in the Baubeclab is supported by an SNSF Professorship (SNF157488) and Systems-X.ch Special Opportunities Grant (2015_322) to T.B., and by the University of Zurich.

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Authors and Affiliations

  1. Department of Molecular Mechanisms of Disease, University of Zurich, Zurich, Switzerland

    Massimiliano Manzo, Christina Ambrosi & Tuncay Baubec

  2. Molecular Life Science PhD Program of the Life Science Zurich Graduate School, University of Zurich, Zurich, Switzerland

    Massimiliano Manzo & Christina Ambrosi

Authors
  1. Massimiliano Manzo
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  2. Christina Ambrosi
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  3. Tuncay Baubec
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Correspondence to Tuncay Baubec .

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Editors and Affiliations

  1. Josep Carreras Leukaemia, Research Institute, Badalona, Barcelona, Spain

    Tanya Vavouri

  2. IGTP, IMPPC, Badalona, Barcelona, Spain

    Miguel A. Peinado

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Manzo, M., Ambrosi, C., Baubec, T. (2018). Genome-Wide Profiling of DNA Methyltransferases in Mammalian Cells. In: Vavouri, T., Peinado, M. (eds) CpG Islands. Methods in Molecular Biology, vol 1766. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7768-0_9

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  • DOI: https://doi.org/10.1007/978-1-4939-7768-0_9

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7767-3

  • Online ISBN: 978-1-4939-7768-0

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