Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues

Nature Genetics volume 44, pages 1207–1214 (2012)Cite this article

Subjects

Abstract

DNA methylation has been comprehensively profiled in normal and cancer cells, but the dynamics that form, maintain and reprogram differentially methylated regions remain enigmatic. Here, we show that methylation patterns within populations of cells from individual somatic tissues are heterogeneous and polymorphic. Using in vitro evolution of immortalized fibroblasts for over 300 generations, we track the dynamics of polymorphic methylation at regions developing significant differential methylation on average. The data indicate that changes in population-averaged methylation occur through a stochastic process that generates a stream of local and uncorrelated methylation aberrations. Despite the stochastic nature of the process, nearly deterministic epigenetic remodeling emerges on average at loci that lose or gain resistance to methylation accumulation. Changes in the susceptibility to methylation accumulation are correlated with changes in histone modification and CTCF occupancy. Characterizing epigenomic polymorphism within cell populations is therefore critical to understanding methylation dynamics in normal and cancer cells.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Epipolymorphism.
Figure 2: Differentially methylated loci are epipolymorphic.
Figure 3: Extensive average differential methylation during fibroblast evolution in vitro.
Figure 4: Hypermethylation is a parallel, stochastic and gradual evolutionary process.
Figure 5: Spatial constraints canalize hypermethylation patterns.
Figure 6: H3K4me3, CTCF binding and H3K27me3 are anticorrelated with DNA methylation kinetics.

Accession codes

Primary accessions

Gene Expression Omnibus

Sequence Read Archive

References

  1. Wu, S.C. & Zhang, Y. Active DNA demethylation: many roads lead to Rome. Nat. Rev. Mol. Cell Biol. 11, 607–620 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Smallwood, S.A. et al. Dynamic CpG island methylation landscape in oocytes and preimplantation embryos. Nat. Genet. 43, 811–814 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Feng, S., Jacobsen, S.E. & Reik, W. Epigenetic reprogramming in plant and animal development. Science 330, 622–627 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Bird, A. DNA methylation patterns and epigenetic memory. Genes Dev. 16, 6–21 (2002).

    Article  CAS  PubMed  Google Scholar 

  5. Hodges, E. et al. Directional DNA methylation changes and complex intermediate states accompany lineage specificity in the adult hematopoietic compartment. Mol. Cell 44, 17–28 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Ji, H. et al. Comprehensive methylome map of lineage commitment from haematopoietic progenitors. Nature 467, 338–342 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Song, J., Rechkoblit, O., Bestor, T.H. & Patel, D.J. Structure of DNMT1-DNA complex reveals a role for autoinhibition in maintenance DNA methylation. Science 331, 1036–1040 (2011).

    Article  CAS  PubMed  Google Scholar 

  8. Song, J., Teplova, M., Ishibe-Murakami, S. & Patel, D.J. Structure-based mechanistic insights into DNMT1-mediated maintenance DNA methylation. Science 335, 709–712 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Lister, R. et al. Human DNA methylomes at base resolution show widespread epigenomic differences. Nature 462, 315–322 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Li, Y. et al. The DNA methylome of human peripheral blood mononuclear cells. PLoS Biol. 8, e1000533 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  11. Lister, R. et al. Hotspots of aberrant epigenomic reprogramming in human induced pluripotent stem cells. Nature 471, 68–73 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Hon, G.C. et al. Global DNA hypomethylation coupled to repressive chromatin domain formation and gene silencing in breast cancer. Genome Res. 22, 246–258 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Greaves, M. & Maley, C.C. Clonal evolution in cancer. Nature 481, 306–313 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Irizarry, R.A. et al. The human colon cancer methylome shows similar hypo- and hypermethylation at conserved tissue-specific CpG island shores. Nat. Genet. 41, 178–186 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Noushmehr, H. et al. Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma. Cancer Cell 17, 510–522 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Hansen, K.D. et al. Increased methylation variation in epigenetic domains across cancer types. Nat. Genet. 43, 768–775 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Berman, B.P. et al. Regions of focal DNA hypermethylation and long-range hypomethylation in colorectal cancer coincide with nuclear lamina–associated domains. Nat. Genet. 44, 40–46 (2012).

    Article  CAS  Google Scholar 

  18. Sottoriva, A., Vermeulen, L. & Tavare, S. Modeling evolutionary dynamics of epigenetic mutations in hierarchically organized tumors. PLOS Comput. Biol. 7, e1001132 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Siegmund, K.D., Marjoram, P., Tavare, S. & Shibata, D. High DNA methylation pattern intratumoral diversity implies weak selection in many human colorectal cancers. PLoS ONE 6, e21657 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Siegmund, K.D., Marjoram, P., Woo, Y.J., Tavare, S. & Shibata, D. Inferring clonal expansion and cancer stem cell dynamics from DNA methylation patterns in colorectal cancers. Proc. Natl. Acad. Sci. USA 106, 4828–4833 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Rosenbloom, K.R. et al. ENCODE whole-genome data in the UCSC Genome Browser. Nucleic Acids Res. 38, D620–D625 (2010).

    Article  CAS  PubMed  Google Scholar 

  22. Raney, B.J. et al. ENCODE whole-genome data in the UCSC genome browser (2011 update). Nucleic Acids Res. 39, D871–D875 (2011).

    Article  CAS  PubMed  Google Scholar 

  23. Doi, A. et al. Differential methylation of tissue- and cancer-specific CpG island shores distinguishes human induced pluripotent stem cells, embryonic stem cells and fibroblasts. Nat. Genet. 41, 1350–1353 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Rakyan, V.K. et al. An integrated resource for genome-wide identification and analysis of human tissue-specific differentially methylated regions (tDMRs). Genome Res. 18, 1518–1529 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Milyavsky, M. et al. Prolonged culture of telomerase-immortalized human fibroblasts leads to a premalignant phenotype. Cancer Res. 63, 7147–7157 (2003).

    CAS  PubMed  Google Scholar 

  26. Gal-Yam, E.N. et al. Frequent switching of Polycomb repressive marks and DNA hypermethylation in the PC3 prostate cancer cell line. Proc. Natl. Acad. Sci. USA 105, 12979–12984 (2008).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Harris, R.A. et al. Comparison of sequencing-based methods to profile DNA methylation and identification of monoallelic epigenetic modifications. Nat. Biotechnol. 28, 1097–1105 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Cohen, N.M., Kenigsberg, E. & Tanay, A. Primate CpG islands are maintained by heterogeneous evolutionary regimes involving minimal selection. Cell 145, 773–786 (2011).

    Article  CAS  PubMed  Google Scholar 

  29. Weber, M. et al. Distribution, silencing potential and evolutionary impact of promoter DNA methylation in the human genome. Nat. Genet. 39, 457–466 (2007).

    Article  CAS  PubMed  Google Scholar 

  30. Ito, S. et al. Role of Tet proteins in 5mC to 5hmC conversion, ES-cell self-renewal and inner cell mass specification. Nature 466, 1129–1133 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Bhutani, N. et al. Reprogramming towards pluripotency requires AID-dependent DNA demethylation. Nature 463, 1042–1047 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Okada, Y., Yamagata, K., Hong, K., Wakayama, T. & Zhang, Y. A role for the elongator complex in zygotic paternal genome demethylation. Nature 463, 554–558 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Cortázar, D. et al. Embryonic lethal phenotype reveals a function of TDG in maintaining epigenetic stability. Nature 470, 419–423 (2011).

    Article  PubMed  CAS  Google Scholar 

  34. Feinberg, A.P. & Tycko, B. The history of cancer epigenetics. Nat. Rev. Cancer 4, 143–153 (2004).

    Article  CAS  PubMed  Google Scholar 

  35. Esteller, M. Epigenetics in cancer. N. Engl. J. Med. 358, 1148–1159 (2008).

    Article  CAS  PubMed  Google Scholar 

  36. Taylor, K.H. et al. Ultradeep bisulfite sequencing analysis of DNA methylation patterns in multiple gene promoters by 454 sequencing. Cancer Res. 67, 8511–8518 (2007).

    Article  CAS  PubMed  Google Scholar 

  37. Ehrich, M. et al. Cytosine methylation profiling of cancer cell lines. Proc. Natl. Acad. Sci. USA 105, 4844–4849 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Viré, E. et al. The Polycomb group protein EZH2 directly controls DNA methylation. Nature 439, 871–874 (2006).

    Article  PubMed  CAS  Google Scholar 

  39. O'Hagan, H.M. et al. Oxidative damage targets complexes containing DNA methyltransferases, SIRT1, and polycomb members to promoter CpG islands. Cancer Cell 20, 606–619 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Kim, J.D., Kang, K. & Kim, J. YY1's role in DNA methylation of Peg3 and Xist. Nucleic Acids Res. 37, 5656–5664 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Bartke, T. et al. Nucleosome-interacting proteins regulated by DNA and histone methylation. Cell 143, 470–484 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Adams, D. et al. BLUEPRINT to decode the epigenetic signature written in blood. Nat. Biotechnol. 30, 224–226 (2012).

    Article  CAS  PubMed  Google Scholar 

  43. Milosavljevic, A. Emerging patterns of epigenomic variation. Trends Genet. 27, 242–250 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Mohn, F. et al. Lineage-specific polycomb targets and de novo DNA methylation define restriction and potential of neuronal progenitors. Mol. Cell 30, 755–766 (2008).

    CAS  PubMed  Google Scholar 

  45. Cohen, N.M. et al. DNA methylation programming and reprogramming in primate embryonic stem cells. Genome Res. 19, 2193–2201 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Schlesinger, Y. et al. Polycomb-mediated methylation on Lys27 of histone H3 pre-marks genes for de novo methylation in cancer. Nat. Genet. 39, 232–236 (2007).

    Article  CAS  PubMed  Google Scholar 

  47. Terranova, R., Agherbi, H., Boned, A., Meresse, S. & Djabali, M. Histone and DNA methylation defects at Hox genes in mice expressing a SET domain–truncated form of Mll. Proc. Natl. Acad. Sci. USA 103, 6629–6634 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Brykczynska, U. et al. Repressive and active histone methylation mark distinct promoters in human and mouse spermatozoa. Nat. Struct. Mol. Biol. 17, 679–687 (2010).

    Article  CAS  PubMed  Google Scholar 

  49. Brinkman, A.B. et al. Sequential ChIP-bisulfite sequencing enables direct genome-scale investigation of chromatin and DNA methylation cross-talk. Genome Res. 22, 1128–1138 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Statham, A.L. et al. Bisulfite sequencing of chromatin immunoprecipitated DNA (BisChIP-seq) directly informs methylation status of histone-modified DNA. Genome Res. 22, 1120–1127 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Lienert, F. et al. Identification of genetic elements that autonomously determine DNA methylation states. Nat. Genet. 43, 1091–1097 (2011).

    Article  CAS  PubMed  Google Scholar 

  52. Krueger, F. & Andrews, S.R. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics 27, 1571–1572 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Pencovich, N., Jaschek, R., Tanay, A. & Groner, Y. Dynamic combinatorial interactions of RUNX1 and cooperating partners regulates megakaryocytic differentiation in cell line models. Blood 117, e1–e14 (2011).

    Article  CAS  PubMed  Google Scholar 

  54. R Development Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, 2009).

Download references

Acknowledgements

We thank the members of the Tanay group for discussions. Research in the Tanay laboratory was supported by grants from the Israel Science Foundation (grant 1372/08), the European Commission Framework Programme 7 Network of Excellence EPIGENESYS and the BLUEPRINT European Union consortium. Research in the Rotter laboratory was supported by a Center of Excellence grant from the Flight Attendant Medical Research Institute (FAMRI). E.N.G.-Y. is a fellow of the Talpiot Medical Leadership Program at the Sheba Medical Center.

Author information

Authors and Affiliations

  1. Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot, Israel

    Gilad Landan, Netta Mendelson Cohen, Zohar Mukamel, Amir Bar & Amos Tanay

  2. Department of Biological Regulation, Weizmann Institute of Science, Rehovot, Israel

    Gilad Landan, Zohar Mukamel & Amos Tanay

  3. Department of Molecular Cell Biology, Weizmann Institute of Science, Rehovot, Israel

    Gilad Landan, Alina Molchadsky, Ran Brosh, Naomi Goldfinger & Varda Rotter

  4. Department of Biological Services, Weizmann Institute of Science, Rehovot, Israel

    Shirley Horn-Saban & Daniela Amann Zalcenstein

  5. Cancer Research Center, Sheba Medical Center, Tel-Ha'Shomer, Israel

    Adi Zundelevich & Einav Nili Gal-Yam

Authors
  1. Gilad Landan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Netta Mendelson Cohen
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zohar Mukamel
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Amir Bar
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Alina Molchadsky
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ran Brosh
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Shirley Horn-Saban
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Daniela Amann Zalcenstein
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Naomi Goldfinger
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Adi Zundelevich
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Einav Nili Gal-Yam
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Varda Rotter
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Amos Tanay
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

G.L., E.N.G.-Y., V.R. and A.T. designed the experiments. G.L. and Z.M. performed bisulfite and immunoprecipitation experiments with help from E.N.G.-Y. and A.Z. G.L., N.M.C., A.B. and A.T. analyzed the data. G.L. extracted RNA and conducted tissue culture with help from A.M., R.B. and N.G. S.H.-S. and D.A.Z. performed high-throughput sequencing and assisted with protocol adaptations. G.L. and A.T. wrote the manuscript.

Corresponding author

Correspondence to Amos Tanay.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–20 and Supplementary Note (PDF 6604 kb)

Supplementary Table 1

Names of samples analyzed in this study, as well statistics on the number of mapped reads and the number of adequately covered 4-mers. (XLS 29 kb)

Supplementary Table 2

Names of amplicons assayed using Deep-BIS, as well as statistics on the length and genomic coordinates of primers, genomic sequence, amplicon length, number of CpGs, CpG content, and behavior in the MeDIP-seq data. (XLS 50 kb)

Supplementary Table 3

Names of amplicons assayed using ChIP-Deep-BIS, as well as statistics on the length and genomic coordinates of primers, genomic sequence, amplicon length, number of CpGs, CpG content, and amplicon class, indicating whether regions are imprinted, repeat sequences, or reside on chromosome X. The length of the original amplicon is indicated for those amplicons that represent approximately half of a larger amplicon, designed by introducing internal primers in order to generate smaller amplicons more likely to amplify sonicated material. (XLS 42 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Landan, G., Cohen, N., Mukamel, Z. et al. Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues. Nat Genet 44, 1207–1214 (2012). https://doi.org/10.1038/ng.2442

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.2442

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing