1,900
Views
26
CrossRef citations to date
0
Altmetric
Research Paper

Interactions between core histone marks and DNA methyltransferases predict DNA methylation patterns observed in human cells and tissues

, ORCID Icon &
Pages 272-282 | Received 07 May 2019, Accepted 06 Sep 2019, Published online: 17 Sep 2019

References

  • Iyer LM, Abhiman S, Aravind L. Chapter 2 natural history of eukaryotic DNA methylation systems. Prog Mol Biol Transl. 2011;101:25–104.
  • Law JA, Jacobsen SE. Establishing, maintaining and modifying DNA methylation patterns in plants and animals. Nat Rev Genet. 2010;11:204.
  • Lyko F. The DNA methyltransferase family: a versatile toolkit for epigenetic regulation. Nat Rev Genet. 2017;19:81.
  • Ooi SK, Qiu C, Bernstein E, et al. DNMT3L connects unmethylated lysine 4 of histone H3 to de novo methylation of DNA. Nature. 2007;448:714.
  • Zhang Y, Jurkowska R, Soeroes S, et al. Chromatin methylation activity of Dnmt3a and Dnmt3a/3L is guided by interaction of the ADD domain with the histone H3 tail. Nucleic Acids Res. 2010;38:4246–4253.
  • Guo X, Wang L, Li J, et al. Structural insight into autoinhibition and histone H3-induced activation of DNMT3A. Nature. 2015;517:640.
  • Singh P, Li AX, Tran DA, et al. de Novo DNA methylation in the male germ line occurs by default but is excluded at sites of H3K4 methylation. Cell Rep. 2013;4:205–219.
  • Dhayalan A, Rajavelu A, Rathert P, et al. The Dnmt3a PWWP domain reads histone 3 lysine 36 trimethylation and guides DNA methylation. J Biol Chem. 2010;285:26114–26120.
  • Vermeulen M, Eberl CH, Matarese F, et al. Quantitative interaction proteomics and genome-wide profiling of epigenetic histone marks and their readers. Cell. 2010;142:967–980.
  • Rose NR, Klose RJ. Understanding the relationship between DNA methylation and histone lysine methylation. Biochimica Et Biophysica Acta Bba - Gene Regul Mech. 2014;1839:1362–1372.
  • Lehnertz B, Ueda Y, Derijck A, et al. Suv39h-mediated histone H3 lysine 9 methylation directs DNA methylation to major satellite repeats at pericentric heterochromatin. Curr Biol. 2003;13:1192–1200.
  • Fuks F, Hurd PJ, Deplus R, et al. The DNA methyltransferases associate with HP1 and the SUV39H1 histone methyltransferase. Nucleic Acids Res. 2003;31:2305–2312.
  • Morselli M, Pastor WA, Montanini B, et al. In vivo targeting of de novo DNA methylation by histone modifications in yeast and mouse. Elife. 2015;4:e06205.
  • Lu L, Lin K, Qian Z, et al. Predicting DNA methylation status using word composition. J Biomed Sci Eng. 2010;13:672–676.
  • Kim S, Li M, Paik H, et al. Predicting DNA methylation susceptibility using CpG flanking sequences. Pac Symposium Biocomput Pac Symposium Biocomput. 2008;315–326.
  • Zhou X, Li Z, Dai Z, et al. Prediction of methylation CpGs and their methylation degrees in human DNA sequences. Comput Biol Med. 2012;42:408–413.
  • Bhasin M, Zhang H, Reinherz EL, et al. Prediction of methylated CpGs in DNA sequences using a support vector machine. Febs Lett. 2005;579:4302–4308.
  • Bock C, Paulsen M, Tierling S, et al. CpG island methylation in human lymphocytes is highly correlated with DNA sequence, repeats, and predicted DNA structure. Plos Genet. 2006;2:e26.
  • Zhang W, Spector TD, Deloukas P, et al. Predicting genome-wide DNA methylation using methylation marks, genomic position, and DNA regulatory elements. Genome Biol. 2015;16:14.
  • Ernst J, Kellis M. Large-scale imputation of epigenomic datasets for systematic annotation of diverse human tissues. Nat Biotechnol. 2015;33:364.
  • Das R, Dimitrova N, Xuan Z, et al. Computational prediction of methylation status in human genomic sequences. Proc Natl Acad Sci. 2006;103:10713–10716.
  • Zheng H, Wu H, Li J, et al. CpGIMethPred: computational model for predicting methylation status of CpG islands in human genome. Bmc Med Genomics. 2013;6:S13.
  • Fan S, Zhang MQ, Zhang X. Histone methylation marks play important roles in predicting the methylation status of CpG islands. Biochem Biophys Res Commun. 2008;374:559–564.
  • Consortium R, Kundaje A, Meuleman W, et al. Integrative analysis of 111 reference human epigenomes. Nature. 2015;518:317.
  • Ernst J, Kellis M. ChromHMM: automating chromatin-state discovery and characterization. Nat Methods. 2012;9:215.
  • Coarfa C, Yu F, Miller CA, et al. Pash 3.0: a versatile software package for read mapping and integrative analysis of genomic and epigenomic variation using massively parallel DNA sequencing. Bmc Bioinformatics. 2010;11:572.
  • Feng J, Liu T, Qin B, et al. Identifying ChIP-seq enrichment using MACS. Nat Protoc. 2012;7:1728.
  • McLean CY, Bristor D, Hiller M, et al. GREAT improves functional interpretation of cis-regulatory regions. Nat Biotechnol. 2010;28:495.
  • Heinz S, Benner C, Spann N, et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol Cell. 2010;38:576–589.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.