Genome-Wide Analysis of DNA Methylation Patterns by High-Throughput Sequencing

  • Tuncay Baubec
  • Altuna Akalin


Epigenetic modifications of chromatin and DNA are relevant for eukaryotic gene expression. DNA methylation is the paradigm epigenetic modification that is associated with transcriptional repression. Perturbations of DNA methylation patterns are frequently associated with cancer and aging, raising a great interest in understanding the contribution of this mark to human health. High-throughput sequencing allows interrogating the status of methylated DNA at nucleotide resolution and genome-wide, bringing unprecedented views on the distribution and dynamics of this relevant modification in healthy and diseased tissues. Here we discuss commonly used wet-lab methodologies and computational approaches to identify DNA methylation patterns and measure their dynamics during biological processes in a quantitative and unbiased manner.


Epigenetic modifications DNA methylation 

Supplementary material


  1. Aird D, Ross MG, Chen W-S et al (2011) Analyzing and minimizing PCR amplification bias in Illumina sequencing libraries. Genome Biol 12:R18. doi: 10.1186/gb-2011-12-2-r18 CrossRefPubMedPubMedCentralGoogle Scholar
  2. Akalin A, Garrett-Bakelman FE, Kormaksson M et al (2012a) Base-pair resolution DNA methylation sequencing reveals profoundly divergent epigenetic landscapes in acute myeloid leukemia. PLoS Genet 8:e1002781. doi: 10.1371/journal.pgen.1002781.s011 CrossRefPubMedPubMedCentralGoogle Scholar
  3. Akalin A, Kormaksson M, Li S et al (2012b) methylKit: a comprehensive R package for the analysis of genome-wide DNA methylation profiles. Genome Biol 13:R87. doi: 10.1186/gb-2012-13-10-r87 CrossRefPubMedPubMedCentralGoogle Scholar
  4. Ball MP, Li JB, Gao Y et al (2009) Targeted and genome-scale strategies reveal gene-body methylation signatures in human cells. Nat Biotechnol 27:361–368. doi: 10.1038/nbt.1533 CrossRefPubMedPubMedCentralGoogle Scholar
  5. Baubec T, Ivanek R, Lienert F, Schübeler D (2013) Methylation-dependent and -independent genomic targeting principles of the MBD protein family. Cell 153:480–492. doi: 10.1016/j.cell.2013.03.011 CrossRefPubMedGoogle Scholar
  6. Baubec T, Colombo DF, Wirbelauer C et al (2015) Genomic profiling of DNA methyltransferases reveals a role for DNMT3B in genic methylation. Nature 520:243. doi: 10.1038/nature14176 CrossRefPubMedGoogle Scholar
  7. Brinkman AB, Simmer F, Ma K et al (2010) Whole-genome DNA methylation profiling using MethylCap-seq. Methods 52:232–236. doi: 10.1016/j.ymeth.2010.06.012 CrossRefPubMedGoogle Scholar
  8. Burger L, Gaidatzis D, Schübeler D, Stadler MB (2013) Identification of active regulatory regions from DNA methylation data. Nucleic Acids Res 41:e155. doi: 10.1093/nar/gkt599 CrossRefPubMedPubMedCentralGoogle Scholar
  9. Clark SJ, Harrison J, Paul CL, Frommer M (1994) High sensitivity mapping of methylated cytosines. Nucleic Acids Res 22:2990–2997CrossRefPubMedPubMedCentralGoogle Scholar
  10. Cokus SJ, Feng S, Zhang X et al (2008) Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning. Nature 452:215–219. doi: 10.1038/nature06745 CrossRefPubMedPubMedCentralGoogle Scholar
  11. Cross SH, Charlton JA, Nan X, Bird AP (1994) Purification of CpG islands using a methylated DNA binding column. Nat Genet 6:236–244. doi: 10.1038/ng0394-236 CrossRefPubMedGoogle Scholar
  12. Dinh HQ, Dubin M, Sedlazeck FJ et al (2012) Advanced methylome analysis after bisulfite deep sequencing: an example in Arabidopsis. PLoS One 7:e41528. doi: 10.1371/journal.pone.0041528.s026 CrossRefPubMedPubMedCentralGoogle Scholar
  13. Dodt M, Roehr JT, Ahmed R, Dieterich C (2012) FLEXBAR-flexible barcode and adapter processing for next-generation sequencing platforms. Biology (Basel) 1:895–905. doi: 10.3390/biology1030895 Google Scholar
  14. Doi A, Park I-H, Wen B et al (2009) 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. doi: 10.1038/ng.471 CrossRefPubMedPubMedCentralGoogle Scholar
  15. Dolzhenko E, Smith AD (2014) Using beta-binomial regression for high-precision differential methylation analysis in multifactor whole-genome bisulfite sequencing experiments. BMC Bioinformatics 15:215. doi: 10.1186/1471-2105-15-215 CrossRefPubMedPubMedCentralGoogle Scholar
  16. Durbin R (1998) Biological sequence analysis. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  17. Feng S, Cokus SJ, Zhang X et al (2010) Conservation and divergence of methylation patterning in plants and animals. Proc Natl Acad Sci U S A 107:8689–8694. doi: 10.1073/pnas.1002720107 CrossRefPubMedPubMedCentralGoogle Scholar
  18. Feng H, Conneely KN, Wu H (2014) A Bayesian hierarchical model to detect differentially methylated loci from single nucleotide resolution sequencing data. Nucleic Acids Res 42:e69. doi: 10.1093/nar/gku154 CrossRefPubMedPubMedCentralGoogle Scholar
  19. Ficz G, Branco MR, Seisenberger S et al (2011) Dynamic regulation of 5-hydroxymethylcytosine in mouse ES cells and during differentiation. Nature 473:398–402. doi: 10.1038/nature10008 CrossRefPubMedGoogle Scholar
  20. Frith MC, Mori R, Asai K (2012) A mostly traditional approach improves alignment of bisulfite-converted DNA. Nucleic Acids Res 40:e100. doi: 10.1093/nar/gks275 CrossRefPubMedPubMedCentralGoogle Scholar
  21. Gaidatzis D, Burger L, Murr R et al (2014) DNA sequence explains seemingly disordered methylation levels in partially methylated domains of mammalian genomes. PLoS Genet 10:e1004143. doi: 10.1371/journal.pgen.1004143.g005 CrossRefPubMedPubMedCentralGoogle Scholar
  22. Gebhard C, Schwarzfischer L, Pham T-H et al (2006) Rapid and sensitive detection of CpG-methylation using methyl-binding (MB)-PCR. Nucleic Acids Res 34:e82. doi: 10.1093/nar/gkl437 CrossRefPubMedPubMedCentralGoogle Scholar
  23. Gent JI, Ellis NA, Guo L et al (2013) CHH islands: de novo DNA methylation in near-gene chromatin regulation in maize. Genome Res 23:628–637. doi: 10.1101/gr.146985.112 CrossRefPubMedPubMedCentralGoogle Scholar
  24. Goll MG, Bestor TH (2005) Eukaryotic cytosine methyltransferases. Annu Rev Biochem 74:481–514. doi: 10.1146/annurev.biochem.74.010904.153721 CrossRefPubMedGoogle Scholar
  25. Gu H, Smith ZD, Bock C et al (2011) Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling. Nat Protoc 6:468–481. doi: 10.1038/nprot.2010.190 CrossRefPubMedGoogle Scholar
  26. Guo W, Fiziev P, Yan W et al (2013) BS-Seeker2: a versatile aligning pipeline for bisulfite sequencing data. BMC Genomics 14:774. doi: 10.1186/1471-2164-14-774 CrossRefPubMedPubMedCentralGoogle Scholar
  27. Hansen KD, Langmead B, Irizarry RA (2012) BSmooth: from whole genome bisulfite sequencing reads to differentially methylated regions. Genome Biol 13:R83. doi: 10.1186/gb-2012-13-10-r83 CrossRefPubMedPubMedCentralGoogle Scholar
  28. Harris EY, Ponts N, Le Roch KG, Lonardi S (2012) BRAT-BW: efficient and accurate mapping of bisulfite-treated reads. Bioinformatics 28:1795–1796. doi: 10.1093/bioinformatics/bts264 CrossRefPubMedPubMedCentralGoogle Scholar
  29. Hebestreit K, Dugas M, Klein H-U (2013) Detection of significantly differentially methylated regions in targeted bisulfite sequencing data. Bioinformatics 29:1647–1653. doi: 10.1093/bioinformatics/btt263 CrossRefPubMedGoogle Scholar
  30. Hendrich B, Bird A (1998) Identification and characterization of a family of mammalian methyl-CpG binding proteins. Mol Cell Biol 18:6538–6547CrossRefPubMedPubMedCentralGoogle Scholar
  31. Hon GC, Rajagopal N, Shen Y et al (2013) Epigenetic memory at embryonic enhancers identified in DNA methylation maps from adult mouse tissues. Nat Genet 45:1198–1206. doi: 10.1038/ng.2746 CrossRefPubMedPubMedCentralGoogle Scholar
  32. Huang Y, Pastor WA, Shen Y et al (2010) The behaviour of 5-hydroxymethylcytosine in bisulfite sequencing. PLoS One 5:e8888. doi: 10.1371/journal.pone.0008888 CrossRefPubMedPubMedCentralGoogle Scholar
  33. Ivanov M, Kals M, Kacevska M et al (2013) In-solution hybrid capture of bisulfite-converted DNA for targeted bisulfite sequencing of 174 ADME genes. Nucleic Acids Res 41:e72. doi: 10.1093/nar/gks1467 CrossRefPubMedPubMedCentralGoogle Scholar
  34. Jones PA, Taylor SM (1980) Cellular differentiation, cytidine analogs and DNA methylation. Cell 20:85–93CrossRefPubMedGoogle Scholar
  35. Jørgensen HF, Adie K, Chaubert P, Bird AP (2006) Engineering a high-affinity methyl-CpG-binding protein. Nucleic Acids Res 34:e96. doi: 10.1093/nar/gkl527 CrossRefPubMedPubMedCentralGoogle Scholar
  36. Klambauer G, Schwarzbauer K, Mayr A et al (2012) cn.MOPS: mixture of Poissons for discovering copy number variations in next-generation sequencing data with a low false discovery rate. Nucleic Acids Res 40:e69. doi: 10.1093/nar/gks003 CrossRefPubMedPubMedCentralGoogle Scholar
  37. Kohli RM, Zhang Y (2013) TET enzymes, TDG and the dynamics of DNA demethylation. Nature 502:472–479. doi: 10.1038/nature12750 CrossRefPubMedPubMedCentralGoogle Scholar
  38. Komori HK, LaMere SA, Torkamani A et al (2011) Application of microdroplet PCR for large-scale targeted bisulfite sequencing. Genome Res 21:1738–1745. doi: 10.1101/gr.116863.110 CrossRefPubMedPubMedCentralGoogle Scholar
  39. Krueger F, Andrews SR (2011) Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics 27:1571–1572. doi: 10.1093/bioinformatics/btr167 CrossRefPubMedPubMedCentralGoogle Scholar
  40. Laird PW, Jaenisch R (1994) DNA methylation and cancer. Hum Mol Genet 3 Spec No: 1487–1495Google Scholar
  41. Landan G, Cohen NM, Mukamel Z et al (2012) Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues. Nat Genet 44:1207–1214. doi: 10.1038/ng.2442 CrossRefPubMedGoogle Scholar
  42. 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:R25. doi: 10.1186/gb-2009-10-3-r25 CrossRefPubMedPubMedCentralGoogle Scholar
  43. Lee EJ, Pei L, Srivastava G et al (2011) Targeted bisulfite sequencing by solution hybrid selection and massively parallel sequencing. Nucleic Acids Res 39:e127. doi: 10.1093/nar/gkr598 CrossRefPubMedPubMedCentralGoogle Scholar
  44. Li L-C, Dahiya R (2002) MethPrimer: designing primers for methylation PCRs. Bioinformatics 18:1427–1431CrossRefPubMedGoogle Scholar
  45. Li S, Garrett-Bakelman FE, Akalin A et al (2013) An optimized algorithm for detecting and annotating regional differential methylation. BMC Bioinformatics 14(Suppl 5):S10. doi: 10.1186/1471-2105-14-S5-S10 CrossRefPubMedPubMedCentralGoogle Scholar
  46. Lister R, Pelizzola M, Dowen RH et al (2009) Human DNA methylomes at base resolution show widespread epigenomic differences. Nature 462:315–322. doi: 10.1038/nature08514 CrossRefPubMedPubMedCentralGoogle Scholar
  47. Lister R, Mukamel EA, Nery JR et al (2013) Global epigenomic reconfiguration during mammalian brain development. Science 341:1237905. doi: 10.1126/science.1237905 CrossRefPubMedPubMedCentralGoogle Scholar
  48. Liu Y, Siegmund KD, Laird PW, Berman BP (2012) Bis-SNP: combined DNA methylation and SNP calling for Bisulfite-seq data. Genome Biol 13:R61. doi: 10.1186/gb-2012-13-7-r61 CrossRefPubMedPubMedCentralGoogle Scholar
  49. Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J 17(1)Google Scholar
  50. Meissner A (2005) Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis. Nucleic Acids Res 33:5868–5877. doi: 10.1093/nar/gki901 CrossRefPubMedPubMedCentralGoogle Scholar
  51. Mohn F, Weber M, Schübeler D, Roloff T-C (2009) Methylated DNA immunoprecipitation (MeDIP). Methods Mol Biol 507:55–64. doi: 10.1007/978-1-59745-522-0_5 CrossRefPubMedGoogle Scholar
  52. Molaro A, Hodges E, Fang F et al (2011) Sperm methylation profiles reveal features of epigenetic inheritance and evolution in primates. Cell 146:1029–1041. doi: 10.1016/j.cell.2011.08.016 CrossRefPubMedPubMedCentralGoogle Scholar
  53. Nair SS, Coolen MW, Stirzaker C et al (2014) Comparison of methyl-DNA immunoprecipitation (MeDIP) and methyl-CpG binding domain (MBD) protein capture for genome-wide DNA methylation analysis reveal CpG sequence coverage bias. Epigenetics 6:34–44. doi: 10.4161/epi.6.1.13313 CrossRefGoogle Scholar
  54. Okano M, Bell DW, Haber DA, Li E (1999) DNA methyltransferases Dnmt3a and Dnmt3b are essential for de novo methylation and mammalian development. Cell 99:247–257CrossRefPubMedGoogle Scholar
  55. Pedersen B, Hsieh T-F, Ibarra C, Fischer RL (2011) MethylCoder: software pipeline for bisulfite-treated sequences. Bioinformatics 27:2435–2436. doi: 10.1093/bioinformatics/btr394 CrossRefPubMedPubMedCentralGoogle Scholar
  56. Plongthongkum N, Diep DH, Zhang K (2014) Advances in the profiling of DNA modifications: cytosine methylation and beyond. Nat Rev Genet 15:647–661. doi: 10.1038/nrg3772 CrossRefPubMedGoogle Scholar
  57. Rauch T, Pfeifer GP (2005) Methylated-CpG island recovery assay: a new technique for the rapid detection of methylated-CpG islands in cancer. Lab Invest 85:1172–1180. doi: 10.1038/labinvest.3700311 CrossRefPubMedGoogle Scholar
  58. Smallwood SEBA, Lee HJ, Angermueller C et al (2014) Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity. Nat Methods 11:817. doi: 10.1038/nmeth.3035 CrossRefPubMedPubMedCentralGoogle Scholar
  59. Smith ZD, Meissner A (2013) DNA methylation: roles in mammalian development. Nat Rev Genet 14:204–220. doi: 10.1038/nrg3354 CrossRefPubMedGoogle Scholar
  60. Smyth GK (2004) Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 3: Article 3. doi:  10.2202/1544-6115.1027
  61. Stadler MB, Murr R, Burger L et al (2011) DNA-binding factors shape the mouse methylome at distal regulatory regions. Nature 480:490–495. doi: 10.1038/nature10716 PubMedGoogle Scholar
  62. Sun D, Xi Y, Rodriguez B et al (2014) MOABS: model based analysis of bisulfite sequencing data. Genome Biol 15:R38. doi: 10.1186/gb-2014-15-2-r38 CrossRefPubMedPubMedCentralGoogle Scholar
  63. Suzuki MM, Bird A (2008) DNA methylation landscapes: provocative insights from epigenomics. Nat Rev Genet 9:465–476. doi: 10.1038/nrg2341 CrossRefPubMedGoogle Scholar
  64. Taiwo O, Wilson GA, Morris T et al (2012) Methylome analysis using MeDIP-seq with low DNA concentrations. Nat Protoc 7:617–636. doi: 10.1038/nprot.2012.012 CrossRefPubMedGoogle Scholar
  65. Taylor KH, Kramer RS, Davis JW et al (2007) Ultradeep bisulfite sequencing analysis of DNA methylation patterns in multiple gene promoters by 454 sequencing. Cancer Res 67:8511–8518. doi: 10.1158/0008-5472.CAN-07-1016 CrossRefPubMedGoogle Scholar
  66. Wang RY, Gehrke CW, Ehrlich M (1980) Comparison of bisulfite modification of 5-methyldeoxycytidine and deoxycytidine residues. Nucleic Acids Res 8:4777–4790CrossRefPubMedPubMedCentralGoogle Scholar
  67. Warnecke PM, Stirzaker C, Song J et al (2002) Identification and resolution of artifacts in bisulfite sequencing. Methods 27:101–107CrossRefPubMedGoogle Scholar
  68. Weber M, Davies JJ, Wittig D et al (2005) Chromosome-wide and promoter-specific analyses identify sites of differential DNA methylation in normal and transformed human cells. Nat Genet 37:853–862. doi: 10.1038/ng1598 CrossRefPubMedGoogle Scholar
  69. Xi Y, Li W (2009) BSMAP: whole genome bisulfite sequence MAPping program. BMC Bioinformatics 10:232. doi: 10.1186/1471-2105-10-232 CrossRefPubMedPubMedCentralGoogle Scholar
  70. Zemach A, McDaniel IE, Silva P, Zilberman D (2010) Genome-wide evolutionary analysis of eukaryotic DNA methylation. Science 328:916–919. doi: 10.1126/science.1186366 CrossRefPubMedGoogle Scholar
  71. Ziller MJ, Gu H, Müller F et al (2013) Charting a dynamic DNA methylation landscape of the human genome. Nature 500:477–481. doi: 10.1038/nature12433 CrossRefPubMedPubMedCentralGoogle Scholar
  72. Ziller MJ, Hansen KD, Meissner A, Aryee MJ (2015) Coverage recommendations for methylation analysis by whole-genome bisulfite sequencing. Nat Methods 12:230. doi: 10.1038/nmeth.3152 CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Epigenomics and Chromatin Biology Lab, Institute of Veterinary Biochemistry and Molecular BiologyUniversity of ZurichZurichSwitzerland
  2. 2.Bioinformatics Platform, Berlin Institute for Medical Systems BiologyMax Delbrück CentreBerlinGermany

Personalised recommendations