MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data.

Giulia De Riso, Antonella Sarnataro, Giovanni Scala, Mariella Cuomo, Rosa Della Monica, Stefano Amente, Lorenzo Chiariotti, Gennaro Miele, Sergio Cocozza
Author Information
  1. Giulia De Riso: Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy. ORCID
  2. Antonella Sarnataro: Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy.
  3. Giovanni Scala: Department of Biology, University of Naples Federico II, Via Vicinale Cupa Cintia 21, 80126 Naples, Italy.
  4. Mariella Cuomo: Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy.
  5. Rosa Della Monica: CEINGE - Biotecnologie Avanzate, Via Gaetano Salvatore, 486, 80145 Naples, Italy. ORCID
  6. Stefano Amente: Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy. ORCID
  7. Lorenzo Chiariotti: Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy.
  8. Gennaro Miele: Department of Physics "E. Pancini", University of Naples "Federico II", Via Cinthia, 80126 Naples, Italy.
  9. Sergio Cocozza: Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, via Sergio Pansini 5, 80131 Naples, Italy.

Abstract

DNA methylation is an epigenetic mark implicated in crucial biological processes. Most of the knowledge about DNA methylation is based on bulk experiments, in which DNA methylation of genomic regions is reported as average methylation. However, average methylation does not inform on how methylated cytosines are distributed in each single DNA molecule. Here, we propose Methylation Class (MC) profiling as a genome-wide approach to the study of DNA methylation heterogeneity from bulk bisulfite sequencing experiments. The proposed approach is built on the concept of MCs, groups of DNA molecules sharing the same number of methylated cytosines. The relative abundances of MCs from sequencing reads incorporates the information on the average methylation, and directly informs on the methylation level of each molecule. By applying our approach to publicly available bisulfite-sequencing datasets, we individuated cell-to-cell differences as the prevalent contributor to methylation heterogeneity. Moreover, we individuated signatures of loci undergoing imprinting and X-inactivation, and highlighted differences between the two processes. When applying MC profiling to compare different conditions, we identified methylation changes occurring in regions with almost constant average methylation. Altogether, our results indicate that MC profiling can provide useful insights on the epigenetic status and its evolution at multiple genomic regions.

References

  1. Nat Methods. 2016 Mar;13(3):229-232 [PMID: 26752769]
  2. Biomolecules. 2020 Sep 03;10(9): [PMID: 32899254]
  3. Epigenetics Chromatin. 2016 Jun 29;9:26 [PMID: 27358654]
  4. J Neurosci. 2016 Feb 03;36(5):1711-22 [PMID: 26843651]
  5. Nucleic Acids Res. 2008 Jun;36(10):e55 [PMID: 18413340]
  6. Brief Funct Genomics. 2016 Nov;15(6):443-453 [PMID: 27416614]
  7. Genes Dis. 2018 Jan 31;5(1):1-8 [PMID: 30258928]
  8. Epigenetics Chromatin. 2018 May 25;11(1):21 [PMID: 29801521]
  9. Nat Rev Genet. 2005 Aug;6(8):597-610 [PMID: 16136652]
  10. Nucleic Acids Res. 2020 Sep 18;48(16):e92 [PMID: 32621604]
  11. Epigenetics Chromatin. 2014 Oct 23;7(1):28 [PMID: 25493099]
  12. BMC Bioinformatics. 2018 Mar 7;19(1):87 [PMID: 29514626]
  13. Trends Genet. 2021 Nov;37(11):1012-1027 [PMID: 34120771]
  14. Genome Biol. 2020 Jul 13;21(1):172 [PMID: 32660534]
  15. Proc Natl Acad Sci U S A. 2018 Dec 18;115(51):13015-13020 [PMID: 30510006]
  16. Epigenetics Chromatin. 2021 Jun 29;14(1):30 [PMID: 34187555]
  17. Stem Cell Reports. 2018 Aug 14;11(2):578-592 [PMID: 30078558]
  18. Exp Mol Med. 2017 Apr 28;49(4):e322 [PMID: 28450738]
  19. Eur J Hum Genet. 2002 Jan;10(1):6-16 [PMID: 11896451]
  20. Genome Res. 2010 Sep;20(9):1279-87 [PMID: 20627893]
  21. BMC Genomics. 2018 Apr 2;19(1):229 [PMID: 29606093]
  22. Curr Opin Cell Biol. 2007 Jun;19(3):281-9 [PMID: 17467259]
  23. Nucleic Acids Res. 2015 Dec 15;43(22):10689-99 [PMID: 26338779]
  24. Nat Rev Mol Cell Biol. 2019 Oct;20(10):590-607 [PMID: 31399642]
  25. Nat Genet. 2009 Feb;41(2):178-186 [PMID: 19151715]
  26. Nat Biotechnol. 2010 Oct;28(10):1106-14 [PMID: 20852634]
  27. Nat Commun. 2020 Jun 19;11(1):3153 [PMID: 32561758]
  28. Biochem Soc Trans. 2018 Jun 19;46(3):577-586 [PMID: 29678955]
  29. Biol Sex Differ. 2015 Dec 30;6:35 [PMID: 26719789]
  30. Comput Struct Biotechnol J. 2022 Oct 23;20:5925-5934 [PMID: 36382198]
  31. Bioinformatics. 2022 Jun 24;38(Suppl 1):i307-i315 [PMID: 35758820]
  32. Clin Epigenetics. 2019 Oct 28;11(1):149 [PMID: 31661019]
  33. Biomolecules. 2021 Jan 22;11(2): [PMID: 33499115]
  34. Mol Cell. 2008 Jun 20;30(6):755-66 [PMID: 18514006]
  35. Front Genet. 2020 Oct 30;11:507038 [PMID: 33193597]
  36. Nat Genet. 2009 Dec;41(12):1350-3 [PMID: 19881528]
  37. Trends Biotechnol. 2018 Sep;36(9):952-965 [PMID: 29724495]
  38. Nucleic Acids Res. 2010 Aug;38(15):4929-45 [PMID: 20385583]
  39. Epigenetics Chromatin. 2021 Feb 17;14(1):12 [PMID: 33597016]
  40. Hum Genomics. 2016 Jul 25;10 Suppl 2:18 [PMID: 27461342]
  41. Nat Genet. 2012 Nov;44(11):1207-14 [PMID: 23064413]
  42. Nat Commun. 2015 Feb 18;6:6363 [PMID: 25691127]
  43. Commun Biol. 2021 Feb 22;4(1):239 [PMID: 33619351]
  44. Nat Protoc. 2011 Apr;6(4):468-81 [PMID: 21412275]
  45. Biophys J. 2017 Oct 3;113(7):1395-1404 [PMID: 28978434]
  46. Nat Rev Genet. 2021 Apr;22(4):235-250 [PMID: 33244170]
  47. Nat Commun. 2020 Oct 16;11(1):5238 [PMID: 33067439]
  48. Genome Biol. 2014 Apr 30;15(5):R68 [PMID: 24887417]
  49. Epigenetics. 2016 Dec;11(12):881-888 [PMID: 27748645]
  50. Science. 2018 Sep 28;361(6409): [PMID: 30139913]
  51. Epigenetics. 2019 Dec;14(12):1141-1163 [PMID: 31284823]
  52. Genome Biol. 2020 Sep 4;21(1):221 [PMID: 32883324]
  53. Neuropsychopharmacology. 2013 Jan;38(1):23-38 [PMID: 22781841]
  54. F1000Res. 2016 Jun 23;5:1479 [PMID: 27429743]
  55. Sci Rep. 2018 Jul 4;8(1):10138 [PMID: 29973619]
  56. Nat Genet. 2003 Mar;33 Suppl:245-54 [PMID: 12610534]
  57. Nat Commun. 2021 Jan 15;12(1):400 [PMID: 33452255]
  58. BMC Bioinformatics. 2016 Nov 25;17(1):484 [PMID: 27884103]
  59. Nat Biotechnol. 2010 May;28(5):495-501 [PMID: 20436461]
  60. Genomics Proteomics Bioinformatics. 2018 Aug;16(4):234-243 [PMID: 30196115]
  61. Nat Rev Genet. 2001 Jan;2(1):21-32 [PMID: 11253064]
  62. Hum Mol Genet. 2015 Mar 15;24(6):1528-39 [PMID: 25381334]
  63. Bioinformatics. 2011 Jun 1;27(11):1571-2 [PMID: 21493656]
  64. Genome Biol. 2014 Sep 27;15(9):472 [PMID: 25260792]
  65. Nat Rev Genet. 2013 Mar;14(3):204-20 [PMID: 23400093]
  66. Genomics. 2020 Jan;112(1):144-150 [PMID: 31078719]
  67. Nat Rev Genet. 2012 Oct;13(10):705-19 [PMID: 22986265]
  68. Nat Genet. 2011 Jun 26;43(8):768-75 [PMID: 21706001]
  69. Nat Rev Genet. 2012 May 29;13(7):484-92 [PMID: 22641018]
  70. Genome Biol. 2014 Apr 01;15(4):r54 [PMID: 24690455]
  71. Nat Genet. 2017 May;49(5):719-729 [PMID: 28346445]
  72. Cancer Cell. 2014 Dec 8;26(6):813-825 [PMID: 25490447]
  73. Nucleic Acids Res. 2020 May 7;48(8):e46 [PMID: 32103242]
  74. Epigenetics Chromatin. 2013 Oct 11;6(1):33 [PMID: 24279302]
  75. Genome Res. 2010 Nov;20(11):1582-9 [PMID: 20841429]
  76. Epigenetics. 2017 Jan 2;12(1):41-54 [PMID: 27858532]
  77. Nat Protoc. 2017 Dec;12(12):2478-2492 [PMID: 29120462]
  78. Nucleic Acids Res. 2014 Feb;42(4):2235-44 [PMID: 24288373]

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