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.

  • Opinion
  • Published:

Associating cellular epigenetic models with human phenotypes

Abstract

Epigenetic association studies have been carried out to test the hypothesis that environmental perturbations trigger cellular reprogramming, with downstream effects on cellular function and phenotypes. There have now been numerous studies of the potential molecular mediators of epigenetic changes by epigenome-wide association studies (EWAS). However, a challenge for the field is the interpretation of the results obtained. We describe a second-generation EWAS approach, which focuses on the possible cellular models of epigenetic perturbations, studied by rigorous analysis and interpretation of genomic data. Thus refocused, epigenetics research aligns with the field of functional genomics to provide insights into environmental and genetic influences on phenotypic variation in humans.

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

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Figure 1: Epigenetic landscapes of cell reprogramming and cell-fate changes.
Figure 2: Preliminary data from scRNA-seq analysis.
Figure 3: Interpreting the results of a second-generation EWAS.

Similar content being viewed by others

References

  1. Feinberg, A. P. & Vogelstein, B. Hypomethylation distinguishes genes of some human cancers from their normal counterparts. Nature 301, 89–92 (1983).

    Article  CAS  PubMed  Google Scholar 

  2. Gama-Sosa, M. A. et al. The 5-methylcytosine content of DNA from human tumors. Nucleic Acids Res. 11, 6883–6894 (1983).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Greger, V., Passarge, E., Höpping, W., Messmer, E. & Horsthemke, B. Epigenetic changes may contribute to the formation and spontaneous regression of retinoblastoma. Hum. Genet. 83, 155–158 (1989).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  5. Riggs, A. D. X inactivation, differentiation, and DNA methylation. Cytogenet. Cell Genet. 14, 9–25 (1975).

    Article  CAS  PubMed  Google Scholar 

  6. Holliday, R. A new theory of carcinogenesis. Br. J. Cancer 40, 513–522 (1979).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Michels, K. B. et al. Recommendations for the design and analysis of epigenome-wide association studies. Nat. Methods 10, 949–955 (2013).

    Article  CAS  PubMed  Google Scholar 

  8. Birney, E., Smith, G. D. & Greally, J. M. Epigenome-wide association studies and the interpretation of disease-omics. PLOS Genet. 12, e1006105 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Rakyan, V. K., Down, T. A., Balding, D. J. & Beck, S. Epigenome-wide association studies for common human diseases. Nat. Rev. Genet. 12, 529–541 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Heijmans, B. T. & Mill, J. Commentary: the seven plagues of epigenetic epidemiology. Int. J. Epidemiol. 41, 74–78 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  11. Leek, J. T. et al. Tackling the widespread and critical impact of batch effects in high-throughput data. Nat. Rev. Genet. 11, 733–739 (2010).

    Article  CAS  PubMed  Google Scholar 

  12. Chen, Y. et al. Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics 8, 203–209 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Kraft, P., Zeggini, E. & Ioannidis, J. P. A. Replication in genome-wide association studies. Stat. Sci. 24, 561–573 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Houseman, E. A. et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics 13, 86 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Jaffe, A. E. & Irizarry, R. A. Accounting for cellular heterogeneity is critical in epigenome-wide association studies. Genome Biol. 15, R31 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Bell, J. T. et al. Epigenome-wide scans identify differentially methylated regions for age and age-related phenotypes in a healthy ageing population. PLOS Genet. 8, e1002629 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Grundberg, E. et al. Global analysis of DNA methylation variation in adipose tissue from twins reveals links to disease-associated variants in distal regulatory elements. Am. J. Hum. Genet. 93, 876–890 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Bell, J. T. et al. DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol. 12, R10 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Gertz, J. et al. Analysis of DNA methylation in a three-generation family reveals widespread genetic influence on epigenetic regulation. PLOS Genet. 7, e1002228 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Chen, L. et al. Genetic drivers of epigenetic and transcriptional variation in human immune cells. Cell 167, 1398–1414.e24 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Cheung, W. A. et al. Functional variation in allelic methylomes underscores a strong genetic contribution and reveals novel epigenetic alterations in the human epigenome. Genome Biol. 18, 50 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Banovich, N. E. et al. Methylation QTLs are associated with coordinated changes in transcription factor binding, histone modifications, and gene expression levels. PLOS Genet. 10, e1004663 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Gutierrez-Arcelus, M. et al. Passive and active DNA methylation and the interplay with genetic variation in gene regulation. eLife 2, e00523 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  24. Zhang, D. et al. Genetic control of individual differences in gene-specific methylation in human brain. Am. J. Hum. Genet. 86, 411–419 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Richmond, R. C. et al. DNA methylation and BMI: investigating identified methylation sites at HIF3A in a causal framework. Diabetes 65, 1231–1244 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Wahl, S. et al. Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature 541, 81–86 (2017).

    Article  CAS  PubMed  Google Scholar 

  27. Dekkers, K. F. et al. Blood lipids influence DNA methylation in circulating cells. Genome Biol. 17, 138 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  28. Zilberman, D., Gehring, M., Tran, R. K., Ballinger, T. & Henikoff, S. Genome-wide analysis of Arabidopsis thaliana DNA methylation uncovers an interdependence between methylation and transcription. Nat. Genet. 39, 61–69 (2007).

    Article  CAS  PubMed  Google Scholar 

  29. Ball, M. P. et al. Targeted and genome-scale strategies reveal gene-body methylation signatures in human cells. Nat. Biotechnol. 27, 361–368 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Pisco, A. O., d'Herouel, A. F. & Huang, S. Conceptual confusion: the case of epigenetics. Preprint at bioRxiv http://biorxiv.org/content/early/2016/05/12/053009 (2016).

    Google Scholar 

  31. Haig, D. Commentary: the epidemiology of epigenetics. Int. J. Epidemiol. 41, 13–16 (2012).

    Article  PubMed  Google Scholar 

  32. Gillman, M. W. et al. Meeting report on the 3rd International Congress on Developmental Origins of Health and Disease (DOHaD). Pediatr. Res. 61, 625–629 (2007).

    Article  PubMed  Google Scholar 

  33. Nanney, D. L. Epigenetic control systems. Proc. Natl Acad. Sci. USA 44, 712–717 (1958).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Wu, H., Hauser, R., Krawetz, S. A. & Pilsner, J. R. Environmental susceptibility of the sperm epigenome during windows of male germ cell development. Curr. Environ. Health Rep. 2, 356–366 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  35. Marsit, C. J. Influence of environmental exposure on human epigenetic regulation. J. Exp. Biol. 218, 71–79 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Perera, F. & Herbstman, J. Prenatal environmental exposures, epigenetics, and disease. Reprod. Toxicol. 31, 363–373 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Takahashi, K. & Yamanaka, S. Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors. Cell 126, 663–676 (2006).

    Article  CAS  PubMed  Google Scholar 

  38. Zong, J., Yao, X., Yin, J., Zhang, D. & Ma, H. Evolution of the RNA-dependent RNA polymerase (RdRP) genes: duplications and possible losses before and after the divergence of major eukaryotic groups. Gene 447, 29–39 (2009).

    Article  CAS  PubMed  Google Scholar 

  39. Holoch, D. & Moazed, D. RNA-mediated epigenetic regulation of gene expression. Nat. Rev. Genet. 16, 71–84 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Kaslow, D. C. & Migeon, B. R. DNA methylation stabilizes X chromosome inactivation in eutherians but not in marsupials: evidence for multistep maintenance of mammalian X dosage compensation. Proc. Natl Acad. Sci. USA 84, 6210–6214 (1987).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Sharp, A. J. et al. DNA methylation profiles of human active and inactive X chromosomes. Genome Res. 21, 1592–1600 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Li, E., Beard, C. & Jaenisch, R. Role for DNA methylation in genomic imprinting. Nature 366, 362–365 (1993).

    Article  CAS  PubMed  Google Scholar 

  43. Smith, N. C. & Matthews, J. M. Mechanisms of DNA-binding specificity and functional gene regulation by transcription factors. Curr. Opin. Struct. Biol. 38, 68–74 (2016).

    Article  CAS  PubMed  Google Scholar 

  44. Lelli, K. M., Slattery, M. & Mann, R. S. Disentangling the many layers of eukaryotic transcriptional regulation. Annu. Rev. Genet. 46, 43–68 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Alon, U. Network motifs: theory and experimental approaches. Nat. Rev. Genet. 8, 450–461 (2007).

    Article  CAS  PubMed  Google Scholar 

  46. Cheng, Y. et al. Principles of regulatory information conservation between mouse and human. Nature 515, 371–375 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Savic, D. et al. CETCh-seq: CRISPR epitope tagging ChIP-seq of DNA-binding proteins. Genome Res. 25, 1581–1589 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Feldmann, A. et al. Transcription factor occupancy can mediate active turnover of DNA methylation at regulatory regions. PLOS Genet. 9, e1003994 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Stadler, M. B. et al. DNA-binding factors shape the mouse methylome at distal regulatory regions. Nature 480, 490–495 (2011).

    Article  CAS  PubMed  Google Scholar 

  50. Domcke, S. et al. Competition between DNA methylation and transcription factors determines binding of NRF1. Nature 528, 575–579 (2015).

    Article  CAS  PubMed  Google Scholar 

  51. Li, X. et al. A maternal-zygotic effect gene, Zfp57, maintains both maternal and paternal imprints. Dev. Cell 15, 547–557 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Donohoe, M. E., Zhang, L.-F., Xu, N., Shi, Y. & Lee, J. T. Identification of a Ctcf cofactor, Yy1, for the X chromosome binary switch. Mol. Cell 25, 43–56 (2007).

    Article  CAS  PubMed  Google Scholar 

  53. Wang, J. et al. Imprinted X inactivation maintained by a mouse Polycomb group gene. Nat. Genet. 28, 371–375 (2001).

    Article  CAS  PubMed  Google Scholar 

  54. Schuettengruber, B., Chourrout, D., Vervoort, M., Leblanc, B. & Cavalli, G. Genome regulation by Polycomb and trithorax proteins. Cell 128, 735–745 (2007).

    Article  CAS  PubMed  Google Scholar 

  55. Grimaud, C., Nègre, N. & Cavalli, G. From genetics to epigenetics: the tale of Polycomb group and trithorax group genes. Chromosome Res. 14, 363–375 (2006).

    Article  CAS  PubMed  Google Scholar 

  56. Davis, F. P. & Eddy, S. R. Transcription factors that convert adult cell identity are differentially Polycomb repressed. PLOS ONE 8, e63407 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Orsi, G. A. et al. High-resolution mapping defines the cooperative architecture of Polycomb response elements. Genome Res. 24, 809–820 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Frey, F. et al. Molecular basis of PRC1 targeting to Polycomb response elements by PhoRC. Genes Dev. 30, 1116–1127 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Sipos, L., Kozma, G., Molnár, E. & Bender, W. In situ dissection of a Polycomb response element in Drosophila melanogaster. Proc. Natl Acad. Sci. USA 104, 12416–12421 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Kozma, G., Bender, W. & Sipos, L. Replacement of a Drosophila Polycomb response element core, and in situ analysis of its DNA motifs. Mol. Genet. Genomics 279, 595–603 (2008).

    Article  CAS  PubMed  Google Scholar 

  61. Busturia, A. et al. The MCP silencer of the Drosophila Abd-B gene requires both Pleiohomeotic and GAGA factor for the maintenance of repression. Development 128, 2163–2173 (2001).

    Article  CAS  PubMed  Google Scholar 

  62. Di Croce, L. & Helin, K. Transcriptional regulation by Polycomb group proteins. Nat. Struct. Mol. Biol. 20, 1147–1155 (2013).

    Article  CAS  PubMed  Google Scholar 

  63. Blackledge, N. P., Rose, N. R. & Klose, R. J. Targeting Polycomb systems to regulate gene expression: modifications to a complex story. Nat. Rev. Mol. Cell Biol. 16, 643–649 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Francis, N. J., Follmer, N. E., Simon, M. D., Aghia, G. & Butler, J. D. Polycomb proteins remain bound to chromatin and DNA during DNA replication in vitro. Cell 137, 110–122 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Anvar, Z. et al. ZFP57 recognizes multiple and closely spaced sequence motif variants to maintain repressive epigenetic marks in mouse embryonic stem cells. Nucleic Acids Res. 44, 1118–1132 (2016).

    Article  CAS  PubMed  Google Scholar 

  66. Guo, A. M., Sun, K., Su, X., Wang, H. & Sun, H. YY1TargetDB: an integral information resource for Yin Yang 1 target loci. Database (Oxford) 2013, bat007 (2013).

    Article  CAS  Google Scholar 

  67. Waddington, C. H. The Strategy of the Genes: a Discussion of Some Aspects of Theoretical Biology (Allen & Unwin, 1957).

    Google Scholar 

  68. Chen, F. et al. Prenatal retinoid deficiency leads to airway hyperresponsiveness in adult mice. J. Clin. Invest. 124, 801–811 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  69. Foong, R. E. et al. The effects of in utero vitamin D deficiency on airway smooth muscle mass and lung function. Am. J. Respir. Cell. Mol. Biol. 53, 664–675 (2015).

    Article  CAS  PubMed  Google Scholar 

  70. Lelièvre-Pégorier, M. et al. Mild vitamin A deficiency leads to inborn nephron deficit in the rat. Kidney Int. 54, 1455–1462 (1998).

    Article  PubMed  Google Scholar 

  71. Greally, J. M. & Jacobs, M. N. In vitro and in vivo testing methods of epigenomic endpoints for evaluating endocrine disruptors. ALTEX 30, 445–471 (2013).

    Article  PubMed  Google Scholar 

  72. Grün, F. et al. Endocrine-disrupting organotin compounds are potent inducers of adipogenesis in vertebrates. Mol. Endocrinol. 20, 2141–2155 (2006).

    Article  PubMed  CAS  Google Scholar 

  73. Kirchner, S., Kieu, T., Chow, C., Casey, S. & Blumberg, B. Prenatal exposure to the environmental obesogen tributyltin predisposes multipotent stem cells to become adipocytes. Mol. Endocrinol. 24, 526–539 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Woodsworth, D. J., Castellarin, M. & Holt, R. A. Sequence analysis of T cell repertoires in health and disease. Genome Med. 5, 98 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  75. Houseman, E. A., Molitor, J. & Marsit, C. J. Reference-free cell mixture adjustments in analysis of DNA methylation data. Bioinformatics 30, 1431–1439 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Zou, J., Lippert, C., Heckerman, D., Aryee, M. & Listgarten, J. Epigenome-wide association studies without the need for cell-type composition. Nat. Methods 11, 309–311 (2014).

    Article  CAS  PubMed  Google Scholar 

  77. Adalsteinsson, B. T. et al. Heterogeneity in white blood cells has potential to confound DNA methylation measurements. PLOS ONE 7, e46705 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Moris, N., Pina, C. & Arias, A. M. Transition states and cell fate decisions in epigenetic landscapes. Nat. Rev. Genet. 17, 693–703 (2016).

    Article  CAS  PubMed  Google Scholar 

  79. Paul, F. et al. Transcriptional heterogeneity and lineage commitment in myeloid progenitors. Cell 163, 1663–1677 (2015).

    Article  CAS  PubMed  Google Scholar 

  80. Jaitin, D. A. et al. Massively parallel single-cell RNA-seq for marker-free decomposition of tissues into cell types. Science 343, 776–779 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  81. Wijetunga, N. A. et al. The meta-epigenomic structure of purified human stem cell populations is defined at cis-regulatory sequences. Nat. Commun. 5, 5195 (2014).

    Article  CAS  PubMed  Google Scholar 

  82. Guo, H. et al. Single-cell methylome landscapes of mouse embryonic stem cells and early embryos analyzed using reduced representation bisulfite sequencing. Genome Res. 23, 2126–2135 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  83. Smallwood, S. A. et al. Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity. Nat. Methods 11, 817–820 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Satija, R., Farrell, J. A., Gennert, D., Schier, A. F. & Regev, A. Spatial reconstruction of single-cell gene expression data. Nat. Biotechnol. 33, 495–502 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Newman, A. M. et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods 12, 453–457 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. Zhao, M. et al. Distinct epigenomes in CD4+ T cells of newborns, middle-ages and centenarians. Sci. Rep. 6, 38411 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Qi, Q. et al. Diversity and clonal selection in the human T cell repertoire. Proc. Natl Acad. Sci. USA 111, 13139–13144 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Ulahannan, N. & Greally, J. M. Genome-wide assays that identify and quantify modified cytosines in human disease studies. Epigenetics Chromatin 8, 5 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Relton, C. L. & Davey Smith, G. Two-step epigenetic Mendelian randomization: a strategy for establishing the causal role of epigenetic processes in pathways to disease. Int. J. Epidemiol. 41, 161–176 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  91. Brem, R. B., Yvert, G., Clinton, R. & Kruglyak, L. Genetic dissection of transcriptional regulation in budding yeast. Science 296, 752–755 (2002).

    Article  CAS  PubMed  Google Scholar 

  92. Stranger, B. E. et al. Genome-wide associations of gene expression variation in humans. PLOS Genet. 1, e78 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  93. Morley, M. et al. Genetic analysis of genome-wide variation in human gene expression. Nature 430, 743–747 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Degner, J. F. et al. DNase I sensitivity QTLs are a major determinant of human expression variation. Nature 482, 390–394 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Pai, A. A., Pritchard, J. K. & Gilad, Y. The genetic and mechanistic basis for variation in gene regulation. PLOS Genet. 11, e1004857 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  96. Lappalainen, T. Functional genomics bridges the gap between quantitative genetics and molecular biology. Genome Res. 25, 1427–1431 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  97. Albert, F. W. & Kruglyak, L. The role of regulatory variation in complex traits and disease. Nat. Rev. Genet. 16, 197–212 (2015).

    Article  CAS  PubMed  Google Scholar 

  98. Waddington, C. H. The epigenotype. 1942. Int. J. Epidemiol. 41, 10–13 (2012).

    Article  CAS  PubMed  Google Scholar 

  99. Waddington, C. H. Organisers and Genes (Cambridge Univ. Press, 1940).

    Google Scholar 

  100. Li, Y. & Sasaki, H. Genomic imprinting in mammals: its life cycle, molecular mechanisms and reprogramming. Cell Res. 21, 466–473 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Gendrel, A.-V. & Heard, E. Noncoding RNAs and epigenetic mechanisms during X-chromosome inactivation. Annu. Rev. Cell Dev. Biol. 30, 561–580 (2014).

    Article  CAS  PubMed  Google Scholar 

  102. Bonasio, R., Tu, S. & Reinberg, D. Molecular signals of epigenetic states. Science 330, 612–616 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank S. Henikoff for sharing his insights and acknowledge his creation of the useful term epi+genetics, as well as R. Satija for advice in single-cell RNA sequencing data analysis.

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Tuuli Lappalainen or John M. Greally.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Related links

PowerPoint slides

Glossary

Canalization

The maintenance of a cell and its progeny within a differentiation lineage. The term refers to the canal-like structures depicted by Waddington in his epigenetic landscape, which he described not as canals but as creodes, a neologism from biblical Greek words meaning 'necessary' and 'path'.

Epigenetic

We define an epigenetic property as that of a cell, mediated by genomic regulators, conferring on the cell the ability to remember a past event.

Epigenome-wide association studies

(EWAS). Studies of the epigenome for nonrandom association of a difference in organization of a genomic regulator, comparing individuals with a phenotype with individuals lacking the phenotype. The epigenome is itself defined as the genome-wide distribution of transcriptional regulators believed to mediate the memory of past cellular events.

Genome-wide association study

(GWAS). A study that looks for association between genetic variation and a high-level trait such as disease or biomarker across individuals, typically scanning millions of genetic variants genome-wide for association signals.

Polycreodism

A systematic variability of cell fate decisions to create a distinctive repertoire of cells in a tissue.

Quantitative trait loci

(QTLs). Loci in the genome at which genetic variation is associated with molecular variation across individuals. For example, individuals with a particular single nucleotide variant have altered expression levels of a gene (eQTL), altered DNA methylation (meQTL; also known as mQTL) or altered chromatin state (chromQTL).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lappalainen, T., Greally, J. Associating cellular epigenetic models with human phenotypes. Nat Rev Genet 18, 441–451 (2017). https://doi.org/10.1038/nrg.2017.32

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrg.2017.32

This article is cited by

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