The meta-epigenomic structure of purified human stem cell populations is defined at cis-regulatory sequences

Nature Communications

Volumn 5, Issue , 2014, Pages

  Wijetunga, N Ari ^a   Delahaye, Fabien ^a   Zhao, Yong M ^a   Golden, Aaron ^a   Mar, Jessica C ^a   Einstein, Francine H ^a   Greally, John M ^a  

^a ALBERT EINSTEIN COLLEGE OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CELLS AND CELL COMPONENTS; DATA ACQUISITION; DNA; GENE EXPRESSION; GENOMICS; HETEROGENEITY; METHYLATION; SUBPOPULATION;

ARTICLE; CD34 SELECTION; CELL DIFFERENTIATION; CELL POPULATION; CELL SUBPOPULATION; CPG ISLAND; DNA METHYLATION; ENHANCER REGION; EPIGENETICS; GENE EXPRESSION; GENE LOCUS; GENETIC VARIABILITY; HEMATOPOIETIC STEM CELL; HUMAN; HUMAN CELL; LEUKOCYTE; MOLECULAR MECHANICS; PROMOTER REGION; REGULATORY SEQUENCE; ALGORITHM; CELL LINEAGE; CHEMISTRY; CHROMATIN; CHROMOSOMAL MAPPING; CYTOLOGY; DNA SEQUENCE; GENE EXPRESSION PROFILING; GENETIC EPIGENESIS; GENETIC POLYMORPHISM; METABOLISM; STEM CELL;

CD34 ANTIGEN; CHROMATIN; HISTONE;

ALGORITHMS; ANTIGENS, CD34; CELL DIFFERENTIATION; CELL LINEAGE; CHROMATIN; CHROMOSOME MAPPING; CPG ISLANDS; DNA METHYLATION; EPIGENESIS, GENETIC; EPIGENOMICS; GENE EXPRESSION PROFILING; HEMATOPOIETIC STEM CELLS; HISTONES; HUMANS; LEUKOCYTES; POLYMORPHISM, GENETIC; SEQUENCE ANALYSIS, DNA; STEM CELLS;

EID: 84923358136     PISSN: None     EISSN: 20411723     Source Type: Journal    
DOI: 10.1038/ncomms6195     Document Type: Article

References (49)

1. Shen, Y. et al. A map of the cis-regulatory sequences in the mouse genome. Nature 488, 116-120 (2012).
2. Varley, K. E. et al. Dynamic DNA methylation across diverse human cell lines and tissues. Genome Res. 23, 555-567 (2013).
3. Satterlee, J. S., Schubeler, D. & Ng, H. H. Tackling the epigenome: challenges and opportunities for collaboration. Nat. Biotechnol. 28, 1039-1044 (2010).
4. Bell, J. T. & Spector, T. D. A twin approach to unraveling epigenetics. Trends Genet. 27, 116-125 (2011).
5. 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).
6. Verma, M. Epigenome-Wide Association Studies (EWAS) in Cancer. Curr. Genomics 13, 308-313 (2012).
7. Flanagan, J. M. et al. Intra-and interindividual epigenetic variation in human germ cells. Am. J. Hum. Genet. 79, 67-84 (2006).
8. Feinberg, A. P. & Irizarry, R. A. Evolution in health and medicine Sackler colloquium: stochastic epigenetic variation as a driving force of development, evolutionary adaptation, and disease. Proc. Natl Acad. Sci. USA 107(Suppl 1): 1757-1764 (2010).
9. Talens, R. P. et al. Variation, patterns, and temporal stability of DNA methylation: considerations for epigenetic epidemiology. FASEB J. 24, 3135-3144 (2010).
10. Bell, J. T. et al. DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines. Genome Biol. 12, R10 (2011).
11. Teschendorff, A. E. et al. Epigenetic variability in cells of normal cytology is associated with the risk of future morphological transformation. Genome Med. 4, 24 (2012).
12. Gemma, C. et al. Inactive or moderately active human promoters are enriched for inter-individual epialleles. Genome Biol. 14, R43 (2013).
13. Gutierrez-Arcelus, M. et al. Passive and active DNA methylation and the interplay with genetic variation in gene regulation. eLife 2, e00523 (2013).
14. Vaughn, M. W. et al. Epigenetic natural variation in Arabidopsis thaliana. PLoS Biol. 5, e174 (2007).
15. Schmitz, R. J. & Ecker, J. R. Epigenetic and epigenomic variation in Arabidopsis thaliana. Trends Plant Sci. 17, 149-154 (2012).
16. Landan, G. et al. Epigenetic polymorphism and the stochastic formation of differentially methylated regions in normal and cancerous tissues. Nat. Genet. 44, 1207-1214 (2012).
17. Wang, J. et al. Dual DNA methylation patterns in the CNS reveal developmentally poised chromatin and monoallelic expression of critical genes. PLoS ONE 5, e13843 (2010).
18. Jeffries, A. R. et al. Stochastic choice of allelic expression in human neural stem cells. Stem Cells 30, 1938-1947 (2012).
19. Teng, M. et al. The influence of cis-regulatory elements on DNA methylation fidelity. PLoS ONE 7, e32928 (2012).
20. Gervin, K. et al. Extensive variation and low heritability of DNA methylation identified in a twin study. Genome Res. 21, 1813-1821 (2011).
21. Li, C. C. et al. A sustained dietary change increases epigenetic variation in isogenic mice. PLoS Genet. 7, e1001380 (2011).
22. Houseman, E. A. et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics 13, 86 (2012).
23. Meissner, A. et al. Genome-scale DNA methylation maps of pluripotent and differentiated cells. Nature 454, 766-770 (2008).
24. Suzuki, M. et al. Optimized design and data analysis of tag-based cytosine methylation assays. Genome Biol. 11, R36 (2010).
25. Bocker, M. T. et al. Genome-wide promoter DNA methylation dynamics of human hematopoietic progenitor cells during differentiation and aging. Blood 117, e182-e189 (2011).
26. Duncan, B. K. & Miller, J. H. Mutagenic deamination of cytosine residues in DNA. Nature 287, 560-561 (1980).
27. 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).
28. Hoffman, M. M. et al. Unsupervised pattern discovery in human chromatin structure through genomic segmentation. Nat. Methods 9, 473-476 (2012).
29. Zhu, Q., Song, Z., Xie, Y. & Wang, L. A novel recursive Bayesian learning-based method for the efficient and accurate segmentation of video with dynamic background. IEEE Transact. Image Process. 21, 3865-3876 (2012).
30. Kohonen, T. Self-Organizing Maps (Springer-Verlag New York, Inc, 2001).
31. 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).
32. Ernst, J. & Kellis, M. ChromHMM: automating chromatin-state discovery and characterization. Nat. Methods 9, 215-216 (2012).
33. Stella, C. C. et al. CD34-positive cells: biology and clinical relevance. Haematologica 80, 367-387 (1995).
34. Gaujoux, R. & Seoighe, C. A flexible R package for nonnegative matrix factorization. BMC Bioinformatics 11, 367 (2010).
35. Gaujoux, R. & Seoighe, C. Semi-supervised nonnegative matrix factorization for gene expression deconvolution: a case study. Infect. Genet. Evol. 12, 913-921 (2012).
36. Rada-Iglesias, A. et al. A unique chromatin signature uncovers early developmental enhancers in humans. Nature 470, 279-283 (2011).
37. Zentner, G. E., Tesar, P. J. & Scacheri, P. C. Epigenetic signatures distinguish multiple classes of enhancers with distinct cellular functions. Genome Res. 21, 1273-1283 (2011).
38. Creyghton, M. P. et al. Histone H3K27ac separates active from poised enhancers and predicts developmental state. Proc. Natl Acad. Sci. USA 107, 21931-21936 (2010).
39. Bernstein, B. E. et al. A bivalent chromatin structure marks key developmental genes in embryonic stem cells. Cell 125, 315-326 (2006).
40. Perisic, T., Holsboer, F., Rein, T. & Zschocke, J. The CpG island shore of the GLT-1 gene acts as a methylation-sensitive enhancer. Glia 60, 1345-1355 (2012).
41. 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).
42. 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).
43. Pujadas, E. & Feinberg, A. P. Regulated noise in the epigenetic landscape of development and disease. Cell 148, 1123-1131 (2012).
44. Hansen, K. D. et al. Increased methylation variation in epigenetic domains across cancer types. Nat. Genet. 43, 768-775 (2011).
45. Koestler, D. C. et al. Blood-based profiles of DNA methylation predict the underlying distribution of cell types: a validation analysis. Epigenetics 8, 816-826 (2013).
46. Koestler, D. C., Christensen, B. C., Marsit, C. J., Kelsey, K. T. & Houseman, E. A. Recursively partitioned mixture model clustering of DNA methylation data using biologically informed correlation structures. Stat. Appl. Genet. Mol. Biol. 12, 225-240 (2013).
47. Liu, Y. et al. Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nat. Biotechnol. 31, 142-147 (2013).
48. Montano, C. M. et al. Measuring cell-type specific differential methylation in human brain tissue. Genome Biol. 14, R94 (2013).
49. Jaffe, A. E. et al. Bump hunting to identify differentially methylated regions in epigenetic epidemiology studies. Int. J. Epidemiol. 41, 200-209 (2012).