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.

Mapping and analysis of chromatin state dynamics in nine human cell types

Abstract

Chromatin profiling has emerged as a powerful means of genome annotation and detection of regulatory activity. The approach is especially well suited to the characterization of non-coding portions of the genome, which critically contribute to cellular phenotypes yet remain largely uncharted. Here we map nine chromatin marks across nine cell types to systematically characterize regulatory elements, their cell-type specificities and their functional interactions. Focusing on cell-type-specific patterns of promoters and enhancers, we define multicell activity profiles for chromatin state, gene expression, regulatory motif enrichment and regulator expression. We use correlations between these profiles to link enhancers to putative target genes, and predict the cell-type-specific activators and repressors that modulate them. The resulting annotations and regulatory predictions have implications for the interpretation of genome-wide association studies. Top-scoring disease single nucleotide polymorphisms are frequently positioned within enhancer elements specifically active in relevant cell types, and in some cases affect a motif instance for a predicted regulator, thus suggesting a mechanism for the association. Our study presents a general framework for deciphering cis-regulatory connections and their roles in disease.

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: Chromatin state discovery and characterization.
Figure 2: Cell-type-specific promoter and enhancer states and associated functional enrichments.
Figure 3: Correlations in activity patterns link enhancers to gene targets and upstream regulators.
Figure 4: Validation of regulatory predictions by nucleosome depletions and enhancer activity.
Figure 5: Disease variants annotated by chromatin dynamics and regulatory predictions.

Similar content being viewed by others

Accession codes

Primary accessions

Gene Expression Omnibus

Data deposits

Sequencing and expression data has been deposited into the Gene Expression Omnibus under accession number GSE26386.

References

  1. Birney, E. et al. Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature 447, 799–816 (2007)

    Article  ADS  CAS  Google Scholar 

  2. Kim, H. D., Shay, T., O’Shea, E. K. & Regev, A. Transcriptional regulatory circuits: predicting numbers from alphabets. Science 325, 429–432 (2009)

    Article  ADS  CAS  Google Scholar 

  3. Barski, A. et al. High-resolution profiling of histone methylations in the human genome. Cell 129, 823–837 (2007)

    Article  CAS  Google Scholar 

  4. Mikkelsen, T. S. et al. Genome-wide maps of chromatin state in pluripotent and lineage-committed cells. Nature 448, 553–560 (2007)

    Article  ADS  CAS  Google Scholar 

  5. Guenther, M. G., Levine, S. S., Boyer, L. A., Jaenisch, R. & Young, R. A. A chromatin landmark and transcription initiation at most promoters in human cells. Cell 130, 77–88 (2007)

    Article  CAS  Google Scholar 

  6. Heintzman, N. D. et al. Distinct and predictive chromatin signatures of transcriptional promoters and enhancers in the human genome. Nature Genet. 39, 311–318 (2007)

    Article  CAS  Google Scholar 

  7. Hon, G., Wang, W. & Ren, B. Discovery and annotation of functional chromatin signatures in the human genome. PLOS Comput. Biol. 5, e1000566 (2009)

    Article  ADS  Google Scholar 

  8. Ernst, J. & Kellis, M. Discovery and characterization of chromatin states for systematic annotation of the human genome. Nature Biotechnol. 28, 817–825 (2010)

    Article  CAS  Google Scholar 

  9. Bernstein, B. E. et al. Genomic maps and comparative analysis of histone modifications in human and mouse. Cell 120, 169–181 (2005)

    Article  CAS  Google Scholar 

  10. Heintzman, N. D. et al. Histone modifications at human enhancers reflect global cell-type-specific gene expression. Nature 459, 108–112 (2009)

    Article  ADS  CAS  Google Scholar 

  11. Phillips, J. E. & Corces, V. G. CTCF: master weaver of the genome. Cell 137, 1194–1211 (2009)

    Article  Google Scholar 

  12. Hansen, R. S. et al. Sequencing newly replicated DNA reveals widespread plasticity in human replication timing. Proc. Natl Acad. Sci. USA 107, 139–144 (2010)

    Article  ADS  CAS  Google Scholar 

  13. Raha, D. et al. Close association of RNA polymerase II and many transcription factors with Pol III genes. Proc. Natl Acad. Sci. USA 107, 3639–3644 (2010)

    Article  ADS  CAS  Google Scholar 

  14. Kasowski, M. et al. Variation in transcription factor binding among humans. Science 328, 232–235 (2010)

    Article  ADS  CAS  Google Scholar 

  15. Guelen, L. et al. Domain organization of human chromosomes revealed by mapping of nuclear lamina interactions. Nature 453, 948–951 (2008)

    Article  ADS  CAS  Google Scholar 

  16. Jaenisch, R. & Young, R. Stem cells, the molecular circuitry of pluripotency and nuclear reprogramming. Cell 132, 567–582 (2008)

    Article  CAS  Google Scholar 

  17. De Santa, F. et al. A large fraction of extragenic RNA pol II transcription sites overlap enhancers. PLoS Biol. 8, e1000384 (2010)

    Article  Google Scholar 

  18. Kim, T. K. et al. Widespread transcription at neuronal activity-regulated enhancers. Nature 465, 182–187 (2010)

    Article  ADS  CAS  Google Scholar 

  19. Talbert, P. B. & Henikoff, S. Histone variants — ancient wrap artists of the epigenome. Nature Rev. Mol. Cell Biol. 11, 264–275 (2010)

    Article  CAS  Google Scholar 

  20. Schadt, E. E. et al. Mapping the genetic architecture of gene expression in human liver. PLoS Biol. 6, e107 (2008)

    Article  Google Scholar 

  21. Pickrell, J. K. et al. Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 464, 768–772 (2010)

    Article  ADS  CAS  Google Scholar 

  22. Montgomery, S. B. et al. Transcriptome genetics using second generation sequencing in a Caucasian population. Nature 464, 773–777 (2010)

    Article  ADS  CAS  Google Scholar 

  23. Veyrieras, J. B. et al. High-resolution mapping of expression-QTLs yields insight into human gene regulation. PLoS Genet. 4, e1000214 (2008)

    Article  Google Scholar 

  24. Kunarso, G. et al. Transposable elements have rewired the core regulatory network of human embryonic stem cells. Nature Genet. 42, 631–634 (2010)

    Article  CAS  Google Scholar 

  25. Fujiwara, T. et al. Discovering hematopoietic mechanisms through genome-wide analysis of GATA factor chromatin occupancy. Mol. Cell 36, 667–681 (2009)

    Article  CAS  Google Scholar 

  26. Lemaigre, F. & Zaret, K. S. Liver development update: new embryo models, cell lineage control, and morphogenesis. Curr. Opin. Genet. Dev. 14, 582–590 (2004)

    Article  CAS  Google Scholar 

  27. Sabourin, L. A. & Rudnicki, M. A. The molecular regulation of myogenesis. Clin. Genet. 57, 16–25 (2000)

    Article  CAS  Google Scholar 

  28. Bartel, F. O., Higuchi, T. & Spyropoulos, D. D. Mouse models in the study of the Ets family of transcription factors. Oncogene 19, 6443–6454 (2000)

    Article  CAS  Google Scholar 

  29. Law, J. C., Ritke, M. K., Yalowich, J. C., Leder, G. H. & Ferrell, R. E. Mutational inactivation of the p53 gene in the human erythroid leukemic K562 cell line. Leuk. Res. 17, 1045–1050 (1993)

    Article  CAS  Google Scholar 

  30. Forte, E. & Luftig, M. A. MDM2-dependent inhibition of p53 is required for Epstein-Barr virus B-cell growth transformation and infected-cell survival. J. Virol. 83, 2491–2499 (2009)

    Article  CAS  Google Scholar 

  31. Solozobova, V., Rolletschek, A. & Blattner, C. Nuclear accumulation and activation of p53 in embryonic stem cells after DNA damage. BMC Cell Biol. 10, 46 (2009)

    Article  Google Scholar 

  32. Cawley, S. et al. Unbiased mapping of transcription factor binding sites along human chromosomes 21 and 22 points to widespread regulation of noncoding RNAs. Cell 116, 499–509 (2004)

    Article  CAS  Google Scholar 

  33. Wei, C. L. et al. A global map of p53 transcription-factor binding sites in the human genome. Cell 124, 207–219 (2006)

    Article  CAS  Google Scholar 

  34. Hoshino, H. et al. Co-repressor SMRT and class II histone deacetylases promote Bach2 nuclear retention and formation of nuclear foci that are responsible for local transcriptional repression. J. Biochem. 141, 719–727 (2007)

    Article  CAS  Google Scholar 

  35. Vassen, L., Fiolka, K. & Moroy, T. Gfi1b alters histone methylation at target gene promoters and sites of gamma-satellite containing heterochromatin. EMBO J. 25, 2409–2419 (2006)

    Article  CAS  Google Scholar 

  36. He, H. H. et al. Nucleosome dynamics define transcriptional enhancers. Nature Genet. 42, 343–347 (2010)

    Article  CAS  Google Scholar 

  37. Hindorff, L. A. et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl Acad. Sci. USA 106, 9362–9367 (2009)

    Article  ADS  CAS  Google Scholar 

  38. Ganesh, S. K. et al. Multiple loci influence erythrocyte phenotypes in the CHARGE Consortium. Nature Genet. 41, 1191–1198 (2009)

    Article  CAS  Google Scholar 

  39. Han, J. W. et al. Genome-wide association study in a Chinese Han population identifies nine new susceptibility loci for systemic lupus erythematosus. Nature Genet. 41, 1234–1237 (2009)

    Article  CAS  Google Scholar 

  40. Kathiresan, S. et al. Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans. Nature Genet. 40, 189–197 (2008)

    Article  CAS  Google Scholar 

  41. Teslovich, T. M. et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466, 707–713 (2010)

    Article  ADS  CAS  Google Scholar 

  42. Houlston, R. S. et al. Meta-analysis of genome-wide association data identifies four new susceptibility loci for colorectal cancer. Nature Genet. 40, 1426–1435 (2008)

    Article  CAS  Google Scholar 

  43. Newton-Cheh, C. et al. Genome-wide association study identifies eight loci associated with blood pressure. Nature Genet. 41, 666–676 (2009)

    Article  CAS  Google Scholar 

  44. Stahl, E. A. et al. Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci. Nature Genet. 42, 508–514 (2010)

    Article  CAS  Google Scholar 

  45. Liu, X. et al. Genome-wide meta-analyses identify three loci associated with primary biliary cirrhosis. Nature Genet. 42, 658–660 (2010)

    Article  CAS  Google Scholar 

  46. Kamatani, Y. et al. Genome-wide association study of hematological and biochemical traits in a Japanese population. Nature Genet. 42, 210–215 (2010)

    Article  CAS  Google Scholar 

  47. Soranzo, N. et al. A genome-wide meta-analysis identifies 22 loci associated with eight hematological parameters in the HaemGen consortium. Nature Genet. 41, 1182–1190 (2009)

    Article  CAS  Google Scholar 

  48. Papaemmanuil, E. et al. Loci on 7p12.2, 10q21.2 and 14q11.2 are associated with risk of childhood acute lymphoblastic leukemia. Nature Genet. 41, 1006–1010 (2009)

    Article  CAS  Google Scholar 

  49. Visel, A., Rubin, E. M. & Pennacchio, L. A. Genomic views of distant-acting enhancers. Nature 461, 199–205 (2009)

    Article  ADS  CAS  Google Scholar 

  50. Naumova, N. & Dekker, J. Integrating one-dimensional and three-dimensional maps of genomes. J. Cell Sci. 123, 1979–1988 (2010)

    Article  CAS  Google Scholar 

  51. Ludwig, T. E. et al. Feeder-independent culture of human embryonic stem cells. Nature Methods 3, 637–646 (2006)

    Article  CAS  Google Scholar 

  52. Geiss, G. K. et al. Direct multiplexed measurement of gene expression with color-coded probe pairs. Nature Biotechnol. 26, 317–325 (2008)

    Article  CAS  Google Scholar 

  53. Reich, M. et al. GenePattern 2.0. Nature Genet. 38, 500–501 (2006)

    Article  CAS  Google Scholar 

  54. Kent, W. J. et al. The human genome browser at UCSC. Genome Res. 12, 996–1006 (2002)

    Article  CAS  Google Scholar 

  55. Pruitt, K. D., Tatusova, T. & Maglott, D. R. NCBI reference sequences (RefSeq): a curated non-redundant sequence database of genomes, transcripts and proteins. Nucleic Acids Res. 35, D61–D65 (2007)

    Article  CAS  Google Scholar 

  56. Siepel, A. et al. Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes. Genome Res. 15, 1034–1050 (2005)

    Article  CAS  Google Scholar 

  57. Ernst, J. & Bar-Joseph, Z. STEM: a tool for the analysis of short time series gene expression data. BMC Bioinformatics 7, 191 (2006)

    Article  Google Scholar 

  58. Ashburner, M. et al. Gene Ontology: tool for the unification of biology. Nature Genet. 25, 25–29 (2000)

    Article  CAS  Google Scholar 

  59. Matys, V. et al. TRANSFAC: transcriptional regulation, from patterns to profiles. Nucleic Acids Res. 31, 374–378 (2003)

    Article  CAS  Google Scholar 

  60. Sandelin, A., Alkema, W., Engstrom, P., Wasserman, W. W. & Lenhard, B. JASPAR: an open-access database for eukaryotic transcription factor binding profiles. Nucleic Acids Res. 32, D91–D94 (2004)

    Article  CAS  Google Scholar 

  61. Berger, M. F. et al. Variation in homeodomain DNA binding revealed by high-resolution analysis of sequence preferences. Cell 133, 1266–1276 (2008)

    Article  CAS  Google Scholar 

  62. Badis, G. et al. Diversity and complexity in DNA recognition by transcription factors. Science 324, 1720–1723 (2009)

    Article  ADS  CAS  Google Scholar 

  63. Berger, M. F. et al. Compact, universal DNA microarrays to comprehensively determine transcription-factor binding site specificities. Nature Biotechnol. 24, 1429–1435 (2006)

    Article  CAS  Google Scholar 

  64. Touzet, H. & Varre, J. S. Efficient and accurate P-value computation for Position Weight Matrices. Algorithms Mol. Biol. 2, 15 (2007)

    Article  Google Scholar 

  65. Bernstein, B. E. et al. A bivalent chromatin structure marks key developmental genes in embryonic stem cells. Cell 125, 315–326 (2006)

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We thank members of the epigenomics community at the Broad Institute and the Bernstein and Kellis laboratories, and M. Daly, D. Altshuler and E. Lander for discussions and criticisms. We also thank M. Suva, E. Mendenhall and S. Gillespie for assistance with experiments, and L. Goff and A. Chess for critical reading of the manuscript. We acknowledge the Broad Institute Genome Sequencing Platform for their expertise and assistance with data production. This research was supported by the National Human Genome Research Institute under an ENCODE grant (U54 HG004570; B.E.B.), R01 HG004037 (M. Kellis), RC1 HG005334 (M. Kellis), the Howard Hughes Medical Institute (B.E.B.), the National Science Foundation (awards 0644282 (M. Kellis) and 0905968 (J.E.)) and the Sloan Foundation (M. Kellis).

Author information

Authors and Affiliations

Authors

Contributions

J.E. conducted chromatin state analysis. J.E. and P.K. conducted regulatory motif analysis. J.E. and L.W. conducted GWAS SNP analysis. T.S.M., N.S. and T.D. implemented the ChIP-seq data processing pipeline. C.B.E., X.Z., L.W., R.I., M.C. and M. Ku developed the experimental pipeline and conducted experiments. M. Kellis designed and directed the computational analysis. B.E.B. designed the experimental approach and oversaw the work. J.E., M. Kellis and B.E.B. wrote the paper.

Corresponding author

Correspondence to Manolis Kellis.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Information

This file contains Supplementary Figures 1-19 with legends and additional references. (PDF 2664 kb)

Supplementary Data 1

This file contains the data for the Experimental Primers and Constructs. (XLS 35 kb)

PowerPoint slides

Rights and permissions

Reprints and permissions

About this article

Cite this article

Ernst, J., Kheradpour, P., Mikkelsen, T. et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 473, 43–49 (2011). https://doi.org/10.1038/nature09906

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nature09906

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

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