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Chromatin accessibility pre-determines glucocorticoid receptor binding patterns

Nature Genetics volume 43, pages 264–268 (2011)Cite this article

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Abstract

Development, differentiation and response to environmental stimuli are characterized by sequential changes in cellular state initiated by the de novo binding of regulated transcriptional factors to their cognate genomic sites1,2,3. The mechanism whereby a given regulatory factor selects a limited number of in vivo targets from a myriad of potential genomic binding sites is undetermined. Here we show that up to 95% of de novo genomic binding by the glucocorticoid receptor4, a paradigmatic ligand-activated transcription factor, is targeted to preexisting foci of accessible chromatin. Factor binding invariably potentiates chromatin accessibility. Cell-selective glucocorticoid receptor occupancy patterns appear to be comprehensively predetermined by cell-specific differences in baseline chromatin accessibility patterns, with secondary contributions from local sequence features. The results define a framework for understanding regulatory factor–genome interactions and provide a molecular basis for the tissue selectivity of steroid pharmaceuticals and other agents that intersect the living genome.

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Figure 1: Dominant effect of chromatin accessibility on glucocorticoid receptor occupancy patterns.
Figure 2: The quantitative effect of chromatin context on glucocorticoid receptor occupancy of GRBEs.
Figure 3: Cell-specific chromatin landscapes determine cell-selective glucocorticoid receptor occupancy.
Figure 4: Regulatory motifs in glucocorticoid receptor–occupied regions differ substantially between cell types.

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Gene Expression Omnibus

Sequence Read Archive

References

  1. Britten, R.J. & Davidson, E.H. Gene regulation for higher cells: a theory. Science 165, 349–357 (1969).

    Article  CAS  Google Scholar 

  2. McKenna, N.J. & O'Malley, B.W. Combinatorial control of gene expression by nuclear receptors and coregulators. Cell 108, 465–474 (2002).

    Article  CAS  Google Scholar 

  3. Okita, K., Ichisaka, T. & Yamanaka, S. Generation of germline-competent induced pluripotent stem cells. Nature 448, 313–317 (2007).

    Article  CAS  Google Scholar 

  4. Evans, R.M. The steroid and thyroid hormone receptor superfamily. Science 240, 889–895 (1988).

    Article  CAS  Google Scholar 

  5. Felsenfeld, G. & Groudine, M. Controlling the double helix. Nature 421, 448–453 (2003).

    Article  Google Scholar 

  6. Wu, C. The 5′ ends of Drosophila heat shock genes in chromatin are hypersensitive to DNase I. Nature 286, 854–860 (1980).

    Article  CAS  Google Scholar 

  7. Gross, D.S. & Garrard, W.T. Nuclease hypersensitive sites in chromatin. Annu. Rev. Biochem. 57, 159–197 (1988).

    Article  CAS  Google Scholar 

  8. Htun, H., Barsony, J., Renyi, I., Gould, D.L. & Hager, G.L. Visualization of glucocorticoid receptor translocation and intranuclear organization in living cells with a green fluorescent protein chimera. Proc. Natl. Acad. Sci. USA 93, 4845–4850 (1996).

    Article  CAS  Google Scholar 

  9. So, A.Y.-L., Chaivorapol, C., Bolton, E.C., Li, H. & Yamamoto, K.R. Determinants of cell- and gene-specific transcriptional regulation by the glucocorticoid receptor. PLoS Genet. 3, e94 (2007).

    Article  Google Scholar 

  10. Reddy, T.E. et al. Genomic determination of the glucocorticoid response reveals unexpected mechanisms of gene regulation. Genome Res. 19, 2163–2171 (2009).

    Article  CAS  Google Scholar 

  11. Richard-Foy, H. & Hager, G.L. Sequence-specific positioning of nucleosomes over the steroid-inducible MMTV promoter. EMBO J. 6, 2321–2328 (1987).

    Article  CAS  Google Scholar 

  12. Becker, P., Renkawitz, R. & Schütz, G. Tissue-specific DNaseI hypersensitive sites in the 5′-flanking sequences of the tryptophan oxygenase and the tyrosine aminotransferase genes. EMBO J. 3, 2015–2020 (1984).

    Article  CAS  Google Scholar 

  13. Hager, G.L. et al. Influence of chromatin structure on the binding of transcription factors to DNA. Cold Spring Harb. Symp. Quant. Biol. 58, 63–71 (1993).

    Article  CAS  Google Scholar 

  14. Hesselberth, J.R. et al. Global mapping of protein-DNA interactions in vivo by digital genomic footprinting. Nat. Methods 6, 283–289 (2009).

    Article  CAS  Google Scholar 

  15. Sekimata, M. et al. CCCTC-binding factor and the transcription factor T-bet orchestrate T helper 1 cell-specific structure and function at the interferon-gamma locus. Immunity 31, 551–564 (2009).

    Article  CAS  Google Scholar 

  16. Robertson, G. et al. Genome-wide profiles of STAT1 DNA association using chromatin immunoprecipitation and massively parallel sequencing. Nat. Methods 4, 651–657 (2007).

    Article  CAS  Google Scholar 

  17. Johnson, D.S., Mortazavi, A., Myers, R.M. & Wold, B. Genome-wide mapping of in vivo protein-DNA interactions. Science 316, 1497–1502 (2007).

    Article  CAS  Google Scholar 

  18. Stalder, J. et al. Tissue-specific DNA cleavages in the globin chromatin domain introduced by DNAase I. Cell 20, 451–460 (1980).

    Article  CAS  Google Scholar 

  19. von der Ahe, D. et al. Glucocorticoid and progesterone receptors bind to the same sites in two hormonally regulated promoters. Nature 313, 706–709 (1985).

    Article  CAS  Google Scholar 

  20. Diamond, M.I., Miner, J.N., Yoshinaga, S.K. & Yamamoto, K.R. Transcription factor interactions: selectors of positive or negative regulation from a single DNA element. Science 249, 1266–1272 (1990).

    Article  CAS  Google Scholar 

  21. Bailey, T.L. & Gribskov, M. Concerning the accuracy of MAST E-values. Bioinformatics 16, 488–489 (2000).

    Article  CAS  Google Scholar 

  22. Beck, I.M.E. et al. Crosstalk in inflammation: the interplay of glucocorticoid receptor-based mechanisms and kinases and phosphatases. Endocr. Rev. 30, 830–882 (2009).

    Article  CAS  Google Scholar 

  23. Rigaud, G., Roux, J., Pictet, R. & Grange, T. In vivo footprinting of rat TAT gene: dynamic interplay between the glucocorticoid receptor and a liver-specific factor. Cell 67, 977–986 (1991).

    Article  CAS  Google Scholar 

  24. Cordingley, M.G. & Hager, G.L. Binding of multiple factors to the MMTV promoter in crude and fractionated nuclear extracts. Nucleic Acids Res. 16, 609–628 (1988).

    Article  CAS  Google Scholar 

  25. 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  Google Scholar 

  26. John, S. et al. Kinetic complexity of the global response to glucocorticoid receptor action. Endocrinology 150, 1766–1774 (2009).

    Article  CAS  Google Scholar 

  27. John, S. et al. Interaction of the glucocorticoid receptor with the chromatin landscape. Mol. Cell 29, 611–624 (2008).

    Article  CAS  Google Scholar 

  28. Sekimata, M. et al. CCCTC-binding factor and the transcription factor T-bet orchestrate T helper 1 cell-specific structure and function at the interferon-gamma locus. Immunity 31, 551–564 (2009).

    Article  CAS  Google Scholar 

  29. Sabo, P.J. et al. Genome-scale mapping of DNase I sensitivity in vivo using tiling DNA microarrays. Nat. Methods 3, 511–518 (2006).

    Article  CAS  Google Scholar 

  30. Hesselberth, J.R. et al. Global mapping of protein-DNA interactions in vivo by digital genomic footprinting. Nat. Methods 6, 283–289 (2009).

    Article  CAS  Google Scholar 

  31. Sabo, P.J. et al. Discovery of functional noncoding elements by digital analysis of chromatin structure. Proc. Natl. Acad. Sci. USA 101, 16837–16842 (2004).

    Article  CAS  Google Scholar 

  32. Bailey, T.L., Williams, N., Misleh, C. & Li, W.W. MEME: discovering and analyzing DNA and protein sequence motifs. Nucleic Acids Res. 34, W369–W373 (2006).

    Article  CAS  Google Scholar 

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Acknowledgements

We would like to thank T. Miranda, S. Morris, K. Nalley and L. Grontved for critical reading of the manuscript. We also thank M. Weaver, K. Lee, F. Neri, D. Bates and M. Diegel for technical assistance with the DNase I library preparation and sequencing. This research was supported in part by the Intramural Research Program of the US NIH, National Cancer Institute, Center for Cancer Research and funding from US NIH grant 1RC2HG005654 to J.A.S.

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Authors and Affiliations

  1. Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, National Institutes of Health (NIH), Bethesda, Maryland, USA

    Sam John, Myong-Hee Sung, Simon C Biddie, Thomas A Johnson & Gordon L Hager

  2. Department of Genome Sciences, University of Washington, Seattle, Washington, USA

    Peter J Sabo, Robert E Thurman & John A Stamatoyannopoulos

  3. Department of Medicine, Division of Oncology, University of Washington, Seattle Cancer Care Alliance, Seattle, Washington, USA

    John A Stamatoyannopoulos

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  1. Sam John
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Contributions

S.J., P.J.S., G.L.H. and J.A.S. designed the experiments. S.J., P.J.S., S.C.B. and T.A.J. conducted the DNase-seq, ChIP-seq and expression array experiments. S.J., P.J.S., R.E.T., M.-H.S. and J.A.S. analyzed the data. S.J., P.J.S., R.E.T., M.-H.S., G.L.H. and J.A.S. wrote the manuscript.

Corresponding authors

Correspondence to Gordon L Hager or John A Stamatoyannopoulos.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Note, Supplementary Figures 1–10 (PDF 6921 kb)

Supplementary Table 1

DNaseI sensitive regions in the baseline (pre-hormone) state in the murine mammary adenocarcinoma cell line, 3134; DNase I sensitive regions in post dexamethasone-treated 3134 cells (XLS 3781 kb)

Supplementary Table 2

DNaseI hypersensitive sites (DHSs) in the baseline (pre-hormone) state in the murine mammary adenocarcinoma cell line, 3134 (XLS 3781 kb)

Supplementary Table 3

DNaseI hypersensitive sites (DHSs) in post dexamethasone-treated 3134 cells (XLS 3781 kb)

Supplementary Table 4

GR occupancy sites in the murine mammary adenocarcinoma cell line, 3134 (FDR 0%) (XLS 489 kb)

Supplementary Table 5

Expression analysis of mammary (3134) and pituitary (AtT-20) cells (XLS 132 kb)

Supplementary Table 6

GRBE sequence classes with greater than 50 instances in the genome. Chromatin Context Coefficient (CCC) classes in the murine genome (XLS 302 kb)

Supplementary Table 7

DNaseI sensitive regions in the baseline (pre-hormone) state in the murine pituitary cell line, AtT-20; DNase I sensitive regions in the post-hormone state in the murine pituitary cell line, AtT-20 (XLS 3781 kb)

Supplementary Table 8

DNaseI hypersensitive sites (DHSs) in the baseline (pre-hormone) state in the murine pituitary cell line, AtT-20 (XLS 3781 kb)

Supplementary Table 9

DNaseI hypersensitive sites (DHSs) post-hormone in AtT-20 cells (XLS 3781 kb)

Supplementary Table 10

GR occupancy sites in the murine pituitary cell line, AtT-20 (FDR 0%) (XLS 202 kb)

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John, S., Sabo, P., Thurman, R. et al. Chromatin accessibility pre-determines glucocorticoid receptor binding patterns. Nat Genet 43, 264–268 (2011). https://doi.org/10.1038/ng.759

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