Letter | Published:

A Myc enhancer cluster regulates normal and leukaemic haematopoietic stem cell hierarchies

Nature volume 553, pages 515520 (25 January 2018) | Download Citation

  • A Correction to this article was published on 16 May 2018

This article has been updated


The transcription factor Myc is essential for the regulation of haematopoietic stem cells and progenitors and has a critical function in haematopoietic malignancies1. Here we show that an evolutionarily conserved region located 1.7 megabases downstream of the Myc gene that has previously been labelled as a ‘super-enhancer’2 is essential for the regulation of Myc expression levels in both normal haematopoietic and leukaemic stem cell hierarchies in mice and humans. Deletion of this region in mice leads to a complete loss of Myc expression in haematopoietic stem cells and progenitors. This caused an accumulation of differentiation-arrested multipotent progenitors and loss of myeloid and B cells, mimicking the phenotype caused by Mx1-Cre-mediated conditional deletion of the Myc gene in haematopoietic stem cells3. This super-enhancer comprises multiple enhancer modules with selective activity that recruits a compendium of transcription factors, including GFI1b, RUNX1 and MYB. Analysis of mice carrying deletions of individual enhancer modules suggests that specific Myc expression levels throughout most of the haematopoietic hierarchy are controlled by the combinatorial and additive activity of individual enhancer modules, which collectively function as a ‘blood enhancer cluster’ (BENC). We show that BENC is also essential for the maintenance of MLL–AF9-driven leukaemia in mice. Furthermore, a BENC module, which controls Myc expression in mouse haematopoietic stem cells and progenitors, shows increased chromatin accessibility in human acute myeloid leukaemia stem cells compared to blasts. This difference correlates with MYC expression and patient outcome. We propose that clusters of enhancers, such as BENC, form highly combinatorial systems that allow precise control of gene expression across normal cellular hierarchies and which also can be hijacked in malignancies.

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Change history

  • 16 May 2018

    In the originally published version of this Letter, the citation after 'TAMERE' in the Methods section should have been to a new reference (Herault et al., 1998; now ref. 49) rather than to ref. 43. This has been corrected online.


  1. 1.

    & Myc roles in hematopoiesis and leukemia. Genes Cancer 1, 605–616 (2010)

  2. 2.

    et al. Role of SWI/SNF in acute leukemia maintenance and enhancer-mediated Myc regulation. Genes Dev. 27, 2648–2662 (2013)

  3. 3.

    et al. c-Myc controls the balance between hematopoietic stem cell self-renewal and differentiation. Genes Dev. 18, 2747–2763 (2004)

  4. 4.

    et al. Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature 485, 376–380 (2012)

  5. 5.

    et al. Long-range enhancers regulating Myc expression are required for normal facial morphogenesis. Nat. Genet. 46, 753–758 (2014)

  6. 6.

    et al. A map of the cis-regulatory sequences in the mouse genome. Nature 488, 116–120 (2012)

  7. 7.

    The ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012)

  8. 8.

    et al. 8q24 prostate, breast, and colon cancer risk loci show tissue-specific long-range interaction with MYC. Proc. Natl Acad. Sci. USA 107, 9742–9746 (2010)

  9. 9.

    et al. A NOTCH1-driven MYC enhancer promotes T cell development, transformation and acute lymphoblastic leukemia. Nat. Med. 20, 1130–1137 (2014)

  10. 10.

    et al. Long-range enhancer activity determines Myc sensitivity to Notch inhibitors in T cell leukemia. Proc. Natl Acad. Sci. USA 111, E4946–E4953 (2014)

  11. 11.

    . et al. Mice lacking a Myc enhancer that includes human SNP rs6983267 are resistant to intestinal tumors. Science 338, 1360–1363 (2012)

  12. 12.

    et al. Identification of focally amplified lineage-specific super-enhancers in human epithelial cancers. Nat. Genet. 48, 176–182 (2016)

  13. 13.

    et al. Interactome maps of mouse gene regulatory domains reveal basic principles of transcriptional regulation. Cell 155, 1507–1520 (2013)

  14. 14.

    et al. Mapping long-range promoter contacts in human cells with high-resolution capture Hi-C. Nat. Genet. 47, 598–606 (2015)

  15. 15.

    et al. Transcriptional plasticity promotes primary and acquired resistance to BET inhibition. Nature 525, 543–547 (2015)

  16. 16.

    et al. Systematic mapping of functional enhancer–promoter connections with CRISPR interference. Science 354, 769–773 (2016)

  17. 17.

    et al. Identification of regulatory networks in HSCs and their immediate progeny via integrated proteome, transcriptome, and DNA methylome analysis. Cell Stem Cell 15, 507–522 (2014)

  18. 18.

    et al. c-Myc regulates mammalian body size by controlling cell number but not cell size. Nature 414, 768–773 (2001)

  19. 19.

    et al. c-Myc-mediated control of cell fate in megakaryocyte–erythrocyte progenitors. Blood 114, 2097–2106 (2009)

  20. 20.

    et al. Chromatin state dynamics during blood formation. Science 345, 943–949 (2014)

  21. 21.

    , & Transcriptional addiction in cancer. Cell 168, 629–643 (2017)

  22. 22.

    et al. Multiple loci are associated with white blood cell phenotypes. PLoS Genet. 7, e1002113 (2011)

  23. 23.

    et al. Identification of nine novel loci associated with white blood cell subtypes in a Japanese population. PLoS Genet. 7, e1002067 (2011)

  24. 24.

    et al. High-resolution genomic profiling of adult and pediatric core-binding factor acute myeloid leukemia reveals new recurrent genomic alterations. Blood 119, e67–e75 (2012)

  25. 25.

    et al. Genomic analysis reveals few genetic alterations in pediatric acute myeloid leukemia. Proc. Natl Acad. Sci. USA 106, 12944–12949 (2009)

  26. 26.

    et al. Stem cell gene expression programs influence clinical outcome in human leukemia. Nat. Med. 17, 1086–1093 (2011)

  27. 27.

    et al. A 17-gene stemness score for rapid determination of risk in acute leukaemia. Nature 540, 433–437 (2016)

  28. 28.

    et al. The transcriptional program of a human B cell line in response to Myc. Nucleic Acids Res. 29, 397–406 (2001)

  29. 29.

    et al. Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution. Nat. Genet. 48, 1193–1203 (2016)

  30. 30.

    et al. A regulatory archipelago controls Hox genes transcription in digits. Cell 147, 1132–1145 (2011)

  31. 31.

    , , & An integrated holo-enhancer unit defines tissue and gene specificity of the Fgf8 regulatory landscape. Dev. Cell 24, 530–542 (2013)

  32. 32.

    , , & Locus control regions. Blood 100, 3077–3086 (2002)

  33. 33.

    et al. DNA targeting specificity of RNA-guided Cas9 nucleases. Nat. Biotechnol. 31, 827–832 (2013)

  34. 34.

    et al. One-step generation of mice carrying mutations in multiple genes by CRISPR/Cas-mediated genome engineering. Cell 153, 910–918 (2013)

  35. 35.

    & Detection of LacZ expression by FACS-Gal analysis. Protoc. Exch. (2008)

  36. 36.

    et al. Transformation from committed progenitor to leukaemia stem cell initiated by MLL–AF9. Nature 442, 818–822 (2006)

  37. 37.

    & Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009)

  38. 38.

    et al. Model-based analysis of ChIP–seq (MACS). Genome Biol. 9, R137 (2008)

  39. 39.

    , , , & Mapping and quantifying mammalian transcriptomes by RNA-seq. Nat. Methods 5, 621–628 (2008)

  40. 40.

    & Modeling Survival Data: Extending the Cox Model (Springer, 2000)

  41. 41.

    , & lumi: a pipeline for processing Illumina microarray. Bioinformatics 24, 1547–1548 (2008)

  42. 42.

    et al. The transcriptional architecture of early human hematopoiesis identifies multilevel control of lymphoid commitment. Nat. Immunol. 14, 756–763 (2013)

  43. 43.

    et al. Densely interconnected transcriptional circuits control cell states in human hematopoiesis. Cell 144, 296–309 (2011)

  44. 44.

    et al. PERT: a method for expression deconvolution of human blood samples from varied microenvironmental and developmental conditions. PLOS Comput. Biol. 8, e1002838 (2012)

  45. 45.

    et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl Acad. Sci. USA 102, 15545–15550 (2005)

  46. 46.

    et al. The Molecular Signatures Database hallmark gene set collection. Cell Syst. 1, 417–425 (2015)

  47. 47.

    et al. A Myc network accounts for similarities between embryonic stem and cancer cell transcription programs. Cell 143, 313–324 (2010)

  48. 48.

    & The Immunological Genome Project: networks of gene expression in immune cells. Nat. Immunol. 9, 1091–1094 (2008)

  49. 49.

    , , & Engineering chromosomes in mice through targeted meiotic recombination (TAMERE). Nat. Genetics 20, 381–384 (1998)

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We thank members of the Spitz and Trumpp laboratories and colleagues for sharing reagents and helpful comments; A. Przybylla, M. Sohn and M. Neubauer for technical assistance; L. Alfaro and W. Zhang for sample preparation for RNA sequencing; M. Milsom for critical reading of the manuscript; R. Grosschedl and S. Boller for help with B cell development analysis; and the DKFZ Flow Cytometry Core facility and the EMBL and DKFZ Laboratory Animal Resource Facilities. Support was provided by PhD fellowships to V.V.U. (Jeff Schell Darwin Trust); M.P. (EMBL international PhD program), C.B. (Helmholtz International Graduate School for Cancer Research) and post-doctoral fellowship to S.R. (EMBL (EIPOD) under Marie Curie Actions COFUND). The J.E.D. and M.L. laboratories were supported in part by the Medicine by Design program (Toronto University), the Ontario Institute for Cancer Research, Cancer Stem Cell Consortium (OGI-047), the Canadian Institutes of Health Research and the CIHR-Japan Epigenetics in Stem Cells Program, Canadian Cancer Society, Terry Fox Foundation, and a Canada Research Chair to J.E.D. The A.T. laboratory was supported by the SFB 873 and FOR 2674 (Deutsche Forschungsgemeinschaft), the SyTASC consortium (Deutsche Krebshilfe) and the Dietmar Hopp Foundation.

Author information

Author notes

    • Peter W. Zandstra

    Present address: Michael Smith Laboratories, School of Biomedical Engineering, The University of British Columbia, #301 - 2185 East Mall, Vancouver, British Columbia V6T 1Z4, Canada.

    • Carsten Bahr
    • , Lisa von Paleske
    •  & Veli V. Uslu

    These authors contributed equally to this work.

    • Andreas Trumpp
    •  & François Spitz

    These authors jointly supervised this work.


  1. Division of Stem Cells and Cancer, German Cancer Research Center (DKFZ) and DKFZ-ZMBH Alliance, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany

    • Carsten Bahr
    • , Lisa von Paleske
    • , Roberta Scognamiglio
    • , Petra Zeisberger
    • , Amelie S. Benk
    •  & Andreas Trumpp
  2. Heidelberg Institute for Stem Cell Technology and Experimental Medicine (HI-STEM gGmbH), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany

    • Carsten Bahr
    • , Lisa von Paleske
    • , Roberta Scognamiglio
    • , Petra Zeisberger
    • , Amelie S. Benk
    •  & Andreas Trumpp
  3. Faculty of Biosciences, University of Heidelberg, 69120 Heidelberg, Germany

    • Carsten Bahr
    • , Lisa von Paleske
    • , Roberta Scognamiglio
    • , Amelie S. Benk
    •  & Andreas Trumpp
  4. Developmental Biology Unit, European Molecular Biology Laboratory (EMBL), 69117 Heidelberg, Germany

    • Veli V. Uslu
    • , Silvia Remeseiro
    • , Katja Langenfeld
    • , Massimo Petretich
    •  & François Spitz
  5. Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario M5G 2M9, Canada

    • Naoya Takayama
    • , Alex Murison
    • , Mathieu Lupien
    •  & John E. Dick
  6. Department of Molecular Genetics, University of Toronto, Toronto, Ontario M5G 1A1, Canada

    • Naoya Takayama
    •  & John E. Dick
  7. Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario M5G 1A1, Canada

    • Stanley W. Ng
    •  & Peter W. Zandstra
  8. Department of Medical Biophysics, University of Toronto, Toronto, Ontario M5G 2M9, Canada

    • Alex Murison
    •  & Mathieu Lupien
  9. Department of Immunology, Weizmann Institute of Science, Rehovot 76100, Israel

    • Ido Amit
  10. German Cancer Consortium (DKTK), 69120 Heidelberg, Germany

    • Andreas Trumpp
  11. Nationales Zentrum für Tumorerkrankungen (NCT), 69120 Heidelberg, Germany

    • Andreas Trumpp
  12. CNRS, UMR3738, 25 Rue du Dr Roux, 75015 Paris, France

    • François Spitz
  13. (Epi)genomics of Animal Development Unit, Developmental and Stem Cell Biology Department, Institut Pasteur, 75015 Paris, France

    • François Spitz


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C.B., L.v.P., V.V.U., A.T. and F.S. designed experiments. C.B., L.v.P., V.V.U., S.R., M.P., K.L., R.S., P.Z. and A.S.B. performed experiments related to mouse data. I.A. contributed to ChIP–seq analysis. A.M. and S.W.N. analysed RNA sequencing data, ATAC-seq and microarray data of patients with AML with conceptual input from C.B., M.L., J.E.D. and A.T. N.T. performed xenograft experiments. P.W.Z., M.L. and J.E.D. led and supervised the human studies. C.B., L.v.P., V.V.U., A.T. and F.S. analysed all other data. A.T. supervised and coordinated all haematopoiesis and leukaemia work as well as gene expression analyses. F.S. supervised the genetic strategies and gene regulation analyses. C.B., L.v.P, F.S. and A.T. wrote the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Andreas Trumpp or François Spitz.

Reviewer Information Nature thanks B. Amati and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Supplementary information

PDF files

  1. 1.

    Supplementary Figure 1

    This file contains the flow cytometric gating Strategies for hematopoietic cell populations (11 gating strategies).

  2. 2.

    Life Sciences Reporting Summary

Excel files

  1. 1.

    Supplementary Table 1

    A list of insertion and deletion mouse lines.

  2. 2.

    Supplementary Table 2

    The percentage of MLL-AF9-IRES-GFP positive cells in the peripheral blood of leukemia mice.

  3. 3.

    Supplementary Table 3

    AML patient characteristics.

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