Search Posts

Epigenomet kortlagt


Map of the human epigenome completed Date:November 17, 2016Source:CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences
Shedding light on how the body regulates which genes are active in which cells.
Over the last five years, a worldwide consortium of scientists has established epigenetic maps of 2,100 cell types.

external image 161117150743_1_540x360.jpg
This is a methylated DNA molecule. DNA methylation plays an important role for epigenetic gene regulation in development and cancer.
Credit: Christoph Bock/CeMM

Within this coordinated effort, the CeMM Research Center for Molecular Medicine contributed detailed DNA methylation maps of the developing blood,

opening up new perspectives for the understanding and treatment of leukemia and immune diseases.

One of the great mysteries in biology is how the many different cell types that make up our bodies are derived from a single cell and from one DNA sequence, or genome.

The identity of each cell type is largely defined by an instructive layer of molecular annotations on top of the genome — the epigenome — which acts as a blueprint unique to each cell type and developmental stage.

The epigenome changes as cells develop and in response to changes in the environment.

Defects in the factors that read, write, and erase the epigenetic blueprint are involved in many diseases.

Analysis of the epigenomes of healthy and abnormal cells will facilitate new ways to diagnose and treat various diseases, and ultimately lead to improved health outcomes.

A collection of 41 coordinated papers now published by scientists from across the International Human Epigenome Consortium (IHEC) sheds light on these processes, taking global research in the field of epigenomics a major step forward.

The latest study from Christoph Bock's team, published today in the journal Cell Stem Cell, charts the epigenetic landscape of DNA methylation in human blood.

This study highlights the dynamic nature of the epigenome in the development of human blood.

Our body produces billions of blood cells every day, which develop from a few thousand stem cells at the top of a complex hierarchy of blood cells.

Using the latest sequencing and epigenome mapping technology the scientists unraveled a blueprint of blood development that is encoded in the DNA methylation patterns of blood stem cells and their differentiating progeny.

As the stem cells differentiate, they pick one of several epigenetically defined routes and follow it, eventually arriving at one specialized cell type.

Researchers are seeking to utilize epigenetic information for medicine. For instance, certain routes of differentiation are jammed in leukemia, such that cells can no longer reach their destination and take wrong turns instead.

Surveillance of those cells by epigenetic tests can contribute to a more precise diagnosis of leukemia — clinical tests of this approach are ongoing.

This is relevant to cancer diagnostics and personalized medicine,

it provides a compass for future efforts aiming to reprogram the epigenome of individual cells, for example by erasing critical epigenetic alterations from leukemia cells.

Journal Reference:

  1. Matthias Farlik, Florian Halbritter, Fabian Müller, Fizzah A. Choudry, Peter Ebert, Johanna Klughammer, Samantha Farrow, Antonella Santoro, Valerio Ciaurro, Anthony Mathur, Rakesh Uppal, Hendrik G. Stunnenberg, Willem H. Ouwehand, Elisa Laurenti, Thomas Lengauer, Mattia Frontini, Christoph Bock. DNA Methylation Dynamics of Human Hematopoietic Stem Cell Differentiation. Cell Stem Cell, 2016; DOI: 10.1016/j.stem.2016.10.019 =


Methylation differs in HSCs from fetal liver, bone marrow, cord, and peripheral blood

Myeloid and lymphoid progenitors are distinguished by enhancer-linked DNA methylation

Machine learning enables data-driven reconstruction of the hematopoietic lineage

Hematopoietic stem cells give rise to all blood cells in a differentiation process that involves widespread epigenome remodeling.

Scientists present genome-wide reference maps of the associated DNA methylation dynamics.

They identified characteristic differences between hematopoietic stem cells derived from fetal liver, cord blood, bone marrow, and peripheral blood.

They also observed lineage-specific DNA methylation between myeloid and lymphoid progenitors,

and characterized immature multi-lymphoid progenitors,

and detected progressive DNA methylation differences in maturing megakaryocytes.

They linked these patterns to gene expression, histone modifications, and chromatin accessibility,

and they used machine learning to derive a model of human hematopoietic differentiation directly from DNA methylation data.

The results contribute to a better understanding of human hematopoietic stem cell differentiation

and provide a framework for studying blood-linked diseases.

This provides a framework for visualization DNA methylation at individual genomic loci.
For example, a putative enhancer of the myeloid-linked TREML1 gene displays decreased DNA methylation in HSCs, MPPs, and myeloid progenitors, which correlates with increased RNA expression levels.

A promoter-associated regulatory region in the EXOC6 gene illustrates the frequently observed case of large DNA methylation differences that occur in the absence of detectable changes in gene expression.
The most striking overlap was observed between regions with lower DNA methylation in myeloid cells and binding sites of myeloerythroid transcription factors such as GATA1 and TAL1.

In contrast, regions with lower DNA methylation levels in lymphoid progenitors did not show such strong enrichment patterns for any transcription factor binding sites.

For about half of the transcription factors, the lower DNA methylation in myeloid (as opposed to lymphoid) progenitors was mirrored in higher expression levels in myeloid progenitors.

Among the genes whose promoters were less methylated and more highly expressed in myeloid progenitors were myeloid regulators such as TAL1, MYB, MARCKS, and ICAM4.

Conversely, several genes that play a role in lymphocyte function—including ITGAL, DUSP1, and MX1—were less methylated and more highly expressed in lymphoid progenitors

The scientists established genome-wide maps of the DNA methylation dynamics in human hematopoietic differentiation, which comprise 17 cell types, four different sources of HSCs, and a total of 639 DNA methylation profiles.

This resource, accessible via public repositories and a dedicated website (, provides insights into the role of epigenetic regulation in HSCs and their differentiating progeny, and it constitutes a reference for biomedical research focusing on diseases of the blood.

A key outcome of our study is the high accuracy with which DNA methylation profiles predict cell type throughout the human hematopoietic lineage.

This is not merely due to the correlation between DNA methylation and gene expression (which was low in our dataset), but rather suggests that DNA methylation itself reflects a cell’s differentiation trajectory at the epigenetic level.

We showed that prediction based on DNA methylation in regulatory regions can place sorted cell populations into a developmental context.

They based most of their datasets on stem and progenitor cell populations purified from the peripheral blood of healthy donors.

Nevertheless, the microenvironment of peripheral blood differs markedly from that of bone marrow, cord blood, and fetal liver, which are commonly used sources of HSCs in basic research.

HSCs from peripheral blood showed lower DNA methylation levels at the binding sites of CTCF and cohesin complex proteins than HSCs from other sources, which may reflect changes in chromatin 3D architecture that influence gene expression.

These differences stress the importance of taking cell source and microenvironment into account when studying human hematopoietic stem and progenitor cells.

DNA methylation dynamics of myeloid-lymphoid lineage choice showed an asymmetric pattern: regulatory regions that showed reduced DNA methylation levels in myeloid progenitors were enriched for binding sites of transcription factors associated with hematopoietic differentiation, myeloid lineage fate, and leukemia as well as lymphoma,

— whereas there was no strong enrichment among regions that had reduced DNA methylation levels in lymphoid progenitors.

It supports the view that DNA methylation may epigenetically shield lymphoid progenitors from the default program of myeloid differentiation.

Third, we combined DNA methylation mapping and in vitro differentiation assays to characterize four populations of immature multi-lymphoid progenitors that appear to constitute epigenetically and functionally distinguishable cell types.

DNA methylation can be used as a clinical biomarker,

it is expected that detailed DNA methylation analysis of immunodeficiencies, cardiovascular diseases, and blood cell malignancies will help advance precision medicine.


    • Bock et al., 2016b
    • C. Bock, F. Halbritter, F.J. Carmona, S. Tierling, P. Datlinger, Y. Assenov, M. Berdasco, A.K. Bergmann, K. Booher, F. Busato, BLUEPRINT Consortium, et al.
    • Quantitative comparison of DNA methylation assays for biomarker development and clinical applications
    • Nat. Biotechnol., 34 (2016), pp. 726–737
    • CrossRef | View Record in Scopus

    • Chen et al., 2014
    • L. Chen, M. Kostadima, J.H. Martens, G. Canu, S.P. Garcia, E. Turro, K. Downes, I.C. Macaulay, E. Bielczyk-Maczynska, S. Coe, BRIDGE Consortium, et al.
    • Transcriptional diversity during lineage commitment of human blood progenitors
    • Science, 345 (2014), p. 1251033
    • CrossRef

    • Corces et al., 2016
    • M.R. Corces, J.D. Buenrostro, B. Wu, P.G. Greenside, S.M. Chan, J.L. Koenig, M.P. Snyder, J.K. Pritchard, A. Kundaje, W.J. Greenleaf, et al.
    • Lineage-specific and single-cell chromatin accessibility charts human hematopoiesis and leukemia evolution
    • Nat. Genet., 48 (2016), pp. 1193–1203
    • CrossRef | View Record in Scopus

    • Dahl et al., 2016
    • J.A. Dahl, I. Jung, H. Aanes, G.D. Greggains, A. Manaf, M. Lerdrup, G. Li, S. Kuan, B. Li, A.Y. Lee, et al.
    • Broad histone H3K4me3 domains in mouse oocytes modulate maternal-to-zygotic transition
    • Nature, 537 (2016), pp. 548–552
    • CrossRef | View Record in Scopus

    • Farlik et al., 2015
    • M. Farlik, N.C. Sheffield, A. Nuzzo, P. Datlinger, A. Schönegger, J. Klughammer, C. Bock
    • Single-cell DNA methylome sequencing and bioinformatic inference of epigenomic cell-state dynamics
    • Cell Rep., 10 (2015), pp. 1386–1397
    • Article |

| View Record in Scopus | Citing articles (41)

    • Goardon et al., 2011
    • N. Goardon, E. Marchi, A. Atzberger, L. Quek, A. Schuh, S. Soneji, P. Woll, A. Mead, K.A. Alford, R. Rout, et al.
    • Coexistence of LMPP-like and GMP-like leukemia stem cells in acute myeloid leukemia
    • Cancer Cell, 19 (2011), pp. 138–152
    • Article |

View Record in Scopus
Citing articles (202)

      • Haas et al., 2015
      • S. Haas, J. Hansson, D. Klimmeck, D. Loeffler, L. Velten, H. Uckelmann, S. Wurzer, Á.M. Prendergast, A. Schnell, K. Hexel, et al.
      • Inflammation-induced emergency megakaryopoiesis driven by hematopoietic stem cell-like megakaryocyte progenitors
      • Cell Stem Cell, 17 (2015), pp. 422–434
      • Article |

View Record in Scopus Citing articles (18)

      • Habibi et al., 2013
      • E. Habibi, A.B. Brinkman, J. Arand, L.I. Kroeze, H.H.D. Kerstens, F. Matarese, K. Lepikhov, M. Gut, I. Brun-Heath, N.C. Hubner, et al.
      • Whole-genome bisulfite sequencing of two distinct interconvertible DNA methylomes of mouse embryonic stem cells
      • Cell Stem Cell, 13 (2013), pp. 360–369
      • Article |

View Record in Scopus Citing articles (100)

    • Kim et al., 2011
    • K. Kim, R. Zhao, A. Doi, K. Ng, J. Unternaehrer, P. Cahan, H. Huo, Y.H. Loh, M.J. Aryee, M.W. Lensch, et al.
    • Donor cell type can influence the epigenome and differentiation potential of human induced pluripotent stem cells
    • Nat. Biotechnol., 29 (2011), pp. 1117–1119
    • CrossRef | View Record in Scopus | Citing articles (220)

    • Kuleshov et al., 2016
    • M.V. Kuleshov, M.R. Jones, A.D. Rouillard, N.F. Fernandez, Q. Duan, Z. Wang, S. Koplev, S.L. Jenkins, K.M. Jagodnik, A. Lachmann, et al.
    • Enrichr: a comprehensive gene set enrichment analysis web server 2016 update
    • Nucleic Acids Res., 44 (W1) (2016), pp. W90–W97
    • CrossRef | View Record in Scopus

    • Kundaje et al., 2015
    • A. Kundaje, W. Meuleman, J. Ernst, M. Bilenky, A. Yen, A. Heravi-Moussavi, P. Kheradpour, Z. Zhang, J. Wang, M.J. Ziller, Roadmap Epigenomics Consortium, et al.
    • Integrative analysis of 111 reference human epigenomes
    • Nature, 518 (2015), pp. 317–330
    • CrossRef

    • Lecine et al., 1998
    • P. Lecine, J.L. Villeval, P. Vyas, B. Swencki, Y. Xu, R.A. Shivdasani
    • Mice lacking transcription factor NF-E2 provide in vivo validation of the proplatelet model of thrombocytopoiesis and show a platelet production defect that is intrinsic to megakaryocytes
    • Blood, 92 (1998), pp. 1608–1616
    • View Record in Scopus | Citing articles (115)

    • Lister et al., 2013
    • R. Lister, E.A. Mukamel, J.R. Nery, M. Urich, C.A. Puddifoot, N.D. Johnson, J. Lucero, Y. Huang, A.J. Dwork, M.D. Schultz, et al.
    • Global epigenomic reconfiguration during mammalian brain development
    • Science, 341 (2013), p. 1237905
    • CrossRef

    • Liu et al., 2016
    • X. Liu, C. Wang, W. Liu, J. Li, C. Li, X. Kou, J. Chen, Y. Zhao, H. Gao, H. Wang, et al.
    • Distinct features of H3K4me3 and H3K27me3 chromatin domains in pre-implantation embryos
    • Nature, 537 (2016), pp. 558–562
    • CrossRef | View Record in Scopus

    • Love et al., 2014
    • M.I. Love, W. Huber, S. Anders
    • Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
    • Genome Biol., 15 (2014), p. 550
    • CrossRef

    • McCracken et al., 2013
    • M.N. McCracken, E.H. Gschweng, E. Nair-Gill, J. McLaughlin, A.R. Cooper, M. Riedinger, D. Cheng, C. Nosala, D.B. Kohn, O.N. Witte
    • Long-term in vivo monitoring of mouse and human hematopoietic stem cell engraftment with a human positron emission tomography reporter gene
    • Proc. Natl. Acad. Sci. USA, 110 (2013), pp. 1857–1862
    • CrossRef | View Record in Scopus | Citing articles (16)

    • Moran et al., 2016
    • S. Moran, A. Martínez-Cardús, S. Sayols, E. Musulén, C. Balañá, A. Estival-Gonzalez, C. Moutinho, H. Heyn, A. Diaz-Lagares, M.C. de Moura, et al.
    • Epigenetic profiling to classify cancer of unknown primary: a multicentre, retrospective analysis
    • Lancet Oncol., 17 (2016), pp. 1386–1395
    • Article | PDF (204 K) | View Record in Scopus

    • Notta et al., 2016
    • F. Notta, S. Zandi, N. Takayama, S. Dobson, O.I. Gan, G. Wilson, K.B. Kaufmann, J. McLeod, E. Laurenti, C.F. Dunant, et al.
    • Distinct routes of lineage development reshape the human blood hierarchy across ontogeny
    • Science, 351 (2016), p. aab2116
    • CrossRef

    • Polo et al., 2010
    • J.M. Polo, S. Liu, M.E. Figueroa, W. Kulalert, S. Eminli, K.Y. Tan, E. Apostolou, M. Stadtfeld, Y. Li, T. Shioda, et al.
    • Cell type of origin influences the molecular and functional properties of mouse induced pluripotent stem cells
    • Nat. Biotechnol., 28 (2010), pp. 848–855
    • CrossRef | View Record in Scopus | Citing articles (629)

    • Sheffield and Bock, 2016
    • N.C. Sheffield, C. Bock
    • LOLA: enrichment analysis for genomic region sets and regulatory elements in R and Bioconductor
    • Bioinformatics, 32 (2016), pp. 587–589
    • CrossRef

    • Vedi et al., 2016
    • A. Vedi, A. Santoro, C.F. Dunant, J.E. Dick, E. Laurenti
    • Molecular landscapes of human hematopoietic stem cells in health and leukemia
    • Ann. N Y Acad. Sci., 1370 (2016), pp. 5–14
    • CrossRef | View Record in Scopus

    • Wijetunga et al., 2014
    • N.A. Wijetunga, F. Delahaye, Y.M. Zhao, A. Golden, J.C. Mar, F.H. Einstein, J.M. Greally
    • The meta-epigenomic structure of purified human stem cell populations is defined at cis-regulatory sequences
    • Nat. Commun., 5 (2014), p. 5195
    • CrossRef

    • Zerbino et al., 2015
    • D.R. Zerbino, S.P. Wilder, N. Johnson, T. Juettemann, P.R. Flicek
    • The Ensembl Regulatory Build
    • Genome Biol., 16 (2015), p. 56
    • CrossRef

    • Zhang et al., 2016
    • B. Zhang, H. Zheng, B. Huang, W. Li, Y. Xiang, X. Peng, J. Ming, X. Wu, Y. Zhang, Q. Xu, et al.
    • Allelic reprogramming of the histone modification H3K4me3 in early mammalian development
    • Nature, 537 (2016), pp. 553–557
    • CrossRef | View Record in Scopus

    • Ziller et al., 2013
    • M.J. Ziller, H. Gu, F. Müller, J. Donaghey, L.T.-Y. Tsai, O. Kohlbacher, P.L. De Jager, E.D. Rosen, D.A. Bennett, B.E. Bernstein, et al.
    • Charting a dynamic DNA methylation landscape of the human genome
    • Nature, 500 (2013), pp. 477–481
    • CrossRef |

Tegn abonnement på

BioNyt Videnskabens Verden ( er Danmarks ældste populærvidenskabelige tidsskrift for naturvidenskab. Det er det eneste blad af sin art i Danmark, som er helliget international forskning inden for livsvidenskaberne.

Bladet bringer aktuelle, spændende forskningsnyheder inden for biologi, medicin og andre naturvidenskabelige områder som f.eks. klimaændringer, nanoteknologi, partikelfysik, astronomi, seksualitet, biologiske våben, ecstasy, evolutionsbiologi, kloning, fedme, søvnforskning, muligheden for liv på mars, influenzaepidemier, livets opståen osv.

Artiklerne roses for at gøre vanskeligt stof forståeligt, uden at den videnskabelige holdbarhed tabes.

Leave a Reply