DNA-binding factors shape the mouse methylome at distal regulatory regions

Journal name:
Nature
Year published:
DOI:
doi:10.1038/nature10716
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Published online

Abstract

Methylation of cytosines is an essential epigenetic modification in mammalian genomes, yet the rules that govern methylation patterns remain largely elusive. To gain insights into this process, we generated base-pair-resolution mouse methylomes in stem cells and neuronal progenitors. Advanced quantitative analysis identified low-methylated regions (LMRs) with an average methylation of 30%. These represent CpG-poor distal regulatory regions as evidenced by location, DNase I hypersensitivity, presence of enhancer chromatin marks and enhancer activity in reporter assays. LMRs are occupied by DNA-binding factors and their binding is necessary and sufficient to create LMRs. A comparison of neuronal and stem-cell methylomes confirms this dependency, as cell-type-specific LMRs are occupied by cell-type-specific transcription factors. This study provides methylome references for the mouse and shows that DNA-binding factors locally influence DNA methylation, enabling the identification of active regulatory regions.

At a glance

Figures

  1. Features of the mouse ES cell methylome.
    Figure 1: Features of the mouse ES cell methylome.

    a, Distribution of CpG methylation frequency for all CpGs with at least tenfold coverage. Of all cytosines, 4.1% show intermediate methylation levels. b, Representative genomic region. Computational segmentation identifies UMRs (blue pentagons), LMRs (red triangles) and FMRs (unmarked). Each dot represents one CpG (CpG islands marked in green). Included is an independently verified LMR upstream of Tbx3. Mbp, million base pairs. c, Composite profile of CpG methylation for all three groups. kb, kilobases. d, Distances to TSS. e, f, Distribution of all three classes among genome features. e, A small percentage of LMRs overlap with CpG islands. Numbers indicate observed percentage of overlaps per group (expected percentage in parentheses). f, Distribution of the regions throughout the genome.

  2. General features of LMRs.
    Figure 2: General features of LMRs.

    Composite profiles 3kb around segment midpoints. a, Evolutionary conservation based on multi-species alignments (upper left). Enrichment of DNase I tags (lower left). Chromatin features that predict enhancer function are enriched at LMRs (middle and right). b, Heat map of methylation levels, histone modifications and protein binding (H3K4me1 signal rescaled for visibility).

  3. DNA binding is necessary and sufficient for LMR formation.
    Figure 3: DNA binding is necessary and sufficient for LMR formation.

    a, Including BisSeq data improves prediction of CTCF binding, measured as per cent of explained variance (100% = perfect prediction). b, Introduction of a CTCF motif (black triangle) into an otherwise methylated reporter construct leads to local demethylation. Insertion of a mutated site has no effect. Pre-methylation of the CTCF-motif-containing construct does not inhibit demethylation. Bar graphs show average CTCF enrichment from three experiments (error bars, s.d.). c, Allele-specific CTCF binding and DNA methylation for three loci. Two contain a heterozygous SNP (top and middle) and one serves as control (bottom). ChIP-seq and DNA methylation were quantified in 100-bp and 400-bp windows, respectively. d, CTCF binding in cells with or without DNA methylation. CTCF binding is globally unchanged in cells without methylation (EStko), but increases by approximately twofold at sites located in the H19 ICR (orange dots).

  4. REST is required for LMR formation at its binding sites.
    Figure 4: REST is required for LMR formation at its binding sites.

    Bisulphite profile of a genomic region containing a REST binding site coinciding with an LMR. This LMR regains methylation in the absence of REST (REST−/− ES cells), whereas reintroduction of REST re-establishes it.

  5. Methylation dynamics during differentiation.
    Figure 5: Methylation dynamics during differentiation.

    a, Methylation of individual CpGs at an NP-specific LMR in a gene important for neuronal differentiation (Slc1a3). b, Comparison of DNA methylation in ES cells and NP of all CG-low regions (density increases from blue to red). LMRs were grouped into ES-cell-specific LMRs (box 1), constitutive LMRs (box 2) and NP-specific LMRs (box 3) and analysed for enriched DNA-binding motifs (indicated on the right). c, Methylation versus expression changes for Klf4 and Pax6. Klf4 binding sites in ES cells gain methylation in NP, whereas Pax6 binding sites lose methylation (top 200 sites; P<2.2×10−16 for Klf4; P = 7.4×10−7 for Pax6; error bars, s.e.m.). Changes in methylation at binding sites are anti-correlated to expression changes of the respective factors (right graph).

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Author information

  1. These authors contributed equally to this work.

    • Michael B. Stadler,
    • Rabih Murr &
    • Lukas Burger

Affiliations

  1. Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, 4058 Basel, Switzerland

    • Michael B. Stadler,
    • Rabih Murr,
    • Lukas Burger,
    • Robert Ivanek,
    • Florian Lienert,
    • Anne Schöler,
    • Christiane Wirbelauer,
    • Dimos Gaidatzis,
    • Vijay K. Tiwari &
    • Dirk Schübeler
  2. Swiss Institute of Bioinformatics, 4058 Basel, Switzerland

    • Michael B. Stadler,
    • Lukas Burger,
    • Anne Schöler &
    • Dimos Gaidatzis
  3. Faculty of Science, University of Basel, 4056 Basel, Switzerland

    • Florian Lienert,
    • Anne Schöler &
    • Dirk Schübeler
  4. Novartis Institutes for BioMedical Research, Biomarker Development, 4056 Basel, Switzerland

    • Edward J. Oakeley
  5. Biozentrum of the University of Basel and Swiss Institute of Bioinformatics, Klingelbergstrasse 50–70, CH 4056, Basel, Switzerland

    • Erik van Nimwegen

Contributions

Experiments were designed by R.M., F.L., A.S., V.K.T., E.J.O. and D.S. BisSeq, RNA-Seq and ChIP-seq experiments were conducted by R.M., A.S. and V.K.T. ChIP-seq data analysis was performed by M.B.S. and L.B. BS-PCR validation was performed by R.M., F.L. and C.W. Sequencing data processing was performed by D.G. and M.B.S. LMRs were first noticed by D.G. Bioinformatic and statistical analyses were conducted by M.B.S., L.B., R.I. and E.v.N. The manuscript was prepared by R.M., M.B.S., L.B. and D.S.

Competing financial interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to:

Data sets generated for this study are available from GEO under accession GSE30206.

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Supplementary information

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  1. Supplementary Information (15.5M)

    The file contains Supplementary Figures 1-16 with legends, Supplementary Methods and additional references. The methods in this file were replaced on 25 April 2012.

Word documents

  1. Supplementary Table 1 (56K)

    The table displays details of sequence datasets used in this study, and additional references (for external data sets only).

Other

  1. Supplementary Table 2 (9.6M)

    The table displays methylation segments identified in ES cells.

  2. Supplementary Table 3 (7M)

    The table displays Methylation segments identified in NP. A short description of each column is given at the top of the table.

  3. Supplementary Table 4 (29K)

    The table displays Genotype structure of the ES cell line used in the study.

Additional data