Letter | Published:

DNA methylation dynamics of the human preimplantation embryo

Nature volume 511, pages 611615 (31 July 2014) | Download Citation


In mammals, cytosine methylation is predominantly restricted to CpG dinucleotides and stably distributed across the genome, with local, cell-type-specific regulation directed by DNA binding factors1,2,3. This comparatively static landscape is in marked contrast with the events of fertilization, during which the paternal genome is globally reprogrammed. Paternal genome demethylation includes the majority of CpGs, although methylation remains detectable at several notable features4,5,6,7. These dynamics have been extensively characterized in the mouse, with only limited observations available in other mammals, and direct measurements are required to understand the extent to which early embryonic landscapes are conserved8,9,10. We present genome-scale DNA methylation maps of human preimplantation development and embryonic stem cell derivation, confirming a transient state of global hypomethylation that includes most CpGs, while sites of residual maintenance are primarily restricted to gene bodies. Although most features share similar dynamics to those in mouse, maternally contributed methylation is divergently targeted to species-specific sets of CpG island promoters that extend beyond known imprint control regions. Retrotransposon regulation is also highly diverse, and transitions from maternally to embryonically expressed elements. Together, our data confirm that paternal genome demethylation is a general attribute of early mammalian development that is characterized by distinct modes of epigenetic regulation.

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Gene Expression Omnibus

Data deposits

RRBS data is deposited at the Gene Expression Omnibus under accession number GSE51239.


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We would like to thank all members of the Meissner, Regev and Eggan laboratories, in particular M. Ziller for critical reading of the text and K. Koszka for supervising human embryo thawing. We also thank D. Sakkas and R. Holmes of Boston IVF for clinical assessment of embryo morphology and viability, as well as S. Levine, M. Gravina and K. Thai from the MIT BioMicro Center. Finally, we thank T. S. Mikkelsen, H. Gu, and A. Gnirke from the Broad Institute for their guidance and expertise. A.R. is an investigator of the Merkin Foundation for Stem Cell Research at the Broad Institute. This work was supported by the Harvard Stem Cell Institute (K.E.), and NIH Pioneer Award (5DP1OD003958), the Burroughs Wellcome Career Award at the Scientific Interface and HHMI (to A.R. and K.E.), P01GM099117 (to A.M. and K. E.) and a Center for Excellence in Genome Science from the NHGRI (1P50HG006193-01, to A.R. and A.M.). A.M. is a New York Stem Cell Foundation Robertson Investigator. This research was supported by The New York Stem Cell Foundation.

Author information

Author notes

    • Zachary D. Smith
    • , Michelle M. Chan
    •  & Kathryn C. Humm

    These authors contributed equally to this work.


  1. Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA

    • Zachary D. Smith
    • , Michelle M. Chan
    • , Rahul Karnik
    • , Aviv Regev
    • , Kevin Eggan
    •  & Alexander Meissner
  2. Harvard Stem Cell Institute, Cambridge, Massachusetts 02138, USA

    • Zachary D. Smith
    • , Rahul Karnik
    • , Kevin Eggan
    •  & Alexander Meissner
  3. Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts 02138, USA

    • Zachary D. Smith
    • , Kathryn C. Humm
    • , Rahul Karnik
    • , Shila Mekhoubad
    • , Kevin Eggan
    •  & Alexander Meissner
  4. Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts 02138, USA

    • Zachary D. Smith
    • , Shila Mekhoubad
    •  & Kevin Eggan
  5. Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA

    • Michelle M. Chan
  6. Division of Reproductive Endocrinology & Infertility, Department of Obstetrics & Gynecology, Beth Israel Deaconess Medical Center, Boston, Massachusetts 02215, USA

    • Kathryn C. Humm
  7. Obstetrics, Gynecology, and Reproductive Biology, Harvard Medical School, Boston, Massachusetts 02215, USA

    • Kathryn C. Humm
  8. Boston IVF, Waltham, Massachusetts 02451, USA

    • Kathryn C. Humm
  9. Howard Hughes Medical Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA

    • Kathryn C. Humm
    •  & Aviv Regev
  10. Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA

    • Aviv Regev
  11. Howard Hughes Medical Institute, Harvard University, Cambridge, Massachusetts 02138, USA

    • Kevin Eggan


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Z.D.S., K.E. and A.M. conceived the study and Z.D.S., M.M.C., K.C.H., A.R., K.E. and A.M. facilitated its design. Z.D.S., K.C.H. and S.M. collected samples and Z.D.S. performed methylation profiling, M.M.C. and R.K. performed all analysis with assistance from Z.D.S. Z.D.S., M.M.C. and A.M. interpreted the data and wrote the paper with the assistance of the other authors.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Kevin Eggan or Alexander Meissner.

Extended data

Supplementary information

Excel files

  1. 1.

    Supplementary Table 1

    Promoter methylation and gene expression values over human preimplantation development and ESC derivation: Methylation of promoters and corresponding gene expression dynamics across human early development and during ESC derivation. Expression is calculated as the fragments per kb per million (FPKM).

  2. 2.

    Supplementary Table 2

    Methylation dynamics of orthologous human and mouse CpG islands: Methylation values in human CGI promoters over preimplantation development. Nearest gene refers to the TSS that is most proximal to the CGI. Human CGIs that aligned to mouse but did not maintain CGI status are indicated under the mouse proximal gene annotation and methylation over the orthologous region is reported when captured (Methods).

  3. 3.

    Supplementary Table 3

    Mean LTR subfamily methylation and expression dynamics over human preimplantation development: Family and subfamily designations, genomic representation as indicated by repeat masker, and the number of members captured by RRBS are included. Mean methylation is reported for subfamilies over the human preimplantation and ESC derivation timeline. Expression is calculated as the fragments per kb per million (FPKM), which accounts for differences in genomic representation. Total expression refers to the fragments per million (FPM) and indicates the total contribution of a given family to the transcriptome (Methods).

  4. 4.

    Supplementary Table 4

    Mean LINE subfamily methylation and expression dynamics over human preimplantation development: Subfamily level mean methylation and expression, including both mean and total, dynamics for LINEs over human preimplantation and ESC derivation, organized as in Supplementary Table 3.

  5. 5.

    Supplementary Table 5

    Mean SINE subfamily methylation and expression dynamics over human preimplantation development: Subfamily level mean methylation and expression, including both mean and total, dynamics for SINEs over human preimplantation and ESC derivation, organized as in Supplementary Table 3.

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