DNA methylation is a crucial element in the epigenetic regulation of mammalian embryonic development1,2,3,4,5. However, its dynamic patterns have not been analysed at the genome scale in human pre-implantation embryos due to technical difficulties and the scarcity of required materials. Here we systematically profile the methylome of human early embryos from the zygotic stage through to post-implantation by reduced representation bisulphite sequencing and whole-genome bisulphite sequencing. We show that the major wave of genome-wide demethylation is complete at the 2-cell stage, contrary to previous observations in mice. Moreover, the demethylation of the paternal genome is much faster than that of the maternal genome, and by the end of the zygotic stage the genome-wide methylation level in male pronuclei is already lower than that in female pronuclei. The inverse correlation between promoter methylation and gene expression gradually strengthens during early embryonic development, reaching its peak at the post-implantation stage. Furthermore, we show that active genes, with the trimethylation of histone H3 at lysine 4 (H3K4me3) mark at the promoter regions in pluripotent human embryonic stem cells, are essentially devoid of DNA methylation in both mature gametes and throughout pre-implantation development. Finally, we also show that long interspersed nuclear elements or short interspersed nuclear elements that are evolutionarily young are demethylated to a milder extent compared to older elements in the same family and have higher abundance of transcripts, indicating that early embryos tend to retain higher residual methylation at the evolutionarily younger and more active transposable elements. Our work provides insights into the critical features of the methylome of human early embryos, as well as its functional relation to the regulation of gene expression and the repression of transposable elements.

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Gene Expression Omnibus

Data deposits

All sequencing data were deposited at the NCBI Gene Expression Omnibus (GEO) under accession number GSE49828.


  1. 1.

    DNA methylation patterns and epigenetic memory. Genes Dev. 16, 6–21 (2002)

  2. 2.

    , & Epigenetic reprogramming in plant and animal development. Science 330, 622–627 (2010)

  3. 3.

    , , & DNA methylation pattern in human zygotes and developing embryos. Reproduction 128, 703–708 (2004)

  4. 4.

    , & Role for DNA methylation in genomic imprinting. Nature 366, 362–365 (1993)

  5. 5.

    & DNA methylation dynamics during the mammalian life cycle. Phil. Trans. R. Soc. B 368, 20110328 (2013)

  6. 6.

    et al. Human DNA methylomes at base resolution show widespread epigenomic differences. Nature 462, 315–322 (2009)

  7. 7.

    & Early embryos reprogram DNA methylation in two steps. Cell Stem Cell 10, 487–489 (2012)

  8. 8.

    et al. Dynamic CpG island methylation landscape in oocytes and preimplantation embryos. Nature Genet. 43, 811–814 (2011)

  9. 9.

    et al. A unique regulatory phase of DNA methylation in the early mammalian embryo. Nature 484, 339–344 (2012)

  10. 10.

    et al. Mouse oocyte methylomes at base resolution reveal genome-wide accumulation of non-CpG methylation and role of DNA methyltransferases. PLoS Genet. 9, e1003439 (2013)

  11. 11.

    et al. The dynamics of genome-wide DNA methylation reprogramming in mouse primordial germ cells. Mol. Cell 48, 849–862 (2012)

  12. 12.

    & Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nature Genet. 33 (suppl.). 245–254 (2003)

  13. 13.

    & Epigenetic events in mammalian germ-cell development: reprogramming and beyond. Nature Rev. Genet. 9, 129–140 (2008)

  14. 14.

    et al. Dynamic stage-specific changes in imprinted differentially methylated regions during early mammalian development and prevalence of non-CpG methylation in oocytes. Development 138, 811–820 (2011)

  15. 15.

    et al. Single-cell methylome landscapes of mouse embryonic stem cells and early embryos analyzed using reduced representation bisulfite sequencing. Genome Res. 23, 2126–2135 (2013)

  16. 16.

    Functions of DNA methylation: islands, start sites, gene bodies and beyond. Nature Rev. Genet. 13, 484–492 (2012)

  17. 17.

    et al. Genome-wide chromatin state transitions associated with developmental and environmental cues. Cell 152, 642–654 (2013)

  18. 18.

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

  19. 19.

    et al. Tracking the progression of the human inner cell mass during embryonic stem cell derivation. Nature Biotechnol. 30, 278–282 (2012)

  20. 20.

    et al. Epigenomic analysis of multilineage differentiation of human embryonic stem cells. Cell 153, 1134–1148 (2013)

  21. 21.

    et al. Transcriptional and epigenetic dynamics during specification of human embryonic stem cells. Cell 153, 1149–1163 (2013)

  22. 22.

    et al. Genome-wide maps of chromatin state in pluripotent and lineage-committed cells. Nature 448, 553–560 (2007)

  23. 23.

    et al. Single-cell RNA-Seq profiling of human preimplantation embryos and embryonic stem cells. Nature Struct. Mol. Biol. 20, 1131–1139 (2013)

  24. 24.

    , , , & Human pre-implantation embryo development. Development 139, 829–841 (2012)

  25. 25.

    & The impact of retrotransposons on human genome evolution. Nature Rev. Genet. 10, 691–703 (2009)

  26. 26.

    et al. Sperm methylation profiles reveal features of epigenetic inheritance and evolution in primates. Cell 146, 1029–1041 (2011)

  27. 27.

    , , , & Serum progesterone concentration on day of HCG administration and IVF outcome. Reprod. Biomed. Online 16, 627–631 (2008)

  28. 28.

    et al. Retain singleton or twins? Multifetal pregnancy reduction strategies in triplet pregnancies with monochorionic twins. Eur. J. Obstet. Gynecol. Reprod. Biol. 167, 146–148 (2013)

  29. 29.

    et al. The role of Tet3 DNA dioxygenase in epigenetic reprogramming by oocytes. Nature 477, 606–610 (2011)

  30. 30.

    & Replication-dependent loss of 5-hydroxymethylcytosine in mouse preimplantation embryos. Science 334, 194 (2011)

  31. 31.

    , , , & Generation and replication-dependent dilution of 5fC and 5caC during mouse preimplantation development. Cell Res. 21, 1670–1676 (2011)

  32. 32.

    et al. Parental origin of chromatin in human monopronuclear zygotes revealed by asymmetric histone methylation patterns, differs between IVF and ICSI. Mol. Reprod. Dev. 76, 101–108 (2009)

  33. 33.

    et al. Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling. Nature Protocols 6, 468–481 (2011)

  34. 34.

    et al. Maternal and zygotic Dnmt1 are necessary and sufficient for the maintenance of DNA methylation imprints during preimplantation development. Genes Dev. 22, 1607–1616 (2008)

  35. 35.

    et al. Maintenance of genomic methylation patterns during preimplantation development requires the somatic form of DNA methyltransferase 1. Dev. Biol. 313, 335–346 (2008)

  36. 36.

    et al. mRNA-Seq whole-transcriptome analysis of a single cell. Nature Methods 6, 377–382 (2009)

  37. 37.

    & Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics 27, 1571–1572 (2011)

  38. 38.

    , , & Bis-SNP: Combined DNA methylation and SNP calling for Bisulfite-seq data. Genome Biol. 13, R61 (2012)

  39. 39.

    et al. Initial sequencing and analysis of the human genome. Nature 409, 860–921 (2001)

  40. 40.

    , & Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nature Protocols 4, 44–57 (2009)

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F.T. and J.Q. were supported by grants from the National Basic Research Program of China (2012CB966704, 2011CB944504 and 2011CB966303) and from the National Natural Science of China (31322037, 31230047, 31271543 and 81170538). J.Q. and F.T. were supported by a grant from the Beijing Municipal Science and Technology Commission (Z131100005213006). L.Y. was supported by grants from the National Natural Science Foundation of China (81000275) and National Basic Research Program of China (2011CB944503). R.L. was supported by a grant from National Key Technologies Research and Development Program (2012BAI32B01).

Author information

Author notes

    • Hongshan Guo
    • , Ping Zhu
    • , Liying Yan
    •  & Rong Li

    These authors contributed equally to this work.


  1. Biodynamic Optical Imaging Center & Center for Reproductive Medicine, College of Life Sciences, Third Hospital, Peking University, Beijing 100871, China

    • Hongshan Guo
    • , Ping Zhu
    • , Liying Yan
    • , Rong Li
    • , Boqiang Hu
    • , Ying Lian
    • , Jie Yan
    • , Xiulian Ren
    • , Shengli Lin
    • , Junsheng Li
    • , Xiaohu Jin
    • , Xiaodan Shi
    • , Ping Liu
    • , Xianlong Li
    • , Fan Guo
    • , Xinglong Wu
    • , Xiaoying Fan
    • , Jun Yong
    • , Lu Wen
    • , Sunney X. Xie
    • , Fuchou Tang
    •  & Jie Qiao
  2. Peking-Tsinghua Center for Life Sciences, Peking University, Beijing 100871, China

    • Ping Zhu
  3. Key Laboratory of Assisted Reproduction, Ministry of Education, Beijing 100191, China

    • Liying Yan
    • , Rong Li
    • , Ying Lian
    • , Jie Yan
    • , Xiulian Ren
    • , Shengli Lin
    • , Junsheng Li
    • , Xiaohu Jin
    • , Xiaodan Shi
    • , Ping Liu
    •  & Jie Qiao
  4. Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing 100191, China

    • Xiaoye Wang
    • , Wei Wang
    •  & Yuan Wei
  5. Department of Chemistry and Chemical Biology, Harvard University, Cambridge, Massachusetts 02138, USA

    • Jun Yong
    •  & Sunney X. Xie
  6. Ministry of Education Key Laboratory of Cell Proliferation and Differentiation, Beijing 100871, China

    • Fuchou Tang


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F.T. and J.Q. conceived the experiments and supervised the project. H.G., L.Y., R.L., Y.L. J.Y., X.R., S.L., J.L., X.J., X.S., P.L., X.W., W.W., Y.W., X.L., F.G., X.W., X.F., J.Y. and L.W. performed the experiments. P.Z and B.H. did all of the bioinformatic analyses. S.X.X., J.Q. and F.T. wrote the manuscript with help from all of the authors.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Fuchou Tang or Jie Qiao.

Extended data

Supplementary information

Excel files

  1. 1.

    Supplementary Table 1

    Summary of the numbers of embryos or cells of each biological replicate used for the RRBS analysis in this study.

  2. 2.

    Supplementary Table 2

    Summary of the sequencing qualities, reads mapping, and the covered CpG sites and their mean coverage depths at 1, 5, and 10 in each stage of the RRBS dataset. The right-hand column shows the average bisulfite conversion rate of each stage.

  3. 3.

    Supplementary Table 3

    Summary of the sequencing qualities, reads mapping, and the covered CpG sites and their mean coverage depths at 1, 5, and 10 of each single cell RRBS and WGBS samples. The right-hand column shows the average bisulfite conversion rate of each stage.

  4. 4.

    Supplementary Table 4

    The list of the filtered ASM regions covered in our WGBS of post-implanted liver tissue, including the chromosome positions, called SNPs positions, SNP genotypes, and the chromosome locations of the allele specific methylation regions.

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