Dynamic epigenomic landscapes during early lineage specification in mouse embryos

Published online:


In mammals, all somatic development originates from lineage segregation in early embryos. However, the dynamics of transcriptomes and epigenomes acting in concert with initial cell fate commitment remains poorly characterized. Here we report a comprehensive investigation of transcriptomes and base-resolution methylomes for early lineages in peri- and postimplantation mouse embryos. We found allele-specific and lineage-specific de novo methylation at CG and CH sites that led to differential methylation between embryonic and extraembryonic lineages at promoters of lineage regulators, gene bodies, and DNA-methylation valleys. By using Hi-C experiments to define chromatin architecture across the same developmental period, we demonstrated that both global demethylation and remethylation in early development correlate with chromatin compartments. Dynamic local methylation was evident during gastrulation, which enabled the identification of putative regulatory elements. Finally, we found that de novo methylation patterning does not strictly require implantation. These data reveal dynamic transcriptomes, DNA methylomes, and 3D chromatin landscapes during the earliest stages of mammalian lineage specification.

  • Subscribe to Nature Genetics for full access:



Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.


  1. 1.

    Rossant, J. & Tam, P. P. Emerging asymmetry and embryonic patterning in early mouse development. Dev. Cell 7, 155–164 (2004).

  2. 2.

    Zernicka-Goetz, M., Morris, S. A. & Bruce, A. W. Making a firm decision: multifaceted regulation of cell fate in the early mouse embryo. Nat. Rev. Genet. 10, 467–477 (2009).

  3. 3.

    Rossant, J. & Tam, P. P. Blastocyst lineage formation, early embryonic asymmetries and axis patterning in the mouse. Development 136, 701–713 (2009).

  4. 4.

    Bielinska, M., Narita, N. & Wilson, D. B. Distinct roles for visceral endoderm during embryonic mouse development. Int. J. Dev. Biol. 43, 183–205 (1999).

  5. 5.

    Arnold, S. J. & Robertson, E. J. Making a commitment: cell lineage allocation and axis patterning in the early mouse embryo. Nat. Rev. Mol. Cell Biol. 10, 91–103 (2009).

  6. 6.

    Lawson, K. A., Meneses, J. J. & Pedersen, R. A. Clonal analysis of epiblast fate during germ layer formation in the mouse embryo. Development 113, 891–911 (1991).

  7. 7.

    Smith, Z. D. & Meissner, A. DNA methylation: roles in mammalian development. Nat. Rev. Genet. 14, 204–220 (2013).

  8. 8.

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

  9. 9.

    Bourc’his, D., Xu, G. L., Lin, C. S., Bollman, B. & Bestor, T. H. Dnmt3L and the establishment of maternal genomic imprints. Science 294, 2536–2539 (2001).

  10. 10.

    Branco, M. R. et al. Maternal DNA methylation regulates early trophoblast development. Dev. Cell 36, 152–163 (2016).

  11. 11.

    McGraw, S. et al. Loss of DNMT1o disrupts imprinted X chromosome inactivation and accentuates placental defects in females. PLoS Genet. 9, e1003873 (2013).

  12. 12.

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

  13. 13.

    Wang, L. et al. Programming and inheritance of parental DNA methylomes in mammals. Cell 157, 979–991 (2014).

  14. 14.

    Guo, H. et al. The DNA methylation landscape of human early embryos. Nature 511, 606–610 (2014).

  15. 15.

    Smith, Z. D. et al. DNA methylation dynamics of the human preimplantation embryo. Nature 511, 611–615 (2014).

  16. 16.

    Gao, F. et al. De novo DNA methylation during monkey pre-implantation embryogenesis. Cell Res. 27, 526–539 (2017).

  17. 17.

    Nagy, A., Gertsenstein, M., Vintersten, K. & Behringer, R. Separating postimplantation germ layers. CSH Protoc. (2006).

  18. 18.

    Beddington, R. S. P. Isolation, culture and manipulation of post-implantation mouse embryos. In: M. Monk ed. Mammalian Development: A Practical Approach (pp. 43–69. IRL Press, Oxford, UK, 1987).

  19. 19.

    Kwon, G. S., Viotti, M. & Hadjantonakis, A. K. The endoderm of the mouse embryo arises by dynamic widespread intercalation of embryonic and extraembryonic lineages. Dev. Cell 15, 509–520 (2008).

  20. 20.

    Peng, X. et al. TELP, a sensitive and versatile library construction method for next-generation sequencing. Nucleic Acids Res. 43, e35 (2015).

  21. 21.

    Hon, G. C. et al. Epigenetic memory at embryonic enhancers identified in DNA methylation maps from adult mouse tissues. Nat. Genet. 45, 1198–1206 (2013).

  22. 22.

    Habibi, E. et al. Whole-genome bisulfite sequencing of two distinct interconvertible DNA methylomes of mouse embryonic stem cells. Cell Stem Cell 13, 360–369 (2013).

  23. 23.

    Hu, Y. G. et al. Regulation of DNA methylation activity through Dnmt3L promoter methylation by Dnmt3 enzymes in embryonic development. Hum. Mol. Genet. 17, 2654–2664 (2008).

  24. 24.

    He, Y. & Ecker, J. R. Non-CG methylation in the human genome. Annu. Rev. Genomics Hum. Genet. 16, 55–77 (2015).

  25. 25.

    Pastor, W. A. et al. Naive human pluripotent cells feature a methylation landscape devoid of blastocyst or germline memory. Cell Stem Cell 18, 323–329 (2016).

  26. 26.

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

  27. 27.

    Jeong, M. et al. Large conserved domains of low DNA methylation maintained by Dnmt3a. Nat. Genet. 46, 17–23 (2014).

  28. 28.

    Auclair, G., Guibert, S., Bender, A. & Weber, M. Ontogeny of CpG island methylation and specificity of DNMT3 methyltransferases during embryonic development in the mouse. Genome Biol. 15, 545 (2014).

  29. 29.

    Schroeder, D. I. et al. Early developmental and evolutionary origins of gene body DNA methylation patterns in mammalian placentas. PLoS Genet. 11, e1005442 (2015).

  30. 30.

    Lieberman-Aiden, E. et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009).

  31. 31.

    Du, Z. et al. Allelic reprogramming of 3D chromatin architecture during early mammalian development. Nature 547, 232–235 (2017).

  32. 32.

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

  33. 33.

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

  34. 34.

    Peat, J. R. et al. Genome-wide bisulfite sequencing in zygotes identifies demethylation targets and maps the contribution of TET3 oxidation. Cell Reports 9, 1990–2000 (2014).

  35. 35.

    Amouroux, R. et al. De novo DNA methylation drives 5hmC accumulation in mouse zygotes. Nat. Cell Biol. 18, 225–233 (2016).

  36. 36.

    Stadler, M. B. et al. DNA-binding factors shape the mouse methylome at distal regulatory regions. Nature 480, 490–495 (2011).

  37. 37.

    Burger, L., Gaidatzis, D., Schübeler, D. & Stadler, M. B. Identification of active regulatory regions from DNA methylation data. Nucleic Acids Res. 41, e155 (2013).

  38. 38.

    Vierstra, J. et al. Mouse regulatory DNA landscapes reveal global principles of cis-regulatory evolution. Science 346, 1007–1012 (2014).

  39. 39.

    McLean, C. Y. et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 28, 495–501 (2010).

  40. 40.

    Schöler, H. R., Dressler, G. R., Balling, R., Rohdewohld, H. & Gruss, P. Oct-4: a germline-specific transcription factor mapping to the mouse t-complex. EMBO J. 9, 2185–2195 (1990).

  41. 41.

    DeVeale, B. et al. Oct4 is required ~E7.5 for proliferation in the primitive streak. PLoS Genet. 9, e1003957 (2013).

  42. 42.

    Iwafuchi-Doi, M. et al. Transcriptional regulatory networks in epiblast cells and during anterior neural plate development as modeled in epiblast stem cells. Development 139, 3926–3937 (2012).

  43. 43.

    Ang, S. L. et al. The formation and maintenance of the definitive endoderm lineage in the mouse: involvement of HNF3/forkhead proteins. Development 119, 1301–1315 (1993).

  44. 44.

    Bossard, P. & Zaret, K. S. GATA transcription factors as potentiators of gut endoderm differentiation. Development 125, 4909–4917 (1998).

  45. 45.

    Kuo, C. T. et al. GATA4 transcription factor is required for ventral morphogenesis and heart tube formation. Genes Dev. 11, 1048–1060 (1997).

  46. 46.

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

  47. 47.

    Libbus, B. L. & Hsu, Y. C. Sequential development and tissue organization in whole mouse embryos cultured from blastocyst to early somite stage. Anat. Rec. 197, 317–329 (1980).

  48. 48.

    Morris, S. A. et al. Dynamics of anterior-posterior axis formation in the developing mouse embryo. Nat. Commun. 3, 673 (2012).

  49. 49.

    Kalkan, T. & Smith, A. Mapping the route from naive pluripotency to lineage specification. Philos. Trans. R. Soc. Lond. B Biol. Sci. 369, 20130540 (2014).

  50. 50.

    Baubec, T. et al. Genomic profiling of DNA methyltransferases reveals a role for DNMT3B in genic methylation. Nature 520, 243–247 (2015).

  51. 51.

    Berman, B. P. et al. Regions of focal DNA hypermethylation and long-range hypomethylation in colorectal cancer coincide with nuclear lamina-associated domains. Nat. Genet. 44, 40–46 (2011).

  52. 52.

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

  53. 53.

    Smith, Z. D. et al. Epigenetic restriction of extraembryonic lineages mirrors the somatic transition to cancer. Nature 549, 543–547 (2017).

  54. 54.

    Zylicz, J. J. et al. Chromatin dynamics and the role of G9a in gene regulation and enhancer silencing during early mouse development. eLife 4, e09571 (2015).

  55. 55.

    Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).

  56. 56.

    Solter, D. & Knowles, B. B. Immunosurgery of mouse blastocyst. Proc. Natl. Acad. Sci. USA 72, 5099–5102 (1975).

  57. 57.

    Ohnishi, Y. et al. Cell-to-cell expression variability followed by signal reinforcement progressively segregates early mouse lineages. Nat. Cell Biol. 16, 27–37 (2014).

  58. 58.

    Harrison, S. M., Dunwoodie, S. L., Arkell, R. M., Lehrach, H. & Beddington, R. S. Isolation of novel tissue-specific genes from cDNA libraries representing the individual tissue constituents of the gastrulating mouse embryo. Development 121, 2479–2489 (1995).

  59. 59.

    Libbus, B. L. & Hsu, Y. C. Changes in S-phase associated with differentiation of mouse embryos in culture from blastocyst to early somite stage. Anat. Embryol. (Berl.) 159, 235–244 (1980).

  60. 60.

    Picelli, S. et al. Full-length RNA-seq from single cells using Smart-seq2. Nat. Protoc. 9, 171–181 (2014).

  61. 61.

    Guo, W. et al. BS-Seeker2: a versatile aligning pipeline for bisulfite sequencing data. BMC Genomics 14, 774 (2013).

  62. 62.

    Trapnell, C. et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protoc. 7, 562–578 (2012).

  63. 63.

    Servant, N. et al. HiC-Pro: an optimized and flexible pipeline for Hi-C data processing. Genome Biol. 16, 259 (2015).

  64. 64.

    Imakaev, M. et al. Iterative correction of Hi-C data reveals hallmarks of chromosome organization. Nat. Methods 9, 999–1003 (2012).

  65. 65.

    Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).

  66. 66.

    Akdemir, K. C. & Chin, L. HiCPlotter integrates genomic data with interaction matrices. Genome Biol. 16, 198 (2015).

  67. 67.

    de Hoon, M. J., Imoto, S., Nolan, J. & Miyano, S. Open source clustering software. Bioinformatics 20, 1453–1454 (2004).

  68. 68.

    Crooks, G. E., Hon, G., Chandonia, J. M. & Brenner, S. E. WebLogo: a sequence logo generator. Genome Res. 14, 1188–1190 (2004).

  69. 69.

    Huang, W., Sherman, B. T. & Lempicki, R. A. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 37, 1–13 (2009).

  70. 70.

    Anders, S., Pyl, P. T. & Huber, W. HTSeq—a Python framework to work with high-throughput sequencing data. Bioinformatics 31, 166–169 (2015).

  71. 71.

    Dixon, J. R. et al. Chromatin architecture reorganization during stem cell differentiation. Nature 518, 331–336 (2015).

  72. 72.

    Naumova, N. et al. Organization of the mitotic chromosome. Science 342, 948–953 (2013).

  73. 73.

    Bell, R. E. et al. Enhancer methylation dynamics contribute to cancer plasticity and patient mortality. Genome Res. 26, 601–611 (2016).

Download references


We are grateful to members of the Xie laboratory for helpful comments during preparation of the manuscript. We thank J. Na for critical reading of the manuscript. This work was supported by the National Key R&D Program of China (2016YFC0900301 to W. Xie; 2017YFC1001401 to L.L.), the National Basic Research Program of China (2015CB856201 to W. Xie), the National Natural Science Foundation of China (31422031 to W. Xie), the THU-PKU Center for Life Sciences (W. Xie), Beijing Advanced Innovation Center for Structural Biology (W. Xie), and the Biomedical Research Council of A*STAR (Agency for Science, Technology and Research), Singapore (F.X.). W. Xie is a Howard Hughes Medical Institute (HHMI) International Research Scholar. J.W. was funded by grants from the NIH (R01GM095942 and R21HD087722) and the Empire State Stem Cell Fund through the New York State Department of Health (NYSTEM) (C028103 and C028121), and is a recipient of an Irma T. Hirschl and Weill-Caulier Trusts Career Scientist Award.

Author information

Author notes

  1. Yu Zhang, Yunlong Xiang, Qiangzong Yin, and Zhenhai Du contributed equally to this work.


  1. Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, School of Life Sciences, Tsinghua University, Beijing, China

    • Yu Zhang
    • , Yunlong Xiang
    • , Qiangzong Yin
    • , Zhenhai Du
    • , Qiujun Wang
    • , Weikun Xia
    • , Yuanyuan Li
    • , Wenhao Zhang
    • , Jing Ma
    •  & Wei Xie
  2. THU-PKU Center for Life Sciences, Tsinghua University, Beijing, China

    • Yunlong Xiang
    • , Zhenhai Du
    • , Qiujun Wang
    • , Weikun Xia
    • , Wenhao Zhang
    •  & Wei Xie
  3. Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore

    • Xu Peng
    •  & Feng Xu
  4. Department of Cell, Developmental and Regenerative Biology, and Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    • Miguel Fidalgo
    •  & Jianlong Wang
  5. State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, China

    • Zhen-ao Zhao
    •  & Lei Li
  6. Singapore Institute for Clinical Sciences, A*STAR, Singapore, Singapore

    • Feng Xu


  1. Search for Yu Zhang in:

  2. Search for Yunlong Xiang in:

  3. Search for Qiangzong Yin in:

  4. Search for Zhenhai Du in:

  5. Search for Xu Peng in:

  6. Search for Qiujun Wang in:

  7. Search for Miguel Fidalgo in:

  8. Search for Weikun Xia in:

  9. Search for Yuanyuan Li in:

  10. Search for Zhen-ao Zhao in:

  11. Search for Wenhao Zhang in:

  12. Search for Jing Ma in:

  13. Search for Feng Xu in:

  14. Search for Jianlong Wang in:

  15. Search for Lei Li in:

  16. Search for Wei Xie in:


Y.Z. and Q.Y. developed and conducted STEM-seq experiments. Y.X. dissected mouse tissues from embryos in vivo, carried out in vitro culture of embryos, and conducted RNA-seq. Z.D. conducted Hi-C experiments and related analysis. Z.Z. and L.L. advised on embryo lineage dissection. X.P. and F.X. advised on the development of STEM-seq. Y.L. and Q.W. conducted high-throughput sequencing. Y.Z. and Y.X. carried out data analysis. Q.W., W.Z., and W. Xia helped with the generation of Tet1/2 double-knockout mice. J.M., M.F., and J.W. helped with various experiments and/or advised the project. Y.Z. and W. Xie wrote the manuscript.

Competing interests

A patent for STEM-seq has been filed (2014104662612 China and PCT/CN2015/088680).

Corresponding author

Correspondence to Wei Xie.

Integrated Supplementary Information

Supplementary information

  1. Supplementary Figures

    Supplementary Figures 1–10.

  2. Life Sciences Reporting Summary

  3. Supplementary Table 1

    Lists of lineage-specific genes from E3.5 to E7.5.

  4. Supplementary Table 2

    Sequencing summary.

  5. Supplementary Table 3

    Differentially methylated genes.

  6. Supplementary Table 4

    Lists of all UMRs and LMRs.

  7. Supplementary Table 5

    Early-embryo-specific UMRs and LMRs.