Key role for CTCF in establishing chromatin structure in human embryos

Abstract

In the interphase of the cell cycle, chromatin is arranged in a hierarchical structure within the nucleus1,2, which has an important role in regulating gene expression3,4,5,6. However, the dynamics of 3D chromatin structure during human embryogenesis remains unknown. Here we report that, unlike mouse sperm, human sperm cells do not express the chromatin regulator CTCF and their chromatin does not contain topologically associating domains (TADs). Following human fertilization, TAD structure is gradually established during embryonic development. In addition, A/B compartmentalization is lost in human embryos at the 2-cell stage and is re-established during embryogenesis. Notably, blocking zygotic genome activation (ZGA) can inhibit TAD establishment in human embryos but not in mouse or Drosophila. Of note, CTCF is expressed at very low levels before ZGA, and is then highly expressed at the ZGA stage when TADs are observed. TAD organization is significantly reduced in CTCF knockdown embryos, suggesting that TAD establishment during ZGA in human embryos requires CTCF expression. Our results indicate that CTCF has a key role in the establishment of 3D chromatin structure during human embryogenesis.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Three-dimensional chromatin structures of human sperm and embryos.
Fig. 2: Human sperm does not have typical TAD structures.
Fig. 3: Establishment of insulated boundaries during human embryogenesis.
Fig. 4: CTCF regulates the establishment of chromatin landscape in human embryos.

Data availability

Data generated for this study have been deposited to the Genome Sequence Archive with the accession number CRA000852 and CRA000108. Hi-C data of unmixed human sperm sample have been deposited in CRA000108, and the other data have been deposited in CRA000852. Raw image files used in the figures that support the findings of this study are available from the corresponding authors upon reasonable request.

Code availability

Codes used for the analysis reported in this study are available at https://github.com/ChenXP0310/2019-humanembryo3D.

References

  1. 1.

    Fullwood, M. J. et al. An oestrogen-receptor-α-bound human chromatin interactome. Nature 462, 58–64 (2009).

    ADS  CAS  Article  Google Scholar 

  2. 2.

    Atlasi, Y. & Stunnenberg, H. G. The interplay of epigenetic marks during stem cell differentiation and development. Nat. Rev. Genet. 18, 643–658 (2017).

    CAS  Article  Google Scholar 

  3. 3.

    Rao, S. S. et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159, 1665–1680 (2014).

    CAS  Article  Google Scholar 

  4. 4.

    Tang, Z. et al. CTCF-mediated human 3D genome architecture reveals chromatin topology for transcription. Cell 163, 1611–1627 (2015).

    CAS  Article  Google Scholar 

  5. 5.

    Bonev, B. et al. Multiscale 3D genome rewiring during mouse neural development. Cell 171, 557–572 (2017).

    CAS  Article  Google Scholar 

  6. 6.

    Hsieh, T. H. et al. mapping nucleosome resolution chromosome folding in yeast by micro-C. Cell 162, 108–119 (2015).

    CAS  Article  Google Scholar 

  7. 7.

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

    ADS  CAS  Article  Google Scholar 

  8. 8.

    Ke, Y. et al. 3D chromatin structures of mature gametes and structural reprogramming during mammalian embryogenesis. Cell 170, 367–381 (2017).

    CAS  Article  Google Scholar 

  9. 9.

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

    ADS  CAS  Article  Google Scholar 

  10. 10.

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

    ADS  CAS  Article  Google Scholar 

  11. 11.

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

    ADS  CAS  Article  Google Scholar 

  12. 12.

    Giorgetti, L. et al. Structural organization of the inactive X chromosome in the mouse. Nature 535, 575–579 (2016).

    ADS  CAS  Article  Google Scholar 

  13. 13.

    Li, C. et al. DNA methylation reprogramming of functional elements during mammalian embryonic development. Cell Discov. 4, 41 (2018).

    Article  Google Scholar 

  14. 14.

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

    ADS  CAS  Article  Google Scholar 

  15. 15.

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

    ADS  CAS  Article  Google Scholar 

  16. 16.

    Jung, Y. H. et al. Chromatin states in mouse sperm correlate with embryonic and adult regulatory landscapes. Cell Rep. 18, 1366–1382 (2017).

    CAS  Article  Google Scholar 

  17. 17.

    Baranello, L., Kouzine, F. & Levens, D. CTCF and cohesin cooperate to organize the 3D structure of the mammalian genome. Proc. Natl Acad. Sci. USA 111, 889–890 (2014).

    ADS  CAS  Article  Google Scholar 

  18. 18.

    Nora, E. P. et al. Targeted degradation of CTCF decouples local insulation of chromosome domains from genomic compartmentalization. Cell 169, 930–944 (2017).

    CAS  Article  Google Scholar 

  19. 19.

    Hug, C. B., Grimaldi, A. G., Kruse, K. & Vaquerizas, J. M. Chromatin architecture emerges during zygotic genome activation independent of transcription. Cell 169, 216–228 (2017).

    CAS  Article  Google Scholar 

  20. 20.

    Xue, Z. et al. Genetic programs in human and mouse early embryos revealed by single-cell RNA sequencing. Nature 500, 593–597 (2013).

    ADS  CAS  Article  Google Scholar 

  21. 21.

    Hendrickson, P. G. et al. Conserved roles of mouse DUX and human DUX4 in activating cleavage-stage genes and MERVL/HERVL retrotransposons. Nat. Genet. 49, 925–934 (2017).

    CAS  Article  Google Scholar 

  22. 22.

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

    CAS  Article  Google Scholar 

  23. 23.

    Schmitt, A. D. et al. A compendium of chromatin contact maps reveals spatially active regions in the human genome. Cell Rep. 17, 2042–2059 (2016).

    CAS  Article  Google Scholar 

  24. 24.

    Wu, J. et al. Chromatin analysis in human early development reveals epigenetic transition during ZGA. Nature 557, 256–260 (2018).

    ADS  CAS  Article  Google Scholar 

  25. 25.

    Gao, L. et al. Chromatin accessibility landscape in human early embryos and its association with evolution. Cell 173, 248–259 (2018).

    CAS  Article  Google Scholar 

  26. 26.

    Flyamer, I. M. et al. Single-nucleus Hi-C reveals unique chromatin reorganization at oocyte-to-zygote transition. Nature 544, 110–114 (2017).

    ADS  CAS  Article  Google Scholar 

  27. 27.

    Roy, T. K., Bradley, C. K., Bowman, M. C. & McArthur, S. J. Single-embryo transfer of vitrified-warmed blastocysts yields equivalent live-birth rates and improved neonatal outcomes compared with fresh transfers. Fertil. Steril. 101, 1294–1301 (2014).

    Article  PubMed  Google Scholar 

  28. 28.

    Zuin, J. et al. Cohesin and CTCF differentially affect chromatin architecture and gene expression in human cells. Proc. Natl Acad. Sci. USA 111, 996–1001 (2014). 

    ADS  CAS  Article  PubMed  Google Scholar 

  29. 29.

    Guillou, E. et al. Cohesin organizes chromatin loops at DNA replication factories. Genes Dev. 24, 2812–2822 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  30. 30.

    Ramírez, F. et al. High-resolution TADs reveal DNA sequences underlying genome organization in flies. Nat. Commun. 9, 189 (2018).

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  31. 31.

    Wolff, J. et al. Galaxy HiCExplorer: a web server for reproducible Hi-C data analysis, quality control and visualization. Nucleic Acids Res. 46 (W1), W11–W16 (2018).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  32. 32.

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

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  33. 33.

    Durand, N. C. et al. Juicer provides a one-click system for analyzing loop-resolution Hi-C experiments. Cell Syst. 3, 95–98 (2016).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Ursu, O. et al. GenomeDISCO: a concordance score for chromosome conformation capture experiments using random walks on contact map graphs. Bioinformatics 34, 2701–2707 (2018).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Gassler, J. et al. A mechanism of cohesin-dependent loop extrusion organizes zygotic genome architecture. EMBO J. 36, 3600–3618 (2017). 

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  36. 36.

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

    ADS  CAS  Article  PubMed  PubMed Central  Google Scholar 

  37. 37.

    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).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  38. 38.

    Li, G. et al. Genome wide abnormal DNA methylome of human blastocyst in assisted reproductive technology. J. Genet. Genom. 44, 475–481 (2017).

    CAS  Article  Google Scholar 

  39. 39.

    Langmead, B., Trapnell, C., Pop, M. & Salzberg, S. L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol. 10, R25 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  40. 40.

    DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  41. 41.

    Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  42. 42.

    John, S. et al. Chromatin accessibility pre-determines glucocorticoid receptor binding patterns. Nat. Genet. 43, 264–268 (2011).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Ramírez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44 (W1), W160–W165 (2016). 

    MathSciNet  CAS  Article  PubMed  PubMed Central  Google Scholar 

  44. 44.

    Eisenberg, E. & Levanon, E. Y. Human housekeeping genes, revisited. Trends Genet. 29, 569–574 (2013).

    CAS  Article  PubMed  Google Scholar 

  45. 45.

    Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).

    CAS  Article  Google Scholar 

  46. 46.

    Gu, Z., Gu, L., Eils, R., Schlesner, M. & Brors, B. circlize Implements and enhances circular visualization in R. Bioinformatics 30, 2811–2812 (2014).

    CAS  Article  PubMed  Google Scholar 

  47. 47.

    Consortium, E. P.; ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).

    ADS  CAS  Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the grants from The Ministry of Science and Technology of China (2018YFC1004000 and 2018YFC1003300), National Natural Science Foundation of China (81430029, 91731312, 81871171, 31425015, 31630040, 31871454, 81622021 and 81871168), CAS funding (QYZDY-SSW-SMC016) and Strategic Priority Research Program of the Chinese Academy of Sciences (XDB13040200).

Author information

Affiliations

Authors

Contributions

J.L. and Z.-J.C. conceived the study. X.C., Y.K. and K.W. facilitated its designs. K.W., H.Z., J.Z., W.T. and H.L. collected human embryos. K.W. and Z.H. performed siRNA-microinjection in human embryos. Y.K., X.C. and Y.S. performed Hi-C library construction. Z.L. performed RNA-seq library construction. X.C., Y.S., and L.G. performed the bioinformatics analyses. X.C., Y.K., K.W., Z.-J.C. and J.L. interpreted the data. X.C., Y.K., Z.-J.C., and J.L. wrote the paper with the assistance of the other authors.

Corresponding authors

Correspondence to Jiang Liu or Zi-Jiang Chen.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Validation of optimized ultra-low-input Hi-C.

a, Interaction heat maps for mouse embryonic day (E)3.5 embryos. Top, pooled mouse E3.5 embryos Hi-C8. Bottom, a single mouse E3.5 embryo with ultra-low-input Hi-C from this study. b, A track snapshot of PC1 values for chromosome 1 in pooled mouse E3.5 embryos and single mouse E3.5 embryo along with public mouse ES cell (mESC) data9. c, Interaction heat maps for pooled mouse E3.5 embryos and single mouse E3.5 embryo for a zoomed-in region from chromosome 1 overlaid with TADs, directional index, boundaries and TAD separation scores. d, GenomeDISCO reproducibility (Methods) among the Hi-C data for each chromosome in pooled human blastocysts and two human single-blastocyst replicates. e, The strength of average TADs in pooled human blastocyst data, single human blastocyst data and metaphase HeLa data36. TAD positions are annotated in combined human blastocyst data. TAD structure strength (Methods) is shown on each corresponding panel. f, GenomeDISCO reproducibility for biological replicates of human sperm and embryos. n = 2–3 independent biological replicates for each stage. Each dot represents one comparison between two biological replicates. Data are mean ± s.d.

Extended Data Fig. 2 TAD establishment during human embryonic development.

a, Interaction heat maps for human embryos with equal reads along with human H1 ES cells. b, An example for TAD calling by using TAD separation score method in human blastocysts with different read depths. The orange track under each heat map represents TAD domains. The bottom panels are TAD boundaries and TAD separation score tracks. M, million reads. c, Venn diagram for the overlap of TAD boundaries of human blastocyst between 10 million read depth data (10 M, blue) and total combined data (total, red). d, An equal-read-depth TAD signal track snapshot for human sperm and embryos along with human H1 ES cells. e, Average directional index around human TAD boundaries(0.5 Mb) at different embryonic stages. Directional index generated by a random blastocyst valid read pair dataset is also shown as a control. f, g, Interaction heat map examples at 50-kb resolution for unmixed human embryos and human embryos from mixed samples. h, The strength for average TADs in mouse morula embryos from mixed samples (six mouse morulae for each mixed sample), unmixed mouse morula and mouse MII oocyte. TAD positions are annotated in combined mouse E3.5 embryos. TAD structure strength is shown on each corresponding panel. i, Relative variance of TAD signal for replicates of human embryos including human embryos from mixed samples. We used the chromosome as the unit for this analysis. Two-cell (n = 3), 8-cell (n = 3), morula (n = 3), blastocyst (n = 3) and 6-week embryos (n = 2). Boxes represent the 25th, 50th and 75th percentiles and whiskers show 1.5× the interquartile range. ***adjusted P < 0.001 for all pairwise comparison between two stage samples (two-sided Wilcoxon rank-sum test with Benjamini–Hochberg multiple testing correction). NS, not significant.

Extended Data Fig. 3 A/B compartmentalization dynamics during human embryonic development.

a, Pearson correlation heat maps of chromosome 1 at 500-kb resolution in human 2-cell, 8-cell, morula and blastocysts, 6-week embryos and H1 ES cells (equal no. of reads generated from 2–3 biological independent replicates for each stage). b, Top, whole-genome PC1 value circle plots for human 2-cell embryos and human blastocysts (with R package circlize46). Bottom, PC1 tracks in mouse zygotes and mouse E3.5 embryos. c, Pearson correlation heat maps at 500-kb resolution of chromosome 1 in mouse zygotes and early embryos8 (equal number of reads generated from 2–3 biological independent replicates for each stage). d, e, Five-by-five contact enrichment maps of A–B compartments averaged over genomic positions using GC content in mouse early embryo Hi-C data8 (d) and ref. 7 (e). f, PC1 value distribution in human embryos and mitotic HeLa cells36.

Extended Data Fig. 4 A/B compartment switches during human embryonic development.

a, The percentage of genomic regions with A/B compartment switches from morula to 6-week stage, and the percentage of single A/B switched regions relative to total switched regions. b, Left, the box plot illustrates the gene expression dynamics with A/B compartment switches between human blastocysts and 6-week embryos (biological replicates pooled; blastocyst, n = 3; 6-week embryo, n = 2). P values are shown (one-sided Wilcoxon rank-sum test). Boxes represent the 25th, 50th and 75th percentiles and whiskers show 1.5× the interquartile range (b, df). Middle, PC1 heat map for A/B compartment switched regions. Heat map is sorted according to A/B compartment switched PC1 values. Right, GO enrichment for genes with A/B compartment switches between blastocysts and 6-week embryos using DAVID v.6.8. c, A/B compartment status around the NEFMNEFL locus in human blastocysts and 6-week embryos overlaid with gene expression. d, Unmethylated CpG (methylation level <0.25) density within A or B compartments in human sperm and embryos (biological replicates pooled; sperm, n = 3; morula, n = 2; blastocyst, n = 3; 6-week embryos, n = 2). P values are shown (one-sided Wilcoxon rank-sum test). e, Reduced CpG methylation level (ML) (MLsperm − MLblastocyst) in A compartments and B compartments of human blastocyst (biological replicates pooled; n = 3). P value is calculated by one-sided Wilcoxon rank-sum test. f, Reduced methylation level (MLsperm − MLblastocyst) for regions with A-to-A, A-to-B, B-to-A, and B-to-B compartment switches from human sperm to blastocysts (replicates pooled; n = 3). ***P < 0.001 for comparisons between ‘A-to-A’ and other groups (two-sided Wilcoxon rank-sum test). Right, randomly shuffled A/B compartment switched regions as control.

Extended Data Fig. 5 Human sperm have no typical TADs.

a, Interaction heat maps around Hoxa cluster in mouse sperm8,16 and mouse E3.5 embryos8. b, Density plot of interaction insert size for human sperm, human blastocysts and mouse sperm (Methods). c, Contact probability decay curve for human sperm, mouse sperm and metaphase HeLa cells. d, e, Examples of interaction heat maps at human and mouse conserved syntenic regions from unmixed sperm and mixed human and mouse sperm sample. Interaction heat maps in d (right) and e (right) are for HeLa and HT22 cells somatic cell mixed samples, respectively. f, Pearson correlation heat maps of chromosome 2 at 500-kb resolution in human sperm. Left, unmixed human sperm Hi-C. Right, human sperm from the mixed sperm sample (replicates pooled). g, RAD21 western blots and Ponceau staining of samples from somatic cell lines and human and mouse sperm. Black arrow indicates RAD21 band. Experiment repeated on two biologically independent replicates per sample. For gel source data, see Supplementary Fig. 1. h, Right, CTCF western blots in the control and knockdown cell lines (control and siCTCF HEK 293; control and siCTCF HeLa). Left, Ponceau staining. Black arrow indicates CTCF band. Experiment repeated on two biologically independent replicates per sample. For gel source data, see Supplementary Fig. 1.

Extended Data Fig. 6 Insulated boundary dynamics in human embryos and mouse embryos.

a, An example for insulated boundaries in human embryos as yellow arrows point in the 2-cell stage. Dark coloured regions in TAD separation score heat maps mean strong insulation. The bottom blue bars are insulated boundaries of each stage. The red bars are 200-kb collapsed boundaries. Grey boxes highlight the 200-kb collapsed boundaries. b, Heat map illustrating the insulation score at stage-specific gained insulated boundaries in mouse embryos. c, d, An example of shared ZGA boundaries in human embryos (c) and mouse embryos (d). Grey boxes highlight the shared 200-kb collapsed ZGA boundaries.

Extended Data Fig. 7 Analysis of housekeeping genes and repeat elements at insulated boundaries.

a, Cumulative distribution function plot for the distance of stage-specific gained boundaries to the closest housekeeping genes in mouse embryos8 (pooled data from 2–3 biological replicates). The dash line marks a distance of 200 kb; 2-cell versus 4-cell, P = 1.25 × 10−9; 2-cell versus 8-cell, P = 1.59 × 10−11 (two-sided Kolmogorov–Smirnov test). b, Gene expression (expression data from ref. 22; 8-cell, n = 20; morula, n = 16; blastocyst, n = 30) for housekeeping genes within 200 kb of the stage-specific gained boundaries and the other housekeeping genes at the stages when insulated boundaries are being formed. Boxes represent the 25th, 50th and 75th percentiles and whiskers show 1.5× the interquartile range. P values are shown (two-sided Wilcoxon rank-sum test). c–e, Enrichment analysis of repeat elements at stage-specific gained insulated boundaries in human embryos. Enrichment analysis of AluY repeats (c), LINE repeats (d) and MIR repeats (e). f–h, Enrichment analysis of repeat elements at stage-specific gained insulated boundaries in mouse embryos. Enrichment analysis of Alu repeats (f), LINE repeats (g) and MIR repeats (h). i, Examples of the earlier stage gained insulated boundary locating around Alu dense regions in human and mouse. j, Left, snapshot of insulated boundaries overlaid with insulation score, AluS density and housekeeping genes. Grey box highlights the 200-kb collapsed boundary. Right, expression of AluS repeats at this boundary. k, Expression z-score of AluS repeats locating at human 2-cell gained boundaries during human embryonic development (repeat expression data from ref. 21; n = 2 for each stage; for repeat expression calculation, see Methods). Average gene expression of AluS repeats within a boundary was used. The number of 2-cell gained boundaries with AluS repeats is shown (n = 442).

Extended Data Fig. 8 TAD establishment depends on ZGA in human embryos.

a, ZGA gene expression in human embryos and α-amanitin treated 8-cell embryos (pooled replicates; for data from ref. 22: oocyte, n = 3; zygote, n = 3; 2-cell, n = 6; 4-cell, n = 12; 8-cell, n = 20; morula, n = 16; blastocyst, n = 30; for data from this study: 8-cell, n = 2; α-amanitin treated 8-cell, n = 2). ZGA genes were identified as in ref. 22 (Methods). P values are calculated by the one-sided Wilcoxon rank-sum test. Boxes represent the 25th, 50th and 75th percentiles and whiskers show 1.5× the interquartile range. b, Gene expression for human ZGA genes DUXA and ZSCAN5B in control 8-cell and α-amanitin treated 8-cell embryos. c, The Spearman correlation for two α-amanitin treated 8-cell Hi-C replicates. d, Interaction heat maps of human 2-cell, 8-cell, unmixed α-amanitin treated 8-cell embryos and α-amanitin 8-cell from the mixed sample (Methods).

Extended Data Fig. 9 CTCF regulates TAD establishment in human embryos.

a, Gene expression for different cohesin complex subunits during human embryonic development. Expression data from ref. 20: oocyte, n = 3; zygote, n = 2; 2-cell, n = 3; 4-cell, n = 4; 8-cell, n = 11; morula, n = 3. Data are mean ± s.e.m. b, Dynamics of CTCF expression during human embryonic development. Expression data from refs. 20,21. Data are mean ± s.e.m. c, CTCF gene expression in control 8-cell and α-amanitin treated 8-cell embryos. d, Interaction heat maps of untreated control morula and siCTCF morula with equal reads at 50-kb resolution. Right, contrast heat map between control and siCTCF morula. Dark colour represents increased interactions in untreated morula compared with siCTCF morula. e, Violin plot for relative variance of TAD signal in 8-cell, control morula and siCTCF morula (equal number of reads generated from 2–3 biological replicates for each stage). P values are shown (two-sided Wilcoxon rank-sum test). The white boxes in the violin plot represent median values. f, Enrichment heat maps for the insulation score of control morula and siCTCF morula at control morula TAD boundaries (\(\pm \)600 kb). b, TAD boundary centre.

Extended Data Fig. 10 The change of FIRE score and gene expression in siCTCF morula.

a, Snapshot of FIREs in human blastocysts, 6-week embryos and H1 human ES cells overlaid with PC1 tracks and FIRE score tracks. One zoomed-in region in human blastocysts is also shown. b, Snapshot of FIREs in human morula and blastocysts overlaid with DHSs25 and A/B compartments. c, Bar plot showing FIREs enrichment and depletion in A/B compartments (replicates pooled; blastocyst, n = 3; 6-week, n = 2; H1 human ES cell, n = 2). P values are also shown (χ2 test). d, Box plot showing ATAC-seq reads24 signal at FIREs, non-FIREs and whole genome in human blastocysts. Boxes represent the 25th, 50th and 75th percentiles and whiskers show 1.5× the interquartile range. P values are also shown (two-sided Wilcoxon rank-sum test). e, Box plot showing DNase-seq reads25 signal at FIREs, non-FIREs and whole genome in human blastocysts. Boxes represent the 25th, 50th and 75th percentiles and whiskers show 1.5× the interquartile range. P values are also shown (two-sided Wilcoxon rank-sum test). f, Histograms of FIRE score difference between siCTCF and untreated control morula (siCTCF − untreated) in FIREs and non-FIREs for siCTCF morula no. 1, siCTCF morula no. 2 and siCTCF morula no. 3. P values for differential FIREscore (siCTCF − untreated) in FIREs and non-FIREs are also shown (one-sided t-test). g, The hierarchical cluster of gene expression in control morula and siCTCF morula analysed using the package ggdendro. h, Scatter plot of gene expression between control morula and siCTCF morula. Red dots refer to upregulated genes (254 genes) in siCTCF morula. Blue dots refers to downregulated genes (565 genes) in siCTCF morula. i, Heat map for human ES cell CTCF ChIP–seq signal47 around gene TSSs downregulated in siCTCF morula. Strongly downregulated genes (log2(fold change(siCTCF/control)) < −5).

Extended Data Fig. 11 TADs cannot re-establish in 8-cell (α-amanitin plus CTCF mRNA) embryos.

a, Immunofluorescence confocal images of CTCF in α-amanitin treated 8-cell embryos (n = 2) and 8-cell (α-amanitin plus CTCF mRNA) embryos (n = 3). Scale bar, 40 μm. b, Track snapshot for TAD structures in 8-cell (α-amanitin plus CTCF mRNA) embryos along with untreated 2-cell, 8-cell and morula embryos. c, d, Interaction heat map examples at 50-kb resolution for human 8-cell embryos and 8-cell (α-amanitin plus CTCF mRNA) embryos. e, Interaction heat map examples for mouse morula embryos without mix and mouse morula from the α-amanitin plus CTCF mRNA mixed sample (Methods). f, Enrichment heat maps for the insulation score of human 2-cell embryos, 8-cell embryos, α-amanitin 8-cell embryos, 8-cell (α-amanitin plus CTCF mRNA) embryos and morula embryos around boundaries (± 600 kb). b, boundary centre. Left, boundaries gained at 2-cell stage; right, boundaries gained at 8-cell stage. g, Bar plots for TAD structure strength of human embryos and mouse morula from mixed samples. Left y axis, human embryos; right y axis, mouse morula.

Supplementary information

Supplementary Figure

Supplementary Figure 1: gel source data.

Reporting Summary

Supplementary Table

Table S1: Data summary for human sperm and embryos Hi-C.

Supplementary Table

Table S2: TADs in human embryos based on TAD separation score method.

Supplementary Table

Table S3: GO terms for genes with A/B compartment switches.

Supplementary Table

Table S4: Human embryo stage-gained insulated boundaries.

Supplementary Table

Table S5: Mouse embryo stage-gained insulated boundaries.

Supplementary Table

Table S6: Data summary for the NGS of amanitin-treated embryos and CTCF siRNA knockdown embryos.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Chen, X., Ke, Y., Wu, K. et al. Key role for CTCF in establishing chromatin structure in human embryos. Nature 576, 306–310 (2019). https://doi.org/10.1038/s41586-019-1812-0

Download citation

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing