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Maternal factor NELFA drives a 2C-like state in mouse embryonic stem cells

Nature Cell Biology volume 22, pages 175–186 (2020)Cite this article

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Abstract

Mouse embryonic stem cells (ESCs) sporadically transit into an early embryonic-like state characterized by the expression of 2-cell (2C) stage-restricted transcripts. Here, we identify a maternal factor—negative elongation factor A (NELFA)—whose heterogeneous expression in mouse ESCs is coupled to 2C gene upregulation and expanded developmental potential in vivo. We show that NELFA partners with Top2a in an interaction specific to the 2C-like state, and that it drives the expression of Dux—a key 2C regulator. Accordingly, loss of NELFA and/or Top2a suppressed Dux activation. Further characterization of 2C-like cells uncovered reduced glycolytic activity; remarkably, mere chemical suppression of glycolysis was sufficient to promote a 2C-like fate, obviating the need for genetic manipulation. Global chromatin state analysis on NELFA-induced cells revealed decommissioning of ESC-specific enhancers, suggesting ESC-state impediments to 2C reversion. Our study positions NELFA as one of the earliest drivers of the 2C-like state and illuminates factors and processes that govern this transition.

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Fig. 1: The maternal factor NELFA is heterogeneously expressed in mESCs.
Fig. 2: NELFAhigh mESCs mark a 2C-like state.
Fig. 3: NELFA is a driver of the 2C-like state.
Fig. 4: NELFA activates 2C genes through Dux.
Fig. 5: NELFA cooperates with TOP2A to activate Dux.
Fig. 6: Suppression of glycolysis by 2-DG induces the 2C-like transcriptional program.
Fig. 7: Exit from naïve pluripotency is required for activation of the 2C-like state.

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Data availability

RNA-Seq, ChIP-Seq and ATAC-Seq data that support the findings of this study have been deposited in the GEO under accession code GSE113671. Previously published RNA-Seq data that were re-analysed here are available under accession codes GSE51682 (Zscan4high), GSE85627 (siCAF-1 and Dux overexpression), GSE33923 (MERVL-tdTomatohigh), GSE66582 (pre-implantation mouse embryos of different developmental stages), and ERP005641 (European Nucleotide Archive: https://www.ebi.ac.uk/ena/data/view/PRJEB6168) and GSE89303 (extended pluripotency stem cells). Published ChIP-Seq data for DUX are available under accession code GSE85632. All other data supporting the findings of this study are available from the corresponding author upon reasonable request. Source data for Figs. 2–7 and Extended Data Figs. 1–7, 9 and 10 are available online.

Code availability

All of the codes used are available on request.

References

  1. Ishiuchi, T. & Torres-Padilla, M. E. Towards an understanding of the regulatory mechanisms of totipotency. Curr. Opin. Genet. Dev. 23, 512–518 (2013).

    Article  CAS  PubMed  Google Scholar 

  2. Wu, G. & Scholer, H. R. Lineage segregation in the totipotent embryo. Curr. Topics Dev. Biol. 117, 301–317 (2016).

    Article  Google Scholar 

  3. Zhou, L. Q. & Dean, J. Reprogramming the genome to totipotency in mouse embryos. Trends Cell Biol. 25, 82–91 (2015).

    Article  CAS  PubMed  Google Scholar 

  4. Hamatani, T., Carter, M. G., Sharov, A. A. & Ko, M. S. Dynamics of global gene expression changes during mouse preimplantation development. Dev. Cell 6, 117–131 (2004).

    Article  CAS  PubMed  Google Scholar 

  5. Falco, G. et al. Zscan4: a novel gene expressed exclusively in late 2-cell embryos and embryonic stem cells. Dev. Biol. 307, 539–550 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. De Iaco, A. et al. DUX-family transcription factors regulate zygotic genome activation in placental mammals. Nat. Genet. 49, 941–945 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Fadloun, A. et al. Chromatin signatures and retrotransposon profiling in mouse embryos reveal regulation of LINE-1 by RNA. Nat. Struct. Mol. Biol. 20, 332–338 (2013).

    Article  CAS  PubMed  Google Scholar 

  9. Peaston, A. E. et al. Retrotransposons regulate host genes in mouse oocytes and preimplantation embryos. Dev. Cell 7, 597–606 (2004).

    Article  CAS  PubMed  Google Scholar 

  10. Macfarlan, T. S. et al. Embryonic stem cell potency fluctuates with endogenous retrovirus activity. Nature 487, 57–63 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Beddington, R. S. & Robertson, E. J. An assessment of the developmental potential of embryonic stem cells in the midgestation mouse embryo. Development 105, 733–737 (1989).

    Article  CAS  PubMed  Google Scholar 

  12. Svoboda, P. Mammalian zygotic genome activation. Semin. Cell Dev. Biol. 84, 118–126 (2018).

    Article  CAS  PubMed  Google Scholar 

  13. Adelman, K. & Lis, J. T. Promoter-proximal pausing of RNA polymerase II: emerging roles in metazoans. Nat. Rev. Genet. 13, 720–731 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Wu, J. et al. The landscape of accessible chromatin in mammalian preimplantation embryos. Nature 534, 652–657 (2016).

    Article  CAS  PubMed  Google Scholar 

  15. Deng, Q., Ramskold, D., Reinius, B. & Sandberg, R. Single-cell RNA-Seq reveals dynamic, random monoallelic gene expression in mammalian cells. Science 343, 193–196 (2014).

    Article  CAS  PubMed  Google Scholar 

  16. Ishiuchi, T. et al. Early embryonic-like cells are induced by downregulating replication-dependent chromatin assembly. Nat. Struct. Mol. Biol. 22, 662–671 (2015).

    Article  CAS  PubMed  Google Scholar 

  17. Ancelin, K. et al. Maternal LSD1/KDM1A is an essential regulator of chromatin and transcription landscapes during zygotic genome activation. eLife 5, e08851 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  18. Hatanaka, Y. et al. Histone chaperone CAF-1 mediates repressive histone modifications to protect preimplantation mouse embryos from endogenous retrotransposons. Proc. Natl Acad. Sci. USA 112, 14641–14646 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Liu, X. et al. Distinct features of H3K4me3 and H3K27me3 chromatin domains in pre-implantation embryos. Nature 537, 558–562 (2016).

    Article  CAS  PubMed  Google Scholar 

  20. Akiyama, T. et al. Transient bursts of Zscan4 expression are accompanied by the rapid derepression of heterochromatin in mouse embryonic stem cells. DNA Res. 22, 307–318 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Zalzman, M. et al. Zscan4 regulates telomere elongation and genomic stability in ES cells. Nature 464, 858–863 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Choi, Y. J. et al. Deficiency of microRNA miR-34a expands cell fate potential in pluripotent stem cells. Science 355, eaag1927 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  23. Williams, L. H. et al. Pausing of RNA polymerase II regulates mammalian developmental potential through control of signaling networks. Mol. Cell 58, 311–322 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Wong, M. M., Belew, M. D., Kwieraga, A., Nhan, J. D. & Michael, W. M. Programmed DNA breaks activate the germline genome in Caenorhabditis elegans. Dev. Cell 46, 302–315.e5 (2018).

    Article  CAS  PubMed  Google Scholar 

  26. Carbognin, E., Betto, R. M., Soriano, M. E., Smith, A. G. & Martello, G. Stat3 promotes mitochondrial transcription and oxidative respiration during maintenance and induction of naive pluripotency. EMBO J. 35, 618–634 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Koche, R. P. et al. Reprogramming factor expression initiates widespread targeted chromatin remodeling. Cell Stem Cell 8, 96–105 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Ying, Q.-L. et al. The ground state of embryonic stem cell self-renewal. Nature 453, 519–523 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Ma, Z., Swigut, T., Valouev, A., Rada-Iglesias, A. & Wysocka, J. Sequence-specific regulator Prdm14 safeguards mouse ESCs from entering extraembryonic endoderm fates. Nat. Struct. Mol. Biol. 18, 120–127 (2011).

    Article  CAS  PubMed  Google Scholar 

  30. Yamaji, M. et al. PRDM14 ensures naive pluripotency through dual regulation of signaling and epigenetic pathways in mouse embryonic stem cells. Cell Stem Cell 12, 368–382 (2013).

    Article  CAS  PubMed  Google Scholar 

  31. Grabole, N. et al. Prdm14 promotes germline fate and naive pluripotency by repressing FGF signalling and DNA methylation. EMBO Rep. 14, 629–637 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Akimitsu, N. et al. Enforced cytokinesis without complete nuclear division in embryonic cells depleting the activity of DNA topoisomerase IIα. Genes Cells 8, 393–402 (2003).

    Article  CAS  PubMed  Google Scholar 

  33. Chen, Z. & Zhang, Y. Loss of DUX causes minor defects in zygotic genome activation and is compatible with mouse development. Nat. Genet. 1, 947–951 (2019).

    Article  CAS  Google Scholar 

  34. Eckersley-Maslin, M. et al. Dppa2 and Dppa4 directly regulate the Dux-driven zygotic transcriptional program. Genes Dev. 33, 194–208 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. De Iaco, A., Coudray, A., Duc, J. & Trono, D. DPPA2 and DPPA4 are necessary to establish a 2C-like state in mouse embryonic stem cells. EMBO Rep 20, e47382 (2019).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  36. Houghton, F. D., Thompson, J. G., Kennedy, C. J. & Leese, H. J. Oxygen consumption and energy metabolism of the early mouse embryo. Mol. Reprod. Dev. 44, 476–485 (1996).

    Article  CAS  PubMed  Google Scholar 

  37. Brinster, R. L. & Troike, D. E. Requirements for blastocyst development in vitro. J. Anim. Sci. 49, 26–34 (1979).

    Article  PubMed  Google Scholar 

  38. Baumann, C. G., Morris, D. G., Sreenan, J. M. & Leese, H. J. The quiet embryo hypothesis: molecular characteristics favoring viability. Mol. Reprod. Dev. 74, 1345–1353 (2007).

    Article  CAS  PubMed  Google Scholar 

  39. Leese, H. J. Metabolic control during preimplantation mammalian development. Hum. Reprod. Update 1, 63–72 (1995).

    Article  CAS  PubMed  Google Scholar 

  40. Barbehenn, E. K., Wales, R. G. & Lowry, O. H. The explanation for the blockade of glycolysis in early mouse embryos. Proc. Natl Acad. Sci. USA 71, 1056–1060 (1974).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Sturmey, R., Reis, A., Leese, H. & McEvoy, T. Role of fatty acids in energy provision during oocyte maturation and early embryo development. Reprod. Domest. Anim. 44, 50–58 (2009).

    Article  PubMed  Google Scholar 

  42. Nagaraj, R. et al. Nuclear localization of mitochondrial TCA cycle enzymes as a critical step in mammalian zygotic genome activation. Cell 168, 210–223.e11 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Rodriguez-Terrones, D. et al. A molecular roadmap for the emergence of early-embryonic-like cells in culture. Nat. Genet. 50, 106–119 (2018).

    Article  CAS  PubMed  Google Scholar 

  44. Macfarlan, T. S. et al. Endogenous retroviruses and neighboring genes are coordinately repressed by LSD1/KDM1A. Genes Dev. 25, 594–607 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Maksakova, I. A. et al. Distinct roles of KAP1, HP1 and G9a/GLP in silencing of the two-cell-specific retrotransposon MERVL in mouse ES cells. Epigenetics Chromatin 6, 15 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Suzuki, A. et al. Loss of MAX results in meiotic entry in mouse embryonic and germline stem cells. Nat. Commun. 7, 11056 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Reid, M. A., Dai, Z. & Locasale, J. W. The impact of cellular metabolism on chromatin dynamics and epigenetics. Nat. Cell Biol. 19, 1298–1306 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Cluntun, A. A. et al. The rate of glycolysis quantitatively mediates specific histone acetylation sites. Cancer Metab. 3, 10 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Mentch, S. J. et al. Histone methylation dynamics and gene regulation occur through the sensing of one-carbon metabolism. Cell Metab. 22, 861–873 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Kim, H. et al. Core pluripotency factors directly regulate metabolism in embryonic stem cell to maintain pluripotency. Stem Cells 33, 2699–2711 (2015).

    Article  CAS  PubMed  Google Scholar 

  51. Hu, Z. & Tee, W.-W. Enhancers and chromatin structures: regulatory hubs in gene expression and diseases. Biosci. Rep. 37, BSR20160183 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Fu, X., Wu, X., Djekidel, M. N. & Zhang, Y. Myc and Dnmt1 impede the pluripotent to totipotent state transition in embryonic stem cells. Nat. Cell Biol. 21, 835–844 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Zhao, T. et al. Single-cell RNA-Seq reveals dynamic early embryonic-like programs during chemical reprogramming. Cell Stem Cell 23, 31–45.e7 (2018).

    Article  CAS  PubMed  Google Scholar 

  54. Yang, J. et al. Establishment of mouse expanded potential stem cells. Nature 550, 393–397 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Yang, Y. et al. Derivation of pluripotent stem cells with in vivo embryonic and extraembryonic potency. Cell 169, 243–257.e25 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Whyte, W. A. et al. Master transcription factors and mediator establish super-enhancers at key cell identity genes. Cell 153, 307–319 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Bi, X. et al. Proteomic profiling of barley spent grains guides enzymatic solubilization of the remaining proteins. Appl. Microbiol. Biotechnol. 102, 4159–4170 (2018).

    Article  CAS  PubMed  Google Scholar 

  58. Corces, M. R. et al. An improved ATAC-Seq protocol reduces background and enables interrogation of frozen tissues. Nat. Methods 14, 959–962 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Criscione, S. W., Zhang, Y., Thompson, W., Sedivy, J. M. & Neretti, N. Transcriptional landscape of repetitive elements in normal and cancer human cells. BMC Genomics 15, 583 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  61. 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).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  62. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

  64. Yu, G., Wang, L. G., Han, Y. & He, Q. Y. clusterProfiler: an R package for comparing biological themes among gene clusters. Omics 16, 284–287 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Ashburner, M. et al. Gene Ontology: tool for the unification of biology. Nat. Genet. 25, 25–29 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Ogata, H. et al. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 27, 29–34 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  69. Yu, G., Wang, L.-G. & He, Q.-Y. ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics 31, 2382–2383 (2015).

    Article  CAS  PubMed  Google Scholar 

  70. Ramirez, F., Dundar, F., Diehl, S., Gruning, B. A. & Manke, T. deepTools: a flexible platform for exploring deep-sequencing data. Nucleic Acids Res. 42, W187–W191 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We thank M. Ko (Keio University School of Medicine) for the kind gift of Zscan4-Emerald reporter mESCs, M. E. Torres-Padilla (IES/Helmholtz Zentrum München) for the Zscan4-mCherry construct, D. Trono (École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland) for the Dux knockout and wild-type mESCs, G. Almouzni and J.-P. Quivy (CNRS/Institut Curie) for the CAF-1 antibodies, and D. A. Silva (BMSI, A*STAR), P. Hutchinson and T. Guo Hui (LSI, NUS) for excellent help with the flow cytometry. This research is supported by National Research Foundation (NRF) Singapore, under the NRF fellowship to W.-W.T. (NRF-NRFF2016-06) and Biomedical Research Council, Agency for Science, Technology and Research (1531C00144).

Author information

Author notes

  1. These authors contributed equally: Zhenhua Hu, Dennis Eng Kiat Tan, Gloryn Chia.

Authors and Affiliations

  1. Chromatin Dynamics and Disease Epigenetics Group, Institute of Molecular and Cell Biology, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore

    Zhenhua Hu, Dennis Eng Kiat Tan, Haihan Tan, Hwei Fen Leong, Benjamin Jieming Chen, Mei Sheng Lau & Wee-Wei Tee

  2. Department of Pharmacy, National University of Singapore, Singapore, Singapore

    Gloryn Chia

  3. Bioprocessing Technology Institute, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore

    Kelly Yu Sing Tan, Xuezhi Bi, Dongxiao Yang & Ying Swan Ho

  4. Duke-NUS Medical School, Singapore, Singapore

    Xuezhi Bi

  5. Research Centre for Animal Genetic Resources of Mongolia Plateau, College of Life Sciences, Inner Mongolia University, Hohhot, China

    Baojiang Wu & Siqin Bao

  6. Laboratory of Developmental and Regenerative Biology, Institute of Medical Biology, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore

    Esther Sook Miin Wong

  7. Department of Physiology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore

    Wee-Wei Tee

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  1. Zhenhua Hu
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Contributions

Z.H. performed all of the computational analyses and analysed the data. D.E.K.T. and G.C. performed the majority of the experiments and analysed the data. K.Y.S.T., X.B., Y.S.H., D.Y., H.F.L., B.J.C., H.T., M.S.L., B.W., S.B. and E.S.M.W. provided experimental support. W.-W.T. conceived of and designed the study, analysed the data and wrote the manuscript with contributions from all authors.

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Correspondence to Wee-Wei Tee.

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Extended data

Extended Data Fig. 1 Stage-specific expression profiles.

a, Boxplots showing distinct stage-specific gene expression patterns during mouse pre-implantation development15. C1-C7, the seven clusters identified from Fig. 1a14. Number of genes (n) in C1 to C7 is 2072, 1595, 140, 445, 761, 1685, and 898 respectively. Center line, median; box limits, upper and lower quartiles; whiskers, 1.5× interquartile range. b, NELFA showing distinct stage-specific expression in mouse pre-implantation embryos. Left panel: schematic depiction of the NELF (Negative Elongation Factor) complex, consisting of NELFA, NELFB, NELFC/D and NELFE subunits. Right panel: relative expression of NELF subunits in mouse pre-implantation embryos14. c, Immunofluorescence staining of Oct4 (red), NELFE (green upper panel) and NELFB (green lower panel) in mESCs, showing uniform expression of these factors. Scale bar = 20 μm.

Source data

Extended Data Fig. 2 NELFA is a potent driver of the 2C state.

a, RT-qPCR validation of selected 2C genes in NELFA reporter mESCs. The plot is generated with n=3 technical replicates from two independent experiments, with similar results obtained. b, Immunofluorescence for various 2C-like markers (as indicated) in Zscan4-Emerald reporter mESCs. Representative images are shown from two independent experiments. Quantification of expression of the markers in individual cells was performed based on the immunofluorescence data. Scale bar = 20 µm. c, NELFAhigh-upregulated genes (n=1086) are specifically enriched in various 2C-like mESC transcriptomes. Boxplots showing the relative expression of NELFAhigh-upregulated genes (Up) and other genes (Rest) in 2C-like cells induced by CAF-1 inhibition (left panel), Dux overexpression (middle panel), and Zscan4-positive ESCs (right panel) respectively. Center line, median; box limits, upper and lower quartiles; whiskers, 1.5× interquartile range. p-values determined by two-tailed Student’s T-tests.

Source data

Extended Data Fig. 3 NELFA-induced cells are 2C-like.

a, NELFA-induced genes (n=229) are specifically upregulated in 2C-like transcriptomes. Boxplots showing the relative expression of NELFA-induced genes (Up) and non-induced genes (Rest) in various 2C-like cells, namely mESCs induced by CAF-1 knockdown7 (upper left panel) and Dux overexpression7 (upper right), our NELFAhigh cells (bottom-left), and Zscan4-positive mESCs20 (bottom-right) respectively. Center line, median; box limits, upper and lower quartiles; whiskers, 1.5× interquartile range. p-values determined by two-tailed Student’s T-tests. b, RT-qPCR analysis of select 2C genes in mESCs following overexpression of NELFA, as function of NELFB and NELFE knockdown. Plot is representative of n=2 independent experiment with similar results obtained, with mean from two independent experiments represented as bar graph. c, 2C-like genes from various 2C-like cell models (NELFAhigh, n=1086; NELFA(+Dox), n=229; Dux(+Dox), n=2236; Zscan4high, n=456) are enriched within ATAC-gained region linked genes (n=4002), but depleted within ATAC-lost region linked genes (n=10332), in NELFA-induced 2C-like cells. ATAC regions were annotated to genes using GREAT24, and p-values were determined by Chi-squared tests, assuming a background of 20,000 genes.

Source data

Extended Data Fig. 4 NELFA (HA) ChIP-qPCR validation.

a, NELFA (HA) ChIP-qPCR validation of NELFA occupancy at Dux and Zscan4c promoter regions. Percent input values shown are normalized against -Dox untreated control condition. Dots represent n=3 technical replicates from two independent experiments. Primers are listed in Supplementary Table 11. b, Pie chart detailing the genomic distribution of NELFA (HA) ChIP-seq peaks.

Source data

Extended Data Fig. 5 Suppressed glycolysis is a feature of 2C-like cells.

a, GSEA enrichment plot for metabolic pathways (mmu01100) in the respective cell lines. The leading gene list is in Supplementary Table 10. b, Left panel: box plots charting distribution of changes in glycolysis genes (n=65 genes; mmu00010) in the respective cell lines. Right panel: bar charts showing expression of glucose transporters genes in the respective cell lines. c, RT-qPCR analysis of key glycolysis genes (top panel) and ATAC-seq signals (bottom panel) in both NELFA- and Dux-induced 2C-like cells. n=3 and n=2 biological replicates for Dux and NELFA induction, respectively. d, 2-NBDG staining in Zscan4-mCherry reporter mESCs. Scale bar = 20 µm. Three independent experiments were performed. N numbers represent ESCs and are indicated on the graph. e, Representative FACS analysis of Zscan4-Em reporter mESCs after 2-DG treatment. 3 independent experiments. f, Representative FACS analysis of Annexin-V PE-stained NELFA reporter mESCs, with and without 2-DG treatment (upper panel). Assessment of cell cytotoxicity and proliferation rate as a function of 2-DG treatment (middle and lower panels), g, Representative FACS analysis of NELFA reporter cells following rotenone treatment (upper panel). Representative microscope images of mESCs following rotenone treatment (second panel from top). Scale bar = 200 µm. Assessment of cell cytotoxicity and proliferation rate following rotenone treatment (bottom 2 panels). h, 2-DG-induced genes (n=175) are specifically upregulated in 2C-like transcriptomes. Boxplots showing the relative expression of 2-DG-induced genes (Up) and non-induced genes (Rest) in various 2C-like cells. i, RT-qPCR analysis showing impaired activation of 2C genes upon 2-DG treatment and knockdown of NELFA, n=3 biological replicates. Center line, median; box limits, upper and lower quartiles; whiskers, 1.5× interquartile range (b, h). Data presented as the mean ± s.e.m of n = 3 independent experiments (f, g). p-values determined by two-tailed Student’s T-test (c, e, g, h, i).

Source data

Extended Data Fig. 6 Top2a is involved in the activation of Dux by NELFA.

a, Reciprocal co-IP western analysis in 2-DG-treated mESCs, showing robust interaction between Top2a and NELFA specifically upon 2-DG treatment. Co-IP of NELFA (HA) (left panel) and Top2a (right panel) with and without 2-DG treatment. Two independent experiments were performed, with similar results. b, RT-qPCR analysis of Dux following transient Top2a knockdown and 2-DG treatment. Mean is represented as bar graph derived from n=3 independent experiments and p-values are determined using a two-tailed Student’s T-tests. Unprocessed western blots are shown in Source Extended data Fig. 6.

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Extended Data Fig. 7 Naïve mESC culture conditions restrict expression of 2C genes.

a, Metagene analysis of ATAC-seq signals in pre-implantation mouse embryos of different developmental stages (left panel) and Dux-overexpressing cells (right panel) across ESC-specific enhancers, including super-enhancers and typical enhancers. Enhancer intervals were obtained from published data56. b, FACS analysis of NELFA-StrepHA-P2A-EGFP mESCs cultured in naïve, serum-free ESC conditions (N2B27/2i/LIF), showing the loss of the NELFAhigh subpopulation under naïve conditions. Representative data from three independent experiments. Representative phase contrast and EGFP fluorescence images are also shown. Scale bar = 200 µm. c, General FACS gating strategy.

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Extended Data Fig. 8 NELFA induction triggers extensive chromatin remodeling.

Left panel: Immunofluorescence for EGFP (marking NELFA; green) in NELFA reporter mESCs reveals structural changes in heterochromatin. 5 independent experiments were performed, with similar results. Right panel: Immunofluorescence for HA (marking NELFA; green) and Zscan4 (magenta) in Dox-induced NELFA-StrepHA-P2A-EGFP mESCs reveals structural changes in heterochromatin. DAPI (blue) staining depicts the different extents of chromatin decondensation. Cells demarcated by white dotted boxes are shown in magnification. Data is representative of 3 independent experiments. Scale bar = 20 µm.

Extended Data Fig. 9 Assessing metabolic requirements of 2C-like cells.

a, FACS analysis of NELFA reporter cells following 4 and 14 days of 2-DG treatment. Two independent experiments were performed, with similar results. b, FACS analysis of NELFA reporter cells under different culture conditions as indicated. Two independent experiments were performed, with similar results. c, Confocal images of Aco2 and Idh3a in both NELFA reporter and NELFA-inducible mESCs. Representative images of two independent experiments are shown. Scale bar = 20 μm.

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Extended Data Fig. 10 H3K27me3 decreased across 2C genes following 2-DG treatment and CAF-1 is depleted in NELFA induced cells.

a, ChIP-qPCR quantification of H3K27me3 in NELFA reporter mESCs, with and without 2-DG treatment. Fold change < 1 indicates loss of this histone modification at the tested locus. Chromosome 2 subtelomeric region serves as a negative control. Dots represent n=3 technical replicates from two independent experiments. The primers used are listed in Supplementary Table 11. b, Immunofluorescence for HA (marking NELFA; green) and the CAF-1 p60 subunit (magenta) in NELFA-induced mESCs. Quantification of expression of the markers in individual cells was performed based on the immunofluorescence data. N number represents ESCs and is indicated on the graph. Two independent experiments were performed, with similar results. Scale bar = 20 µm.

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Supplementary information

Reporting Summary

Supplementary Tables 1–13

Supplementary Table 1: Mouse pre-implantation stage-specific gene list. Supplementary Table 2: Differentially expressed genes and repetitive elements in the NELFA reporter. Supplementary Table 3: Differentially expressed genes and repetitive elements in Dox-inducible NELFA mESCs. Supplementary Table 4: Differentially expressed genes and repetitive elements in DUXWT_NELFApos_VS_NELFAneg. Supplementary Table 5: Differentially expressed genes and repetitive elements in DUXKO_NELFApos_VS_NELFAneg. Supplementary Table 6: NELFA co-immunoprecipitation liquid chromatography with tandem mass spectrometry. Supplementary Table 7: GSEA analysis against the Kyoto Encyclopedia of Genes and Genomes database for NELFAhigh and Dox-inducible NELFA mESCs. Supplementary Table 8: Differentially expressed genes and repetitive elements in 2-DG-treated NELFA reporter mESCs. Supplementary Table 9: Annotation of ATAC-gained and ATAC-lost regions. Supplementary Table 10: Leading-edge genes for metabolic pathways Kyoto Encyclopedia of Genes and Genomes GSEA. Supplementary Table 11: List of primers used. Supplementary Table 12: List of siRNA used. Supplementary Table 13: List of antibodies used.

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Hu, Z., Tan, D.E.K., Chia, G. et al. Maternal factor NELFA drives a 2C-like state in mouse embryonic stem cells. Nat Cell Biol 22, 175–186 (2020). https://doi.org/10.1038/s41556-019-0453-8

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