Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

Esrrb guides naive pluripotent cells through the formative transcriptional programme

Nature Cell Biology volume 25, pages 643–657 (2023)Cite this article

Subjects

Abstract

During embryonic development, naive pluripotent epiblast cells transit to a formative state. The formative epiblast cells form a polarized epithelium, exhibit distinct transcriptional and epigenetic profiles and acquire competence to differentiate into all somatic and germline lineages. However, we have limited understanding of how the transition to a formative state is molecularly controlled. Here we used murine embryonic stem cell models to show that ESRRB is both required and sufficient to activate formative genes. Genetic inactivation of Esrrb leads to illegitimate expression of mesendoderm and extra-embryonic markers, impaired formative expression and failure to self-organize in 3D. Functionally, this results in impaired ability to generate formative stem cells and primordial germ cells in the absence of Esrrb. Computational modelling and genomic analyses revealed that ESRRB occupies key formative genes in naive cells and throughout the formative state. In so doing, ESRRB kickstarts the formative transition, leading to timely and unbiased capacity for multi-lineage differentiation.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Transcriptional changes associated with irreversible exit from naive pluripotency.
Fig. 2: Differentiation reversibility is associated with Esrrb expression.
Fig. 3: Esrrb promotes the expression of formative genes.
Fig. 4: Esrrb promotes the expression of formative genes.
Fig. 5: Esrrb coordinates the activation of naive and formative programmes.
Fig. 6: Esrrb is required for generation of FS cells.
Fig. 7: Differentiation towards PGCs is impaired by loss of Esrrb.
Fig. 8: Impaired lumenogenesis in Esrrb KO 3D structures.

Similar content being viewed by others

Data availability

Sequencing data that support the findings of this study have been deposited in the Gene Expression Omnibus (GEO) under accession code GSE184137. Previously published RNA-seq and CUT&RUN data that were re-analysed here are available under accession codes GSE23943 and GSE146863. Primers, oligonucleotides sequences and antibodies are presented in Supplementary Tables 4–6. Source data are provided with this paper. All other data supporting the findings of this study are available from the corresponding author on reasonable request.

Code availability

Data files and models used to build the ABN are available at https://github.com/kuglerh/Esrrb. The code used to build the ABN has been described in refs. 17,39,63 and made publicly available on GitHub at https://github.com/fsprojects/ReasoningEngine.

References

  1. Boroviak, T., Loos, R., Bertone, P., Smith, A. & Nichols, J. The ability of inner-cell-mass cells to self-renew as embryonic stem cells is acquired following epiblast specification. Nat. Cell Biol. 16, 516–528 (2014).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  2. Kinoshita, M. & Smith, A. Pluripotency deconstructed. Dev. Growth Differ. 60, 44–52 (2018).

    Article  PubMed  Google Scholar 

  3. Morgani, S., Nichols, J. & Hadjantonakis, A.-K. The many faces of pluripotency: in vitro adaptations of a continuum of in vivo states. BMC Dev. Biol. 17, 7 (2017).

    Article  PubMed Central  PubMed  Google Scholar 

  4. Bedzhov, I. & Zernicka-Goetz, M. Self-organizing properties of mouse pluripotent cells initiate morphogenesis upon implantation. Cell 156, 1032–1044 (2014).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  5. Endoh, M. & Niwa, H. Stepwise pluripotency transitions in mouse stem cells. EMBO Rep. 23, e55010 (2022).

    Article  CAS  PubMed  Google Scholar 

  6. Smith, A. Formative pluripotency: the executive phase in a developmental continuum. Development 144, 365–373 (2017).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  7. Pera, M. F. & Rossant, J. The exploration of pluripotency space: charting cell state transitions in peri-implantation development. Cell Stem Cell 28, 1896–1906 (2021).

    Article  CAS  PubMed  Google Scholar 

  8. Buecker, C. et al. Reorganization of enhancer patterns in transition from naive to primed pluripotency. Cell Stem Cell 14, 838–853 (2014).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  9. Hayashi, K., Ohta, H., Kurimoto, K., Aramaki, S. & Saitou, M. Reconstitution of the mouse germ cell specification pathway in culture by pluripotent stem cells. Cell 146, 519–532 (2011).

    Article  CAS  PubMed  Google Scholar 

  10. Kalkan, T. et al. Tracking the embryonic stem cell transition from ground state pluripotency. Development 144, 1221–1234 (2017).

    CAS  PubMed Central  PubMed  Google Scholar 

  11. Meissner, A. Epigenetic modifications in pluripotent and differentiated cells. Nat. Biotechnol. 28, 1079–1088 (2010).

    Article  CAS  PubMed  Google Scholar 

  12. Evans, M. J. & Kaufman, M. H. Establishment in culture of pluripotential cells from mouse embryos. Nature 292, 154–156 (1981).

    Article  CAS  PubMed  Google Scholar 

  13. Martin, G. R. Isolation of a pluripotent cell line from early mouse embryos cultured in medium conditioned by teratocarcinoma stem cells. Proc. Natl Acad. Sci. USA 78, 7634–7638 (1981).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  14. Smith, A. G. et al. Inhibition of pluripotential embryonic stem cell differentiation by purified polypeptides. Nature 336, 688–690 (1988).

    Article  CAS  PubMed  Google Scholar 

  15. Williams, R. L. et al. Myeloid leukaemia inhibitory factor maintains the developmental potential of embryonic stem cells. Nature 336, 684–687 (1988).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  17. Dunn, S.-J., Martello, G., Yordanov, B., Emmott, S. & Smith, A. G. Defining an essential transcription factor program for naïve pluripotency. Science 344, 1156–1160 (2014).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  18. Wray, J., Kalkan, T. & Smith, A. G. The ground state of pluripotency. Biochem. Soc. Trans. 38, 1027–1032 (2010).

    Article  CAS  PubMed  Google Scholar 

  19. Kinoshita, M. et al. Capture of mouse and human stem cells with features of formative pluripotency. Cell Stem Cell 28, 453–471.e8 (2021).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  20. Betschinger, J. et al. Exit from pluripotency is gated by intracellular redistribution of the bHLH transcription factor Tfe3. Cell 153, 335–347 (2013).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  21. Ying, Q.-L., Stavridis, M., Griffiths, D., Li, M. & Smith, A. Conversion of embryonic stem cells into neuroectodermal precursors in adherent monoculture. Nat. Biotechnol. 21, 183–186 (2003).

    Article  CAS  PubMed  Google Scholar 

  22. Festuccia, N. et al. Esrrb is a direct Nanog target gene that can substitute for Nanog function in pluripotent cells. Cell Stem Cell 11, 477–490 (2012).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  23. Ivanova, N. et al. Dissecting self-renewal in stem cells with RNA interference. Nature 442, 533–538 (2006).

    Article  CAS  PubMed  Google Scholar 

  24. Martello, G. et al. Esrrb is a pivotal target of the Gsk3/Tcf3 axis regulating embryonic stem cell self-renewal. Cell Stem Cell 11, 491–504 (2012).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  25. Zhang, M. et al. Esrrb complementation rescues development of Nanog-null germ cells. Cell Rep. 22, 332–339 (2018).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  26. Qiu, D. et al. Klf2 and Tfcp2l1, two Wnt/β-catenin targets, act synergistically to induce and maintain naive pluripotency. Stem Cell Rep. 5, 314–322 (2015).

    Article  CAS  Google Scholar 

  27. Yang, P. et al. Multi-omic profiling reveals dynamics of the phased progression of pluripotency. Cell Syst. 8, 427–445.e10 (2019).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  28. Kalkan, T. et al. Complementary activity of ETV5, RBPJ, and TCF3 drives formative transition from naive pluripotency. Cell Stem Cell 24, 785–801.e7 (2019).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  29. Lackner, A. et al. Cooperative genetic networks drive embryonic stem cell transition from naïve to formative pluripotency. EMBO J. 40, e105776 (2021).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  30. Acampora, D. et al. Loss of the Otx2-binding site in the Nanog promoter affects the integrity of embryonic stem cell subtypes and specification of inner cell mass-derived epiblast. Cell Rep. 15, 2651–2664 (2016).

    Article  CAS  PubMed  Google Scholar 

  31. Mulas, C., Kalkan, T. & Smith, A. NODAL secures pluripotency upon embryonic stem cell progression from the ground state. Stem Cell Rep. 9, 77–91 (2017).

    Article  Google Scholar 

  32. Mohammed, H. et al. Single-cell landscape of transcriptional heterogeneity and cell fate decisions during mouse early gastrulation. Cell Rep. 20, 1215–1228 (2017).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  33. Chambers, I. et al. Nanog safeguards pluripotency and mediates germline development. Nature 450, 1230–1234 (2007).

    Article  CAS  PubMed  Google Scholar 

  34. Hayashi, K., de Sousa Lopes, S. M. C., Tang, F., Lao, K. & Surani, M. A. Dynamic equilibrium and heterogeneity of mouse pluripotent stem cells with distinct functional and epigenetic states. Cell Stem Cell 3, 391–401 (2008).

    Article  CAS  PubMed  Google Scholar 

  35. Kolodziejczyk, A. A. et al. Single cell RNA-sequencing of pluripotent states unlocks modular transcriptional variation. Cell Stem Cell 17, 471–485 (2015).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  36. Papatsenko, D. et al. Single-cell analyses of ESCs reveal alternative pluripotent cell states and molecular mechanisms that control self-renewal. Stem Cell Rep. 5, 207–220 (2015).

    Article  CAS  Google Scholar 

  37. Sánchez-Castillo, M. et al. CODEX: a next-generation sequencing experiment database for the haematopoietic and embryonic stem cell communities. Nucleic Acids Res. 43, D1117–D1123 (2015).

    Article  PubMed  Google Scholar 

  38. Adachi, K. et al. Esrrb unlocks silenced enhancers for reprogramming to naive pluripotency. Cell Stem Cell 23, 266–275.e6 (2018).

    Article  CAS  PubMed  Google Scholar 

  39. Dunn, S.-J., Li, M. A., Carbognin, E., Smith, A. & Martello, G. A common molecular logic determines embryonic stem cell self-renewal and reprogramming. EMBO J. 38, e100003 (2019).

    Article  PubMed  Google Scholar 

  40. Festuccia, N. et al. Esrrb extinction triggers dismantling of naïve pluripotency and marks commitment to differentiation. EMBO J. 37, e95476 (2018).

    Article  PubMed Central  PubMed  Google Scholar 

  41. Fan, R. et al. Wnt/Beta-catenin/Esrrb signalling controls the tissue-scale reorganization and maintenance of the pluripotent lineage during murine embryonic diapause. Nat. Commun. 11, 5499 (2020).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  42. Shy, B. R. et al. Regulation of Tcf7l1 DNA binding and protein stability as principal mechanisms of Wnt/β-catenin signaling. Cell Rep. 4, 1–9 (2013).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  43. Wray, J. et al. Inhibition of glycogen synthase kinase-3 alleviates Tcf3 repression of the pluripotency network and increases embryonic stem cell resistance to differentiation. Nat. Cell Biol. 13, 838–845 (2011).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  44. Martello, G., Bertone, P. & Smith, A. Identification of the missing pluripotency mediator downstream of leukaemia inhibitory factor. EMBO J. 32, 2561–2574 (2013).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  45. Zhang, X., Zhang, J., Wang, T., Esteban, M. A. & Pei, D. Esrrb activates Oct4 transcription and sustains self-renewal and pluripotency in embryonic stem cells. J. Biol. Chem. 283, 35825–35833 (2008).

    Article  CAS  PubMed  Google Scholar 

  46. Sone, M. et al. Hybrid cellular metabolism coordinated by Zic3 and esrrb synergistically enhances induction of naive pluripotency. Cell Metab. 25, 1103–1117.e6 (2017).

    Article  CAS  PubMed  Google Scholar 

  47. Atlasi, Y. et al. Epigenetic modulation of a hardwired 3D chromatin landscape in two naive states of pluripotency. Nat. Cell Biol. 21, 568–578 (2019).

    Article  CAS  PubMed  Google Scholar 

  48. Festuccia, N., Owens, N., Chervova, A., Dubois, A. & Navarro, P. The combined action of Esrrb and Nr5a2 is essential for murine naïve pluripotency. Development 148, dev199604 (2021).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  49. Kojima, Y. et al. The transcriptional and functional properties of mouse epiblast stem cells resemble the anterior primitive streak. Cell Stem Cell 14, 107–120 (2014).

    Article  CAS  PubMed  Google Scholar 

  50. Tsakiridis, A. et al. Distinct Wnt-driven primitive streak-like populations reflect in vivo lineage precursors. Development 141, 1209–1221 (2014).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  51. Nichols, J. & Smith, A. Naive and primed pluripotent states. Cell Stem Cell 4, 487–492 (2009).

    Article  CAS  PubMed  Google Scholar 

  52. Brons, I. G. M. et al. Derivation of pluripotent epiblast stem cells from mammalian embryos. Nature 448, 191–195 (2007).

    Article  CAS  PubMed  Google Scholar 

  53. Guo, G. et al. Klf4 reverts developmentally programmed restriction of ground state pluripotency. Development 136, 1063–1069 (2009).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  54. Tesar, P. J. et al. New cell lines from mouse epiblast share defining features with human embryonic stem cells. Nature 448, 196–199 (2007).

    Article  CAS  PubMed  Google Scholar 

  55. Sumi, T., Oki, S., Kitajima, K. & Meno, C. Epiblast ground state is controlled by canonical Wnt/β-catenin signaling in the postimplantation mouse embryo and epiblast stem cells. PLoS ONE 8, e63378 (2013).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  56. Magnúsdóttir, E. & Surani, M. A. How to make a primordial germ cell. Development 141, 245–252 (2014).

    Article  PubMed  Google Scholar 

  57. Hackett, J. A. et al. Tracing the transitions from pluripotency to germ cell fate with CRISPR screening. Nat. Commun. 9, 4292 (2018).

    Article  PubMed Central  PubMed  Google Scholar 

  58. Okamura, E. et al. Esrrb function is required for proper primordial germ cell development in presomite stage mouse embryos. Dev. Biol. 455, 382–392 (2019).

    Article  CAS  PubMed  Google Scholar 

  59. Miyazono, K., Maeda, S. & Imamura, T. BMP receptor signaling: transcriptional targets, regulation of signals, and signaling cross-talk. Cytokine Growth Factor Rev. 16, 251–263 (2005).

    Article  CAS  PubMed  Google Scholar 

  60. Shahbazi, M. N. et al. Pluripotent state transitions coordinate morphogenesis in mouse and human embryos. Nature 552, 239–243 (2017).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  61. Wang, X. et al. Formative pluripotent stem cells show features of epiblast cells poised for gastrulation. Cell Res. 31, 526–541 (2021).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  62. Neagu, A. et al. In vitro capture and characterization of embryonic rosette-stage pluripotency between naive and primed states. Nat. Cell Biol. 22, 534–545 (2020).

    Article  CAS  PubMed  Google Scholar 

  63. Yordanov, B. et al. A method to identify and analyze biological programs through automated reasoning. NPJ Syst. Biol. Appl. 2, 16010 (2016).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  64. Argelaguet, R. et al. Multi-omics profiling of mouse gastrulation at single-cell resolution. Nature 576, 487–491 (2019).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  65. Boroviak, T. et al. Lineage-specific profiling delineates the emergence and progression of naive pluripotency in mammalian embryogenesis. Dev. Cell 35, 366–382 (2015).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  66. Gassler, J. et al. Zygotic genome activation by the totipotency pioneer factor Nr5a2. Science 378, 1305–1315 (2022).

    Article  CAS  PubMed  Google Scholar 

  67. Festuccia, N. et al. Mitotic binding of Esrrb marks key regulatory regions of the pluripotency network. Nat. Cell Biol. 18, 1139–1148 (2016).

    Article  CAS  PubMed  Google Scholar 

  68. Mitsunaga, K. et al. Loss of PGC-specific expression of the orphan nuclear receptor ERR-beta results in reduction of germ cell number in mouse embryos. Mech. Dev. 121, 237–246 (2004).

    Article  CAS  PubMed  Google Scholar 

  69. Byerly, M. S. et al. Estrogen-related receptor β deletion modulates whole-body energy balance via estrogen-related receptor γ and attenuates neuropeptide Y gene expression. Eur. J. Neurosci. 37, 1033–1047 (2013).

    Article  PubMed Central  PubMed  Google Scholar 

  70. Latos, P. A. et al. Fgf and Esrrb integrate epigenetic and transcriptional networks that regulate self-renewal of trophoblast stem cells. Nat. Commun. 6, 7776 (2015).

    Article  CAS  PubMed  Google Scholar 

  71. Luo, J. et al. Placental abnormalities in mouse embryos lacking the orphan nuclear receptor ERR-β. Nature 388, 778–782 (1997).

    Article  CAS  PubMed  Google Scholar 

  72. Bulut-Karslioglu, A. et al. Inhibition of mTOR induces a paused pluripotent state. Nature 540, 119–123 (2016).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  73. Gu, P. et al. Orphan nuclear receptor LRH-1 is required to maintain Oct4 expression at the epiblast stage of embryonic development. Mol. Cell. Biol. 25, 3492–3505 (2005).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  74. Benchetrit, H. et al. Direct induction of the three pre-implantation blastocyst cell types from fibroblasts. Cell Stem Cell 24, 983–994.e7 (2019).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  75. Handyside, A. H., O’Neill, G. T., Jones, M. & Hooper, M. L. Use of BRL-conditioned medium in combination with feeder layers to isolate a diploid embryonal stem cell line. Rouxs Arch. Dev. Biol. 198, 48–56 (1989).

    Article  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

  78. Robinson, M. D., McCarthy, D. J. & Smyth, G. K edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26, 139–140 (2010).

    Article  CAS  PubMed  Google Scholar 

  79. Kalaitzis, A. A. & Lawrence, N. D. A simple approach to ranking differentially expressed gene expression time courses through Gaussian process regression. BMC Bioinformatics 12, 180 (2011).

    Article  PubMed Central  PubMed  Google Scholar 

  80. Law, C. W., Chen, Y., Shi, W. & Smyth, G. K voom: precision weights unlock linear model analysis tools for RNA-seq read counts. Genome Biol. 15, R29 (2014).

    Article  PubMed Central  PubMed  Google Scholar 

  81. Chen, E. Y. et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool. BMC Bioinformatics 14, 128 (2013).

    Article  PubMed Central  PubMed  Google Scholar 

  82. Korotkevich, G., Sukhov, V., Budin, N., Shpak, B., Artyomov, M. N. & Sergushichev, A. Fast gene set enrichment analysis. Preprint at bioRxiv https://www.biorxiv.org/content/10.1101/060012v3 (2021).

  83. Kanehisa, M. & Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27–30 (2000).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  84. Kuleshov, M. V. et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 44, W90–W97 (2016).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  85. Xie, Z. et al. Gene set knowledge discovery with enrichr. Curr. Protoc. 1, e90 (2021).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  86. Cacchiarelli, D. et al. Integrative analyses of human reprogramming reveal dynamic nature of induced pluripotency. Cell 162, 412–424 (2015).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  87. Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  88. Danecek, P. et al. Twelve years of SAMtools and BCFtools. GigaScience 10, giab008 (2021).

    Article  PubMed Central  PubMed  Google Scholar 

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

    Article  PubMed Central  PubMed  Google Scholar 

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

    Article  PubMed Central  PubMed  Google Scholar 

  91. 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 Central  PubMed  Google Scholar 

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

    Article  CAS  Google Scholar 

  93. 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).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  94. Skene, P. J. & Henikoff, S. An efficient targeted nuclease strategy for high-resolution mapping of DNA binding sites. eLife 6, e21856 (2017).

    Article  PubMed Central  PubMed  Google Scholar 

  95. Gretarsson, K. H. & Hackett, J. A. Dppa2 and Dppa4 counteract de novo methylation to establish a permissive epigenome for development. Nat. Struct. Mol. Biol. 27, 706–716 (2020).

    Article  CAS  PubMed  Google Scholar 

  96. Yordanov, B., Dunn, S.-J., Gravill, C., Kugler, H. & Wintersteiger, C. M. in Bioinformatics Research and Applications (eds Bansal, M. S., Cai, Z. & Mangul, S.) 114–125 (Springer Nature Switzerland, 2022).

  97. H, N., K, O., D, S. & K, A. A parallel circuit of LIF signalling pathways maintains pluripotency of mouse ES cells. Nature 460, 118–122 (2009).

    Article  Google Scholar 

  98. Silva, J. et al. Nanog is the gateway to the pluripotent ground state. Cell 138, 722–737 (2009).

    Article  CAS  PubMed Central  PubMed  Google Scholar 

Download references

Acknowledgements

We thank A. Smith for critical reading of the manuscript. This work was supported by Fondazione Telethon Core Grant, Armenise-Harvard Foundation Career Development Award, European Research Council (grant agreement 759154, CellKarma) and the Rita-Levi Montalcini programme from Ministero dell'istruzione, dell'università e della ricerca (MIUR) to D.C. and M.C. We thank TIGEM NGS core, NEGEDIA and A. Manfredi for genomic library preparation and sequencing run. Work in J.A.H.’s laboratory is supported by programme grants from the European Molecular Biology Laboratory (EMBL). Work in H.K.’s group is supported by the ISRAEL SCIENCE FOUNDATION (grant no. 190/19). G.M.’s laboratory is supported by grants from the Giovanni Armenise–Harvard Foundation, the Telethon Foundation (GJC21157), Microsoft Research and an ERC Starting Grant (MetEpiStem).

Author information

Author notes

  1. These authors contributed equally: Elena Carbognin, Valentina Carlini, Francesco Panariello.

  2. These authors jointly supervised this work: Jamie A. Hackett, Davide Cacchiarelli, Graziano Martello.

Authors and Affiliations

  1. Department of Molecular Medicine, Medical School, University of Padua, Padua, Italy

    Elena Carbognin, Valentina Perrera & Cristina Malucelli

  2. Department of Biology, University of Padua, Padua, Italy

    Elena Carbognin, Martina Chieregato, Elena Guerzoni, Davide Benvegnù & Graziano Martello

  3. Epigenetics & Neurobiology Unit, European Molecular Biology Laboratory (EMBL)-Rome, Adriano Buzzati-Traverso Campus, Rome, Italy

    Valentina Carlini & Jamie A. Hackett

  4. Collaboration for joint PhD degree between EMBL and Heidelberg University, Faculty of Biosciences, Heidelberg, Germany

    Valentina Carlini

  5. Telethon Institute of Genetics and Medicine (TIGEM), Armenise/Harvard Laboratory of Integrative Genomics, Pozzuoli, Italy

    Francesco Panariello, Marcella Cesana, Antonio Grimaldi, Margherita Mutarelli, Annamaria Carissimo & Davide Cacchiarelli

  6. Department of Advanced Biomedical Sciences, University of Naples ‘Federico II’, Naples, Italy

    Marcella Cesana

  7. Istituto di Scienze Applicate e Sistemi Intelligenti ‘Eduardo Caianiello’, Consiglio Nazionale delle Ricerche, Pozzuoli, Italy

    Margherita Mutarelli

  8. Istituto per le Applicazioni del Calcolo ‘Mauro Picone,’ Consiglio Nazionale delle Ricerche, Naples, Italy

    Annamaria Carissimo

  9. The Faculty of Engineering, Bar-Ilan University, Ramat Gan, Israel

    Eitan Tannenbaum & Hillel Kugler

  10. Department of Translational Medicine, University of Naples ‘Federico II’, Naples, Italy

    Davide Cacchiarelli

  11. School for Advanced Studies, Genomics and Experimental Medicine Program, University of Naples ‘Federico II’, Naples, Italy

    Davide Cacchiarelli

Authors
  1. Elena Carbognin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Valentina Carlini
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Francesco Panariello
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Martina Chieregato
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Elena Guerzoni
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Davide Benvegnù
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Valentina Perrera
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Cristina Malucelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Marcella Cesana
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Antonio Grimaldi
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Margherita Mutarelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Annamaria Carissimo
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Eitan Tannenbaum
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Hillel Kugler
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Jamie A. Hackett
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Davide Cacchiarelli
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Graziano Martello
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

G.M. and E.C. conceived the project. E.C., G.M., D.C. and J.A.H. designed the experiments and interpreted the results. E.C. and E.G. performed ESC experiments and analyses. C.M. and D.B. performed molecular analyses of Esrrb KO cells. V.P. performed ChIP–PCR experiments. M. Chieregato performed 3D experiments. V.C. performed PGCLC assays. F.P. and A.C. performed bioinformatic analysis of transcriptomic data. M. Cesana performed ChIP–seq experiments. A.G. performed ATAC-seq experiments. M.M. performed ChIP–seq and ATAC-seq analysis. G.M., H.K. and E.T. performed computational modelling. E.C., F.P. and J.A.H. prepared figures. G.M. and E.C. wrote the manuscript with help from all authors. G.M., D.C. and J.A.H. secured fundings and supervised the project.

Corresponding authors

Correspondence to Jamie A. Hackett, Davide Cacchiarelli or Graziano Martello.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Nature Cell Biology thanks Laurent David and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. Peer reviewer reports are available.

Additional information

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

Extended data

Extended Data Fig. 1 Gene signatures of different pluripotent states.

a: Line chart showing dynamics of mRNA expression based on qPCR of four pluripotency markers (Tfcp2l1, Esrrb, Sall4, Oct4) in E14 cells during monolayer differentiation (withdrawal of either 2iL or 2i for 96 h) both in 2iL (purple) and 2i (green). White circles indicate the mean of n = 4 independent experiments, shown as dots. P-values indicate two-sided unpaired t-test between the indicated time points. b: Heatmaps showing Z-score normalised expression of all genes of each group (defined in Fig. 1d) in E14 cells differentiating from 2iL (purple box) and 2i (green box). Integration of n = 2 independent biological replicates for each time point. See also Supplementary Table 2 for the biological processes enriched in the 6 signatures.

Source data

Extended Data Fig. 2 Transcriptional response changes during commitment.

a: Bar plot showing the number of AP positive colonies in the clonal assay of cells cultured in 2iL and during differentiation (purple bars) and of cells in which 2iL was re-applied for 24 h at the indicated time point (yellow bars, re-induction). Bars indicate mean +/−SD of n = 8 independent experiments, shown as dots. Only the sample ‘24’ was measured in n = 4 independent experiments. Two-sided unpaired Student t-test. b: Heatmaps showing Z-score normalised expression of selected genes for each group (naive, formative, committed) during differentiation and re-induction. Integration of n = 4 independent experiments for each time point. c: Barplots showing expression by RNAseq of Jak/Stat direct targets (Socs3 and Stat3, orange), WNT targets (Cdx2 and Axin2, green) and FGF targets (Dusp6 and Spry4, purple) in differentiating cells and after re-induction with 24 h of LIF. Mean +/−SD of n = 4 independent experiments. d: UCSC genome browser visualisation of normalised ATAC-seq profiles at the indicated loci. Rectangles indicate peaks found only in 2iL (green) or only at 48 h (red). Integration of n = 2 biological replicates. e: Volcano plot summarising published RNA-seq data98 of ESCs cultured in Serum+LIF (S + L) or 2iL. Data were interpolated with the six groups of genes identified in Fig. 1 (naive early and late, formative early and late, committed early and late). f: Schematic representation of experimental strategy. Cells overexpressing pluripotency genes were mixed and differentiated for 96 h. The clonal assay was then performed and cells were collected after 4 days. PCR on genomic DNA was used to identify factors enriched in pluripotent colonies. g: Bar plot showing quantification of AP positive colonies of cells overexpressing an empty vector or pluripotency factors, either maintained in 2iL or differentiated for 96 h. Bars indicate mean n = 2 independent experiments, shown as dots.

Source data

Extended Data Fig. 3 Characterisation of ESC differentiation and regulation of Esrrb expression.

a: Representative images of immunostaining for EpiSCs markers (Oct4 and T) in WT cells maintained in 2iL or differentiated for 96 h in N2B27 or in presence of CHIR and Activin A to induce T expression. Scale bar=25μm. Similar results were obtained in n = 2 independent experiments. b: Barplots showing expression by RNA-seq of key EpiSCs markers in WT cells maintained in 2iL or differentiated for 96 h upon 2iL withdrawal. Mean of n = 2 independent biological replicates is shown. n.d. indicates samples in which expression was undetectable or below 5 CPM. c: Violin plot showing quantification of mean intensity (arbitrary units) for ESRRB in E14 cells cultured in 2iL or differentiated for 48 h, 96 h or 120 h (48, 96 120) or after reinduction with 2iL for 24 h (48 + 24 and 96 + 24). At least 3 randomly selected fields for each sample have been measured. N = 3 independent experiments were analysed. Each violin indicates an independent experiment. d: Left: Representative images of clonal assay followed by Alkaline Phosphatase staining of cells either maintained in 2iL or differentiated for 96 h with or without the Gsk3 inhibitor CHIR (96+CHIR). Centre: Bar plot showing quantification of AP positive colonies. Bars indicate mean of 2 biological replicates, shown as dots. Right: Bar plot showing relative mRNA expression, measured by qPCR, for Esrrb. Bars indicate mean of 2 biological replicates, shown as dots. e: Barplot showing expression by qPCR of Esrrb in E14 cells cultured in 2iL, N2B27, ActivinA (20 ng/ml), FGF2 (12.5 ng/ml) and inhibitors of TGF-beta (A83-01, 1 μM) and FGF signalling pathways (PD173074, 0.5 μm) for 48 h. Mean +/−SD of 3 independent biological replicates are shown as dots. f: ChIP-PCR analysis of E14 cells cultured in 2iL and differentiated for 24 h, 48 h, 72 h and 96 h in N2B27. Immunoprecipitation was performed using anti-ESRRB and anti-H3K27ac antibody followed by PCR with primers located on Esrrb intron or Tfcp2l1, Utf1 and Tcf15 promoter regions. Fold-enrichment over a negative region is plotted. Mean +/−SD of n = 4 independent experiments, shown as dots.

Source data

Extended Data Fig. 4 Regulation of Esrrb expression.

a: Genome browser snapshot of histone modifications on regulatory regions on Esrrb gene in naive (2iL, blue) and formative (48 h, red) states. Integration of n = 2 biological replicates. b: Top: Representative images of immunostaining for H3K27ac (green) and ESRRB (red) in E14 cells cultured in 2iL, differentiated for 84 h (84) or after a pulse with 2iLIF for 24 h at 84 h (2iL pulse), with or without Sodium Butyrate (NaButy or H2O) treatment. Nuclei were identified by DAPI staining (blue). Scale bar: 25μm. Bottom: Barplot showing quantification of mean intensity for H3K27ac (blue) and ESRRB (red) immunostaining normalised to the 2iL H2O samples. Mean +/−SD of n = 3 independent experiments, shown as dots. c: Plots showing abundance of the indicated histone modifications detected by CUT&RUN and DNA methylation in naive (2iL, left) and formative cells (48, right), on regions bound by ESRRB only in 2iL (‘2iL’), only at 48 h (‘48’), or in 2iL and after 48 h (‘2iL-48’), identified in Fig. 4a, b. Integration of n = 2 biological replicates. For ‘2iL’ and ‘2iL-48’ regions we observed enrichment for H3K4me3, H3K27ac, H3K27me3 and H3K9me3 in naive cells. In formative cells, H3K4me3 and H3K9me3 decreased by ~50% while H3K27me3 was lost, while DNA methylation substantially increased. Those regions, where Esrrb binding increases at 48 h (‘48’), are heavily DNA methylated and pre-decorated by H3K4me3 and H3K27ac in naive cells, while the repressive marks H3K9me3 and H3K27me3 are absent.

Source data

Extended Data Fig. 5 Esrrb KO clones characterisation.

a: Left: Bar plot showing the number of AP positive colonies after clonal assay of cells with loxP sites flanking the second exon of both alleles of Esrrb (Esrrb fl/fl, dark blue) and Esrrb KO cells generated by Cre-mediated recombination (light blue), cultured in 2iL and differentiated for 24 h, 48 h and 72 h in N2B27. Mean +/−SD of n = 3 independent experiments, shown as dots. Right: Barplots showing expression measured by qPCR of Esrrb in Esrrb fl/fl (dark blue) and Esrrb KO (light blue) cells cultured in 2iL and differentiated for 24 h, 48 h and 72 h. Mean of n = 2 independent experiments. b: Schematic representation of edited alleles of 3 CRISPR-generated Esrrb KO clones. The edited genome is indicated in red. The blue sequence is an insertion. Black bars indicate deletions. c: Bright field images of 3 CRISPR-generated Esrrb KO clones, cultured in 2iL and after 48 h of 2iL withdrawal. Scale bar: 300μm. d: Barplot showing expression by RNAseq of naive markers in WT E14 cells and in 3 CRISPR-generated Esrrb KO clones. WT values were set as 1. Mean of n = 2 biological replicates.

Source data

Extended Data Fig. 6 Proliferation and viability analysis of Esrrb KO clones and FS differentiation.

a: Left: Proliferation assay over 4 days of WT cells and Esrrb KO clones, cultured in 2iL. Mean +/−SD of n = 3 independent experiments is shown. Right: Barplot showing percentage of dead cells measured by Propidium Iodide staining in two WT cell lines and 2 Esrrb KO clones. Boiled cells (95 degrees Celsius for 5 min) were used as positive control. Mean +/−SD of n = 3 independent experiments is shown. P-value calculated with One-way ANOVA followed by Tukey multiple pairwise-comparisons. b: Gene Set Enrichment Analysis (GSEA) of key markers of Apoptosis and cell stress in WT and Esrrb KO cells cultured in 2iL (naive) and 48 h (formative), which failed to detect any significant differences between WT and KO cells. P values calculated by the GSEA software. c: Expression measured by qPCR of selected naive and formative genes in WT E14 cells (grey) and three Esrrb KO clones (blue) cultured in 2iL and after 24 h, 48 h and 72 h of differentiation in N2B27. Mean of n = 2 biological replicates is shown. d: Expression measured by qPCR of naive and lineage markers in Conditional Esrrb cells kept in 2iL+DOX. WT cells and Esrrb KO expressing a DOX-inducible empty vector (iEmpty) kept in 2iL+DOX are used as controls. Mean +/− SD n = 3 independent experiments (dots) is shown. e: Gene expression of formative genes measured by qPCR in Conditional Esrrb cells cultured in 2iL+DOX (3rd bar) and withdrawn of 2iL and DOX for 48 h (4th bar). Esrrb KO and WT cells expressing an inducible Empty vector (iEmpty) differentiated for 48 h were used as controls (2nd and 6th bars). Bars indicate mean +/−SD of n = 5 independent experiments, shown as dots. One-way ANOVA followed by Tukey multiple pairwise-comparisons. f: Left: Experimental strategy used for FS cells generation from ESCs. Right: Representative images of WT cells cultures in AloXR medium for 3 passages (P1, P2 and P3). Scale bar: 25μm. Similar results were obtained in n = 3 independent experiments. g: Relative mRNA expression measured by qPCR of naive and formative genes in E14 cells cultured in 2iL or AloXR medium for up to 3 passages. Mean of n = 3 technical replicates.

Source data

Extended Data Fig. 7 FS cell differentiation of Esrrb KO clones.

a: Gene Set Enrichment Analysis (GSEA) of key markers of Apoptosis and cell stress in WT and Esrrb KO cells cultured in 2iL (naive) and P1/48 h (formative) failed to detect any significant differences between WT and KO cells. P values calculated by the GSEA software. b: PCA of RNA sequencing data of WT and Esrrb KO cells during FS differentiation. Genes contributing to Principal Components PC1 and PC3 are indicated. N = 3 independent biological replicates, shown as dots, for 2iL samples. N = 4 for P1-P3 samples. N = 2 for KO3 at P2 and P3. c: Heatmaps showing mean normalised relative mRNA expression measured by qPCR of naive and formative genes in WT and Esrrb KO cells cultured in 2iL or AloXR medium for up to 3 passages (P1, P2, P3). Mean of n = 3 technical replicates. d: Representative images of immunostaining for TFCP2L1 and OTX2 in WT cells (left panels) and for OTX2 in Esrrb KO cells (right panels) cultured in 2iL or AloXR medium for up to 3 passages. Nuclei were identified by DAPI staining (blue). Scale bar: 25μm. Similar results were obtained in n = 2 independent experiments. e: Left: Representative images of WT and Esrrb KO cells cultured in FGF2 + ActivinA+XAV939 for at least 6 passages, to induce EpiSCs differentiation. Scale bar: 25μm. Right: Barplots showing gene expression measured by qPCR of naive (Esrrb and Klf4), general pluripotency (Oct4) and EpiSCs (Fgf5, T) markers in WT and Esrrb KO cells cultured in FGF2 + ActivinA+XAV939 for at least 6 passages, to induce EpiSCs differentiation. Embryo-derived EpiSCs (OEC2 and GOF18) and WT E14 ESCs cultured in 2iL are used as controls. Mean +/−SD of N = 4 biological replicates, shown as dots.

Source data

Extended Data Fig. 8 PGCLC differentiation of Esrrb KO clones.

a: Normalised frequency of individual gRNAs (indicative of KO) targeting Esrrb during induction of PGCLC (CRISPR screening results from57). Dots indicate the mean of n = 2 independent CRISPR screens. b: Left: Frequency of individual gRNA targeting Esrrb in EpiLC that have acquired correct formative status (Stella-) and EpiLC blocked from formative transition (Stella+). Note Esrrb gRNA (KO) are enriched in EpiLC that fail to acquire formative status, indicating a functional role for Esrrb in promoting the formative program. Right: Normalised frequency of individual gRNAs targeting Olfr568 as a representative negative control gene that should not influence the induction of PGCLC upon KO. Dots indicate the mean of n = 2 independent CRISPR screens. c: Immunoblot of clonal lines derived from SGET ESC transiently transfected with Cas9 and gRNAs binding Esrrb coding sequence. Out of 5 independent Esrrb KO clones, 3 (A1.2, B2.1, A2.5) were randomly chosen for further validations. Beta-TUBULIN was used as loading control. The experiment was repeated 3 times with similar results. Esrrb KO clones do not display Esrrb protein expression, but a shorter mRNA can still be detected (Fig. 7d). d: Schematic representation of SGET activation during in vitro cell fate transitions of ESC (Stella + /Esg1+) into EpiLC (Esg1+) and early and late PGCLCs (Stella+) (adapted from Hackett et al., 2018). e: Total number of cells in SGET WT and Esrrb KO clones obtained after 3 days of PGCLC induction from EpiLC differentiation. Mean +/−SD of n = 3 independent experiments (dots) is shown. f: Gene expression of selected genes in WT (grey) and n = 3 independent Esrrb KO SGET lines (blue) at EpiLC, d3 and d5 PGCLC stages. g: Expression of the PGC-early (left) and PGC-late (right) geneset in EpiLC, d3 and d5 PGCLC from WT and Esrrb KO lines. Bars indicate the median, box indicates the 25th and 75th percentiles, whiskers represent median plus/minus the interquartile (25-75%) range multiplied by 2. Two-sided paired Student t-test, n.s. not significant. Integration of n = 3 biological replicates for each sample. h: Gene expression of BMP direct targets in WT (grey) and n = 3 independent Esrrb KO SGET lines (blue) at EpiLC, d3 and d5 PGCLC stages.

Source data

Extended Data Fig. 9 Differentiation of Esrrb KO clones in 2D and 3D.

a: Heatmap showing Z-scored, mean-scaled, normalised gene expression, measured by RNA-seq, of master regulator genes for each of the three primary germ layers and trophoblast in WT cells and three Esrrb KO clones cultured in 2iL and after 24 h, 48 h and 72 h of differentiation in N2B27. Integration of n = 2 biological replicates for each sample. b: Representative images of WT cells cultured in N2B27 medium in matrigel for 48 h, 72 h or 96 h, to allow 3D organisation and lumenogenesis. F-actin was labelled by Phalloidin staining (green) and immunostaining for the apical protein PODXL was performed (red). Scale bar: 30 μm. Similar results were obtained in n = 5 independent experiments. c: Top: Barplot showing quantification of number of structured/field in WT and Esrrb KO cells cultured in N2B27 medium in matrigel for 48 h, 72 h or 96 h. Bars indicate mean of 2 independent experiments, shown as dots. Centre: Violin plot showing quantification of Area (expressed in pixels) of >14 structures in WT and Esrrb KO cells. P-values calculated by two-way repeated measures ANOVA. Similar results were obtained in 3 independent experiments. Bottom: Violin plot showing quantification of the ratio of the 2 main diameters (roundness) of >17 structures in WT and Esrrb KO cells, as shown in the WT panel. P-values indicate two-sided unpaired t-test. Similar results were obtained in 3 independent experiments. Box plots show 1st, 2nd and 3rd quartile, whiskers represent median plus/minus the interquartile (25-75%) range multiplied by 1.5. d: Line plots showing quantification of F-ACTIN intensity along the diameter of 3D structures obtained by culturing WT and Esrrb KO cells in N2B27 in matrigel for 48 h, 72 h or 96 h. At least 8 structures were quantified from n = 2 independent experiments. The shades indicate the SD. e: Violin plots showing quantification of OTX2 intensity in 3D structures obtained from WT and Esrrb KO cells cultured in N2B27 in matrigel for 48 h. N > 380 nuclei for each sample. Two independent experiments are shown (left and right). Box plots show 1st, 2nd and 3rd quartile, whiskers represent median plus/minus the interquartile (25-75%) range multiplied by 1.5.

Source data

Extended Data Fig. 10 Network analysis of formative gene regulation by Esrrb.

a: Barplot showing expression of Otx2 measured by qPCR in ES cells treated for 48 h with ActivinA (20 ng/ml), FGF2 (12.5 ng/ml) and inhibitors of TGF-beta (A83-01, 1 μM) and FGF signalling pathways (PD173074, 0.5 μm). Cells cultured in 2iL or N2B27 for 48 h were used as controls. Mean +/−SD of n = 3 independent biological replicates (dots) are shown. b: Genome browser snapshot of histone modifications at Otx2 enhancer (E) bound by Esrrb and promoter (P), in naive and formative cells. Profiles are the integration of n = 2 biological replicates. c: ABN derived from a Pearson correlation threshold of 0.56 (see Methods). Solid black lines indicate required and definite interaction, dashed lines indicate optional interactions, red lines indicate disallowed interactions. Positive regulations are indicated by a black arrow, negative regulations are indicated by a black circle-headed line. d: Summary of 4 experimental constraints, each with initial (left column) and final (right column) conditions. Gene expression is discretized as high (blue) or low (white).

Source data

Supplementary information

Supplementary Information

Supplementary Figures 1-3

Reporting Summary

Peer Review File

Supplementary Table 1

Supplementary Table 1. Six gene signatures identified in this study. Supplementary Table 2. Biological processes enriched in the six signatures identified. Supplementary Table 3. Biological processes enriched in genes bound by Esrrb. Supplementary Table 4. Primer list. Supplementary Table 5. gRNA sequences. Supplementary Table 6. Antibody list.

Source data

Source Data Fig. 1

Statistical source data.

Source Data Fig. 2

Statistical source data.

Source Data Fig. 3

Statistical source data.

Source Data Fig. 5

Statistical source data.

Source Data Fig. 5

Unprocessed western blots.

Source Data Fig. 6

Statistical source data.

Source Data Fig. 7

Statistical source data.

Source Data Fig. 8

Statistical source data.

Extended Data Fig. 1

Statistical source data.

Extended Data Fig. 2

Statistical source data.

Extended Data Fig. 3

Statistical source data.

Extended Data Fig. 4

Statistical source data.

Extended Data Fig. 5

Statistical source data.

Extended Data Fig. 6

Statistical source data.

Extended Data Fig. 7

Statistical source data.

Extended Data Fig. 8

Statistical source data.

Extended Data Fig. 8

Unprocessed western blots.

Extended Data Fig. 9

Statistical source data.

Extended Data Fig. 10

Statistical source data.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Carbognin, E., Carlini, V., Panariello, F. et al. Esrrb guides naive pluripotent cells through the formative transcriptional programme. Nat Cell Biol 25, 643–657 (2023). https://doi.org/10.1038/s41556-023-01131-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41556-023-01131-x

This article is cited by

Search

Advanced 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