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A subset of transposable elements as mechano-response enhancer elements in controlling human embryonic stem cell fate

Abstract

Transposable elements (TEs), constituting half of the human genome, are essential for development and diseases. While the regulation of TE activity by cellular intrinsic mechanisms is well documented, their response to microenvironmental signals, particularly mechanical cues involving numerous biological processes, remains unknown. Here we show that various TE families, notably LTR7, undergo transcriptomic, epigenetic and three-dimensional genome changes in response to matrix mechanical cues in human embryonic stem cells. Interestingly, LTR7s act as ‘mechano-response enhancer elements’ (MREEs), controlling the gene expression and cell fate of human embryonic stem cells. Mechanistically, mechano-effectors YAP/TEAD1 control LTR7’s epigenetic activity by engaging with BRD4. Furthermore, YAP recruits CTCF, a key genome architecture protein, to facilitate long-range interactions between gene promoters and TEs as MREEs. In particular, a mechano-responsive LTR7 element is a distal enhancer for FAM189A2, thereby inhibiting definitive endoderm differentiation. These findings highlight the underappreciated role of TEs as MREEs that control human cell fate and gene expression.

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Fig. 1: Dynamic RNA expression and epigenetic modifications of TEs in response to matrix stiffness.
Fig. 2: Mechanical cues regulate LTR7 epigenetic activity via YAP/TEAD1.
Fig. 3: LTR7s are MREEs regulated by YAP/TEAD1.
Fig. 4: YAP recruits CTCF to mediate long-range interactions between gene promoters and TE-derived MREEs in response to stiffness.
Fig. 5: FAM-LTR7 inhibits DE differentiation of hES cells by acting as a MREE of FAM189A2.

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Data availability

All CUT&RUN, HiCAR, ChIP-seq and RNA-seq data have been deposited to the NCBI Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo) under accession numbers GSE266645, GSE266646, GSE266647 and GSE266648. Publicly available RNA-seq data (GSE127887 and GSE178888) were obtained from the GEO. All the data were analysed using published pipelines with parameters described in Methods. No custom codes were developed in this study. Source data are provided with this paper.

References

  1. Bourque, G. et al. Ten things you should know about transposable elements. Genome Biol. 19, 199 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Senft, A. D. & Macfarlan, T. S. Transposable elements shape the evolution of mammalian development. Nat. Rev. Genet. 22, 691–711 (2021).

    Article  CAS  PubMed  Google Scholar 

  3. Fueyo, R., Judd, J., Feschotte, C. & Wysocka, J. Roles of transposable elements in the regulation of mammalian transcription. Nat. Rev. Mol. Cell Biol. 23, 481–497 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Sultana, T., Zamborlini, A., Cristofari, G. & Lesage, P. Integration site selection by retroviruses and transposable elements in eukaryotes. Nat. Rev. Genet. 18, 292–308 (2017).

    Article  CAS  PubMed  Google Scholar 

  5. Chuong, E. B., Elde, N. C. & Feschotte, C. Regulatory activities of transposable elements: from conflicts to benefits. Nat. Rev. Genet. 18, 71–86 (2017).

    Article  CAS  PubMed  Google Scholar 

  6. Payer, L. M. & Burns, K. H. Transposable elements in human genetic disease. Nat. Rev. Genet. 20, 760–772 (2019).

    Article  CAS  PubMed  Google Scholar 

  7. Geis, F. K. & Goff, S. P. Silencing and transcriptional regulation of endogenous retroviruses: an overview. Viruses 12, 884 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Deniz, Ö., Frost, J. M. & Branco, M. R. Regulation of transposable elements by DNA modifications. Nat. Rev. Genet. 20, 417–431 (2019).

    Article  CAS  PubMed  Google Scholar 

  9. Padeken, J., Methot, S. P. & Gasser, S. M. Establishment of H3K9-methylated heterochromatin and its functions in tissue differentiation and maintenance. Nat. Rev. Mol. Cell Biol. 23, 623–640 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Pappalardo, X. G. & Barra, V. Losing DNA methylation at repetitive elements and breaking bad. Epigenetics Chromatin 14, 25 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Sun, T. et al. Crosstalk between RNA m6A and DNA methylation regulates transposable element chromatin activation and cell fate in human pluripotent stem cells. Nat. Genet. 55, 1324–1335 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Xu, W. et al. METTL3 regulates heterochromatin in mouse embryonic stem cells. Nature 591, 317–321 (2021).

    Article  CAS  PubMed  Google Scholar 

  13. Liu, J. et al. The RNA m6A reader YTHDC1 silences retrotransposons and guards ES cell identity. Nature 591, 322–326 (2021).

    Article  CAS  PubMed  Google Scholar 

  14. Liu, J. et al. N6-Methyladenosine of chromosome-associated regulatory RNA regulates chromatin state and transcription. Science 367, 580–586 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Wei, J. et al. FTO mediates LINE1 m6A demethylation and chromatin regulation in mESCs and mouse development. Science 376, 968–973 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Chelmicki, T. et al. m6A RNA methylation regulates the fate of endogenous retroviruses. Nature 591, 312–316 (2021).

    Article  CAS  PubMed  Google Scholar 

  17. De Belly, H., Paluch, E. K. & Chalut, K. J. Interplay between mechanics and signalling in regulating cell fate. Nat. Rev. Mol. Cell Biol. 23, 465–480 (2022).

    Article  PubMed  Google Scholar 

  18. Hayward, M.-K., Muncie, J. M. & Weaver, V. M. Tissue mechanics in stem cell fate, development, and cancer. Dev. Cell 56, 1833–1847 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Ma, S., Meng, Z., Chen, R. & Guan, K.-L. The Hippo pathway: Biology and pathophysiology. Annu. Rev. Biochem. 88, 577–604 (2019).

    Article  CAS  PubMed  Google Scholar 

  20. Franklin, J. M., Wu, Z. & Guan, K.-L. Insights into recent findings and clinical application of YAP and TAZ in cancer. Nat. Rev. Cancer 23, 512–525 (2023).

    Article  CAS  PubMed  Google Scholar 

  21. Goodwin, K. & Nelson, C. M. Mechanics of development. Dev. Cell 56, 240–250 (2021).

    Article  CAS  PubMed  Google Scholar 

  22. Sutlive, J. et al. Generation, transmission, and regulation of mechanical forces in embryonic morphogenesis. Small 18, e2103466 (2022).

    Article  PubMed  Google Scholar 

  23. Zhu, M. & Zernicka-Goetz, M. Principles of self-organization of the mammalian embryo. Cell 183, 1467–1478 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Collinet, C. & Lecuit, T. Programmed and self-organized flow of information during morphogenesis. Nat. Rev. Mol. Cell Biol. 22, 245–265 (2021).

    Article  CAS  PubMed  Google Scholar 

  25. Wu, Z. & Guan, K.-L. Hippo signaling in embryogenesis and development. Trends Biochem. Sci. 46, 51–63 (2021).

    Article  CAS  PubMed  Google Scholar 

  26. Valet, M., Siggia, E. D. & Brivanlou, A. H. Mechanical regulation of early vertebrate embryogenesis. Nat. Rev. Mol. Cell Biol. 23, 169–184 (2022).

    Article  CAS  PubMed  Google Scholar 

  27. Chanet, S. & Martin, A. C. Mechanical force sensing in tissues. Prog. Mol. Biol. Transl. Sci. 126, 317–352 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  28. Kirby, T. J. & Lammerding, J. Emerging views of the nucleus as a cellular mechanosensor. Nat. Cell Biol. 20, 373–381 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Miroshnikova, Y. A. & Wickström, S. A. Mechanical forces in nuclear organization. Cold Spring Harb. Perspect. Biol. 14, a039685 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Cho, S., Irianto, J. & Discher, D. E. Mechanosensing by the nucleus: from pathways to scaling relationships. J. Cell Biol. 216, 305–315 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Tajik, A. et al. Transcription upregulation via force-induced direct stretching of chromatin. Nat. Mater. 15, 1287–1296 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Sun, J., Chen, J., Mohagheghian, E. & Wang, N. Force-induced gene up-regulation does not follow the weak power law but depends on H3K9 demethylation. Sci. Adv. 6, eaay9095 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Dupont, S. & Wickström, S. A. Mechanical regulation of chromatin and transcription. Nat. Rev. Genet. 23, 624–643 (2022).

    Article  CAS  PubMed  Google Scholar 

  34. Kalukula, Y., Stephens, A. D., Lammerding, J. & Gabriele, S. Mechanics and functional consequences of nuclear deformations. Nat. Rev. Mol. Cell Biol. 23, 583–602 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Le, H. Q. et al. Mechanical regulation of transcription controls Polycomb-mediated gene silencing during lineage commitment. Nat. Cell Biol. 18, 864–875 (2016).

    Article  CAS  PubMed  Google Scholar 

  36. Miroshnikova, Y. A., Nava, M. M. & Wickström, S. A. Emerging roles of mechanical forces in chromatin regulation. J. Cell Sci. 130, 2243–2250 (2017).

    Article  CAS  PubMed  Google Scholar 

  37. Dupont, S. et al. Role of YAP/TAZ in mechanotransduction. Nature 474, 179–183 (2011).

    Article  CAS  PubMed  Google Scholar 

  38. Vining, K. H. & Mooney, D. J. Mechanical forces direct stem cell behaviour in development and regeneration. Nat. Rev. Mol. Cell Biol. 18, 728–742 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Guimarães, C. F., Gasperini, L., Marques, A. P. & Reis, R. L. The stiffness of living tissues and its implications for tissue engineering. Nat. Rev. Mater. 5, 351–370 (2020).

    Article  Google Scholar 

  40. Keung, A. J., Asuri, P., Kumar, S. & Schaffer, D. V. Soft microenvironments promote the early neurogenic differentiation but not self-renewal of human pluripotent stem cells. Integr. Biol. 4, 1049–1058 (2012).

    Article  CAS  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Gene Ontology Consortium et al. The Gene Ontology knowledgebase in 2023. Genetics 224, iyad031 (2023).

  43. Cai, X., Wang, K.-C. & Meng, Z. Mechanoregulation of YAP and TAZ in cellular homeostasis and disease progression. Front. Cell Dev. Biol. 9, 673599 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Hong, W. & Guan, K.-L. The YAP and TAZ transcription co-activators: key downstream effectors of the mammalian Hippo pathway. Semin. Cell Dev. Biol. 23, 785–793 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Lu, X. et al. The retrovirus HERVH is a long noncoding RNA required for human embryonic stem cell identity. Nat. Struct. Mol. Biol. 21, 423–425 (2014).

    Article  CAS  PubMed  Google Scholar 

  46. Local, A. et al. Identification of H3K4me1-associated proteins at mammalian enhancers. Nat. Genet. 50, 73–82 (2018).

    Article  CAS  PubMed  Google Scholar 

  47. Creyghton, M. P. et al. Histone H3K27ac separates active from poised enhancers and predicts developmental state. Proc. Natl Acad. Sci. USA 107, 21931–21936 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Stein, C. et al. YAP1 exerts its transcriptional control via TEAD-mediated activation of enhancers. PLoS Genet. 11, e1005465 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Zhao, B. et al. TEAD mediates YAP-dependent gene induction and growth control. Genes Dev. 22, 1962–1971 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Zhao, B. et al. Inactivation of YAP oncoprotein by the Hippo pathway is involved in cell contact inhibition and tissue growth control. Genes Dev. 21, 2747–2761 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Zanconato, F. et al. Transcriptional addiction in cancer cells is mediated by YAP/TAZ through BRD4. Nat. Med. 24, 1599–1610 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Lawson, H. A., Liang, Y. & Wang, T. Transposable elements in mammalian chromatin organization. Nat. Rev. Genet. 24, 712–723 (2023).

    Article  CAS  PubMed  Google Scholar 

  53. Choudhary, M. N. K., Quaid, K., Xing, X., Schmidt, H. & Wang, T. Widespread contribution of transposable elements to the rewiring of mammalian 3D genomes. Nat. Commun. 14, 634 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Diehl, A. G., Ouyang, N. & Boyle, A. Transposable elements contribute to cell and species-specific chromatin looping and gene regulation in mammalian genomes. Nat. Commun. 11, 1796 (2020).

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Haarhuis, J. H. I. et al. The cohesin release factor WAPL restricts chromatin loop extension. Cell 169, 693–707.e14 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Busslinger, G. A. et al. Cohesin is positioned in mammalian genomes by transcription, CTCF and Wapl. Nature 544, 503–507 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Zhou, Q. et al. ZNF143 mediates CTCF-bound promoter–enhancer loops required for murine hematopoietic stem and progenitor cell function. Nat. Commun. 12, 43 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Shan, Q. et al. Tcf1–CTCF cooperativity shapes genomic architecture to promote CD8+ T cell homeostasis. Nat. Immunol. 23, 1222–1235 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Dowen, J. M. & Young, R. A. SMC complexes link gene expression and genome architecture. Curr. Opin. Genet. Dev. 25, 131–137 (2014).

    Article  CAS  PubMed  Google Scholar 

  61. Rowley, M. J. & Corces, V. G. Organizational principles of 3D genome architecture. Nat. Rev. Genet. 19, 789–800 (2018).

    Article  CAS  PubMed  Google Scholar 

  62. Hyle, J. et al. Acute depletion of CTCF directly affects MYC regulation through loss of enhancer–promoter looping. Nucleic Acids Res. 47, 6699–6713 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Ottema, S. et al. The leukemic oncogene EVI1 hijacks a MYC super-enhancer by CTCF-facilitated loops. Nat. Commun. 12, 5679 (2021).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Yang, J. H. & Hansen, A. S. Enhancer selectivity in space and time: from enhancer–promoter interactions to promoter activation. Nat. Rev. Mol. Cell Biol. 25, 574–591 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Wei, X. et al. HiCAR is a robust and sensitive method to analyze open-chromatin-associated genome organization. Mol. Cell 82, 1225–1238.e6 (2022).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Zhang, Y. et al. Transcriptionally active HERV-H retrotransposons demarcate topologically associating domains in human pluripotent stem cells. Nat. Genet. 51, 1380–1388 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. Juric, I. et al. MAPS: model-based analysis of long-range chromatin interactions from PLAC-seq and HiChIP experiments. PLoS Comput. Biol. 15, e1006982 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  69. Zeevaert, K. et al. YAP1 is essential for self-organized differentiation of pluripotent stem cells. Biomater. Adv. 146, 213308 (2023).

    Article  CAS  PubMed  Google Scholar 

  70. Stronati, E. et al. YAP1 regulates the self-organized fate patterning of hESC-derived gastruloids. Stem Cell Rep. 17, 211–220 (2022).

    Article  CAS  Google Scholar 

  71. Zhao, C. et al. A comprehensive human embryo reference tool using single-cell RNA-sequencing data. Nat. Methods 22, 193–206 (2025).

    Article  CAS  PubMed  Google Scholar 

  72. Pagliari, S. et al. YAP-TEAD1 control of cytoskeleton dynamics and intracellular tension guides human pluripotent stem cell mesoderm specification. Cell Death Differ. 28, 1193–1207 (2021).

    Article  CAS  PubMed  Google Scholar 

  73. Jaramillo, M., Singh, S. S., Velankar, S., Kumta, P. N. & Banerjee, I. Inducing endoderm differentiation by modulating mechanical properties of soft substrates. J. Tissue Eng. Regen. Med. 9, 1–12 (2015).

    Article  CAS  PubMed  Google Scholar 

  74. Chen, Y.-F. et al. Control of matrix stiffness promotes endodermal lineage specification by regulating SMAD2/3 via lncRNA LINC00458. Sci. Adv. 6, eaay0264 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Yang, J. et al. Genome-scale CRISPRa screen identifies novel factors for cellular reprogramming. Stem Cell Rep. 12, 757–771 (2019).

    Article  CAS  Google Scholar 

  76. Estarás, C., Hsu, H.-T., Huang, L. & Jones, K. A. YAP repression of the WNT3 gene controls hESC differentiation along the cardiac mesoderm lineage. Genes Dev. 31, 2250–2263 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  77. Kang, J. et al. Modulation of tissue repair by regeneration enhancer elements. Nature 532, 201–206 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. van den Heuvel, A., Stadhouders, R., Andrieu-Soler, C., Grosveld, F. & Soler, E. Long-range gene regulation and novel therapeutic applications. Blood 125, 1521–1525 (2015).

    Article  PubMed  Google Scholar 

  79. Deng, W. et al. Reactivation of developmentally silenced globin genes by forced chromatin looping. Cell 158, 849–860 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Yan, R. et al. An enhancer-based gene-therapy strategy for spatiotemporal control of cargoes during tissue repair. Cell Stem Cell 30, 96–111.e6 (2023).

    Article  CAS  PubMed  Google Scholar 

  81. Iwashita, H. et al. Secreted cerberus1 as a marker for quantification of definitive endoderm differentiation of the pluripotent stem cells. PLoS ONE 8, e64291 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  82. Ee, L.-S. et al. Enhancer remodeling by OTX2 directs specification and patterning of mammalian definitive endoderm. Dev. Cell https://doi.org/10.1016/j.devcel.2025.07.020 (2025).

  83. Umair, Z. et al. Dusp1 modulates activin/smad2 mediated germ layer specification via FGF signal inhibition in Xenopus embryos. Anim. Cells Syst. 24, 359–370 (2020).

    Article  CAS  Google Scholar 

  84. Sanjana, N. E., Shalem, O. & Zhang, F. Improved vectors and genome-wide libraries for CRISPR screening. Nat. Methods 11, 783–784 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Diao, Y. et al. Pax3/7BP is a Pax7- and Pax3-binding protein that regulates the proliferation of muscle precursor cells by an epigenetic mechanism. Cell Stem Cell 11, 231–241 (2012).

    Article  CAS  PubMed  Google Scholar 

  86. Diao, Y., Wang, X. & Wu, Z. SOCS1, SOCS3, and PIAS1 promote myogenic differentiation by inhibiting the leukemia inhibitory factor-induced JAK1/STAT1/STAT3 pathway. Mol. Cell. Biol. 29, 5084–5093 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Yu, Y. et al. A stress-induced miR-31–CLOCK–ERK pathway is a key driver and therapeutic target for skin aging. Nat. Aging 1, 795–809 (2021).

    Article  PubMed  Google Scholar 

  88. Chen, S., Zhou, Y., Chen, Y. & Gu, J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics https://doi.org/10.1093/bioinformatics/bty560 (2018).

  89. Kim, D., Paggi, J. M., Park, C., Bennett, C. & Salzberg, S. L. Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype. Nat. Biotechnol. 37, 907–915 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  90. Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

    Article  CAS  PubMed  Google Scholar 

  91. 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  Google Scholar 

  92. Kong, Y. et al. Transposable element expression in tumors is associated with immune infiltration and increased antigenicity. Nat. Commun. 10, 5228 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  93. Gorkin, D. U. et al. An atlas of dynamic chromatin landscapes in mouse fetal development. Nature 583, 744–751 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. 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 

  95. Feng, J., Liu, T., Qin, B., Zhang, Y. & Liu, X. S. Identifying ChIP-seq enrichment using MACS. Nat. Protoc. 7, 1728–1740 (2012).

    Article  CAS  PubMed  Google Scholar 

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

    Article  PubMed  PubMed Central  Google Scholar 

  97. Ewels, P. A. et al. The nf-core framework for community-curated bioinformatics pipelines. Nat. Biotechnol. 38, 276–278 (2020).

    Article  CAS  PubMed  Google Scholar 

  98. Martin, M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet. J. 17, 10–12 (2011).

    Article  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Open2C et al. Pairtools: From sequencing data to chromosome contacts. PLoS Comput. Biol. 20, e1012164 (2024).

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Open2C et al. Cooltools: Enabling high-resolution Hi-C analysis in Python. PLoS Comput. Biol. 20, e1012067 (2024).

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

    Article  PubMed  PubMed Central  Google Scholar 

  104. van der Weide, R. H. et al. Hi-C analyses with GENOVA: a case study with cohesin variants. NAR Genom. Bioinform 3, lqab040 (2021).

    Article  PubMed  PubMed Central  Google Scholar 

  105. Ou, J. & Zhu, L. J. trackViewer: a Bioconductor package for interactive and integrative visualization of multi-omics data. Nat. Methods 16, 453–454 (2019).

    Article  CAS  PubMed  Google Scholar 

  106. Grant, C. E., Bailey, T. L. & Noble, W. S. FIMO: scanning for occurrences of a given motif. Bioinformatics 27, 1017–1018 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Tse, J. R. & Engler, A. J. Preparation of hydrogel substrates with tunable mechanical properties. Curr. Protoc. Cell Biol. 10, 10.16 (2010).

    Google Scholar 

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Acknowledgements

This study is supported by research funds from the Duke Regeneration Center, Duke Whitehead Scholarship, Glenn Foundation for Medical Research and AFAR Grants for Junior Faculty, National Institutes of Health (NIH) U01HL156064, and R35HG011328 to Y.D. and by the National Institute of General Medical Sciences of the NIH under award number R35GM142504 to Z.M. Y.X. is supported by the Center for Advanced Genomic Technologies postdoctoral fellowship and the Duke Regeneration Center Fellowship to Accelerate Career Independence.

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Contributions

T.S. and Y.D. conceived the study. T.S. performed the experiments and led the bioinformatics analysis, with support from Y.X. N.A., L.C., K.Z., B.D.H., J.O., Z.M. and S.V. T.S. and Y.D. wrote the paper, with contributions from S.V. and Z.M.

Corresponding author

Correspondence to Yarui Diao.

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The authors declare no competing interests.

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Nature Cell Biology thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available.

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Extended data

Extended Data Fig. 1 Mechanical cues regulate TE activity in hESCs.

a, b, RT-qPCR analysis of (a) pluripotency and (b) differentiation marker genes in WT hESCs cultured on soft versus stiff matrices in mTeSR medium. P values are 0.057, 0.067, 0.056 (a), 0.97, 0.22, 0.17, 0.069, 0.25, 0.18, 0.09 (b). n = 3 biologically independent experiments. c, RT-qPCR validation of RNA expression changes in selected TE subfamilies under soft versus stiff conditions. P = 0.00059, P = 0.045, P = 0.0099, P = 0.0053, P = 0.0023. n = 3 biologically independent experiments. d, e, MA scatter plots showing differential (d) H3K27ac and (e) H3K9me3 ChIP-seq signals at individual TE loci. Red dots: upregulated loci in soft; blue dots: downregulated loci in soft (Fold change > 1.5). f, g, Box plots quantifying changes in (f) H3K27ac and (g) H3K9me3 ChIP-seq signals across TE subfamilies in soft versus stiff conditions. n = 2 biologically independent experiments. h, KEGG and GO pathway analyses of genes located within 50 kb of TE loci exhibiting differential H3K27ac or H3K9me3 signals in response to stiffness. P values were calculated by the two-tailed Student’s t-test (a –c). NS, not significant. Data in (a - c) represent mean ± s.e.m. In box plots (f, g), center lines represent the median value, box limits the 25th and 75th percentiles, and whiskers denote minima and maxima (1.5× the interquartile range). Source numerical data are available in source data.

Extended Data Fig. 2 Mechanical cues regulate the HERV-H via YAP/TEAD1.

a, Immunofluorescence staining of YAP localization in WT hESCs cultured on substrates with different stiffness. YAP is predominantly nuclear on stiff substrates but translocates to the cytoplasm on soft substrates. Higher-magnification insets highlight nuclear versus cytoplasmic localization. b, RT-qPCR analysis of YAP target genes CCN1 and CCN2 in hESCs cultured on soft versus stiff substrates. P = 0.029, P = 0.0046. n = 3 biologically independent experiments. c, GSEA analysis indicating that YAP signature genes are negatively enriched in soft versus stiff conditions. d, Overlap of YAP/TEAD1 co-occupied genomic loci with TE sequences. The numbers of overlapping and non-overlapping loci are indicated. e, Jaccard index analysis quantifying the overlap between YAP/TEAD1 binding peaks and TE loci. f, (Left) Heatmap displaying H3K27ac ChIP-seq signals at 305 YAP/TEAD1 co-bound LTR7 loci under stiff versus soft conditions. (Right) Box plot quantifying H3K27ac signals at these loci, showing reduced enhancer activity in soft matrices. n = 2 biologically independent experiments. g, RT-qPCR analysis of HERVH-int expression in hESCs cultured on Matrigel-coated polyacrylamide hydrogels with varying stiffness. P = 5.6e-9. n = 3 biologically independent experiments. h, RT-qPCR analysis of HERVH-int expression in hESCs cultured on Matrigel-coated CytoSoft silicon gels at stiff (64 kPa) or soft (2 kPa) substrates. P = 0.012. n = 3 biologically independent experiments. i, Cell morphology and AP staining analysis of hESCs expressing empty vector or YAP5SA under self-renewal culture conditions. j, RT-qPCR analysis of OCT4 mRNA expression in hESCs expressing empty vector control or YAP5SA under self-renewal culture conditions. P = 0.00057. n = 3 biologically independent experiments. P values were calculated by the two-tailed Student’s t-test (b, g, h, j). Data in (b, g, h, j) represent mean ± s.e.m. In box plots(f), center lines represent the median value, box limits the 25th and 75th percentiles, and whiskers denote minima and maxima (1.5× the interquartile range). Source numerical data are available in source data.

Extended Data Fig. 3 YAP/TEAD1 control the enhancer activity of LTR7s.

a, Western blot validation of YAP and TEAD1 knockout (KO) efficiency in hESCs. b, AP staining and morphology analysis showing that YAP and TEAD1 KO does not impair hESC pluripotency maintenance. c, d, RT-qPCR analysis of (c) pluripotency genes and (d) HERVH-int expression in WT, YAP-KO, and TEAD1-KO hESCs. P = 0.016, 0.25, 0.18, 0.85, 0.95, 0.056, 0.43, 0.06, 0.76, 0.49, 0.96, 0.0058(c); 0.011, 0.0099, 0.011, 0.0082 (d). n = 3 biologically independent experiments. e, MA scatter plot showing RNA expression changes of HERVH-int in YAP-KO versus WT hESCs. Downregulated HERVH-int loci are highlighted in blue, while upregulated loci are in red (fold change > 1.2). f, Density plot showing the genomic distance between LTR7 elements and the nearest transcription start site (TSS). 97.1% of YAP/TEAD1-co-bound LTR7s are located more than 2 kb from a TSS. g, Pie chart summarizing histone modifications at 342 YAP/TEAD1-co-occupied LTR7s that do not overlap with TSSs. h, i, Luciferase reporter assays quantifying the enhancer activity of LTR7 elements in a minimal promoter reporter construct in WT hESCs (h) and in YAP-KO and TEAD1-KO hESCs (i). P = 0.0086 (h), P = 0.0.0029, P = 0.0069, P = 0.03, P = 0.011(i) n = 3 biologically independent experiments. j, Volcano plot showing differential BRD4 binding at genomic loci. BRD4 peaks overlapping with LTR7s are predominantly downregulated in YAP-KO or TEAD1-KO hESCs compared to WT control hESCs, indicating reduced enhancer activity. P values were calculated by the two-tailed Student’s t-test (c, d, h, i). NS, not significant. Data in (c, d, h, i) represent mean ± s.e.m. Source numerical data and unprocessed blots are available in source data.

Source data

Extended Data Fig. 4 YAP recruits CTCF to modulate long-range enhancer-promoter interactions between human genes and TE MREEs.

a, RAD21 binding is detected at 81% of YAP/CTCF co-occupied TE loci. b, Box plot quantifying CTCF ChIP-seq signal at YAP/CTCF co-occupied TEs under stiff and soft conditions. n = 2 biologically independent experiments. c, d, (c) Heatmap and (d) box plot showing a reduction in RAD21 signal at YAP/CTCF co-occupied TEs under soft versus stiff conditions. n = 2 biologically independent experiments. e, MA scatter plot showing RAD21 ChIP-seq signal changes at YAP/CTCF co-occupied TE loci under soft versus stiff conditions. Loci with significantly reduced RAD21 binding in soft matrices are highlighted in blue, and those with increased binding are in red. f, Density plot showing the genomic distance of YAP/CTCF co-occupied TEs from the nearest TAD boundaries in hESCs. g, h, (g) Aggregated insulation scores of YAP/CTCF co-occupied TEs under soft and stiff conditions. The local maximal insulation scores indicate that these elements’ genome insulation function, if any, do not reduce in soft matrices. (h) Quantification of insulation score differences. n = 2 biologically independent experiments. i, Box plot quantifying H3K27ac signals at YAP/CTCF co-occupied TEs under soft versus stiff conditions. n = 2 biologically independent experiments. j, Density plot showing the genomic distance between YAP and CTCF peak summits at their co-occupied TE loci. km, (k) Heatmaps, (l) aggregated ChIP-seq signals, and (m) box plots comparing CTCF ChIP-seq signals at TE loci co-occupied by YAP and CTCF versus those bound by CTCF alone. n = 2 biologically independent experiments. In box plots(b, d, h, i, and m), center lines represent the median value, box limits the 25th and 75th percentiles, and whiskers denote minima and maxima (1.5× the interquartile range). Source numerical data are available in source data.

Source data

Extended Data Fig. 5 FAM-LTR7 acts as a YAP-regulated TE MREE of FAM189A2 to inhibit definitive endoderm differentiation.

a, UMAP visualization of cell types during early human development. b, YAP mRNA levels across indicated developmental stages. c, d, Immunostaining of YAP in hESCs and DE cells. (c) Representative images showing YAP localization. (d) Quantification of nuclear/cytoplasmic YAP ratio. P = 0.038 (d). n = 3 biologically independent experiments. e, f, Western blot analysis of YAP. Representative blots (e); quantification of YAP signal (f). P = 0.028 (f). n = 3 biologically independent experiments. g, RT-qPCR analysis of YAP targets in hESCs and DE cells. P = 0.0015, P = 0.013. n = 3 biologically independent experiments. h, RT-qPCR analysis in DE cells expressing YAP5SA and control P = 0.0077, P = 0.0036. n = 3 biologically independent experiments. i, HiCAR analysis showing pairwise chromatin contact frequencies within a 300 kb genomic window centered around all LTR7 sequences in hESCs. j, k, Quantification of H3K27ac under (j) soft vs. stiff matrices and (k) WT vs. YAP KO conditions. n = 2 biologically independent experiments. l, Two sgRNAs targeting the flanking sequences of FAM-LTR7 (left). RT-qPCR analysis shows the FAM189A2 expression (right). P = 0.16, P = 0.18. n = 3 biologically independent experiments. m, RT-qPCR quantification of FAM189A2 in FAM-LTR7 KO hESC clones compared to WT. P = 0.0032, P = 0.0006, P = 0.0008. n = 3 biologically independent experiments. n, Schematic illustration of the FAM-LTR7 locus in a representative mutant hESC. o, Genome browser screenshot displaying RNA-seq data from WT and FAM-LTR7 KO hESCs. p, RT-qPCR analysis of FAM189A2 expression in WT and FAM-LTR7 KO hESCs. P = 0.0015, P = 0.86. n = 3 biologically independent experiments. q, RT-qPCR analysis of DE markers in DE cells with FAM-LTR7 deletion. P = 0.1, P = 0.1. n = 3 biologically independent experiments. P values were calculated using the two-tailed Student’s t-test (d, f - h, l, m, p, q). Data in (d, f - h, j - m, p, q) represent mean ± s.e.m. Source numerical data and unprocessed blots are available in source data.

Extended Data Fig. 6 FAM189A2 inhibits mesoderm differentiation of hESCs.

a, RT-qPCR analysis of FAM189A2 mRNA expression in H1 hESCs and lineage-specified cells. P = 0.00098, P = 0.0038, P = 0.00056. n = 3 biologically independent experiments. b, RT-qPCR analysis of mesoderm markers in control and FAM189A2 knockdown hESCs undergoing mesoderm differentiation. P = 3.6e-06, P = 0.0006. n = 3 biologically independent experiments. c, Immunofluorescence staining of mesoderm marker T in control and FAM189A2 knockdown cells. Red: T; Blue: DAPI. n = 3 biologically independent experiments. d, Heatmap showing decreased expression of mesoderm markers in hESC-derived mesoderm cells from FAM189A2 knockdown hESCs compared to WT control cells. Blue indicates genes downregulated upon FAM189A2 depletion during mesoderm differentiation. e, Gene Set Enrichment Analysis (GSEA) of differentially expressed genes showing repression of Wnt signaling (top) and mesoderm developmental signatures (bottom) in FAM189A2 knockdown cells compared to control cells. P values were calculated using a two-tailed Student’s t-test (a, b). Data in (a, b) represent mean ± s.e.m. Source numerical data are available in source data.

Extended Data Fig. 7 Mechanical regulation of TE subfamilies, including HERVH-int, in cancer cells.

a, Volcano plot showing RNA expression changes of TE subfamilies in ovarian cancer cells cultured on soft vs. stiff substrates. Blue dots indicate downregulated TE RNAs in soft conditions, while red dots indicate upregulated TE RNAs. HERVH-int, which is significantly downregulated, is highlighted. Data from GEO accession GSE178888. b, (Left) Genome browser snapshot of a representative locus showing reduced HERVH-int RNA expression in ovarian cancer cells on a soft substrate. (Right) Bar plot showing the quantification of HERVH-int expression. P = 0.0056. n = 3 biologically independent experiments. c, Volcano plot showing RNA expression changes of TE subfamilies in breast cancer cells cultured on soft vs. stiff substrates. Blue and red dots indicate downregulated and upregulated TE RNAs, respectively, in soft conditions. HERVH-int is highlighted. Data from GEO accession GSE127887. d, (Left) Genome browser snapshot of a representative locus showing reduced HERVH-int RNA expression in breast cancer cells on a soft substrate. (Right) Bar plot showing the quantification of HERVH-int expression. P = 1.5е-06. n = 3 biologically independent experiments. P values were calculated using a two-tailed Student’s t-test (b, c). Data in (b, c) represent mean ± s.e.m. Source numerical data are available in source data.

Extended Data Fig. 8 YAP recruits CTCF to mediate long-range chromatin interactions.

a, Heatmaps showing CTCF occupancy at YAP/CTCF co-occupied peaks in WT and YAP-KO cells. b, c, Aggregate Peak Analysis (APA) plots (b) and box plot quantification (c) of chromatin interactions anchored at YAP/CTCF co-occupied peaks in WT and YAP-KO cells. Loss of YAP reduces these interactions. n = 2 biologically independent experiments. In box plots(c), center lines represent the median value, box limits the 25th and 75th percentiles, and whiskers denote minima and maxima (1.5× the interquartile range). Source numerical data are available in source data.

Extended Data Fig. 9 YAP and mechanical cues regulate TE-gene chromatin interactions in DE cells.

a, b, Aggregate Peak Analysis (APA) of 1,463 TE enhancer-promoter (E-P) interactions co-occupied by YAP/CTCF under stiff and soft conditions in hESC-derived DE cells. APA plots are shown in (a), and box plots quantifying interaction strength are shown in (b), revealing a substantial weakening of these interactions under soft conditions. n = 2 biologically independent experiments. c, mRNA expression of genes associated with the 1,463 TE E-P pairs is substantially reduced under soft conditions in DE cells. n = 2 biologically independent experiments. d, e, Aggregate Peak Analysis (APA) of 1,463 TE enhancer-promoter (E-P) interactions co-occupied by YAP/CTCF in DE cells derived from YAP KO vs WT control hESCs. APA plots are shown in (d), and box plots quantifying interaction strength are shown in (e), revealing a marked weakening of these interactions under soft conditions. n = 2 biologically independent experiments. f, mRNA expression of genes associated with the 1,463 TE E-P pairs is markedly reduced in YAP KO hESC-derived DE cells. n = 2 biologically independent experiments. In box plots (b, c, e, f), center lines represent the median value, box limits the 25th and 75th percentiles, and whiskers denote minima and maxima (1.5× the interquartile range). Source numerical data are available in source data.

Extended Data Fig. 10 Mechanisms by which FAM189A2, YAP, and mechanical cues regulate DE differentiation.

a, Heatmap showing upregulation of SMAD2/3 target genes in hESC-derived DE cells from FAM189A2 knockdown hESCs compared to WT control cells. Red indicates genes with increased expression upon FAM189A2 depletion. b, GSEA analysis highlighting enrichment of SMAD2/3 target genes that are increased in DE cells derived from FAM189A2 knockdown hESCs compared to WT controls. c, RT-qPCR analysis showing comparable expression of pluripotency markers in DE cells derived from WT and YAP KO hESCs. P = 0.31, P = 0.93, P = 0.73. n = 3 biologically independent experiments. d, Heatmap displaying increased expression of endoderm genes in YAP KO-derived DE cells compared to WT controls. Genes in red are direct YAP targets with YAP binding at their promoters. e, GSEA analysis showing enrichment of endoderm differentiation gene signatures among the genes increased in YAP KO-derived DE cells compared to WT controls. f, RT-qPCR analysis showing comparable expression of pluripotency markers in DE cells derived from WT hESCs cultured on soft vs. stiff matrices. P = 0.7, P = 0.58, P = 0.34. n = 3 biologically independent experiments. g, Heatmap showing upregulated endoderm genes in DE cells cultured on soft vs. stiff matrices. Genes in red are direct YAP targets with YAP binding at their promoters. h, GSEA analysis showing enrichment of endoderm differentiation gene signatures among the genes increased in DE cells cultured on soft vs. stiff matrices. P values were calculated using a two-tailed Student’s t-test (c, f). Data in (c, f) represent mean ± s.e.m. Source numerical data are available in source data.

Supplementary information

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Supplementary Tables

Supplementary Table 1. Sequencing data information. Supplementary Table 2. Oligonucleotide sequences used in this study. Supplementary Table 3. RNA expression changes of the TE subfamily in soft and stiff matrices. Supplementary Table 4. RNA expression changes of the broad TE family in soft and stiff matrices. Supplementary Table 5. Peak number of repeats overlapped with YAP. Supplementary Table 6. TE enhancers and their targets. Supplementary Table 7. LTR7s exhibiting decreased H3K27ac mark in soft versus stiff matrices. Supplementary Table 8. Distance of genes to LTR7s. Supplementary Table 9. LTR7s exhibiting decreased H3K27ac mark in YAP KO versus WT hES cells. Supplementary Table 10. Chromatin interactions at 10 kb resolution identified in hES cells in stiff matrices. Supplementary Table 11. RNA-seq analysis reveals differentially expressed genes in YAP-KO versus WT hES cells. Supplementary Table 12. RNA-seq analysis reveals differentially expressed genes in WT hES cells in stiff versus. soft conditions. Supplementary Table 13. The genes whose promoters forming interactions with YAP-occupied TE MREEs exhibiting decreased H3K27ac modification in both soft matrices and YAP-KO compared with WT cells in stiff matrices. Supplementary Table 14. RNA-seq analysis reveals differentially expressed genes in hES cell-derived mesoderm in FAM189A2 KD versus control cells. Supplementary Table 15. RNA-seq analysis reveals differentially expressed genes in hES cell-derived DE cells in FAM189A2 KD versus control DE cells. Supplementary Table 16. RNA-seq reveals DE genes in YAP-KO versus YAP-WT DE. Supplementary Table 17. RNA-seq in soft versus stiff DE.

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Sun, T., Xu, Y., Angel, N. et al. A subset of transposable elements as mechano-response enhancer elements in controlling human embryonic stem cell fate. Nat Cell Biol (2025). https://doi.org/10.1038/s41556-025-01770-2

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