Abstract
Remote enhancers are thought to interact with their target promoters via physical proximity, yet the importance of this proximity for enhancer function remains unclear. Here we investigate the three-dimensional (3D) conformation of enhancers during mammalian development by generating high-resolution tissue-resolved contact maps for nearly a thousand enhancers with characterized in vivo activities in ten murine embryonic tissues. Sixty-one percent of developmental enhancers bypass their neighboring genes, which are often marked by promoter CpG methylation. The majority of enhancers display tissue-specific 3D conformations, and both enhancer–promoter and enhancer–enhancer interactions are moderately but consistently increased upon enhancer activation in vivo. Less than 14% of enhancer–promoter interactions form stably across tissues; however, these invariant interactions form in the absence of the enhancer and are likely mediated by adjacent CTCF binding. Our results highlight the general importance of enhancer–promoter physical proximity for developmental gene activation in mammals.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$29.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 print issues and online access
$209.00 per year
only $17.42 per issue
Buy this article
- Purchase on Springer Link
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
Sequencing data generated in this study are available at the Gene Expression Omnibus repository under accession number GSE217078. Several mouse embryonic ChIP–seq, DNase-seq, bisulfite-seq and RNA-seq data for different tissues at E11.5 were downloaded from ENCODE (https://www.encodeproject.org/). The CTCF ChIP–seq datasets used for comparison were downloaded from GEO (https://www.ncbi.nlm.nih.gov/geo/) under accession numbers GSM5501396, GSM5501397 and GSM5501398. Enhancer interaction profiles are available at https://www.kvonlab.org/data/echic. Source data are provided with this paper.
Code availability
Public software and packages were used following the developer’s manuals. The custom code used for data analysis has been deposited at GitHub (https://github.com/kvonlab/Chen_et_al_2024) and Zenodo (https://doi.org/10.5281/zenodo.10594800)100.
References
Lettice, L. A. et al. Disruption of a long-range cis-acting regulator for Shh causes preaxial polydactyly. Proc. Natl Acad. Sci. USA 99, 7548–7553 (2002).
Long, H. K. et al. Loss of extreme long-range enhancers in human neural crest drives a craniofacial disorder. Cell Stem Cell 27, 765–783 (2020).
Shlyueva, D., Stampfel, G. & Stark, A. Transcriptional enhancers: from properties to genome-wide predictions. Nat. Rev. Genet. 15, 272–286 (2014).
Long, H. K., Prescott, S. L. & Wysocka, J. Ever-changing landscapes: transcriptional enhancers in development and evolution. Cell 167, 1170–1187 (2016).
Schoenfelder, S. & Fraser, P. Long-range enhancer–promoter contacts in gene expression control. Nat. Rev. Genet. 20, 437–455 (2019).
Dixon, J. R. et al. Topological domains in mammalian genomes identified by analysis of chromatin interactions. Nature 485, 376–380 (2012).
Nora, E. P. et al. Spatial partitioning of the regulatory landscape of the X-inactivation centre. Nature 485, 381–385 (2012).
Lupiáñez, D. G. et al. Disruptions of topological chromatin domains cause pathogenic rewiring of gene–enhancer interactions. Cell 161, 1012–1025 (2015).
Lettice, L. A. et al. Enhancer-adoption as a mechanism of human developmental disease. Hum. Mutat. 32, 1492–1499 (2011).
Northcott, P. A. et al. Enhancer hijacking activates GFI1 family oncogenes in medulloblastoma. Nature 511, 428–434 (2014).
Bulger, M. & Groudine, M. Looping versus linking: toward a model for long-distance gene activation. Genes Dev. 13, 2465–2477 (1999).
Furlong, E. E. M. & Levine, M. Developmental enhancers and chromosome topology. Science 361, 1341–1345 (2018).
Oudelaar, A. M. & Higgs, D. R. The relationship between genome structure and function. Nat. Rev. Genet. 22, 154–168 (2021).
Andrey, G. et al. A switch between topological domains underlies HoxD genes collinearity in mouse limbs. Science 340, 1234167 (2013).
Tolhuis, B., Palstra, R. J., Splinter, E., Grosveld, F. & de Laat, W. Looping and interaction between hypersensitive sites in the active β-globin locus. Mol. Cell 10, 1453–1465 (2002).
Madsen, J. G. S. et al. Highly interconnected enhancer communities control lineage-determining genes in human mesenchymal stem cells. Nat. Genet. 52, 1227–1238 (2020).
Rubin, A. J. et al. Lineage-specific dynamic and pre-established enhancer–promoter contacts cooperate in terminal differentiation. Nat. Genet. 49, 1522–1528 (2017).
Deng, W. et al. Reactivation of developmentally silenced globin genes by forced chromatin looping. Cell 158, 849–860 (2014).
Ghavi-Helm, Y. et al. Enhancer loops appear stable during development and are associated with paused polymerase. Nature 512, 96–100 (2014).
Andrey, G. et al. Characterization of hundreds of regulatory landscapes in developing limbs reveals two regimes of chromatin folding. Genome Res. 27, 223–233 (2017).
Jin, F. et al. A high-resolution map of the three-dimensional chromatin interactome in human cells. Nature 503, 290–294 (2013).
Montavon, T. et al. A regulatory archipelago controls Hox genes transcription in digits. Cell 147, 1132–1145 (2011).
Alexander, J. M. et al. Live-cell imaging reveals enhancer-dependent Sox2 transcription in the absence of enhancer proximity. eLife 8, e41769 (2019).
Benabdallah, N. S. et al. Decreased enhancer–promoter proximity accompanying enhancer activation. Mol. Cell 76, 473–484 (2019).
Gómez Acuña, L. I., Flyamer, I., Boyle, S., Friman, E. T. & Bickmore, W. A. Transcription decouples estrogen-dependent changes in enhancer–promoter contact frequencies and physical proximity. Preprint at bioRxiv https://doi.org/10.1101/2023.03.29.534720 (2023).
Zaugg, J. B. et al. Current challenges in understanding the role of enhancers in disease. Nat. Struct. Mol. Biol. 29, 1148–1158 (2022).
Visel, A., Minovitsky, S., Dubchak, I. & Pennacchio, L. A. VISTA Enhancer Browser—a database of tissue-specific human enhancers. Nucleic Acids Res. 35, D88–D92 (2006).
Attanasio, C. et al. Fine tuning of craniofacial morphology by distant-acting enhancers. Science 342, 1241006 (2013).
Dickel, D. E. et al. Genome-wide compendium and functional assessment of in vivo heart enhancers. Nat. Commun. 7, 12923 (2016).
Dickel, D. E. et al. Ultraconserved enhancers are required for normal development. Cell 172, 491–499 (2018).
Kvon, E. Z. et al. Progressive loss of function in a limb enhancer during snake evolution. Cell 167, 633–642 (2016).
Osterwalder, M. et al. Enhancer redundancy provides phenotypic robustness in mammalian development. Nature 554, 239–243 (2018).
Gorkin, D. U. et al. An atlas of dynamic chromatin landscapes in mouse fetal development. Nature 583, 744–751 (2020).
Smith, C. M. et al. The mouse Gene Expression Database (GXD): 2014 update. Nucleic Acids Res. 42, D818–D824 (2014).
Kvon, E. Z., Waymack, R., Gad, M. & Wunderlich, Z. Enhancer redundancy in development and disease. Nat. Rev. Genet. 22, 324–336 (2021).
Hnisz, D., Shrinivas, K., Young, R. A., Chakraborty, A. K. & Sharp, P. A. A phase separation model for transcriptional control. Cell 169, 13–23 (2017).
Fudenberg, G. & Imakaev, M. FISH-ing for captured contacts: towards reconciling FISH and 3C. Nat. Methods 14, 673–678 (2017).
Giorgetti, L. & Heard, E. Closing the loop: 3C versus DNA FISH. Genome Biol. 17, 215 (2016).
Kubo, N. et al. Promoter-proximal CTCF binding promotes distal enhancer-dependent gene activation. Nat. Struct. Mol. Biol. 28, 152–161 (2021).
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).
Paliou, C. et al. Preformed chromatin topology assists transcriptional robustness of Shh during limb development. Proc. Natl Acad. Sci. USA 116, 12390–12399 (2019).
Sagai, T., Hosoya, M., Mizushina, Y., Tamura, M. & Shiroishi, T. Elimination of a long-range cis-regulatory module causes complete loss of limb-specific Shh expression and truncation of the mouse limb. Development 132, 797–803 (2005).
Hsieh, T.-H. S. et al. Enhancer–promoter interactions and transcription are largely maintained upon acute loss of CTCF, cohesin, WAPL or YY1. Nat. Genet. 54, 1919–1932 (2022).
Zuin, J. et al. Nonlinear control of transcription through enhancer–promoter interactions. Nature 604, 571–577 (2022).
Xiao, J. Y., Hafner, A. & Boettiger, A. N. How subtle changes in 3D structure can create large changes in transcription. eLife 10, e64320 (2021).
Williamson, I. et al. Spatial genome organization: contrasting views from chromosome conformation capture and fluorescence in situ hybridization. Genes Dev. 28, 2778–2791 (2014).
Brandão, H. B., Gabriele, M. & Hansen, A. S. Tracking and interpreting long-range chromatin interactions with super-resolution live-cell imaging. Curr. Opin. Cell Biol. 70, 18–26 (2021).
Chen, L.-F., Lee, J. & Boettiger, A. Recent progress and challenges in single-cell imaging of enhancer–promoter interaction. Curr. Opin. Genet. Dev. 79, 102023 (2023).
Jerkovic, I. & Cavalli, G. Understanding 3D genome organization by multidisciplinary methods. Nat. Rev. Mol. Cell Biol. 22, 511–528 (2021).
Pownall, M. E. et al. Chromatin expansion microscopy reveals nanoscale organization of transcription and chromatin. Science 381, 92–100 (2023).
Espinola, S. M. et al. Cis-regulatory chromatin loops arise before TADs and gene activation, and are independent of cell fate during early Drosophila development. Nat. Genet. 53, 477–486 (2021).
Simmons, E. et al. Independence of chromatin conformation and gene regulation during Drosophila dorsoventral patterning. Nat. Genet. 53, 487–499 (2021).
Platt, J. L. et al. Capture‐C reveals preformed chromatin interactions between HIF‐binding sites and distant promoters. EMBO Rep. 17, 1410–1421 (2016).
Ray, J. et al. Chromatin conformation remains stable upon extensive transcriptional changes driven by heat shock. Proc. Natl Acad. Sci. USA 116, 19431–19439 (2019).
Pollex, T. et al. New enhancer–promoter interactions are gained during tissue differentiation and reflect changes in E/P activity. Preprint at bioRxiv https://doi.org/10.1101/2022.12.07.519443 (2022).
Smemo, S. et al. Obesity-associated variants within FTO form long-range functional connections with IRX3. Nature 507, 371–375 (2014).
Birnbaum, R. Y. et al. Functional characterization of tissue-specific enhancers in the DLX5/6 locus. Hum. Mol. Genet. 21, 4930–4938 (2012).
Lettice, L. A. et al. A long-range Shh enhancer regulates expression in the developing limb and fin and is associated with preaxial polydactyly. Hum. Mol. Genet. 12, 1725–1735 (2003).
Li, G. et al. Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation. Cell 148, 84–98 (2012).
Kvon, E. Z. et al. Genome-scale functional characterization of Drosophila developmental enhancers in vivo. Nature 512, 91–95 (2014).
Calhoun, V. C., Stathopoulos, A. & Levine, M. Promoter-proximal tethering elements regulate enhancer–promoter specificity in the Drosophila Antennapedia complex. Proc. Natl Acad. Sci. USA 99, 9243–9247 (2002).
Ringel, A. R. et al. Repression and 3D-restructuring resolves regulatory conflicts in evolutionarily rearranged genomes. Cell 185, 3689–3704 (2022).
Juven-Gershon, T. & Kadonaga, J. T. Regulation of gene expression via the core promoter and the basal transcriptional machinery. Dev. Biol. 339, 225–229 (2010).
Zabidi, M. A. et al. Enhancer–core-promoter specificity separates developmental and housekeeping gene regulation. Nature 518, 556–559 (2014).
Bergman, D. T. et al. Compatibility rules of human enhancer and promoter sequences. Nature 607, 176–184 (2022).
Martinez-Ara, M., Comoglio, F., van Arensbergen, J. & van Steensel, B. Systematic analysis of intrinsic enhancer–promoter compatibility in the mouse genome. Mol. Cell 82, 2519–2531 (2022).
Batut, P. J. et al. Genome organization controls transcriptional dynamics during development. Science 375, 566–570 (2022).
Pachano, T. et al. Orphan CpG islands amplify poised enhancer regulatory activity and determine target gene responsiveness. Nat. Genet. 53, 1036–1049 (2021).
Galouzis, C. C. & Furlong, E. E. M. Regulating specificity in enhancer–promoter communication. Curr. Opin. Cell Biol. 75, 102065 (2022).
Chakraborty, S. et al. Enhancer–promoter interactions can bypass CTCF-mediated boundaries and contribute to phenotypic robustness. Nat. Genet. 55, 280–290 (2023).
Hung, T.-C., Kingsley, D. M. & Boettiger, A. N. Boundary stacking interactions enable cross-TAD enhancer–promoter communication during limb development. Nat. Genet. 56, 306–314 (2024).
Jiang, Y. et al. The methyltransferase SETDB1 regulates a large neuron-specific topological chromatin domain. Nat. Genet. 49, 1239–1250 (2017).
Wang, Y. et al. The 3D Genome Browser: a web-based browser for visualizing 3D genome organization and long-range chromatin interactions. Genome Biol. 19, 151 (2018).
ENCODE Project Consortium. An integrated encyclopedia of DNA elements in the human genome. Nature 489, 57–74 (2012).
Amândio, A. R. et al. Sequential in cis mutagenesis in vivo reveals various functions for CTCF sites at the mouse HoxD cluster. Genes Dev. 35, 1490–1509 (2021).
Flöttmann, R. et al. Noncoding copy-number variations are associated with congenital limb malformation. Genet. Med. 20, 599–607 (2018).
Short, P. J. et al. De novo mutations in regulatory elements in neurodevelopmental disorders. Nature 555, 611–616 (2018).
Firth, H. V. et al. DECIPHER: database of chromosomal imbalance and phenotype in humans using Ensembl resources. Am. J. Hum. Genet. 84, 524–533 (2009).
ENCODE Project Consortium et al. Expanded encyclopaedias of DNA elements in the human and mouse genomes. Nature 583, 699–710 (2020).
Dryden, N. H. et al. Unbiased analysis of potential targets of breast cancer susceptibility loci by capture Hi-C. Genome Res. 24, 1854–1868 (2014).
Hughes, J. R. et al. Analysis of hundreds of cis-regulatory landscapes at high resolution in a single, high-throughput experiment. Nat. Genet. 46, 205–212 (2014).
Orlando, G., Kinnersley, B. & Houlston, R. S. Capture Hi-C library generation and analysis to detect chromatin interactions. Curr. Protoc. Hum. Genet. 98, e63 (2018).
Pennacchio, L. A. et al. In vivo enhancer analysis of human conserved non-coding sequences. Nature 444, 499–502 (2006).
Wingett, S. et al. HiCUP: pipeline for mapping and processing Hi-C data. F1000Res. 4, 1310 (2015).
Cairns, J. et al. CHiCAGO: robust detection of DNA looping interactions in capture Hi-C data. Genome Biol. 17, 127 (2016).
Freire-Pritchett, P. et al. Detecting chromosomal interactions in capture Hi-C data with CHiCAGO and companion tools. Nat. Protoc. 16, 4144–4176 (2021).
Schoenfelder, S. et al. The pluripotent regulatory circuitry connecting promoters to their long-range interacting elements. Genome Res. 25, 582–597 (2015).
Cairns, J., Orchard, W. R., Malysheva, V. & Spivakov, M. Chicdiff: a computational pipeline for detecting differential chromosomal interactions in capture Hi-C data. Bioinformatics 35, 4764–4766 (2019).
Zerbino, D. R., Wilder, S. P., Johnson, N., Juettemann, T. & Flicek, P. R. The Ensembl Regulatory Build. Genome Biol. 16, 56 (2015).
Yu, G., Wang, L.-G., Han, Y. & He, Q.-Y. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16, 284–287 (2012).
Wu, T. et al. clusterProfiler 4.0: a universal enrichment tool for interpreting omics data. Innovation 2, 100141 (2021).
Osterwalder, M. et al. Characterization of mammalian in vivo enhancers using mouse transgenesis and CRISPR genome editing. Methods Mol. Biol. 2403, 147–186 (2022).
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Putri, G. H., Anders, S., Pyl, P. T., Pimanda, J. E. & Zanini, F. Analysing high-throughput sequencing data in Python with HTSeq 2.0. Bioinformatics 38, 2943–2945 (2022).
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).
Chaumeil, J., Micsinai, M. & Skok, J. A. Combined immunofluorescence and DNA FISH on 3D-preserved interphase nuclei to study changes in 3D nuclear organization. J. Vis. Exp. 3, e50087 (2013).
Naciri, I. et al. Linking chromosomal silencing with Xist expression from autosomal integrated transgenes. Front. Cell Dev. Biol. 9, 693154 (2021).
Chaumeil, J., Augui, S., Chow, J. C. & Heard, E. Combined immunofluorescence, RNA fluorescent in situ hybridization, and DNA fluorescent in situ hybridization to study chromatin changes, transcriptional activity, nuclear organization, and X-chromosome inactivation. Methods Mol. Biol. 463, 297–308 (2008).
Bolland, D. J., King, M. R., Reik, W., Corcoran, A. E. & Krueger, C. Robust 3D DNA FISH using directly labeled probes. J. Vis. Exp. https://doi.org/10.3791/50587 (2013).
Chen, Z. & Kvon, E. Z. Analysis pipeline for Chen_et_al_2024 paper. Zenodo https://doi.org/10.5281/zenodo.10594800 (2024).
Kvon, E. Z. et al. Comprehensive in vivo interrogation reveals phenotypic impact of human enhancer variants. Cell 180, 1262–1271 (2020).
Uslu, V. V. et al. Long-range enhancers regulating Myc expression are required for normal facial morphogenesis. Nat. Genet. 46, 753–758 (2014).
Padhi, E. M. et al. Coding and noncoding variants in EBF3 are involved in HADDS and simplex autism. Hum. Genomics 15, 44 (2021).
Turner, T. N. et al. Genomic patterns of de novo mutation in simplex autism. Cell 171, 710–722 (2017).
Shibata, M., Kurokawa, D., Nakao, H., Ohmura, T. & Aizawa, S. MicroRNA-9 modulates Cajal–Retzius cell differentiation by suppressing Foxg1 expression in mouse medial pallium. J. Neurosci. 28, 10415–10421 (2008).
Shimogori, T. et al. A genomic atlas of mouse hypothalamic development. Nat. Neurosci. 13, 767–775 (2010).
Rodríguez-Carballo, E. et al. The HoxD cluster is a dynamic and resilient TAD boundary controlling the segregation of antagonistic regulatory landscapes. Genes Dev. 31, 2264–2281 (2017).
Acknowledgements
We acknowledge the UCI Transgenic Mouse Facility for help with generation of enhancer-knockout mice and the UCI Genomics Research and Technology Hub for help with sequencing as well as L. Scipioni and S. Sun for help with DNA FISH. This work was supported by National Institutes of Health grants R00HG009682 and DP2GM149555 (to E.Z.K.), R01HG003988 (to L.A.P.) and F31HD112201 (to G.B.). Z.C. was supported by NSF grant DMS1763272 (to Qing Nie) and Simons Foundation grant 594598 (to Qing Nie). J.L.-R. is funded by the Spanish Ministerio de Ciencia e Innovación (grant PID2020-113497GB-I00 and institutional María de Maeztu grant CEX2020-001088-M). Research conducted at the E.O. Lawrence Berkeley National Laboratory was performed under Department of Energy Contract DE-AC02-05CH11231, University of California. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
Author information
Authors and Affiliations
Contributions
E.Z.K. conceived the project with input from Z.C., V.S., D.E.D., A.V. and L.A.P. Z.C., V.S., I.B. and E.Z.K. designed experiments. Z.C., V.S., G.B., S.J., B.C. and E.Z.K. performed capture Hi-C experiments, and Z.C. analyzed the data with input from E.Z.K. and B.J.M. Z.C., S.J., A.D. and E.Z.K. performed enhancer-knockout studies, and Z.C. analyzed the data. Z.C. and G.B. performed 3D-FISH experiments and analyzed the data. A.A.-C. and J.L.-R. performed ISH experiments. E.Z.K and Z.C. wrote the paper with input from the remaining authors.
Corresponding author
Ethics declarations
Competing interests
The authors declare no competing interests.
Peer review
Peer review information
Nature Genetics thanks Daniel Ibrahim, Douglas Higgs and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
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 Enhancer capture Hi-C identifies enhancer-centric chromatin interactions in mouse embryonic tissues.
a, Unique on-target read counts for each library. The percentages above indicate the capture rates for each library. b, c, Principal component analysis and hierarchical clustering of all replicates based on the presence of peaks called by CHiCAGO in each replicate (considering peaks with valid di-tags on neighboring fragments). d, Significant enhancer-centric chromatin interactions identified in this study. The number on each link represents the number of fragments falling into different annotation categories and the width of links is proportional to the percentage (in the parentheses) of different kinds of interactions. Only interactions within 2 Mb are included. CTCF sites with ‘B’: CTCF sites at TAD boundary; Pc: polycomb; Enh: enhancers; Bait-Enh: baited enhancers; Pr: promoters. e, An average number of interactions detected per bait for different kinds of baits (promoter (n = 176), enhancer (n = 935) and negative control elements (n = 87)). Data are represented as mean ± s.e.m. f, Distribution of genomic distances between enhancers and the TSSs of interacting genes (black, frequencies; red, cumulative). g, Violin plots showing read counts on promoters of active genes that interact with enhancer baits (n = 541), promoter baits (n = 126) and control element baits (n = 25). The central horizontal lines are the median, with the boxes extending from the 25th to the 75th percentiles. The whiskers further extend by ±1.5 times the interquartile range from the limits of each box. h, Histogram showing the proportion of bait regions that interact with proximal genes and distal genes. i, Venn diagram showing the overlap between significant interactions called from enhancer baits and corresponding promoter baits. All P values were calculated by a two-sided Wilcox test and adjusted for multiple testing. j, Zoom-in view on Zic1/Zic4 locus for hs654 interaction profiles across 10 tissues. The average size for each pooled fragment is ~3 kb. FB, forebrain. MB, midbrain. HB, hindbrain. CF, face. HR, heart. FL, forelimb. HL, hindlimb. TK, trunk. TL, tail. NT, neural tube.
Extended Data Fig. 2 Examples of enhancer—promoter interactions linked to congenital disorders.
a, Hs1507 limb enhancer (green) located in the non-coding region which is duplicated in patients with polydactyly (pink bar indicates the homologous region in the mouse genome)8. Hs1507 forms significant chromatin interactions with the promoter of the Epha4 (blue line) located ~1.5 Mb away. Shown is the Epha4 genomic region (chr1:74,788,119-77,634,678; mm10). b, Many de novo rare variants identified in patients with preaxial polydactyly101 are located in the ZRS limb enhancer (green bar) which forms significant interactions with the promoter of Shh located ~850 kb away. Shown is the Shh (blue line) genomic region (chr5:28,320,000-29,400,000; mm10). c, Hs1877 face enhancer (green) located in the non-coding region containing 146 SNPs found in patients with cleft lip risk (purple bar indicates the homologous region in the mouse genome)102. Hs1877 forms significant chromatin interactions with the promoter of the Myc (blue line) located ~900 kb away in the face. The Myc genomic region (chr15:61,880,003-63,506,895; mm10). d, Three de novo rare variants identified in patients with autism are located in the hs737 midbrain/hindbrain enhancer (green bar)103,104, which forms strong significant interactions with the promoter of Ebf3 (blue line) located ~1,000 kb away in the midbrain. Shown is the Ebf3 genomic region (chr7:136,018,204-137,420,338; mm10). Red arrowheads indicate capture Hi-C viewpoints.
Extended Data Fig. 3 Examples of enhancer—enhancer chromatin interactions.
a, The Mir9-2 genomic region (chr13:83,558,457-84,861,438; mm10) is shown with chromatin interaction heatmaps centered on hs268 (blue), hs267 (green), hs266 (yellow) and hs853 (red) enhancers in the forebrain (FB) and forelimb (FL). Shown on the top are hs268, hs267, hs266 and hs853 enhancer activities in a transgenic mid-gestation (E11.5) mouse embryo, which match with the expression profiles of Mir9 in the brain and neural tube at E11.5105,106. Red arrowheads indicate capture Hi-C viewpoints. Arches indicate significant interactions in the forebrain. Shown on the bottom are H3K27ac (yellow) and H3K4me3 (green) ChIP-seq tracks in forebrain and limb buds (LB) at E11.5, CTCF (light blue) ChIP-seq tracks in the whole brain (WB) and forelimb at E12.533,74,75,107. b, Schematic depicting 3D chromatin interactions between enhancers and Mir9-2 gene in the forebrain and forelimb. c, Coronal sections of forebrain for hs268, hs267, hs266 and hs853 enhancer activity from VISTA enhancer database27, which reproducibly label the same subregions in E11.5 forebrain as C130071C03Rik (Mir9-2 precursor) expression106. d, e, Chromatin interaction heatmaps centered on mm1165, hs746, mm428 and mm427 enhancers in the face (CF) and forebrain (FB) for Msx1 genomic region (chr5: 37,554,764-38,206,723; mm10) (d) and hs1315 and mm1403 enhancers in the neural tube (NT) and forelimb (FL) for Tfap2a genomic region (chr13: 39,098,000-41,000,000; mm10) (e). Shown on the top are mm1165, hs746, mm428, mm427, hs1315 and mm1403 enhancer activities in a transgenic mid-gestation (E11.5) mouse embryos. Arches indicate significant interactions. Red arrowheads indicate capture Hi-C viewpoints.
Extended Data Fig. 4 Properties of enhancer-interacting and skipped promoters.
a–c, The CpG methylation (a), mRNA expression levels (b) and DNase signal (c) of enhancer-interacting and skipped promoters in tissues where enhancers are active. High me, high methylation skipped promoters (>50% CpG methylation within ± 1 kb from TSS). Low me, low methylation skipped promoters (<50% CpG methylation within ± 1 kb from TSS). d, e, H3K27me3 (d), H3K9me3 (e) signal at ± 2.5 kb of enhancer-interacting and skipped promoters in tissues where enhancers are active. The pie charts below show the fraction of promoters marked with H3K27me3 or H3K9me3. f, Pie charts showing the fraction of skipped promoters marked by CpG methylation, H3K27me3, H3K9me3 or the combination of marks. g-i, Violin plot showing CpG length (g), or CpG methylation level at transcription start sites for enhancer-interacting and skipped genes with different window sizes ± 250 bp (h) and ± 2 kb (i)). The number of high and low methylated skipped as well as interacting promoters in CpG analysis are n = 58, n = 86 and n = 71 (CF), n = 138, n = 126 and n = 90 (FB), n = 64, n = 116 and n = 96 (FL) and n = 100, n = 162 and n = 102 (HB), n = 55, n = 92 and n = 91 (HL), n = 213, n = 169 and n = 125 (MB) and, n = 87, n = 86 and n = 87 (NT). FB, forebrain. MB, midbrain. HB, hindbrain. CF, face. FL, forelimb. HL, hindlimb. NT, neural tube. HR, heart. P values are calculated by two-sided Wilcoxon rank test after adjusted for multiple testing (a-c, f-i) or by one-sided chi-squared test (d, e). A statistical test was not performed for H3K9me3 since most of the values are zero. The same DNA methylation, mRNA expression, DNaseI hypersensitivity, H3K27ac and H3K9me3 dataset (a mixture of fore- and hindlimb buds) were used for both fore- and hindlimb interaction analyses. For the boxplots in panels a-e and g-i, the central horizontal lines are the median, with the boxes extending from the 25th to the 75th percentiles. The whiskers further extend by ±1.5 times the interquartile range from the limits of each box.
Extended Data Fig. 5 Zic1/Zic4 and Mir9-2 brain enhancer knock-outs.
a, Map of the deleted region encompassing hs654 midbrain enhancer of Zic1/Zic4 together with H3K27ac, DNase-seq, ATAC-seq from midbrain and conservation track across 60 species. b, Sanger sequencing of the PCR product from hs654 knock-out mice (n = 4 biological replicates). c, representative PCR genotyping results of the hs654 enhancer knockout mice. Lanes in the gel were rearranged so that results for wild-type and heterozygous mice are adjacent to each other. d, Map of the deleted region encompassing hs267, hs266 and hs853 forebrain enhancers of Mir9-2 together with H3K27ac, DNase-seq, ATAC-seq from midbrain and conservation track across 60 species. e, Sanger sequencing of the PCR product from hs267-853 knock-out mice (n = 3 biological replicates). f, representative PCR genotyping results of the hs267-853 enhancer knockout mice. g, Genotype frequency data for enhancer knockout lines. Mice homozygous for either deletion were born at normal Mendelian ratios, and no gross phenotypes or impairments were observed. P-values were calculated using the one-sided chi-square test.
Extended Data Fig. 6 Enhancer–promoter interaction frequency across tissues.
a, The ratio of E–P interaction frequency between active and inactive tissues. Red dashed line indicates no difference between active and inactive tissues. b, Univariate logistic regression for relative interaction frequencies and enhancer activity across all tissues. c, The ratio of E–P interaction frequency between active and inactive tissues for interactions within or across TADs. d, The distribution of distances between the closest TAD boundary and enhancer for enhancers acting within or across TADs. e, The ratio of interaction frequency between active and inactive tissues on interacting promoters or intervening regions before and after removing ENCODE annotated elements ( ± 20 kb). Red dashed line indicates no difference between active and inactive tissues. f, The ratio of E–P interaction frequency between active and inactive tissues for enhancers with different ranks. Only tissues with ≥10 interactions in each rank category are shown. g, The fold-change of gene expression levels between active state (baited enhancers interact with active promoters) and inactive state (baited enhancers don’t interact with promoters or in inactive tissues). Data are represented as mean ± s.e.m. h, The ratio of E–P interaction frequency between active and inactive tissues for expressed genes (TPM > = 0.5) and lowly expressed or inactive genes (TPM < 0.5). i, Chromatin interaction profiles in forebrain, midbrain and hindbrain centered on the enhancer hs1172 at Nr2f1 locus (chr13:78,057,768-78,705,499). j, The ratio of E–P interaction frequency between active and inactive brain regions for enhancers active in one of the brain domains. k-m, Cumulative frequency plots of interprobe distances for the indicated loci and tissues. n-p, Frequency distribution of FISH interprobe distances in 250 nm bins between Zic1/4 and hs654 (n), Mir9-2 and hs266 (o), Snai2 and hs1431 (p) in indicated tissues. P values are calculated by paired-sample (a, c, e, g, h, j) or unpaired-sample (d, f) two-sided Wilcoxon rank test and adjusted for multiple testing or by one-sided chi-squared test (b, n-p). For the boxplots in panels a, c-f, h and j, the central horizontal lines are the median, with the boxes extending from the 25th to the 75th percentiles. The whiskers further extend by ±1.5 times the interquartile range from the limits of each box.
Extended Data Fig. 7 Properties of invariant enhancer–promoter interactions.
a, Metaplot showing average ratio of enhancer interaction frequency between active and inactive tissues for invariant (interactions present in all 7 main tissues: brain, face, limb, heart, neural tube, trunk and tail, n = 171) and tissue-specific ( ≤ 6 main tissues, n = 775) interactions. Light blue/orange shading indicates 95% confidence intervals estimated by non-parametric bootstrapping. 10 kb upstream and downstream of enhancer bait and target promoter are also indicated (grey bar). b, The average ratio of invariant enhancer-promoter interaction frequency between active and inactive tissues for enhancers active in the brain, face, limb, heart and neural tube E–P. Data is shown only for tissues with at least 20 active enhancers that form invariant E–P interactions. P values were calculated by paired-sample two-sided Wilcox test and adjusted for multiple testing. c, The number of tissues in which enhancers forming invariant (10 tissues, n = 98) or tissue-specific ( ≤ 4 tissues, n = 196) E–P interactions are active in vivo. d, The average phyloP scores of enhancers forming invariant (10 tissues, n = 98) or tissue-specific ( ≤ 4 tissues, n = 196) E–P interactions. P values in panels c and d were calculated by two-sided Wilcox test. e, Gene Ontology enrichment for genes that form invariant (10 tissues) E–P interactions (Biological process and Molecular function). Q values were calculated by over-representation test and adjusted for multiple testing. For the boxplots in panels b-d, the central horizontal lines are the median, with the boxes extending from the 25th to the 75th percentiles. The whiskers further extend by ±1.5 times the interquartile range from the limits of each box.
Extended Data Fig. 8 Tissue specificity of enhancer-enhancer chromatin interactions.
a, Pie chart showing the fraction of E–E interactions present in different numbers of tissues. b, The average ratio of E–E interaction frequency between active and inactive tissues for enhancers active in neural tube, heart, tail and trunk. The number of E–E interactions for each tissue is indicated at the top. P values were calculated by paired-sample two-sided Wilcox test and adjusted for multiple testing. c, The average ratio of enhancer–enhancer interaction frequency between active and inactive tissues for enhancers of different ranks. The E–E interaction number for rank 3 to 5 are n = 217, n = 122 and n = 69 (brain), n = 53, n = 59 and n = 18 (cf), n = 100, n = 84 and n = 45 (limb), n = 80, n = 51 and n = 32 (nt), respectively. Cf: face. Nt: neural tube. P values were calculated by unpaired-sample two-sided Wilcox test with multiple testing. For the boxplots in panels b and c, the central horizontal lines are the median, with the boxes extending from the 25th to the 75th percentiles. The whiskers further extend by ±1.5 times the interquartile range from the limits of each box.
Extended Data Fig. 9 CRISPR/Cas9-mediated ZRS limb enhancer replacement with a fragment of the lacZ gene.
a, Schematic overview of the strategy for ZRS enhancer replacement. A 4.5 kb mouse genomic region containing the ZRS enhancer (red) is shown together with the vertebrate conservation track (dark blue). The donor vector contained two homology arms (gray) and an inactive fragment of the lacZ coding sequence (blue). The sgRNA recognition site is indicated in purple. PCR primers used for genotyping are shown as arrows. b, PCR genotyping analysis of heterozygous and wildtype mice using primer pairs LacZ-F1 and LacZ-R1 or LacZ-F2 and LacZ-R2. See Methods for details. c, Shh whole-mount in situ hybridization in E10.5 wild type (left) and ZRSlacZ/lacZ knock-in embryos (n ≥ 3 biological replicates for each genotype). Shh expression is not detectable in limb buds but is present elsewhere in the embryo.
Supplementary information
Supplementary Tables 1–5
Supplementary Table 1. Enhancer bait regions. Supplementary Table 2. Enhancer-centric significant interactions. Supplementary Table 3. Interactions for regions linked to human congenital disorders. Supplementary Table 4. Probe information for 3D DNA FISH. Supplementary Table 5. Primer sequences used in this study.
Source data
Source Data Fig. 5
Statistical source data for 3D DNA FISH.
Source Data Extended Data Fig. 5
Uncropped gels for Extended Data Fig. 5.
Source Data Extended Data Fig. 9
Uncropped gels for Extended Data Fig. 9b and all WISH images for Extended Data Fig. 9c.
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.
About this article
Cite this article
Chen, Z., Snetkova, V., Bower, G. et al. Increased enhancer–promoter interactions during developmental enhancer activation in mammals. Nat Genet 56, 675–685 (2024). https://doi.org/10.1038/s41588-024-01681-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41588-024-01681-2
This article is cited by
-
Enhancer–promoter interactions become more instructive in the transition from cell-fate specification to tissue differentiation
Nature Genetics (2024)
-
Enhancer contacts during embryonic development show diverse interaction modes and modest yet significant increases upon gene activation
Nature Genetics (2024)