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3D structures of individual mammalian genomes studied by single-cell Hi-C
Open accessAbstract
The folding of genomic DNA from the beads-on-a-string-like structure of nucleosomes into higher-order assemblies is crucially linked to nuclear processes. Here we calculate 3D structures of entire mammalian genomes using data from a new chromosome conformation capture procedure that allows us to first image and then process single cells. The technique enables genome folding to be examined at a scale of less than 100 kb, and chromosome structures to be validated. The structures of individual topological-associated domains and loops vary substantially from cell to cell. By contrast, A and B compartments, lamina-associated domains and active enhancers and promoters are organized in a consistent way on a genome-wide basis in every cell, suggesting that they could drive chromosome and genome folding. By studying genes regulated by pluripotency factor and nucleosome remodelling deacetylase (NuRD), we illustrate how the determination of single-cell genome structure provides a new approach for investigating biological processes.
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“In regard to chromatin structure, Stevens and colleagues reported that the combination of chromosome conformation capture (3C) and tagged fluorescent imaging was able to detect the folding of a genomic sequence <100bp in a single cell (303).”
From Epigenetic Modifications in Stress Response Genes Associated With Childhood Trauma (2019) · cites this paper as [303]
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“Currently, single-cell Hi-C studies confirm the presence of TADs in individual cells but demonstrate significant variability in their shape (i.e., in the folding of DNA within TADs) [142,143,144,145].”
From Enhancer Function in the 3D Genome (2023) · cites this paper as [144]
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Citations
Cites
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Si-C is a method for inferring super-resolution intact genome structure from single-cell Hi-C data
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“2d shows that the variability in the Si-C ensembles at three resolutions (median RMSDs 0.1 nuclear radii) are comparable to the published NucDynamics 100-kb structure ensembles 9 .”
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BackgroundNanog Expression in Embryonic Stem Cells – An Ideal Model System to Dissect Enhancer Function
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“By computing a complete 3D genome structure from single-cell Hi-C data we have shown [9] that it is possible to overcome the limitation of Hi-C, of only detecting DNA sequences in close spatial proximity, because we can now determine distances between loci regardless of whether they have direct…”
BackgroundMethodInfluentialSelf-citationA tour of 3D genome with a focus on CTCF
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Nanoscale 3D DNA tracing in single human cells visualizes loop extrusion directly in situPreprint
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Application of single-cell multi-omics approaches in horticulture research
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The Dynamic 3D Genome in Gametogenesis and Early Embryonic Development
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“Single-cell Hi-C [21] Single-cell Hi-C Crosslinking, single nuclei sorting with FACS, nuclei imaging, overlaid nuclei with low melting agarose.”
MethodTopology of Folded Molecular Chains: From Single Biomolecules to Engineered Origami
Scalvini, B., Sheikhhassani, V., Woodard, J. C., Aupič, J., Dame, R. T., Jerala, R., & Mashaghi, A. (2020) · Trends in Chemistry · doi:10.1016/j.trechm.2020.04.009 · Cited by 21
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Deep generative modeling and clustering of single cell Hi-C data
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Bayesian inference of chromatin structure ensembles from population-averaged contact data
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“In structures calculated from single-cell Hi-C data (9), TADs have been shown to vary widely in terms of compaction between individual cells.”
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“This question has been addressed extensively for bulk data using both experimental and computational approaches (He et al. 2014; Javierre et al. 2016; Cao et al. 2017; Jung et al. 2019).”
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“…for understanding the link between cell function and 3D genome structure [5], [6], [7], [8], [9], but also offers the potential to reconstruct the 3D genome structure of both haploid and diploid cells [10], [11], [12], offering valuable insights into chromatin dynamics during the cell cycle.”
Chromatin loops and causality loops: the influence of RNA upon spatial nuclear architecture
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Hi-C implementation of genome structure for in silico models of radiation-induced DNA damage
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“With the increased development in single-cell Hi-C [53] a development of the G-NOME software would be to use data to perform single-cell conformation modelling.”
MethodParo, R., Grossniklaus, U., Santoro, R., & Wutz, A. (2021) · Learning materials in biosciences · doi:10.1007/978-3-030-68670-3 · Cited by 26
Self-citationChawla, A., Nagy, C., & Turecki, G. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22147612 · Cited by 22
“Employing a modified sc-Hi-C-seq protocol that allows imaging of single cells before capture in mouse ESCs showed concentric rings of A/B surrounding an internal nucleolus across all cells and a strong correlation between gene expression and locational depth within the A compartment [49].”
MethodPerspectives for the reconstruction of 3D chromatin conformation using single cell Hi-C data
Kos, P. I., Galitsyna, A. A., Ulianov, S. V., Gelfand, M. S., Razin, S. V., & Chertovich, A. V. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009546 · Cited by 21
“Several techniques for the reconstruction of chromatin conformations from single-cell Hi-C data have been proposed based on polymer models [4, 12] and the Bayesian inference [22].”
BackgroundMethodSnapHiC2: A computationally efficient loop caller for single cell Hi-C data
Li, X., Lee, L., Abnousi, A., Yu, M., Liu, W., Huang, L., Li, Y., & Hu, M. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.05.046 · Cited by 20
“The recently developed single cell Hi-C (scHi-C) [1–4] and its derived technologies, such as sn -m3c-seq [5,6], provide powerful tools to study chromatin spatial organization directly from complex tissues at single cell resolution.”
BackgroundLong interspersed nuclear element 1 and B1/Alu repeats blueprint genome compartmentalization
Li, S., & Shen, X. (2023) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2023.102049 · Cited by 20
The Impact of Space and Time on the Functional Output of the GenomePreprint
Nollmann, M., Bennabi, I., Götz, M., & Gregor, T. (2021) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a040378 · Cited by 23
Application of Hi-C and other omics data analysis in human cancer and cell differentiation research
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“The first case mainly focused on developing 3C technology [8,14–22] and fundamental analysis methods [23–25].”
BackgroundFolding Features and Dynamics of 3D Genome Architecture in Plant Fungal Pathogens
Xia, C., Huang, L., Huang, J., Zhang, H., Huang, Y., Benhamed, M., Wang, M., Chen, X., Zhang, M., Liu, T., et al. (2022) · Microbiology Spectrum · doi:10.1128/spectrum.02608-22 · Cited by 21
“For this analysis, the trimmed and filtered Hi-C paired reads were processed using the nuc_processing (53), with parameters set as follows: -re1 MboI -n 20 -r 3 -o cyr34 -or report -b/path/to/bowtie2 -p -k -sam -v.”
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“At the nanoscale, Hi- C-based methods have been used to map the spatial interactions between different chromatin compartments ( Belaghzal et al., 2021 ; Falk et al., 2019 ; Lieberman-Aiden et al., 2009 ) and reconstitute the genomic 3D organization in silico ( Stevens et al., 2017 ).”
MethodStructural–Functional Domains of the Eukaryotic Genome
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Epigenetic regulation for acquiring glial identity by neural stem cells during cortical development
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“…et al., 2015; Corces et al., 2016; Kind et al., 2013; Macosko et al., 2015; Nagano et al., 2013; Rotem et al., 2015; Shalek et al., 2014; Stevens et al., 2017), super-resolution imaging (Chen, Guan, & Huang, 2016; Ricci, Cosma, & Lakadamyali, 2017), and epigenetic editing by the use of…”
BackgroundPhysical mechanisms of chromatin spatial organization
Chiariello, A. M., Bianco, S., Esposito, A., Fiorillo, L., Conte, M., Irani, E., Musella, F., Abraham, A., Prisco, A., & Nicodemi, M. (2021) · FEBS Journal · doi:10.1111/febs.15762 · Cited by 20
Genome-wide profiling of DNA repair proteins in single cells
de Luca, K. L., Rullens, P. M. J., Karpińska, M. A., de Vries, S., Gacek‐Matthews, A., Pongor, L. S., Legube, G., Jachowicz, J. W., Oudelaar, A. M., & Kind, J. (2024) · Nature Communications · doi:10.1038/s41467-024-54159-4 · Cited by 21
Comparison of computational methods for 3D genome analysis at single-cell Hi-C level
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Polymer models for the mechanisms of chromatin 3D folding: review and perspective
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DNA Replication Timing Enters the Single-Cell Era
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“When multiple single-cell microscopic data sets were integrated, a chromatin contact map that very much resembled the cell population average Hi-C contact map was obtained: TAD-like structures could be visualized in the target region, and the A/B compartment distribution could also be predicted from the contact map [1…”
BackgroundInfluentialShi, X., Li, Y., Zhou, H., Hou, X., Yang, J., Malik, V., Faiola, F., Ding, J., Bao, X., Modic, M., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-55054-8 · Cited by 21
“Since the nucleolus is a hub for interchromosomal interactions, wenextexaminedthecontactsbetweenribosomalDNAs(rDNAs)from n ucleolar o rganizer r egion (NOR)-bearing chromosomes (Chr13, 14, 15, 21, and 22).”
InfluentialZhang, X., & Wang, T. (2021) · Plant and Cell Physiology · doi:10.1093/pcp/pcab134 · Cited by 18
Noble, A. J., Purcell, R. V., Adams, A. T., Lam, Y. K., Ring, P. M., Anderson, J. R., & Osborne, A. J. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.831866 · Cited by 18
Enhancer-Promoter Communication: It’s Not Just About Contact
Wurmser, A., & Basu, S. (2022) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2022.867303 · Cited by 19
“Indeed, transcription has been shown to correlate with proximity to the inter-chromosomal region (Cremer et al., 2017; Stevens et al., 2017; Shah et al., 2018).”
BackgroundSelf-citationChromatin Hubs: A biological and computational outlook
Mora, A., Huang, X., Jauhari, S., Jiang, Q. L., & Li, X. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.07.002 · Cited by 18
“Stevens et al. reported that the organization of A/B compartments, LADs, and active enhancers and promoters, is consistent between single cells, while TADs and individual chromatin loops vary considerably from cell to cell [96].”
BackgroundMethodFunctional annotation of the animal genomes: An integrated annotation resource for the horse
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Hi-TrAC detects active sub-TADs and reveals internal organizations of super-enhancers
Cao, Y., Liu, S., Cui, K., Tang, Q., & Zhao, K. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad378 · Cited by 18
Self-citationThree‐dimensional genome structure and function
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“In the future, along with these interatomic data increasing in diverse tissues and cell types even in single cell [58],we can learnmore knowledge of transcriptional co-regulation using this framework.”
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Genome reconstruction and haplotype phasing using chromosome conformation capture methodologies
Xu, Z., & Dixon, J. R. (2019) · Briefings in Functional Genomics · doi:10.1093/bfgp/elz026 · Cited by 18
“Hi-C has been a powerful tool to investigate the structure of many genomes, such as human (22), mouse (19), Drosophila (21) and bacteria (11,15), as well as generating data for structural modeling of 3D architecture (29,30).”
BackgroundWu, H., Wang, M., Zheng, Y., & Xie, X. S. (2025) · Cell Discovery · doi:10.1038/s41421-025-00770-8 · Cited by 16
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Condensin I folds the Caenorhabditis elegans genome
Das, M., Semple, J. I., Haemmerli, A., Volodkina, V., Scotton, J., Gitchev, T., Annan, A., Campos, J., Statzer, C., Dakhovnik, A., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01832-5 · Cited by 24
“Eukaryotic genomes undergo extensive folding during interphase while maintaining essential functions such as replication, transcription and repair 1–4 .”
Inter-chromosomal contacts demarcate genome topology along a spatial gradient
Mokhtaridoost, M., Chalmers, J. J., Soleimanpoor, M., McMurray, B. J., Lato, D. F., Nguyen, S. C., Musienko, V., Nash, J. O., Espeso‐Gil, S., Ahmed, S., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-53983-y · Cited by 18
“The structural feature of clustered telomeric and centromeric interactions on opposite ends of the nucleus (termed Rabl ’ s con fi guration [1885] 42 ) is observed in yeast 43 , drosophila 44 , plants 45 , and mammals 3,46 , and has been proposed to reduce chromosomal entanglements 42,47 .”
Integrative modelling of cellular assemblies
Joseph, A. P., Polles, G., Alber, F., & Topf, M. (2017) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2017.07.001 · Cited by 15
“Recently, the development of single cell HiC assays enabled the modelling of genomes of individual cells [21,74,75].”
BackgroundMethodThe “Genomic Code”: DNA Pervasively Moulds Chromatin Structures Leaving no Room for “Junk”
Bernardi, G. (2021) · Life · doi:10.3390/life11040342 · Cited by 14
“and L1 isochores (a clearer version of Figure 2A3 of [38]) is compared with a Hi-C pattern (modified from [39]), in which”
ResultEngineering three-dimensional genome folding
Zhang, D., Lam, J. C., & Blobel, G. A. (2021) · Nature Genetics · doi:10.1038/s41588-021-00860-9 · Cited by 17
Chromosomal Rearrangements and Altered Nuclear Organization: Recent Mechanistic Models in Cancer
Federico, C., Bruno, F., Ragusa, D., Clements, C. S., Brancato, D., Henry, M. P., Bridger, J. M., Tosi, S., & Saccone, S. (2021) · Cancers · doi:10.3390/cancers13225860 · Cited by 17
“These biochemical–molecular approaches have disclosed the presence in interphase of two genomic compartments A and B [40], organized into TADs of various sizes, with the former compartment located more internally in the nucleus and the latter more towards the nuclear periphery and surrounding nucleoli [47,48], where h…”
BackgroundInterplay between regulatory elements and chromatin topology in cellular lineage determination
Shukla, V., Cetnarowska, A., Hyldahl, M., & Mandrup, S. (2022) · Trends in Genetics · doi:10.1016/j.tig.2022.05.011 · Cited by 15
Szczurek, A., Birk, U. J., Knecht, H., Dobrucki, J. W., Mai, S., & Cremer, C. G. (2018) · Nucleus · doi:10.1080/19491034.2017.1419846 · Cited by 16
“A- and B- nuclear compartments were later demonstrated to spatially segregate and occupy the interior or the periphery of the cell nucleus, respectively [10].”
BackgroundBetween form and function: the complexity of genome folding
Oudelaar, A. M., Hanssen, L. L. P., Hardison, R. C., Kassouf, M. T., Hughes, J. R., & Higgs, D. R. (2017) · Human Molecular Genetics · doi:10.1093/hmg/ddx306 · Cited by 16
“partments) is stochastic (41,42), which can be explained from the assumed polymeric behavior of chromosomes (10).”
BackgroundEnhancer Function in the 3D Genome
Razin, S. V., Ulianov, S. V., & Iarovaia, O. V. (2023) · Genes · doi:10.3390/genes14061277 · Cited by 15
Gene silencing dynamics are modulated by transiently active regulatory elements
Vermunt, M. W., Luan, J. Y., Zhang, Z., Thrasher, A. J., Huang, A., Saari, M. S., Khandros, E., Beagrie, R. A., Zhang, S., Vemulamada, P., et al. (2023) · Molecular Cell · doi:10.1016/j.molcel.2023.02.006 · Cited by 16
The interplay between histone modifications and nuclear lamina in genome regulation
Sun, C., Zhao, Y., Guo, L., Qiu, J., & Peng, Q. (2024) · Journal of genetics and genomics/Journal of Genetics and Genomics · doi:10.1016/j.jgg.2024.10.005 · Cited by 16
Dynamics of transcriptional enhancers and chromosome topology in gene regulation
Yokoshi, M., & Fukaya, T. (2019) · Development Growth & Differentiation · doi:10.1111/dgd.12597 · Cited by 14
“…Hi- C methods reported that genome topologies are highly variable even among the same cell types (Flyamer et al., 2017; Nagano et al., 2013, 2017; Stevens et al., 2017), suggesting that TADs seen in bulk approaches emerge as a consequence of population averaging of individual unique…”
MethodBernardi, G. (2019) · BioEssays · doi:10.1002/bies.201900106 · Cited by 17
Differences in the intrinsic spatial dynamics of the chromatin contribute to cell differentiation
Zhang, S., Chen, F., & Bahar, İ. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz1102 · Cited by 15
“In panel A, we compare the soft mode spectrum for single mouse embryonic stem cells chromosome 15 (based on single-cell Hi-C data (10)) with that obtained for a population of the same cell type, which reveals that several soft modes (along the diagonal) are shared.”
BackgroundMethodResultInfluentialBeato, M., Wright, R. H. G., & Dily, F. L. (2020) · Journal of Molecular Endocrinology · doi:10.1530/jme-19-0266 · Cited by 17
“We have used Hi-C approaches to explore the role of genome topology in gene regulation by progestins.”
InfluentialA unified framework for inferring the multi-scale organization of chromatin domains from Hi-C
Bak, J. H., Kim, M. H., Liu, L., & Hyeon, C. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008834 · Cited by 13
Liu, X., Sun, Q., Wang, Q., Hu, C., Chen, X., Li, H., Czajkowsky, D. M., & Shao, Z. (2021) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2020.06.017 · Cited by 18
“Although the underlying mechanisms driving the formation of both TADs and compartments are still incompletely understood, their conservation among different cell types and across species suggests that they constitute fundamental components of the eukaryotic genome architecture [4,9,10].”
BackgroundHi-C as a molecular rangefinder to examine genomic rearrangements
Kim, K., Kim, M., Kim, Y., Lee, D.-S., & Jung, I. (2021) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2021.04.024 · Cited by 16
Visualizing Live Chromatin Dynamics through CRISPR-Based Imaging Techniques
Chaudhary, N., Im, J., Nho, S.-H., & Kim, H. (2021) · Molecules and Cells · doi:10.14348/molcells.2021.2254 · Cited by 16
“Single-cell Hi-C studies revealed high cell-to-cell variability in chromatin structure (Flyamer et al., 2017; Nagano et al., 2013; Ramani et al., 2017; Stevens et al., 2017), implying that the chromatin structure within each cell changes over time.”
BackgroundMultiple parameters shape the 3D chromatin structure of single nuclei at the doc locus in Drosophila
Götz, M., Messina, O., Espínola, S., Fiche, J.-B., & Nöllmann, M. (2022) · Nature Communications · doi:10.1038/s41467-022-32973-y · Cited by 16
Federico, C., Pappalardo, A. M., Ferrito, V., Tosi, S., & Saccone, S. (2017) · Chromosome Research · doi:10.1007/s10577-017-9560-1 · Cited by 15
“These highlight the correspondence with the GC-richest and GC-poorest chromosomal band DNA, respectively (Saccone et al. 2002; Jabbari and Bernardi 2017; Stevens et al. 2017).”
BackgroundComputational approaches to macromolecular interactions in the cell
Vakser, I. A., & Deeds, E. J. (2019) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2019.03.012 · Cited by 15
Understanding the mechanistic insight of arsenic exposure and decoding the histone cipher
Bhattacharjee, P., Paul, S., & Bhattacharjee, P. (2019) · Toxicology · doi:10.1016/j.tox.2019.152340 · Cited by 15
Arrastia, M. V., Jachowicz, J. W., Ollikainen, N., Curtis, M. S., Lai, C., Quinodoz, S. A., Selck, D. A., Guttman, M., & Ismagilov, R. F. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.08.11.242081 · Cited by 15
Beagrie, R. A., & Pombo, A. (2017) · Nature · doi:10.1038/547034a · Cited by 13
Seeing the forest through the trees: prioritising potentially functional interactions from Hi-C
Liu, N., Low, W. Y., Alinejad‐Rokny, H., Pederson, S., Sadlon, T. J., Barry, S. C., & Breen, J. (2021) · Epigenetics & Chromatin · doi:10.1186/s13072-021-00417-4 · Cited by 16
Wang, Y., Qu, Z., Fang, Y., Chen, Y., Peng, J., Song, J., Li, J., Shi, J., Zhou, J., & Zhao, Y. (2023) · Cell Discovery · doi:10.1038/s41421-022-00511-1 · Cited by 14
A comprehensive review of bioinformatics tools for chromatin loop calling
Liu, L., Han, K., Sun, H., Han, L., Gao, D., Xi, Q., Zhang, L., & Lin, H. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad072 · Cited by 14
Advances in Genomic Profiling and Analysis of 3D Chromatin Structure and Interaction
Tang, B., Cheng, X., Xi, Y., Chen, Z., Zhou, Y., & Jin, V. X. (2017) · Genes · doi:10.3390/genes8090223 · Cited by 15
Ping, W., Sheng, Y., Hu, G., Zhong, H., Li, Y., Liu, Y., Luo, W., Yan, C., Wen, Y., Wang, X., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad219 · Cited by 13
Metadata
- Authors
- Stevens, T. J., Lando, D., Basu, S., Atkinson, L. P., Cao, Y., Lee, S. F., Leeb, M., Wohlfahrt, K. J., Boucher, W., O’Shaughnessy-Kirwan, A., Cramard, J., Faure, A. J., Ralser, M., Blanco, E., Morey, L., Sansó, M., Palayret, M. G. S., Lehner, B., Di Croce, L., Wutz, A., Hendrich, B., Klenerman, D., & Laue, E. D.
- Affiliations
- MRC Laboratory of Molecular Biology (GB)
- University of Cambridge (GB)
- Wellcome/MRC Cambridge Stem Cell Institute (GB)
- European Molecular Biology Laboratory (ES)
- Institució Catalana de Recerca i Estudis Avançats (ES)
- Corresponding author
- Laue, Ernest D.
- ORCID
- Venue
- Nature
- Published
- 2017-03-13
- Volume
- 544
- Issue
- 7648
- Pages
- 59-64
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC5385134
- OpenAlex
- W2597274540
- Cited by
- 832
- References
- 41
- Citations by year
- 2026: 42 · 2025: 73 · 2024: 62 · 2023: 71 · 2022: 95 · 2021: 115 · 2020: 95 · 2019: 121 · 2018: 99 · 2017: 58
- FWCI
- 41.56
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Wellcome Trust (082010/Z/07/Z, 277899, 206291/Z/17/Z, 082010)
- Medical Research Council (MR/M010082/1, MC_PC_12009, MR/P019471/1)
- Cancer Research UK Cambridge Institute, University of Cambridge
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Nuclear Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Chromosomal and Genetic Variations
- Keywords
- 3D genome organization, single-cell Hi-C, chromosome conformation capture, topologically associating domains, chromatin looping, lamina-associated domains, mouse embryonic stem cells, cell-to-cell variability, pluripotency factors, nucleosome remodeling, nuclear organization
- MeSH terms
- Mouse Embryonic Stem Cells, CCCTC-Binding Factor, Cohesins, Animals, Chromosomal Proteins, Non-Histone, DNA, Enhancer Elements, Genetic, Gene Expression Regulation, Haploidy, Models, Molecular, Molecular Conformation, Nucleosomes, Promoter Regions, Genetic, Repressor Proteins, Reproducibility of Results, G1 Phase, Genome, Cell Cycle Proteins, Chromosomes, Mammalian, Chromatin Assembly and Disassembly, Mice, Gene Regulatory Networks, Mi-2 Nucleosome Remodeling and Deacetylase Complex, Molecular Imaging, Single-Cell Analysis
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