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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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Bulathsinghalage, C., & Liu, L. (2020) · BMC Bioinformatics · doi:10.1186/s12859-020-03689-x · Cited by 8
ASHIC: hierarchical Bayesian modeling of diploid chromatin contacts and structures
Ye, T., & Ma, W. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa872 · Cited by 8
“Briefly, we first estimate X m and X p separately, then estimate the relative position between the two homologs to improve the final structure prediction (Supplementary Methods).”
MethodInfluentialSnapHiC: a computational pipeline to map chromatin contacts from single cell Hi-C dataPreprint
Yu, M., Abnousi, A., Zhang, Y.-X., Li, G., Lee, L., Chen, Z.-Y., Fang, R.-X., Wen, J., Sun, Q., Li, Y., et al. (2020) · bioRxiv · doi:10.1101/2020.12.13.422543 · Cited by 6
3D models of fungal chromosomes to enhance visual integration of omics data
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“As for the ‘population aver-age’ limit, single cell Hi-C strategies are developing ( 36 ), opening the promising perspective of creating 3D genome models of single cells.”
BackgroundChatzipapas, K., Tran, H. N., Dordevic, M., Sakata, D., Incerti, S., Visvikis, D., & Bert, J. (2024) · Physica Medica · doi:10.1016/j.ejmp.2024.104839 · Cited by 7
“There is a lot of on-going research to investigate and improve the modelling of the geometry of cellular DNA, either by implementing continuous Hilbert curves [16, 17], by implementing 3D structures [18, 19] or using bottom-up approaches (dnaFabric) [20].”
Zooming in on chromosome dynamics
Eykelenboom, J. K., & Tanaka, T. U. (2020) · Cell Cycle · doi:10.1080/15384101.2020.1757242 · Cited by 7
Bayesian methods in integrative structure modeling
Habeck, M. (2023) · Biological Chemistry · doi:10.1515/hsz-2023-0145 · Cited by 8
“C works with beads at 10 kb – 100 kb resolution and can utilize whole-genome data measured on single cells (Stevens et al. 2017).”
c-Jun as a one-way valve at the naive to primed interface
Li, D., Luo, L., Guo, L., Wu, C., Zhang, R., Peng, Y., Wu, M., Kuang, J., Li, Y., Zhang, Y., et al. (2023) · Cell & Bioscience · doi:10.1186/s13578-023-01141-0 · Cited by 7
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MethodUncovering topologically associating domains from three-dimensional genome maps with TADGATE
Dang, D., Zhang, S.-W., Dong, K., Duan, R., & Zhang, S. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae1267 · Cited by 8
“Notably, both single-cell Hi-C and super-resolution imaging data have revealed the existence and variations of TAD-like domains (TLDs) in single cells ( 35– 37 ).”
Unraveling the 3D genome of human malaria parasites
Batugedara, G., & Roch, K. G. L. (2018) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2018.07.015 · Cited by 7
High-resolution single-cell 3D-models of chromatin ensembles during Drosophila embryogenesis
Sun, Q., Perez-Rathke, A., Czajkowsky, D. M., Shao, Z., & Liang, J. (2021) · RePEc: Research Papers in Economics · Cited by 7
Genome-Directed Cell Nucleus Assembly
Razin, S. V., & Ulianov, S. V. (2022) · Biology · doi:10.3390/biology11050708 · Cited by 8
Assessment of Multiway Interactions with Tri-C
Oudelaar, A. M., Downes, D. J., & Hughes, J. R. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2497-5_6 · Cited by 6
Xing, Z., Mai, H., Liu, X., Fu, X., Zhang, X., Xie, L., Chen, Y., Shlien, A., & Wen, F. (2022) · Genome biology · doi:10.1186/s13059-022-02740-9 · Cited by 7
“Excitingly, singlecell Hi-C was developed and solves this problem [16].”
BackgroundBiomolecular Topology: Modelling and Analysis
Liu, J., Xia, K., Wu, J., Yau, S. S. ‐., & Wei, G. (2022) · Acta Mathematica Sinica English Series · doi:10.1007/s10114-022-2326-5 · Cited by 9
“Figure 2 (B) illustrates the chromosome structure from the mammalian genome [180].”
BackgroundZhao, Y., Xiao, Y., Hu, Z., Wang, J., Xu, Z., Mo, Y., Guojun, Q., Chen, K., Wu, W., & Ma, W. (2023) · Frontiers in Oncology · doi:10.3389/fonc.2023.1067305 · Cited by 7
“It is worth noting that single-cell Hi-C techniques to study the relationships of whole chromatin DNA at spatial locations on a genome-wide scale and multiomics single-cell sequencing that integrate epigenetics, transcriptomes and genotypes are not within our scope (40, 41).”
BackgroundCapturing heterogeneity: single-cell structures of the 3D genome
de Wit, E. (2017) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.3404 · Cited by 7
A transient absence of SMC-mediated loops after mitosis
Liu, N. Q., & de Wit, E. (2019) · Nature Cell Biology · doi:10.1038/s41556-019-0421-3 · Cited by 7
A DNA Sequence Based Polymer Model for Chromatin Folding
Zhou, R., & Gao, Y. Q. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22031328 · Cited by 6
“It was reported that the heterochromatin (compartment B) tends to populate near the nuclear periphery and near the nuclear center, while the euchromatin (compartment A) tends to populate in between [1,3,12].”
BackgroundInfluentialModeling the 3D genome of plants
Stefano, M. D., & Nützmann, H. (2021) · Nucleus · doi:10.1080/19491034.2021.1927503 · Cited by 6
Hirata, Y., Oda, A., Motono, C., Shiro, M., & Ohta, K. (2022) · Scientific Reports · doi:10.1038/s41598-022-15038-4 · Cited by 7
Scool: a new data storage format for single-cell Hi-C data
Wolff, J., Abdennur, N. A., Backofen, R., & Grüning, B. A. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa924 · Cited by 7
L1 and B1 repeats blueprint the spatial organization of chromatinPreprint
Lu, J. Y., Chang, L., Li, T., Wang, T., Yin, Y., Zhan, G., Zhang, K., Percharde, M., Wang, L., Peng, Q., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/802173 · Cited by 7
“Simulation of three-dimensional (3D) genome structures predicted that the euchromatic A compartment adopts a central position, whereas the heterochromatic B compartment moves towards the nuclear periphery and perinucleolar regions (Buchwalter et al., 2019; Stevens et al., 2017).”
BackgroundNormalization and De-noising of Single-cell Hi-C Data with BandNorm and 3DVIPreprint
Zheng, Y., Shen, S., & Keleş, S. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.10.434870 · Cited by 7
Wang, H., Yang, J., Yu, X., Zhang, Y., Qian, J., & Wang, J. (2025) · Nature Communications · doi:10.1038/s41467-025-58674-w · Cited by 7
“…human GM12878, human K562 and mouse ESC cells), different types of inputs of single-cell chromatin contacts (i.e. Dip-C, snHi-C, scHi-C and snm3C) 40,44,45,47 , different levels of resolutions (i.e. 10kb-and 30kb-resolution), and different types of benchmark datasets as gold-standards (i.e. 3D…”
InfluentialThe significance of chromosome conformation capture in 3D genome architecture comprehension
Cetin, S., & Sefer, E. (2025) · Computational Biology and Chemistry · doi:10.1016/j.compbiolchem.2025.108534 · Cited by 8
Dynamical properties of chromatin provide insights into key folding principles
Kadam, S., Sahoo, S., Kumar, P., & Padinhateeri, R. (2025) · Biophysical Journal · doi:10.1016/j.bpj.2025.08.018 · Cited by 5
scHi-CSim: a flexible simulator that generates high-fidelity single-cell Hi-C data for benchmarking
Fan, S., Dang, D., Ye, Y., Zhang, S.-W., Gao, L., & Zhang, S. (2023) · Journal of Molecular Cell Biology · doi:10.1093/jmcb/mjad003 · Cited by 6
“…) has been applied to probe the cell-to-cell variability and dynamics of chromatin structures among the cell population or across some critical biological processes ( Nagano et al., 2013 , 2017 ; Flyamer et al., 2017 ; Ramani et al., 2017 , 2020 ; Stevens et al., 2017 ; Tan et al., 2018 , 2019 ) .”
Chromatin structure from high resolution microscopy: Scaling laws and microphase separation
Remini, L., Segers, M., Palmeri, J., Walter, J., Parmeggiani, A., & Carlon, E. (2024) · Physical review. E · doi:10.1103/physreve.109.024408 · Cited by 7
Epigenetics in metabolic dysfunction-associated steatohepatitis
Zhang, Y., Ding, R., Hu, L., Liu, E., & Qu, P. (2025) · Cellular Signalling · doi:10.1016/j.cellsig.2025.111684 · Cited by 6
Linking DNA-packing density distribution and TAD boundary locations
Meng, L., Sheong, F. K., & Luo, Q. (2025) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2418456122 · Cited by 6
Chromatin imaging and new technologies for imaging the nucleome
Szydlowski, N., Go, J. S., & Hu, Y. (2018) · WIREs Systems Biology and Medicine · doi:10.1002/wsbm.1442 · Cited by 6
“In addition, reconciling single-cell fluorescence imaging with recently reported single-cell chromosome conformation capture (3C/Hi-C) experiments (Stevens et al., 2017) requires careful consideration.”
BackgroundMYC as a driver of stochastic chromatin networks: implications for the fitness of cancer cells
Sumida, N., Sifakis, E. G., Kiani, N. A., Ronnegren, A. L., Scholz, B. A., Vestlund, J., Gómez-Cabrero, D., Tegner, J. N., Göndör, A., & OHLSSON, R. I. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa817 · Cited by 6
“Although Hi-C protocols (19) have been developed to examine chromatin structure at the single cell level or in small cell populations (20,21), they are not sufficiently quantitative to robustly address specific enhancer-gene communications.”
BackgroundZibetti, C. (2022) · Cells · doi:10.3390/cells11050806 · Cited by 6
Cell-Type Resolved Insights into the Cis-Regulatory Genome of NAFLD
Dam, T. V., Toft, N. I., & Grøntved, L. (2022) · Cells · doi:10.3390/cells11050870 · Cited by 6
Chromosome Conformation Capture in Bacteria and Archaea
Rashid, F. M., Detmar, L., & Dame, R. T. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2413-5_1 · Cited by 7
Strawbridge, S. E., Kurowski, A., Corujo-Simón, E., Fletcher, A., Nichols, J., & Fletcher, A. G. (2023) · Biology Open · doi:10.1242/bio.060055 · Cited by 5
“, 2022), and the relationship of genomic loci within the nucleus as determined by single-cell Hi-C structures (Stevens et al., 2017).”
BackgroundPhysical properties of the chromosomes and implications for development
Sugawara, T., & Kimura, A. (2017) · Development Growth & Differentiation · doi:10.1111/dgd.12363 · Cited by 6
Review: Chromatin organization in plant and animal stem cell maintenance
Zheng, Y., & Liu, X. (2019) · Plant Science · doi:10.1016/j.plantsci.2018.12.026 · Cited by 6
Disentangling chromatin architecture to gain insights into the etiology of brain disorders
Lamonica, J. M., & Zhou, Z. (2019) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2019.06.009 · Cited by 5
Chu, W., Chu, X., & Wang, J. (2022) · Advanced Science · doi:10.1002/advs.202103617 · Cited by 4
Chromatin network retards droplet coalescence
Qi, Y., & Zhang, B. (2022) · Biophysical Journal · doi:10.1016/j.bpj.2021.11.1933 · Cited by 6
Cremer, C. G., & Birk, U. J. (2022) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2021.0152 · Cited by 6
Li, Y., Roth, E. W., Agrawal, V., Eshein, A., Fredrick, J., Almassalha, L. M., Shim, A. R., Bleher, R., Dravid, V. P., & Backman, V. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/636209 · Cited by 8
Condensin I folds the C. elegans genomePreprint
Das, M., Semple, J. I., Haemmerli, A., Volodkina, V., Scotton, J., Gitchev, T., Annan, A., Campos, J., Statzer, C., Dakhovnik, A., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.14.495661 · Cited by 6
“Chromatin conformation capture technologies and high-resolution imaging have been used to monitor genome conformation of interphase chromosomes (Dekker et al. 2002; Lieberman-Aiden et al. 2009; Cattoni et al. 2017; Stevens et al. 2017).”
MethodUnraveling the three-dimensional (3D) genome architecture in Neurodevelopmental Disorders (NDDs)
Carballo-Pacoret, P., Carracedo, Á., & Rodriguez‐Fontenla, C. (2024) · Neurogenetics · doi:10.1007/s10048-024-00774-8 · Cited by 6
“The initial discovery of compartments A and B associated them with euchromatin and heterochromatin, respectively [19, 31 ].”
Organization and Dynamics of Chromosomes
Thirumalai, D., Shi, G., Shin, S., & Hyeon, C. (2025) · Annual Review of Physical Chemistry · doi:10.1146/annurev-physchem-082423-024123 · Cited by 5
“Single-cell measurements [16, 84] also showed that TADs are not conserved structural units but rather adopt different structures from cell to cell.”
BackgroundVisualization of chromatin higher-order structures and dynamics in live cells
Park, T. L., Lee, Y., & Cho, W. (2021) · BMB Reports · doi:10.5483/bmbrep.2021.54.10.098 · Cited by 5
“Since ensemble averaged data from the techniques underestimated cell-to-cell variability, the single-cell Hi-C method has been developed (14-18).”
MethodInfluence of ionic conditions on knotting in a coarse-grained model for DNA
Wettermann, S., Datta, R., & Virnau, P. (2023) · Frontiers in Chemistry · doi:10.3389/fchem.2022.1096014 · Cited by 5
“The revelation of DNA packing and folding in the cell nucleus [20, 41, 39, 11] and the emergence of commercially available nanopore techniques [17, 16] has ushered in a new era of DNA research in the past decade.”
scGrapHiC: deep learning-based graph deconvolution for Hi-C using single cell gene expression
Murtaza, G., Butaney, B., Wagner, J., & Singh, R. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae223 · Cited by 6
“Building upon these techniques, a recent extension of the Hi-C protocol is single-cell Hi-C (scHi-C) (Stevens et al. 2017).”
MethodGeneration of densely labeled oligonucleotides for the detection of small genomic elements
Steinek, C., Guirao‐Ortiz, M., Stumberger, G., Tölke, A. J., Hörl, D., Carell, T., Harz, H., & Leonhardt, H. (2024) · Cell Reports Methods · doi:10.1016/j.crmeth.2024.100840 · Cited by 6
Conte, M., Abraham, A., Esposito, A., Yang, L., Gibcus, J. H., Parsi, K. M., Vercellone, F., Fontana, A., Pierno, F. D., Dekker, J., et al. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms251810215 · Cited by 6
“Consistent with previous studies [45,53,154,155], this variability underscores the highly dynamic nature of the 3D structures of single chromatin conformations.”
ResultMeasuring the three-dimensional structural properties of topologically associating domains
Liu, T., & Wang, Z. (2018) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2018.8621459 · Cited by 5
“Other methods include ChromSDE [9] and a single-cell structural reconstruction method [10].”
The corrected gene proximity map for analyzing the 3D genome organization using Hi-C data
Ye, C., Paccanaro, A., Gerstein, M., & Yan, K. (2020) · BMC Bioinformatics · doi:10.1186/s12859-020-03545-y · Cited by 5
The Toolbox for Untangling Chromosome Architecture in Immune Cells
Liu, S., & Zhao, K. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.670884 · Cited by 6
“target, small cell number Requires high quality antibody (54, 55)”
BackgroundCan 3D diploid genome reconstruction from unphased Hi-C data be salvaged?
Segal, M. R. (2022) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqac038 · Cited by 5
“First, for 3D diploid reconstructions based on single-cell Hi-C (23,24) or SPRITE (25) assays the issue of inter-cellular structural variation becomes moot, but allelic ambiguity concerns persist.”
MethodSumida, N., Sifakis, E. G., Scholz, B. A., Fernandez-Woodbridge, A., Kiani, N. A., Gómez-Cabrero, D., Svensson, J. P., Tegner, J. N., Göndör, A., & OHLSSON, R. I. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/286583 · Cited by 5
“…level or in small cell populations, they either do not currently have the resolution sufficient to address enhancer-gene communications (Nagano et al. 2013; Stevens et al. 2017) and/or cannot discriminate between real and virtual networks (Nagano et al. 2013; Du et al. 2017; Stevens et al. 2017).”
BackgroundMultiplex Chromatin Interaction Analysis with Single-Molecule PrecisionPreprint
Zheng, M., Tian, S. Z., Maurya, R., Lee, B., Kim, M., Capurso, D., Piecuch, E., Gong, L., Zhu, J. J., Wong, C., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/252049 · Cited by 5
HiCluster: A Robust Single-Cell Hi-C Clustering Method Based on Convolution and Random WalkPreprint
Zhou, J., Ma, J., Chen, Y., Cheng, C., Bao, B., Peng, J., B, T. J. S. A., Dixon, J. R., & Ecker, J. R. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/506717 · Cited by 5
CSynth: A Dynamic Modelling and Visualisation Tool for 3D Chromatin StructurePreprint
Todd, S. J. P., Todd, P., McGowan, S. J., Hughes, J. R., Kakui, Y., Leymarie, F. F., Latham, W., & Taylor, S. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/499806 · Cited by 5
Steindel, M., Davis, O., Neumann, K., Agsu, G. G., Mao, L., Kranz, A., Pirvan, L., Adhya, D., Morf, J., Zhang, Z., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.21.639010 · Cited by 5
Self-citationNondisruptive 3D profiling of combinations of epigenetic marks in single cells
Chen, Y., Radda, J. S. D., Alderman, M. H., Jin, S., Cheng, Y., Zhang, Y., Liu, M., Xiao, A., & Wang, S. (2026) · Nature Methods · doi:10.1101/2025.06.13.659535 · Cited by 5
Li, W., Liao, Y., Liu, Z., Niu, L., Huang, J., Jia, Y., Xu, R., Guan, S., Liang, Z., Li, Y., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-63876-3 · Cited by 4
“…structure calculations at single-cell resolution, which revealed that the chromosomes packed together to form an outer B compartment ring, an inner A compartment ring, and an internal B compartment region around the hollow nucleoli in all cells, based on the previous de fi nition standards 24,52 .”
Effect of active loop extrusion on the two-contact correlations in the interphase chromosome
Starkov, D., & Belan, S. (2024) · The Journal of Chemical Physics · doi:10.1063/5.0221933 · Cited by 4
scHiGex: predicting single-cell gene expression based on single-cell Hi-C data
Shrestha, B., Siciliano, A. J., Zhu, H., Liu, T., & Wang, Z. (2025) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaf002 · Cited by 4
“This breakthrough also enables the computational reconstruction of chromosomes’ three-dimensional (3D) architectures [ 10 ].”
Representing and extracting knowledge from single-cell data
Mihai, I. S., Chafle, S., & Henriksson, J. (2023) · Biophysical Reviews · doi:10.1007/s12551-023-01091-4 · Cited by 5
“Single-cell HiC generates a map of location-to-location abundances (Nagano et al. 2013; Stevens et al. 2017; Zhang et al. 2022).”
BackgroundRothörl, J., Brems, M. A., Stevens, T. J., & Virnau, P. (2023) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2023.1284484 · Cited by 5
“…contact lengths for a 20 kbp structure from our minimization protocol and minimizations performed by Tan et al. (2018). roughly account for 1.5% of the close beads pairs observed in the fi nal structure (de fi ned as distances smaller than 3) which lies in the expected range (Stevens et al., 2017).”
BackgroundMethodInfluentialSelf-citationJoint Tensor Modeling of Single Cell 3D Genome and Epigenetic Data with Muscle
Park, K., & Keleş, S. (2024) · Journal of the American Statistical Association · doi:10.1080/01621459.2024.2358557 · Cited by 4
“…in single cell sequencing technologies of Hi-C (scHi-C) enabled profiling interactions between distant genomic loci in individual cells (Stevens et al. 2017; Ramani et al. 2017; Tan et al. 2021; Ulianov et al. 2021) and even simultaneously with their DNA methylation status (sn-m3C-seq…”
Deep neural network models for cell type prediction based on single-cell Hi-C data
Zhou, B., Liu, Q., Wang, M., & Wu, H. (2024) · BMC Genomics · doi:10.1186/s12864-024-10764-7 · Cited by 4
“The single-cell Hi-C technology verifies that the organization module of single cell is the basis of dynamic chromosomes [1], and reveals that the chromosome conformation diagram can be reinterpreted by cell cycle [2].”
BackgroundMaxComp: Predicting single-cell chromatin compartments from 3D chromosome structures
Zhan, Y., Musella, F., & Alber, F. (2025) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1013114 · Cited by 4
Two main stream methods analysis and visual 3D genome architecture
Fu, S., Zhang, L., Lv, J., Zhu, B., Wang, W., & Wang, X. (2018) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2018.07.011 · Cited by 4
Advancements in mapping 3D genome architecture
McKay, D. J., Stutzman, A. V., & Dowen, J. M. (2019) · Methods · doi:10.1016/j.ymeth.2019.06.002 · Cited by 4
“While approaches like single cell HiC aim to resolve this issue, it can be technically challenging and prohibitively expensive for labs to generate sufficiently deep sequencing data for large numbers of single cells [30,31].”
Defining and detecting links in chromosomes
Niewieczerzał, S., Niemyska, W. H., & Sulkowska, J. I. (2019) · Scientific Reports · doi:10.1038/s41598-019-47999-4 · Cited by 4
3D reconstruction of genomic regions from sparse interaction data
Mendieta-Esteban, J., Stefano, M. D., Castillo, D., Farabella, I., & Martı́-Renom, M. A. (2021) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqab017 · Cited by 4
“Others are focused on the 3D modelling of chromatin based on single-cell Hi-C data, like manifold based optimization (30) and NucDynamics (31).”
D2 Plot, a Matrix of DNA Density and Distance to Periphery, Reveals Functional Genome Regions
Che, Y., Yang, X., Jia, P., Wang, T., Xu, D., Guo, T., & Ye, K. (2022) · Advanced Science · doi:10.1002/advs.202202149 · Cited by 3
Chu, X., & Wang, J. (2023) · Open Biology · doi:10.1098/rsob.230175 · Cited by 5
Papale, A., & Holcman, D. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011794 · Cited by 4
A mini-review of single-cell Hi-C embedding methods
Ma, R., Huang, J., Jiang, T., & Ma, W. (2024) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2024.11.002 · Cited by 6
Razin, S. V., Ulianov, S. V., & Gavrilov, A. A. (2019) · Molecular Biology · doi:10.1134/s0026893319060153 · Cited by 4
“The TAD shape is quite plastic and can vary broadly on evidence of a computer modeling based on the Hi-C analysis of single cells [37].”
BackgroundMethodMa, W., Gu, C., Ma, L., Fan, C., Zhang, C., Sun, Y., Li, C., & Yang, G. (2020) · Science China Life Sciences · doi:10.1007/s11427-019-1638-6 · Cited by 4
Ahmad, A., Frindel, C., & Rousseau, D. (2020) · Frontiers in Robotics and AI · doi:10.3389/frobt.2020.00039 · Cited by 4
“Hence, defining the 3D-organization of cancerassociated chromatin domains could represent a new frontier to decipher tumor heterogeneity during tumor progression and metastasis formation (Kundu et al., 2017; Boettiger et al., 2016; Stevens et al., 2017).”
BackgroundInterphase chromatin as a self-returning random walk: Can DNA fold into liquid trees?Preprint
Huang, K., Backman, V., & Szleifer, I. G. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/413872 · Cited by 4
Li, G., Liu, Y., Zhang, Y., Fang, R., Kellis, M., & Ren, B. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/470963 · Cited by 4
Martens, L. D., Faust, O., Pirvan, L., Bihary, D., & Samarajiwa, S. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.19.049585 · Cited by 4
“Chromatin forms both global [9] and local three–dimensional architectures; an example being the looping of DNA to bring distal regulatory regions such as enhancer and promoter into (which was not certified by peer review) is the author/funder.”
BackgroundCapturing the complexity of topologically associating domains through multi-feature optimizationPreprint
Sauerwald, N., & Kingsford, C. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.01.04.425264 · Cited by 4
“Understanding TAD-like structures in single cells is an active field of research [16, 26, 3, 1], and an analysis similar to the one presented here at the single cell level would be necessary to understand the relationships between these structures and any corresponding biological properties in individual cells.”
BackgroundLi, Y., Xiao, P., Boadu, F., Goldkamp, A. K., Nirgude, S., Cheng, J. J., Hagen, D. E., Kalish, J. M., & Rivera, R. M. (2023) · medRxiv · doi:10.1101/2023.12.14.23299981 · Cited by 4
Droplet Hi-C for Fast and Scalable Profiling of Chromatin Architecture in Single CellsPreprint
Chang, L., Xie, Y., Taylor, B., Wang, Z., Sun, J., Tan, T. M., Bejar, R. L., Chen, C. C., Furnari, F. B., Hu, M., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.18.590148 · Cited by 4
Single-cell technologies for multimodal omics measurements
Bai, D., & Zhu, C. (2023) · Frontiers in Systems Biology · doi:10.3389/fsysb.2023.1155990 · Cited by 3
“Singlecell Hi-C techniques capture the snapshots of 3D genome organization 1 cell at a time and reveal the dynamic and distinct chromosome conformations during different cell cycle phases and cell types (Nagano et al., 2013; Ramani et al., 2017; Stevens et al., 2017).”
MethodFan, S., Dang, D., Gao, L., & Zhang, S. (2024) · Advanced Science · doi:10.1002/advs.202406364 · Cited by 4
Schiccompare: An R Package for Differential Analysis of Single-Cell Hi-C Data
Nguyen, M., Wall, B. P. G., Harrell, J. C., & Dozmorov, M. G. (2024) · Journal of Molecular Biology · doi:10.1016/j.jmb.2025.169155 · Cited by 3
Hong, F., Han, K., Hao, Y., Su, W., Xie, X., Li, X., Chen, Q., Wei, Y., Luo, X., Xie, S., et al. (2025) · Briefings in Bioinformatics · doi:10.1093/bib/bbaf520 · Cited by 5
“By integrating cutting-edge experimental techniques with advanced computational methodologies, this field has unraveled the intricate interplay between chromatin folding [48], gene regulation [3], and cellular heterogeneity [140].”
Evaluation and comparison of methods for recapitulation of 3D spatial chromatin structures
Park, J., & Lin, S. (2017) · Briefings in Bioinformatics · doi:10.1093/bib/bbx134 · Cited by 3
Genomic Cytometry and New Modalities for Deep Single‐Cell Interrogation
Salomon, R., Martelotto, L. G., Valdés‐Mora, F., & Gallego‐Ortega, D. (2020) · Cytometry Part A · doi:10.1002/cyto.a.24209 · Cited by 3
“Assays that take advantage of a plate-based approach include: Smart-Seq (33), Smart-Seq2 (34), Smart-Seq3 (35), STRT-seq (36), STRT-seq-2i (37), Cell-Seq, Cell-Seq2 (38), MARS-Seq (39), mcSCRB-seq (40), Qartz-seq (41), Qartzseq2 (42), scBS-seq (43), and single-cell HiC (44).”
Acute Protein Depletion Strategies to Functionally Dissect the 3D Genome
Maresca, M., Liu, N. Q., & de Wit, E. (2022) · Methods in molecular biology · doi:10.1007/978-1-0716-2497-5_15 · Cited by 3
CscoreTool-M infers 3D sub-compartment probabilities within cell population
Zheng, X., Tran, J. R., & Zheng, Y. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad314 · Cited by 3
“The Rabl effect shows centromerecentromere or telomere-telomere interactions among different chromosomes (Imakaev et al. 2012; Nagano et al. 2017; Stevens et al. 2017).”
BackgroundPandupuspitasari, N. S., Khan, F. A., Huang, C., Ali, A., Yousaf, M. R., Shakeel, F., Putri, E. M., Negara, W., Muktiani, A., Prasetiyono, B. W. H. E., et al. (2023) · Functional & Integrative Genomics · doi:10.1007/s10142-023-01146-5 · Cited by 3
“In most cases, the A compartment is active and the B compartment is inactive (Stevens et al. 2017).”
BackgroundSpatiotemporal DNA methylation dynamics shape megabase-scale methylome landscapes
Toh, H., & Sasaki, H. (2024) · Life Science Alliance · doi:10.26508/lsa.202302403 · Cited by 4
“To examine the effect of chromosome territories on DNA methylation levels in mice (Mayer et al, 2005; Stevens et al, 2017), we used constitutive LADs as indicators, which have been shown to be conserved across cell types (Peric-Hupkes et al, 2010).”
BackgroundMethodLoop Extrusion Machinery Impairments in Models and Disease
Ryzhkova, A. S., Maltseva, E., Баттулин, Н. Р., & Kabirova, E. (2024) · Cells · doi:10.3390/cells13221896 · Cited by 2
Deciphering single-cell 3D chromatin structure using scCTG
Jiang, R., Xue, Y., Huang, Y., & Gao, Y. Q. (2024) · The Journal of Chemical Physics · doi:10.1063/5.0241334 · Cited by 3
Zhang, B., Lan, X., Tan, S., Xie, Z., Zhu, L., Gong, X., Dai, X., Fang, X., & Xu, W. (2025) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2025.118170 · Cited by 3
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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