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Lineage-Specific Genome Architecture Links Enhancers and Non-coding Disease Variants to Target Gene Promoters
Open accessAbstract
Long-range interactions between regulatory elements and gene promoters play key roles in transcriptional regulation. The vast majority of interactions are uncharted, constituting a major missing link in understanding genome control. Here, we use promoter capture Hi-C to identify interacting regions of 31,253 promoters in 17 human primary hematopoietic cell types. We show that promoter interactions are highly cell type specific and enriched for links between active promoters and epigenetically marked enhancers. Promoter interactomes reflect lineage relationships of the hematopoietic tree, consistent with dynamic remodeling of nuclear architecture during differentiation. Interacting regions are enriched in genetic variants linked with altered expression of genes they contact, highlighting their functional role. We exploit this rich resource to connect non-coding disease variants to putative target promoters, prioritizing thousands of disease-candidate genes and implicating disease pathways. Our results demonstrate the power of primary cell promoter interactomes to reveal insights into genomic regulatory mechanisms underlying common diseases.
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“Capture Hi-C analyses in multiple cell types consistently detect enhancer–promoter contacts that cross TAD boundaries [141, 243].”
From Transcriptional enhancers and their communication with gene promoters (2021) · cites this paper as [243]
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“PCHi-C showed that active promoters contacted a median of two active enhancers in human primary blood cells [243].”
From Transcriptional enhancers and their communication with gene promoters (2021) · cites this paper as [243]
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“A similar network of contacts is also detectable between the active promoters of multiple histone genes in many mammalian cell types [243, 279, 471, 492].”
From Transcriptional enhancers and their communication with gene promoters (2021) · cites this paper as [243]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“the number of enhancers correlates with the expression level of a gene across cell types [243, 278, 279, 349].”
From Transcriptional enhancers and their communication with gene promoters (2021) · cites this paper as [243]
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“These enrichment methods have detected multitudes of enhancer–promoter loops in many human and mouse cell types [243, 286–291].”
From Transcriptional enhancers and their communication with gene promoters (2021) · cites this paper as [243]
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“Enhancers vastly outnumber promoters in human and mouse genomes [131], and consistently promoters often contact more than one enhancer in the same cell type [141, 243, 278, 279].”
From Transcriptional enhancers and their communication with gene promoters (2021) · cites this paper as [243]
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“disease-associated SNPs in non-coding areas of the genome influence genes associated with diseases including Alzheimer’s Disease (AD)”
From Neuronal DNA double-strand breaks lead to genome structural variations and 3D genome disruption in neurodegeneration (2023) · cites this paper as [50]
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Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106
limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458
clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters
Yu, G., Wang, L.-G., Han, Y., & He, Q.-Y. (2012) · OMICS: A Journal of Integrative Biology · doi:10.1089/omi.2011.0118 · Cited by 36,259
A global reference for human genetic variation
The 1000 Genomes Project Consortium, authors, C., Auton, A., Abecasis, G. R., Steering committee, Altshuler, D. M., Durbin, R. M., Abecasis, G. R., Bentley, D. R., Chakravarti, A., et al. (2015) · Nature · doi:10.1038/nature15393 · Cited by 18,247
Self-citationAn integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
Self-citationHeinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y. C., Laslo, P., Cheng, J. X., Murre, C., Singh, H., & Glass, C. K. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.05.004 · Cited by 13,382
Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome
Lieberman-Aiden, E., van Berkum, N. L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., Amit, I., Lajoie, B. R., Sabo, P. J., Dorschner, M. O., et al. (2009) · Science · doi:10.1126/science.1181369 · Cited by 8,898
Topological domains in mammalian genomes identified by analysis of chromatin interactions
Dixon, J. R., Selvaraj, S., Yue, F., Kim, A., Li, Y., Shen, Y., Hu, M., Liu, J. S., & Ren, B. (2012) · Nature · doi:10.1038/nature11082 · Cited by 6,829
The Reactome pathway Knowledgebase
Fabregat, A., Sidiropoulos, K., Garapati, P., Gillespie, M., Hausmann, K., Haw, R., Jassal, B., Jupe, S., Korninger, F., McKay, S., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1351 · Cited by 5,605
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534
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Items 701–800 of 1,000
Schmidt, A. F., Finan, C., Chopade, S., Ellmerich, S., Rossor, M. N., Hingorani, A. D., & Pepys, M. B. (2023) · medRxiv · doi:10.1101/2023.08.15.23293564 · Cited by 4
A unified model of gene expression control by cohesin and CTCFPreprint
Narita, T., Kilic, S., Higashijima, Y., Pappas, G., Maskey, E., & Choudhary, C. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.11.29.625887 · Cited by 4
Saw, A. K., Madhok, A., Bhattacharya, A., Nandi, S., & Galande, S. (2025) · Frontiers in Genetics · doi:10.3389/fgene.2025.1553469 · Cited by 3
Trang, B. K., Sharma, P. K., Cook, L. E., Mount, Z., Thomas, R. M., Kulkarni, N. N., Cabrera, E. C., Rachimi, S., Pahl, M. C., Pippin, J. A., et al. (2025) · Genome biology · doi:10.1186/s13059-025-03880-4 · Cited by 7
Zhang, G., Zhang, W., Wang, C., Jiang, Z., Xu, Q., Li, H., Kirkland, J. L., Wei, G., & Sun, Y. (2026) · Aging Cell · doi:10.1111/acel.70366 · Cited by 3
Exome sequencing identifies PD‐L2 as a potential predisposition gene for lymphoma
Shao, J., Gao, L., Leung, M. L., Gallinger, B., Inglese, C. N., Meyn, M. S., del Gaudio, D., Das, S., & Li, Z. (2022) · Hematological Oncology · doi:10.1002/hon.3033 · Cited by 3
Wei, X., Tran, D., & Diao, Y. (2023) · Current Protocols · doi:10.1002/cpz1.899 · Cited by 3
Davidson, B. S. A., Arcila-Galvis, J. E., Trevisán-Herraz, M., Mikulášová, A., Brackley, C. A., Russell, L. J., & Rico, D. (2024) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2024.1294510 · Cited by 4
Planell, N., Martinez‐de‐Morentin, X., Mouzo, D., Lara‐Astiaso, D., Vilas‐Zornoza, A., Martín‐Úriz, P. S., Alignani, D., Paiva, B., Maillo, A., Kurowska, A., et al. (2025) · Science Advances · doi:10.1126/sciadv.adw3110 · Cited by 4
Integrating natural and engineered genetic variations to decode regulatory influence on blood traits
Tardáguila, M., Schiller, D. V., Colombo, M., Gori, I., Coomber, E. L., Vanderstichele, T., Benaglio, P., Chiereghin, C., Gerety, S. S., Vuckovic, D., et al. (2026) · Cell Reports · doi:10.1016/j.celrep.2026.116937 · Cited by 3
Self-citationRegulatory Genomic Data Cubism
Fang, H., & Wang, K. (2018) · iScience · doi:10.1016/j.isci.2018.04.017 · Cited by 3
Integration of Multiple Resolution Data in 3D Chromatin Reconstruction Using ChromStruct
Caudai, C., Zoppè, M., Tonazzini, A., Ivan Merelli, A., & Salerno, E. (2021) · Biology · doi:10.3390/biology10040338 · Cited by 3
How to find genomic regions relevant for gene regulation
Guo, X., Ohler, U., & Yildirim, F. (2021) · Medizinische Genetik · doi:10.1515/medgen-2021-2074 · Cited by 3
Disorder of three‐dimensional chromosome structure plays a role in carcinogenesis
Zhang, L., Liu, F., Wu, L., Fu, S., Xing, L., Zhang, L., Wang, X., & Wang, Y.-X. (2021) · Clinical and Translational Discovery · doi:10.1002/ctd2.17 · Cited by 3
A systematic study of motif pairs that may facilitate enhancer–promoter interactions
Wang, S., Hu, H., & Li, X. (2022) · Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics · doi:10.1515/jib-2021-0038 · Cited by 4
Advanced genomics and clinical phenotypes in psoriatic arthritis
Vecellio, M. L., Rodolfi, S., & Selmi, C. F. (2021) · Seminars in Immunology · doi:10.1016/j.smim.2022.101665 · Cited by 3
Computational methods for identifying enhancer‐promoter interactions
Gong, H., Chen, Z., Tang, Y., Li, M., Zhang, S., Zhang, X., & Chen, Y. (2023) · Quantitative Biology · doi:10.15302/j-qb-022-0322 · Cited by 3
Pandupuspitasari, 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
Liu, S., Zhong, H., Zhu, J., Wu, Y., Deng, Y., & Wu, L. (2023) · International Journal of Cancer · doi:10.1002/ijc.34761 · Cited by 3
Liaw, Y., Matsuda, K., & Liaw, Y. (2024) · JBMR Plus · doi:10.1093/jbmrpl/ziae028 · Cited by 3
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
Three-dimensional chromosome architecture and drug addiction
Chitaman, J. M., Fraser, P., & Feng, J. (2019) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2019.05.009 · Cited by 3
Self-citationDeciphering High-Resolution 3D Chromatin Organization via Capture Hi-C
Hauth, A., Galupa, R., Servant, N., Villacorta, L., Hauschulz, K., van Bemmel, J. G., Loda, A., & Heard, É. (2022) · Journal of Visualized Experiments · doi:10.3791/64166 · Cited by 3
LncVar: Deciphering Genetic Variations Associated with Long Noncoding Genes
Chen, X., Hao, Y., Cui, Y., Fan, Z., & Chen, R. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-8808-2_14 · Cited by 3
Capture Hi-C: Characterization of chromatin contacts
Davis, R. R., Campbell, M., Izumiya, Y., & Tepper, C. G. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-819414-0.00021-5 · Cited by 3
An intriguing characteristic of enhancer-promoter interactions
Talukder, A., Hu, H., & Li, X. (2021) · BMC Genomics · doi:10.1186/s12864-021-07440-5 · Cited by 3
Robust Hi-C chromatin loop maps in human neurogenesis and brain tissues at high-resolutionPreprint
Lu, L., Liu, X., Huang, W., Giusti‐Rodríguez, P., Cui, J., Zhang, S., Xu, W., Wen, Z., Ma, S., Rosen, J. D., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/744540 · Cited by 3
Zhou, N., Friedberg, I., & Kaiser, M. S. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2019.12.16.878371 · Cited by 3
Su, C., Johnson, M. E., Torres, A., Thomas, R. M., Manduchi, E., Sharma, P. K., Coz, C. L., Leonard, M. E., Lu, S., Hodge, K. M., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2019.12.20.885426 · Cited by 3
Complex small-world regulatory networks emerge from the 3D organisation of the human genomePreprint
Brackley, C. A., Gilbert, N., Michieletto, D., Papantonis, A., Pereira, M. C. F., Cook, P. R., & Marenduzzo, D. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.05.12.091041 · Cited by 3
Profiling of transcribed cis -regulatory elements in single cellsPreprint
Moody, J., Kouno, T., Suzuki, A., Shibayama, Y., Terao, C., Chang, J.-C., López-Redondo, F., Yip, C. W., Severin, J., Suetsugu, H., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.04.438388 · Cited by 3
The role of insulators and transcription in 3D chromatin organisation of fliesPreprint
Chathoth, K. T., Mikheeva, L. A., Crevel, G., Wolfe, J. C., Hunter, I., Beckett-Doyle, S., Cotterill, S., Dai, H., Harrison, A., & Zabet, N. R. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.26.441424 · Cited by 3
González‐Serna, D., Shi, C., Kerick, M., Hankinson, J., Ding, J., McGovern, A., Tutino, M., Martin, G. V., Ortego‐Centeno, N., Callejas-Rubio, J. L., et al. (2022) · medRxiv · doi:10.1101/2022.05.08.22274711 · Cited by 3
Malysheva, V., Ray-Jones, H. F., Lakes, N., Brown, R. A., Cazares, T. A., Clay, O., Ohayon, D. E., Artemov, P., Wayman, J. A., Yang, Z. F., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.19.512842 · Cited by 3
Self-citationPollex, T., Rabinowitz, A. H., Gambetta, M. C., Marco-Ferreres, R., Viales, R. R., Jankowski, A., Schaub, C., & Furlong, E. E. M. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.07.519443 · Cited by 3
Genetic cold cases: lessons from solving complex congenital limb disordersPreprint
Andrey, G., & Duboule, D. (2023) · Genes & Development · doi:10.1101/gad.350450.123 · Cited by 3
Competition between transcription and loop extrusion modulates promoter and enhancer dynamicsPreprint
Sexton, T., Platania, A., Erb, C., Barbieri, M., Molcrette, B., Grandgirard, E., de Kort, M. A. C., Meaburn, K. J., Taylor, T., Shchuka, V. M., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-3164817/v1 · Cited by 3
The Gene Expression Landscape of Disease GenesPreprint
García‐González, J., Cote, A. C., Garcia-Gonzalez, S., Liou, L., & O’Reilly, P. F. (2024) · medRxiv · doi:10.1101/2024.06.20.24309121 · Cited by 3
Variance quantitative trait loci reveal gene-gene interactions which alter blood traitsPreprint
Pershad, Y., Poisner, H. M., Corty, R. W., Hellwege, J. N., & Bick, A. G. (2024) · medRxiv · doi:10.1101/2024.09.18.24313883 · Cited by 3
Mammalian enhancers and GWASs act proximally and seldom skip active genesPreprint
Narita, T., & Choudhary, C. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.11.29.625864 · Cited by 3
Node features of chromosome structure networks and their connections to genome annotation
Xu, Y., Das, P., McCord, R. P., & Shen, T. (2024) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2024.05.026 · Cited by 2
Identification of functional enhancer variants associated with type I diabetes in CD4+ T cells
Mishra, A., Jajodia, A., Weston, E., Jayavelu, N. D., García, M. G., Hossack, D., & Hawkins, R. D. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1387253 · Cited by 2
GEEES: inferring cell-specific gene–enhancer interactions from multi-modal single-cell data
Chen, S., & Keleş, S. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae638 · Cited by 2
Hemizygous Moesin (MSN) Gene Deletion in an Adult With Chronic Neutropenia
Castillo‐Aleman, Y. M., Lugo, F. S., Sana, S., Alsaadawi, N., Ventura‐Carmenate, Y., Dennison, D., Statache, G., Osorio-Zuluaga, J., Raza, A., & Grossman, D. (2024) · Case Reports in Immunology · doi:10.1155/crii/3860726 · Cited by 2
SuperGLUE facilitates an explainable training framework for multi-modal data analysis
Liu, T., Zhao, J., & Zhao, H. (2025) · Cell Reports Methods · doi:10.1016/j.crmeth.2025.101167 · Cited by 2
Linkage: an interactive web application for linking of DNA regulatory peaks to genes
Xu, S., Chen, S., Liu, Z., Zhang, C., Luo, Y., Zheng, J., Lu, Z., Yang, J., & Yang, J. (2025) · BMC Genomics · doi:10.1186/s12864-025-12115-6 · Cited by 2
Yuan, M., Zhou, Y., Long, Z.-Y., Peng, Y., Wu, S., Chen, Y., Peng, F., Zhou, Y., Wang, L., & Yuan, H. (2025) · Clinical Rheumatology · doi:10.1007/s10067-025-07774-5 · Cited by 2
CRISPR–Cas-based live cell imaging of genome dynamics
Zhu, Y., Moerner, W. E., & Qi, L. S. (2026) · Nature Reviews Genetics · doi:10.1038/s41576-026-00949-z · Cited by 5
Sun, X., Mews, M., Wheeler, N. R., Benchek, P. H., Gu, T., Gomez, L., Ray, N. R., Reitz, C., Naj, A. C., Below, J. E., et al. (2026) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2026.04.007 · Cited by 2
Population-scale immune multiome atlas reveals regulatory disease mechanisms
Kanai, M., Delorey, T. M., Jarno, H., Rodosthenous, R. S., Juvila, J., Murphy, S., Teixeira-Soldano, I., Hwang, H. S., Karjalainen, J. M., Halonen, J., et al. (2026) · Nature · doi:10.1038/s41586-026-11078-2 · Cited by 16
Rovirosa, L., Tomás-Daza, L., Urmeneta, B., Valencia, A., & Javierre, B. M. (2023) · Journal of Visualized Experiments · doi:10.3791/65316 · Cited by 2
Self-citationLiao, X., Guo, S., Liao, B., Shen, X., He, W., Meng, Y., Liang, C., Pei, J., Liu, J., Zhang, Y., et al. (2023) · Planta · doi:10.1007/s00425-023-04223-y · Cited by 2
Yu, J., Leng, J., Hou, Z., Sun, D., & Wu, L. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae093 · Cited by 2
CatLearning: highly accurate gene expression prediction from histone mark
Lu, W., Tang, Y., Liu, Y., Lin, S., Shuai, Q., Liang, B., Zhang, R., Cheng, Y., & Dong, F. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae373 · Cited by 2
Constructing polymorphonuclear cells: chromatin folding shapes nuclear morphology
Murre, C., Patta, I., Mishra, S. V., & Hu, M. (2024) · Trends in Immunology · doi:10.1016/j.it.2024.09.012 · Cited by 2
Chakraborty, S., Sarma, J., Roy, S. S., Mitra, S., Bagchi, S., Das, S., Saha, S., Mahapatra, S., Bhattacharjee, S., Maulik, M., et al. (2024) · PLoS Genetics · doi:10.1371/journal.pgen.1011502 · Cited by 2
Regulatory roles of three-dimensional structures of chromatin domains
Li, K. Y., Cao, Q., Chow, S. H.-C., Nicoletti, C., Puri, P., Wang, H., Leung, D., & Yip, K. Y.-L. (2025) · Genome biology · doi:10.1186/s13059-025-03659-7 · Cited by 3
Unveiling Epigenetic Regulatory Elements Associated with Breast Cancer Development
Jardanowska-Kotuniak, M., Dramiński, M., Wlasnowolski, M., Łapiński, M., Sengupta, K., Agarwal, A., Filip, A., Ghosh, N., Pancaldi, V., Grynberg, M., et al. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26146558 · Cited by 3
Im, C., Raduski, A. R., Mills, L. J., Bhattarai, K. R., Mobley, R. J., Barnett, K. R., Lu, Z., Liao, K. K., Anderson, N., Johnson, R. A., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-64337-7 · Cited by 4
Automatic detection of genomic regions with informative epigenetic patterns
Pazos, F., García-Moreno, A., & Oliveros, J. C. (2018) · BMC Genomics · doi:10.1186/s12864-018-5286-5 · Cited by 2
Contextual Emergence: Constituents, Context and Meaning
Bishop, R. C. (2022) · The frontiers collection · doi:10.1007/978-3-030-92192-7_15 · Cited by 2
Reiner, A. P., & Johnson, A. D. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-813456-6.00005-9 · Cited by 2
Cappelletti, L., Petrini, A., Gliozzo, J., Casiraghi, E., Schubach, M., Kircher, M., & Valentini, G. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-45385-5_54 · Cited by 2
[Advances in three-dimensional genomics].
Zhang, F., Shen, Z., Yu, C., & Yang, Z. (2020) · PubMed · doi:10.13345/j.cjb.200197 · Cited by 2
Algorithmic considerations when analysing capture Hi-C data
Disney–Hogg, L., Kinnersley, B., & Houlston, R. S. (2022) · Wellcome Open Research · doi:10.12688/wellcomeopenres.16394.2 · Cited by 2
DNA methylation oscillation defines classes of enhancersPreprint
Libertini, E., Hamoudi, R., Heath, S. C., Lancashire, L., García, A. R., Grassi, L., Downes, K., Ouwehand, W. H., Javierre, B. M., Cairns, J., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/262212 · Cited by 2
Self-citationChesi, A., Wagley, Y., Johnson, M. E., Manduchi, E., Su, C., Lu, S., Leonard, M. E., Hodge, K. M., Pippin, J. A., Hankenson, K. D., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/405142 · Cited by 2
Genetic predisposition to myeloproliferative neoplasms implicates hematopoietic stem cell biologyPreprint
Bao, E. L., Nandakumar, S. K., Liao, X., Bick, A. G., Karjalainen, J. M., Tabaka, M., Gan, O. I., Havulinna, A. S., Kiiskinen, T., Lareau, C. A., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/790626 · Cited by 2
Discovery and Functional Characterization of Pro-growth Enhancers in Human Cancer CellsPreprint
Chen, P.-S. B., Fiaux, P. C., Li, B., Zhang, K., Kubo, N., Jiang, S., Hu, R., Wu, S.-H., Wang, M.-C., Wang, W., et al. (2021) · bioRxiv · doi:10.1101/2021.02.04.429675 · Cited by 3
Lagler, T. M., Yang, Y., Harigaya, Y., Sankaran, V. G., Hu, M., Reiner, A. P., Raffield, L. M., Wen, J., & Li, Y. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.15.435494 · Cited by 2
Xie, T., Solórzano, J., Madrid-Mencía, M., Essabbar, A., Pernet, J., Kuo, M.-S., Hucteau, A., Coullomb, A., Verstraete, N., Delfour, O., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.09.439207 · Cited by 2
Su, C., Gao, L., May, C., Pippin, J., Boehm, K., Lee, M. Y. Y., Liu, C.-Y., Pahl, M. C., Golson, M., Naji, A., et al. (2021) · bioRxiv · doi:10.1101/2021.11.30.470653 · Cited by 4
Genomic profiling of HIV-1 integration in microglia links viral insertions to TAD organizationPreprint
Rheinberger, M., Costa, A. L., Kampmann, M., Glavaš, D., Shytaj, I. L., Penzo, C., Tibroni, N., Fackler, O., Vlahoviček, K., Lucic, B., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.02.14.480322 · Cited by 2
DNA co-methylation has a stable structure and is related to specific aspects of genome regulationPreprint
Watkins, S., Suderman, M. J., Hemani, G., Burrows, K., Lawlor, D. A., West, J., Willan, K., Timpson, N. J., Min, J. L., & Gaunt, T. R. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.03.16.484648 · Cited by 3
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Roberts, B. S., Anderson, A. G., Partridge, E. C., Cooper, G. M., & Myers, R. (2024) · Genome Research · doi:10.1101/gr.278598.123 · Cited by 2
Farooq, H., Du, L., Delafrouz, P., Wei, J., Chronis, C., & Liang, J. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.13.598913 · Cited by 3
Simplifying causal gene identification in GWAS lociPreprint
Schipper, M., Ulirsch, J. C., Posthuma, D., Ripke, S., & Heilbron, K. (2024) · medRxiv · doi:10.1101/2024.07.26.24311057 · Cited by 2
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Han, L., Liu, Z., Wang, L., Liu, Y., Wei, Y., Ma, J., He, Y., Zuo, Y., Fang, J., Yang, H., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.13.681959 · Cited by 3
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Bai, J., Lyu, Q., Tan, J., Issner, R., Tischer, B., Liu, H., Goel, V. Y., Ling, X., Bernstein, B., Tsirigos, A., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.09.693120 · Cited by 2
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Zhu, H., Chan, A. S. L., & Narita, M. (2025) · Genes & Development · doi:10.1101/gad.352761.125 · Cited by 2
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Gokuladhas, S., Zaied, R. E., Schierding, W. S., Farrow, S. L., Fadason, T., & O'Sullivan, J. M. (2022) · Results and problems in cell differentiation · doi:10.1007/978-3-031-06573-6_5 · Cited by 2
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Hauth, A., Galupa, R., Servant, N., Villacorta, L., Hauschulz, K., van Bemmel, J. G., Loda, A., & Heard, É. (2022) · Journal of Visualized Experiments · doi:10.3791/64166-v · Cited by 1
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Wang, H., Han, Y., & Qian, P. (2023) · Advances in experimental medicine and biology · doi:10.1007/978-981-99-7471-9_3 · Cited by 2
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Willis, T. W., Gkrania‐Klotsas, E., Wareham, N. J., McKinney, E. F., Lyons, P., Smith, K. G. C., & Wallace, C. (2024) · Clinical Immunology · doi:10.1016/j.clim.2024.110356 · Cited by 1
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Beliveau, B. J., & Akilesh, S. (2024) · Nature Reviews Nephrology · doi:10.1038/s41581-024-00894-2 · Cited by 1
Murakami, K., Iida, K., & Okada, M. (2025) · Genes to Cells · doi:10.1111/gtc.70000 · Cited by 1
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Srivastava, J., & Ovcharenko, I. (2025) · Molecular Biology and Evolution · doi:10.1093/molbev/msaf050 · Cited by 1
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Huang, X., Hullur, A. R., Jafari, E., Shridhar, K., Zhou, M., Mackie, K., Huang, K., & Wang, Y. (2025) · Bioinformatics · doi:10.1093/bioinformatics/btaf186 · Cited by 2
Zhang, Y., Wen, B., Jiao, Y., Liu, Y., Guo, X., Wu, Y., Li, J., Han, L., Xu, Y., Gao, X., et al. (2025) · Advanced Science · doi:10.1002/advs.202505021 · Cited by 1
Functional Validation of Noncoding Variants Associated With Nonsyndromic Orofacial Cleft
Zhu, S., Tao, H.-X., Cornell, R. A., & Liu, H. (2025) · Human Mutation · doi:10.1155/humu/6824122 · Cited by 1
Yang, Y., Xie, C., He, Q., & Yang, M. (2025) · GigaScience · doi:10.1093/gigascience/giaf053 · Cited by 1
Corona, A., Clarelli, F., Pääkkönen, K., Harroud, A., Shchetynsky, K., Zollo, A., Mingione, A., Sorosina, M., Mascia, E., Giordano, A., et al. (2026) · Multiple Sclerosis Journal · doi:10.1177/13524585261417130 · Cited by 1
Dang, X., Wang, Q., Zhang, C., Yao, L., Su, H., Yang, C. X., Feng, H., She, C. H., Chen, X. X., Yang, X. T., et al. (2026) · Communications Medicine · doi:10.1038/s43856-026-01487-9 · Cited by 1
Simplifying causal gene identification in GWAS loci
Schipper, M., Ulirsch, J. C., Posthuma, D., Ripke, S., & Heilbron, K. (2026) · PLoS Genetics · doi:10.1371/journal.pgen.1012079 · Cited by 4
Boolean logic links chromatin accessibility states to gene expression variability across cell types
Malekpour, S. A., Jafari, M., & Sadeghi, M. (2026) · Nucleic Acids Research · doi:10.1093/nar/gkag230 · Cited by 1
Queme, B., Muruganujan, A., Ebert, D., Mushayahama, T., Gauderman, W. J., & Mi, H. (2026) · BMC Genomics · doi:10.1186/s12864-026-12824-6 · Cited by 1
Zhigulev, A., Buyan, A., Lázár, E., Gryzunov, N., Lång, K., Mauron, R., Nozdrin, V., Spalinskas, R., Pradhananga, S., Sjögren, M. P., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-71758-5 · Cited by 1
Fortin, H. J., Struba, A. Z., Bustan, A., & Baker, C. L. (2026) · Genome biology · doi:10.1186/s13059-026-04155-2
Fritz, A. J., Greenyer, H. W., Dillac, L., Chavarkar, P., Neeli, A., Ullah, R., Malik, M., Hong, D., Toor, R. H., Pacht, E., et al. (2026) · Cell Reports · doi:10.1016/j.celrep.2026.118101 · Cited by 2
Breaking barriers: Quebec platelet disorder.
Frontini, M. (2020) · PubMed · doi:10.1182/blood.2020008213 · Cited by 1
Self-citation
Metadata
- Authors
- Javierre, B. M., Burren, O. S., Wilder, S. P., Kreuzhuber, R., Hill, S. M., Sewitz, S., Cairns, J., Wingett, S. W., Várnai, C., Thiecke, M. J., Burden, F., Farrow, S., Cutler, A. J., Rehnström, K., Downes, K., Grassi, L., Kostadima, M., Freire-Pritchett, P., Wang, F., Martens, J. H., Kim, B., Sharifi, N., Janssen-Megens, E. M., Yaspo, M.-L., Linser, M., Kovacsovics, A., Clarke, L., Richardson, D., Datta, A., Flicek, P., Stunnenberg, H. G., Todd, J. A., Zerbino, D. R., Stegle, O., Ouwehand, W. H., Frontini, M., Wallace, C., Spivakov, M., & Fraser, P.
- Affiliations
- Babraham Institute (GB)
- University of Cambridge (GB)
- European Bioinformatics Institute (GB)
- National Health Service (GB)
- MRC Biostatistics Unit (GB)
- Radboud University Nijmegen (NL)
- Corresponding author
- Frontini, Mattia
- Wallace, Chris
- Spivakov, Mikhail
- Fraser, Peter
- ORCID
- Javierre, Biola M.
- Burren, Oliver S.
- Wilder, Steven P.
- Kreuzhuber, Roman
- Sewitz, Sven
- Cairns, Jonathan
- Wingett, Steven W.
- Várnai, Csilla
- Thiecke, Michiel J.
- Burden, Frances
- Cutler, Antony J.
- Downes, Kate
- Grassi, Luigi
- Kostadima, Myrto
- Freire-Pritchett, Paula
- Wang, Fan
- Martens, Joost H.
- Yaspo, Marie-Laure
- Clarke, Laura
- Richardson, David
- Datta, Avik
- Flicek, Paul
- Stunnenberg, Hendrik G.
- Zerbino, Daniel R.
- Stegle, Oliver
- Ouwehand, Willem H.
- Frontini, Mattia
- Wallace, Chris
- Spivakov, Mikhail
- Fraser, Peter
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2016-11
- Volume
- 167
- Issue
- 5
- Pages
- 1369-1384.e19
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC5123897
- OpenAlex
- W2553838260
- Cited by
- 1,046
- References
- 87
- Citations by year
- 2026: 59 · 2025: 84 · 2024: 102 · 2023: 113 · 2022: 116 · 2021: 135 · 2020: 126 · 2019: 130 · 2018: 117 · 2017: 59 · 2016: 4
- FWCI
- 53.72
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Cell (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion, cc-by)
- Radboud Repository (Radboud University) (submittedVersion)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Radboud Repository (Radboud University) (submittedVersion, other-oa)
- Apollo (cc-by)
- Funders
- Biotechnology and Biological Sciences Research Council (BB/J004480/1)
- National Institute for Health Research (PG-0310-1002)
- Wellcome Trust (107212, 107881, 089989, 091157, 095908, 100140)
- Seventh Framework Programme (282510, 241447)
- European Research Council
- Medical Research Council (MC_UP_1302/3, MC_UP_1302/5, MC_UP_1302/1, MR/L007150/1)
- European Molecular Biology Laboratory
- British Heart Foundation (RG/09/12/28096)
- Juvenile Diabetes Research Foundation United States of America (5-SRA-2015-130, 9-2011-253)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer-related molecular mechanisms research
- Keywords
- enhancer-promoter interactions, long-range chromatin interactions, promoter capture Hi-C, hematopoietic lineage, enhancers, transcriptional regulation
- MeSH terms
- Blood Cells, Cell Separation, Chromatin, Disease, Enhancer Elements, Genetic, Hematopoiesis, Humans, Promoter Regions, Genetic, Cell Lineage, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study, Epigenomics
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