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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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Additional file 1 of Inferring chromosome radial organization from Hi-C data
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Additional file 9 of CRISPR screens identify gene targets at breast cancer risk loci
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Self-citationWang, M., He, B., Hao, Y., Srinivasan, D., Shrinet, J., & Fraser, P. (2024) · Figshare · doi:10.6084/m9.figshare.26642443
Self-citationAdditional file 10 of 3D genome organization in the epithelial-mesenchymal transition spectrum
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Additional file 4 of Cis-regulatory atlas of primary human CD4+ T cells
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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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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