The DOI matches its Crossref record; 87 of the 87 references it cites were found in a registry or an index.
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“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]
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.
In the citing paper
“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]
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.
In the citing paper
“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.
In the citing paper
“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]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“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]
The cited source says what the claim attributes to it.
In the citing paper
“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]
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
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
Flagged first, then by citations
Cited by
Sorted by citations
Functional mapping and annotation of genetic associations with FUMA
Watanabe, K., Taskesen, E., van Bochoven, A., & Posthuma, D. (2017) · Nature Communications · doi:10.1038/s41467-017-01261-5 · Cited by 4,083
Võsa, U., Claringbould, A., Westra, H.-J., Bonder, M. J., Deelen, P., Zeng, B., Kirsten, H., Saha, A., Kreuzhuber, R., Yazar, S., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00913-z · Cited by 2,607
Self-citationGenomic atlas of the human plasma proteome
Sun, B. B., Maranville, J. C., Peters, J. E., Stacey, D., Staley, J. R., Blackshaw, J., Burgess, S., Jiang, T., Paige, E., Surendran, P., et al. (2018) · Nature · doi:10.1038/s41586-018-0175-2 · Cited by 2,268
Self-citationMultiscale 3D Genome Rewiring during Mouse Neural Development
Bonev, B., Mendelson Cohen, N., Szabo, Q., Fritsch, L., Papadopoulos, G. L., Lubling, Y., Xu, X., Lv, X., Hugnot, J.-P., Tanay, A., et al. (2017) · Cell · doi:10.1016/j.cell.2017.09.043 · Cited by 1,338
Complex genetic signatures in immune cells underlie autoimmunity and inform therapy
Orrù, V., Steri, M., Sidore, C., Marongiu, M., Serra, V., Olla, S., Sole, G., Lai, S., Dei, M., Mulas, A., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0684-4 · Cited by 1,246
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
