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Genetic Control of Chromatin States in Humans Involves Local and Distal Chromosomal Interactions
Open accessAbstract
Deciphering the impact of genetic variants on gene regulation is fundamental to understanding human disease. Although gene regulation often involves long-range interactions, it is unknown to what extent non-coding genetic variants influence distal molecular phenotypes. Here, we integrate chromatin profiling for three histone marks in lymphoblastoid cell lines (LCLs) from 75 sequenced individuals with LCL-specific Hi-C and ChIA-PET-based chromatin contact maps to uncover one of the largest collections of local and distal histone quantitative trait loci (hQTLs). Distal QTLs are enriched within topologically associated domains and exhibit largely concordant variation of chromatin state coordinated by proximal and distal non-coding genetic variants. Histone QTLs are enriched for common variants associated with autoimmune diseases and enable identification of putative target genes of disease-associated variants from genome-wide association studies. These analyses provide insights into how genetic variation can affect human disease phenotypes by coordinated changes in chromatin at interacting regulatory elements.
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“Mapping interactions between enhancers and promoters in disease-relevant cells improves the accuracy of the assignment (Grubert et al., 2015; McGeachie et al., 2016; Pomerantz et al., 2009), but this is not always feasible.”
From Insulated Neighborhoods: Structural and Functional Units of Mammalian Gene Control (2016) · cites this paper as Grubert et al., 2015
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Citations
Cites
Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.
Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009) · Genome Biology · doi:10.1186/gb-2009-10-3-r25 · Cited by 21,849
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping
Rao, S. S. P., Huntley, M. H., Durand, N. C., Stamenova, E. K., Bochkov, I. D., Robinson, J. T., Sanborn, A. L., Machol, I., Omer, A. D., Lander, E. S., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.021 · Cited by 9,212
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
An integrated map of genetic variation from 1,092 human genomes
The 1000 Genomes Project Consortium (2012) · Nature · doi:10.1038/nature11632 · Cited by 7,711
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
GENCODE: The reference human genome annotation for The ENCODE Project
Harrow, J., Frankish, A., Gonzalez, J. M., Tapanari, E., Diekhans, M., Kokocinski, F., Aken, B. L., Barrell, D., Zadissa, A., Searle, S., et al. (2012) · Genome Research · doi:10.1101/gr.135350.111 · Cited by 4,585
Meta-Analysis of 74,046 Individuals Identifies 11 New Susceptibility Loci for Alzheimer’s Disease
(EADI), E. A. D. I., Lambert, J.-C., (GERAD), G. A. E. R. I. A. D., Alzheimer's Disease Genetic Consortium (ADGC), (CHARGE), C. F. H. A. A. R. I. G. E., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2802 · Cited by 4,336
Hindorff, L. A., Sethupathy, P., Junkins, H. A., Ramos, E. M., Mehta, J. P., Collins, F. S., & Manolio, T. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0903103106 · Cited by 4,013
Cited by
Sorted by citations
Items 101–200 of 339
Benaglio, P., Newsome, J. M., Han, J. Y., Chiou, J., Aylward, A., Corban, S., Miller, M., Okino, M.-L., Kaur, J., Preißl, S., et al. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010759 · Cited by 50
Population-level variation in enhancer expression identifies disease mechanisms in the human brain
Dong, P., Hoffman, G. E., Apontes, P., Bendl, J. M., Rahman, S., Fernando, M. B., Zeng, B., Vicari, J. M., Zhang, W., Girdhar, K., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01170-4 · Cited by 45
Cheung, W., Johnson, A. F., Rowell, W. J., Farrow, E., Hall, R. J., Cohen, A. S. A., Means, J. C., Zion, T. N., Portik, D. M., Saunders, C. T., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-38782-1 · Cited by 49
OncoBase: a platform for decoding regulatory somatic mutations in human cancers
Li, X., Shi, L., Wang, Y., Zhong, J., Zhao, X., Teng, H., Shi, X., Yang, H., Ruan, S., Li, M., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky1139 · Cited by 49
Gleason, K. J., Yang, F., Pierce, B. L., He, X., & Chen, L. (2020) · Genome biology · doi:10.1186/s13059-020-02125-w · Cited by 45
Zhang, X., Chen, X., Weirauch, M. T., Zhang, X., Burleson, J., Brandt, E. B., & Ji, H. (2018) · Current Zoology · doi:10.1093/eep/dvy020 · Cited by 47
Mechanisms of Type 2 Diabetes Risk Loci
Gaulton, K. J. (2017) · Current Diabetes Reports · doi:10.1007/s11892-017-0908-x · Cited by 43
Principles and methods of in-silico prioritization of non-coding regulatory variants
Lee, P. H., Lee, C. R., Li, X., Wee, B., Dwivedi, T., & Daly, M. J. (2017) · Human Genetics · doi:10.1007/s00439-017-1861-0 · Cited by 46
Chromatin accessibility associates with protein-RNA correlation in human cancer
Sanghi, A., Gruber, J. J., Metwally, A. A., Jiang, L., Reynolds, W. D., Sunwoo, J. B., Orloff, L. A., Chang, H. Y., Kasowski, M. M., & Snyder, M. P. (2021) · Nature Communications · doi:10.1038/s41467-021-25872-1 · Cited by 42
Simul-seq: combined DNA and RNA sequencing for whole-genome and transcriptome profiling
Reuter, J., Spacek, D. V., Pai, R. K., & Snyder, M. P. (2016) · Nature Methods · doi:10.1038/nmeth.4028 · Cited by 37
Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease
Hou, L., Xiong, X., Park, Y., Boix, C. A., James, B. T., Sun, N., He, L., Patel, A., Zhang, Z., Molinié, B., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01509-5 · Cited by 44
Intergenic GWAS SNPs are key components of the spatial and regulatory network for human growth
Schierding, W. S., Antony, J., Cutfield, W. S., Horsfield, J. A., & O'Sullivan, J. M. (2016) · Human Molecular Genetics · doi:10.1093/hmg/ddw165 · Cited by 38
A plausibly causal functional lupus-associated risk variant in the STAT1–STAT4 locus
Patel, Z. H., Lu, X., Miller, D., Forney, C. R., Lee, J., Lynch, A., Schroeder, C., Parks, L. G., Magnusen, A. F., Chen, X., et al. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy140 · Cited by 37
Sokhi, U. K., Liber, M. P., Frye, L., Park, S., Kang, K., Pannellini, T., Zhao, B., Norinsky, R., Ivashkiv, L. B., & Gong, S. (2018) · Nature Communications · doi:10.1038/s41467-018-03081-7 · Cited by 37
Grishin, D., & Gusev, A. (2022) · Nature Genetics · doi:10.1038/s41588-022-01075-2 · Cited by 35
Epigenomic charting and functional annotation of risk loci in renal cell carcinoma
Nassar, A. H., Alaiwi, S. A., Baca, S. C., Adib, E., Corona, R. I., Seo, J.-H., Fonseca, M. A., Spisák, S., Zarif, T. E., Tisza, V., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-35833-5 · Cited by 37
Li, M. J., Liu, Z., Liu, Z., Yan, B., Pan, Z., Huang, D., Liang, Q., Ying, D., Xu, F., Yao, H., et al. (2017) · Genome biology · doi:10.1186/s13059-017-1177-3 · Cited by 36
Disease classification: from phenotypic similarity to integrative genomics and beyond
Dozmorov, M. G. (2018) · Briefings in Bioinformatics · doi:10.1093/bib/bby049 · Cited by 36
Chromatin modules and their implication in genomic organization and gene regulation
van Mierlo, G., Pushkarev, O., Kribelbauer, J. F., & Deplancke, B. (2022) · Trends in Genetics · doi:10.1016/j.tig.2022.11.003 · Cited by 35
Structure meets function: How chromatin organisation conveys functionality
Ruiz-Velasco, M., & Zaugg, J. B. (2017) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2017.01.003 · Cited by 40
Buchberger, E., Reis, M., Lu, T.-H., & Posnien, N. (2019) · Genes · doi:10.3390/genes10070492 · Cited by 34
Transcriptional Enhancers: Bridging the Genome and PhenomePreprint
Ren, B., & Yue, F. (2015) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.2015.80.027219 · Cited by 34
Colon-specific eQTL analysis to inform on functional SNPs
Moreno, V. R., Alonso, M. H., Closa, A., Vallès, X., Díez-Villanueva, A., Valle, L., Castellvı́-Bel, S., Pamplona, R. S., López‐Doriga, A., Cordero, D., et al. (2018) · British Journal of Cancer · doi:10.1038/s41416-018-0018-9 · Cited by 33
Interferon-stimulated genes: new platforms and computational approaches
Green, R. R., Ireton, R. C., & Gale, M. (2018) · Mammalian Genome · doi:10.1007/s00335-018-9755-6 · Cited by 37
Epigenomic insights into common human disease pathology
Bell, C. G. (2024) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-024-05206-2 · Cited by 36
Identification of human genetic variants controlling circular RNA expression
Ahmed, I., Karedath, T., Al-Dasim, F. M., & Malek, J. A. (2019) · RNA · doi:10.1261/rna.071654.119 · Cited by 30
Prowse-Wilkins, C., Lopdell, T., Xiang, R., Jagt, C. J. V., Littlejohn, M. D., Chamberlain, A. J., & Goddard, M. E. (2022) · BMC Genomics · doi:10.1186/s12864-022-09002-9 · Cited by 34
A Bayesian model selection approach to mediation analysis
Crouse, W. L., Keele, G. R., Gastonguay, M. S., Churchill, G. A., & Valdar, W. S. J. (2022) · PLoS Genetics · doi:10.1371/journal.pgen.1010184 · Cited by 36
Integrating Genes Affecting Coronary Artery Disease in Functional Networks by Multi-OMICs Approach
Vilne, B., & Schunkert, H. (2018) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2018.00089 · Cited by 31
Zhao, Q., Dacre, M., Nguyen, T., Pjanic, M., Liu, B., Iyer, D., Cheng, P. P., Wirka, R. C., Kim, J. B., Fraser, H. B., et al. (2020) · Genome biology · doi:10.1186/s13059-020-02049-5 · Cited by 30
del Rosario, R. C. H., Poschmann, J., Lim, C., Cheng, C. Y., Kumar, P., Riou, C., Ong, S. T., Gerges, S., Hajan, H. S., Kumar, D., et al. (2022) · Nature Microbiology · doi:10.1038/s41564-021-01049-w · Cited by 32
Spatial promoter–enhancer hubs in cancer: organization, regulation, and function
Zhao, J., & Faryabi, R. B. (2023) · Trends in Cancer · doi:10.1016/j.trecan.2023.07.017 · Cited by 28
Andrew, S. C., Jensen, H., Hagen, I. J., Lundregan, S. L., & Griffith, S. C. (2018) · Molecular Ecology · doi:10.1111/mec.14897 · Cited by 28
Predicting 3D chromatin interactions from DNA sequence using Deep Learning
Piecyk, R. S., Schlegel, L., & Johannes, F. M. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.06.047 · Cited by 27
Genome-Wide Expression Quantitative Trait Loci Analysis Using Mixed Models
Lee, C. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00341 · Cited by 28
Local environment‐driven adaptive evolution in a marine invasive ascidian (Molgula manhattensis)
Chen, Y., Gao, Y., Huang, X., Li, S., & Zhan, A. (2021) · Ecology and Evolution · doi:10.1002/ece3.7322 · Cited by 26
Wang, H., Huang, B., & Wang, J. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab841 · Cited by 26
Reconstruct high-resolution 3D genome structures for diverse cell-types using FLAMINGO
Wang, H., Yang, J., Zhang, Y., Qian, J., & Wang, J. (2022) · Nature Communications · doi:10.1038/s41467-022-30270-2 · Cited by 28
Li, H., Achour, I., Bastarache, L. A., Berghout, J., Gardeux, V., Li, J., Lee, Y., Pesce, L. L., Yang, X. H., Ramos, K. S., et al. (2016) · npj Genomic Medicine · doi:10.1038/npjgenmed.2016.6 · Cited by 27
Zhang, M., Lykke‐Andersen, S., Zhu, B., Xiao, W., Hoskins, J. W., Zhang, X., Rost, L. M., Collins, I. J., van de Bunt, M., Jia, J., et al. (2017) · Gut · doi:10.1136/gutjnl-2016-313146 · Cited by 26
The complexity of epigenetic diseases
Brazel, A. J., & Vernimmen, D. (2015) · The Journal of Pathology · doi:10.1002/path.4647 · Cited by 25
Mechanisms Underlying the Selection and Function of Macrophage-Specific EnhancersPreprint
Link, V. M., Gosselin, D., & Glass, C. K. (2015) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.2015.80.027367 · Cited by 25
Functional Characterization of Genetic Variant Effects on Expression
Flynn, E. D., & Lappalainen, T. (2022) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-122120-010010 · Cited by 24
Bykova, M., Hou, Y., Eng, C., & Cheng, F. (2022) · Human Molecular Genetics · doi:10.1093/hmg/ddac208 · Cited by 24
Characterization of sequence determinants of enhancer function using natural genetic variation
Yang, M. G., Ling, E., Cowley, C. J., Greenberg, M. E., & Vierbuchen, T. (2022) · eLife · doi:10.7554/elife.76500 · Cited by 25
Ozgyin, L., Horváth, A., Hevessy, Z., & Bálint, B. L. (2019) · Scientific Reports · doi:10.1038/s41598-019-40897-9 · Cited by 23
Wang, L., Xia, Y., Chen, Y., Dai, R., Qiu, W., Meng, Q., Kuney, L., & Chen, C. (2019) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2019.02.002 · Cited by 23
A genome-wide association study implicatesNR2F2in lymphangioleiomyomatosis pathogenesis
Kim, W., Giannikou, K., Dreier, J. R., Lee, S., Tyburczy, M. E., Silverman, E. K., Radzikowska, E., Wu, S., Wu, C., Henske, E. P., et al. (2019) · European Respiratory Journal · doi:10.1183/13993003.00329-2019 · Cited by 23
Li, C., Lenhard, B., & Luscombe, N. M. (2018) · Genome Research · doi:10.1101/gr.231449.117 · Cited by 24
Enhancer-promoter hubs organize transcriptional networks promoting oncogenesis and drug resistance
Perlman, B. S., Burget, N. G., Zhou, Y., Schwartz, G. W., Petrovic, J., Modrusan, Z. D., & Faryabi, R. B. (2024) · Nature Communications · doi:10.1038/s41467-024-52375-6 · Cited by 23
de Paz, A. M., & Ausió, J. (2015) · BioEssays · doi:10.1002/bies.201500157 · Cited by 21
Wang, M., Hancock, T., Chamberlain, A. J., Jagt, C. J. V., Pryce, J. E., Cocks, B. G., Goddard, M. E., & Hayes, B. J. (2018) · BMC Genomics · doi:10.1186/s12864-018-4800-0 · Cited by 20
Jeng, M. Y., Mumbach, M. R., Granja, J. M., Satpathy, A. T., Chang, H. Y., & Chang, A. L. S. (2018) · Journal of Investigative Dermatology · doi:10.1016/j.jid.2018.09.011 · Cited by 22
Hammelman, J., Krismer, K., Banerjee, B., Gifford, D. K., & Sherwood, R. I. (2020) · Genome Research · doi:10.1101/gr.263228.120 · Cited by 19
Cavalli, M., Pan, G., Nord, H., & Wadelius, C. (2016) · Lipids in Health and Disease · doi:10.1186/s12944-016-0183-x · Cited by 20
Budach, S., Heinig, M., & Marsico, A. (2016) · Genetics · doi:10.1534/genetics.116.187153 · Cited by 22
Chen, X., Guo, M., Duan, Y.-Y., Jiang, F., Wu, H., Dong, S., Zhou, X., Thynn, H. N., Liu, C., Zhang, L., et al. (2020) · JCI Insight · doi:10.1172/jci.insight.136477 · Cited by 19
SHAMAN: bin-free randomization, normalization and screening of Hi-C matricesPreprint
Cohen, N. M., Olivares‐Chauvet, P., Lubling, Y., Baran, Y., Lifshitz, A., Hoichman, M., & Tanay, A. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/187203 · Cited by 17
Genetic risk for neurodegenerative conditions is linked to disease-specific microglial pathways
Askarova, A., Yaa, R. M., Marzi, S. J., & Nott, A. (2025) · PLoS Genetics · doi:10.1371/journal.pgen.1011407 · Cited by 21
HiCeekR: A Novel Shiny App for Hi-C Data Analysis
Filippo, L. D., Righelli, D., Gagliardi, M., Matarazzo, M. R., & Angelini, C. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.01079 · Cited by 18
Shen, Z., Hoeksema, M. A., Ouyang, Z., Benner, C. W., & Glass, C. K. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa476 · Cited by 16
Pudjihartono, M., Perry, J. K., Print, C. G., O'Sullivan, J. M., & Schierding, W. S. (2022) · Clinical Epigenetics · doi:10.1186/s13148-022-01342-3 · Cited by 19
Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data
Wu, Y., Qi, T., Wang, H., Zhang, F., Zheng, Z., Phillips‐Cremins, J. E., Deary, I. J., McRae, A. F., Wray, N. R., Zeng, J., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15587-0 · Cited by 14
Topologically-associating domains: gene warehouses adapted to serve transcriptional regulation
Razin, S. V., Gavrilov, A. A., Vassetzky, Y. S., & Ulianov, S. V. (2016) · Transcription · doi:10.1080/21541264.2016.1181489 · Cited by 18
Jiménez‐Sousa, M. Á., Gómez‐Moreno, A. Z., Tenor, D. P., Medrano, L. M., Sánchez‐Ruano, J. J., Fernández‐Rodríguez, A., Artaza-Varasa, T., Saura-Montalbán, J., Vázquez‐Morón, S., Ryan, P., et al. (2017) · Clinical and Translational Medicine · doi:10.1186/s40169-017-0156-3 · Cited by 17
Molecular and computational approaches to map regulatory elements in 3D chromatin structure
Lee, B. H., & Rhie, S. K. (2021) · Epigenetics & Chromatin · doi:10.1186/s13072-021-00390-y · Cited by 17
‘There and Back Again’—Forward Genetics and Reverse Phenotyping in Pulmonary Arterial Hypertension
Swietlik, E. M., Prapa, M., Martin, J. M., Pandya, D., Auckland, K., Morrell, N. W., & Gräf, S. (2020) · Genes · doi:10.3390/genes11121408 · Cited by 15
Llimos, G., Gardeux, V., Koch, U., Kribelbauer, J. F., Hafner, A., Alpern, D., Pezoldt, J., Litovchenko, M., Russeil, J., Dainese, R., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29625-6 · Cited by 16
Gusev, A., Spisák, S., Fay, A. P., Carol, H. A., Vavra, K. C., Signoretti, S., Tisza, V., Pomerantz, M. M., Abbasi, F., Seo, J.-H., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/631150 · Cited by 15
Using Gene Expression to Annotate Cardiovascular GWAS Loci
Heinig, M. (2018) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2018.00059 · Cited by 15
Ma, M., Huang, D., Liang, X., Zhang, L., Cheng, S., Cheng, B., Qi, X., Li, P., Du, Y., Liu, L., et al. (2019) · Osteoporosis International · doi:10.1007/s00198-019-04958-z · Cited by 15
Cis-acting regulatory elements regulating CYP3A4 transcription in human liver
Collins, J. M., & Wang, D. (2020) · Pharmacogenetics and Genomics · doi:10.1097/fpc.0000000000000402 · Cited by 15
Alasoo, K., Rodrigues, J., Mukhopadhyay, S., Knights, A. J., Mann, A. L., Kundu, K., Hale, C., Dougan, G., & Gaffney, D. J. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/102392 · Cited by 15
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
Genetic and epigenetic determinants of inter-individual variability in responses to toxicants
Lewis, L., Crawford, G. E., Furey, T. S., & Rusyn, I. (2017) · Current Opinion in Toxicology · doi:10.1016/j.cotox.2017.08.006 · Cited by 16
Nititham, J., Fergusson, C., Palmer, C., Liao, W. J., & Foerster, J. (2018) · Experimental Dermatology · doi:10.1111/exd.13761 · Cited by 14
Allele-Specific QTL Fine Mapping with PLASMA
Wang, A. T., Shetty, A. H., O’Connor, E. P., Bell, C. A., Pomerantz, M. M., Freedman, M. L., & Gusev, A. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.12.011 · Cited by 14
Transcription factor expression is the main determinant of variability in gene co‐activity
van Duin, L., Krautz, R., Rennie, S., & Andersson, R. (2023) · Molecular Systems Biology · doi:10.15252/msb.202211392 · Cited by 11
Multiome-wide Association Studies: Novel Approaches for Understanding Diseases
Shao, M., Chen, K., Zhang, S., Tian, M., Shen, Y., Cao, C., & Gu, N. (2024) · Genomics Proteomics & Bioinformatics · doi:10.1093/gpbjnl/qzae077 · Cited by 14
A Long-Distance Chromatin Affair
Denker, A., & de Laat, W. L. (2015) · Cell · doi:10.1016/j.cell.2015.08.022 · Cited by 13
Dainese, R., Gardeux, V., Llimos, G., Alpern, D., Jiang, J. Y., Meireles-Filho, A. C. A., & Deplancke, B. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1913261117 · Cited by 13
Shi, W., Fornés, O., & Wasserman, W. W. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty992 · Cited by 14
Gusev, F. E., Reshetov, D. A., Mitchell, A., Андреева, Т. В., Dincer, A., Grigorenko, A. P., Fedonin, G. G., Halene, T. B., Aliseychik, M., Goltsov, A. Y., et al. (2019) · The FASEB Journal · doi:10.1096/fj.201802646r · Cited by 13
Chidambaran, V., Zhang, X., Pilipenko, V. V., Chen, X., Wronowski, B., Geisler, K. J., Martin, L. J., Barski, A., Weirauch, M. T., & Ji, H. (2021) · Epigenomics · doi:10.2217/epi-2020-0424 · Cited by 12
Wang, H., Yang, J., Zhang, Y., & Wang, J. (2020) · Methods · doi:10.1016/j.ymeth.2020.10.010 · Cited by 12
Epigenetic perturbations in aging stem cells
Krauss, S. R., & de Haan, G. (2016) · Mammalian Genome · doi:10.1007/s00335-016-9645-8 · Cited by 14
Tracking the evolution of 3D gene organization demonstrates its connection to phenotypic divergence
Diament, A., & Tuller, T. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx205 · Cited by 12
Adding another dimension to gene regulation
Koch, L. (2015) · Nature Reviews Genetics · doi:10.1038/nrg4007 · Cited by 11
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Metadata
- Authors
- Grubert, F., Zaugg, J. B., Kasowski, M., Ursu, O., Spacek, D. V., Martin, A. R., Greenside, P., Srivas, R., Phanstiel, D. H., Pekowska, A., Heidari, N., Euskirchen, G., Huber, W., Pritchard, J. K., Bustamante, C. D., Steinmetz, L. M., Kundaje, A., & Snyder, M.
- Affiliations
- Stanford Medicine (US)
- European Molecular Biology Laboratory (DE)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Snyder, Michael
- ORCID
- Venue
- Cell
- Publisher
- Elsevier BV
- Published
- 2015-08
- Volume
- 162
- Issue
- 5
- Pages
- 1051-1065
- ISSN
- 0092-8674 (ISSN-L)
- PMC
- PMC4556133
- OpenAlex
- W2112673809
- Cited by
- 319
- References
- 56
- Citations by year
- 2026: 12 · 2025: 13 · 2024: 18 · 2023: 21 · 2022: 25 · 2021: 23 · 2020: 37 · 2019: 39 · 2018: 48 · 2017: 39 · 2016: 36 · 2015: 8
- FWCI
- 18.95
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Cell (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Howard Hughes Medical Institute
- National Heart, Lung, and Blood Institute (R01HL122887, U01HL107393)
- National Human Genome Research Institute (U41HG007000, U54HG006996, R00HG008662, K99HG008662, U41-HG007000-02S1, P50HG007735, U01HG007919, P01HG000205, T32HG000044)
- National Institute of General Medical Sciences (T32GM007790, T32GM007205)
- National Institute of Environmental Health Sciences (R01ES025009)
- U.S. National Library of Medicine (LM 07033, T15LM007033)
- 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 › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- histone modifications, chromatin state, long-range chromatin interactions, topologically associating domains, non-coding variants, gene expression regulation, lymphoblastoid cell lines, Hi-C, ChIA-PET
- MeSH terms
- Cell Line, Chromatin, Chromosomes, Human, Female, Histones, Humans, Lymphocytes, Male, Cohort Studies, Human Genome Project, Quantitative Trait Loci, Regulatory Elements, Transcriptional, Gene Regulatory Networks, Genome-Wide Association Study
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