The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
The accessible chromatin landscape of the human genome
Open accessAbstract
DNase I hypersensitive sites (DHSs) are markers of regulatory DNA and have underpinned the discovery of all classes of cis-regulatory elements including enhancers, promoters, insulators, silencers and locus control regions. Here we present the first extensive map of human DHSs identified through genome-wide profiling in 125 diverse cell and tissue types. We identify ∼2.9 million DHSs that encompass virtually all known experimentally validated cis-regulatory sequences and expose a vast trove of novel elements, most with highly cell-selective regulation. Annotating these elements using ENCODE data reveals novel relationships between chromatin accessibility, transcription, DNA methylation and regulatory factor occupancy patterns. We connect ∼580,000 distal DHSs with their target promoters, revealing systematic pairing of different classes of distal DHSs and specific promoter types. Patterning of chromatin accessibility at many regulatory regions is organized with dozens to hundreds of co-activated elements, and the transcellular DNase I sensitivity pattern at a given region can predict cell-type-specific functional behaviours. The DHS landscape shows signatures of recent functional evolutionary constraint. However, the DHS compartment in pluripotent and immortalized cells exhibits higher mutation rates than that in highly differentiated cells, exposing an unexpected link between chromatin accessibility, proliferative potential and patterns of human variation. An extensive map of human DNase I hypersensitive sites, markers of regulatory DNA, in 125 diverse cell and tissue types is described; integration of this information with other ENCODE-generated data sets identifies new relationships between chromatin accessibility, transcription, DNA methylation and regulatory factor occupancy patterns. This paper describes the first extensive map of human DNaseI hypersensitive sites — markers of regulatory DNA — in 125 diverse cell and tissue types. Integration of this information with other data sets generated by ENCODE (Encyclopedia of DNA Elements) identified new relationships between chromatin accessibility, transcription, DNA methylation and regulatory-factor occupancy patterns. Evolutionary-conservation analysis revealed signatures of recent functional constraint within DNaseI hypersensitive sites.
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
“Assisted loading events are coupled with increases in enhancer activity as measured by DNase hypersensitivity or H3K27 acetylation (H3K27ac), two well-established markers for active enhancers38–40.”
From Synergistic gene expression during the acute phase response is characterized by transcription factor assisted loading (2017) · cites this paper as [40]
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
“According to recent estimates, the number of enhancers in the human genome ranges from 400,000 to 1,000,000 [22,23].”
From Enhancer Function in the 3D Genome (2023) · cites this paper as [23]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“To some degree this can be overcome by correlative approaches (e.g. correlating open chromatin status between promoters and enhancers across large numbers of cell types) but such links remain inferential45,134,135.”
From Towards a comprehensive catalogue of validated and target-linked human enhancers (2020) · cites this paper as [45]
In the citing paper
“most genetic variation that contributes to common psychiatric disorders is not in protein-coding regions”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Thurman et al., 2012
In the citing paper
“Thus, methods that measure chromatin accessibility by combining sensitivity to enzymatic digestion with sequencing6–8 provide an integrated map of chromatin states that encompasses a diverse repertoire of functional regulatory elements2,5.”
From Droplet-based combinatorial indexing for massive-scale single-cell chromatin accessibility (2019) · cites this paper as [2]
In the citing paper
“Both classical observations5 and recent genome-wide efforts2 have shown that active regulatory elements are canonically nucleosome free and accessible to transcriptional machinery.”
From Droplet-based combinatorial indexing for massive-scale single-cell chromatin accessibility (2019) · cites this paper as [2]
In the citing paper
“We found that chromatin accessibility from bulk ATAC-seq8 and DNase-seq2 and the aggregate chromatin accessibility across the different single-cell technologies18,19,24,25 were highly correlated (Fig. 1c,d).”
From Droplet-based combinatorial indexing for massive-scale single-cell chromatin accessibility (2019) · cites this paper as [2]
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
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
Self-citationLandscape of transcription in human cells
Djebali, S., Davis, C. A., Merkel, A., Dobin, A., Lassmann, T., Mortazavi, A., Tanzer, A., Lagarde, J., Lin, W., Schlesinger, F., et al. (2012) · Nature · doi:10.1038/nature11233 · Cited by 5,187
Self-citationGENCODE: 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
miRBase: tools for microRNA genomics
Griffiths‐Jones, S., Saini, H. K., van Dongen, S., & Enright, A. J. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm952 · Cited by 4,432
FIMO: scanning for occurrences of a given motif
Grant, C. E., Bailey, T. L., & Noble, W. S. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr064 · Cited by 4,247
Heintzman, N. D., Stuart, R. K., Hon, G., Fu, Y., Ching, C. W., Hawkins, R. D., Barrera, L. O., Van Calcar, S., Qu, C., Ching, K. A., et al. (2007) · Nature Genetics · doi:10.1038/ng1966 · Cited by 3,398
Self-citationThe long-range interaction landscape of gene promoters
Sanyal, A., Lajoie, B. R., Jain, G., & Dekker, J. (2012) · Nature · doi:10.1038/nature11279 · Cited by 1,489
Self-citationHigh-Resolution Mapping and Characterization of Open Chromatin across the Genome
Boyle, A. P., Davis, S., Shulha, H. P., Meltzer, P., Margulies, E. H., Weng, Z., Furey, T. S., & Crawford, G. E. (2008) · Cell · doi:10.1016/j.cell.2007.12.014 · Cited by 1,415
Self-citationDNA-binding factors shape the mouse methylome at distal regulatory regions
Stadler, M. B., Murr, R., Burger, L., Ivanek, R., Lienert, F., Schöler, A., Nimwegen, E. V., Wirbelauer, C., Oakeley, E. J., Gaidatzis, D., et al. (2011) · Nature · doi:10.1038/nature10716 · Cited by 1,383
An Extended Transcriptional Network for Pluripotency of Embryonic Stem Cells
Kim, J., Chu, J., Shen, X., Wang, J., & Orkin, S. H. (2008) · Cell · doi:10.1016/j.cell.2008.02.039 · Cited by 1,361
Flagged first, then by citations
Cited by
Sorted by citations
Items 901–1,000 of 1,010
Identifying causal regulatory SNPs in ChIP-seq enhancers
Huang, D., & Ovcharenko, I. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1318 · Cited by 44
Multiple cellular origins and molecular evolution of intrahepatic cholangiocarcinoma
Wei, M., Lü, L., Lin, P., Chen, Z., Quan, Z., & Tang, Z. (2016) · Cancer Letters · doi:10.1016/j.canlet.2016.02.038 · Cited by 44
Umer, H. M., Cavalli, M., Dąbrowski, M. J., Diamanti, K., Kruczyk, M., Pan, G., Komorowski, J., & Wadelius, C. (2016) · Human Mutation · doi:10.1002/humu.23014 · Cited by 44
Epigenetic memory: A macrophage perspective
Logie, C., & Stunnenberg, H. G. (2016) · Seminars in Immunology · doi:10.1016/j.smim.2016.06.003 · Cited by 44
Genetic variants alter T-bet binding and gene expression in mucosal inflammatory disease
Soderquest, K., Hertweck, A., Giambartolomei, C., Henderson, S. R., Mohamed, R., Goldberg, R., Perucha, E., Franke, L., Herrero, J., Plagnol, V., et al. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1006587 · Cited by 44
Tao, H., Li, H., Xu, K., Hong, H., Jiang, S., Du, G., Wang, J., Sun, Y., Huang, X., Ding, Y., et al. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa405 · Cited by 44
Virtual ChIP-seq: predicting transcription factor binding by learning from the transcriptome
Karimzadeh, M., & Hoffman, M. M. (2022) · Genome biology · doi:10.1186/s13059-022-02690-2 · Cited by 44
Evolutionary expansion of DNA hypomethylation in the mammalian germline genomePreprint
Qu, J., Hodges, E. C., Molaro, A., Gagneux, P., Dean, M. D., Hannon, G. J., & Smith, A. D. (2017) · Genome Research · doi:10.1101/gr.225896.117 · Cited by 46
Han, F., Liu, X., Chen, C., Liu, Y., Du, M., Guan, Y., Zhang, Y., Wang, D., Ahmed, M., Li, X., et al. (2020) · Cell Research · doi:10.1038/s41422-020-0303-z · Cited by 43
Cas9 Functionally Opens Chromatin
Barkal, A. A., Srinivasan, S., Hashimoto, T., Gifford, D. K., & Sherwood, R. I. (2016) · PLoS ONE · doi:10.1371/journal.pone.0152683 · Cited by 43
Fatemi, S. H., Folsom, T. D., & THURAS, P. D. (2017) · Synapse · doi:10.1002/syn.21973 · Cited by 43
Enhancer–gene maps in the human and zebrafish genomes using evolutionary linkage conservation
Clément, Y., Torbey, P., Gilardi‐Hebenstreit, P., & Crollius, H. R. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz1199 · Cited by 43
Genome-Wide Analysis Identifies an Essential Human TBX3 Pacemaker Enhancer
van Eif, V. W. W., Protze, S. I., Bosada, F. M., Yuan, X., Sinha, T., van Duijvenboden, K., Ernault, A. C., Mohan, R. A., Wakker, V., Vries, C. D. G.-D., et al. (2020) · Circulation Research · doi:10.1161/circresaha.120.317054 · Cited by 43
Kirstein, N., Buschle, A., Wu, X., Krebs, S., Blum, H., Kremmer, E., Vorberg, I. M., Hammerschmidt, W., Lacroix, L., Hyrien, O., et al. (2021) · eLife · doi:10.7554/elife.62161 · Cited by 43
Möller, E., Praz, V., Rajendran, S., Dong, R., Cauderay, A., Xing, Y., Lee, L., Fusco, C., Broye, L. C., Cironi, L., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-29910-4 · Cited by 43
Cazares, T. A., Rizvi, F. W., Iyer, B., Chen, X., Kotliar, M., Bejjani, A. T., Wayman, J. A., Donmez, O. A., Wronowski, B., Parameswaran, S., et al. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010863 · Cited by 44
Evidence for Site-Specific Occupancy of the Mitochondrial Genome by Nuclear Transcription Factors
Marinov, G. K., Wang, Y. E., Chan, D. C., & Wold, B. J. (2014) · PLoS ONE · doi:10.1371/journal.pone.0084713 · Cited by 43
Grillo, G., Keshavarzian, T., Linder, S., Arlidge, C., Mout, L., Nand, A., Teng, M., Qamra, A., Zhou, S., Kron, K. J., et al. (2023) · Cancer Discovery · doi:10.1158/2159-8290.cd-23-0331 · Cited by 42
Oger, F., Dubois‐Chevalier, J., Gheeraert, C., Avner, S., Durand, E., Froguel, P., Salbert, G., Staels, B., Lefèbvre, P., & Eeckhoute, J. (2013) · Journal of Biological Chemistry · doi:10.1074/jbc.m113.526996 · Cited by 42
Lin, Y., Sibanda, V. L., Zhang, H., Hu, H., Liu, H., & Guo, A. (2015) · Scientific Reports · doi:10.1038/srep09653 · Cited by 42
Increased DNA methylation of Dnmt3b targets impairs leukemogenesis
Schulze, I., Rohde, C., Scheller, M., Bäumer, N., Krause, A., Herbst, F., Riemke, P., Hebestreit, K., Tschanter, P., Lin, Q., et al. (2016) · Blood · doi:10.1182/blood-2015-07-655928 · Cited by 42
Epigenetic regulation of bone cells
Park‐Min, K. H. (2016) · Connective Tissue Research · doi:10.1080/03008207.2016.1177037 · Cited by 42
Wang, X., & Kültz, D. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1614712114 · Cited by 42
Temporal and Spatial Epigenome Editing Allows Precise Gene Regulation in Mammalian Cells
Kuscu, C., Mammadov, R., Czikora, Á., Unlu, H., Tufan, T., Fischer, N. L., Arslan, Ş., Bekiranov, S., Kanemaki, M. T., & Adli, M. (2018) · Journal of Molecular Biology · doi:10.1016/j.jmb.2018.08.001 · Cited by 42
Integrated epigenomic profiling reveals endogenous retrovirus reactivation in renal cell carcinoma
Siebenthall, K. T., Miller, C. P., Vierstra, J. D., Mathieu, J., Tretiakova, M., Reynolds, A. P., Sandstrom, R. S., Rynes, E., Neph, S. J., Haugen, E., et al. (2019) · EBioMedicine · doi:10.1016/j.ebiom.2019.01.063 · Cited by 42
Self-citationPeñalosa-Ruiz, G., Bright, A. R., Mulder, K. W., & Veenstra, G. J. C. (2019) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2019.194407 · Cited by 42
An enhancer cluster controls gene activity and topology of the SCN5A-SCN10A locus in vivo
Man, J. C. K., Mohan, R. A., van den Boogaard, M., Hilvering, C. R. E., Jenkins, C., Wakker, V., Bianchi, V., de Laat, W. L., Barnett, P., Boukens, B. J., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-12856-5 · Cited by 43
Kulik, M., Bothe, M., Kibar, G., Fuchs, A., Schöne, S., Preković, S., Mayayo‐Peralta, I., Chung, H., Zwart, W. T., Helsen, C., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab185 · Cited by 42
Androgen Receptor Function Links Human Sexual Dimorphism to DNA Methylation
Ammerpohl, O., Bens, S., Appari, M., Werner, R., Korn, B., Drop, S. L. S., Verheijen, F. W., van der Zwan, Y. G., Bunch, T., Hughes, I. A., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0073288 · Cited by 42
pENCODE: A Plant Encyclopedia of DNA Elements
Lane, A. K., Niederhuth, C. E., Ji, L., & Schmitz, R. J. (2014) · Annual Review of Genetics · doi:10.1146/annurev-genet-120213-092443 · Cited by 42
Cotney, J. L., & Noonan, J. P. (2015) · Cold Spring Harbor Protocols · doi:10.1101/pdb.prot084848 · Cited by 42
Functional compensation among HMGN variants modulates the DNase I hypersensitive sites at enhancersPreprint
Deng, T., Zhu, Z., Zhang, S., Postnikov, Y. V., Huang, D., Horsch, M., Furusawa, T., Beckers, J., Rozman, J., Klingenspor, M., et al. (2015) · Genome Research · doi:10.1101/gr.192229.115 · Cited by 42
Cis-regulatory landscapes of four cell types of the retina
Hartl, D., Krebs, A. R., Jüttner, J., Roska, B., & Schübeler, D. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx923 · Cited by 37
Readout of histone methylation by Trim24 locally restricts chromatin opening by p53
Isbel, L., Iskar, M., Durdu, S., Weiss, J., Grand, R. S., Hietter-Pfeiffer, E., Kozicka, Z., Michael, A. K., Burger, L., Thomä, N. H., et al. (2023) · Nature Structural & Molecular Biology · doi:10.1038/s41594-023-01021-8 · Cited by 41
The Interactions of microRNA and Epigenetic Modifications in Prostate Cancer
Singh, P. K., & Campbell, M. J. (2013) · Cancers · doi:10.3390/cancers5030998 · Cited by 41
Predictive modelling of gene expression from transcriptional regulatory elements
Budden, D., Hurley, D., & Crampin, E. J. (2014) · Briefings in Bioinformatics · doi:10.1093/bib/bbu034 · Cited by 41
Chen, H., Yu, H., Wang, J., Zhang, Z., Gao, Z., Chen, Z., Lu, Y., Liu, W., Jiang, D., Zheng, S. L., et al. (2015) · The Prostate · doi:10.1002/pros.23008 · Cited by 41
Self-citationNovel regional age-associated DNA methylation changes within human common disease-associated loci
Bell, C. G., Xia, Y., Yuan, W., Gao, F., Ward, K. J., Roos, L., Mangino, M., Hysi, P. G., Bell, J. T., Wang, J., et al. (2016) · Genome biology · doi:10.1186/s13059-016-1051-8 · Cited by 41
Predicting gene expression in massively parallel reporter assays: A comparative study
Kreimer, A., Zeng, H., Edwards, M. D., Guo, Y., Tian, K., Shin, S., Welch, R., Wainberg, M., Mohan, R., Sinnott-Armstrong, N., et al. (2017) · Human Mutation · doi:10.1002/humu.23197 · Cited by 41
High-intensity UV laser ChIP-seq for the study of protein-DNA interactions in living cells
Steube, A., Schenk, T., Tretyakov, A. N., & Saluz, H. P. (2017) · Nature Communications · doi:10.1038/s41467-017-01251-7 · Cited by 41
Computational Biology Solutions to Identify Enhancers-target Gene Pairs
Hariprakash, J. M., & Ferrari, F. (2019) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2019.06.012 · Cited by 41
eQTL Colocalization Analyses Identify NTN4 as a Candidate Breast Cancer Risk Gene
Beesley, J., Sivakumaran, H., Marjaneh, M. M., Shi, W., Hillman, K. M., Kaufmann, S., Hussein, N., Kar, S., Lima, L. G., Ham, S., et al. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.08.006 · Cited by 41
Structural basis for p53 binding to its nucleosomal target DNA sequence
Nishimura, M., Takizawa, Y., Nozawa, K., & Kurumizaka, H. (2022) · PNAS Nexus · doi:10.1093/pnasnexus/pgac177 · Cited by 41
Epigenetics: A New Player in the Regulation of Mammalian Puberty
Rzeczkowska, P. A., Hou, H., Wilson, M. D., & Palmert, M. R. (2014) · Neuroendocrinology · doi:10.1159/000362559 · Cited by 41
Dong, X., Wang, X. R., Zhang, F., & Tian, W. (2016) · Molecular Biology and Evolution · doi:10.1093/molbev/msw128 · Cited by 41
Koohy, H., Bolland, D. J., Matheson, L. S., Schoenfelder, S., Stellato, C., Dimond, A., Várnai, C., Chovanec, P., Chessa, T. A. M., Denizot, J., et al. (2018) · Genome biology · doi:10.1186/s13059-018-1489-y · Cited by 41
Robust validation of methylation levels association at CPT1A locus with lipid plasma levels
Gagnon, F., Aïssi, D., Carrié, A., Morange, P., & Trégouët, D. (2014) · Journal of Lipid Research · doi:10.1194/jlr.e051276 · Cited by 41
Genetics and Genomics of Coronary Artery Disease
Pjanic, M., Miller, C. L., Wirka, R. C., Kim, J. B., DiRenzo, D. M., & Quertermous, T. (2016) · Current Cardiology Reports · doi:10.1007/s11886-016-0777-y · Cited by 40
An atlas of transcribed enhancers across helper T cell diversity for decoding human diseases
Oguchi, A., Suzuki, A., Komatsu, S., Yoshitomi, H., Bhagat, S., Son, R., Bonnal, R. J. P., Kojima, S., Koido, M., Takeuchi, K., et al. (2024) · Science · doi:10.1126/science.add8394 · Cited by 40
Han, Y., Hazelett, D. J., Wiklund, F. E., Schumacher, F. R., Stram, D. O., Berndt, S. I., Wang, Z., Rand, K. A., Hoover, R. N., Machiela, M. J., et al. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv269 · Cited by 40
DNase I hypersensitivity mapping, genomic footprinting, and transcription factor networks in plants
Sullivan, A. M., Bubb, K. L., Sandstrom, R. S., Stamatoyannopoulos, J. A., & Queitsch, C. (2015) · Current Plant Biology · doi:10.1016/j.cpb.2015.10.001 · Cited by 40
Self-citationChromatin remodeling effects on enhancer activity
García-González, E. G., Escamilla-Del-Arenal, M., Arzate‐Mejía, R. G., & Targa, F. R. (2016) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-016-2184-3 · Cited by 41
Qiu, Z., Li, R., Zhang, S., Wang, K., Xu, M., Li, J., Du, Y., Yu, H. J., & Cui, X. (2016) · Molecular Plant · doi:10.1016/j.molp.2016.05.013 · Cited by 40
Qu, Y., Siggens, L., Cordeddu, L., Gaidzik, V. I., Karlsson, K., Bullinger, L., Döhner, K., Ekwall, K., Lehmann, S., & Lennartsson, A. (2016) · Blood · doi:10.1182/blood-2016-07-726877 · Cited by 40
Lee, N., Park, S. J., Haddad, G., Kim, D., Park, S., Park, S. K., & Choi, K. Y. (2016) · Scientific Reports · doi:10.1038/srep39049 · Cited by 40
Algorithm for cellular reprogramming
Ronquist, S., Patterson, G., Muir, L. A., Lindsly, S., Chen, H., Brown, M. A., Wicha, M. S., Bloch, A. M., Brockett, R. W., & Rajapakse, I. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1712350114 · Cited by 40
Venkatesh, I., Mehra, V., Wang, Z., Callif, B. L., & Blackmore, M. G. (2018) · Developmental Neurobiology · doi:10.1002/dneu.22605 · Cited by 40
Nuclear compartmentalization, dynamics, and function of regulatory DNA sequences
Cremer, M., & Cremer, T. J. (2018) · Genes Chromosomes and Cancer · doi:10.1002/gcc.22714 · Cited by 40
Mocap: large-scale inference of transcription factor binding sites from chromatin accessibility
Chen, X. X., Yu, B., Carriero, N. J., Silva, C. T., & Bonneau, R. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx174 · Cited by 40
Ghosh, R. P., Shi, Q., Yang, L., Reddick, M. P., Tv, N., Zhurkin, V. B., Fordyce, P. M., Stasevich, T. J., Chang, H. Y., Greenleaf, W. J., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11118-8 · Cited by 40
Unique and assay specific features of NOMe-, ATAC- and DNase I-seq data
Nordström, K. J. V., Schmidt, F., Gasparoni, N., Salhab, A., Gasparoni, G., Kattler, K., Müller, F., Ebert, P., Costa, I. G., Pfeifer, N., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz799 · Cited by 40
Hemophilia B Leyden and once mysterious cis-regulatory mutations
Funnell, A. P. W., & Crossley, M. (2013) · Trends in Genetics · doi:10.1016/j.tig.2013.09.007 · Cited by 40
Sethi, I., Sinha, S., & Buck, M. J. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-1042 · Cited by 40
Adaptive Lasso and group-Lasso for functional Poisson regressionPreprint
Ivanoff, S., Picard, F., & Rivoirard, V. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1412.6966 · Cited by 40
Ma, Q., Srivastav, S. P., Gamez, S., Dayama, G., Feitosa-Suntheimer, F., Patterson, E. I., Johnson, R. M., Matson, E. M., Gold, A. S., Brackney, D. E., et al. (2021) · Genome Research · doi:10.1101/gr.265157.120 · Cited by 40
Cai, C., Wan, P., Wang, H., Cai, X. M., Wang, J., Chai, Z., Wang, J., Wang, H., Zhang, M., Yang, N., et al. (2023) · Cell Proliferation · doi:10.1111/cpr.13430 · Cited by 39
Self-citationEffects of supercoiling on enhancer–promoter contacts
Benedetti, F., Dorier, J., & Stasiak, A. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku759 · Cited by 39
High-dimensional genomic data bias correction and data integration using MANCIE
Zang, C., Wang, T., Deng, K., Li, B., Hu, S. S., Qin, Q., Xiao, T., Zhang, S., Meyer, C. A., He, H. H., et al. (2016) · Nature Communications · doi:10.1038/ncomms11305 · Cited by 39
Zhao, J., Zhao, Y., Wang, L., Zhang, J., Karnes, R. J., Kohli, M., Wang, G., & Huang, H. (2016) · Oncotarget · doi:10.18632/oncotarget.9535 · Cited by 41
Baerenfaller, K., Shu, H., Hirsch‐Hoffmann, M., Fütterer, J., Opitz, L., Rehrauer, H., Hennig, L., & Gruissem, W. (2016) · Plant Cell & Environment · doi:10.1111/pce.12811 · Cited by 39
The origins of developmental gene regulation
Arenas‐Mena, C. (2017) · Evolution & Development · doi:10.1111/ede.12217 · Cited by 39
Dechassa, M. L., Tryndyak, V., de Conti, A., Xiao, W., Beland, F. A., & Pogribny, I. P. (2018) · Molecular Carcinogenesis · doi:10.1002/mc.22818 · Cited by 39
Shashikant, T., Khor, J. M., & Ettensohn, C. A. (2018) · BMC Genomics · doi:10.1186/s12864-018-4542-z · Cited by 39
Fu, S., Wang, Q., Moore, J. E., Purcaro, M. J., Pratt, H., Fan, K., Gu, C., Jiang, C., Zhu, R., Kundaje, A. B., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky753 · Cited by 39
From Genotype to Phenotype: Through Chromatin
Romanowska, J., & Joshi, A. (2019) · Genes · doi:10.3390/genes10020076 · Cited by 39
Guo, Y., & Gifford, D. K. (2017) · BMC Genomics · doi:10.1186/s12864-016-3434-3 · Cited by 39
Whole genome sequencing and rare variant analysis in essential tremor families
Odgerel, Z., Sonti, S., Hernandez, N. C., Park, J., Ottman, R., Louis, E. D., & Clark, L. N. (2019) · PLoS ONE · doi:10.1371/journal.pone.0220512 · Cited by 39
From Genetic Association to Molecular Mechanisms for Islet-cell Dysfunction in Type 2 Diabetes
Mattis, K. K., & Gloyn, A. L. (2020) · Journal of Molecular Biology · doi:10.1016/j.jmb.2019.12.045 · Cited by 39
Laboratory methods to decipher epigenetic signatures: a comparative review
Halabian, R., Arshad, V., Ahmadi, A., Saeedi, P., Jamalkandi, S. A., & Alivand, M. R. (2021) · Cellular & Molecular Biology Letters · doi:10.1186/s11658-021-00290-9 · Cited by 39
Inoue, K., & Imai, Y. (2014) · Journal of Bone and Mineral Research · doi:10.1002/jbmr.2229 · Cited by 39
Oppermann, U. C. T. (2013) · Arthritis Research & Therapy · doi:10.1186/ar4186 · Cited by 39
Tuteja, G., Chung, T. R., & Bejerano, G. (2015) · Placenta · doi:10.1016/j.placenta.2015.11.001 · Cited by 39
Integrated epigenomic analysis stratifies chromatin remodellers into distinct functional groups
Giles, K. A., Gould, C. M., Du, Q., Skvortsova, K., Song, J. Z., Maddugoda, M. P., Achinger-Kawecka, J., Stirzaker, C., Clark, S. J., & Taberlay, P. C. (2019) · Epigenetics & Chromatin · doi:10.1186/s13072-019-0258-9 · Cited by 39
Enhancer-associated RNAs as therapeutic targets
Léveillé, N., Melo, C. A., & Agami, R. (2015) · Expert Opinion on Biological Therapy · doi:10.1517/14712598.2015.1029452 · Cited by 38
Göttgens, E., Span, P. N., & Zegers, M. M. (2016) · International review of cytology · doi:10.1016/bs.ircmb.2016.06.003 · Cited by 38
Scherrer, K. (2018) · Experimental Cell Research · doi:10.1016/j.yexcr.2018.09.011 · Cited by 38
Zhang, J., & Sun, H. (2020) · Hypertension Research · doi:10.1038/s41440-020-00553-6 · Cited by 38
Meléndez-Ramírez, C., Durán, R. C., Barrios‐García, T., Giacoman-Lozano, M., López-Ornelas, A., Herrera-Gamboa, J. G., Estudillo, E., Soto‐Reyes, E., Velasco, I., & Treviño, V. (2021) · Scientific Reports · doi:10.1038/s41598-021-96263-1 · Cited by 38
Melchiotti, R., Puan, K. J., Andiappan, A. K., Poh, T. Y., Starke, M., Li, Z., Petsch, K., Lai, T. S., Chew, F. T., Larbi, A., et al. (2014) · BMC Medical Genetics · doi:10.1186/1471-2350-15-73 · Cited by 38
Gheldof, N., Witwicki, R. M., Migliavacca, E., Leleu, M., Didelot, G., Harewood, L., Rougemont, J., & Reymond, A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0079973 · Cited by 38
Morin, A., Kwan, T., Ge, B., Létourneau, L., Ban, M., Tandre, K., Caron, M., Sandling, J. K., Carlsson, J., Bourque, G., et al. (2016) · BMC Medical Genomics · doi:10.1186/s12920-016-0220-7 · Cited by 38
Enhancing Pluripotency and Lineage Specification
Xie, W., & Ren, B. (2013) · Science · doi:10.1126/science.1236254 · Cited by 38
Sheffield, N. C., & Furey, T. S. (2012) · Genes · doi:10.3390/genes3040651 · Cited by 37
Self-citationRaj, A., Shim, H., Gilad, Y., Pritchard, J. K., & Stephens, M. (2015) · PLoS ONE · doi:10.1371/journal.pone.0138030 · Cited by 37
Lennartsson, A., Arner, E., Fagiolini, M., Saxena, A., Andersson, R., Takahashi, H., Noro, Y., Sng, J., Sandelin, A., Hensch, T. K., et al. (2015) · Epigenetics & Chromatin · doi:10.1186/s13072-015-0043-3 · Cited by 37
Manichaikul, A. W., Wang, X., Zhao, W., Wojczynski, M. K., Siebenthall, K. T., Stamatoyannopoulos, J. A., Saleheen, D., Borecki, I. B., Reilly, M. P., Rich, S. S., et al. (2015) · Journal of Lipid Research · doi:10.1194/jlr.m064592 · Cited by 37
Self-citationSteering Against Wind: A New Network of NamiRNAs and Enhancers
Liang, Y. J., Zou, Q., & Yu, W. (2017) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2017.05.001 · Cited by 39
Analysis of chromatin accessibility in decidualizing human endometrial stromal cells
Vrljicak, P., Lucas, E. S., Lansdowne, L., Lucciola, R., Muter, J., Dyer, N. P., Brosens, J. J., & Ott, S. (2017) · The FASEB Journal · doi:10.1096/fj.201701098r · Cited by 37
Zhang, Y., Manjunath, M., Zhang, S., Chasman, D. A., Roy, S., & Song, J. S. (2018) · Cancer Research · doi:10.1158/0008-5472.can-17-3486 · Cited by 37
Altered nuclear envelope structure and proteasome function of micronuclei
Maaß, K. K., Rosing, F., Ronchi, P., Willmund, K. V., Devens, F., Hergt, M., Herrmann, H. O., Lichter, P., & Ernst, A. (2018) · Experimental Cell Research · doi:10.1016/j.yexcr.2018.08.029 · Cited by 37
Metadata
- Authors
- Thurman, R. E., Rynes, E., Humbert, R., Vierstra, J., Maurano, M. T., Haugen, E., Sheffield, N. C., Stergachis, A. B., Wang, H., Vernot, B., Garg, K., John, S., Sandstrom, R., Bates, D., Boatman, L., Canfield, T. K., Diegel, M., Dunn, D., Ebersol, A. K., Frum, T., Giste, E., Johnson, A. K., Johnson, E. M., Kutyavin, T., Lajoie, B., Lee, B.-K., Lee, K., London, D., Lotakis, D., Neph, S., Neri, F., Nguyen, E. D., Qu, H., Reynolds, A. P., Roach, V., Safi, A., Sanchez, M. E., Sanyal, A., Shafer, A., Simon, J. M., Song, L., Vong, S., Weaver, M., Yan, Y., Zhang, Z., Zhang, Z., Lenhard, B., Tewari, M., Dorschner, M. O., Hansen, R. S., Navas, P. A., Stamatoyannopoulos, G., Iyer, V. R., Lieb, J. D., Sunyaev, S. R., Akey, J. M., Sabo, P. J., Kaul, R., Furey, T. S., Dekker, J., Crawford, G. E., & Stamatoyannopoulos, J. A.
- Affiliations
- University of Washington (US)
- Duke University (US)
- Cape Town HVTN Immunology Laboratory / Hutchinson Centre Research Institute of South Africa (ZA)
- University of Massachusetts Chan Medical School (US)
- The University of Texas at Austin (US)
- Chinese Academy of Sciences (CN)
- University of North Carolina at Chapel Hill (US)
- University of Bergen (NO)
- Brigham and Women's Hospital (US)
- Corresponding author
- Stamatoyannopoulos, John A.
- ORCID
- Rynes, Eric
- Vierstra, Jeff
- Maurano, Matthew T.
- Haugen, Eric
- Sheffield, Nathan C.
- Stergachis, Andrew B.
- Vernot, Benjamin
- Garg, Kavita
- Sandstrom, Richard
- Bates, Daniel
- Frum, Tristan
- Lajoie, Bryan
- Lee, Bum-Kyu
- Lee, Kristen
- Lotakis, Dimitra
- Neph, Shane
- Qu, Hongzhu
- Reynolds, Alex P.
- Safi, Alexias
- Sanyal, Amartya
- Simon, Jeremy M.
- Song, Lingyun
- Zhang, Zhancheng
- Zhang, Zhuzhu
- Lenhard, Boris
- Tewari, Muneesh
- Iyer, Vishwanath R.
- Sunyaev, Shamil R.
- Akey, Joshua M.
- Sabo, Peter J.
- Kaul, Rajinder
- Furey, Terrence S.
- Dekker, Job
- Crawford, Gregory E.
- Stamatoyannopoulos, John A.
- Venue
- Nature
- Published
- 2012-09
- Volume
- 489
- Issue
- 7414
- Pages
- 75-82
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3721348
- OpenAlex
- W1964963969
- Cited by
- 2,679
- References
- 38
- Citations by year
- 2026: 81 · 2025: 97 · 2024: 119 · 2023: 140 · 2022: 170 · 2021: 218 · 2020: 192 · 2019: 199 · 2018: 227 · 2017: 238 · 2016: 238 · 2015: 247 · 2014: 242 · 2013: 235 · 2012: 31
- FWCI
- 96.99
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- UNC Libraries
- Funders
- National Science Foundation (HHSN261200800001E, DGE-0-718124, 0718124)
- Norges Forskningsråd
- National Institutes of Health (#HHSN261200800001E, 5u54hg004563-04, HG004563)
- National Institute of Mental Health (R01MH084676)
- National Human Genome Research Institute (U54‑HG004563, U54HG004592, HG004592, HG004563, R01HG003143)
- National Cancer Institute (HHSN261200800001E), P30CA016086)
- National Institute of General Medical Sciences (R01GM076036, GM076036)
- National Institute of Diabetes and Digestive and Kidney Diseases (F30DK095678)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Keywords
- DNase I hypersensitive sites, chromatin accessibility, cis-regulatory elements, enhancers, promoter, insulators, silencers, locus control region, cell type-specific gene regulation, DNA methylation, transcription factor occupancy, evolutionary constraints, mutation rate, pluripotent cells, human diversity, ENCODE
- MeSH terms
- Chromatin, Deoxyribonuclease I, DNA, DNA-Binding Proteins, Encyclopedias as Topic, Humans, Promoter Regions, Genetic, Regulatory Sequences, Nucleic Acid, Transcription Factors, Transcription, Genetic, Genome, Human, DNA Footprinting, Evolution, Molecular, DNA Methylation, Genomics, Transcription Initiation Site, Molecular Sequence Annotation, Mutation Rate
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
