The DOI matches its Crossref record; 66 of the 67 references it cites were found in a registry or an index.
Mapping and analysis of chromatin state dynamics in nine human cell types
Open accessAbstract
Chromatin profiling has emerged as a powerful means of genome annotation and detection of regulatory activity. The approach is especially well suited to the characterization of non-coding portions of the genome, which critically contribute to cellular phenotypes yet remain largely uncharted. Here we map nine chromatin marks across nine cell types to systematically characterize regulatory elements, their cell-type specificities and their functional interactions. Focusing on cell-type-specific patterns of promoters and enhancers, we define multicell activity profiles for chromatin state, gene expression, regulatory motif enrichment and regulator expression. We use correlations between these profiles to link enhancers to putative target genes, and predict the cell-type-specific activators and repressors that modulate them. The resulting annotations and regulatory predictions have implications for the interpretation of genome-wide association studies. Top-scoring disease single nucleotide polymorphisms are frequently positioned within enhancer elements specifically active in relevant cell types, and in some cases affect a motif instance for a predicted regulator, thus suggesting a mechanism for the association. Our study presents a general framework for deciphering cis-regulatory connections and their roles in disease.
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
“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 [135]
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
“Currently mono-methylation of histone H3 lysine 4 (H3K4me1), associated with the binding of Trithorax/MLL complexes, is taken to be the hallmark of both ‘primed’ and active enhancers, whilst active enhancers additionally tend to associate with the acetylation of histone H3 lysine 27 (H3K27ac) [133–137].”
From Transcriptional enhancers and their communication with gene promoters (2021) · cites this paper as [134]
Experimental — accuracy not yet measuredIn the citing paper
“ChIPseq using antibodies to H3K4Me3, a mark associated with active promoter sites (Ernst et al., 2011), and to H3K27Ac, a mark associated with enhancer elements (Heintzman et al., 2009), demonstrated mapped read peaks corresponding to at least four major transcriptional start sites within the SYNE1 locus (P1–P4), one of which (P3) lies immediately upstream of the p.L3206M mutation (Figure 3E).”
From Using Whole-Exome Sequencing to Identify Inherited Causes of Autism (2013) · cites this paper as Ernst et al., 2011
In the citing paper
“This mystery, which we will call the enhancer-gene specificity conundrum, is important to solve because the majority of disease-associated non-coding variation occurs in the vicinity of enhancers and thus likely impacts these enhancers’ target genes (Ernst et al., 2011; Farh et al., 2015; Hnisz et al., 2013; Maurano et al., 2012).”
From Insulated Neighborhoods: Structural and Functional Units of Mammalian Gene Control (2016) · cites this paper as Ernst et al., 2011
In the citing paper
“Tens of thousands of non-coding genetic variants have been linked with various human diseases and traits in genome-wide association studies (GWAS), and the majority of these variants occur in enhancers (Ernst et al., 2011; Farh et al., 2015; Hnisz et al., 2013; Maurano et al., 2012).”
From Insulated Neighborhoods: Structural and Functional Units of Mammalian Gene Control (2016) · cites this paper as Ernst et al., 2011
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
Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206
The Human Genome Browser at UCSC
Kent, W. J., Sugnet, C. W., Furey, T. S., Roskin, K. M., Pringle, T. H., Zahler, A. M., & Haussler, A. D. (2002) · Genome Research · doi:10.1101/gr.229102 · Cited by 10,400
High-Resolution Profiling of Histone Methylations in the Human Genome
Barski, A., Cuddapah, S., Cui, K., Roh, T.-Y., Schones, D. E., Wang, Z., Wei, G., Chepelev, I., & Zhao, K. (2007) · Cell · doi:10.1016/j.cell.2007.05.009 · Cited by 6,845
A bivalent chromatin structure marks key developmental genes in embryonic stem cells
Bernstein, B. E., Mikkelsen, T. S., Xie, X., Kamal, M., Huebert, D. J., Cuff, J., Fry, B., Meissner, A., Wernig, M., Plath, K., et al. (2006) · Cell · doi:10.1016/j.cell.2006.02.041 · Cited by 5,361
Self-citationThe ENCODE Project Consortium (2007) · Nature · doi:10.1038/nature05874 · Cited by 5,223
Self-citationPruitt, K. D., Tatusova, T. A., & Maglott, D. R. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl842 · Cited by 4,441
Genome-wide maps of chromatin state in pluripotent and lineage-committed cells
Mikkelsen, T. S., Ku, M., Jaffe, D. B., Issac, B., Lieberman, E., Giannoukos, G., Alvarez, P., Brockman, W., Kim, T.-K., Koche, R. P., et al. (2007) · Nature · doi:10.1038/nature06008 · Cited by 4,129
Self-citationHindorff, 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
Evolutionarily conserved elements in vertebrate, insect, worm, and yeast genomes
Siepel, A., Bejerano, G., Pedersen, J. S., Hinrichs, A. S., Hou, M., Rosenbloom, K., Clawson, H., Spieth, J., Hillier, L. W., Richards, S., et al. (2005) · Genome Research · doi:10.1101/gr.3715005 · Cited by 3,971 · cited 1×
“We used annotations obtained through the UCSC Genome Browser 54 for RefSeq TSSs and transcribed regions 55 , PhastCons 56 , DNase-seq for K562 cells 12 , c-Myc ChIP-seq for K562 cells 13 , NF-κ B ChIP-seq for GM12878 14 , Oct4 in ES cells 24 and nuclear lamina 15 .”
Biological, clinical and population relevance of 95 loci for blood lipids
Teslovich, T. M., Musunuru, K., Smith, A. V., Edmondson, A. C., Stylianou, I. M., Koseki, M., Pirruccello, J. P., Ripatti, S., Chasman, D. I., Willer, C. J., et al. (2010) · Nature · doi:10.1038/nature09270 · Cited by 3,487
Cited by
Sorted by citations
Items 301–400 of 1,013
The reference epigenome and regulatory chromatin landscape of chronic lymphocytic leukemia
Beekman, R., Chapaprieta, V., Russiñol, N., Vilarrasa‐Blasi, R., Verdaguer-Dot, N., Martens, J. H. A., Duran‐Ferrer, M., Kulis, M., Serra, F., Javierre, B. M., et al. (2018) · Nature Medicine · doi:10.1038/s41591-018-0028-4 · Cited by 196
Genome-wide kinetics of DNA excision repair in relation to chromatin state and mutagenesis
Adar, S., Hu, J., Lieb, J. D., & Sancar, A. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1603388113 · Cited by 195
Cui, X., Lu, F., Qiu, Q., Zhou, B., Gu, L., Zhang, S., Kang, Y., Cui, X., Ma, X., Yao, Q., et al. (2016) · Nature Genetics · doi:10.1038/ng.3556 · Cited by 194
Self-citationMiotto, B., Ji, Z., & Struhl, K. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1609060113 · Cited by 194
ZNF143 provides sequence specificity to secure chromatin interactions at gene promoters
Bailey, S. D., Zhang, X., Desai, K., Aid, M., Corradin, O., Cowper-Sal·lari, R., Akhtar-Zaidi, B., Scacheri, P. C., Haibe-Kains, B., & Lupien, M. (2015) · Nature Communications · doi:10.1038/ncomms7186 · Cited by 194
Self-citationStirzaker, C., Zotenko, E., Song, J. Z., Qu, W., Nair, S. S., Locke, W. J., Stone, A. M., Armstong, N. J., Robinson, M. D., Dobrovic, A., et al. (2015) · Nature Communications · doi:10.1038/ncomms6899 · Cited by 193
Hatzi, K., Jiang, Y., Huang, C., Garrett-Bakelman, F. E., Gearhart, M. D., Γιαννοπούλου, Ε., Zumbo, P., Kirouac, K. N., Bhaskara, S., Polo, J. M., et al. (2013) · Cell Reports · doi:10.1016/j.celrep.2013.06.016 · Cited by 193
Dissecting the regulatory architecture of gene expression QTLs
Gaffney, D. J., Veyrieras, J., Degner, J. F., Piqué-Regi, R., Pai, A. A., Crawford, G. E., Stephens, M., Gilad, Y., & Pritchard, J. K. (2012) · Genome biology · doi:10.1186/gb-2012-13-1-r7 · Cited by 194
The NIH Roadmap Epigenomics Program data Resource
Chadwick, L. H. (2012) · Epigenomics · doi:10.2217/epi.12.18 · Cited by 193
Inferring regulatory element landscapes and transcription factor networks from cancer methylomes
Yao, L., Shen, H., Laird, P. W., Farnham, P., & Berman, B. P. (2015) · Genome biology · doi:10.1186/s13059-015-0668-3 · Cited by 193
Comprehensive epigenetic landscape of rheumatoid arthritis fibroblast-like synoviocytes
Ai, R., Laragione, T., Hammaker, D. R., Boyle, D. L., Wildberg, A., Maeshima, K., Palescandolo, E., Krishna, V., Pocalyko, D. J., Whitaker, J. W., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-04310-9 · Cited by 193
vel Szic, K. S., Declerck, K., Vidaković, M., & Vanden Berghe, W. (2015) · Clinical Epigenetics · doi:10.1186/s13148-015-0068-2 · Cited by 192
Zhang, J., Jackson, A. F., Naito, T., Dose, M., Seavitt, J. R., Liu, F., Heller, E. J., Kashiwagi, M., Yoshida, T., Gounari, F., et al. (2011) · Nature Immunology · doi:10.1038/ni.2150 · Cited by 191
The vitamin D receptor: contemporary genomic approaches reveal new basic and translational insights
Pike, J. W., Meyer, M. B., Lee, S.-M., Onal, M., & Benkusky, N. A. (2017) · Journal of Clinical Investigation · doi:10.1172/jci88887 · Cited by 193
Hannon, E. J., Gorrie-Stone, T. J., Smart, M., Burrage, J., Hughes, A., Bao, Y., Meena Kumari, B., Schalkwyk, L. C., & Mill, J. S. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2018.09.007 · Cited by 191
Leveraging Functional-Annotation Data in Trans-ethnic Fine-Mapping Studies
Kichaev, G., & Paşaniuc, B. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.06.007 · Cited by 188
Ron, G., Globerson, Y., Moran, D., & Kaplan, T. (2017) · Nature Communications · doi:10.1038/s41467-017-02386-3 · Cited by 188
An Interactive Database for the Assessment of Histone Antibody Specificity
Rothbart, S. B., Dickson, B. M., Raab, J. R., Grzybowski, A. T., Krajewski, K., Guo, A. H., Shanle, E. K., Josefowicz, S. Z., Fuchs, S. M., Allis, C. D., et al. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.06.022 · Cited by 187
Magnani, L., Stoeck, A., Zhang, X., Lánczky, A., Mirabella, A., Wang, T., Győrffy, B., & Lupien, M. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1219992110 · Cited by 187
Self-citationTaberlay, P. C., Statham, A. L., Kelly, T. K., Clark, S. J., & Jones, P. A. (2014) · Genome Research · doi:10.1101/gr.163485.113 · Cited by 186
Epigenetics in Adipose Tissue, Obesity, Weight Loss, and Diabetes
Martínez, J. A., Milagro, F. I., Claycombe, K., & Schalinske, K. L. (2014) · Advances in Nutrition · doi:10.3945/an.113.004705 · Cited by 185
Brackley, C. A., Johnson, J., Kelly, S. L., Cook, P. R., & Marenduzzo, D. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw135 · Cited by 185
Léveillé, N., Melo, C. A., Rooijers, K., Díaz-Lagares, A., Melo, S. A., Korkmaz, G., Lopes, R., Moqadam, F. A., Maia, A. R., Wijchers, P. J., et al. (2015) · Nature Communications · doi:10.1038/ncomms7520 · Cited by 183
Deep-coverage whole genome sequences and blood lipids among 16,324 individuals
Natarajan, P., Peloso, G. M., Zekavat, S. M., Montasser, M. E., Ganna, A., Chaffin, M. D., Khera, A. V., Zhou, W., Bloom, J. M., Engreitz, J., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05747-8 · Cited by 183
Self-citationSystematic identification of silencers in human cells
Pang, B., & Snyder, M. P. (2020) · Nature Genetics · doi:10.1038/s41588-020-0578-5 · Cited by 183
DBTSS: DataBase of Transcriptional Start Sites progress report in 2012
Yamashita, R., Sugano, S., Suzuki, Y., & Nakai, K. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1005 · Cited by 182
Combining SNP-to-gene linking strategies to identify disease genes and assess disease omnigenicity
Gazal, S., Weissbrod, O., Hormozdiari, F., Dey, K. K., Nasser, J., Jagadeesh, K. A., Weiner, D. J., Shi, H., Fulco, C. P., O’Connor, L. J., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01087-y · Cited by 181
Picard, F., Cadoret, J., Audit, B., Arnéodo, A., Alberti, A., Battail, C., Duret, L., & Prioleau, M. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004282 · Cited by 181
Brown, C. D., Mangravite, L. M., & Engelhardt, B. E. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003649 · Cited by 183
Role of Tet1 and 5-hydroxymethylcytosine in cocaine action
Feng, J., Shao, N., Szulwach, K. E., Vialou, V., Huynh, J. L., Zhong, C., Le, T. T., Ferguson, D., Cahill, M. E., Li, Y., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.3976 · Cited by 181
Distinct roles of cohesin-SA1 and cohesin-SA2 in 3D chromosome organization
Kojic, A., Cuadrado, A., Koninck, M. D., Giménez-Llorente, D., Rodríguez-Corsino, M., Goméz-López, G., Dily, F. L., Martí-Renom, M. A., & Losada, A. (2018) · Nature Structural & Molecular Biology · doi:10.1038/s41594-018-0070-4 · Cited by 183
Sex-chromosome dosage effects on gene expression in humans
Raznahan, A., Parikshak, N. N., Chandran, V., Blumenthal, J. D., Clasen, L. S., Alexander-Bloch, A. F., Zinn, A. R., Wangsa, D., Wise, J., Murphy, D. G. M., et al. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1802889115 · Cited by 179
Werner, M. S., & Ruthenburg, A. J. (2015) · Cell Reports · doi:10.1016/j.celrep.2015.07.033 · Cited by 180
Aberrant DNA methylation patterns of spermatozoa in men with unexplained infertility
Urdinguio, R. G., Bayón, G. F., Dmitrijeva, M., Toraño, E. G., Bravo, C., Fraga, M. F., Bassas, L., Larriba, S., & Fernández, A. F. (2015) · Human Reproduction · doi:10.1093/humrep/dev053 · Cited by 180
Epigenetic inactivation of the p53-induced long noncoding RNA TP53 target 1 in human cancer
Díaz‐Lagares, Á., Crujeiras, A. B., López-Serra, P., Soler, M., Setién, F., Goyal, A., Sandoval, J., Hashimoto, Y., Martínez‐Cardús, A., Gómez, A., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1608585113 · Cited by 179
Cancers with wrong HATs: the impact of acetylation
Di Cerbo, V., & Schneider, R. (2013) · Briefings in Functional Genomics · doi:10.1093/bfgp/els065 · Cited by 178
Enhancing GTEx by bridging the gaps between genotype, gene expression, and disease
eGTEx Project (2017) · Nature Genetics · doi:10.1038/ng.3969 · Cited by 179
Memories from the Polycomb Group Proteins
Lanzuolo, C., & Orlando, V. (2012) · Annual Review of Genetics · doi:10.1146/annurev-genet-110711-155603 · Cited by 176
Seumois, G., Chávez, L., Gerasimova, A. V., Lienhard, M., Omran, N., Kalinke, L., Vedanayagam, M., Ganesan, A. P. V., Chawla, A., Djukanović, R., et al. (2014) · Nature Immunology · doi:10.1038/ni.2937 · Cited by 175
Cerhan, J. R., Berndt, S. I., Vijai, J., Ghesquières, H., McKay, J., Wang, S., Wang, Z., Yeager, M., Conde, L., de Bakker, P. I. W., et al. (2014) · Nature Genetics · doi:10.1038/ng.3105 · Cited by 174
Reddy, T. E., Gertz, J., Pauli, F., Kucera, K. S., Varley, K. E., Newberry, K. M., Marinov, G. K., Mortazavi, A., Williams, B. A., Song, L., et al. (2012) · Genome Research · doi:10.1101/gr.131201.111 · Cited by 175
Tobi, E. W., Slieker, R. C., Stein, A. D., Suchiman, H. E. D., Slagboom, P. E., van Zwet, E. W., Heijmans, B. T., & Lumey, L. H. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv043 · Cited by 173
Siddiq, A., Couch, F. J., Chen, G. K., Lindström, S., Eccles, D., Millikan, R. C., Michailidou, K., Stram, D. O., Beckmann, L., Rhie, S. K., et al. (2012) · Human Molecular Genetics · doi:10.1093/hmg/dds381 · Cited by 173
AP-1 activity induced by co-stimulation is required for chromatin opening during T cell activation
Yukawa, M., Jagannathan, S., Vallabh, S., Kartashov, A. V., Chen, X., Weirauch, M. T., & Barski, A. (2019) · The Journal of Experimental Medicine · doi:10.1084/jem.20182009 · Cited by 173
Smoke-related DNA methylation changes in the etiology of human disease
Besingi, W., & Johansson, Å. (2013) · Human Molecular Genetics · doi:10.1093/hmg/ddt621 · Cited by 172
Polycomb-Repressed Genes Have Permissive Enhancers that Initiate Reprogramming
Taberlay, P. C., Kelly, T. K., Liu, C.-C., You, J. S., De Carvalho, D. D., Miranda, T. B., Zhou, X. J., Liang, G., & Jones, P. A. (2011) · Cell · doi:10.1016/j.cell.2011.10.040 · Cited by 171
Mechanisms underlying helper T-cell plasticity: Implications for immune-mediated disease
Hirahara, K., Poholek, A. C., Vahedi, G., Laurence, A. D. J., Kanno, Y., Milner, J. D., & O’Shea, J. J. (2013) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2013.03.015 · Cited by 171
Kaiser, M., Johnson, D. C., Wu, P., Walker, B. A., Brioli, A., Mirabella, F., Wardell, C. P., Melchor, L., Davies, F. E., & Morgan, G. J. (2013) · Blood · doi:10.1182/blood-2013-03-487884 · Cited by 171
Current insights into the C9orf72 repeat expansion diseases of the FTLD/ALS spectrum
Cruts, M., Gijselinck, I., Langenhove, T. V., van der Zee, J., & Broeckhoven, C. V. (2013) · Trends in Neurosciences · doi:10.1016/j.tins.2013.04.010 · Cited by 170
Epigenetic Regulation of Sensory Axon Regeneration after Spinal Cord Injury
Finelli, M. J., Wong, J. K., & Zou, H. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.0589-13.2013 · Cited by 169
A compendium and comparative epigenomics analysis of cis-regulatory elements in the pig genome
Zhao, Y., Hou, Y., Xu, Y., Luan, Y., Zhou, H., Qi, X., Hu, M., Wang, D., Wang, Z., Fu, Y., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-22448-x · Cited by 169
Transcriptional Regulation of Innate and Adaptive Lymphocyte Lineages
Obaldia, M. E. D., & Bhandoola, A. (2015) · Annual Review of Immunology · doi:10.1146/annurev-immunol-032414-112032 · Cited by 167
Evaluation of chromatin accessibility in prefrontal cortex of individuals with schizophrenia
Bryois, J., Garrett, M. E., Song, L., Safi, A., Giusti-Rodriguez, P., Johnson, G. D., Shieh, A. W., Buil, A., Fullard, J. F., Roussos, P., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05379-y · Cited by 167
Human tRNA genes function as chromatin insulators
Raab, J. R., Chiu, J., Zhu, J., Katzman, S. J., Kurukuti, S., Wade, P. A., Haussler, D. H., & Kamakaka, R. T. (2011) · The EMBO Journal · doi:10.1038/emboj.2011.406 · Cited by 166
The NF-κB Genomic Landscape in Lymphoblastoid B Cells
Zhao, B., Barrera, L. A., Ersing, I., Willox, B., Schmidt, S. C. S., Greenfeld, H., Zhou, H., Mollo, S. B., Shi, T. T., Takasaki, K., et al. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.07.037 · Cited by 165
Self-citationCui, J., Stahl, E. A., Saevarsdóttir, S., Miceli‐Richard, C., Diogo, D., Trynka, G., Raj, T., Mirkov, M. U., Canhão, H. M., Ikari, K., et al. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003394 · Cited by 165
McClay, J. L., Åberg, K. A., Clark, S. L., Nerella, S., Kumar, G., Xie, L. Y., Hudson, A. D., Harada, A., Hultman, C. M., Magnusson, P. K. E., et al. (2013) · Human Molecular Genetics · doi:10.1093/hmg/ddt511 · Cited by 165
Reorganization of chromosome architecture in replicative cellular senescence
Criscione, S. W., De Cecco, M., Siranosian, B., Zhang, Y., Kreiling, J. A., Sedivy, J. M., & Neretti, N. (2016) · Science Advances · doi:10.1126/sciadv.1500882 · Cited by 164
Transcriptional response to stress is pre-wired by promoter and enhancer architecture
Vihervaara, A., Mahat, D. B., Guertin, M. J., Chu, T., Danko, C. G., Lis, J. T., & Sistonen, L. (2017) · Nature Communications · doi:10.1038/s41467-017-00151-0 · Cited by 164
Shen, H., Fridley, B. L., Song, H., Lawrenson, K., Cunningham, J. M., Ramus, S. J., Cicek, M. S., Tyrer, J. P., Stram, D. A., Larson, M. C., et al. (2013) · Nature Communications · doi:10.1038/ncomms2629 · Cited by 164
Qiu, X., Boufaied, N., Hallal, T., Feit, A. S., de Polo, A., Luoma, A., Alahmadi, W., Larocque, J., Zadra, G., Xie, Y., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-30257-z · Cited by 171
Genome-scale high-resolution mapping of activating and repressive nucleotides in regulatory regions
Ernst, J., Melnikov, A., Zhang, X., Wang, L., Rogov, P., Mikkelsen, T. S., & Kellis, M. (2016) · Nature Biotechnology · doi:10.1038/nbt.3678 · Cited by 162
Self-citationChen, H., Tian, Y., Shu, W., Bo, X., & Wang, S. (2012) · PLoS ONE · doi:10.1371/journal.pone.0041374 · Cited by 161
Uniform, optimal signal processing of mapped deep-sequencing data
Kumar, V., Muratani, M., Rayan, N. A., Kraus, P., Lufkin, T., Ng, H., & Prabhakar, S. (2013) · Nature Biotechnology · doi:10.1038/nbt.2596 · Cited by 161
Lowe, R., Gemma, C., Beyan, H., Hawa, M. I., Bazeos, A., Leslie, R. D., Montpetit, A., Rakyan, V. K., & Ramagopalan, S. V. (2013) · Epigenetics · doi:10.4161/epi.24362 · Cited by 160
Cellular network entropy as the energy potential in Waddington's differentiation landscape
Banerji, C. R. S., Miranda-Saavedra, D., Simone Severini, B., Widschwendter, M., Enver, T., Zhou, J. X., & Teschendorff, A. E. (2013) · Scientific Reports · doi:10.1038/srep03039 · Cited by 160
Heyn, P. C., Logan, C. V., Fluteau, A., Challis, R. C., Auchynnikava, T., Martin, C.-A., Marsh, J. A., Taglini, F., Kilanowski, F. M., Parry, D. A., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0274-x · Cited by 160
Wang, X., He, L., Goggin, S. M., Saadat, A., Wang, L., Sinnott-Armstrong, N., Claussnitzer, M., & Kellis, M. (2018) · Nature Communications · doi:10.1038/s41467-018-07746-1 · Cited by 159
Self-citationKozlenkov, A., Roussos, P., Timashpolsky, A., Barbu, M., Rudchenko, S., Bibikova, M. V., Klotzle, B., Byne, W. M., Lyddon, R., Narzo, A. F. D., et al. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt838 · Cited by 159
Hu, X., Kim, H., Stahl, E. A., Plenge, R. M., Daly, M. J., & Raychaudhuri, S. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.09.002 · Cited by 159
High-throughput and quantitative assessment of enhancer activity in mammals by CapStarr-seq
Vanhille, L., Griffon, A., Maqbool, M. A., Zacarias-Cabeza, J., Dao, L. T. M., Fernandez, N., Ballester, B., Andrau, J. C., & Spicuglia, S. (2015) · Nature Communications · doi:10.1038/ncomms7905 · Cited by 158
Hilton, H. N., Clarke, C. L., & Graham, J. D. (2017) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2017.08.011 · Cited by 158
Bell, C. G., Gao, F., Yuan, W., Roos, L., Acton, R., Xia, Y., Bell, J. T., Ward, K. J., Mangino, M., Hysi, P. G., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-01586-1 · Cited by 157
Aberrant Super‐Enhancer Landscape in Human Hepatocellular Carcinoma
Tsang, F. H., Law, C., Tang, T. C. C., Cheng, C. L., Chin, D. W., Tam, V., Wei, L., Wong, C. C., Ng, I. O., & Wong, C. (2019) · Hepatology · doi:10.1002/hep.30544 · Cited by 157
Jaffe, A. E., Shin, J., Collado-Torres, L., Leek, J. T., Tao, R., Li, C., Gao, Y., Jia, Y., Maher, B. J., Hyde, T. M., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.3898 · Cited by 156
Integrating Diverse Datasets Improves Developmental Enhancer Prediction
Erwin, G. D., Oksenberg, N., Truty, R., Kostka, D., Murphy, K. K., Ahituv, N., Pollard, K. S., & Capra, J. A. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003677 · Cited by 156
Genetic Variation in Human DNA Replication Timing
Koren, A., Handsaker, R. E., Kamitaki, N., Karlić, R., Ghosh, S. D., Polak, P. P., Eggan, K. C., & McCarroll, S. A. (2014) · Cell · doi:10.1016/j.cell.2014.10.025 · Cited by 156
CTCF: insights into insulator function during development
Herold, M. V. B., Bartkuhn, M., & Renkawitz, R. (2012) · Development · doi:10.1242/dev.065268 · Cited by 155
Genome organization and long-range regulation of gene expression by enhancers
Smallwood, A., & Ren, B. (2013) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2013.02.005 · Cited by 155
Super-enhancer hypermutation alters oncogene expression in B cell lymphoma
Bal, É., Kumar, R., Hadigol, M., Holmes, A. B., Hilton, L. K., Loh, J. W., Dreval, K., Wong, J., Vlasevska, S., Corinaldesi, C., et al. (2022) · Nature · doi:10.1038/s41586-022-04906-8 · Cited by 155
Integrative epigenetic taxonomy of primary prostate cancer
Stelloo, S., Nevedomskaya, E., Kim, Y., Schuurman, K., Valle-Encinas, E., Lobo, J., Krijgsman, O., Peeper, D. S., Chang, S. L., Feng, F. Y.-C., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-07270-2 · Cited by 154
ICGC MMML-Seq project, Kretzmer, H., BLUEPRINT project, Bernhart, S. H., Wang, W., Haake, A., Weniger, M. A., Bergmann, A. K., Betts, M. J., Pau, E. C. D. S., et al. (2015) · Nature Genetics · doi:10.1038/ng.3413 · Cited by 154
AMP kinase promotes glioblastoma bioenergetics and tumour growth
Chhipa, R. R., Fan, Q., Anderson, J., Muraleedharan, R., Huang, Y., Ciraolo, G. M., Chen, X., Waclaw, R. R., Chow, L. M. L., Khuchua, Z. A., et al. (2018) · Nature Cell Biology · doi:10.1038/s41556-018-0126-z · Cited by 154
Agirre, X., Castellano, G., Pascual, M., Heath, S. C., Kulis, M., Segura, V., Bergmann, A. K., Esteve‐Codina, A., Merkel, A., Raineri, E., et al. (2015) · Genome Research · doi:10.1101/gr.180240.114 · Cited by 153
Genetic variant effects on gene expression in human pancreatic islets and their implications for T2D
Viñuela, A., Varshney, A., van de Bunt, M., Prasad, R. B., Asplund, O., Bennett, A., Boehnke, M., Brown, A. A., Erdos, M. R., Fadista, J., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18581-8 · Cited by 152
Schmidt, E. M., Zhang, J., Zhou, W., Chen, J., Mohlke, K. L., Chen, Y., & Willer, C. J. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv201 · Cited by 152
An encyclopedia of human enhancer–gene regulatory interactions
Gschwind, A. R., Mualim, K. S., Karbalayghareh, A., Sheth, M. U., Dey, K. K., Jagoda, E., Nurtdinov, R., Xi, W., Tan, A. S., Galante, J., et al. (2026) · Nature · doi:10.1038/s41586-026-10781-4 · Cited by 161
Self-citationMolecular mechanisms of retroviral integration site selection
Kvaratskhelia, M., Sharma, A., Larue, R. C., Serrao, E., & Engelman, A. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku769 · Cited by 150
Ruark, E., Seal, S., McDonald, H., Zhang, F., Elliot, A., Lau, K., Perdeaux, E. R., Rapley, E. A., Eeles, R. A., Peto, J., et al. (2013) · Nature Genetics · doi:10.1038/ng.2635 · Cited by 151
Stable Chromosome Condensation Revealed by Chromosome Conformation Capture
Eagen, K. P., Hartl, T. A., & Kornberg, R. D. (2015) · Cell · doi:10.1016/j.cell.2015.10.026 · Cited by 151
Interphase human chromosome exhibits out of equilibrium glassy dynamics
Shi, G., Liu, L., Hyeon, C., & Thirumalai, D. (2018) · Nature Communications · doi:10.1038/s41467-018-05606-6 · Cited by 150
Diverse epigenetic strategies interact to control epidermal differentiation
Mulder, K. W., Wang, X., Escriu, C., Ito, Y., Schwarz, R. F., Gillis, J., Sirokmány, G., Donati, G., Uribe‐Lewis, S., Pavlidis, P., et al. (2012) · Nature Cell Biology · doi:10.1038/ncb2520 · Cited by 149
Pleiotropic genes for metabolic syndrome and inflammation
Kraja, A. T., Chasman, D. I., North, K. E., Reiner, A. P., Yanek, L. R., Kilpeläinen, T. O., Smith, J. A., Dehghan, A., Dupuis, J., Johnson, A. D., et al. (2014) · Molecular Genetics and Metabolism · doi:10.1016/j.ymgme.2014.04.007 · Cited by 149
A quantitative atlas of histone modification signatures from human cancer cells
LeRoy, G., DiMaggio, P. A., Chan, E. Y., Zee, B. M., Blanco, M. A., Bryant, B. M., Flaniken, I. Z., Liu, S., Kang, Y., Trojer, P., et al. (2013) · Epigenetics & Chromatin · doi:10.1186/1756-8935-6-20 · Cited by 149
Identifying and functionally characterizing tissue-specific and ubiquitously expressed human lncRNAs
Jiang, C., Li, Y., Zhao, Z., Lu, J., Chen, H., Ding, N., Wang, G., Xu, J., & Li, X. (2016) · Oncotarget · doi:10.18632/oncotarget.6859 · Cited by 149
A Cohesin-Independent Role for NIPBL at Promoters Provides Insights in CdLS
Zuin, J., Franke, V., van IJcken, W. F. J., van der Sloot, A., Krantz, I. D., van der Reijden, M. I. J. A., Nakato, R., Lenhard, B., & Wendt, K. S. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004153 · Cited by 148
Comparative pan-cancer DNA methylation analysis reveals cancer common and specific patterns
Yang, X., Gao, L., & Zhang, S. (2016) · Briefings in Bioinformatics · doi:10.1093/bib/bbw063 · Cited by 147
Editing the Epigenome: Reshaping the Genomic Landscape
Holtzman, L., & Gersbach, C. A. (2018) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-083117-021632 · Cited by 147
Liquid–Liquid Phase Separation in ChromatinPreprint
Rippe, K. (2021) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a040683 · Cited by 147
Extensive conservation of ancient microsynteny across metazoans due to cis -regulatory constraints
Irimia, M., Tena, J. J., Alexis, M. S., Fernandez-Miñan, A., Maeso, I., Bogdanović, O., de la Calle-Mustienes, E., Roy, S. W., Gómez-Skarmeta, J. L., & Fraser, H. B. (2012) · Genome Research · doi:10.1101/gr.139725.112 · Cited by 146
Metadata
- Authors
- Ernst, J., Kheradpour, P., Mikkelsen, T. S., Shoresh, N., Ward, L. D., Epstein, C. B., Zhang, X., Wang, L., Issner, R., Coyne, M., Ku, M., Durham, T., Kellis, M., & Bernstein, B. E.
- Affiliations
- Broad Institute (US)
- Corresponding author
- Kellis, Manolis
- ORCID
- Venue
- Nature
- Published
- 2011-03-23
- Volume
- 473
- Issue
- 7345
- Pages
- 43-49
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3088773
- OpenAlex
- W2117792884
- Cited by
- 2,898
- References
- 67
- Citations by year
- 2026: 47 · 2025: 62 · 2024: 109 · 2023: 130 · 2022: 141 · 2021: 179 · 2020: 203 · 2019: 191 · 2018: 216 · 2017: 237 · 2016: 237 · 2015: 306 · 2014: 260 · 2013: 287 · 2012: 225
- FWCI
- 108.00
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DSpace@MIT (Massachusetts Institute of Technology) (submittedVersion, cc-by-nc-sa)
- eScholarship (California Digital Library) (submittedVersion)
- PubMed Central
- Funders
- Howard Hughes Medical Institute
- Broad Institute
- National Institutes of Health (5u54hg004570-04)
- National Human Genome Research Institute (RC1HG005334, U54-HG004570, R01HG004037)
- 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
- histone modifications, cell type-specific chromatin, enhancers, promoter, insulators, cis-regulatory elements, transcriptional activators and repressors, genome-wide association study, human cell types
- MeSH terms
- Binding Sites, Cell Line, Cell Physiological Phenomena, Cells, Cultured, Chromatin, Chromosome Mapping, Gene Expression Regulation, Humans, Promoter Regions, Genetic, Transcription Factors, Reproducibility of Results, Genome, Human, Cell Line, Tumor, Hep G2 Cells
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
