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Systematic Localization of Common Disease-Associated Variation in Regulatory DNA
Open accessAbstract
Predictions of Genetic Disease: Many genome-wide association studies (GWAS) have identified loci and variants associated with disease, but the ability to predict disease on the basis of these genetic variants remains small. Maurano et al. (p. 1190 ; see the Perspective by Schadt and Chang ; see the cover) characterize the location of GWAS variants in the genome with respect to their proximity to regulatory DNA [marked by deoxyribonuclease I (DNase I) hypersensitive sites] by tissue type, disease, and enrichments in physiologically relevant transcription factor binding sites and networks. They found many noncoding disease associations in regulatory DNA, indicating tissue and developmental-specific regulatory roles for many common genetic variants and thus enabling links to be made between gene regulation and adult-onset disease.
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“As the majority of schizophrenia-associated variants do not directly index coding changes affecting protein structure”
From DNA methylation meta-analysis reveals cellular alterations in psychosis and markers of treatment-resistant schizophrenia (2021) · cites this paper as Maurano et al., 2012
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“The second challenge is that the majority of MS risk variants appear to localise to gene regulatory regions, rather than coding sequence,55 and specifically to enhancer elements active in stimulated immune cell subsets.56”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [55]
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“It is now widely recognized that a major component of the heritability of nearly all common diseases partitions to these regions, and in particular to regions that have enhancer-like signatures in disease-relevant cell types65.”
From Towards a comprehensive catalogue of validated and target-linked human enhancers (2020) · cites this paper as [65]
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“Although most causal genetic variants for Mendelian disorders fall in protein-coding regions, the heritable component of common disease risk distributes largely to non-coding regions, and appears to be particularly enriched in enhancers that are specific to disease-relevant cell types.”
From Towards a comprehensive catalogue of validated and target-linked human enhancers (2020) · cites this paper as [65]
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“The importance of enhancer variation in human pathology has been further highlighted by genome-wide association studies (GWAS), since GWAS-detected genetic variants associated with complex traits and diseases are typically non-coding, non-promoter associated and highly enriched in enhancers [184, 208, 209].”
From Transcriptional enhancers and their communication with gene promoters (2021) · cites this paper as [209]
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“The vast majority of these disease-risk genetic variants are located in non-coding regions of the genome (5).”
From Brain cell type–specific enhancer–promoter interactome maps and disease - risk association (2019) · cites this paper as [5]
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“While the T cell component plays an important role, functional and epigenomic annotation studies have begun to suggest that other elements of the immune system may be involved as well.(7, 8)”
From Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility (2019) · cites this paper as [8]
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“Beyond impacting isoform composition through splicing modulation, non-coding variants can influence traits and cause diseases by altering gene expression23,24.”
From Advancing regulatory variant effect prediction with AlphaGenome (2026) · cites this paper as [24]
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“The majority of disease-associated genetic variation lies in non-coding regions (7) enriched for non-coding RNAs and cis regulatory elements that regulate gene expression and splicing of their cognate coding gene targets (8, 9).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [7]
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“Histone modifications can reliably be measured across the genome using chromatin immunoprecipitation followed by sequencing (ChIP-seq), while chromatin accessibility is typically measured by either DNase hypersensitivity analysis (DNase-seq) [168] or assay for transposase-accessible chromatin using sequencing”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [168]
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“A large portion of GWAS variants and even variants in high LD with the lead variant fall within non-coding regions of the genome, making their functional importance difficult to infer [168].”
From Genetic architecture of Alzheimer's disease (2020) · cites this paper as [168]
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“More than 90% of disease-associated SNVs (daSNVs) are localized in noncoding regions with unknown target genes40”
From Three-dimensional genome restructuring across timescales of activity-induced neuronal gene expression (2020) · cites this paper as [40]
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Citations
Cites
The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041
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
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
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
A map of human genome variation from population-scale sequencing.
The 1000 Genomes Project Consortium (2010) · Nature · doi:10.1038/nature09534 · Cited by 7,877
Common polygenic variation contributes to risk of schizophrenia and bipolar disorder
The International Schizophrenia Consortium (2009) · Nature · doi:10.1038/nature08185 · Cited by 4,821
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
Integrating common and rare genetic variation in diverse human populations
The International HapMap 3 Consortium (2010) · Nature · doi:10.1038/nature09298 · Cited by 3,026
King, M.-C., & Wilson, A. C. (1975) · Science · doi:10.1126/science.1090005 · Cited by 2,815
Fetal nutrition and cardiovascular disease in adult life
Barker, D. J. P., Godfrey, K. M., Gluckman, P. D., Harding, J. E., Owens, J. A., & Robinson, J. S. (1993) · The Lancet · doi:10.1016/0140-6736(93)91224-a · Cited by 2,753
Research works printed but not linked: 1
- A. V. Aho B. W. Kernighan P. J. Weinberger The AWK Programming Language (Addison Wesley Reading MA ed. 1 1988).
Cited by
Sorted by citations
Items 201–300 of 1,024
Rare variant association studies: considerations, challenges and opportunities
Auer, P. L., & Lettre, G. (2015) · Genome Medicine · doi:10.1186/s13073-015-0138-2 · Cited by 261
Gilsbach, R., Schwaderer, M., Preißl, S., Grüning, B. A., Kranzhöfer, D., Schneider, P., Nührenberg, T. G., Mulero‐Navarro, S., Weichenhan, D., Braun, C., et al. (2018) · Nature Communications · doi:10.1038/s41467-017-02762-z · Cited by 251
Enhancer Function: Mechanistic and Genome-Wide Insights Come Together
Plank, J. L., & Dean, A. (2014) · Molecular Cell · doi:10.1016/j.molcel.2014.06.015 · Cited by 263
RSAT 2015: Regulatory Sequence Analysis Tools
Medina-Rivera, A., Defrance, M., Sand, O., Herrmann, C., Castro-Mondragon, J. A., Delerce, J., Jaeger, S., Blanchet, C., Vincens, P., Caron, C., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv362 · Cited by 246
The formation and function of the cardiac conduction system
van Weerd, J. H., & Christoffels, V. M. (2016) · Development · doi:10.1242/dev.124883 · Cited by 256
Dynamic Rewiring of Promoter-Anchored Chromatin Loops during Adipocyte Differentiation
Siersbæk, R., Madsen, J. G. S., Javierre, B. M., Nielsen, R., Bagge, E. K., Cairns, J., Wingett, S. W., Traynor, S., Spivakov, M., Fraser, P., et al. (2017) · Molecular Cell · doi:10.1016/j.molcel.2017.04.010 · Cited by 243
Dissecting super-enhancer hierarchy based on chromatin interactions
Huang, J., Li, K., Cai, W., Liu, X., Zhang, Y., Orkin, S. H., Xu, J., & Yuan, G.-C. (2018) · Nature Communications · doi:10.1038/s41467-018-03279-9 · Cited by 241
Enhancer variants: evaluating functions in common disease
Corradin, O., & Scacheri, P. C. (2014) · Genome Medicine · doi:10.1186/s13073-014-0085-3 · Cited by 241
Enhancer redundancy in development and disease
Kvon, E. Z., Waymack, R., Gad, M., & Wunderlich, Z. (2021) · Nature Reviews Genetics · doi:10.1038/s41576-020-00311-x · Cited by 247
Jagadeesh, K. A., Dey, K. K., Montoro, D. T., Mohan, R., Gazal, S., Engreitz, J. M., Xavier, R. J., Price, A. L., & Regev, A. (2022) · Nature Genetics · doi:10.1038/s41588-022-01187-9 · Cited by 239
Hrdličková, B., de Almeida, R. C., Borek, Z., & Withoff, S. (2014) · Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease · doi:10.1016/j.bbadis.2014.03.011 · Cited by 239
lncRNAs: Insights into their function and mechanics in underlying disorders
Li, X., Wu, Z., Fu, X., & Han, W. (2014) · Mutation Research/Reviews in Mutation Research · doi:10.1016/j.mrrev.2014.04.002 · Cited by 233
Slieker, R. C., Bos, S. D., Goeman, J. J., Bovée, J. V. M. G., Talens, R. P., van der Breggen, R., Suchiman, H. E. D., Lameijer, E.-W., Putter, H., van den Akker, E. B., et al. (2013) · Epigenetics & Chromatin · doi:10.1186/1756-8935-6-26 · Cited by 234
Modulation of long noncoding RNAs by risk SNPs underlying genetic predispositions to prostate cancer
Guo, H., Ahmed, M., Zhang, F., Yao, C. Q., Li, S., Liang, Y., Hua, J., Soares, F., Sun, Y., Langstein, J., et al. (2016) · Nature Genetics · doi:10.1038/ng.3637 · Cited by 226
Exome Sequencing: Current and Future Perspectives
Warr, A., Robert, C., Hume, D. A., Archibald, A. L., Deeb, N., & Watson, M. (2015) · G3 Genes Genomes Genetics · doi:10.1534/g3.115.018564 · Cited by 226
In pursuit of design principles of regulatory sequences
Levo, M., & Segal, E. (2014) · Nature Reviews Genetics · doi:10.1038/nrg3684 · Cited by 215
de la Fuente Revenga, M., Zhu, B., Guevara, C. A., Naler, L. B., Saunders, J. M., Zhou, Z., Toneatti, R., Sierra, S., Wolstenholme, J. T., Beardsley, P. M., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.109836 · Cited by 224
The road to precision psychiatry: translating genetics into disease mechanisms
Gandal, M. J., Leppa, V., Won, H., Parikshak, N. N., & Geschwind, D. H. (2016) · Nature Neuroscience · doi:10.1038/nn.4409 · Cited by 223
DeepC: predicting 3D genome folding using megabase-scale transfer learning
Schweßinger, R., Gosden, M. E., Downes, D. J., Brown, R. C., Oudelaar, A. M., Telenius, J. M., Teh, Y. W., Lunter, G. A., & Hughes, J. R. (2020) · Nature Methods · doi:10.1038/s41592-020-0960-3 · Cited by 223
Modeling the specificity of protein‐DNA interactions
Stormo, G. D. (2013) · Quantitative Biology · doi:10.1007/s40484-013-0012-4 · Cited by 221
The human lncRNA LINC-PINT inhibits tumor cell invasion through a highly conserved sequence element
Marín-Béjar, O., Mas, A. M., González, J., Martínez, D., Athie, A., Morales, X., Galduroz, M., Raimondi, I., Grossi, E., Guo, S., et al. (2017) · Genome biology · doi:10.1186/s13059-017-1331-y · Cited by 223
A large-scale screen for coding variants predisposing to psoriasis
Tang, H., Jin, X., Li, Y., Jiang, H., Tang, X., Yang, X., Cheng, H., Qiu, Y., Chen, G., Mei, J., et al. (2013) · Nature Genetics · doi:10.1038/ng.2827 · Cited by 219
Pan, Z., Yao, Y., Yin, H. H., Cai, Z., Wang, Y., Bai, L., Kern, C., Halstead, M. M., Chanthavixay, G., Trakooljul, N., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26153-7 · Cited by 214
He, H. H., Meyer, C. A., Hu, S. S., Chen, M.-W., Zang, C., Liu, Y., Rao, P. K., Fei, T., Xu, H., Long, H., et al. (2014) · Nature Methods · doi:10.1038/nmeth.2762 · Cited by 218
Chromatin three-dimensional interactions mediate genetic effects on gene expression
Delaneau, O., Zazhytska, M., Borel, C., Giannuzzi, G., Rey, G., Howald, C., Kumar, S., Ongen, H., Popadin, K. Y., Marbach, D., et al. (2019) · Science · doi:10.1126/science.aat8266 · Cited by 212
Abascal, F., Acosta, R., Addleman, N. J., Adrian, J., Afzal, V., Aken, B. L., Ai, R., Akiyama, J. A., Jammal, O. A., Amrhein, H., et al. (2020) · Nature · doi:10.1038/s41586-020-2449-8 · Cited by 225
Self-citationSingle-cell eQTL models reveal dynamic T cell state dependence of disease loci
Nathan, A., Asgari, S., Ishigaki, K., Valencia, C., Amariuta, T., Luo, Y., Beynor, J. I., Baglaenko, Y., Suliman, S., Price, A. L., et al. (2022) · Nature · doi:10.1038/s41586-022-04713-1 · Cited by 221
Integrating rare genetic variants into pharmacogenetic drug response predictions
Ingelman‐Sundberg, M., Mkrtchian, S., Zhou, Y., & Lauschke, V. M. (2018) · Human Genomics · doi:10.1186/s40246-018-0157-3 · Cited by 220
Population Variation and Genetic Control of Modular Chromatin Architecture in Humans
Waszak, S. M., Delaneau, O., Gschwind, A. R., Kilpinen, H., Raghav, S. K., Witwicki, R. M., Orioli, A., Wiederkehr, M., Panousis, N. I., Yurovsky, A., et al. (2015) · Cell · doi:10.1016/j.cell.2015.08.001 · Cited by 214
Maurano, M. T., Haugen, E., Sandstrom, R. S., Vierstra, J. D., Shafer, A., Kaul, R., & Stamatoyannopoulos, J. A. (2015) · Nature Genetics · doi:10.1038/ng.3432 · Cited by 220
Self-citationLi, J., Cai, T., Jiang, Y. W., Chen, H., He, X., Chen, C., Li, X., Shao, Q., Xia, R., Li, Z., et al. (2015) · Molecular Psychiatry · doi:10.1038/mp.2015.40 · Cited by 212
HBS1L-MYB intergenic variants modulate fetal hemoglobin via long-range MYB enhancers
Stadhouders, R., Aktuna, S., Thongjuea, S., Aghajanirefah, A., Pourfarzad, F., van IJcken, W. F. J., Lenhard, B., Rooks, H., Best, S., Menzel, S., et al. (2014) · Journal of Clinical Investigation · doi:10.1172/jci71520 · Cited by 214
Catarino, R. R., & Stark, A. (2018) · Genes & Development · doi:10.1101/gad.310367.117 · Cited by 215
Smith, J. G., & Gerszten, R. E. (2017) · Circulation · doi:10.1161/circulationaha.116.025446 · Cited by 211
McAllister, K. A., Mechanic, L. E., Amos, C. I., Aschard, H., Blair, I. A., Chatterjee, N., Conti, D. V., Gauderman, W. J., Hsu, L., Hutter, C. M., et al. (2017) · American Journal of Epidemiology · doi:10.1093/aje/kwx227 · Cited by 210
Sumida, T. S., Cheru, N. T., & Hafler, D. A. (2024) · Nature reviews. Immunology · doi:10.1038/s41577-024-00994-x · Cited by 229
Iotchkova, V., Ritchie, G. R. S., Geihs, M., Morganella, S., Min, J. L., Walter, K., Timpson, N. J., Dunham, I., Birney, E., & Soranzo, N. (2019) · Nature Genetics · doi:10.1038/s41588-018-0322-6 · Cited by 216
Antaki, D., Guevara, J., Maihofer, A. X., Klein, M., Gujral, M., Grove, J., Carey, C. E., Hong, O., Arranz, M. J., Hervas, A., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01064-5 · Cited by 206
Chromatin accessibility profiling methods
Minnoye, L., Marinov, G. K., Krausgruber, T., Pan, L., Marand, A. P., Secchia, S., Greenleaf, W. J., Furlong, E. E. M., Zhao, K., Schmitz, R. J., et al. (2021) · Nature Reviews Methods Primers · doi:10.1038/s43586-020-00008-9 · Cited by 206
Landscape of cohesin-mediated chromatin loops in the human genome
Grubert, F., Srivas, R., Spacek, D. V., Kasowski, M. M., Ruiz-Velasco, M., Sinnott-Armstrong, N., Greenside, P., Narasimha, A. M., Liu, Q., Geller, B. S., et al. (2020) · Nature · doi:10.1038/s41586-020-2151-x · Cited by 203
DQB1 Locus Alone Explains Most of the Risk and Protection in Narcolepsy with Cataplexy in Europe
Behalf of the European Narcolepsy Network (EU-NN), Tafti, M., Hor, H., Dauvilliers, Y. A., Lammers, G. J., Overeem, S., Mayer, G., Javidi, S., Iranzo, Á., Santamaría, J., et al. (2014) · SLEEP · doi:10.5665/sleep.3300 · Cited by 202
Crowley, J. J., Zhabotynsky, V., Sun, W., Huang, S., Pakatci, I. K., Kim, Y., Wang, J., Morgan, A. P., Calaway, J. D., Aylor, D. L., et al. (2015) · Nature Genetics · doi:10.1038/ng.3222 · Cited by 200
The Virome in Host Health and Disease
Cadwell, K. (2015) · Immunity · doi:10.1016/j.immuni.2015.05.003 · Cited by 209
Watson, C. T., Roussos, P., Garg, P., Ho, D. J., Azam, N., Katsel, P. L., Haroutunian, V., & Sharp, A. J. (2016) · Genome Medicine · doi:10.1186/s13073-015-0258-8 · Cited by 201
Dissecting neural differentiation regulatory networks through epigenetic footprinting
Ziller, M. J., Edri, R., Yaffe, Y., Donaghey, J., Pop, R., Mallard, W., Issner, R., Gifford, C. A., Goren, A., Xing, J. C., et al. (2014) · Nature · doi:10.1038/nature13990 · Cited by 203
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
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
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
Takata, A., Matsumoto, N., & Kato, T. (2017) · Nature Communications · doi:10.1038/ncomms14519 · Cited by 192
Kang, K., Park, S. H., Chen, J., Qiao, Y., Giannopoulou, E., Berg, K., Hanidu, A., Li, J., Nabozny, G., Kang, K., et al. (2017) · Immunity · doi:10.1016/j.immuni.2017.07.017 · Cited by 196
Enhanced meta-analysis and replication studies identify five new psoriasis susceptibility loci
Tsoi, L. C., Spain, S. L., Ellinghaus, E., Stuart, P. E., Capon, F., Knight, J., Tejasvi, T., Kang, H. M., Allen, M. H., Lambert, S., et al. (2015) · Nature Communications · doi:10.1038/ncomms8001 · Cited by 195
Romanoski, C. E., Glass, C. K., Stunnenberg, H. G., Wilson, L., & Almouzni, G. (2015) · Nature · doi:10.1038/518314a · Cited by 192
Epigenetics of Atherosclerosis: Emerging Mechanisms and Methods
Khyzha, N., Alizada, A., Wilson, M. D., & Fish, J. E. (2017) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2017.02.004 · Cited by 196
Moorthy, S. D., Davidson, S., Shchuka, V. M., Singh, G., Malek-Gilani, N., Langroudi, L., Martchenko, A., So, V., Macpherson, N. N., & Mitchell, J. A. (2016) · Genome Research · doi:10.1101/gr.210930.116 · Cited by 202
A Sox2 distal enhancer cluster regulates embryonic stem cell differentiation potential
Zhou, H. Y., Katsman, Y., Dhaliwal, N. K., Davidson, S., Macpherson, N. N., Sakthidevi, M., Collura, F., & Mitchell, J. A. (2014) · Genes & Development · doi:10.1101/gad.248526.114 · Cited by 192
A common genetic variant within SCN10A modulates cardiac SCN5A expression
van den Boogaard, M., Smemo, S., Burnicka-Turek, O., Arnolds, D. E., van de Werken, H. J. G., Klous, P., McKean, D. M., Muehlschlegel, J. D., Moosmann, J., Toka, O., et al. (2014) · Journal of Clinical Investigation · doi:10.1172/jci73140 · Cited by 192
Alteration of Epigenetic Regulation by Long Noncoding RNAs in Cancer
Morlando, M., & Fatica, A. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19020570 · Cited by 197
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
An atlas of chromatin accessibility in the adult human brainPreprint
Fullard, J. F., Hauberg, M. E., Bendl, J. M., Egervári, G., Cirnaru, M., Reach, S. M., Motl, J., Ehrlich, M. E., Hurd, Y. L., & Roussos, P. (2018) · Genome Research · doi:10.1101/gr.232488.117 · Cited by 183
Chiou, J., Zeng, C., Zhang, C., Han, J. Y., Schlichting, M., Miller, M., Mendez, R., Huang, S., Wang, J., Sui, Y., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00823-0 · Cited by 186
Comprehensive Functional Annotation of 77 Prostate Cancer Risk Loci
Hazelett, D. J., Rhie, S. K., Gaddis, M., Yan, C., Lakeland, D. L., Coetzee, S. G., Henderson, B. E., Noushmehr, H., Cozen, W., Kote‐Jarai, Z., et al. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004102 · Cited by 185
Chimeric EWSR1-FLI1 regulates the Ewing sarcoma susceptibility gene EGR2 via a GGAA microsatellite
Grünewald, T. G. P., Bernard, V., Gilardi‐Hebenstreit, P., Raynal, V., Surdez, D., Aynaud, M.-M., Mirabeau, O., Cidre‐Aranaz, F., Tirode, F., Zaïdi, S., et al. (2015) · Nature Genetics · doi:10.1038/ng.3363 · Cited by 200
The road ahead in genetics and genomics
McGuire, A. L., Gabriel, S., Tishkoff, S. A., Wonkam, A., Chakravarti, A., Furlong, E. E. M., Treutlein, B., Meissner, A., Chang, H. Y., López-Bigas, N., et al. (2020) · Nature Reviews Genetics · doi:10.1038/s41576-020-0272-6 · Cited by 188
LncRNAs in cancer: Regulatory and therapeutic implications
Nandwani, A., Rathore, S., & Datta, M. (2020) · Cancer Letters · doi:10.1016/j.canlet.2020.11.048 · Cited by 186
An atlas of gene regulatory elements in adult mouse cerebrum
Li, Y. E., Preissl, S., Hou, X., Zhang, Z., Zhang, K., Qiu, Y., Poirion, O. B., Li, B., Chiou, J., Liu, H., et al. (2021) · Nature · doi:10.1038/s41586-021-03604-1 · Cited by 185
Sveinbjörnsson, G., Albrechtsen, A., Zink, F., Gudjonsson, S. A., Oddsson, Á., Másson, G., Hólm, H., Kong, A., Þorsteinsdóttir, U., Sulem, P., et al. (2016) · Nature Genetics · doi:10.1038/ng.3507 · Cited by 175
Chromosome conformation capture technologies and their impact in understanding genome function
Sati, S., & Cavalli, G. (2016) · Chromosoma · doi:10.1007/s00412-016-0593-6 · Cited by 195
Candidate silencer elements for the human and mouse genomes
Jayavelu, N. D., Jajodia, A., Mishra, A., & Hawkins, R. D. (2020) · Nature Communications · doi:10.1038/s41467-020-14853-5 · Cited by 193
Recent genetic findings in schizophrenia and their therapeutic relevance
Harrison, P. J. (2014) · Journal of Psychopharmacology · doi:10.1177/0269881114553647 · Cited by 201
Genetic Regulation of Adipose Gene Expression and Cardio-Metabolic Traits
Civelek, M., Wu, Y., Pan, C., Raulerson, C. K., Ko, A., He, A., Tilford, C. A., Saleem, N. K., Stančáková, A., Scott, L. J., et al. (2017) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.01.027 · Cited by 176
Direct GR Binding Sites Potentiate Clusters of TF Binding across the Human Genome
Vockley, C. M., D’Ippolito, A. M., McDowell, I. C., Majoros, W. H., Safi, A., Song, L., Crawford, G. E., & Reddy, T. E. (2016) · Cell · doi:10.1016/j.cell.2016.07.049 · Cited by 182
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
Combinatorial bZIP dimers display complex DNA-binding specificity landscapes
Rodríguez‐Martínez, J. A., Reinke, A. W., Bhimsaria, D., Keating, A. E., & Ansari, A. Z. (2017) · eLife · doi:10.7554/elife.19272 · Cited by 179
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
Genetic determinants of co-accessible chromatin regions in activated T cells across humans
Gate, R. E., Cheng, C. S., Aiden, A. P., Siba, A., Tabaka, M., Lituiev, D., Machol, I., Gordon, M. G., Subramaniam, M., Shamim, M., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0156-2 · Cited by 181
Brown, C. D., Mangravite, L. M., & Engelhardt, B. E. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003649 · Cited by 183
Enhancers in disease: molecular basis and emerging treatment strategies
Claringbould, A., & Zaugg, J. B. (2021) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2021.07.012 · Cited by 179
An update on the genetic architecture of hyperuricemia and gout
Merriman, T. R. (2015) · Arthritis Research & Therapy · doi:10.1186/s13075-015-0609-2 · Cited by 180
Hormozdiari, F., Gazal, S., van de Geijn, B., Finucane, H. K., Ju, C. J. ‐., Loh, P., Schoech, A. P., Reshef, Y., Liu, X., O’Connor, L. J., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0148-2 · Cited by 176
The RNA N6-methyladenosine modification landscape of human fetal tissues
Xiao, S., Cao, S., Huang, Q., Xia, L., Deng, M., Yang, M., Jia, G., Liu, X., Shi, J., Wang, W., et al. (2019) · Nature Cell Biology · doi:10.1038/s41556-019-0315-4 · Cited by 180
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
Amariuta, T., Ishigaki, K., Sugishita, H., Ohta, T., Koido, M., Dey, K. K., Matsuda, K., Murakami, Y., Price, A. L., Kawakami, E., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-00740-8 · Cited by 184
Pioneer of prostate cancer: past, present and the future of FOXA1
Teng, M., Zhou, S., Cai, C., Lupien, M., & He, H. H. (2020) · Protein & Cell · doi:10.1007/s13238-020-00786-8 · Cited by 180
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
Rare variants in neuronal excitability genes influence risk for bipolar disorder
Ament, S. A., Szelinger, S., Glusman, G., Ashworth, J. R., Hou, L., Akula, N., Shekhtman, T., Badner, J. A., Brunkow, M. E., Mauldin, D. E., et al. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1424958112 · Cited by 179
Griesemer, D. S., Xue, J. R., Reilly, S. K., Ulirsch, J. C., Kukreja, K., Davis, J. R., Kanai, M., Yang, D. K., Butts, J. C., Guney, M. H., et al. (2021) · Cell · doi:10.1016/j.cell.2021.08.025 · Cited by 176
Comparative Analysis of Gene Regulatory Networks: From Network Reconstruction to Evolution
Thompson, D. A., Regev, A., & Roy, S. (2015) · Annual Review of Cell and Developmental Biology · doi:10.1146/annurev-cellbio-100913-012908 · Cited by 178
SNPsnap: a Web-based tool for identification and annotation of matched SNPs
Pers, T. H., Timshel, P. N., & Hirschhorn, J. N. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu655 · Cited by 171
Zhu, Z., Zhu, X. D., Liu, C.-L., Shi, H., Shen, S., Yang, Y., Hasegawa, K., Camargo, C. A., & Liang, L. (2019) · European Respiratory Journal · doi:10.1183/13993003.01507-2019 · Cited by 181
From variant to function in human disease genetics
Lappalainen, T., & MacArthur, D. G. (2021) · Science · doi:10.1126/science.abi8207 · Cited by 174
The status of the human gene catalogue
Amaral, P., Sala, S. C., Vega, F. M. D. L., Faial, T., Frankish, A., Gingeras, T., Guigó, R., Harrow, J., Hatzigeorgiou, A. G., Johnson, R., et al. (2023) · Nature · doi:10.1038/s41586-023-06490-x · Cited by 202
A comparative atlas of single-cell chromatin accessibility in the human brain
Li, Y. E., Preissl, S., Miller, M., Johnson, N. D., Wang, Z., Jiao, H., Zhu, C., Wang, Z., Xie, Y., Poirion, O., et al. (2023) · Science · doi:10.1126/science.adf7044 · Cited by 173
A Systematic Approach to Identify Candidate Transcription Factors that Control Cell Identity
D’Alessio, A. C., Fan, Z. P., Wert, K. J., Baranov, P., Cohen, M. A., Saini, J. S., Cohick, E., Charniga, C., Dadon, D., Hannett, N. M., et al. (2015) · Stem Cell Reports · doi:10.1016/j.stemcr.2015.09.016 · Cited by 172
Genetics of inflammatory bowel disease: beyond NOD2
Mirkov, M. U., Verstockt, B., & Cleynen, I. (2017) · The Lancet. Gastroenterology & hepatology · doi:10.1016/s2468-1253(16)30111-x · Cited by 179
Panopoulos, A. D., D’Antonio, M., Benaglio, P., Williams, R. M., Hashem, S. I., Schuldt, B. M., DeBoever, C., Arias, A. D., Garcia, M., Nelson, B., et al. (2017) · Stem Cell Reports · doi:10.1016/j.stemcr.2017.03.012 · Cited by 169
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Patsopoulos, N. A. (2018) · Cold Spring Harbor Perspectives in Medicine · doi:10.1101/cshperspect.a028951 · Cited by 188
Spatiotemporal DNA methylome dynamics of the developing mouse fetus
He, Y., Hariharan, M., Gorkin, D. U., Dickel, D. E., Luo, C., Castanon, R., Nery, J. R., Lee, A. Y., Zhao, Y., Huang, H., et al. (2020) · Nature · doi:10.1038/s41586-020-2119-x · Cited by 165
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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
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Ge, Y., & Fuchs, E. V. (2018) · Nature Reviews Genetics · doi:10.1038/nrg.2018.9 · Cited by 172
Single-cell and single-molecule epigenomics to uncover genome regulation at unprecedented resolution
Shema, E., Bernstein, B., & Buenrostro, J. D. (2018) · Nature Genetics · doi:10.1038/s41588-018-0290-x · Cited by 167
Metadata
- Authors
- Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., Shafer, A., Neri, F., Lee, K., Kutyavin, T., Stehling-Sun, S., Johnson, A. K., Canfield, T. K., Giste, E., Diegel, M., Bates, D., Hansen, R. S., Neph, S., Sabo, P. J., Heimfeld, S., Raubitschek, A., Ziegler, S., Cotsapas, C., Sotoodehnia, N., Glass, I., Sunyaev, S. R., Kaul, R., & Stamatoyannopoulos, J. A.
- Affiliations
- University of Washington (US)
- Chinese Academy of Sciences (CN)
- Fred Hutch Cancer Center (US)
- Benaroya Research Institute (US)
- Yale University (US)
- Brigham and Women's Hospital (US)
- Corresponding author
- Maurano, Matthew T.
- Humbert, Richard
- Rynes, Eric
- Stamatoyannopoulos, John A.
- ORCID
- Venue
- Science
- Published
- 2012-09-07
- Volume
- 337
- Issue
- 6099
- Pages
- 1190-1195
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC3771521
- OpenAlex
- W2078059415
- Cited by
- 3,716
- References
- 47
- Citations by year
- 2026: 215 · 2025: 261 · 2024: 296 · 2023: 260 · 2022: 288 · 2021: 352 · 2020: 306 · 2019: 273 · 2018: 270 · 2017: 252 · 2016: 269 · 2015: 249 · 2014: 239 · 2013: 163 · 2012: 17
- FWCI
- 126.66
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Heart, Lung, and Blood Institute (R01HL088456)
- National Institute of Mental Health (F31MH094073)
- National Human Genome Research Institute (U54HG004592)
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK056465)
- National Institute of Environmental Health Sciences (U01ES01156, U01ES017156)
- Eunice Kennedy Shriver National Institute of Child Health and Human Development (R24HD000836)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Keywords
- non-coding variants, regulatory DNA, DNase I hypersensitive sites, common diseases, fetal development, prenatal exposure, transcription factor binding sites, regulatory networks, Crohn's disease, multiple sclerosis, electrocardiogram, disease-associated variants
- MeSH terms
- Alleles, Chromatin, Crohn Disease, Deoxyribonuclease I, Disease, DNA, Electrocardiography, Fetus, Humans, Multiple Sclerosis, Phenotype, Promoter Regions, Genetic, Regulatory Sequences, Nucleic Acid, Transcription Factors, Genetic Variation, Genome, Human, Polymorphism, Single Nucleotide, Fetal Development, Regulatory Elements, Transcriptional, Gene Regulatory Networks, Genome-Wide Association Study
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