Index and biological spectrum of human DNase I hypersensitive sites
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Abstract
DNase I hypersensitive sites (DHSs) are generic markers of regulatory DNA 1–5 and contain genetic variations associated with diseases and phenotypic traits 6–8 . We created high-resolution maps of DHSs from 733 human biosamples encompassing 438 cell and tissue types and states, and integrated these to delineate and numerically index approximately 3.6 million DHSs within the human genome sequence, providing a common coordinate system for regulatory DNA. Here we show that these maps highly resolve the cis -regulatory compartment of the human genome, which encodes unexpectedly diverse cell- and tissue-selective regulatory programs at very high density. These programs can be captured comprehensively by a simple vocabulary that enables the assignment to each DHS of a regulatory barcode that encapsulates its tissue manifestations, and global annotation of protein-coding and non-coding RNA genes in a manner orthogonal to gene expression. Finally, we show that sharply resolved DHSs markedly enhance the genetic association and heritability signals of diseases and traits. Rather than being confined to a small number of distal elements or promoters, we find that genetic signals converge on congruently regulated sets of DHSs that decorate entire gene bodies. Together, our results create a universal, extensible coordinate system and vocabulary for human regulatory DNA marked by DHSs, and provide a new global perspective on the architecture of human gene regulation.
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Open chromatin regions are not limited to active enhancers, and also harbour active gene promoters, regulatory elements in a poised chromatin configuration, and some structural regions such as tissue-invariant binding sites for CTCF.
“However, open chromatin regions are not limited to active enhancers, and also harbour other regions including active gene promoters, regulatory elements in a ‘poised’ chromatin configuration (discussed below), as well as some structural regions such as tissue-invariant binding sites for the architectural protein CCCTC-binding factor (CTCF) [129–132].”
From Transcriptional enhancers and their communication with gene promoters (2021) · cites this paper as [130]
The Introduction (page unavailable) identifies promoters and chromatin insulators among the active regulatory elements marked by accessible DNA, and says DHSs can appear before functional activation. This supports the claim that open chromatin is not limited to active enhancers, but our copy does not specifically identify poised chromatin configurations or tissue-invariant CTCF-binding sites as examples. (LLM, conf=0.84)
Experimental — accuracy not yet measuredA majority of TCs (90%) were supported by FANTOM5 CAGE peaks and/or open chromatin regions from ENCODE and TCGA.
“A majority of TCs (90%) were supported by FANTOM5 CAGE peaks17 and/or open chromatin regions from ENCODE22 and TCGA7”
From Alternative promoters in CpG depleted regions are prevalently associated with epigenetic misregulation of liver cancer transcriptomes (2023) · cites this paper as [22]
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Cites
KEGG: Kyoto Encyclopedia of Genes and Genomes
Kanehisa, M. (2000) · Nucleic Acids Research · doi:10.1093/nar/28.1.27 · Cited by 37,077 · see citing works
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089 · see citing works
KEGG: Kyoto Encyclopedia of Genes and Genomes
Ogata, H., Goto, S., Sato, K., Fujibuchi, W., Bono, H., & Kanehisa, M. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.1.29 · Cited by 31,232 · see citing works
Learning the parts of objects by non-negative matrix factorization
Lee, D. D., & Seung, H. S. (1999) · Nature · doi:10.1038/44565 · Cited by 13,898 · see citing works
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 · see citing works
The UK Biobank resource with deep phenotyping and genomic data
Bycroft, C., Freeman, C., Petkova, D., Band, G., Elliott, L. T., Sharp, K., Motyer, A., Vukcevic, D., Delaneau, O., O’Connell, J., et al. (2018) · Nature · doi:10.1038/s41586-018-0579-z · Cited by 8,876 · see citing works
Integrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368 · see citing works
Self-citationLD Score regression distinguishes confounding from polygenicity in genome-wide association studies
Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bulik-Sullivan, B. K., Loh, P.-R., Finucane, H. K., Ripke, S., Yang, J., Patterson, N., Daly, M. J., Price, A. L., & Neale, B. M. (2015) · Nature Genetics · doi:10.1038/ng.3211 · Cited by 5,559 · see citing works
The approximation of one matrix by another of lower rank
Eckart, C., & Young, G. (1936) · Psychometrika · doi:10.1007/bf02288367 · Cited by 4,497 · see citing works
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 · see citing works
Systematic Localization of Common Disease-Associated Variation in Regulatory DNA
Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., et al. (2012) · Science · doi:10.1126/science.1222794 · Cited by 3,716 · see citing works
Self-citationThe Human Transcription Factors
Lambert, S. A., Jolma, A., Campitelli, L. F., Das, P. K., Yin, Y., Albu, M., Chen, X., Taipale, J., Hughes, T. R., & Weirauch, M. T. (2018) · Cell · doi:10.1016/j.cell.2018.01.029 · Cited by 3,399 · see citing works
GENCODE reference annotation for the human and mouse genomes
Frankish, A., Diekhans, M., Ferreira, A.-M., Johnson, R., Jungreis, I., Loveland, J. E., Mudge, J. M., Sisu, C., Wright, J. C., Armstrong, J. C., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky955 · Cited by 2,929 · see citing works
Mapping and analysis of chromatin state dynamics in nine human cell types
Ernst, J., Kheradpour, P., Mikkelsen, T. S., Shoresh, N., Ward, L. D., Epstein, C. B., Zhang, X., Wang, L., Issner, R., Coyne, M., et al. (2011) · Nature · doi:10.1038/nature09906 · Cited by 2,898 · see citing works
The accessible chromatin landscape of the human genome
Thurman, R. E., Rynes, E., Humbert, R., Vierstra, J., Maurano, M. T., Haugen, E., Sheffield, N. C., Stergachis, A. B., Wang, H., Vernot, B., et al. (2012) · Nature · doi:10.1038/nature11232 · Cited by 2,679 · see citing works
Self-citationPartitioning heritability by functional annotation using genome-wide association summary statistics
ReproGen Consortium, Finucane, H. K., Schizophrenia Working Group of the Psychiatric Genomics Consortium, The RACI Consortium, Bulik-Sullivan, B., Gusev, A., Trynka, G., Reshef, Y., Loh, P.-R., Anttila, V., et al. (2015) · Nature Genetics · doi:10.1038/ng.3404 · Cited by 2,604 · see citing works
Detection of nonneutral substitution rates on mammalian phylogenies
Pollard, K. S., Hubisz, M. J., Rosenbloom, K. R., & Siepel, A. (2010) · Genome Research · doi:10.1101/gr.097857.109 · Cited by 2,353 · see citing works
The UCSC Table Browser data retrieval tool
Karolchik, D. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkh103 · Cited by 2,269 · see citing works
Efficient Bayesian mixed-model analysis increases association power in large cohorts
Loh, P.-R., Tucker, G., Bulik-Sullivan, B. K., Vilhjálmsson, B. J., Finucane, H. K., Salem, R. M., Chasman, D. I., Ridker, P. M., Neale, B. M., Berger, B., et al. (2015) · Nature Genetics · doi:10.1038/ng.3190 · Cited by 1,507 · see citing works
High-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 · see citing works
NUCLEASE HYPERSENSITIVE SITES IN CHROMATIN
Gross, D. S., & Garrard, W. T. (1988) · Annual Review of Biochemistry · doi:10.1146/annurev.bi.57.070188.001111 · Cited by 1,233 · see citing works
The 5′ ends of Drosophila heat shock genes in chromatin are hypersensitive to DNase I
Wu, C. C. M. (1980) · Nature · doi:10.1038/286854a0 · Cited by 1,118 · see citing works
Finucane, H. K., Reshef, Y. A., Anttila, V., Slowikowski, K., Gusev, A., Byrnes, A., Gazal, S., Loh, P.-R., Lareau, C., Shoresh, N., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0081-4 · Cited by 1,097 · see citing works
BEDOPS: high-performance genomic feature operations
Neph, S. J., Kuehn, M. S., Reynolds, A. P., Haugen, E., Thurman, R. E., Johnson, A., Rynes, E., Maurano, M. T., Vierstra, J. D., Thomas, S., et al. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts277 · Cited by 971 · see citing works
Self-citationChromatin accessibility pre-determines glucocorticoid receptor binding patterns
John, S., Sabo, P. J., Thurman, R. E., Sung, M.-H., Biddie, S. C., Johnson, T. A., Hager, G. L., & Stamatoyannopoulos, J. A. (2011) · Nature Genetics · doi:10.1038/ng.759 · Cited by 954 · see citing works
Self-citationChung, J. H., Whiteley, M., & Felsenfeld, G. (1993) · Cell · doi:10.1016/0092-8674(93)80052-g · Cited by 854 · see citing works
SVD based initialization: A head start for nonnegative matrix factorization
Boutsidis, C., & Gallopoulos, E. (2007) · Pattern Recognition · doi:10.1016/j.patcog.2007.09.010 · Cited by 729 · see citing works
Massive mining of publicly available RNA-seq data from human and mouse
Lachmann, A., Torre, D., Keenan, A. B., Jagodnik, K. M., Lee, H. J., Wang, L., Silverstein, M. C., & Ma’ayan, A. (2018) · Nature Communications · doi:10.1038/s41467-018-03751-6 · Cited by 701 · see citing works
Defining functional DNA elements in the human genome
Kellis, M., Wold, B. J., Snyder, M. P., Bernstein, B., Kundaje, A. B., Marinov, G. K., Ward, L. D., Birney, E., Crawford, G. E., Dekker, J., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1318948111 · Cited by 692 · see citing works
Self-citationKRAB zinc-finger proteins contribute to the evolution of gene regulatory networks
Imbeault, M., Helleboid, P.-Y., & Trono, D. (2017) · Nature · doi:10.1038/nature21683 · Cited by 623 · see citing works
Unsupervised pattern discovery in human chromatin structure through genomic segmentation
Hoffman, M. M., Buske, O. J., Wang, J., Weng, Z., Bilmes, J., & Noble, W. S. (2012) · Nature Methods · doi:10.1038/nmeth.1937 · Cited by 566 · see citing works
Partitioning Heritability of Regulatory and Cell-Type-Specific Variants across 11 Common Diseases
Gusev, A., Lee, S. H., Trynka, G., Finucane, H., Vilhjálmsson, B. J., Xu, H., Zang, C., Ripke, S., Bulik-Sullivan, B., Stahl, E., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.10.004 · Cited by 544 · see citing works
Approximately independent linkage disequilibrium blocks in human populations
Berisa, T., & Pickrell, J. K. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv546 · Cited by 534 · see citing works
Song, L., Zhang, Z., Grasfeder, L. L., Boyle, A. P., Giresi, P. G., Lee, B.-K., Sheffield, N. C., Gräf, S., Huss, M., Keefe, D., et al. (2011) · Genome Research · doi:10.1101/gr.121541.111 · Cited by 500 · see citing works
Targeted RNA sequencing reveals the deep complexity of the human transcriptome
Mercer, T. R., Gerhardt, D. J., Dinger, M. E., Crawford, J., Trapnell, C., Jeddeloh, J. A., Mattick, J. S., & Rinn, J. L. (2011) · Nature Biotechnology · doi:10.1038/nbt.2024 · Cited by 490 · see citing works
Tissue-specific DNA cleavages in the globin chromatin domain introduced by DNAase I
Stalder, J. (1980) · Cell · doi:10.1016/0092-8674(80)90631-5 · Cited by 474 · see citing works
Determinants and dynamics of genome accessibility
Bell, O., Tiwari, V. K., Thomä, N. H., & Schübeler, D. (2011) · Nature Reviews Genetics · doi:10.1038/nrg3017 · Cited by 457 · see citing works
Li, Q., Peterson, K. R., Fang, X., & Stamatoyannopoulos, G. (2002) · Blood · doi:10.1182/blood-2002-04-1104 · Cited by 456 · see citing works
Klann, T. S., Black, J. B., Chellappan, M., Safi, A., Song, L., Hilton, I. B., Crawford, G. E., Reddy, T. E., & Gersbach, C. A. (2017) · Nature Biotechnology · doi:10.1038/nbt.3853 · Cited by 447 · see citing works
McGhee, J. D. (1981) · Cell · doi:10.1016/0092-8674(81)90359-7 · Cited by 437 · see citing works
Concepts, estimation and interpretation of SNP-based heritability
Yang, J., Zeng, J., Goddard, M. E., Wray, N. R., & Visscher, P. M. (2017) · Nature Genetics · doi:10.1038/ng.3941 · Cited by 435 · see citing works
Unsupervised pattern discovery in human chromatin structure through genomic segmentation
Hoffman, M. M., Buske, O. J., Wang, J., Weng, Z., Bilmes, J., & Noble, W. S. (2012) · eScholarship@UMassChan · Cited by 397 · see citing works
Global reference mapping of human transcription factor footprints
Vierstra, J., Lazar, J., Sandstrom, R., Halow, J., Lee, K., Bates, D., Diegel, M., Dunn, D., Neri, F., Haugen, E., et al. (2020) · Nature · doi:10.1038/s41586-020-2528-x · Cited by 386 · see citing works
Self-citationThe GENCODE pseudogene resource
Pei, B.-K., Sisu, C., Frankish, A., Howald, C., Habegger, L., Mu, X., Harte, R., Balasubramanian, S., Tanzer, A., Diekhans, M., et al. (2012) · Genome Biology · doi:10.1186/gb-2012-13-9-r51 · Cited by 355 · see citing works
The Majority of Primate-Specific Regulatory Sequences Are Derived from Transposable Elements
Jacques, P., Jeyakani, J., & Bourque, G. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003504 · Cited by 345 · see citing works
Developmental Fate and Cellular Maturity Encoded in Human Regulatory DNA Landscapes
Stergachis, A. B., Neph, S. J., Reynolds, A. P., Humbert, R., Miller, B. G., Paige, S. L., Vernot, B., Cheng, J. B., Thurman, R. E., Sandstrom, R. S., et al. (2013) · Cell · doi:10.1016/j.cell.2013.07.020 · Cited by 331 · see citing works
Self-citationUnsupervised pattern discovery in human chromatin structure through genomic segmentation
Hoffman, M. M., Buske, O. J., Wang, J., Weng, Z., Bilmes, J. A., & Noble, W. S. (2013) · ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) · doi:10.1145/2506583.2506701 · Cited by 288 · see citing works
Mouse regulatory DNA landscapes reveal global principles of cis-regulatory evolution
Vierstra, J. D., Rynes, E., Sandstrom, R. S., Zhang, M., Canfield, T. K., Hansen, R. S., Stehling-Sun, S., Sabo, P. J., Byron, R., Humbert, R., et al. (2014) · Science · doi:10.1126/science.1246426 · Cited by 253 · see citing works
Self-citationEnter the Matrix: Factorization Uncovers Knowledge from Omics
Stein-O’Brien, G., Arora, R., Culhane, A. C., Favorov, A. V., Garmire, L. X., Greene, C. S., Goff, L. A., Li, Y., Ngom, A., Ochs, M. F., et al. (2018) · Trends in Genetics · doi:10.1016/j.tig.2018.07.003 · Cited by 235 · see citing works
Conservation of trans-acting circuitry during mammalian regulatory evolution
Stergachis, A. B., Neph, S., Sandstrom, R., Haugen, E., Reynolds, A. P., Zhang, M., Byron, R., Canfield, T., Stelhing-Sun, S., Lee, K., et al. (2014) · Nature · doi:10.1038/nature13972 · Cited by 212 · see citing works
Self-citationIdentifying gene regulatory elements by genome-wide recovery of DNase hypersensitive sites
Crawford, G. E., Holt, I. E., Mullikin, J. C., Tai, D. S., Green, E. D., Wolfsberg, T. G., & Collins, F. S. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0307540100 · Cited by 182 · see citing works
Gazal, S., Loh, P.-R., Finucane, H. K., Ganna, A., Schoech, A., Sunyaev, S., & Price, A. L. (2018) · Nature Genetics · doi:10.1038/s41588-018-0231-8 · Cited by 154 · see citing works
Discovery of functional noncoding elements by digital analysis of chromatin structure
Sabo, P. J., Hawrylycz, M., Wallace, J. C., Humbert, R., Yu, M., Shafer, A., Kawamoto, J., Hall, R., Mack, J., Dorschner, M. O., et al. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0407387101 · Cited by 139 · see citing works
Self-citationFunctional footprinting of regulatory DNA
Vierstra, J., Reik, A., Chang, K.-H., Stehling-Sun, S., Zhou, Y., Hinkley, S. J., Paschon, D. E., Zhang, L., Psatha, N., Bendana, Y. R., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3554 · Cited by 133 · see citing works
Self-citationShibata, Y., Sheffield, N. C., Fedrigo, O. D., Babbitt, C. C., Wortham, M., Tewari, A. K., London, D., Song, L., Lee, B., Iyer, V. R., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002789 · Cited by 121 · see citing works
DNase I hypersensitive sites in the chromatin of human μ immunoglobulin heavy-chain genes
Mills, F. C., Fisher, L. M., Kuroda, R., Ford, A. M., & Gould, H. J. (1983) · Nature · doi:10.1038/306809a0 · Cited by 104 · see citing works
Comparative analysis of pseudogenes across three phyla
Sisu, C., Pei, B., Leng, J., Frankish, A., Zhang, Y., Balasubramanian, S., Harte, R., Wang, D., Rutenberg-Schoenberg, M., Clark, W. T., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1407293111 · Cited by 96 · see citing works
Genome‐Scale Mapping of DNase I Hypersensitivity
John, S., Sabo, P. J., Canfield, T. K., Lee, K., Vong, S., Weaver, M., Wang, H., Vierstra, J. D., Reynolds, A. P., Thurman, R. E., et al. (2013) · Current Protocols in Molecular Biology · doi:10.1002/0471142727.mb2127s103 · Cited by 92 · see citing works
Self-citationDetecting genome-wide directional effects of transcription factor binding on polygenic disease risk
Reshef, Y. A., Finucane, H. K., Kelley, D. R., Gusev, A., Kotliar, D., Ulirsch, J. C., Hormozdiari, F., Nasser, J., O’Connor, L., van de Geijn, B., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0196-7 · Cited by 68 · see citing works
Fast analysis of scATAC-seq data using a predefined set of genomic regions
Giansanti, V., Tang, M., & Cittaro, D. (2020) · F1000Research · doi:10.12688/f1000research.22731.1 · Cited by 16 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- [15]Sabo PJ Genome-scale mapping of DNase I sensitivity in vivo using tiling DNA microarrays. Nat. Methods 3, 511– 518 (2006). 16791208
Cited by
Sorted by citations
Expanded encyclopaedias of DNA elements in the human and mouse genomes
The ENCODE Project Consortium, Abascal, F., Acosta, R., Addleman, N. J., Adrian, J., Afzal, V., Ai, R., Aken, B., Akiyama, J. A., Jammal, O. A., et al. (2020) · Nature · doi:10.1038/s41586-020-2493-4 · Cited by 2,378 · see citing works
Self-citationA cross-population atlas of genetic associations for 220 human phenotypes
Sakaue, S., Kanai, M., Tanigawa, Y., Karjalainen, J. M., Kurki, M., Koshiba, S., Narita, A., Konuma, T., Yamamoto, K., Akiyama, M., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00931-x · Cited by 2,296 · see citing works
Demontis, D., Walters, G., Athanasiadis, G., Walters, R., Therrien, K., Nielsen, T., Farajzadeh, L., Voloudakis, G., Bendl, J., Zeng, B., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01285-8 · Cited by 646 · see citing works
SCENIC+: single-cell multiomic inference of enhancers and gene regulatory networks
Bravo González-Blas, C., De Winter, S., Hulselmans, G., Hecker, N., Matetovici, I., Christiaens, V., Poovathingal, S., Wouters, J., Aibar, S., & Aerts, S. (2023) · Nature Methods · doi:10.1038/s41592-023-01938-4 · Cited by 778 · see citing works
Nucleotide Transformer: building and evaluating robust foundation models for human genomics
Dalla-Torre, H., Gonzalez, L., Mendoza-Revilla, J., Lopez Carranza, N., Grzywaczewski, A. H., Oteri, F., Dallago, C., Trop, E., de Almeida, B. P., Sirelkhatim, H., et al. (2025) · Nature Methods · doi:10.1038/s41592-024-02523-z · Cited by 656 · see citing works
“Enhancers were split in tissue-specific and tissue-invariant based on the vocabulary from Meuleman et al. 33 (https://www.meuleman.org/research/dhsin-dex/).”
A single-cell atlas of chromatin accessibility in the human genome
Zhang, K., Hocker, J. D., Miller, M., Hou, X., Chiou, J., Poirion, O. B., Qiu, Y., Li, Y. E., Gaulton, K. J., Wang, A., et al. (2021) · Cell · doi:10.1016/j.cell.2021.10.024 · Cited by 502 · see citing works
Regulatory genomic circuitry of human disease loci by integrative epigenomics
Boix, C. A., James, B. T., Park, Y., Meuleman, W. R. A., & Kellis, M. (2021) · Nature · doi:10.1038/s41586-020-03145-z · Cited by 384 · see citing works
Self-citationA human cell atlas of fetal chromatin accessibility
Domcke, S., Hill, A. J., Daza, R. M., Cao, J., O’Day, D. R., Pliner, H. A., Aldinger, K. A., Pokholok, D., Zhang, F., Milbank, J. H., et al. (2020) · Science · doi:10.1126/science.aba7612 · Cited by 375 · see citing works
Global reference mapping of human transcription factor footprints
Vierstra, J., Lazar, J., Sandstrom, R., Halow, J., Lee, K., Bates, D., Diegel, M., Dunn, D., Neri, F., Haugen, E., et al. (2020) · Nature · doi:10.1038/s41586-020-2528-x · Cited by 386 · see citing works
Self-citationWeeks, E. M., Ulirsch, J. C., Cheng, N., Trippe, B. L., Fine, R. S., Miao, J., Patwardhan, T. A., Kanai, M., Nasser, J., Fulco, C. P., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01443-6 · Cited by 330 · see citing works
Systematic differences in discovery of genetic effects on gene expression and complex traits
Mostafavi, H., Spence, J. P., Naqvi, S., & Pritchard, J. K. (2023) · Nature Genetics · doi:10.1038/s41588-023-01529-1 · Cited by 336 · see citing works
Als, T. D., Kurki, M., Grove, J., Voloudakis, G., Therrien, K., Tasanko, E. M., Nielsen, T. T., Naamanka, J., Veerapen, K., Levey, D. F., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02352-1 · Cited by 321 · see citing works
A sequence-based global map of regulatory activity for deciphering human genetics
Chen, K. M., Wong, A. K., Troyanskaya, O. G., & Zhou, J. (2022) · Nature Genetics · doi:10.1038/s41588-022-01102-2 · Cited by 269 · see citing works
de Almeida, B. P., Reiter, F., Pagani, M., & Stark, A. (2021) · doi:10.1101/2021.10.05.463203 · Cited by 284
de Almeida, B. P., Reiter, F., Pagani, M., & Stark, A. (2022) · Nature Genetics · doi:10.1038/s41588-022-01048-5 · Cited by 283 · see citing works
Swanson, E., Lord, C., Reading, J., Heubeck, A. T., Genge, P. C., Thomson, Z., Weiss, M. D., Li, X.-J., Savage, A. K., Green, R. R., et al. (2021) · eLife · doi:10.7554/elife.63632 · Cited by 267 · see citing works
Characterizing cis-regulatory elements using single-cell epigenomics
Preissl, S., Gaulton, K. J., & Ren, B. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-022-00509-1 · Cited by 251 · see citing works
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 214 · see citing works
Self-citationPeneder, P., Stütz, A. M., Surdez, D., Krumbholz, M., Semper, S., Chicard, M., Sheffield, N. C., Pierron, G., Lapouble, E., Tötzl, M., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23445-w · Cited by 200 · see citing works
Multiple causal variants underlie genetic associations in humans
Abell, N. S., DeGorter, M. K., Gloudemans, M. J., Greenwald, E., Smith, K. S., He, Z., & Montgomery, S. B. (2022) · Science · doi:10.1126/science.abj5117 · Cited by 186 · see citing works
Cell-type-directed design of synthetic enhancers
Taskiran, I. I., Spanier, K. I., Dickmänken, H., Kempynck, N., Pančíková, A., Ekşi, E. C., Hulselmans, G., Ismail, J. N., Theunis, K., Vandepoel, R., et al. (2024) · Nature · doi:10.1038/s41586-023-06936-2 · Cited by 175 · see citing works
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 · see citing works
The missing link between genetic association and regulatory function
Connally, N. J., Nazeen, S., Lee, D., Shi, H., Stamatoyannopoulos, J. A., Chun, S., Cotsapas, C. J., Cassa, C. A., & Sunyaev, S. R. (2022) · eLife · doi:10.7554/elife.74970 · Cited by 144 · see citing works
Self-citationEnhancer grammar in development, evolution, and disease: dependencies and interplay
Jindal, G. A., & Farley, E. K. (2021) · Developmental Cell · doi:10.1016/j.devcel.2021.02.016 · Cited by 147 · see citing works
A map of cis-regulatory elements and 3D genome structures in zebrafish
Yang, H., Luan, Y., Liu, T., Lee, H. J., Li, F., Wang, Y., Wang, X., Zhang, B., Jin, Q., Ang, K. C., et al. (2020) · Nature · doi:10.1038/s41586-020-2962-9 · Cited by 144 · see citing works
Massively parallel characterization of transcriptional regulatory elements
Agarwal, V., Inoue, F., Schubach, M., Penzar, D., Martin, B. K., Dash, P. M., Keukeleire, P., Zhang, Z., Sohota, A., Zhao, J., et al. (2025) · Nature · doi:10.1038/s41586-024-08430-9 · Cited by 146 · see citing works
Ferrie, J. J., Karr, J. P., Tjian, R., & Darzacq, X. (2022) · Molecular Cell · doi:10.1016/j.molcel.2022.09.021 · Cited by 144 · see citing works
Machine-guided design of cell-type-targeting cis-regulatory elements
Gosai, S. J., Castro, R. I., Fuentes, N., Butts, J. C., Mouri, K., Alasoadura, M., Kales, S., Nguyen, T. T. L., Noche, R. R., Rao, A. S., et al. (2024) · Nature · doi:10.1038/s41586-024-08070-z · Cited by 142 · see citing works
Pampari, A., Shcherbina, A., Kvon, E. Z., Kosicki, M., Nair, S., Kundu, S., Kathiria, A. S., Risca, V. I., Kuningas, K., Alasoo, K., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.12.25.630221 · Cited by 161 · see citing works
He, L., Pratt, H., Gao, M., Wei, F., Weng, Z., & Struhl, K. (2021) · eLife · doi:10.7554/elife.67312 · Cited by 122 · see citing works
An encyclopedia of enhancer-gene regulatory interactions in the human genome
Gschwind, A. R., Mualim, K. S., Karbalayghareh, A., Sheth, M. U., Dey, K. K., Jagoda, E., Nurtdinov, R. N., Xi, W., Tan, A. S., Jones, H., et al. (2023) · doi:10.1101/2023.11.09.563812 · Cited by 119 · see citing works
Self-citationA framework for clinical cancer subtyping from nucleosome profiling of cell-free DNA
Doebley, A.-L., Ko, M., Liao, H., Cruikshank, A. E., Santos, K., Kikawa, C., Hiatt, J. B., Patton, R. D., Sarkar, N. D., Collier, K. A., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-35076-w · Cited by 135 · see citing works
Liquid biopsy epigenomic profiling for cancer subtyping
Baca, S. C., Seo, J.-H., Davidsohn, M. P., Fortunato, B. J., Semaan, K., Sotudian, S., Lakshminarayanan, G., Dióssy, M., Qiu, X., Zarif, T. E., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02605-z · Cited by 128 · see citing works
Tedesco, M., Giannese, F., Lazarević, D., Giansanti, V., Rosano, D., Monzani, S., Catalano, I., Grassi, E., Zanella, E. R., Botrugno, O. A., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-01031-1 · Cited by 112 · see citing works
Identification of constrained sequence elements across 239 primate genomes
Kuderna, L. F. K., Ulirsch, J. C., Rashid, S., Ameen, M., Sundaram, L., Hickey, G., Cox, A. J., Gao, H., Kumar, A., Aguet, F., et al. (2023) · Nature · doi:10.1038/s41586-023-06798-8 · Cited by 103 · see citing works
SCENIC+: single-cell multiomic inference of enhancers and gene regulatory networks
González-Blas, C. B., De Winter, S., Hulselmans, G., Hecker, N., Matetovici, I., Christiaens, V., Poovathingal, S., Wouters, J., Aibar, S., & Aerts, S. (2022) · doi:10.1101/2022.08.19.504505 · Cited by 778 · see citing works
A clinician’s handbook for using ctDNA throughout the patient journey
Hasenleithner, S. O., & Speicher, M. R. (2022) · Molecular Cancer · doi:10.1186/s12943-022-01551-7 · Cited by 109 · see citing works
Fragmentation landscape of cell-free DNA revealed by deconvolutional analysis of end motifs
Zhou, Z., Ma, M.-J. L., Chan, R. W. Y., Lam, W. K., Peng, W., Gai, W., Hu, X., Ding, S. C., Ji, L., Zhou, Q. X., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2220982120 · Cited by 100 · see citing works
Insights from complex trait fine-mapping across diverse populationsPreprint
Kanai, M., Ulirsch, J. C., Karjalainen, J. M., Kurki, M., Karczewski, K. J., Fauman, E. B., Wang, Q. S., Jacobs, H., Aguet, F., Ardlie, K., et al. (2021) · medRxiv · doi:10.1101/2021.09.03.21262975 · Cited by 96 · see citing works
Affinity-optimizing enhancer variants disrupt development
Lim, F., Solvason, J. J., Ryan, G. E., Le, S. H., Jindal, G. A., Steffen, P., Jandu, S. K., & Farley, E. K. (2024) · Nature · doi:10.1038/s41586-023-06922-8 · Cited by 96 · see citing works
The Genomic and Epigenomic Landscape of Double-Negative Metastatic Prostate Cancer
Lundberg, A., Zhang, M., Aggarwal, R. R., Li, H., Zhang, L., Foye, A., Sjöström, M., Chou, J., Chang, K. C., Moreno-Rodriguez, T., et al. (2023) · Cancer Research · doi:10.1158/0008-5472.can-23-0593 · Cited by 85 · see citing works
Limited overlap of eQTLs and GWAS hits due to systematic differences in discoveryPreprint
Mostafavi, H., Spence, J. P., Naqvi, S., & Pritchard, J. K. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.05.07.491045 · Cited by 86 · see citing works
The renal lineage factor PAX8 controls oncogenic signalling in kidney cancer
Patel, S. A., Hirosue, S., Rodrigues, P., Vojtasova, E., Richardson, E. K., Ge, J., Syafruddin, S. E., Speed, A., Papachristou, E. K., Baker, D., et al. (2022) · Nature · doi:10.1038/s41586-022-04809-8 · Cited by 83 · see citing works
Developmental and evolutionary dynamics of cis-regulatory elements in mouse cerebellar cells
Sarropoulos, I., Sepp, M., Frömel, R., Leiss, K., Trost, N., Leushkin, E. V., Okonechnikov, K., Joshi, P. K., Giere, P., Kutscher, L. M., et al. (2021) · Science · doi:10.1126/science.abg4696 · Cited by 77 · see citing works
Transcriptional enhancers and their communication with gene promoters
Ray-Jones, H., & Spivakov, M. (2021) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-021-03903-w · Cited by 81 · see citing works
Epigenetic regulation of ACE2, the receptor of the SARS-CoV-2 virus1
Beacon, T. H., Delcuve, G. P., & Davie, J. (2020) · Genome · doi:10.1139/gen-2020-0124 · Cited by 75 · see citing works
Khan, M. U. A., Aslam, M. A., Abdullah, M. F., & Stojanović, G. M. (2024) · ACS Applied Bio Materials · doi:10.1021/acsabm.4c00362 · Cited by 78 · see citing works
Interpreting non-coding disease-associated human variants using single-cell epigenomics
Gaulton, K. J., Preißl, S., & Ren, B. (2023) · Nature Reviews Genetics · doi:10.1038/s41576-023-00598-6 · Cited by 79 · see citing works
Mouri, K., Guo, M. H., de Boer, C. G., Lissner, M. M., Harten, I. A., Newby, G. A., DeBerg, H. A., Platt, W. F., Gentili, M., Liu, D. R., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01056-5 · Cited by 71 · see citing works
A plate-based single-cell ATAC-seq workflow for fast and robust profiling of chromatin accessibility
Xu, W., Wen, Y., Liang, Y., Xu, Q., Wang, X., Jin, W., & Chen, X. (2021) · Nature Protocols · doi:10.1038/s41596-021-00583-5 · Cited by 67 · see citing works
Speed–Specificity Trade-Offs in the Transcription Factors Search for Their Genomic Binding Sites
Jana, T., Brodsky, S., & Barkai, N. (2021) · Trends in Genetics · doi:10.1016/j.tig.2020.12.001 · Cited by 63 · see citing works
Baca, S. C., Singler, C., Zacharia, S., Seo, J.-H., Morova, T., Hach, F., Ding, Y., Schwarz, T., Huang, C.-C. F., Anderson, J. R., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01168-y · Cited by 30 · see citing works
Epigenetic Regulation of Kupffer Cell Function in Health and Disease
Bennett, H., Troutman, T. D., Sakai, M., & Glass, C. K. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2020.609618 · Cited by 66 · see citing works
The three-dimensional landscape of cortical chromatin accessibility in Alzheimer’s disease
Bendl, J., Hauberg, M. E., Girdhar, K., Im, E., Vicari, J. M., Rahman, S., Fernando, M. B., Townsley, K. G., Dong, P., Misir, R., et al. (2022) · Nature Neuroscience · doi:10.1038/s41593-022-01166-7 · Cited by 65 · see citing works
Varberg, K. M., Dominguez, E. M., Koseva, B. S., Varberg, J. M., McNally, R. P., Moreno‐Irusta, A., Wesley, E. R., Iqbal, K., Cheung, W., Schwendinger-Schreck, C., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-40424-5 · Cited by 62 · see citing works
Demontis, D., Walters, G. B., Athanasiadis, G. I., Walters, R. K., Therrien, K., Farajzadeh, L., Voloudakis, G., Bendl, J. M., Zeng, B., Zhang, W., et al. (2022) · medRxiv · doi:10.1101/2022.02.14.22270780 · Cited by 61 · see citing works
Orchard, P., Manickam, N., Varshney, A., Vadlamudi, S., Burant, C., Parker, S. C. J., Kaplan, J., Lalancette, C., Mohlke, K. L., Gallagher, K., et al. (2021) · Genome Research · doi:10.1101/gr.268482.120 · Cited by 58 · see citing works
Benaglio, P., Newsome, J. M., Han, J. Y., Chiou, J., Aylward, A., Corban, S., Miller, M., Okino, M.-L., Kaur, J., Preißl, S., et al. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010759 · Cited by 51 · see citing works
The native cistrome and sequence motif families of the maize ear
Savadel, S. D., Hartwig, T., Turpin, Z. M., Vera, D. L., Lung, P.-Y., Sui, X., Blank, M., Frommer, W. B., Dennis, J. H., Zhang, J., et al. (2021) · PLoS Genetics · doi:10.1371/journal.pgen.1009689 · Cited by 49 · see citing works
Cheung, W. A., Johnson, A. F., Rowell, W., Farrow, E., Hall, R. P., Cohen, A. S. A., Means, J. C., Zion, T., Portik, D. M., Saunders, C., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-38782-1 · Cited by 39 · see citing works
Self-citationVollger, M. R., Korlach, J., Eldred, K. C., Swanson, E. G., Underwood, J. G., Bohaczuk, S. C., Mao, Y., Cheng, Y.-H. H., Ranchalis, J. E., Blue, E., et al. (2025) · Nature Genetics · doi:10.1038/s41588-024-02067-0 · Cited by 48 · see citing works
Kojima, S., Koyama, S., Ka, M., Saito, Y., Parrish, E. H., Endo, M., Takata, S., Mizukoshi, M., Hikino, K., Takeda, A., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01390-2 · Cited by 54 · see citing works
Enhancer reprogramming: critical roles in cancer and promising therapeutic strategies
Yang, J., Zhou, F., Luo, X., Fang, Y., Wang, X., Liu, X., Xiao, R., Jiang, D., Tang, Y., Yang, G., et al. (2025) · Cell Death Discovery · doi:10.1038/s41420-025-02366-3 · Cited by 50 · see citing works
Decoding enhancer complexity with machine learning and high-throughput discovery
Smith, G. D., Ching, W. H., Cornejo‐Páramo, P., & Wong, E. S. W. (2023) · Genome biology · doi:10.1186/s13059-023-02955-4 · Cited by 43 · see citing works
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 40 · see citing works
Functional dissection of complex trait variants at single-nucleotide resolution
Siraj, L., Castro, R. I., Dewey, H. B., Kales, S., Butts, J. C., Nguyen, T. T. L., Kanai, M., Berenzy, D., Mouri, K., Wang, Q. S., et al. (2026) · Nature · doi:10.1038/s41586-026-10121-6 · Cited by 51 · see citing works
Self-citationNepal, C., & Andersen, J. B. (2023) · Nature Communications · doi:10.1038/s41467-023-38272-4 · Cited by 39 · see citing works
Deep learning the cis-regulatory code of chromatin dynamics during cellular reprogrammingPreprint
Nair, S., Ameen, M., Sundaram, L., Pampari, A., Schreiber, J. M., Balsubramani, A., Wang, Y. X., Burns, D., Blau, H. M., Karakikes, I., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.10.04.560808 · Cited by 38 · see citing works
Winkley, K., Banerjee, D., Louiselle, D. A., Biswell, R. L., Posey, N., Fatheree, K., McDanel, S., Bradley, T., Moffatt, M. E., Koseva, B. S., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-95532-3 · Cited by 37 · see citing works
Choi, J., Kim, S., Kim, J., Son, H., Yoo, S., Kim, C.-U., Park, Y. J., Moon, S., Cha, B., Jeon, M. C., et al. (2023) · Science Advances · doi:10.1126/sciadv.adg6319 · Cited by 34 · see citing works
Epigenetic regulatory layers in the 3D nucleus
Willemin, A., Szabó, D., & Pombo, A. (2024) · Molecular Cell · doi:10.1016/j.molcel.2023.12.032 · Cited by 38 · see citing works
Chen, P.-S. B., Fiaux, P. C., Zhang, K., Li, B., Kubo, N., Jiang, S., Hu, R., Rooholfada, E., Wu, S.-H., Wang, M.-C., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111630 · Cited by 31 · see citing works
De novo human brain enhancers created by single-nucleotide mutations
Li, S., Hannenhalli, S. S., & Ovcharenko, I. (2023) · Science Advances · doi:10.1126/sciadv.add2911 · Cited by 33 · see citing works
iDHS-Deep: an integrated tool for predicting DNase I hypersensitive sites by deep neural network
Dao, F., Lv, H., Su, W., Sun, Z., Huang, Q.-L., & Lin, H. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab047 · Cited by 36 · see citing works
Zhang, P., Amarasinghe, H. E., Whalley, J. P., Tay, C., Fang, H., Migliorini, G., Brown, A., Allcock, A., Scozzafava, G., Rath, P., et al. (2022) · Genome biology · doi:10.1186/s13059-022-02702-1 · Cited by 35 · see citing works
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 37 · see citing works
Preeclampsia risk prediction from prenatal cell-free DNA screening
Adil, M., Kolarova, T. R., Doebley, A.-L., Chen, L. A., Tobey, C. L., Galipeau, P. C., Rosen, S., Yang, M., Colbert, B. G., Patton, R. D., et al. (2025) · Nature Medicine · doi:10.1038/s41591-025-03509-w · Cited by 36 · see citing works
Kaplow, I. M., Schäffer, D. E., Wirthlin, M. E., Lawler, A. J., Brown, A. R., Kleyman, M., & Pfenning, A. R. (2022) · BMC Genomics · doi:10.1186/s12864-022-08450-7 · Cited by 35 · see citing works
de Sompele, S. V., Small, K. W., Cicekdal, M. B., López-Soriano, V., D’haene, E., Shaya, F. S., Agemy, S. A., der Snickt, T. V., Rey, A. D., Rosseel, T., et al. (2022) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2022.09.013 · Cited by 33 · see citing works
DaSilva, L. F., Senan, S., Patel, Z. M., Reddy, A. J., Gabbita, S., Nussbaum, Z., Córdova, C. M. V., Wenteler, A., Weber, N., Tunjic, T. M., et al. (2024) · doi:10.1101/2024.02.01.578352 · Cited by 32 · see citing works
Self-citationZhang, Z., Xu, P., Hu, Z., Fu, Z., Deng, T., Deng, X., Peng, L., Xie, Y., Long, L., Zheng, D., et al. (2022) · International Journal of Biological Sciences · doi:10.7150/ijbs.69332 · Cited by 30 · see citing works
Annotating the genome at single-nucleotide resolution with DNA foundation models
de Almeida, B. P., Dalla-Torre, H., Richard, G., Blum, C. F., Hexemer, L., Gélard, M., Mendoza‐Revilla, J., Tang, Z., Marin, F. I., Emms, D., et al. (2025) · Nature Methods · doi:10.1038/s41592-025-02881-2 · Cited by 35 · see citing works
TF-COMB – Discovering grammar of transcription factor binding sites
Bentsen, M. S., Heger, V., Schultheis, H., Kuenne, C. T., & Looso, M. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.07.025 · Cited by 31 · see citing works
Yin, C., Castillo-Hair, S. M., Byeon, G. W., Bromley, P., Meuleman, W. R. A., & Seelig, G. (2025) · Cell Systems · doi:10.1016/j.cels.2025.101302 · Cited by 29 · see citing works
Self-citationSomatic epimutations cap genetic determinism in the human diploid chromatin epigenomePreprint
Vollger, M. R., Swanson, E. G., Neph, S. J., Mallory, B. J., Dubocanin, D., Ho, C., Cheng, Y. H. H., Ranchalis, J. E., Munson, K. M., Sedeño-Cortés, A. E., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.06.14.599122 · Cited by 30 · see citing works
Mehmood, F., Arshad, S., & Shoaib, M. (2024) · Briefings in Bioinformatics · doi:10.1093/bib/bbae030 · Cited by 29 · see citing works
Mapping enhancer–gene regulatory interactions from single-cell data
Sheth, M. U., Qiu, W., Ma, X. R., Gschwind, A. R., Jagoda, E., Tan, A. S., Galante, J., Ray, J., Amgalan, D., Einarsson, H., et al. (2026) · Nature Genetics · doi:10.1038/s41588-026-02695-8 · Cited by 29 · see citing works
Yousefi, S., Deng, R., Lanko, K., Salsench, E. M., Nikoncuk, A., van der Linde, H. C., Perenthaler, E., van Ham, T. J., Mulugeta, E., & Barakat, T. S. (2021) · Genome Medicine · doi:10.1186/s13073-021-00980-1 · Cited by 25 · see citing works
Seq2science: an end-to-end workflow for functional genomics analysis
van der Sande, M., Frölich, S., Schäfers, T., Smits, J. G. A., Snabel, R. R., Rinzema, S., & van Heeringen, S. J. (2023) · PeerJ · doi:10.7717/peerj.16380 · Cited by 28 · see citing works
Styrkársdóttir, U., Stefánsdóttir, L., Þorleifsson, G., Stefánsson, Ó. A., Saevarsdóttir, S., Lund, S. H., Rafnar, Þ., Hoshijima, K., Novak, K. A., Oreiro, N., et al. (2023) · Annals of the Rheumatic Diseases · doi:10.1136/ard-2022-223468 · Cited by 28 · see citing works
Pezoulas, V. C., Hazapis, O. G., Lаgopati, N., Exarchos, T. P., Goules, A. V., Tzioufas, A. G., Fotiadis, D. I., Stratis, I. G., Yannacopoulos, A. N., & Gorgoulis, V. G. (2021) · Cancer Genomics & Proteomics · doi:10.21873/cgp.20284 · Cited by 29 · see citing works
Wang, H., Huang, B., & Wang, J. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab841 · Cited by 26 · see citing works
Saldana-Guerrero, I. M., Montano-Gutierrez, L. F., Boswell, K., Hafemeister, C., Poon, E., Shaw, L. E., Stavish, D., Lea, R. A., Wernig-Zorc, S., Bozsaky, E., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-47945-7 · Cited by 25 · see citing works
Fan, K., Moore, J. E., Zhang, X.-O., & Weng, Z. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab345 · Cited by 22 · see citing works
Zaurín, R., Ferrari, R., Nacht, A. S., Carbonell‐Caballero, J., Dily, F. L., Font-Mateu, J., de Llobet, L., Vidal, E., Lioutas, A., Beato, M., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab1125 · Cited by 25 · see citing works
An organism-wide ATAC-seq peak catalog for the bovine and its use to identify regulatory variantsPreprint
Yuan, C., Tang, L., Lopdell, T., Петров, В. А., Oget, C., Moreira, G. C. M., Duarte, J. L. G., Sartelet, A., Cheng, Z., Salavati, M., et al. (2023) · Genome Research · doi:10.1101/gr.277947.123 · Cited by 28 · see citing works
Context transcription factors establish cooperative environments and mediate enhancer communication
Kribelbauer-Swietek, J. F., Pushkarev, O., Gardeux, V., Faltejsková, K., Russeil, J., van Mierlo, G., & Deplancke, B. (2024) · Nature Genetics · doi:10.1038/s41588-024-01892-7 · Cited by 22 · see citing works
Rauner, M., Foessl, I., Formosa, M. M., Kague, É., Prijatelj, V., Alonso, N., Banerjee, B., Bergen, D. J. M., Busse, B., Calado, Â., et al. (2021) · Frontiers in Endocrinology · doi:10.3389/fendo.2021.731217 · Cited by 23 · see citing works
Abatti, L. E., Lado‐Fernández, P., Huynh, L., Collado, M., Hoffman, M. M., & Mitchell, J. A. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad734 · Cited by 23 · see citing works
Serum Protein Exposure Activates a Core Regulatory Program Driving Human Proximal Tubule Injury
Lidberg, K. A., Muthusamy, S., Adil, M., Mahadeo, A., Yang, J., Patel, R. S., Wang, L., Bammler, T. K., Reichel, J. B., Yeung, C. K., et al. (2022) · Journal of the American Society of Nephrology · doi:10.1681/asn.2021060751 · Cited by 22 · see citing works
- Authors
- Meuleman, W., Muratov, A., Rynes, E., Halow, J., Lee, K., Bates, D., Diegel, M., Dunn, D., Neri, F., Teodosiadis, A., Reynolds, A., Haugen, E., Nelson, J., Johnson, A., Frerker, M., Buckley, M., Sandstrom, R., Vierstra, J., Kaul, R., & Stamatoyannopoulos, J.
- Affiliations
- Altius Institute for Biomedical Sciences (US)
- University of Washington (US)
- Corresponding author
- Meuleman, Wouter
- Stamatoyannopoulos, John
- ORCID
- Venue
- Nature
- Published
- 2020-07-29
- Volume
- 584
- Issue
- 7820
- Pages
- 244-251
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC7422677
- OpenAlex
- W3046013264
- Cited by
- 331
- References
- 60
- Citations by year
- 2026: 40 · 2025: 59 · 2024: 61 · 2023: 58 · 2022: 56 · 2021: 43 · 2020: 14
- Type
- paratext
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Nature (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Human Genome Research Institute (U54HG007010, UM1HG009444, R35HG011317)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Keywords
- DNase I hypersensitive sites, cis-regulatory elements, genetic association signals, heritability
- MeSH terms
- Chromatin, Deoxyribonuclease I, DNA, Gene Expression Regulation, Genes, Humans, Promoter Regions, Genetic, Regulatory Sequences, Nucleic Acid, Genome, Human, Molecular Sequence Annotation
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