Genetic determinants of co-accessible chromatin regions in activated T cells across humans
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Abstract
Over 90% of genetic variants associated with complex human traits map to non-coding regions, but little is understood about how they modulate gene regulation in health and disease. One possible mechanism is that genetic variants affect the activity of one or more cis-regulatory elements leading to gene expression variation in specific cell types. To identify such cases, we analyzed ATAC-seq and RNA-seq profiles from stimulated primary CD4+ T cells in up to 105 healthy donors. We found that regions of accessible chromatin (ATAC-peaks) are co-accessible at kilobase and megabase resolution, consistent with the three-dimensional chromatin organization measured by in situ Hi-C in T cells. Fifteen percent of genetic variants located within ATAC-peaks affected the accessibility of the corresponding peak (local-ATAC-QTLs). Local-ATAC-QTLs have the largest effects on co-accessible peaks, are associated with gene expression and are enriched for autoimmune disease variants. Our results provide insights into how natural genetic variants modulate cis-regulatory elements, in isolation or in concert, to influence gene expression.
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Variants associated with chromatin accessibility capture stimulus-sensitive signals and explain a significant proportion of heritability, even more so than eQTLs.
“Second, it has been recently shown that the variants associated with chromatin accessibility capture stimulus-sensitive signals and explain a significant proportion of heritability, even more so than eQTLs47,48.”
From A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles (2020) · cites this paper as [48]
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Cites
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106 · see citing works
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 · see citing works
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607 · see citing works
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437 · see citing works
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
Li, B., & Dewey, C. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-323 · Cited by 22,179 · see citing works
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386 · see citing works
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072 · see citing works
Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y. C., Laslo, P., Cheng, J. X., Murre, C., Singh, H., & Glass, C. K. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.05.004 · Cited by 13,382 · see citing works
Fast and accurate long-read alignment with Burrows-Wheeler transform.
Li, H., & Durbin, R. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp698 · Cited by 12,063 · 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
A 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping
Rao, S. S. P., Huntley, M. H., Durand, N. C., Stamenova, E. K., Bochkov, I. D., Robinson, J. T., Sanborn, A. L., Machol, I., Omer, A. D., Lander, E. S., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.021 · Cited by 9,212 · see citing works
Self-citationGCTA: a tool for genome-wide complex trait analysis
Yang, J., Lee, S. H., Goddard, M. E., & Visscher, P. M. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.11.011 · Cited by 8,279 · see citing works
Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets.
Macosko, E. Z., Basu, A., Satija, R., Nemesh, J., Shekhar, K., Goldman, M., Tirosh, I., Bialas, A. R., Kamitaki, N., Martersteck, E. M., et al. (2015) · Cell · doi:10.1016/j.cell.2015.05.002 · Cited by 7,110 · see citing works
Self-citationSpatial reconstruction of single-cell gene expression data
Satija, R., Farrell, J. A., Gennert, D., Schier, A. F., & Regev, A. (2015) · Nature Biotechnology · doi:10.1038/nbt.3192 · Cited by 7,055 · see citing works
Self-citationBuenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., & Greenleaf, W. J. (2013) · Nature Methods · doi:10.1038/nmeth.2688 · Cited by 6,422 · see citing works
Self-citationIntegrative 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
Master Transcription Factors and Mediator Establish Super-Enhancers at Key Cell Identity Genes
Whyte, W. A., Orlando, D. A., Hnisz, D., Abraham, B. J., Lin, C. Y., Kagey, M. H., Rahl, P. B., Lee, T. I., & Young, R. A. (2013) · Cell · doi:10.1016/j.cell.2013.03.035 · Cited by 4,143 · see citing works
Type 2 diabetes as an inflammatory disease
Donath, M. Y., & Shoelson, S. E. (2011) · Nature Reviews Immunology · doi:10.1038/nri2925 · Cited by 3,737 · see citing works
Juicer Provides a One-Click System for Analyzing Loop-Resolution Hi-C Experiments
Durand, N. C., Shamim, M. S., Machol, I., Rao, S. S. P., Huntley, M. H., Lander, E. S., & Aiden, E. L. (2016) · Cell Systems · doi:10.1016/j.cels.2016.07.002 · Cited by 3,724 · see citing works
Self-citationSystematic 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
Super-enhancers in the control of cell identity and disease
Hnisz, D., Abraham, B. J., Lee, T. I., Lau, A., Saint-André, V., Sigova, A. A., Hoke, H. A., & Young, R. A. (2013) · Cell · doi:10.1016/j.cell.2013.09.053 · Cited by 3,662 · see citing works
Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells
Klein, A. M., Mazutis, L., Akartuna, I., Tallapragada, N., Veres, A., Li, V., Peshkin, L., Weitz, D. A., & Kirschner, M. W. (2015) · Cell · doi:10.1016/j.cell.2015.04.044 · Cited by 3,356 · see citing works
Genome-wide association studies for complex traits: consensus, uncertainty and challenges
McCarthy, M. I., Abecasis, G. R., Cardon, L. R., Goldstein, D. B., Little, J., Ioannidis, J. P. A., & Hirschhorn, J. N. (2008) · Nature Reviews Genetics · doi:10.1038/nrg2344 · Cited by 2,891 · see citing works
Genome-wide association studies for common diseases and complex traits
Hirschhorn, J. N., & Daly, M. J. (2005) · Nature Reviews Genetics · doi:10.1038/nrg1521 · Cited by 2,853 · 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
Partitioning 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
Franke, A., McGovern, D. P. B., Barrett, J. C., Wang, K., Radford-Smith, G. L., Ahmad, T., Lees, C. W., Balschun, T., Lee, J., Roberts, R., et al. (2010) · Nature Genetics · doi:10.1038/ng.717 · Cited by 2,520 · see citing works
Deaglio, S., Dwyer, K. M., Gao, W., Friedman, D. J., Usheva, A., Erat, A., Chen, J., Enjyoji, K., Linden, J. M., Oukka, M., et al. (2007) · The Journal of Experimental Medicine · doi:10.1084/jem.20062512 · Cited by 2,478 · see citing works
Visscher, P. M., Brown, M. A., McCarthy, M. I., & Yang, J. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.11.029 · Cited by 2,425 · see citing works
Single-cell chromatin accessibility reveals principles of regulatory variation
Buenrostro, J. D., Wu, B., Litzenburger, U. M., Ruff, D., Gonzales, M. L., Snyder, M. P., Chang, H. Y., & Greenleaf, W. J. (2015) · Nature · doi:10.1038/nature14590 · Cited by 2,308 · see citing works
Self-citationInflammation-induced cancer: Crosstalk between tumours, immune cells and microorganisms
Elinav, E., Nowarski, R., Thaiss, C. A., Hu, B., Jin, C., & Flavell, R. A. (2013) · Nature reviews. Cancer · doi:10.1038/nrc3611 · Cited by 2,000 · see citing works
Genetic and epigenetic fine mapping of causal autoimmune disease variants
Farh, K. K.-H., Marson, A., Zhu, J., Kleinewietfeld, M., Housley, W. J., Beik, S., Shoresh, N., Whitton, H., Ryan, R. J. H., Shishkin, A. A., et al. (2015) · Nature · doi:10.1038/nature13835 · Cited by 1,956 · see citing works
Transcriptome and genome sequencing uncovers functional variation in humans
The Geuvadis Consortium, Lappalainen, T., Sammeth, M., Friedländer, M. R., ‘t Hoen, P. A. C., Monlong, J., Rivas, M. A., Gonzàlez-Porta, M., Kurbatova, N., Griebel, T., et al. (2013) · Nature · doi:10.1038/nature12531 · Cited by 1,888 · see citing works
Matrix eQTL: ultra fast eQTL analysis via large matrix operations
Shabalin, A. A. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts163 · Cited by 1,694 · see citing works
Adoptive immunotherapy for cancer: harnessing the T cell response
Restifo, N. P., Dudley, M. E., & Rosenberg, S. A. (2012) · Nature Reviews Immunology · doi:10.1038/nri3191 · Cited by 1,688 · see citing works
CTCF: Master Weaver of the Genome
Phillips‐Cremins, J. E., & Corces, V. G. (2009) · Cell · doi:10.1016/j.cell.2009.06.001 · Cited by 1,540 · see citing works
Architecture of the human regulatory network derived from ENCODE data
Gerstein, M., Kundaje, A. B., Hariharan, M., Landt, S. G., Yan, K., Cheng, C., Mu, X. J., Khurana, E., Rozowsky, J. S., Alexander, R. P., et al. (2012) · Nature · doi:10.1038/nature11245 · Cited by 1,418 · see citing works
Self-citationMultiplexed droplet single-cell RNA-sequencing using natural genetic variation
Kang, H. M., Subramaniam, M., Targ, S., Nguyen, M., Maliskova, L., McCarthy, E., Wan, E., Wong, S., Byrnes, L., Lanata, C. M., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4042 · Cited by 1,339 · cited 1× · see citing works
“With the recent advancement of single cell epigenomic 65 and transcriptomic 66,67,68 profiling, it should be possible to more directly detect context-specific genetic effects in a heterogeneous cell population.”
Self-citationThe Allelic Landscape of Human Blood Cell Trait Variation and Links to Common Complex Disease
Astle, W. J., Elding, H., Jiang, T., Allen, D., Ruklisa, D., Mann, A. L., Mead, D., Bouman, H., Riveros-Mckay, F., Kostadima, M. A., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.042 · Cited by 1,224 · see citing works
Population genomics of human gene expression
Stranger, B. E., Nica, A. C., Forrest, M. S., Dimas, A. S., Bird, C., Beazley, C., Ingle, C., Dunning, M., Flicek, P., Koller, D., et al. (2007) · Nature Genetics · doi:10.1038/ng2142 · Cited by 1,132 · see citing works
Natural regulatory T cells in infectious disease
Belkaid, Y., & Rouse, B. T. (2005) · Nature Immunology · doi:10.1038/ni1181 · Cited by 1,036 · see citing works
Hicks, R., & Tingley, D. H. (2011) · The Stata Journal Promoting communications on statistics and Stata · doi:10.1177/1536867x1201100407 · Cited by 810 · see citing works
An expansive human regulatory lexicon encoded in transcription factor footprints
Neph, S. J., Vierstra, J. D., Stergachis, A. B., Reynolds, A. P., Haugen, E., Vernot, B., Thurman, R. E., John, S., Sandstrom, R. S., Johnson, A., et al. (2012) · Nature · doi:10.1038/nature11212 · Cited by 746 · see citing works
CTCF mediates long-range chromatin looping and local histone modification in the beta-globin locus.
Splinter, E., Heath, H., Kooren, J., Palstra, R.-J., Klous, P., Grosveld, F., Galjart, N., & de Laat, W. (2007) · Genes & Development · doi:10.1016/j.bcmd.2006.10.131 · Cited by 742 · see citing works
Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells
Chen, L., Ge, B., Casale, F. P., Vasquez, L., Kwan, T., Garrido-Martín, D., Watt, S., Yan, Y., Kundu, K., Ecker, S., et al. (2016) · Cell · doi:10.1016/j.cell.2016.10.026 · Cited by 679 · see citing works
CTCF mediates long-range chromatin looping and local histone modification in the β-globin locus
Splinter, E., Heath, H., Kooren, J., Palstra, R.-J., Klous, P., Grosveld, F., Galjart, N., & de Laat, W. (2006) · Genes & Development · doi:10.1101/gad.399506 · Cited by 677 · see citing works
DNase I sensitivity QTLs are a major determinant of human expression variation
Degner, J. F., Pai, A. A., Piqué-Regi, R., Veyrieras, J., Gaffney, D. J., Pickrell, J. K., Leon, S. D., Michelini, K., Lewellen, N., Crawford, G. E., et al. (2012) · Nature · doi:10.1038/nature10808 · Cited by 633 · see citing works
Enjyoji, K., Sévigny, J., Lin, Y., Frenette, P. S., Christie, P. D., Esch, J. S. A., Imai, M., Edelberg, J. M., Rayburn, H., Lech, M., et al. (1999) · Nature Medicine · doi:10.1038/12447 · Cited by 565 · see citing works
Regulatory circuits of T cell function in cancer
Speiser, D. E., Ho, P., & Verdeil, G. (2016) · Nature reviews. Immunology · doi:10.1038/nri.2016.80 · Cited by 559 · see citing works
Battle, A., Mostafavi, S., Zhu, X., Potash, J. B., Weissman, M. M., McCormick, C., Haudenschild, C. D., Beckman, K. B., Shi, J., Mei, R., et al. (2014) · Genome Research · doi:10.1101/gr.155192.113 · Cited by 547 · see citing works
Enhanced Regulatory Sequence Prediction Using Gapped k-mer Features
Ghandi, M., Lee, D., Mohammad-Noori, M., & Beer, M. A. (2014) · PLoS Comput. Biol. · doi:10.1371/journal.pcbi.1003711 · Cited by 514 · see citing works
Self-citationFoxp3+ regulatory T cells: differentiation, specification, subphenotypes
Feuerer, M., Hill, J. A., Mathis, D. J., & Benoist, C. O. (2009) · Nature Immunology · doi:10.1038/ni.1760 · Cited by 507 · see citing works
Self-citationEcto-ATPases: Identities and Functions
Plesner, L. (1995) · International review of cytology · doi:10.1016/s0074-7696(08)62487-0 · Cited by 506 · see citing works
Polarization of the Effects of Autoimmune and Neurodegenerative Risk Alleles in Leukocytes
Raj, T., Rothamel, K., Mostafavi, S., Ye, C., Lee, M. N., Replogle, J. M., Feng, T., Lee, M., Asinovski, N., Frohlich, I., et al. (2014) · Science · doi:10.1126/science.1249547 · Cited by 506 · see citing works
Self-citationJun, G., Flickinger, M., Hetrick, K. N., Romm, J. M., Doheny, K. F., Abecasis, G. R., Boehnke, M., & Kang, H. M. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.09.004 · Cited by 484 · see citing works
Foxp3 Exploits a Pre-Existent Enhancer Landscape for Regulatory T Cell Lineage Specification
Samstein, R. M., Arvey, A., Josefowicz, S. Z., Peng, X., Reynolds, A., Sandstrom, R., Neph, S., Sabo, P., Kim, J. M., Liao, W., et al. (2012) · Cell · doi:10.1016/j.cell.2012.06.053 · Cited by 472 · see citing works
BATF–JUN is critical for IRF4-mediated transcription in T cells
Li, P., Spolski, R. J., Liao, W., Wang, L., Murphy, T. L., MURPHY, K. M. M., & Leonard, W. J. (2012) · Nature · doi:10.1038/nature11530 · Cited by 453 · see citing works
Matrix eQTL: Ultra fast eQTL analysis via large matrix operationsPreprint
Shabalin, A. A. (2011) · arXiv (Cornell University) · doi:10.17615/g28n-r219 · Cited by 452 · see citing works
Identification of Genetic Variants That Affect Histone Modifications in Human Cells
McVicker, G., van de Geijn, B., Degner, J. F., Cain, C. E., Banovich, N. E., Raj, A., Lewellen, N., Myrthil, M., Gilad, Y., & Pritchard, J. K. (2013) · Science · doi:10.1126/science.1242429 · Cited by 443 · see citing works
Common Genetic Variants Modulate Pathogen-Sensing Responses in Human Dendritic Cells
Lee, M. N., Ye, C., Villani, A.-C., Raj, T., Li, W., Eisenhaure, T. M., Imboywa, S. H., Chipendo, P. I., Ran, F. A., Slowikowski, K., et al. (2014) · Science · doi:10.1126/science.1246980 · Cited by 441 · see citing works
Self-citationA method to predict the impact of regulatory variants from DNA sequence
Lee, D., Gorkin, D. U., Baker, M., Strober, B. J., Asoni, A. L., McCallion, A. S., & Beer, M. (2015) · Nature Genetics · doi:10.1038/ng.3331 · Cited by 417 · see citing works
Self-citationSpecificity through cooperation: BATF–IRF interactions control immune-regulatory networks
Murphy, T. L., Tussiwand, R., & MURPHY, K. M. M. (2013) · Nature reviews. Immunology · doi:10.1038/nri3470 · Cited by 399 · see citing works
Kurachi, M., Barnitz, R. A., Yosef, N., Odorizzi, P. M., DiIorio, M. A., Lemieux, M. E., Yates, K. B., Godec, J., Klatt, M. G., Regev, A., et al. (2014) · Nature Immunology · doi:10.1038/ni.2834 · Cited by 384 · see citing works
Self-citationCoordinated Effects of Sequence Variation on DNA Binding, Chromatin Structure, and Transcription
Kilpinen, H., Waszak, S. M., Gschwind, A. R., Raghav, S. K., Witwicki, R. M., Orioli, A., Migliavacca, E., Wiederkehr, M., Gutierrez-Arcelus, M., Panousis, N. I., et al. (2013) · Science · doi:10.1126/science.1242463 · Cited by 350 · see citing works
Extensive Variation in Chromatin States Across Humans
Kasowski, M., Kyriazopoulou-Panagiotopoulou, S., Grubert, F., Zaugg, J. B., Kundaje, A., Liu, Y., Boyle, A. P., Zhang, Q. C., Zakharia, F., Spacek, D. V., et al. (2013) · Science · doi:10.1126/science.1242510 · Cited by 339 · see citing works
Regulation of immunity by self-reactive T cells
Kronenberg, M., & Rudensky, A. Y. (2005) · Nature · doi:10.1038/nature03725 · Cited by 309 · see citing works
Sun, X., Wu, Y., Gao, W., Enjyoji, K., Csizmadia, E., Müller, C. E., Murakami, T., & Robson, S. C. (2010) · Gastroenterology · doi:10.1053/j.gastro.2010.05.007 · Cited by 279 · see citing works
Fine-mapping cellular QTLs with RASQUAL and ATAC-seq
Kumasaka, N., Knights, A. J., & Gaffney, D. J. (2015) · Nature Genetics · doi:10.1038/ng.3467 · Cited by 259 · see citing works
ATAC-see reveals the accessible genome by transposase-mediated imaging and sequencing
Chen, X., Shen, Y., Draper, W. E., Buenrostro, J. D., Litzenburger, U. M., Cho, S. W., Satpathy, A. T., Carter, A. C., Ghosh, R. P., East-Seletsky, A., et al. (2016) · Nature Methods · doi:10.1038/nmeth.4031 · Cited by 258 · see citing works
Self-citationIntersection of population variation and autoimmunity genetics in human T cell activation
Ye, C. J., Feng, T., Kwon, H.-K., Raj, T., Wilson, M. T., Asinovski, N., McCabe, C., Lee, M. H., Frohlich, I., Paik, H.-I., et al. (2014) · Science · doi:10.1126/science.1254665 · Cited by 236 · see citing works
Self-citationPopulation 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 · cited 1× · see citing works
“Most of the associated SNPs in these studies were also associated with nearby transcript abundance, suggesting the genetic perturbation of cis-regulatory activity as a determinant of gene expression variability 11,12,19,21,23 .”
CTCF-dependent enhancer-blocking by alternative chromatin loop formation
Hou, C., Zhao, H., Tanimoto, K., & Dean, A. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0808506106 · Cited by 205 · see citing works
DNA Specificity Determinants Associate with Distinct Transcription Factor Functions
Hollenhorst, P. C., Chandler, K. J., Poulsen, R. L., Johnson, W. E., Speck, N. A., & Graves, B. J. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000778 · Cited by 198 · see citing works
gkmSVM: an R package for gapped-kmer SVM
Ghandi, M., Mohammad-Noori, M., Ghareghani, N., Lee, D., Garraway, L. A., & Beer, M. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw203 · Cited by 186 · see citing works
Self-citationStroud, C. K., Nara, T., Roqueta‐Rivera, M., Radlowski, E. C., Lawrence, P., Zhang, Y., Cho, B. H., Segre, M., Hess, R. A., Brenna, J. T., et al. (2009) · Journal of Lipid Research · doi:10.1194/jlr.m900039-jlr200 · Cited by 174 · see citing works
Transcriptional risk scores link GWAS to eQTLs and predict complications in Crohn's disease
Marigorta, U. M., Denson, L. A., Hyams, J. S., Mondal, K., Prince, J., Walters, T. D., Griffiths, A., Noe, J. D., Crandall, W. V., Rosh, J. R., et al. (2017) · Nature Genetics · doi:10.1038/ng.3936 · Cited by 166 · see citing works
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 150 · see citing works
T-cell signalling and autoimmunity: molecular mechanisms of disease
Ohashi, P. S. (2002) · Nature reviews. Immunology · doi:10.1038/nri822 · Cited by 148 · see citing works
Prostaglandin E2, an Immunoactivator
Sakata, D., Yao, C., & Narumiya, S. (2010) · Journal of Pharmacological Sciences · doi:10.1254/jphs.09r03cp · Cited by 126 · see citing works
The TGF-β-Smad3 pathway inhibits CD28-dependent cell growth and proliferation of CD4 T cells
Delisle, J., Giroux, M., Boucher, G., Landry, J.-R., Hardy, M.-P., Lemieux, S., Jones, R. G., Wilhelm, B. T., & Perreault, C. (2013) · Genes and Immunity · doi:10.1038/gene.2012.63 · Cited by 82 · see citing works
Characterization of an arachidonic acid-deficient (Fads1 knockout) mouse model
Fan, Y.-Y., Monk, J. M., Hou, T. Y., Callway, E., Vincent, L. L., Weeks, B. R., Yang, P., & Chapkin, R. S. (2012) · Journal of Lipid Research · doi:10.1194/jlr.m024216 · Cited by 77 · see citing works
Cauchy, P., Maqbool, M. A., Cabeza, J. Z., Vanhille, L., Koch, F., Fenouil, R., Gut, M., Gut, I. G., Santana, M. A., Griffon, A., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1475 · Cited by 50 · see citing works
Barrie, A. M., Khare, A., Henkel, M., Zhang, Y., Barmada, M. M., Duerr, R. H., & Ray, A. (2011) · Clinical and Translational Science · doi:10.1111/j.1752-8062.2011.00300.x · Cited by 30 · see citing works
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Chromatin accessibility profiling by ATAC-seq
Grandi, F. C., Modi, H., Kampman, L., & Corces, M. R. (2022) · Nature Protocols · doi:10.1038/s41596-022-00692-9 · Cited by 557 · see citing works
Mimitou, E. P., Lareau, C. A., Chen, K. Y., Zorzetto-Fernandes, A. L., Hao, Y., Takeshima, Y., Luo, W., Huang, T.-S., Yeung, B. Z., Papalexi, E., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-00927-2 · Cited by 529 · see citing works
Self-citationA cis-regulatory atlas in maize at single-cell resolution
Marand, A. P., Chen, Z., Gallavotti, A., & Schmitz, R. J. (2021) · Cell · doi:10.1016/j.cell.2021.04.014 · Cited by 379 · see citing works
Sey, N. Y. A., Hu, B., Mah, W., Fauni, H., McAfee, J. C., Rajarajan, P., Brennand, K. J., Akbarian, S., & Won, H. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0603-0 · Cited by 297 · see citing works
Landscape of stimulation-responsive chromatin across diverse human immune cells
Calderon, D., Nguyen, M. L. T., Mezger, A., Kathiria, A. S., Müller, F., Nguyen, V. Q., Lescano, N., Wu, B., Trombetta, J. J., Ribado, J. V., et al. (2019) · Nature Genetics · doi:10.1038/s41588-019-0505-9 · Cited by 282 · see citing works
Epigenetic scars of CD8+ T cell exhaustion persist after cure of chronic infection in humans
Yates, K. B., Tonnerre, P., Martin, G. E., Gerdemann, U., Abosy, R. A., Comstock, D. E., Weiss, S. A., Wolski, D., Tully, D. C., Chung, R. T., et al. (2021) · Nature Immunology · doi:10.1038/s41590-021-00979-1 · Cited by 253 · see citing works
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., Marbach, D., et al. (2019) · Science · doi:10.1126/science.aat8266 · Cited by 168 · see citing works
Epigenomic dissection of Alzheimer’s disease pinpoints causal variants and reveals epigenome erosion
Xiong, X., James, B. T., Boix, C. A., Park, Y. P., Galani, K., Victor, M. B., Sun, N., Hou, L., Ho, L.-L., Mantero, J., et al. (2023) · Cell · doi:10.1016/j.cell.2023.08.040 · Cited by 205 · see citing works
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 · see citing works
Zhang, Z. S., Luo, K., Zou, Z., Qiu, M., Tian, J., Sieh, L., Shi, H., Zou, Y., Wang, G. T., Morrison, J., et al. (2020) · Nature Genetics · doi:10.1038/s41588-020-0644-z · Cited by 187 · see citing works
Landscape of allele-specific transcription factor binding in the human genome
Abramov, S., Boytsov, A., Bykova, D., Penzar, D., Yevshin, I., Kolmykov, S. K., Fridman, M. V., Favorov, A. V., Vorontsov, I. E., Baulin, E. F., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23007-0 · Cited by 179 · see citing works
Sheng, X., Guan, Y., Ma, Z., Wu, J., Liu, H., Qiu, C., Vitale, S., Miao, Z., Seasock, M. J., Palmer, M., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00909-9 · Cited by 153 · see citing works
Turner, A. W., Hu, S. S., Mosquera, J. V., Feng, W., Hodonsky, C. J., Wong, D., Auguste, G. E., Song, Y., Sol‐Church, K., Farber, E., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01069-0 · Cited by 151 · see citing works
Madsen, J. G. S., Madsen, M. S., Rauch, A., Traynor, S., Hauwaert, E. L. V., Haakonsson, A. K., Javierre, B. M., Hyldahl, M., Fraser, P., & Mandrup, S. (2020) · Nature Genetics · doi:10.1038/s41588-020-0709-z · Cited by 94 · see citing works
Liang, D., Elwell, A. L., Aygün, N., Krupa, O., Wolter, J. M., Kyere, F. A., Lafferty, M. J., Cheek, K. E., Courtney, K. P., Yusupova, M., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00858-w · Cited by 83 · see citing works
Statistical methods for SNP heritability estimation and partition: A review
Zhu, H., & Zhou, X. (2020) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2020.06.011 · Cited by 95 · see citing works
Chen, X., Sunkel, B. D., Wang, M., Kang, S., Wang, T., Gnanaprakasam, J. R., Liu, L., Cassel, T., Scott, D. A., Muñoz-Cabello, A. M., et al. (2022) · Science Immunology · doi:10.1126/sciimmunol.abm8161 · Cited by 93 · see citing works
Epigenomes of Human Hearts Reveal New Genetic Variants Relevant for Cardiac Disease and Phenotype
Tan, W. L. W., Anene-Nzelu, C. G., Wong, E., Lee, C. J. M., Tan, H. S., Tang, S. J., Perrin, A., Wu, K. X., Zheng, W., Ashburn, R. J., et al. (2020) · Circulation Research · doi:10.1161/circresaha.120.317254 · Cited by 91 · see citing works
Deciphering the impact of genomic variation on function
Writing group (ordered by contribution), Engreitz, J., Lawson, H. A., Singh, H., Starita, L. M., Hon, G. C., Carter, H. K., Sahni, N., Reddy, T. E., Lin, X., et al. (2024) · Nature · doi:10.1038/s41586-024-07510-0 · Cited by 91 · see citing works
Genetic and Epigenetic Biomarkers of Immune Checkpoint Blockade Response
Xiao, Q., Nobre, A., Piñeiro, P., Berciano‐Guerrero, M., Alba, E., Cobo, M., Lauschke, V. M., & Barragán, I. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9010286 · Cited by 82 · 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
Multi-level remodelling of chromatin underlying activation of human T cells
Bediaga, N. G., Coughlan, H. D., Johanson, T. M., Garnham, A. L., Naselli, G., Schröder, J., Fearnley, L. G., Bandala‐Sanchez, E., Allan, R. S., Smyth, G. K., et al. (2021) · Scientific Reports · doi:10.1038/s41598-020-80165-9 · Cited by 80 · 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
Yang, J., McGovern, A., Martin, P., Duffus, K., Ge, X. J., Zarrineh, P., Morris, A. P., Adamson, A. D., Fraser, P., Rattray, M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18180-7 · Cited by 71 · 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
Fine-mapping cis-regulatory variants in diverse human populations
Tehranchi, A. K., Hie, B., Dacre, M., Kaplow, I. M., Pettie, K. P., Combs, P. A., & Fraser, H. B. (2019) · eLife · doi:10.7554/elife.39595 · Cited by 65 · 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
Tissue-specific enhancer–gene maps from multimodal single-cell data identify causal disease alleles
Sakaue, S., Weinand, K., Isaac, S., Dey, K. K., Jagadeesh, K. A., Kanai, M., Watts, G. F. M., Zhu, Z., Accelerating Medicines Partnership® RA/SLE Program and Network, Albrecht, J., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01682-1 · Cited by 60 · see citing works
Genetic effects on liver chromatin accessibility identify disease regulatory variants.
Currin, K. W., Erdos, M., Narisu, N., Rai, V., Vadlamudi, S., Perrin, H. J., Idol, J. R., Yan, T.-F., Albanus, R. D., Broadaway, K. A., et al. (2021) · American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.05.001 · Cited by 55 · see citing works
Dong, P., Tu, X., Liang, Z., Kang, B., & Zhong, S. (2020) · Journal of Experimental Botany · doi:10.1093/jxb/eraa220 · Cited by 59 · see citing works
van der Veeken, J., Zhong, Y., Sharma, R., Mažutis, L., Dao, P. H., Pe’er, D., Leslie, C. S., & Rudensky, A. Y. (2019) · Immunity · doi:10.1016/j.immuni.2019.03.031 · Cited by 53 · see citing works
Unravelling the complex genetics of common kidney diseases: from variants to mechanisms
Sullivan, K. M., & Suszták, K. (2020) · Nature Reviews Nephrology · doi:10.1038/s41581-020-0298-1 · Cited by 51 · see citing works
Mechanisms underlying divergent responses of genetically distinct macrophages to IL-4
Hoeksema, M. A., Shen, Z., Holtman, I. R., Zheng, A., Spann, N. J., Cobo, I., Gymrek, M., & Glass, C. K. (2021) · Science Advances · doi:10.1126/sciadv.abf9808 · Cited by 50 · see citing works
Xu, H., Zhang, S., Yi, X., Plewczyński, D., & Li, M. J. (2020) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2020.02.013 · Cited by 48 · see citing works
Method of moments framework for differential expression analysis of single-cell RNA sequencing data
Kim, M. C., Gate, R. E., Lee, D. S., Tolopko, A., Lu, A. C., Gordon, E. D., Shifrut, E., García-Nieto, P. E., Marson, A., Ntranos, V., et al. (2024) · Cell · doi:10.1016/j.cell.2024.09.044 · Cited by 46 · see citing works
Self-citationHsiao, F., Frouard, J., Gramatica, A., Xie, G., Telwatte, S., Lee, G. Q., Roychoudhury, P., Schwarzer, R., Luo, X., Yukl, S. A., et al. (2020) · PLoS Pathogens · doi:10.1371/journal.ppat.1008450 · Cited by 43 · see citing works
Arthur, T. D., Nguyen, J., Henson, B. A., D’Antonio‐Chronowska, A., Jaureguy, J., Silva, N., Arias, A. D., Benaglio, P., Berggren, W. T., Borja, V., et al. (2025) · Cell Genomics · doi:10.1016/j.xgen.2025.100775 · Cited by 39 · see citing works
Multitissue H3K27ac profiling of GTEx samples links epigenomic variation to disease
Hou, L., Xiong, X., Park, Y., Boix, C. A., James, B. T., Sun, N., He, L., Patel, A., Zhang, Z., Molinié, B., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01509-5 · Cited by 37 · see citing works
Grishin, D., & Gusev, A. (2022) · Nature Genetics · doi:10.1038/s41588-022-01075-2 · Cited by 29 · see citing works
Epigenomic charting and functional annotation of risk loci in renal cell carcinoma
Nassar, A. H., Alaiwi, S. A., Baca, S. C., Adib, E., Corona, R. I., Seo, J.-H., Fonseca, M. A., Spisák, S., Zarif, T. E., Tisza, V., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-35833-5 · Cited by 37 · see citing works
Genome-wide association studies identify the role of caspase-9 in kidney disease
Doke, T., Huang, S.-Z., Qiu, C.-X., Sheng, X., Seasock, M. J., Liu, H.-B., Ma, Z., Palmer, M., & Suszták, K. (2021) · Science Advances · doi:10.1126/sciadv.abi8051 · Cited by 29 · see citing works
Self-citationGenetics and Epigenetics of Sex Bias: Insights from Human Cancer and Autoimmunity
Credendino, S. C., Neumayer, C., & Cantone, I. (2020) · Trends in Genetics · doi:10.1016/j.tig.2020.06.016 · Cited by 35 · see citing works
Schoonhoven, A. O.-V., de Bruijn, M. J. W., Stikker, B., Brouwer, R. W. W., Braunstahl, G., van IJcken, W. F. J., Graf, T., Huylebroeck, D., Hendriks, R. W., Stik, G., et al. (2023) · Science Immunology · doi:10.1126/sciimmunol.adg3917 · Cited by 34 · see citing works
Cannon, M. E., Currin, K. W., Young, K. L., Perrin, H. J., Vadlamudi, S., Safi, A., Song, L., Wu, Y., Wabitsch, M., Laakso, M., et al. (2019) · G3 Genes Genomes Genetics · doi:10.1534/g3.119.400294 · Cited by 32 · see citing works
Human brain vascular multi-omics elucidates disease-risk associations
Reid, M. M., Menon, S., Liu, H., Zhou, H., Hu, Z., Frerich, S., Ding, B., Oveisgharan, S., Zhang, Z., Nelson, S., et al. (2025) · Neuron · doi:10.1016/j.neuron.2025.07.001 · Cited by 33 · see citing works
Epigenetics of T cell fate decision
Pace, L., & Amigorena, S. (2020) · Current Opinion in Immunology · doi:10.1016/j.coi.2020.01.002 · Cited by 29 · see citing works
Enhancer Predictions and Genome-Wide Regulatory Circuits
Beer, M., Shigaki, D., & Huangfu, D. (2020) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-121719-010946 · Cited by 27 · see citing works
Self-citationWong, Y. Y., Harbison, J. E., Hope, C. M., Gundsambuu, B., Brown, K. A., Wong, S. W., Brown, C. Y., Couper, J., Breen, J., Liu, N., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-32256-6 · Cited by 29 · see citing works
Deconvoluting the heterogeneity of SLE: The contribution of ancestry
Owen, K. A., Grammer, A. C., & Lipsky, P. E. (2021) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2021.11.005 · Cited by 30 · see citing works
3D genome organization links non-coding disease-associated variants to genes
Orozco, G., Schoenfelder, S., Walker, N. J., Eyre, S., & Fraser, P. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.995388 · Cited by 27 · see citing works
Evolution of DNA Methylation in Papio Baboons
Vilgalys, T. P., Rogers, J., Jolly, C. J., Analysis, B. G., Mukherjee, S., & Tung, J. (2018) · Molecular Biology and Evolution · doi:10.1093/molbev/msy227 · Cited by 29 · 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
An autoimmune transcriptional circuit drives FOXP3 + regulatory T cell dysfunction
Sumida, T. S., Lincoln, M. R., He, L., Park, Y., Ota, M., Oguchi, A., Son, R., Yi, A., Stillwell, H. A., Leissa, G. A., et al. (2024) · Science Translational Medicine · doi:10.1126/scitranslmed.adp1720 · Cited by 25 · see citing works
Interpreting Coronary Artery Disease Risk Through Gene–Environment Interactions in Gene Regulation
Findley, A. S., Richards, A. L., Petrini, C., Alazizi, A., Doman, E. R., Shanku, A. G., Davis, G. O., Hauff, N., Sorokin, Y., Wen, X., et al. (2019) · Genetics · doi:10.1534/genetics.119.302419 · Cited by 23 · see citing works
Development of circulating CD4+ T‐cell memory
Soon, M. S. F., Engel, J. A., Lee, H. J., & Haque, A. (2019) · Immunology and Cell Biology · doi:10.1111/imcb.12272 · Cited by 22 · see citing works
Garske, K. M., Pan, D. Z., Miao, Z., Bhagat, Y. V., Comenho, C., Robles, C. R., Benhammou, J. N., Alvarez, M., Ko, A., Ye, C., et al. (2019) · Nature Metabolism · doi:10.1038/s42255-019-0071-6 · Cited by 22 · see citing works
Self-citationZhang, H., Lü, T., Liu, S., Yang, J., Sun, G., Cheng, T., Xu, J., Chen, F., & Yen, K. (2021) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqab094 · Cited by 21 · see citing works
Inferring cell-type-specific causal gene regulatory networks during human neurogenesis
Aygün, N., Liang, D., Crouse, W. L., Keele, G. R., Love, M. I., & Stein, J. L. (2023) · Genome biology · doi:10.1186/s13059-023-02959-0 · Cited by 22 · see citing works
A landscape of gene expression regulation for synovium in arthritis
Jiang, F., Hu, S., Tian, W., Wang, N., Yang, N., Dong, S., Song, H.-M., Zhang, D., Gao, H.-W., Wang, C., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-45652-x · Cited by 22 · see citing works
Identifying genetic variants that influence the abundance of cell states in single-cell data
Rumker, L., Sakaue, S., Reshef, Y., Kang, J. B., Yazar, S., Alquicira-Hernández, J., Valencia, C., Lagattuta, K. A., Mah-Som, A. Y., Nathan, A., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01909-1 · Cited by 19 · see citing works
Gong, Y., Fei, P., Zhang, Y., Xu, Y., & Wei, J. (2025) · Advanced Science · doi:10.1002/advs.202501095 · Cited by 22 · see citing works
Leveraging Single-Cell Populations to Uncover the Genetic Basis of Complex Traits
Minow, M. A. A., Marand, A. P., & Schmitz, R. J. (2023) · Annual Review of Genetics · doi:10.1146/annurev-genet-022123-110824 · Cited by 21 · see citing works
Chen, X., Guo, M., Duan, Y.-Y., Jiang, F., Wu, H., Dong, S., Zhou, X., Thynn, H. N., Liu, C., Zhang, L., et al. (2020) · JCI Insight · doi:10.1172/jci.insight.136477 · Cited by 19 · see citing works
Chen, H. V., Lorenzini, M. H., Lavalle, S. N., Sajeev, K., Fonseca, A., Fiaux, P. C., Sen, A., Luthra, I., Ho, A. J., Chen, A. R., et al. (2023) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2023.03.008 · Cited by 18 · see citing works
scATAC-Ref: a reference of scATAC-seq with known cell labels in multiple species
Qian, F., Zhou, L., Zhu, Y., Li, Y., Yu, Z., Feng, C., Fang, Q.-L., Zhao, Y. J., Cai, F.-H., Wang, Q., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad924 · Cited by 18 · see citing works
Scalable, multimodal profiling of chromatin accessibility and protein levels in single cellsPreprint
Mimitou, E. P., Lareau, C. A., Chen, K. Y., Zorzetto-Fernandes, A. L., Takeshima, Y., Luo, W., Huang, T.-S., Yeung, B. Z., Thakore, P. I., Wing, J. B., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.09.08.286914 · Cited by 18 · see citing works
Self-citationPace, L. (2021) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a037754 · Cited by 18 · see citing works
Razavi-Mohseni, M., Huang, W., Guo, Y. A., Shigaki, D., Ho, S. W. T., Tan, P. B. O., Skanderup, A. J., & Beer, M. (2024) · Genome Research · doi:10.1101/gr.278565.123 · Cited by 18 · see citing works
Self-citationSalvadores, M., & Supek, F. (2024) · Nature Cancer · doi:10.1038/s43018-023-00707-8 · Cited by 16 · see citing works
Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data
Wu, Y., Qi, T., Wang, H., Zhang, F., Zheng, Z., Phillips‐Cremins, J. E., Deary, I. J., McRae, A. F., Wray, N. R., Zeng, J., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-15587-0 · Cited by 17 · see citing works
Gusev, A., Spisák, S., Fay, A., Carol, H. A., Vavra, K. C., Signoretti, S., Tisza, V., Pomerantz, M., Abbasi, F., Seo, J.-H., et al. (2019) · bioRxiv · doi:10.1101/631150 · Cited by 14 · see citing works
Zhang, G., Li, Y., & Wei, G. (2023) · Communications Biology · doi:10.1038/s42003-023-05141-1 · Cited by 16 · see citing works
ATAC-seq Assay with Low Mitochondrial DNA Contamination from Primary Human CD4+ T Lymphocytes
Rickner, H., Niu, S.-Y., & Cheng, C. S. (2019) · Journal of Visualized Experiments · doi:10.3791/59120 · Cited by 15 · see citing works
Self-citationSeeing the forest through the trees: prioritising potentially functional interactions from Hi-C
Liu, N., Low, W., Alinejad-Rokny, H., Pederson, S., Sadlon, T. J., Barry, S., & Breen, J. (2021) · Epigenetics & Chromatin · doi:10.1186/s13072-021-00417-4 · Cited by 11 · see citing works
Mononen, J., Taipale, M., Malinen, M., Velidendla, B., Niskanen, E. A., Levonen, A., Ruotsalainen, A., & Heikkinen, S. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad1225 · Cited by 14 · see citing works
Liver regulatory mechanisms of noncoding variants at lipid and metabolic trait loci
Pandey, G. K., Vadlamudi, S., Currin, K. W., Moxley, A. H., Nicholas, J. C., McAfee, J. C., Broadaway, K. A., & Mohlke, K. L. (2024) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2024.100275 · Cited by 14 · see citing works
Using functional genomics to advance the understanding of psoriatic arthritis
Shi, C., Rattray, M., Barton, A. C., Bowes, J., & Orozco, G. (2020) · Rheumatology · doi:10.1093/rheumatology/keaa283 · Cited by 15 · see citing works
Fine mapping with epigenetic information and 3D structure
Orozco, G. (2022) · Seminars in Immunopathology · doi:10.1007/s00281-021-00906-4 · Cited by 14 · see citing works
Frontiers and techniques in plant gene regulation
Jores, T., Hamm, M. O., Cuperus, J. T., & Queitsch, C. (2023) · Current Opinion in Plant Biology · doi:10.1016/j.pbi.2023.102403 · Cited by 14 · see citing works
Multiome-wide Association Studies: Novel Approaches for Understanding Diseases
Shao, M., Chen, K., Zhang, S., Tian, M., Shen, Y., Cao, C., & Gu, N. (2024) · Genomics Proteomics & Bioinformatics · doi:10.1093/gpbjnl/qzae077 · Cited by 13 · see citing works
Avalos, D., Rey, G., Ribeiro, D. M., Ramisch, A., Dermitzakis, E. T., & Delaneau, O. (2023) · Communications Biology · doi:10.1038/s42003-023-04688-3 · Cited by 13 · see citing works
Liang, X., Liu, H., Hu, H., Ha, E., Zhou, J., Abedini, A., Sánchez‐Navarro, A., Klötzer, K. A., & Suszták, K. (2024) · Nature Communications · doi:10.1038/s41467-024-53798-x · Cited by 12 · see citing works
Dong, P., Song, L., Bendl, J. M., Misir, R., Shao, Z., Edelstien, J., Davis, D. A., Haroutunian, V. H., Scott, W. K., Acker, S., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-54448-y · Cited by 12 · see citing works
Single cell variant to enhancer to gene map for coronary artery diseasePreprint
Amrute, J., Lee, P. C., Eres, I. E., Lee, C. J. M., Bredemeyer, A. L., Sheth, M. U., Yamawaki, T., Gurung, R., Anene-Nzelu, C. G., Qiu, W., et al. (2024) · medRxiv · doi:10.1101/2024.11.13.24317257 · Cited by 12 · see citing works
Lai, B., Qian, S., Zhang, H., Zhang, S., Kozlova, A., Duan, J., He, X., & Xu, J. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010011 · Cited by 13 · see citing works
Annotating and prioritizing human non-coding variants with RegulomeDBPreprint
Dong, S., Zhao, N., Spragins, E., Kagda, M. S., Li, M., Assis, P., Jolanki, O., Luo, Y., Cherry, J. M., Boyle, A. P., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.18.512627 · Cited by 11 · see citing works
Cao, S., Zhu, H., Cui, J. J., Liu, S., Li, Y., Shi, J., Mo, J., Wang, Z., Wang, H., Hu, J., et al. (2023) · Genome Research · doi:10.1101/gr.277704.123 · Cited by 11 · see citing works
Zaim, S. R., Pebworth, M.-P., McGrath, I., Okada, L. Y., Weiss, M. D. A., Reading, J., Czartoski, J., Torgerson, T. R., McElrath, M. J., Bumol, T. F., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-50612-6 · Cited by 10 · see citing works
Ho, C., Dippel, M. A., McQuade, M. S., Nguyen, L. P., Mishra, A., Pribitzer, S., Hardy, S. R., Chandok, H., Chardon, F. M., McDiarmid, T. A., et al. (2025) · Nature Genetics · doi:10.1038/s41588-025-02301-3 · Cited by 11 · see citing works
Shetty, A. H., Seo, J.-H., Bell, C. A., O’Connor, E. P., Pomerantz, M. M., Freedman, M. L., & Gusev, A. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.09.008 · Cited by 10 · see citing works
Wang, D., Wu, X., Jiang, G., Yang, J., Yu, Z., Yang, Y., Yang, W., Niu, X., Tang, K., & Gong, J. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.1035855 · Cited by 10 · see citing works
ALS is imprinted in the chromatin accessibility of blood cells
Kühlwein, J. K., Ruf, W. P., Kandler, K., Witzel, S., Lang, C., Mulaw, M. A., Ekici, A. B., Weishaupt, J. H., Ludolph, A. C., Grozdanov, V., et al. (2023) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-023-04769-w · Cited by 9 · see citing works
GenomicLinks: deep learning predictions of 3D chromatin interactions in the maize genome
Schlegel, L., Bhardwaj, R., Shahryary, Y., Demirtürk, D., Marand, A. P., Schmitz, R. J., & Johannes, F. M. (2024) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqae123 · Cited by 9 · see citing works
Saelens, W., Pushkarev, O., & Deplancke, B. (2025) · Nature Communications · doi:10.1038/s41467-024-55447-9 · Cited by 9 · see citing works
Genetic variation in chromatin state across multiple tissues in Drosophila melanogaster
Huynh, K., Smith, B. R., Macdonald, S. J., & Long, A. D. (2023) · PLoS Genetics · doi:10.1371/journal.pgen.1010439 · Cited by 9 · see citing works
Liu, T., Guo, L., Liu, G., Hu, X., Li, X., Zhang, J., Dai, Z., Yu, P., Jiang, M., Wang, J., et al. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.779367 · Cited by 9 · see citing works
Integration with systems biology approaches and -omics data to characterize risk variation
Young, H. E., Cote, A. C., & Huckins, L. M. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-819602-1.00017-6 · Cited by 9 · see citing works
Quantifying functional impact of non-coding variants with multi-task Bayesian neural network
Xu, C., Liu, Q., Zhou, J., Xie, M., Feng, J., & Jiang, T. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz767 · Cited by 8 · see citing works
Gate, R. E., Kim, M. C., Lu, A. C., Lee, D. S., Shifrut, E., Subramaniam, M., Marson, A., & Ye, C. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/678060 · Cited by 6 · see citing works
Self-citation
- Authors
- Gate, R. E., Cheng, C. S., Aiden, A. P., Siba, A., Tabaka, M., Lituiev, D., Machol, I., Gordon, M. G., Subramaniam, M., Shamim, M., Hougen, K. L., Wortman, I., Huang, S.-C., Durand, N. C., Feng, T., De Jager, P. L., Chang, H. Y., Aiden, E. L., Benoist, C., Beer, M. A., Ye, C. J., & Regev, A.
- Affiliations
- University of California, San Francisco (US)
- Broad Institute (US)
- Baylor College of Medicine (US)
- Johns Hopkins University (US)
- Harvard University (US)
- Stanford University (US)
- Corresponding author
- Cheng, Christine S.
- Ye, Chun J.
- Regev, Aviv
- ORCID
- Venue
- Nature Genetics
- Published
- 2018-07-09
- Volume
- 50
- Issue
- 8
- Pages
- 1140-1150
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC6097927
- OpenAlex
- W2837542075
- Cited by
- 181
- References
- 83
- Citations by year
- 2026: 10 · 2025: 19 · 2024: 43 · 2023: 22 · 2022: 19 · 2021: 25 · 2020: 23 · 2019: 19 · 2018: 1
- FWCI
- 6.05
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health (5rm1hg006193-10)
- National Human Genome Research Institute (U01HG012192, RM1‐HG006193, P50HG007735, U01HG009380, R01HG007348)
- National Cancer Institute (F32CA168253)
- National Institute of General Medical Sciences (T32GM067547)
- National Institute of Allergy and Infectious Diseases (R21AI133337)
- National Institute of Diabetes and Digestive and Kidney Diseases (F32DK096822)
- National Institute of Arthritis and Musculoskeletal and Skin Diseases (R01AR071522)
- 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 › Chromatin Remodeling and Cancer
- Keywords
- CD4+ T cells, cis-regulatory elements, chromatin accessibility, 3D genome organization, transcription factor binding sites, gene expression regulation, non-coding variants, T cell activation
- MeSH terms
- Adult, Autoimmune Diseases, Chromatin, Female, Gene Expression Regulation, Genotype, Humans, Male, Regulatory Sequences, Nucleic Acid, CD4-Positive T-Lymphocytes, Polymorphism, Single Nucleotide
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