The DOI matches its Crossref record; 83 of the 83 references it cites were found in a registry or an index.
Genetic determinants of co-accessible chromatin regions in activated T cells across humans
Open accessPublished version of a preprint
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“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]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
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
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
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
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
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
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
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
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
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
Statistical significance for genomewide studies
Storey, J. D., & Tibshirani, R. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1530509100 · Cited by 9,692
A 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
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
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
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
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
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
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
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 3,860
Self-citationType 2 diabetes as an inflammatory disease
Donath, M. Y., & Shoelson, S. E. (2011) · Nature Reviews Immunology · doi:10.1038/nri2925 · Cited by 3,737
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
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 · cited 9×
“Aligned reads from six samples (five donors, one pair of donors were replicates) were pooled for each condition, yielding a total of 209 million reads for Th stim and 58 million for Th cells (Methods).”
InfluentialDroplet 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
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 2,923
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
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
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 2,613
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
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
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
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
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
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
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
Matrix eQTL: ultra fast eQTL analysis via large matrix operations
Shabalin, A. A. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts163 · Cited by 1,694
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
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 1,585
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 1,451
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
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 1,153
Multiplexed 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 1,101 · cited 1×
“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-citationNatural regulatory T cells in infectious disease
Belkaid, Y., & Rouse, B. T. (2005) · Nature Immunology · doi:10.1038/ni1181 · Cited by 1,044
Hicks, R., & Tingley, D. H. (2011) · The Stata Journal Promoting communications on statistics and Stata · doi:10.1177/1536867x1201100407 · Cited by 825
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 760
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
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
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
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 635
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 570
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
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
Foxp3+ 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
Self-citationEcto-ATPases: Identities and Functions
Plesner, L. (1995) · International review of cytology · doi:10.1016/s0074-7696(08)62487-0 · Cited by 506
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
Self-citationEnhanced Regulatory Sequence Prediction Using Gapped k-mer Features
Ghandi, M., Lee, D., Mohammad-Noori, M., & Beer, M. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003711 · Cited by 484
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
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
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 467
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
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 442
Self-citationIdentification 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 436
A 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 430
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 397
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 392
Self-citationExtensive 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
Coordinated 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 337
Regulation of immunity by self-reactive T cells
Kronenberg, M., & Rudensky, A. Y. (2005) · Nature · doi:10.1038/nature03725 · Cited by 318
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
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 264
Self-citationFine-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 244
Intersection 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
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×
“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
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
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
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
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
Schmidt, E. M., Zhang, J., Zhou, W., Chen, J., Mohlke, K. L., Chen, Y., & Willer, C. J. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv201 · Cited by 152
T-cell signalling and autoimmunity: molecular mechanisms of disease
Ohashi, P. S. (2002) · Nature reviews. Immunology · doi:10.1038/nri822 · Cited by 148
Prostaglandin E2, an Immunoactivator
Sakata, D., Yao, C., & Narumiya, S. (2010) · Journal of Pharmacological Sciences · doi:10.1254/jphs.09r03cp · Cited by 128
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 85
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
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
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
Cited by
Sorted by citations
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
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
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 387
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
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 269
Metadata
- 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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review