Abstract
Genetic and immunologic studies implicate the interleukin (IL)-23/T helper (Th)17 pathway in inflammatory bowel disease (IBD). IL-23 and IL-1β drive human Th17 differentiation, while prostaglandin E2 (PGE2) and transforming growth factor-β (TGF-β) further modulate Th17 development and plasticity. However, how these inflammatory mediators influence human T cell regulatory programs remains incompletely understood. We used single-cell multi-omics to profile 171,829 peripheral blood T cells from 25 healthy donors in 64 samples exposed to activation stimuli, IL-1β and IL-23 alone or in combination with PGE2, TGF-β, or both. PGE2 broadly suppressed T cell activation, except in Th17 and T follicular helper cells, and markedly altered chromatin accessibility and gene expression, particularly in Th17, Th1, and regulatory T cells, where IBD-associated SNPs were enriched in open chromatin and connected to cell type-specific cis-regulatory elements. Our study demonstrates the utility of single-cell multi-omics for defining stimulus-specific effects on T cells and prioritizing disease-associated genes.
Data availability
The DOGMA-seq data generated in this study are available in the database of Genotypes and Phenotypes (dbGaP; accession number: phs004468.v1.p1; https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs004468.v1.p1) in accordance with the University of Pittsburgh Institutional Review Board consent, which stipulates that individual-level genomic data may be placed in controlled-access databases. Access to these data requires submission of a data access request to dbGaP and approval by the corresponding Data Access Committee. Approved users must agree to the dbGaP data use certification and comply with all data use restrictions. Requests are typically reviewed within 2–4 weeks of submission. Bulk ATAC-seq and bulk RNA-seq data are available by contacting the corresponding author and executing a data use agreement in compliance with institutional and ethical regulations. The University of Pittsburgh Institutional Review Board determined that the bulk ATAC-seq and bulk RNA-seq data cannot be deposited into public repositories because human study participants who provided samples for bulk ATAC-seq and bulk RNA-seq did not provide explicit informed consent for deposition of genomic sequencing data into public repositories. Requests for access will be reviewed within 2–4 weeks. The reused dataset EGAD00001005291 can be found at the European Phenome-Genome Archive (https://ega-archive.org/studies/EGAS00001003823). All other data are available in the article and its Supplementary files or from the corresponding author upon request. Source data are provided with this paper.
Code availability
Scripts to reproduce the analyses are available on GitHub (https://github.com/CHPGenetics/DOGMA_PBMC_T) and archived on Zenodo140.
References
Molodecky, N. A. et al. Increasing incidence and prevalence of the inflammatory bowel diseases with time, based on systematic review. Gastroenterology 142, 46–54e42 (2012).
Ananthakrishnan, A. N. Epidemiology and risk factors for IBD. Nat. Rev. Gastroenterol. Hepatol. 12, 205–217 (2015).
Mak, W. Y., Zhao, M., Ng, S. C. & Burisch, J. The epidemiology of inflammatory bowel disease: east meets west. J. Gastroenterol. Hepatol. 35, 380–389 (2020).
Jostins, L. et al. Host-microbe interactions have shaped the genetic architecture of inflammatory bowel disease. Nature 491, 119–124 (2012).
Liu, J. Z. et al. Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat. Genet. 47, 979–986 (2015).
de Lange, K. M. et al. Genome-wide association study implicates immune activation of multiple integrin genes in inflammatory bowel disease. Nat. Genet. 49, 256–261 (2017).
Luo, Y. et al. Exploring the genetic architecture of inflammatory bowel disease by whole-genome sequencing identifies association at ADCY7. Nat. Genet. 49, 186–192 (2017).
Tesmer, L. A., Lundy, S. K., Sarkar, S. & Fox, D. A. Th17 cells in human disease. Immunol. Rev. 223, 87–113 (2008).
Croxford, A. L., Mair, F. & Becher, B. IL-23: one cytokine in control of autoimmunity. Eur. J. Immunol. 42, 2263–2273 (2012).
Geremia, A. & Jewell, D. P. The IL-23/IL-17 pathway in inflammatory bowel disease. Expert Rev. Gastroenterol. Hepatol. 6, 223–237 (2012).
Monteleone, I., Pallone, F. & Monteleone, G. Th17-related cytokines: new players in the control of chronic intestinal inflammation. BMC Med. 9, 122 (2011).
Monteleone, I., Sarra, M., Pallone, F. & Monteleone, G. Th17-related cytokines in inflammatory bowel diseases: friends or foes? Curr. Mol. Med. 12, 592–597 (2012).
Weaver, C. T., Elson, C. O., Fouser, L. A. & Kolls, J. K. The Th17 pathway and inflammatory diseases of the intestines, lungs, and skin. Annu. Rev. Pathol. 8, 477–512 (2013).
Troncone, E., Marafini, I., Pallone, F. & Monteleone, G. Th17 cytokines in inflammatory bowel diseases: discerning the good from the bad. Int. Rev. Immunol. 32, 526–533 (2013).
Bianchi, E. & Rogge, L. The IL-23/IL-17 pathway in human chronic inflammatory diseases-new insight from genetics and targeted therapies. Genes Immun. 20, 415–425 (2019).
Acosta-Rodriguez, E. V., Napolitani, G., Lanzavecchia, A. & Sallusto, F. Interleukins 1beta and 6 but not transforming growth factor-beta are essential for the differentiation of interleukin 17-producing human T helper cells. Nat. Immunol. 8, 942–949 (2007).
Annunziato, F. et al. Phenotypic and functional features of human Th17 cells. J. Exp. Med. 204, 1849–1861 (2007).
Wilson, N. J. et al. Development, cytokine profile and function of human interleukin 17-producing helper T cells. Nat. Immunol. 8, 950–957 (2007).
Boniface, K., Blom, B., Liu, Y. J. & de Waal Malefyt, R. From interleukin-23 to T-helper 17 cells: human T-helper cell differentiation revisited. Immunol. Rev. 226, 132–146 (2008).
Chizzolini, C. et al. Prostaglandin E2 synergistically with interleukin-23 favors human Th17 expansion. Blood 112, 3696–3703 (2008).
Boniface, K. et al. Prostaglandin E2 regulates Th17 cell differentiation and function through cyclic AMP and EP2/EP4 receptor signaling. J. Exp. Med. 206, 535–548 (2009).
Lee, Y. K. et al. Late developmental plasticity in the T helper 17 lineage. Immunity 30, 92–107 (2009).
Barrie, A. et al. Prostaglandin E2 and IL-23 plus IL-1beta differentially regulate the Th1/Th17 immune response of human CD161(+) CD4(+) memory T cells. Clin. Transl. Sci. 4, 268–273 (2011).
Hirota, K. et al. Fate mapping of IL-17-producing T cells in inflammatory responses. Nat. Immunol. 12, 255–263 (2011).
Sreeramkumar, V., Fresno, M. & Cuesta, N. Prostaglandin E2 and T cells: friends or foes? Immunol. Cell Biol. 90, 579–586 (2012).
Garrido-Mesa, N., Algieri, F., Rodriguez Nogales, A. & Galvez, J. Functional plasticity of Th17 cells: implications in gastrointestinal tract function. Int. Rev. Immunol. 32, 493–510 (2013).
Kleinewietfeld, M. & Hafler, D. A. The plasticity of human Treg and Th17 cells and its role in autoimmunity. Semin. Immunol. 25, 305–312 (2013).
Muranski, P. & Restifo, N. P. Essentials of Th17 cell commitment and plasticity. Blood 121, 2402–2414 (2013).
Sundrud, M. S. & Trivigno, C. Identity crisis of Th17 cells: many forms, many functions, many questions. Semin. Immunol. 25, 263–272 (2013).
Zuniga, L. A., Jain, R., Haines, C. & Cua, D. J. Th17 cell development: from the cradle to the grave. Immunol. Rev. 252, 78–88 (2013).
Travis, M. A. & Sheppard, D. TGF-beta activation and function in immunity. Annu. Rev. Immunol. 32, 51–82 (2014).
Harbour, S. N., Maynard, C. L., Zindl, C. L., Schoeb, T. R. & Weaver, C. T. Th17 cells give rise to Th1 cells that are required for the pathogenesis of colitis. Proc. Natl. Acad. Sci. USA 112, 7061–7066 (2015).
Ueno, A., Ghosh, A., Hung, D., Li, J. & Jijon, H. Th17 plasticity and its changes associated with inflammatory bowel disease. World J. Gastroenterol. 21, 12283–12295 (2015).
Diller, M. L., Kudchadkar, R. R., Delman, K. A., Lawson, D. H. & Ford, M. L. Balancing inflammation: the Link between Th17 and regulatory T cells. Mediat. Inflamm. 2016, 6309219 (2016).
Revu, S. et al. IL-23 and IL-1beta drive human Th17 cell differentiation and metabolic reprogramming in absence of CD28 costimulation. Cell Rep. 22, 2642–2653 (2018).
Schnell, A. et al. Stem-like intestinal Th17 cells give rise to pathogenic effector T cells during autoimmunity. Cell 184, 6281–6298 e23 (2021).
Buckner, J. H. & Harrison, O. J. Th17 cells: from gut homeostasis to CNS pathogenesis. Trends Immunol. 43, 167–169 (2022).
Pawlak, M. et al. Induction of a colitogenic phenotype in Th1-like cells depends on interleukin-23 receptor signaling. Immunity 55, 1663–1679.e6 (2022).
Laudisi, F., Stolfi, C., Monteleone, I. & Monteleone, G. TGF-beta1 signaling and Smad7 control T-cell responses in health and immune-mediated disorders. Eur. J. Immunol. 53, e2350460 (2023).
Mahida, Y. R., Wu, K. & Jewell, D. P. Enhanced production of interleukin 1-beta by mononuclear cells isolated from mucosa with active ulcerative colitis of Crohn’s disease. Gut 30, 835–838 (1989).
Wardle, T. D., Hall, L. & Turnberg, L. A. Use of coculture of colonic mucosal biopsies to investigate the release of eicosanoids by inflamed and uninflamed mucosa from patients with inflammatory bowel disease. Gut 33, 1644–1651 (1992).
McCabe, R. P., Secrist, H., Botney, M., Egan, M. & Peters, M. G. Cytokine mRNA expression in intestine from normal and inflammatory bowel disease patients. Clin. Immunol. Immunopathol. 66, 52–58 (1993).
Babyatsky, M. W., Rossiter, G. & Podolsky, D. K. Expression of transforming growth factors alpha and beta in colonic mucosa in inflammatory bowel disease. Gastroenterology 110, 975–984 (1996).
Fuss, I. J. et al. Both IL-12p70 and IL-23 are synthesized during active Crohn’s disease and are down-regulated by treatment with anti-IL-12 p40 monoclonal antibody. Inflamm. Bowel Dis. 12, 9–15 (2006).
Neurath, M. F. Cytokines in inflammatory bowel disease. Nat. Rev. Immunol. 14, 329–342 (2014).
Ernst, J. et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 473, 43–49 (2011).
Maurano, M. T. et al. Systematic localization of common disease-associated variation in regulatory DNA. Science 337, 1190–1195 (2012).
Trynka, G. et al. Chromatin marks identify critical cell types for fine mapping complex trait variants. Nat. Genet. 45, 124–130 (2013).
Hnisz, D. et al. Super-enhancers in the control of cell identity and disease. Cell 155, 934–947 (2013).
Rivera, C. M. & Ren, B. Mapping human epigenomes. Cell 155, 39–55 (2013).
Farh, K. K. et al. Genetic and epigenetic fine mapping of causal autoimmune disease variants. Nature 518, 337–343 (2015).
Mells, G. F. & Hirschfield, G. M. Making the most of new genetic risk factors—genetic and epigenetic fine mapping of causal autoimmune disease variants. Clin. Res. Hepatol. Gastroenterol. 39, 408–411 (2015).
Wang, K. C. & Chang, H. Y. Epigenomics: technologies and applications. Circ. Res. 122, 1191–1199 (2018).
Mimitou, E. P. et al. Scalable, multimodal profiling of chromatin accessibility, gene expression and protein levels in single cells. Nat. Biotechnol. 39, 1246–1258 (2021).
Swanson, E. et al. Simultaneous trimodal single-cell measurement of transcripts, epitopes, and chromatin accessibility using TEA-seq. Elife 10, e63632 (2021).
Xu, Z., Heidrich-O’Hare, E., Chen, W. & Duerr, R. H. Comprehensive benchmarking of CITE-seq versus DOGMA-seq single cell multimodal omics. Genome Biol. 23, 135 (2022).
Hosokawa, H. & Rothenberg, E. V. How transcription factors drive choice of the T cell fate. Nat. Rev. Immunol. 21, 162–176 (2021).
Soskic, B. et al. Immune disease risk variants regulate gene expression dynamics during CD4(+) T cell activation. Nat. Genet. 54, 817–826 (2022).
Benito, J. M., Lopez, M., Lozano, S., Gonzalez-Lahoz, J. & Soriano, V. Down-regulation of interleukin-7 receptor (CD127) in HIV infection is associated with T cell activation and is a main factor influencing restoration of CD4(+) cells after antiretroviral therapy. J. Infect. Dis. 198, 1466–1473 (2008).
Reddy, M., Eirikis, E., Davis, C., Davis, H. M. & Prabhakar, U. Comparative analysis of lymphocyte activation marker expression and cytokine secretion profile in stimulated human peripheral blood mononuclear cell cultures: an in vitro model to monitor cellular immune function. J. Immunol. Methods 293, 127–142 (2004).
Cano-Gamez, E. et al. Single-cell transcriptomics identifies an effectorness gradient shaping the response of CD4(+) T cells to cytokines. Nat. Commun. 11, 1801 (2020).
Epstein, P. M. Different phosphodiesterases (PDEs) regulate distinct phosphoproteomes during cAMP signaling. Proc. Natl. Acad. Sci. USA 114, 7741–7743 (2017).
Bielenberg, M., Kurelic, R., Frantz, S. & Nikolaev, V. O. A mini-review: phosphodiesterases in charge to balance intracellular cAMP during T-cell activation. Front. Immunol. 15, 1365484 (2024).
Tavares, L. P. et al. Blame the signaling: role of cAMP for the resolution of inflammation. Pharm. Res. 159, 105030 (2020).
Kamthong, P. J. & Wu, M. Inhibitor of nuclear factor-kappaB induction by cAMP antagonizes interleukin-1-induced human macrophage-colony-stimulating-factor expression. Biochem. J. 356, 525–530 (2001).
Gerlo, S. et al. Cyclic AMP: a selective modulator of NF-kappaB action. Cell. Mol. Life Sci. 68, 3823–3841 (2011).
Lee, J. et al. T cell–intrinsic prostaglandin E2-EP2/EP4 signaling is critical in pathogenic TH17 cell-driven inflammation. J. Allergy Clin. Immunol. 143, 631–643 (2019).
Saxton, R. A. & Sabatini, D. M. mTOR signaling in growth, metabolism, and disease. Cell 168, 960–976 (2017).
Wek, R. C. Role of eIF2alpha kinases in translational control and adaptation to cellular stress. Cold Spring Harb. Perspect. Biol. 10, a032870 (2018).
Huang, H. et al. Fine-mapping inflammatory bowel disease loci to single-variant resolution. Nature 547, 173–178 (2017).
Soskic, B. et al. Chromatin activity at GWAS loci identifies T cell states driving complex immune diseases. Nat. Genet. 51, 1486–1493 (2019).
Khor, B., Gardet, A. & Xavier, R. J. Genetics and pathogenesis of inflammatory bowel disease. Nature 474, 307–317 (2011).
Haga, K. et al. MAIT cells are activated and accumulated in the inflamed mucosa of ulcerative colitis. J. Gastroenterol. Hepatol. 31, 965–972 (2016).
Jaeger, N. et al. Single-cell analyses of Crohn’s disease tissues reveal intestinal intraepithelial T cells heterogeneity and altered subset distributions. Nat. Commun. 12, 1921 (2021).
Gazal, S. et al. Linkage disequilibrium-dependent architecture of human complex traits shows action of negative selection. Nat. Genet. 49, 1421–1427 (2017).
Finucane, H. K. et al. Heritability enrichment of specifically expressed genes identifies disease-relevant tissues and cell types. Nat. Genet. 50, 621–629 (2018).
Huang, J. L., Tan, W. T. & Liu, H. Prostaglandins and inflammatory bowel disease: from mechanism to clinic. Inflamm. Bowel Dis. 31, 2907–2916 (2025).
Long, M. D. et al. Role of nonsteroidal anti-inflammatory drugs in exacerbations of inflammatory bowel disease. J. Clin. Gastroenterol. 50, 152–156 (2016).
Preissl, S., Gaulton, K. J. & Ren, B. Characterizing cis-regulatory elements using single-cell epigenomics. Nat. Rev. Genet. 24, 21–43 (2023).
Granja, J. M. et al. ArchR is a scalable software package for integrative single-cell chromatin accessibility analysis. Nat. Genet. 53, 403–411 (2021).
Mitra, S. et al. Single-cell multi-ome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis. Nat. Genet. 56, 627–636 (2024).
Evans, D. M. et al. Interaction between ERAP1 and HLA-B27 in ankylosing spondylitis implicates peptide handling in the mechanism for HLA-B27 in disease susceptibility. Nat. Genet. 43, 761–767 (2011).
Yazar, S. et al. Single-cell eQTL mapping identifies cell type-specific genetic control of autoimmune disease. Science 376, eabf3041 (2022).
Vosa, U. et al. Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression. Nat. Genet 53, 1300–1310 (2021).
Carithers, L. J. et al. A novel approach to high-quality postmortem tissue procurement: the GTEx project. Biopreserv. Biobank. 13, 311–319 (2015).
Drobin, K. et al. Targeted analysis of serum proteins encoded at known inflammatory bowel disease risk loci. Inflamm. Bowel Dis. 25, 306–316 (2019).
Kaser, A., Zeissig, S. & Blumberg, R. S. Genes and environment: how will our concepts on the pathophysiology of IBD develop in the future? Dig. Dis. 28, 395–405 (2010).
Rao, S. S. et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159, 1665–1680 (2014).
Wang, Y. et al. The 3D Genome Browser: a web-based browser for visualizing 3D genome organization and long-range chromatin interactions. Genome Biol. 19, 151 (2018).
Yasuda, K. et al. Satb1 regulates the effector program of encephalitogenic tissue Th17 cells in chronic inflammation. Nat. Commun. 10, 549 (2019).
Ntunzwenimana, J. C. et al. Functional screen of inflammatory bowel disease genes reveals key epithelial functions. Genome Med. 13, 181 (2021).
Ruiz, F. et al. A single nucleotide polymorphism in the gene for GPR183 increases its surface expression on blood lymphocytes of patients with inflammatory bowel disease. Br. J. Pharm. 178, 3157–3175 (2021).
Baars, M. J. D. et al. Dysregulated RASGRP1 expression through RUNX1 mediated transcription promotes autoimmunity. Eur. J. Immunol. 51, 471–482 (2021).
Chen, M. H. et al. Trans-ethnic and ancestry-specific blood-cell genetics in 746,667 individuals from 5 global populations. Cell 182, 1198–1213 e14 (2020).
Di Meglio, P. et al. Targeting CD8(+) T cells prevents psoriasis development. J. Allergy Clin. Immunol. 138, 274–276 e6 (2016).
Cavers, A. et al. Behcet’s disease risk-variant HLA-B51/ERAP1-Hap10 alters human CD8 T cell immunity. Ann. Rheum. Dis. 81, 1603–1611 (2022).
Ali, N. et al. Regulatory T cells in skin facilitate epithelial stem cell differentiation. Cell 169, 1119–1129 e11 (2017).
Castela, E. et al. Effects of low-dose recombinant interleukin 2 to promote T-regulatory cells in alopecia areata. JAMA Dermatol. 150, 748–751 (2014).
Yang, X. et al. Autoimmunity-associated T cell receptors recognize HLA-B*27-bound peptides. Nature 612, 771–777 (2022).
Chen, P. M. & Tsokos, G. C. The role of CD8+ T-cell systemic lupus erythematosus pathogenesis: an update. Curr. Opin. Rheumatol. 33, 586–591 (2021).
Wolk, K. et al. IL-29 is produced by T(H)17 cells and mediates the cutaneous antiviral competence in psoriasis. Sci. Transl. Med. 5, 204ra129 (2013).
Harden, J. L., Krueger, J. G. & Bowcock, A. M. The immunogenetics of psoriasis: a comprehensive review. J. Autoimmun. 64, 66–73 (2015).
Zhang, K. et al. A single-cell atlas of chromatin accessibility in the human genome. Cell 184, 5985–6001.e19 (2021).
Sheibanie, A. F. et al. The proinflammatory effect of prostaglandin E2 in experimental inflammatory bowel disease is mediated through the IL-23->IL-17 axis. J. Immunol. 178, 8138–8147 (2007).
Freimer, J. W. et al. Systematic discovery and perturbation of regulatory genes in human T cells reveals the architecture of immune networks. Nat. Genet. 54, 1133–1144 (2022).
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).
Buenrostro, J. D., Wu, B., Chang, H. Y. & Greenleaf, W. J. ATAC-seq: a method for assaying chromatin accessibility genome-wide. Curr. Protoc. Mol. Biol. 109, 21 29 1–21 29 9 (2015).
Melsted, P. et al. Modular, efficient and constant-memory single-cell RNA-seq preprocessing. Nat. Biotechnol. 39, 813–818 (2021).
Hao, Y. et al. Integrated analysis of multimodal single-cell data. Cell 184, 3573–3587 e29 (2021).
Stuart, T., Srivastava, A., Madad, S., Lareau, C. A. & Satija, R. Single-cell chromatin state analysis with Signac. Nat. Methods 18, 1333–1341 (2021).
Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).
Hafemeister, C. & Satija, R. Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression. Genome Biol. 20, 296 (2019).
Ahlmann-Eltze, C. & Huber, W. glmGamPoi: fitting Gamma-Poisson generalized linear models on single cell count data. Bioinformatics 36, 5701–5702 (2021).
Korsunsky, I. et al. Fast, sensitive and accurate integration of single-cell data with Harmony. Nat. Methods 16, 1289–1296 (2019).
McInnes, L., Healy, J. & Melville, J. UMAP: uniform manifold approximation and projection for dimension reduction. arXiv:1802.03426 (2018).
Cusanovich, D. A. et al. Multiplex single cell profiling of chromatin accessibility by combinatorial cellular indexing. Science 348, 910–914 (2015).
Schep, A. N., Wu, B., Buenrostro, J. D. & Greenleaf, W. J. chromVAR: inferring transcription-factor-associated accessibility from single-cell epigenomic data. Nat. Methods 14, 975–978 (2017).
Zappia, L. & Oshlack, A. Clustering trees: a visualization for evaluating clusterings at multiple resolutions. Gigascience 7, giy083 (2018).
Squair, J. W. et al. Confronting false discoveries in single-cell differential expression. Nat. Commun. 12, 5692 (2021).
Kramer, A., Green, J., Pollard, J. Jr. & Tugendreich, S. Causal analysis approaches in Ingenuity Pathway Analysis. Bioinformatics 30, 523–530 (2014).
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
Dobin, A. et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics 29, 15–21 (2013).
Li, B. & Dewey, C. N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinform. 12, 323 (2011).
Ewels, P. A. et al. The nf-core framework for community-curated bioinformatics pipelines. Nat. Biotechnol. 38, 276–278 (2020).
Dou, J. et al. Single-nucleotide variant calling in single-cell sequencing data with Monopogen. Nat. Biotechnol. 42, 803–812 (2024).
Siva, N. 1000 Genomes project. Nat. Biotechnol. 26, 256 (2008).
Delaneau, O., Zagury, J. F., Robinson, M. R., Marchini, J. L. & Dermitzakis, E. T. Accurate, scalable and integrative haplotype estimation. Nat. Commun. 10, 5436 (2019).
McKenna, A. et al. The Genome Analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res. 20, 1297–1303 (2010).
DePristo, M. A. et al. A framework for variation discovery and genotyping using next-generation DNA sequencing data. Nat. Genet. 43, 491–498 (2011).
Zhang, S. et al. Allele-specific open chromatin in human iPSC neurons elucidates functional disease variants. Science 369, 561–565 (2020).
Zhang, B. et al. Altered and allele-specific open chromatin landscape reveals epigenetic and genetic regulators of innate immunity in COVID-19. Cell Genom. 3, 100232 (2023).
Bulik-Sullivan, B. K. et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).
Finucane, H. K. et al. Partitioning heritability by functional annotation using genome-wide association summary statistics. Nat. Genet. 47, 1228–1235 (2015).
The 1000 Genomes Project Consortium et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
Shabalin, A. A. Matrix eQTL: ultra fast eQTL analysis via large matrix operations. Bioinformatics 28, 1353–1358 (2012).
Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).
Gene Ontology Consortium. The Gene Ontology resource: enriching a GOld mine. Nucleic Acids Res. 49, D325–D334 (2021).
Gene Ontology Consortium et al. The Gene Ontology knowledgebase in 2023. Genetics 224, (2023).
Xu, Z. & Tao, S. Dissecting PGE2-driven Inhibition of T Cell Activation Using Single-cell Multi-omic And Inflammatory Bowel Disease Genetic Association Analysis. Github release DOGMA_PBMC_T v1.0.0. https://doi.org/10.5281/zenodo.18248881 (2026).
Acknowledgements
This research was supported by National Institute of Diabetes and Digestive and Kidney Diseases grants U01DK062420 and R01DK138458, and the University of Pittsburgh Center for Research Computing and Data, RRID:SCR_022735, through the resources provided. Specifically, this work used the HTC cluster, which is supported by NIH award number S10OD028483.
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Z.X., W.C., and R.D. conceived the project and designed the experiments. S.F. and E.H. performed experiments. Z.X., S.T., S.F., X.Y., T.W., and H.H. performed data analysis. Z.X., S.T., S.F., T.W., E.H., W.C., and R.D. wrote the manuscript. W.C. and R.D. supervised the work.
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Xu, Z., Tao, S., Feng, S. et al. Dissecting PGE2-driven inhibition of T cell activation using single-cell multi-omic and inflammatory bowel disease genetic association analysis. Nat Commun (2026). https://doi.org/10.1038/s41467-026-71383-2
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DOI: https://doi.org/10.1038/s41467-026-71383-2
