Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

A distal enhancer at risk locus 11q13.5 promotes suppression of colitis by Treg cells

Abstract

Genetic variations underlying susceptibility to complex autoimmune and allergic diseases are concentrated within noncoding regulatory elements termed enhancers1. The functions of a large majority of disease-associated enhancers are unknown, in part owing to their distance from the genes they regulate, a lack of understanding of the cell types in which they operate, and our inability to recapitulate the biology of immune diseases in vitro. Here, using shared synteny to guide loss-of-function analysis of homologues of human enhancers in mice, we show that the prominent autoimmune and allergic disease risk locus at chromosome 11q13.52,3,4,5,6,7 contains a distal enhancer that is functional in CD4+ regulatory T (Treg) cells and required for Treg-mediated suppression of colitis. The enhancer recruits the transcription factors STAT5 and NF-κB to mediate signal-driven expression of Lrrc32, which encodes the protein glycoprotein A repetitions predominant (GARP). Whereas disruption of the Lrrc32 gene results in early lethality, mice lacking the enhancer are viable but lack GARP expression in Foxp3+ Treg cells, which are unable to control colitis in a cell-transfer model of the disease. In human Treg cells, the enhancer forms conformational interactions with the promoter of LRRC32 and enhancer risk variants are associated with reduced histone acetylation and GARP expression. Finally, functional fine-mapping of 11q13.5 using CRISPR-activation (CRISPRa) identifies a CRISPRa-responsive element in the vicinity of risk variant rs11236797 capable of driving GARP expression. These findings provide a mechanistic basis for association of the 11q13.5 risk locus with immune-mediated diseases and identify GARP as a potential target in their therapy.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: A distal intergenic region of mouse chromosome 7 in shared synteny with human 11q13.5 is required to limit gut inflammation.
Fig. 2: Lrrc32 +70k is required for signal-driven expression of GARP by Foxp3+ Treg cells.
Fig. 3: Lrrc32 +70k promotes Treg-mediated suppression of colitis.
Fig. 4: Inflammatory bowel disease risk alleles at 11q13.5 affect enhancer histone acetylation and GARP expression in human CD4+ Treg cells.

Data availability

RNA-seq data have been deposited in the Gene Expression Omnibus (GEO) database under the accession number GSE128198. Sequencing data for H3K27ac hQTL and mRNA eQTL analyses are deposited under the European Genome-phenome Archive (EGA; study accession EGAS00001003516, datasets EGAD00001004828 and EGAD00001004830).

References

  1. Maurano, M. T. et al. Systematic localization of common disease-associated variation in regulatory DNA. Science 337, 1190–1195 (2012).

    ADS  CAS  PubMed  PubMed Central  Google Scholar 

  2. 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).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  3. Anderson, C. A. et al. Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47. Nat. Genet. 43, 246–252 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Onengut-Gumuscu, S. et al. Fine mapping of type 1 diabetes susceptibility loci and evidence for colocalization of causal variants with lymphoid gene enhancers. Nat. Genet. 47, 381–386 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Ferreira, M. A. et al. Identification of IL6R and chromosome 11q13.5 as risk loci for asthma. Lancet 378, 1006–1014 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Ferreira, M. A. et al. Shared genetic origin of asthma, hay fever and eczema elucidates allergic disease biology. Nat. Genet. 49, 1752–1757 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Paternoster, L. et al. Meta-analysis of genome-wide association studies identifies three new risk loci for atopic dermatitis. Nat. Genet. 44, 187–192 (2012).

    Article  CAS  Google Scholar 

  8. Kundaje, A. et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Sakaguchi, S., Yamaguchi, T., Nomura, T. & Ono, M. Regulatory T cells and immune tolerance. Cell 133, 775–787 (2008).

    Article  CAS  PubMed  Google Scholar 

  10. Josefowicz, S. Z., Lu, L. F. & Rudensky, A. Y. Regulatory T cells: mechanisms of differentiation and function. Annu. Rev. Immunol. 30, 531–564 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Kitagawa, Y. et al. Guidance of regulatory T cell development by Satb1-dependent super-enhancer establishment. Nat. Immunol. 18, 173–183 (2017).

    Article  CAS  PubMed  Google Scholar 

  12. Boschetti, G. et al. Gut inflammation in mice triggers proliferation and function of mucosal Foxp3+ regulatory t cells but impairs their conversion from CD4+ T cells. J. Crohn’s Colitis 11, 105–117 (2017).

    Article  Google Scholar 

  13. Worthington, J. J. et al. Integrin αvβ8-mediated TGF-β activation by effector regulatory T cells is essential for suppression of T-cell-mediated inflammation. Immunity 42, 903–915 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Tran, D. Q. et al. GARP (LRRC32) is essential for the surface expression of latent TGF-β on platelets and activated FOXP3+ regulatory T cells. Proc. Natl Acad. Sci. USA 106, 13445–13450 (2009).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  15. Wang, R., Wan, Q., Kozhaya, L., Fujii, H. & Unutmaz, D. Identification of a regulatory T cell specific cell surface molecule that mediates suppressive signals and induces Foxp3 expression. PLoS ONE 3, e2705 (2008).

    Article  ADS  PubMed  PubMed Central  CAS  Google Scholar 

  16. Dedobbeleer, O., Stockis, J., van der Woning, B., Coulie, P. G. & Lucas, S. Active TGF-β1 released from GARP/TGF-β1 complexes on the surface of stimulated human B lymphocytes increases class-switch recombination and production of IgA. J. Immunol. 199, 391–396 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Wallace, C. H. et al. B lymphocytes confer immune tolerance via cell surface GARP–TGF-β complex. JCI Insight 3, e99863 (2018).

    Article  PubMed Central  Google Scholar 

  18. Vermeersch, E. et al. The role of platelet and endothelial GARP in thrombosis and hemostasis. PLoS One 12, e0173329 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  19. O’Connor, M. N. et al. Functional genomics in zebrafish permits rapid characterization of novel platelet membrane proteins. Blood 113, 4754–4762 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  20. Arvey, A. et al. Genetic and epigenetic variation in the lineage specification of regulatory T cells. eLife 4, e07571 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  21. Schmidl, C. et al. The enhancer and promoter landscape of human regulatory and conventional T-cell subpopulations. Blood 123, e68–e78 (2014).

    Article  CAS  PubMed  Google Scholar 

  22. Oh, H. et al. An NF-κB transcription-factor-dependent lineage-specific transcriptional program promotes regulatory T cell identity and function. Immunity 47, 450–465 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Changelian, P. S. et al. Prevention of organ allograft rejection by a specific Janus kinase 3 inhibitor. Science 302, 875–878 (2003).

    Article  ADS  CAS  PubMed  Google Scholar 

  24. Edwards, J. P. et al. Regulation of the expression of GARP/latent TGF-β1 complexes on mouse T cells and their role in regulatory T cell and TH17 differentiation. J. Immunol. 190, 5506–5515 (2013).

    Article  CAS  PubMed  Google Scholar 

  25. Eschborn, M. et al. Activated glycoprotein A repetitions predominant (GARP)-expressing regulatory T cells inhibit allergen-induced intestinal inflammation in humanized mice. J. Allergy Clin. Immunol. 136, 159–168 (2015).

    Article  CAS  PubMed  Google Scholar 

  26. Salem, M. et al. GARP dampens cancer immunity by sustaining function and accumulation of regulatory T cells in the colon. Cancer Res. 79, 1178–1190 (2019).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Chen, L. et al. Genetic drivers of epigenetic and transcriptional variation in human immune cells. Cell 167, 1398–1414 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Mumbach, M. R. et al. Enhancer connectome in primary human cells identifies target genes of disease-associated DNA elements. Nat. Genet. 49, 1602–1612 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. 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).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Simeonov, D. R. et al. Discovery of stimulation-responsive immune enhancers with CRISPR activation. Nature 549, 111–115 (2017).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  31. De Cuyper, I. M. et al. A novel flow cytometry-based platelet aggregation assay. Blood 121, e70–e80 (2013).

    Article  PubMed  CAS  Google Scholar 

  32. Asseman, C., Mauze, S., Leach, M. W., Coffman, R. L. & Powrie, F. An essential role for interleukin 10 in the function of regulatory T cells that inhibit intestinal inflammation. J. Exp. Med. 190, 995–1004 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Picelli, S. et al. Full-length RNA-seq from single cells using Smart-seq2. Nat. Protoc. 9, 171–181 (2014).

    CAS  PubMed  Google Scholar 

  34. 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).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Pollard, K. S., Hubisz, M. J., Rosenbloom, K. R. & Siepel, A. Detection of nonneutral substitution rates on mammalian phylogenies. Genome Res. 20, 110–121 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Browning, B. L., Zhou, Y. & Browning, S. R. A one-penny imputed genome from next-generation reference panels. Am. J. Hum. Genet. 103, 338–348 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Schmidl, C., Rendeiro, A. F., Sheffield, N. C. & Bock, C. ChIPmentation: fast, robust, low-input ChIP-seq for histones and transcription factors. Nat. Methods 12, 963–965 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Liao, Y., Smyth, G. K. & Shi, W. featureCounts: an efficient general purpose program for assigning sequence reads to genomic features. Bioinformatics 30, 923–930 (2014).

    Article  CAS  PubMed  Google Scholar 

  40. Delaneau, O. et al. A complete tool set for molecular QTL discovery and analysis. Nat. Commun. 8, 15452 (2017).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  41. Giambartolomei, C. et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLoS Genet. 10, e1004383 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Bossini-Castillo, L. et al. Immune disease variants modulate gene expression in regulatory CD4+ T cells and inform drug targets. Preprint at bioRxiv https://doi.org/10.1101/654632 (2019).

  43. Perez-Pinera, P. et al. RNA-guided gene activation by CRISPR–Cas9-based transcription factors. Nat. Methods 10, 973–976 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Chen, X. et al. Functional interrogation of primary human T cells via CRISPR genetic editing. J. Immunol. 201, 1586–1598 (2018).

    Article  CAS  PubMed  Google Scholar 

  45. Demenais, F. et al. Multiancestry association study identifies new asthma risk loci that colocalize with immune-cell enhancer marks. Nat. Genet. 50, 42–53 (2018).

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

The research was supported by Wellcome Trust–Royal Society Fellowship 105663/Z/14/Z, Wellcome Trust grant WT206194, Biotechnology and Biological Sciences Research Council grants BB/N007794/1, BBS/E/B/000C0427 and BBS/E/B/000C0428, Cancer Research UK grant C52623/A22597, Medical Research Council grants MR/N014995/1, MR/S024468/1 and MC_UU_00014/5, Wellcome Trust Major Award 208363/Z/17/Z, Associazione Italiana per la Ricerca sul Cancro (AIRC) grant IG 20607, and US National Institutes of Health (NIH) grants RM1-HG007735, U19-AI142733 and R01-AI121920. We thank members of the Babraham Institute Biological Services Unit, flow cytometry facility and sequencing facility, and Wellcome Sanger Institute flow cytometry, sequencing, IT and data access facilities for data generation and processing. We thank all participating blood donors, and Cambridge and Oxford NHS Blood and Transplant, New York Blood Center and Policlinico San Matteo Pavia Fondazione for the recruitment of study participants. We thank F. De Paoli (Humanitas) for processing human PBMC samples and M. Turner, K. Okkenhaug, E. Shevach, M. Linterman and G. Butcher for support and discussion.

Author information

Authors and Affiliations

Authors

Contributions

R.N., C.J.I., F.M.G., M.D., L.P., L.K, P.K., F.S., S.K.W., A.C., P.V., C.E.W., T.L., T.F., H.F., E.L., D.U., S.M. and R.R. performed experiments. L.B.-C., D.G. and G.T. performed and analysed hQTL and eQTL analyses of human T cells. R.N., C.J.I., F.S., M.R.M., H.F., J.Y., A.L., S.A., G.T. and R.R. analysed data. R.N., C.J.I, L.B.-C., G.T. and R.R. wrote the manuscript. H.Y.C., D.U., G.T. and R.R. provided overall supervision of the work.

Corresponding authors

Correspondence to Charlotte J. Imianowski, Gosia Trynka or Rahul Roychoudhuri.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature thanks Arthur Kaser, Shimon Sakaguchi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data figures and tables

Extended Data Fig. 1 Highly linked genetic polymorphisms at a distal intergenic region of 11q13.5 are associated with risk of multiple immune-mediated diseases.

ad, Graph showing association of polymorphisms within the 11q13.5 locus with risk of indicated immune-mediated disorders (−log10 (P); left axis). Each point represents an individual SNP. Point colours depict R2 values reflecting the level of linkage disequilibrium between each polymorphism and the indicated lead GWAS variant (diamond symbol). Chromosomal position (GRCh38) is represented on the x-axis. GWAS summary statistics and replicate information from ref. 45 (a), ref. 4 (b) ref. 6 (c) and ref. 2 (d).

Extended Data Fig. 2 Alignments showing distribution of H3K27ac at the indicated genomic region in primary human lymphocytes.

Alignment of H3K27ac enrichment at the indicated locus within the indicated lymphocyte lineages; sample information and replicate statistics are from the Roadmap Epigenomics Project8. Grey shaded area marks the risk locus containing the single nucleotide polymorphism (SNP) rs11236797 (position indicated by red triangle).

Extended Data Fig. 3 Steady-state immune phenotype of Enh-KO mice.

a, b, Body mass at indicated age (a) and Kaplan–Meier plot showing survival (b) of mice of indicated genotypes (n = 8 and 7, WT and Enh-KO from 8 independent breedings). c, Representative flow cytometry (left) and replicate measurements (right) of the frequency of the indicated thymocyte subsets in the thymi of mice of the indicated genotypes at 8–10 weeks of age (n = 6 and 5; WT and Enh-KO). d, Representative flow cytometry (left) and replicate measurements of the frequency and absolute number (right) of Foxp3+ Treg cells in the spleens of mice of the indicated genotypes at 8–10 weeks of age (n = 5 mice per group). Representative of two independent experiments (c, d). e, Representative flow cytometry (left) and replicate measurements of the frequency of naive and helper CD4+Foxp3 Tconv cells in the spleens of mice of the indicated genotypes at 8–10 weeks of age (n = 9 mice per group, pooled from two independent experiments). f, Frequency of cells expressing IFN-γ (left) and TNF (right) upon intracellular cytokine staining analysis of splenic CD4+ and CD8+ T cells from mice of the indicated genotypes at 8–10 weeks of age (n = 10 mice per group pooled from two independent experiments). Unpaired two-tailed Student’s t test (a, c-f), Mantel–Cox test (b). Data are mean ± s.e.m.

Source Data

Extended Data Fig. 4 Increased susceptibility of Enh-KO mice to colitis induced by DSS.

a, b, Replicate length measurements (a) and photographs (b) of large intestine from WT and Enh-KO mice treated with DSS or vehicle control (vehicle). n = 4 (WT vehicle), 4 (Enh-KO vehicle), 10 (WT DSS) and 8 (Enh-KO DSS). c, Histopathological scores of sections of large intestine from WT and Enh-KO treated for 16 days with DSS or vehicle. The following scoring criteria were used: extent of inflammation: 0, none; 1, mucosa; 2, mucosa and submucosa; 3, transmural. Crypt damage: 0, none; 1, basal one-thirds; 2, basal two-thirds; 3, only surface epithelium intact; 4, loss of entire crypt and surface epithelium. Tissue involvement: 1, 0 to 25%; 2, 26 to 50%; 3, 51 to 75%; 4, 76 to 100%. Severity of inflammation: 0, none; 1, mild; 2, moderate; 3, severe. Data are representative of two independently repeated experiments with 10 and 4 mice per DSS- and vehicle-treated group. Unpaired two-tailed Student’s t test (a); Wilcoxon-Mann–Whitney Test (c). Data are mean ± s.e.m.

Source Data

Extended Data Fig. 5 Analysis of cytokine expression in WT and Enh-KO mice treated with DSS.

a, Replicate measurements of IFN-γ (left) and Foxp3 (right) in CD4+ T cells from large intestinal lamina propria (n = 8 mice per group). Data representative of two independent experiments. be, Concentration of the indicated cytokines in the serum of WT and Enh-KO mice treated with vehicle or DSS for 16 days. Data pooled from two independent experiments with n = 8, 8, 20 and 17 for WT (vehicle), Enh-KO (vehicle), WT (DSS), Enh-KO (DSS) groups. Data analysed using unpaired two-tailed Student’s t test. Data are mean ± s.e.m.

Source Data

Extended Data Fig. 6 Loss of LRRC32 and GARP expression in Foxp3+ Treg cells from Enh-KO mice.

a, Scatter plot showing global differences in chromatin accessibility at called peaks using ATAC-Seq analysis of WT and Enh-KO CD4+ Foxp3GFP+ Treg cells. Red dots show significantly differentially accessible peaks (FDR < 0.05). Mean log2 reads per million (RPM) values for each called peak (represented as points) from three independent biological replicates are shown, with samples isolated on different days. Two-tailed Wald test with Benjamini–Hochberg correction. b, Representative alignment of gene expression (top) and chromatin accessibility (bottom) within the indicated cell types sorted by FACS from WT and Enh-KO Foxp3eGFP reporter mice. Expected loss of ATAC-seq reads mapping to the deleted region (Enh; highlighted in grey) in Enh-KO cells is observed. Data representative of three independent biological replicates with samples isolated on different days. c, Representative flow cytometry analysis of GARP and Foxp3 expression by CD4+ T cells of mice of the indicated genotypes from mesenteric lymph nodes. d, GARP expression from mice of indicated genotypes in spleen (n = 5 per genotype), thymus (n = 6 and 5 for WT and Enh-KO groups), and mesenteric lymph node (n = 3 and 4 for WT and Enh-KO groups). Data are representative of three and two independent experiments (c, d). Unpaired two-tailed Student’s t test (d). Data are mean ± s.e.m.

Source Data

Extended Data Fig. 7 Lrrc32 +70k is not required for induction of GARP on the surface of CD4+ Tconv cells following stimulation in vitro.

a, Representative flow cytometry showing gating strategy and representative GARP expression on resting (CD44lowCD62L+) and activated (CD44highCD62L) Treg cells (top) and naive (CD44lowCD62L+) and memory (CD44highCD62L) Tconv cells (bottom). Data are representative of two independent experiments. b, Representative flow cytometry (top) and replicate measurements (bottom) of CD25 and GARP expression in CD4+Foxp3 Tconv cells following stimulation under the indicated conditions for 16 h in vitro. Data representative of three independently repeated experiments with five independent biological replicates per group. c, Representative alignments of known H3K27ac ChIP-seq data from the indicated cell types. Sample information and replicate statistics are in ref. 20. Grey bar shows position of the enhancer. Unpaired two-tailed Student’s t test (b). Data are mean ± s.e.m.

Source Data

Extended Data Fig. 8 Specific loss of GARP expression on Treg cells from Enh-KO mice.

a, Representative flow cytometry of GARP expression on CD45CD31+ endothelial cells from lungs of WT and Enh-KO mice. b, Frequency of GARP+ cells among WT and Enh-KO B220+CD19+GL7+ cells, stimulated with bacterial LPS or vehicle control (Veh) for 48 h (n = 6 and 8 for WT and Enh-KO groups). c, Percentage of GARP+ cells among indicated cell types from WT and Enh-KO mice (n = 6 per genotype; unpaired two-tailed Student’s t test). d, Representative histograms showing GARP expression in the cell types shown in c. e, Representative flow cytometry indicating gating strategy for cells shown in c. Unpaired two-tailed Student’s t test (b). Data are representative of two independent experiments. Data are mean ± s.e.m.

Source Data

Extended Data Fig. 9 Molecular and functional characterization of mouse and human enhancer homologues.

a, Evolutionarily conserved STAT5 and NF-κB binding motifs within Lrrc32 +70k. Genomic sequence alignments of reference genome sequences of indicated mammals are shown. The position of conserved STAT5 and NF-κB binding motifs (V$STAT5A_03 and V$NFKAPPAB_01, respectively) are highlighted in grey. The position of rs11236797 is shown. b, Alignment of previously determined STAT5 ChIP-seq binding at the indicated locus in human Treg and Tconv cells. Sample information and replicate statistics are in ref. 21. The identified distal enhancer is shown indicated by the grey shaded area. c, GARP expression in CD4+Foxp3+ Treg cells following stimulation under the indicated conditions for 16 h in vitro. n = 4 technical replicates per condition; data are representative of three independent experiments. d, Representative flow cytometry showing gating (left) and replicate measurements (right) of CD45.2+ (transferred Treg) and CD45.2 (transferred Tconv) cells within the spleen and mesenteric lymph node of cell-transfer recipients. e, Replicate measurements of GARP expression on the indicated cell types from the spleen. f, Replicate measurements of expression of indicated cytokines by CD45.2 Tconv cells from indicated tissues following brief restimulation ex vivo. n = 5 and 6, WT and Enh-KO Treg recipients (d–f). Data representative of two independent experiments. Unpaired two-tailed Student’s t test (cf). Data are mean ± s.e.m.

Source Data

Extended Data Fig. 10 Conformational topography and eQTL analysis of human 11q13.5.

a, Visualization of intrachromosomal interactions at human 11q13.5 within the B lymphoid line GM1287829. A sub-topologically associated domain containing the identified enhancer and the promoter of LRRC32 is indicated. Sample information and replicate statistics are in ref. 29. b, Analysis of intrachromosomal H3K27ac-enriched HiChIP interactions in human CD4+ naive (CD45RA+CD25CD127high), Treg (CD25+CD127low), and TH17 cells (CD45RACD25CD127highCCR6+CXCR5) isolated directly from human peripheral blood. Sample information and replicate statistics are in ref. 28. c, Expression quantitative trait locus (eQTL) analysis of the association between genetic polymorphisms at the indicated SNP with LRRC32 expression in human CD4+CD127CD25+ Treg cells isolated by FACS from the blood of 123 healthy human donors. Point colours reflect linkage disequilibrium (R2) relative to rs11236797. Nominal P value and FDR of the most significantly associated SNP are shown; linear regression, two-sided.

Supplementary information

Reporting Summary

Supplementary Table 1

Genomic sequence alignment of Human Chr11:76588236-76592844 (GRCh38) with the reverse complement of mouse Chr7:105711382-105713753 (mm9).

Supplementary Table 2

Analysis of global gene expression differences between WT and Enh-KO CD4+ Foxp3GFP+ Treg cells and Foxp3GFP– Tconv cells.

Supplementary Table 3

Normalised H3K27Ac enrichment at Chr11:76586431-76600121 in CD4+ CD127- CD25+ Treg cells freshly isolated from 91 genotyped healthy donors.

Supplementary Table 4

Normalised H3K27Ac enrichment at Chr11:76586431-76600121 in CD4+ Naive Tconv cells isolated from 142 genotyped healthy donors.

Supplementary Table 5

Association of distinct polymorphic variants within the 11q13.5 risk locus with IBD risk and H3K27ac enrichment at chr11:76586431-76600121.

Supplementary Table 6

sgRNA sequences used in CRISPRa screen.

Source data

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Nasrallah, R., Imianowski, C.J., Bossini-Castillo, L. et al. A distal enhancer at risk locus 11q13.5 promotes suppression of colitis by Treg cells. Nature 583, 447–452 (2020). https://doi.org/10.1038/s41586-020-2296-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41586-020-2296-7

This article is cited by

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing