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Wang B, Bian Q. Regulation of 3D genome organization during T cell activation. FEBS J 2025; 292:1833-1852. [PMID: 38944686 DOI: 10.1111/febs.17211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 04/23/2024] [Accepted: 06/14/2024] [Indexed: 07/01/2024]
Abstract
Within the three-dimensional (3D) nuclear space, the genome organizes into a series of orderly structures that impose important influences on gene regulation. T lymphocytes, crucial players in adaptive immune responses, undergo intricate transcriptional remodeling upon activation, leading to differentiation into specific effector and memory T cell subsets. Recent evidence suggests that T cell activation is accompanied by dynamic changes in genome architecture at multiple levels, providing a unique biological context to explore the functional relevance and molecular mechanisms of 3D genome organization. Here, we summarize recent advances that link the reorganization of genome architecture to the remodeling of transcriptional programs and conversion of cell fates during T cell activation and differentiation. We further discuss how various chromatin architecture regulators, including CCCTC-binding factor and several transcription factors, collectively modulate the genome architecture during this process.
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Affiliation(s)
- Bao Wang
- Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Reproductive Medicine, Shanghai Jiao Tong University School of Medicine, China
| | - Qian Bian
- Shanghai Institute of Precision Medicine, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, China
- Shanghai Key Laboratory of Reproductive Medicine, Shanghai Jiao Tong University School of Medicine, China
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2
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Murwanti R, Gani AP, Sa'adah M, Daffa ARA, Hutajulu AMC. Immuno-enhancement activity of meniran (Phyllanthus niruri L.) and temu mangga rhizome (Curcuma mangga Val.) combination extract in cyclophosphamide-induced immunodeficient mice. Int Immunopharmacol 2025; 146:113870. [PMID: 39721458 DOI: 10.1016/j.intimp.2024.113870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2024] [Revised: 12/11/2024] [Accepted: 12/12/2024] [Indexed: 12/28/2024]
Abstract
Immunomodulators play a crucial role in maintaining overall health and enhancing the body's defense against various diseases. In Indonesian traditional medicinal practices, meniran (Phyllanthus niruri L.) and temu mangga rhizome (Curcuma mangga Val) are well-regarded for their health benefits and therapeutic properties. Notably, meniran is utilized in jamu, an ancient Indonesian herbal tonic with widespread use in traditional healthcare. This study aimed to formulate a synergistic herbal blend by combining ethanolic extracts of meniran and temu mangga rhizome, assessing their efficacy against Cyclophosphamide (CYP)-induced immunosuppression in a murine model and elucidating potential mechanisms for immune restoration. We conducted quantitative and qualitative investigations of rutin and demethoxycurcumin composition in the combination extracts using high-performance thin-layer chromatography (HPTLC). An in vivo investigation was performed using a CYP-induced immunosuppressed murine model to assess the immunomodulatory effects of the combination extracts. The immunostimulant effect was investigated by analyzing hematology, macrophage activity (Nitric Oxide secretion, phagocytic capacity and index), lymphocyte proliferation (MTT assay), cytokine levels (IL-6 and TNF-α by ELISA), and analysis of CD4+ and CD8+ T cell populations using flow cytometry. Results demonstrated that the combined extracts effectively mitigated the immunosuppressive effects of CYP, significantly enhancing various immune indicators, including red blood cell count, hemoglobin levels, macrophage activity, lymphocyte proliferation, and cytokine serum levels. However, negligible effects were observed on erythrocyte indexes compared to the CYP-induced group. In conclusion, the combination of meniran (Phyllanthus niruri L.) and temu mangga rhizome (Curcuma mangga Val) substantially enhances various aspects of immune function, such as red blood cell count, hemoglobin levels, and macrophage activity, suggesting promising potential for immunomodulation in therapeutic contexts.
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Affiliation(s)
- Retno Murwanti
- Department of Pharmacology and Clinical Pharmacy, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia; Medicinal Plants and Natural Products Research Center, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia.
| | - Andayana Puspitasari Gani
- Department of Pharmaceutical Biology, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia; Medicinal Plants and Natural Products Research Center, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia.
| | - Miftahus Sa'adah
- Department of Pharmaceutics, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia.
| | - Ahmad Ridho Abi Daffa
- Undergraduate Program, Faculty of Pharmacy, Universitas Gadjah Mada, Yogyakarta, Indonesia.
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3
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Pahl MC, Sharma P, Thomas RM, Thompson Z, Mount Z, Pippin JA, Morawski PA, Sun P, Su C, Campbell D, Grant SFA, Wells AD. Dynamic chromatin architecture identifies new autoimmune-associated enhancers for IL2 and novel genes regulating CD4+ T cell activation. eLife 2024; 13:RP96852. [PMID: 39302339 PMCID: PMC11418197 DOI: 10.7554/elife.96852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/22/2024] Open
Abstract
Genome-wide association studies (GWAS) have identified hundreds of genetic signals associated with autoimmune disease. The majority of these signals are located in non-coding regions and likely impact cis-regulatory elements (cRE). Because cRE function is dynamic across cell types and states, profiling the epigenetic status of cRE across physiological processes is necessary to characterize the molecular mechanisms by which autoimmune variants contribute to disease risk. We localized risk variants from 15 autoimmune GWAS to cRE active during TCR-CD28 co-stimulation of naïve human CD4+ T cells. To characterize how dynamic changes in gene expression correlate with cRE activity, we measured transcript levels, chromatin accessibility, and promoter-cRE contacts across three phases of naive CD4+ T cell activation using RNA-seq, ATAC-seq, and HiC. We identified ~1200 protein-coding genes physically connected to accessible disease-associated variants at 423 GWAS signals, at least one-third of which are dynamically regulated by activation. From these maps, we functionally validated a novel stretch of evolutionarily conserved intergenic enhancers whose activity is required for activation-induced IL2 gene expression in human and mouse, and is influenced by autoimmune-associated genetic variation. The set of genes implicated by this approach are enriched for genes controlling CD4+ T cell function and genes involved in human inborn errors of immunity, and we pharmacologically validated eight implicated genes as novel regulators of T cell activation. These studies directly show how autoimmune variants and the genes they regulate influence processes involved in CD4+ T cell proliferation and activation.
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Affiliation(s)
- Matthew C Pahl
- Center for Spatial and Functional Genomics, Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Division of Human Genetics, The Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Prabhat Sharma
- Center for Spatial and Functional Genomics, Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Pathology, The Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Rajan M Thomas
- Center for Spatial and Functional Genomics, Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Pathology, The Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Zachary Thompson
- Center for Spatial and Functional Genomics, Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Pathology, The Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Zachary Mount
- Center for Spatial and Functional Genomics, Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Pathology, The Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
| | - James A Pippin
- Center for Spatial and Functional Genomics, Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Division of Human Genetics, The Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Peter A Morawski
- Benaroya Research Institute at Virginia MasonSeattleUnited States
| | - Peng Sun
- Center for Spatial and Functional Genomics, Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Pathology, The Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Chun Su
- Center for Spatial and Functional Genomics, Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Division of Human Genetics, The Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Daniel Campbell
- Benaroya Research Institute at Virginia MasonSeattleUnited States
- Department of Immunology, University of Washington School of MedicineSeattleUnited States
| | - Struan FA Grant
- Center for Spatial and Functional Genomics, Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Division of Human Genetics, The Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Genetics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Department of Pediatrics, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Division of Endocrinology and Diabetes, The Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
| | - Andrew D Wells
- Center for Spatial and Functional Genomics, Children's Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Pathology, The Children’s Hospital of PhiladelphiaPhiladelphiaUnited States
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
- Institute for Immunology, Perelman School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
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Stasevich EM, Simonova AV, Bogomolova EA, Murashko MM, Uvarova AN, Zheremyan EA, Korneev KV, Schwartz AM, Kuprash DV, Demin DE. Cut from the same cloth: RNAs transcribed from regulatory elements. BIOCHIMICA ET BIOPHYSICA ACTA. GENE REGULATORY MECHANISMS 2024; 1867:195049. [PMID: 38964653 DOI: 10.1016/j.bbagrm.2024.195049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 06/25/2024] [Accepted: 06/28/2024] [Indexed: 07/06/2024]
Abstract
A certain degree of chromatin openness is necessary for the activity of transcription-regulating regions within the genome, facilitating accessibility to RNA polymerases and subsequent synthesis of regulatory element RNAs (regRNAs) from these regions. The rapidly increasing number of studies underscores the significance of regRNAs across diverse cellular processes and diseases, challenging the paradigm that these transcripts are non-functional transcriptional noise. This review explores the multifaceted roles of regRNAs in human cells, encompassing rather well-studied entities such as promoter RNAs and enhancer RNAs (eRNAs), while also providing insights into overshadowed silencer RNAs and insulator RNAs. Furthermore, we assess notable examples of shorter regRNAs, like miRNAs, snRNAs, and snoRNAs, playing important roles. Expanding our discourse, we deliberate on the potential usage of regRNAs as biomarkers and novel targets for cancer and other human diseases.
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Affiliation(s)
- E M Stasevich
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | - A V Simonova
- Laboratory of Intracellular Signaling in Health and Disease, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | - E A Bogomolova
- Laboratory of Intracellular Signaling in Health and Disease, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia; Moscow Center for Advanced Studies, Moscow, Russia
| | - M M Murashko
- Laboratory of Intracellular Signaling in Health and Disease, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia; Moscow Center for Advanced Studies, Moscow, Russia
| | - A N Uvarova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | - E A Zheremyan
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | - K V Korneev
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | - A M Schwartz
- Department of Human Biology, University of Haifa, Haifa, Israel
| | - D V Kuprash
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia
| | - D E Demin
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, Moscow, Russia.
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Di Domenico M, Serretiello E, Smimmo A, Vieira e Silva FF, Raimondi SA, Pascariello C, Marino MM, Lo Muzio L, Caponio VCA, Cantore S, Ballini A. Monitoring of Immune Memory by Phenotypical Lymphocyte Subsets Identikit: An Observational Study in a Blood Donors' Cohort. J Pers Med 2024; 14:733. [PMID: 39063987 PMCID: PMC11277854 DOI: 10.3390/jpm14070733] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Revised: 07/01/2024] [Accepted: 07/05/2024] [Indexed: 07/28/2024] Open
Abstract
The cross-talk between the innate and adaptive immune response represents the first defense weapon against the threat of pathogens. Substantial evidence has shown a relationship between immune phenotype lymphocytes and COVID-19 disease severity and/or implication in susceptibility to SARS-CoV-2 infection. Recently, belonging to ABO blood groups has been investigated as a correlation factor to COVID-19 disease. This pilot study investigated lymphocyte typing in a cohort of blood donors to understand the underlying mechanism in SARS-CoV-2 infection linked to the blood group. The study cohort consisted of 20-64-year-old subjects, without comorbidities, from both sexes, who were COVID-19 vaccinated with previous or no infection history. Whole blood samples, collected at A.O.R.N. Sant'Anna and San Sebastiano Hospital (Campania Region), were processed by multiparametric cytofluorimetric assay, to characterize CD4+ helper and CD8+ cytotoxic T cell CD3+ subpopulations. The CD45RA, CCR7, CD27, CD28, CD57 and PD-1 markers were investigated to delineate the peripheral T-cell maturation stages. Differences were detected in ABO blood types in CD3+, CD4+ gated on CD3+, CD8+ and CD8+ gated on CD3+ percentage. These results contribute to identifying a memory cell "identikit" profile in COVID-19 disease, thus leading to a useful tool in precision medicine.
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Affiliation(s)
- Marina Di Domenico
- Department of Precision Medicine, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (M.D.D.); (E.S.); (A.S.); (F.F.V.e.S.); (M.M.M.); (A.B.)
| | - Enrica Serretiello
- Department of Precision Medicine, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (M.D.D.); (E.S.); (A.S.); (F.F.V.e.S.); (M.M.M.); (A.B.)
- Clinical Pathology and Microbiology Unit, San Giovanni di Dio and Ruggi D’Aragona University Hospital, 84131 Salerno, Italy
| | - Annafrancesca Smimmo
- Department of Precision Medicine, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (M.D.D.); (E.S.); (A.S.); (F.F.V.e.S.); (M.M.M.); (A.B.)
| | - Fábio França Vieira e Silva
- Department of Precision Medicine, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (M.D.D.); (E.S.); (A.S.); (F.F.V.e.S.); (M.M.M.); (A.B.)
| | - Sonia Anna Raimondi
- Azienda Ospedaliera “Sant’Anna e San Sebastiano”, 81100 Caserta, Italy; (S.A.R.); (C.P.)
| | - Caterina Pascariello
- Azienda Ospedaliera “Sant’Anna e San Sebastiano”, 81100 Caserta, Italy; (S.A.R.); (C.P.)
| | - Maria Michela Marino
- Department of Precision Medicine, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (M.D.D.); (E.S.); (A.S.); (F.F.V.e.S.); (M.M.M.); (A.B.)
| | - Lorenzo Lo Muzio
- Department of Clinical and Experimental Medicine, University of Foggia, 71100 Foggia, Italy; (L.L.M.); (V.C.A.C.)
| | - Vito Carlo Alberto Caponio
- Department of Clinical and Experimental Medicine, University of Foggia, 71100 Foggia, Italy; (L.L.M.); (V.C.A.C.)
| | - Stefania Cantore
- Department of Precision Medicine, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (M.D.D.); (E.S.); (A.S.); (F.F.V.e.S.); (M.M.M.); (A.B.)
| | - Andrea Ballini
- Department of Precision Medicine, University of Campania “Luigi Vanvitelli”, 80138 Naples, Italy; (M.D.D.); (E.S.); (A.S.); (F.F.V.e.S.); (M.M.M.); (A.B.)
- Department of Clinical and Experimental Medicine, University of Foggia, 71100 Foggia, Italy; (L.L.M.); (V.C.A.C.)
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Kuhl H, Tan WH, Klopp C, Kleiner W, Koyun B, Ciorpac M, Feron R, Knytl M, Kloas W, Schartl M, Winkler C, Stöck M. A candidate sex determination locus in amphibians which evolved by structural variation between X- and Y-chromosomes. Nat Commun 2024; 15:4781. [PMID: 38839766 PMCID: PMC11153619 DOI: 10.1038/s41467-024-49025-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 05/17/2024] [Indexed: 06/07/2024] Open
Abstract
Most vertebrates develop distinct females and males, where sex is determined by repeatedly evolved environmental or genetic triggers. Undifferentiated sex chromosomes and large genomes have caused major knowledge gaps in amphibians. Only a single master sex-determining gene, the dmrt1-paralogue (dm-w) of female-heterogametic clawed frogs (Xenopus; ZW♀/ZZ♂), is known across >8740 species of amphibians. In this study, by combining chromosome-scale female and male genomes of a non-model amphibian, the European green toad, Bufo(tes) viridis, with ddRAD- and whole genome pool-sequencing, we reveal a candidate master locus, governing a male-heterogametic system (XX♀/XY♂). Targeted sequencing across multiple taxa uncovered structural X/Y-variation in the 5'-regulatory region of the gene bod1l, where a Y-specific non-coding RNA (ncRNA-Y), only expressed in males, suggests that this locus initiates sex-specific differentiation. Developmental transcriptomes and RNA in-situ hybridization show timely and spatially relevant sex-specific ncRNA-Y and bod1l-gene expression in primordial gonads. This coincided with differential H3K4me-methylation in pre-granulosa/pre-Sertoli cells, pointing to a specific mechanism of amphibian sex determination.
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Affiliation(s)
- Heiner Kuhl
- Leibniz-Institute of Freshwater Ecology and Inland Fisheries, IGB, Müggelseedamm 301 & 310, 12587, Berlin, Germany
| | - Wen Hui Tan
- Department of Biological Sciences and Centre for Bioimaging Sciences, National University of Singapore, 14 Science Drive 4, Block S1A, Level 6, Singapore, 117543, Singapore
| | - Christophe Klopp
- SIGENAE, Plate-forme Bio-informatique Genotoul, Mathématiques et Informatique Appliquées de Toulouse, INRAe, 31326, Castanet-Tolosan, France
| | - Wibke Kleiner
- Leibniz-Institute of Freshwater Ecology and Inland Fisheries, IGB, Müggelseedamm 301 & 310, 12587, Berlin, Germany
| | - Baturalp Koyun
- Leibniz-Institute of Freshwater Ecology and Inland Fisheries, IGB, Müggelseedamm 301 & 310, 12587, Berlin, Germany
- Department of Molecular Biology and Genetics, Genetics, Faculty of Science, Bilkent University, SB Building, Ankara, 06800, Turkey
| | - Mitica Ciorpac
- Danube Delta National Institute for Research and Development, Tulcea, 820112, Romania
- Advanced Research and Development Center for Experimental Medicine-CEMEX, "Grigore T. Popa", University of Medicine and Pharmacy, Mihail Kogălniceanu Street 9-13, Iasi, 700259, Romania
| | - Romain Feron
- Department of Ecology and Evolution, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Martin Knytl
- Department of Cell Biology, Faculty of Science, Charles University, Viničná 7, Prague, 12843, Czech Republic
- Department of Biology, McMaster University, 1280 Main Street West, Hamilton, L8S 4K1, Ontario, ON, Canada
| | - Werner Kloas
- Leibniz-Institute of Freshwater Ecology and Inland Fisheries, IGB, Müggelseedamm 301 & 310, 12587, Berlin, Germany
| | - Manfred Schartl
- Developmental Biochemistry, Biocenter, University of Wuerzburg, Am Hubland, 97074, Wuerzburg, Germany
- The Xiphophorus Genetic Stock Center, Department of Chemistry and Biochemistry, Texas State University, San Marcos, TX, 78666, USA
| | - Christoph Winkler
- Department of Biological Sciences and Centre for Bioimaging Sciences, National University of Singapore, 14 Science Drive 4, Block S1A, Level 6, Singapore, 117543, Singapore.
| | - Matthias Stöck
- Leibniz-Institute of Freshwater Ecology and Inland Fisheries, IGB, Müggelseedamm 301 & 310, 12587, Berlin, Germany.
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Shellard EM, Rane SS, Eyre S, Warren RB. Functional Genomics and Insights into the Pathogenesis and Treatment of Psoriasis. Biomolecules 2024; 14:548. [PMID: 38785955 PMCID: PMC11117854 DOI: 10.3390/biom14050548] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 04/17/2024] [Accepted: 04/24/2024] [Indexed: 05/25/2024] Open
Abstract
Psoriasis is a lifelong, systemic, immune mediated inflammatory skin condition, affecting 1-3% of the world's population, with an impact on quality of life similar to diseases like cancer or diabetes. Genetics are the single largest risk factor in psoriasis, with Genome-Wide Association (GWAS) studies showing that many psoriasis risk genes lie along the IL-23/Th17 axis. Potential psoriasis risk genes determined through GWAS can be annotated and characterised using functional genomics, allowing the identification of novel drug targets and the repurposing of existing drugs. This review is focused on the IL-23/Th17 axis, providing an insight into key cell types, cytokines, and intracellular signaling pathways involved. This includes examination of currently available biological treatments, time to relapse post drug withdrawal, and rates of primary/secondary drug failure, showing the need for greater understanding of the underlying genetic mechanisms of psoriasis and how they can impact treatment. This could allow for patient stratification towards the treatment most likely to reduce the burden of disease for the longest period possible.
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Affiliation(s)
- Elan May Shellard
- Faculty of Biology, Medicine and Health, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, The University of Manchester, Manchester M13 9PT, UK
| | - Shraddha S. Rane
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, NIHR Manchester Biomedical Research Centre, The University of Manchester, Manchester M13 9PT, UK; (S.S.R.); (S.E.)
| | - Stephen Eyre
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, NIHR Manchester Biomedical Research Centre, The University of Manchester, Manchester M13 9PT, UK; (S.S.R.); (S.E.)
| | - Richard B. Warren
- Dermatology Centre, Northern Care Alliance NHS Foundation Trust, Manchester M6 8HD, UK;
- NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M23 9LT, UK
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8
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Plaza-Jennings A, Akbarian S. Genomic Exploration of the Brain in People Infected with HIV-Recent Progress and the Road Ahead. Curr HIV/AIDS Rep 2023; 20:357-367. [PMID: 37947981 PMCID: PMC10719125 DOI: 10.1007/s11904-023-00675-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/02/2023] [Indexed: 11/12/2023]
Abstract
PURPOSE OF REVIEW The adult human brain harbors billions of microglia and other myeloid and lymphoid cells highly susceptible to HIV infection and retroviral insertion into the nuclear DNA. HIV infection of the brain is important because the brain is a potentially large reservoir site that may be a barrier to HIV cure strategies and because infection can lead to the development of HIV-associated neurocognitive disorder. To better understand both the central nervous system (CNS) reservoir and how it can cause neurologic dysfunction, novel genomic, epigenomic, transcriptomic, and proteomic approaches need to be employed. Several characteristics of the reservoir are important to learn, including where the virus integrates, whether integrated proviruses are intact or defective, whether integrated proviruses can be reactivated from a latent state to seed ongoing infection, and how this all impacts brain function. RECENT FINDINGS Here, we discuss similarities and differences of viral integration sites between brain and blood and discuss evidence for and against the hypothesis that in the absence of susceptible T-lymphocytes in the periphery, the virus housing in the infected brain is not able to sustain a systemic infection. Moreover, microglia from HIV + brains across a wide range of disease severity appear to share one type of common alteration, which is defined by downregulated expression, and repressive chromosomal compartmentalization, for microglial genes regulating synaptic connectivity. Therefore, viral infection of the brain, including in immunocompetent cases with near-normal levels of CD4 blood lymphocytes, could be associated with an early disruption in microglia-dependent neuronal support functions, contributing to cognitive and neurological deficits in people living with HIV.
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Affiliation(s)
- Amara Plaza-Jennings
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Nash Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Schahram Akbarian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Nash Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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Zhang G, Li Y, Wei G. Multi-omic analysis reveals dynamic changes of three-dimensional chromatin architecture during T cell differentiation. Commun Biol 2023; 6:773. [PMID: 37488215 PMCID: PMC10366224 DOI: 10.1038/s42003-023-05141-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 07/13/2023] [Indexed: 07/26/2023] Open
Abstract
Cell differentiation results in widespread changes in transcriptional programs as well as multi-level remodeling of three-dimensional genome architecture. Nonetheless, few synthetically investigate the chromatin higher-order landscapes in different T helper (Th) cells. Using RNA-Seq, ATAC-Seq and Hi-C assays, we characterize dynamic changes in chromatin organization at different levels during Naive CD4+ T cells differentiation into T helper 17 (Th17) and T helper 1 (Th1) cells. Upon differentiation, we observe decreased short-range and increased extra-long-range chromatin interactions. Although there is no apparent global switch in the A/B compartments, Th cells display the weaker compartmentalization. A portion of topologically associated domains are rearranged. Furthermore, we identify cell-type specific enhancer-promoter loops, many of which are associated with functional genes in Th cells, such as Rorc facilitating Th17 differentiation and Hif1a responding to intracellular oxygen levels in Th1. Taken together, these results uncover the general patterns of chromatin reorganization and epigenetic landscapes of gene regulation during T helper cell differentiation.
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Affiliation(s)
- Ge Zhang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Ying Li
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
| | - Gang Wei
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
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Schoonhoven AOV, de Bruijn MJ, Stikker B, Brouwer RW, Braunstahl GJ, van IJcken WF, Graf T, Huylebroeck D, Hendriks RW, Stik G, Stadhouders R. 3D chromatin reprogramming primes human memory T H2 cells for rapid recall and pathogenic dysfunction. Sci Immunol 2023; 8:eadg3917. [PMID: 37418545 PMCID: PMC7617366 DOI: 10.1126/sciimmunol.adg3917] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 06/13/2023] [Indexed: 07/09/2023]
Abstract
Memory T cells provide long-lasting defense responses through their ability to rapidly reactivate, but how they efficiently "recall" an inflammatory transcriptional program remains unclear. Here, we show that human CD4+ memory T helper 2 (TH2) cells carry a chromatin landscape synergistically reprogrammed at both one-dimensional (1D) and 3D levels to accommodate recall responses, which is absent in naive T cells. In memory TH2 cells, recall genes were epigenetically primed through the maintenance of transcription-permissive chromatin at distal (super)enhancers organized in long-range 3D chromatin hubs. Precise transcriptional control of key recall genes occurred inside dedicated topologically associating domains ("memory TADs"), in which activation-associated promoter-enhancer interactions were preformed and exploited by AP-1 transcription factors to promote rapid transcriptional induction. Resting memory TH2 cells from patients with asthma showed premature activation of primed recall circuits, linking aberrant transcriptional control of recall responses to chronic inflammation. Together, our results implicate stable multiscale reprogramming of chromatin organization as a key mechanism underlying immunological memory and dysfunction in T cells.
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Affiliation(s)
- Anne Onrust-van Schoonhoven
- Department of Pulmonary Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Cell Biology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Marjolein J.W. de Bruijn
- Department of Pulmonary Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Bernard Stikker
- Department of Pulmonary Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Rutger W.W. Brouwer
- Center for Biomics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Gert-Jan Braunstahl
- Department of Pulmonary Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Respiratory Medicine, Franciscus Gasthuis and Vlietland, Rotterdam, Netherlands
| | | | - Thomas Graf
- Centre for Genomic Regulation (CRG) and Institute of Science and Technology (BIST), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Danny Huylebroeck
- Department of Cell Biology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Rudi W. Hendriks
- Department of Pulmonary Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Grégoire Stik
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, Spain
| | - Ralph Stadhouders
- Department of Pulmonary Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
- Department of Cell Biology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
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11
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Qiu Y, Feng D, Jiang W, Zhang T, Lu Q, Zhao M. 3D genome organization and epigenetic regulation in autoimmune diseases. Front Immunol 2023; 14:1196123. [PMID: 37346038 PMCID: PMC10279977 DOI: 10.3389/fimmu.2023.1196123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 05/17/2023] [Indexed: 06/23/2023] Open
Abstract
Three-dimensional (3D) genomics is an emerging field of research that investigates the relationship between gene regulatory function and the spatial structure of chromatin. Chromatin folding can be studied using chromosome conformation capture (3C) technology and 3C-based derivative sequencing technologies, including chromosome conformation capture-on-chip (4C), chromosome conformation capture carbon copy (5C), and high-throughput chromosome conformation capture (Hi-C), which allow scientists to capture 3D conformations from a single site to the entire genome. A comprehensive analysis of the relationships between various regulatory components and gene function also requires the integration of multi-omics data such as genomics, transcriptomics, and epigenomics. 3D genome folding is involved in immune cell differentiation, activation, and dysfunction and participates in a wide range of diseases, including autoimmune diseases. We describe hierarchical 3D chromatin organization in this review and conclude with characteristics of C-techniques and multi-omics applications of the 3D genome. In addition, we describe the relationship between 3D genome structure and the differentiation and maturation of immune cells and address how changes in chromosome folding contribute to autoimmune diseases.
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Affiliation(s)
- Yueqi Qiu
- Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China
- Key Laboratory of Basic and Translational Research on Immune-Mediated Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing, China
| | - Delong Feng
- Department of Dermatology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Wenjuan Jiang
- Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China
- Key Laboratory of Basic and Translational Research on Immune-Mediated Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing, China
| | - Tingting Zhang
- Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China
- Key Laboratory of Basic and Translational Research on Immune-Mediated Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing, China
- State Key Laboratory of Natural Medicines, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
| | - Qianjin Lu
- Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China
- Key Laboratory of Basic and Translational Research on Immune-Mediated Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing, China
- Department of Dermatology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Ming Zhao
- Institute of Dermatology, Chinese Academy of Medical Sciences and Peking Union Medical College, Nanjing, China
- Key Laboratory of Basic and Translational Research on Immune-Mediated Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing, China
- Department of Dermatology, The Second Xiangya Hospital of Central South University, Changsha, China
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12
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Stankey CT, Lee JC. Translating non-coding genetic associations into a better understanding of immune-mediated disease. Dis Model Mech 2023; 16:dmm049790. [PMID: 36897113 PMCID: PMC10040244 DOI: 10.1242/dmm.049790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/11/2023] Open
Abstract
Genome-wide association studies have identified hundreds of genetic loci that are associated with immune-mediated diseases. Most disease-associated variants are non-coding, and a large proportion of these variants lie within enhancers. As a result, there is a pressing need to understand how common genetic variation might affect enhancer function and thereby contribute to immune-mediated (and other) diseases. In this Review, we first describe statistical and experimental methods to identify causal genetic variants that modulate gene expression, including statistical fine-mapping and massively parallel reporter assays. We then discuss approaches to characterise the mechanisms by which these variants modulate immune function, such as clustered regularly interspaced short palindromic repeats (CRISPR)-based screens. We highlight examples of studies that, by elucidating the effects of disease variants within enhancers, have provided important insights into immune function and uncovered key pathways of disease.
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Affiliation(s)
- Christina T. Stankey
- Genetic Mechanisms of Disease Laboratory, The Francis Crick Institute, London NW1 1AT, UK
- Department of Immunology and Inflammation, Imperial College London, London W12 0NN, UK
| | - James C. Lee
- Genetic Mechanisms of Disease Laboratory, The Francis Crick Institute, London NW1 1AT, UK
- Institute of Liver and Digestive Health, Royal Free Hospital, University College London, London NW3 2PF, UK
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13
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Zhao M, Feng D, Hu L, Liu L, Wu J, Hu Z, Long H, Kuang Q, Ouyang L, Lu Q. 3D genome alterations in T cells associated with disease activity of systemic lupus erythematosus. Ann Rheum Dis 2023; 82:226-234. [PMID: 36690410 PMCID: PMC9887402 DOI: 10.1136/ard-2022-222653] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Accepted: 08/17/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVES Three-dimensional (3D) genome alterations can dysregulate gene expression by rewiring physical interactions within chromosomes in a tissue-specific or cell-specific manner and lead to diseases. We aimed to elucidate the 3D genome structure and its role in gene expression networks dysregulated in systemic lupus erythematosus (SLE). METHODS We performed Hi-C experiments using CD4+ T cells from 7 patients with SLE and 5 age-matched and sex-matched healthy controls (HCs) combined with RNA sequencing analysis. Further integrative analyses, including transcription factor motif enrichment, SPI1 knockdown and histone modifications (H3K27ac, H3K4me1, H3K4me3), were performed for altered loop-associated gene loci in SLE. RESULTS We deciphered the 3D chromosome organisation in T cells of patients with SLE and found it was clearly distinct from that of HCs and closely associated with the disease activity of SLE. Importantly, we identified loops within chromosomes associated with the disease activity of SLE and differentially expressed genes and found some key histone modifications close to these loops. Moreover, we demonstrated the contribution of the transcription factor SPI1, whose motif is located in the altered loop in SLE, to the overexpression of interferon pathway gene. In addition, we identified the potential influences of genetic variations in 3D genome alterations in SLE. CONCLUSIONS Our results highlight the 3D genome structure alterations associated with SLE development and provide a foundation for future interrogation of the relationships between chromosome structure and gene expression control in SLE.
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Affiliation(s)
- Ming Zhao
- Department of Dermatology, The Second Xiangya Hospital of Central South University, Changsha, China
- Key Laboratory of Basic and Translational Research on Immune-Mediated Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing, China
| | - Delong Feng
- Department of Dermatology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Longyuan Hu
- Department of Dermatology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Lin Liu
- Epigenetic Group, Frasergen Bioinformatics Co, Ltd, Wuhan, China
| | - Jiali Wu
- Department of Dermatology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Zhi Hu
- Department of Dermatology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Haojun Long
- Department of Dermatology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Qiqi Kuang
- Department of Dermatology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Lianlian Ouyang
- Department of Dermatology, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Qianjin Lu
- Department of Dermatology, The Second Xiangya Hospital of Central South University, Changsha, China
- Key Laboratory of Basic and Translational Research on Immune-Mediated Skin Diseases, Institute of Dermatology, Chinese Academy of Medical Sciences, Nanjing, China
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14
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Tomás-Daza L, Rovirosa L, López-Martí P, Nieto-Aliseda A, Serra F, Planas-Riverola A, Molina O, McDonald R, Ghevaert C, Cuatrecasas E, Costa D, Camós M, Bueno C, Menéndez P, Valencia A, Javierre BM. Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution. Nat Commun 2023; 14:268. [PMID: 36650138 PMCID: PMC9845235 DOI: 10.1038/s41467-023-35911-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 01/06/2023] [Indexed: 01/18/2023] Open
Abstract
Long-range interactions between regulatory elements and promoters are key in gene transcriptional control; however, their study requires large amounts of starting material, which is not compatible with clinical scenarios nor the study of rare cell populations. Here we introduce low input capture Hi-C (liCHi-C) as a cost-effective, flexible method to map and robustly compare promoter interactomes at high resolution. As proof of its broad applicability, we implement liCHi-C to study normal and malignant human hematopoietic hierarchy in clinical samples. We demonstrate that the dynamic promoter architecture identifies developmental trajectories and orchestrates transcriptional transitions during cell-state commitment. Moreover, liCHi-C enables the identification of disease-relevant cell types, genes and pathways potentially deregulated by non-coding alterations at distal regulatory elements. Finally, we show that liCHi-C can be harnessed to uncover genome-wide structural variants, resolve their breakpoints and infer their pathogenic effects. Collectively, our optimized liCHi-C method expands the study of 3D chromatin organization to unique, low-abundance cell populations, and offers an opportunity to uncover factors and regulatory networks involved in disease pathogenesis.
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Affiliation(s)
- Laureano Tomás-Daza
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain
- Barcelona Supercomputing Center, Barcelona, Barcelona, Spain
| | - Llorenç Rovirosa
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain
| | - Paula López-Martí
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain
- Barcelona Supercomputing Center, Barcelona, Barcelona, Spain
| | | | - François Serra
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain
| | | | - Oscar Molina
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain
| | | | - Cedric Ghevaert
- Wellcome-MRC Cambridge Stem Cell Institute, Cambridge, UK
- NHS Blood and Transplant, Cambridge, UK
| | - Esther Cuatrecasas
- Pediatric Institute of Rare Diseases, Sant Joan de Déu Hospital, Esplugues de Llobregat, Barcelona, Spain
| | - Dolors Costa
- Hospital Clinic, Barcelona, Spain
- Institute of Biomedical Research August Pi i Sunyer, Barcelona, Spain
- Cancer Network Biomedical Research Center, Barcelona, Spain
| | - Mireia Camós
- Sant Joan de Déu Research Institute, Esplugues de Llobregat, Barcelona, Spain
- Sant Joan de Déu Hospital, Esplugues de Llobregat, Barcelona, Spain
- Center for Biomedical Research in the Rare Diseases Network (CIBERER), Carlos III Health Institute, Madrid, Spain
| | - Clara Bueno
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain
| | - Pablo Menéndez
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Alfonso Valencia
- Barcelona Supercomputing Center, Barcelona, Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
| | - Biola M Javierre
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, Spain.
- Institute for Health Science Research Germans Trias i Pujol, Badalona, Barcelona, Spain.
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15
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Plaza-Jennings AL, Valada A, O'Shea C, Iskhakova M, Hu B, Javidfar B, Ben Hutta G, Lambert TY, Murray J, Kassim B, Chandrasekaran S, Chen BK, Morgello S, Won H, Akbarian S. HIV integration in the human brain is linked to microglial activation and 3D genome remodeling. Mol Cell 2022; 82:4647-4663.e8. [PMID: 36525955 PMCID: PMC9831062 DOI: 10.1016/j.molcel.2022.11.016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 09/12/2022] [Accepted: 11/17/2022] [Indexed: 12/23/2022]
Abstract
To explore genome organization and function in the HIV-infected brain, we applied single-nuclei transcriptomics, cell-type-specific chromosomal conformation mapping, and viral integration site sequencing (IS-seq) to frontal cortex from individuals with encephalitis (HIVE) and without (HIV+). Derepressive changes in 3D genomic compartment structures in HIVE microglia were linked to the transcriptional activation of interferon (IFN) signaling and cell migratory pathways, while transcriptional downregulation and repressive compartmentalization of neuronal health and signaling genes occurred in both HIVE and HIV+ microglia. IS-seq recovered 1,221 brain integration sites showing distinct genomic patterns compared with peripheral lymphocytes, with enrichment for sequences newly mobilized into a permissive chromatin environment after infection. Viral transcription occurred in a subset of highly activated microglia comprising 0.33% of all nuclei in HIVE brain. Our findings point to disrupted microglia-neuronal interactions in HIV and link retroviral integration to remodeling of the microglial 3D genome during infection.
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Affiliation(s)
- Amara L Plaza-Jennings
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Aditi Valada
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Callan O'Shea
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Marina Iskhakova
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Benxia Hu
- UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Behnam Javidfar
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Gabriella Ben Hutta
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Tova Y Lambert
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jacinta Murray
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Bibi Kassim
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sandhya Chandrasekaran
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Benjamin K Chen
- Division of Infectious Diseases, Department of Medicine, Immunology Institute, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Susan Morgello
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Pathology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Hyejung Won
- UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC 27599, USA; Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
| | - Schahram Akbarian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
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16
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Orozco G, Schoenfelder S, Walker N, Eyre S, Fraser P. 3D genome organization links non-coding disease-associated variants to genes. Front Cell Dev Biol 2022; 10:995388. [PMID: 36340032 PMCID: PMC9631826 DOI: 10.3389/fcell.2022.995388] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 09/27/2022] [Indexed: 11/13/2022] Open
Abstract
Genome sequencing has revealed over 300 million genetic variations in human populations. Over 90% of variants are single nucleotide polymorphisms (SNPs), the remainder include short deletions or insertions, and small numbers of structural variants. Hundreds of thousands of these variants have been associated with specific phenotypic traits and diseases through genome wide association studies which link significant differences in variant frequencies with specific phenotypes among large groups of individuals. Only 5% of disease-associated SNPs are located in gene coding sequences, with the potential to disrupt gene expression or alter of the function of encoded proteins. The remaining 95% of disease-associated SNPs are located in non-coding DNA sequences which make up 98% of the genome. The role of non-coding, disease-associated SNPs, many of which are located at considerable distances from any gene, was at first a mystery until the discovery that gene promoters regularly interact with distal regulatory elements to control gene expression. Disease-associated SNPs are enriched at the millions of gene regulatory elements that are dispersed throughout the non-coding sequences of the genome, suggesting they function as gene regulation variants. Assigning specific regulatory elements to the genes they control is not straightforward since they can be millions of base pairs apart. In this review we describe how understanding 3D genome organization can identify specific interactions between gene promoters and distal regulatory elements and how 3D genomics can link disease-associated SNPs to their target genes. Understanding which gene or genes contribute to a specific disease is the first step in designing rational therapeutic interventions.
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Affiliation(s)
- Gisela Orozco
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
- NIHR Manchester Biomedical Research Centre, Manchester University Foundation Trust, Manchester, United Kingdom
| | - Stefan Schoenfelder
- Enhanc3D Genomics Ltd., Cambridge, United Kingdom
- Epigenetics Programme, The Babraham Institute, Babraham Research Campus, CB22 3AT Cambridge, Cambridge, United Kingdom
| | | | - Stephan Eyre
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
- NIHR Manchester Biomedical Research Centre, Manchester University Foundation Trust, Manchester, United Kingdom
| | - Peter Fraser
- Enhanc3D Genomics Ltd., Cambridge, United Kingdom
- Department of Biological Science, Florida State University, Tallahassee, FL, United States
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17
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Cuartero S, Stik G, Stadhouders R. Three-dimensional genome organization in immune cell fate and function. Nat Rev Immunol 2022; 23:206-221. [PMID: 36127477 DOI: 10.1038/s41577-022-00774-5] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/04/2022] [Indexed: 11/09/2022]
Abstract
Immune cell development and activation demand the precise and coordinated control of transcriptional programmes. Three-dimensional (3D) organization of the genome has emerged as an important regulator of chromatin state, transcriptional activity and cell identity by facilitating or impeding long-range genomic interactions among regulatory elements and genes. Chromatin folding thus enables cell type-specific and stimulus-specific transcriptional responses to extracellular signals, which are essential for the control of immune cell fate, for inflammatory responses and for generating a diverse repertoire of antigen receptor specificities. Here, we review recent findings connecting 3D genome organization to the control of immune cell differentiation and function, and discuss how alterations in genome folding may lead to immune dysfunction and malignancy.
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Affiliation(s)
- Sergi Cuartero
- Josep Carreras Leukaemia Research Institute (IJC), Badalona, Spain. .,Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain.
| | - Grégoire Stik
- Centre for Genomic Regulation (CRG), Institute of Science and Technology (BIST), Barcelona, Spain. .,Universitat Pompeu Fabra (UPF), Barcelona, Spain.
| | - Ralph Stadhouders
- Department of Pulmonary Medicine, Erasmus MC, University Medical Center, Rotterdam, The Netherlands. .,Department of Cell Biology, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
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18
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Sun Y, Dotson GA, Muir LA, Ronquist S, Oravecz-Wilson K, Peltier D, Seike K, Li L, Meixner W, Rajapakse I, Reddy P. Rearrangement of T Cell genome architecture regulates GVHD. iScience 2022; 25:104846. [PMID: 36043052 PMCID: PMC9420521 DOI: 10.1016/j.isci.2022.104846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 05/10/2022] [Accepted: 07/22/2022] [Indexed: 11/19/2022] Open
Abstract
WAPL, cohesin's DNA release factor, regulates three-dimensional (3D) chromatin architecture. The 3D chromatin structure and its relevance to mature T cell functions is not well understood. We show that in vivo lymphopenic expansion, and alloantigen-driven proliferation, alters the 3D structure and function of the genome in mature T cells. Conditional deletion of WAPL, cohesin's DNA release factor, in T cells reduced long-range genomic interactions and altered chromatin A/B compartments and interactions within topologically associating domains (TADs) of the chromatin in T cells at baseline. WAPL deficiency in T cells reduced loop extensions, changed expression of cell cycling genes and reduced proliferation following in vitro and in vivo stimulation, and reduced severity of graft-versus-host disease (GVHD) following experimental allogeneic hematopoietic stem cell transplantation. These data collectively characterize 3D genomic architecture of T cells in vivo and demonstrate biological and clinical implications for its disruption by cohesin release factor WAPL.
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Affiliation(s)
- Yaping Sun
- 1Department of Internal Medicine, Division of Hematology and Oncology, University of Michigan Rogel Cancer Center, Ann Arbor, MI, USA
| | - Gabrielle A. Dotson
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lindsey A. Muir
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Scott Ronquist
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Katherine Oravecz-Wilson
- 1Department of Internal Medicine, Division of Hematology and Oncology, University of Michigan Rogel Cancer Center, Ann Arbor, MI, USA
| | - Daniel Peltier
- 1Department of Internal Medicine, Division of Hematology and Oncology, University of Michigan Rogel Cancer Center, Ann Arbor, MI, USA
| | - Keisuke Seike
- 1Department of Internal Medicine, Division of Hematology and Oncology, University of Michigan Rogel Cancer Center, Ann Arbor, MI, USA
| | - Lu Li
- 1Department of Internal Medicine, Division of Hematology and Oncology, University of Michigan Rogel Cancer Center, Ann Arbor, MI, USA
| | - Walter Meixner
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Indika Rajapakse
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Mathematics, University of Michigan, Ann Arbor, MI, USA
| | - Pavan Reddy
- 1Department of Internal Medicine, Division of Hematology and Oncology, University of Michigan Rogel Cancer Center, Ann Arbor, MI, USA
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19
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Sandholm N, Rubio García A, Pekalski ML, Inshaw JRJ, Cutler AJ, Todd JA. Thymocyte regulatory variant alters transcription factor binding and protects from type 1 diabetes in infants. Sci Rep 2022; 12:14137. [PMID: 35986039 PMCID: PMC9391468 DOI: 10.1038/s41598-022-18296-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Accepted: 08/09/2022] [Indexed: 11/09/2022] Open
Abstract
We recently mapped a genetic susceptibility locus on chromosome 6q22.33 for type 1 diabetes (T1D) diagnosed below the age of 7 years between the PTPRK and thymocyte-selection-associated (THEMIS) genes. As the thymus plays a central role in shaping the T cell repertoire, we aimed to identify the most likely causal genetic factors behind this association using thymocyte genomic data. In four thymocyte populations, we identified 253 DNA sequence motifs underlying histone modifications. The G insertion allele of rs138300818, associated with protection from diabetes, created thymocyte motifs for multiple histone modifications and thymocyte types. In a parallel approach to identifying variants that alter transcription factor binding motifs, the same variant disrupted a predicted motif for Rfx7, which is abundantly expressed in the thymus. Chromatin state and RNA sequencing data suggested strong transcription overlapping rs138300818 in fetal thymus, while expression quantitative trait locus and chromatin conformation data associate the insertion with lower THEMIS expression. Extending the analysis to other T1D loci further highlighted rs66733041 affecting the GATA3 transcription factor binding in the AFF3 locus. Taken together, our results support a role for thymic THEMIS gene expression and the rs138300818 variant in promoting the development of early-onset T1D.
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Affiliation(s)
- Niina Sandholm
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK.
- Folkhälsan Research Center, Helsinki, Finland.
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
| | - Arcadio Rubio García
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Marcin L Pekalski
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Jamie R J Inshaw
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Antony J Cutler
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - John A Todd
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
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20
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Tuong ZK, Stewart BJ, Guo SA, Clatworthy MR. Epigenetics and tissue immunity-Translating environmental cues into functional adaptations. Immunol Rev 2021; 305:111-136. [PMID: 34821397 DOI: 10.1111/imr.13036] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 10/26/2021] [Accepted: 10/28/2021] [Indexed: 12/21/2022]
Abstract
There is an increasing appreciation that many innate and adaptive immune cell subsets permanently reside within non-lymphoid organs, playing a critical role in tissue homeostasis and defense. The best characterized are macrophages and tissue-resident T lymphocytes that work in concert with organ structural cells to generate appropriate immune responses and are functionally shaped by organ-specific environmental cues. The interaction of tissue epithelial, endothelial and stromal cells is also required to attract, differentiate, polarize and maintain organ immune cells in their tissue niche. All of these processes require dynamic regulation of cellular transcriptional programmes, with epigenetic mechanisms playing a critical role, including DNA methylation and post-translational histone modifications. A failure to appropriately regulate immune cell transcription inevitably results in inadequate or inappropriate immune responses and organ pathology. Here, with a focus on the mammalian kidney, an organ which generates differing regional environmental cues (including hypersalinity and hypoxia) due to its physiological functions, we will review the basic concepts of tissue immunity, discuss the technologies available to profile epigenetic modifications in tissue immune cells, including those that enable single-cell profiling, and consider how these mechanisms influence the development, phenotype, activation and function of different tissue immune cell subsets, as well as the immunological function of structural cells.
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Affiliation(s)
- Zewen Kelvin Tuong
- Molecular Immunity Unit, Department of Medicine, MRC-Laboratory of Molecular Biology, University of Cambridge, Cambridge, UK.,Cellular Genetics, Wellcome Sanger Institute, Hinxton, UK
| | - Benjamin J Stewart
- Molecular Immunity Unit, Department of Medicine, MRC-Laboratory of Molecular Biology, University of Cambridge, Cambridge, UK.,Cellular Genetics, Wellcome Sanger Institute, Hinxton, UK
| | - Shuang Andrew Guo
- Molecular Immunity Unit, Department of Medicine, MRC-Laboratory of Molecular Biology, University of Cambridge, Cambridge, UK.,Cellular Genetics, Wellcome Sanger Institute, Hinxton, UK
| | - Menna R Clatworthy
- Molecular Immunity Unit, Department of Medicine, MRC-Laboratory of Molecular Biology, University of Cambridge, Cambridge, UK.,Cellular Genetics, Wellcome Sanger Institute, Hinxton, UK.,Cambridge Institute of Therapeutic Immunology and Infectious Diseases, University of Cambridge, Cambridge, UK
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21
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Thiecke MJ, Yang EJ, Burren OS, Ray-Jones H, Spivakov M. Prioritisation of Candidate Genes Underpinning COVID-19 Host Genetic Traits Based on High-Resolution 3D Chromosomal Topology. Front Genet 2021; 12:745672. [PMID: 34759959 PMCID: PMC8573080 DOI: 10.3389/fgene.2021.745672] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 09/30/2021] [Indexed: 11/30/2022] Open
Abstract
Genetic variants showing associations with specific biological traits and diseases detected by genome-wide association studies (GWAS) commonly map to non-coding DNA regulatory regions. Many of these regions are located considerable distances away from the genes they regulate and come into their proximity through 3D chromosomal interactions. We previously developed COGS, a statistical pipeline for linking GWAS variants with their putative target genes based on 3D chromosomal interaction data arising from high-resolution assays such as Promoter Capture Hi-C (PCHi-C). Here, we applied COGS to COVID-19 Host Genetic Consortium (HGI) GWAS meta-analysis data on COVID-19 susceptibility and severity using our previously generated PCHi-C results in 17 human primary cell types and SARS-CoV-2-infected lung carcinoma cells. We prioritise 251 genes putatively associated with these traits, including 16 out of 47 genes highlighted by the GWAS meta-analysis authors. The prioritised genes are expressed in a broad array of tissues, including, but not limited to, blood and brain cells, and are enriched for genes involved in the inflammatory response to viral infection. Our prioritised genes and pathways, in conjunction with results from other prioritisation approaches and targeted validation experiments, will aid in the understanding of COVID-19 pathology, paving the way for novel treatments.
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Affiliation(s)
| | - Emma J Yang
- Functional Gene Control Group, MRC London Institute of Medical Sciences, London, United Kingdom.,Institute of Clinical Sciences, Faculty of Medicine, Imperial College, London, United Kingdom
| | - Oliver S Burren
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Department of Medicine, University of Cambridge, Cambridge, United Kingdom
| | - Helen Ray-Jones
- Functional Gene Control Group, MRC London Institute of Medical Sciences, London, United Kingdom.,Institute of Clinical Sciences, Faculty of Medicine, Imperial College, London, United Kingdom
| | - Mikhail Spivakov
- Functional Gene Control Group, MRC London Institute of Medical Sciences, London, United Kingdom.,Institute of Clinical Sciences, Faculty of Medicine, Imperial College, London, United Kingdom
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22
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Ray-Jones H, Spivakov M. Transcriptional enhancers and their communication with gene promoters. Cell Mol Life Sci 2021; 78:6453-6485. [PMID: 34414474 PMCID: PMC8558291 DOI: 10.1007/s00018-021-03903-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 07/08/2021] [Accepted: 07/19/2021] [Indexed: 12/13/2022]
Abstract
Transcriptional enhancers play a key role in the initiation and maintenance of gene expression programmes, particularly in metazoa. How these elements control their target genes in the right place and time is one of the most pertinent questions in functional genomics, with wide implications for most areas of biology. Here, we synthesise classic and recent evidence on the regulatory logic of enhancers, including the principles of enhancer organisation, factors that facilitate and delimit enhancer-promoter communication, and the joint effects of multiple enhancers. We show how modern approaches building on classic insights have begun to unravel the complexity of enhancer-promoter relationships, paving the way towards a quantitative understanding of gene control.
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Affiliation(s)
- Helen Ray-Jones
- MRC London Institute of Medical Sciences, London, W12 0NN, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College, London, W12 0NN, UK
| | - Mikhail Spivakov
- MRC London Institute of Medical Sciences, London, W12 0NN, UK.
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College, London, W12 0NN, UK.
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23
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Freire-Pritchett P, Ray-Jones H, Della Rosa M, Eijsbouts CQ, Orchard WR, Wingett SW, Wallace C, Cairns J, Spivakov M, Malysheva V. Detecting chromosomal interactions in Capture Hi-C data with CHiCAGO and companion tools. Nat Protoc 2021; 16:4144-4176. [PMID: 34373652 PMCID: PMC7612634 DOI: 10.1038/s41596-021-00567-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 04/28/2021] [Indexed: 11/10/2022]
Abstract
Capture Hi-C is widely used to obtain high-resolution profiles of chromosomal interactions involving, at least on one end, regions of interest such as gene promoters. Signal detection in Capture Hi-C data is challenging and cannot be adequately accomplished with tools developed for other chromosome conformation capture methods, including standard Hi-C. Capture Hi-C Analysis of Genomic Organization (CHiCAGO) is a computational pipeline developed specifically for Capture Hi-C analysis. It implements a statistical model accounting for biological and technical background components, as well as bespoke normalization and multiple testing procedures for this data type. Here we provide a step-by-step guide to the CHiCAGO workflow that is aimed at users with basic experience of the command line and R. We also describe more advanced strategies for tuning the key parameters for custom experiments and provide guidance on data preprocessing and downstream analysis using companion tools. In a typical experiment, CHiCAGO takes ~2-3 h to run, although pre- and postprocessing steps may take much longer.
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Affiliation(s)
| | - Helen Ray-Jones
- Functional Gene Control Group, Epigenetics Section, MRC London Institute of Medical Sciences, London, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Monica Della Rosa
- Functional Gene Control Group, Epigenetics Section, MRC London Institute of Medical Sciences, London, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK
| | - Chris Q Eijsbouts
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Steven W Wingett
- Bioinformatics, The Babraham Institute, Cambridge, UK
- Cell Biology Division, MRC Laboratory of Molecular Biology, Cambridge, UK
| | - Chris Wallace
- Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, University of Cambridge, Cambridge, UK
- MRC Biostatistics Unit, Cambridge Biomedical Campus, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge, UK
| | | | - Mikhail Spivakov
- Functional Gene Control Group, Epigenetics Section, MRC London Institute of Medical Sciences, London, UK.
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK.
| | - Valeriya Malysheva
- Functional Gene Control Group, Epigenetics Section, MRC London Institute of Medical Sciences, London, UK.
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, UK.
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24
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Chromatin Modifications in 22q11.2 Deletion Syndrome. J Clin Immunol 2021; 41:1853-1864. [PMID: 34435264 DOI: 10.1007/s10875-021-01123-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 08/11/2021] [Indexed: 12/31/2022]
Abstract
PURPOSE Chromosome 22q11.2 deletion syndrome is a common inborn error of immunity. The early consequences of thymic hypoplasia are low T cell numbers. Later in life, atopy, autoimmunity, inflammation, and evolving hypogammaglobulinemia can occur and the causes of these features are not understood. This study utilized an unbiased discovery approach to define alterations in histone modifications. Our goal was to identify durable chromatin changes that could influence cell behavior. METHODS CD4 T cells and CD19 B cells underwent ChIP-seq analysis using antibodies to H3K4me3, H3K27ac, and H4ac. RNA effects were defined in CD4 T cells by RNA-seq. Serum cytokines were examined by Luminex. RESULTS Histone marks of transcriptional activation at CD4 T cell promoters and enhancers were globally increased. The promoter activation signature had elements related to T cell activation and inflammation, concordant with effects seen in the transcriptome. B cells, in contrast, had a minimally altered epigenetic landscape in 22q11.2. Both cell types had an "edge" effect with markedly altered chromatin adjacent to the deletion. CONCLUSIONS People with 22q11.2 deletion have altered CD4 T cell chromatin and a transcriptome concordant with the changes in the epigenome. These effects support a disease model where qualitative changes to T cells occur in addition to quantitative defects that have been well characterized. This study offers unique insight into qualitative differences in the T cells in 22q11.2 deletion, an aspect that has received limited attention.
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25
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Tsai JC, Saad OA, Magesh S, Xu J, Lee AC, Li WT, Chakladar J, Fuster MM, Chang EY, Wang-Rodriguez J, Ongkeko WM. Tobacco Smoke and Electronic Cigarette Vapor Alter Enhancer RNA Expression That Can Regulate the Pathogenesis of Lung Squamous Cell Carcinoma. Cancers (Basel) 2021; 13:cancers13164225. [PMID: 34439379 PMCID: PMC8391195 DOI: 10.3390/cancers13164225] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 08/20/2021] [Accepted: 08/20/2021] [Indexed: 12/29/2022] Open
Abstract
Simple Summary It is well established that tobacco smoke is the key player in lung squamous cell carcinoma (LUSC) pathogenesis, and there is growing evidence that electronic cigarette (e-cigarette) vapor may also cause LUSC. Recently, several studies have associated tobacco smoke with differential enhancer RNA (eRNA) expression. However, the effects of tobacco smoke and e-cigarette vapor on eRNA expression in correlation to LUSC outcomes have not been fully elucidated. This study demonstrates that tobacco smoke and e-cigarette vapor may decrease DNA methylation and increase chromosomal alterations at key sites, which ultimately upregulate the expression of oncogenic eRNAs and downregulate the expression of tumor-suppressing eRNAs. Subsequently, we demonstrate that these eRNAs may have altered interactions with immune cells to promote LUSC pathogenesis and reduced patient survival. We hope our results can be validated in future studies, and the key eRNAs we identified may be used as effective targets for more specialized treatments for smoking-mediated LUSC. Abstract Tobacco is the primary etiologic agent in worsened lung squamous cell carcinoma (LUSC) outcomes. Meanwhile, it has been shown that etiologic agents alter enhancer RNAs (eRNAs) expression. Therefore, we aimed to identify the effects of tobacco and electronic cigarette (e-cigarette) use on eRNA expression in relation to LUSC outcomes. We extracted eRNA counts from RNA-sequencing data of tumor/adjacent normal tissue and before/after e-cigarette tissue from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO), respectively. Tobacco-mediated LUSC eRNAs were correlated to patient survival, clinical variables, and immune-associated elements. eRNA expression was also correlated to mutation rates through the Repeated Evaluation of Variables Conditional Entropy and Redundance (REVEALER) algorithm and methylated sites through methylationArrayAnalysis. Differential expression analysis was then completed for the e-cigarette data to compare with key tobacco-mediated eRNAs. We identified 684 downregulated eRNAs and 819 upregulated eRNAs associated with tobacco-mediated LUSC, specifically, with the cancer pathological stage. We also observed a decrease in immune cell abundance in tobacco-mediated LUSC. Yet, we found an increased association of eRNA expression with immune cell abundance in tobacco-mediated LUSC. We identified 16 key eRNAs with significant correlations to 8 clinical variables, implicating these eRNAs in LUSC malignancy. Furthermore, we observed that these 16 eRNAs were highly associated with chromosomal alterations and reduced CpG site methylation. Finally, we observed large eRNA expression upregulation with e-cigarette use, which corresponded to the upregulation of the 16 key eRNAs. Our findings provide a novel mechanism by which tobacco and e-cigarette smoke influences eRNA interactions to promote LUSC pathogenesis and provide insight regarding disease progression at a molecular level.
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Affiliation(s)
- Joseph C. Tsai
- Department of Surgery, Division of Otolaryngology—Head and Neck Surgery, UC San Diego School of Medicine, San Diego, CA 92093, USA; (J.C.T.); (O.A.S.); (S.M.); (J.X.); (A.C.L.); (W.T.L.); (J.C.)
- Research Service, VA San Diego Healthcare System, San Diego, CA 92161, USA
| | - Omar A. Saad
- Department of Surgery, Division of Otolaryngology—Head and Neck Surgery, UC San Diego School of Medicine, San Diego, CA 92093, USA; (J.C.T.); (O.A.S.); (S.M.); (J.X.); (A.C.L.); (W.T.L.); (J.C.)
- Research Service, VA San Diego Healthcare System, San Diego, CA 92161, USA
| | - Shruti Magesh
- Department of Surgery, Division of Otolaryngology—Head and Neck Surgery, UC San Diego School of Medicine, San Diego, CA 92093, USA; (J.C.T.); (O.A.S.); (S.M.); (J.X.); (A.C.L.); (W.T.L.); (J.C.)
- Research Service, VA San Diego Healthcare System, San Diego, CA 92161, USA
| | - Jingyue Xu
- Department of Surgery, Division of Otolaryngology—Head and Neck Surgery, UC San Diego School of Medicine, San Diego, CA 92093, USA; (J.C.T.); (O.A.S.); (S.M.); (J.X.); (A.C.L.); (W.T.L.); (J.C.)
- Research Service, VA San Diego Healthcare System, San Diego, CA 92161, USA
| | - Abby C. Lee
- Department of Surgery, Division of Otolaryngology—Head and Neck Surgery, UC San Diego School of Medicine, San Diego, CA 92093, USA; (J.C.T.); (O.A.S.); (S.M.); (J.X.); (A.C.L.); (W.T.L.); (J.C.)
- Research Service, VA San Diego Healthcare System, San Diego, CA 92161, USA
| | - Wei Tse Li
- Department of Surgery, Division of Otolaryngology—Head and Neck Surgery, UC San Diego School of Medicine, San Diego, CA 92093, USA; (J.C.T.); (O.A.S.); (S.M.); (J.X.); (A.C.L.); (W.T.L.); (J.C.)
- Research Service, VA San Diego Healthcare System, San Diego, CA 92161, USA
| | - Jaideep Chakladar
- Department of Surgery, Division of Otolaryngology—Head and Neck Surgery, UC San Diego School of Medicine, San Diego, CA 92093, USA; (J.C.T.); (O.A.S.); (S.M.); (J.X.); (A.C.L.); (W.T.L.); (J.C.)
- Research Service, VA San Diego Healthcare System, San Diego, CA 92161, USA
| | - Mark M. Fuster
- VA San Diego Healthcare System, Medical and Research Sections, La Jolla, San Diego, CA 92161, USA;
- Department of Medicine, Division of Pulmonary and Critical Care, University of California, La Jolla, San Diego, CA 92037, USA
| | - Eric Y. Chang
- Department of Radiology, University of California, San Diego, CA 92093, USA;
- Radiology Service, VA San Diego Healthcare System, San Diego, CA 92161, USA
| | - Jessica Wang-Rodriguez
- Department of Pathology, UC San Diego School of Medicine, San Diego, CA 92093, USA;
- Pathology Service, VA San Diego Healthcare System, San Diego, CA 92161, USA
| | - Weg M. Ongkeko
- Department of Surgery, Division of Otolaryngology—Head and Neck Surgery, UC San Diego School of Medicine, San Diego, CA 92093, USA; (J.C.T.); (O.A.S.); (S.M.); (J.X.); (A.C.L.); (W.T.L.); (J.C.)
- Research Service, VA San Diego Healthcare System, San Diego, CA 92161, USA
- Correspondence: ; Tel.: +1-(858)-552-8585-X-7165
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26
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Shi C, Ray-Jones H, Ding J, Duffus K, Fu Y, Gaddi VP, Gough O, Hankinson J, Martin P, McGovern A, Yarwood A, Gaffney P, Eyre S, Rattray M, Warren RB, Orozco G. Chromatin Looping Links Target Genes with Genetic Risk Loci for Dermatological Traits. J Invest Dermatol 2021; 141:1975-1984. [PMID: 33607115 PMCID: PMC8315765 DOI: 10.1016/j.jid.2021.01.015] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2020] [Revised: 01/12/2021] [Accepted: 01/21/2021] [Indexed: 02/08/2023]
Abstract
Chromatin looping between regulatory elements and gene promoters presents a potential mechanism whereby disease risk variants affect their target genes. In this study, we use H3K27ac HiChIP, a method for assaying the active chromatin interactome in two cell lines: keratinocytes and skin lymphoma-derived CD8+ T cells. We integrate public datasets for a lymphoblastoid cell line and primary CD4+ T cells and identify gene targets at risk loci for skin-related disorders. Interacting genes enrich for pathways of known importance in each trait, such as cytokine response (psoriatic arthritis and psoriasis) and replicative senescence (melanoma). We show examples of how our analysis can inform changes in the current understanding of multiple psoriasis-associated risk loci. For example, the variant rs10794648, which is generally assigned to IFNLR1, was linked to GRHL3, a gene essential in skin repair and development, in our dataset. Our findings, therefore, indicate a renewed importance of skin-related factors in the risk of disease.
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Affiliation(s)
- Chenfu Shi
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom.
| | - Helen Ray-Jones
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom; Dermatology Centre, Salford Royal NHS Foundation Trust, NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - James Ding
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Kate Duffus
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Yao Fu
- Genes & Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
| | - Vasanthi Priyadarshini Gaddi
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Oliver Gough
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Jenny Hankinson
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, University of Manchester, Manchester, United Kingdom
| | - Paul Martin
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom; Lydia Becker Institute of Immunology and Inflammation, The University of Manchester, Manchester, United Kingdom
| | - Amanda McGovern
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom
| | - Annie Yarwood
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom; Dermatology Centre, Salford Royal NHS Foundation Trust, NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Patrick Gaffney
- Genes & Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma, USA
| | - Steve Eyre
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom; NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Magnus Rattray
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, United Kingdom
| | - Richard B Warren
- Dermatology Centre, Salford Royal NHS Foundation Trust, NIHR Manchester Biomedical Research Centre, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Gisela Orozco
- Centre for Genetics and Genomics Versus Arthritis, Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, United Kingdom; NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
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27
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van Schoonhoven A, Huylebroeck D, Hendriks RW, Stadhouders R. 3D genome organization during lymphocyte development and activation. Brief Funct Genomics 2021; 19:71-82. [PMID: 31819944 PMCID: PMC7115705 DOI: 10.1093/bfgp/elz030] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Revised: 07/24/2019] [Accepted: 09/20/2019] [Indexed: 12/20/2022] Open
Abstract
Chromosomes have a complex three-dimensional (3D) architecture comprising A/B compartments, topologically associating domains and promoter-enhancer interactions. At all these levels, the 3D genome has functional consequences for gene transcription and therefore for cellular identity. The development and activation of lymphocytes involves strict control of gene expression by transcription factors (TFs) operating in a three-dimensionally organized chromatin landscape. As lymphocytes are indispensable for tissue homeostasis and pathogen defense, and aberrant lymphocyte activity is involved in a wide range of human morbidities, acquiring an in-depth understanding of the molecular mechanisms that control lymphocyte identity is highly relevant. Here we review current knowledge of the interplay between 3D genome organization and transcriptional control during B and T lymphocyte development and antigen-dependent activation, placing special emphasis on the role of TFs.
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Affiliation(s)
- Anne van Schoonhoven
- Department of Pulmonary Medicine, Erasmus MC, Rotterdam, the Netherlands.,Department of Cell Biology,Erasmus MC, Rotterdam, the Netherlands
| | | | - Rudi W Hendriks
- Department of Pulmonary Medicine, Erasmus MC, Rotterdam, the Netherlands
| | - Ralph Stadhouders
- Department of Pulmonary Medicine, Erasmus MC, Rotterdam, the Netherlands.,Department of Cell Biology,Erasmus MC, Rotterdam, the Netherlands
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28
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Robertson CC, Inshaw JRJ, Onengut-Gumuscu S, Chen WM, Santa Cruz DF, Yang H, Cutler AJ, Crouch DJM, Farber E, Bridges SL, Edberg JC, Kimberly RP, Buckner JH, Deloukas P, Divers J, Dabelea D, Lawrence JM, Marcovina S, Shah AS, Greenbaum CJ, Atkinson MA, Gregersen PK, Oksenberg JR, Pociot F, Rewers MJ, Steck AK, Dunger DB, Wicker LS, Concannon P, Todd JA, Rich SS. Fine-mapping, trans-ancestral and genomic analyses identify causal variants, cells, genes and drug targets for type 1 diabetes. Nat Genet 2021; 53:962-971. [PMID: 34127860 PMCID: PMC8273124 DOI: 10.1038/s41588-021-00880-5] [Citation(s) in RCA: 140] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Accepted: 05/05/2021] [Indexed: 12/13/2022]
Abstract
We report the largest and most diverse genetic study of type 1 diabetes (T1D) to date (61,427 participants), yielding 78 genome-wide-significant (P < 5 × 10-8) regions, including 36 that are new. We define credible sets of T1D-associated variants and show that they are enriched in immune-cell accessible chromatin, particularly CD4+ effector T cells. Using chromatin-accessibility profiling of CD4+ T cells from 115 individuals, we map chromatin-accessibility quantitative trait loci and identify five regions where T1D risk variants co-localize with chromatin-accessibility quantitative trait loci. We highlight rs72928038 in BACH2 as a candidate causal T1D variant leading to decreased enhancer accessibility and BACH2 expression in T cells. Finally, we prioritize potential drug targets by integrating genetic evidence, functional genomic maps and immune protein-protein interactions, identifying 12 genes implicated in T1D that have been targeted in clinical trials for autoimmune diseases. These findings provide an expanded genomic landscape for T1D.
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Affiliation(s)
- Catherine C Robertson
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
| | - Jamie R J Inshaw
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Wei-Min Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - David Flores Santa Cruz
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Hanzhi Yang
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Antony J Cutler
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Daniel J M Crouch
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Emily Farber
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - S Louis Bridges
- Division of Rheumatology, Department of Medicine, Hospital for Special Surgery, New York, NY, USA
- Division of Rheumatology, Department of Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Jeffrey C Edberg
- Division of Clinical Immunology and Rheumatology, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Robert P Kimberly
- Division of Clinical Immunology and Rheumatology, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jane H Buckner
- Center for Translational Immunology, Benaroya Research Institute, Seattle, WA, USA
| | - Panos Deloukas
- Clinical Pharmacology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, Saudi Arabia
| | - Jasmin Divers
- Division of Health Services Research, Department of Foundations of Medicine, New York University Long Island School of Medicine, Mineola, NY, USA
| | - Dana Dabelea
- Colorado School of Public Health and Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Jean M Lawrence
- Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena, CA, USA
| | - Santica Marcovina
- Northwest Lipid Metabolism and Diabetes Research Laboratories, University of Washington, Seattle, WA, USA
- Medpace Reference Laboratories, Cincinnati, OH, USA
| | - Amy S Shah
- Cincinnati Children's Hospital Medical Center and the University of Cincinnati, Cincinnati, OH, USA
| | - Carla J Greenbaum
- Center for Interventional Immunology, Benaroya Research Institute, Seattle, WA, USA
- Diabetes Program, Benaroya Research Institute, Seattle, WA, USA
| | - Mark A Atkinson
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL, USA
| | - Peter K Gregersen
- Robert S. Boas Center for Genomics and Human Genetics, Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Jorge R Oksenberg
- Department of Neurology and Weill Institute for Neurosciences, University of California at San Francisco, San Francisco, CA, USA
| | - Flemming Pociot
- Department of Pediatrics, Herlev University Hospital, Copenhagen, Denmark
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Type 1 Diabetes Biology, Department of Clinical Research, Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Marian J Rewers
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Andrea K Steck
- Barbara Davis Center for Diabetes, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - David B Dunger
- Department of Paediatrics, University of Cambridge, Cambridge, UK
- Wellcome Trust Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Linda S Wicker
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Patrick Concannon
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL, USA
- Genetics Institute, University of Florida, Gainesville, FL, USA
| | - John A Todd
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK.
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
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29
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Chu X, Zhang B, Koeken VACM, Gupta MK, Li Y. Multi-Omics Approaches in Immunological Research. Front Immunol 2021; 12:668045. [PMID: 34177908 PMCID: PMC8226116 DOI: 10.3389/fimmu.2021.668045] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2021] [Accepted: 05/28/2021] [Indexed: 12/14/2022] Open
Abstract
The immune system plays a vital role in health and disease, and is regulated through a complex interactive network of many different immune cells and mediators. To understand the complexity of the immune system, we propose to apply a multi-omics approach in immunological research. This review provides a complete overview of available methodological approaches for the different omics data layers relevant for immunological research, including genetics, epigenetics, transcriptomics, proteomics, metabolomics, and cellomics. Thereafter, we describe the various methods for data analysis as well as how to integrate different layers of omics data. Finally, we discuss the possible applications of multi-omics studies and opportunities they provide for understanding the complex regulatory networks as well as immune variation in various immune-related diseases.
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Affiliation(s)
- Xiaojing Chu
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Bowen Zhang
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Valerie A. C. M. Koeken
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, Netherlands
| | - Manoj Kumar Gupta
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Yang Li
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
- Department of Computational Biology for Individualised Medicine, Centre for Individualised Infection Medicine (CiiM), a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, Netherlands
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30
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Scourzic L, Salataj E, Apostolou E. Deciphering the Complexity of 3D Chromatin Organization Driving Lymphopoiesis and Lymphoid Malignancies. Front Immunol 2021; 12:669881. [PMID: 34054841 PMCID: PMC8160312 DOI: 10.3389/fimmu.2021.669881] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Accepted: 04/26/2021] [Indexed: 12/18/2022] Open
Abstract
Proper lymphopoiesis and immune responses depend on the spatiotemporal control of multiple processes, including gene expression, DNA recombination and cell fate decisions. High-order 3D chromatin organization is increasingly appreciated as an important regulator of these processes and dysregulation of genomic architecture has been linked to various immune disorders, including lymphoid malignancies. In this review, we present the general principles of the 3D chromatin topology and its dynamic reorganization during various steps of B and T lymphocyte development and activation. We also discuss functional interconnections between architectural, epigenetic and transcriptional changes and introduce major key players of genomic organization in B/T lymphocytes. Finally, we present how alterations in architectural factors and/or 3D genome organization are linked to dysregulation of the lymphopoietic transcriptional program and ultimately to hematological malignancies.
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Affiliation(s)
| | | | - Effie Apostolou
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
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31
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Bakker OB, Ramírez-Sánchez AD, Borek ZA, de Klein N, Li Y, Modderman R, Kooy-Winkelaar Y, Johannesen MK, Matarese F, Martens JHA, Kumar V, van Bergen J, Qiao SW, Lundin KEA, Sollid LM, Koning F, Wijmenga C, Withoff S, Jonkers IH. Potential impact of celiac disease genetic risk factors on T cell receptor signaling in gluten-specific CD4+ T cells. Sci Rep 2021; 11:9252. [PMID: 33927210 PMCID: PMC8085175 DOI: 10.1038/s41598-021-86612-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2020] [Accepted: 03/18/2021] [Indexed: 02/08/2023] Open
Abstract
Celiac disease is an auto-immune disease in which an immune response to dietary gluten leads to inflammation and subsequent atrophy of small intestinal villi, causing severe bowel discomfort and malabsorption of nutrients. The major instigating factor for the immune response in celiac disease is the activation of gluten-specific CD4+ T cells expressing T cell receptors that recognize gluten peptides presented in the context of HLA-DQ2 and DQ8. Here we provide an in-depth characterization of 28 gluten-specific T cell clones. We assess their transcriptional and epigenetic response to T cell receptor stimulation and link this to genetic factors associated with celiac disease. Gluten-specific T cells have a distinct transcriptional profile that mostly resembles that of Th1 cells but also express cytokines characteristic of other types of T-helper cells. This transcriptional response appears not to be regulated by changes in chromatin state, but rather by early upregulation of transcription factors and non-coding RNAs that likely orchestrate the subsequent activation of genes that play a role in immune pathways. Finally, integration of chromatin and transcription factor binding profiles suggest that genes activated by T cell receptor stimulation of gluten‑specific T cells may be impacted by genetic variation at several genetic loci associated with celiac disease.
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Affiliation(s)
- Olivier B Bakker
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Aarón D Ramírez-Sánchez
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Zuzanna A Borek
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Niek de Klein
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Yang Li
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Rutger Modderman
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Yvonne Kooy-Winkelaar
- Department of Immunohematology and Blood Transfusion, Leiden University Medical Center, Leiden, The Netherlands
| | - Marie K Johannesen
- K.G. Jebsen Coeliac Disease Research Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Immunology, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Filomena Matarese
- Department of Molecular Biology, Nijmegen Centre for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands
| | - Joost H A Martens
- Department of Molecular Biology, Nijmegen Centre for Molecular Life Sciences, Radboud University, Nijmegen, The Netherlands
| | - Vinod Kumar
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
- Nitte (Deemed to be University), Division of Infectious Diseases, Nitte University Centre for Science Education and Research (NUCSER), Paneer Campus, Deralakatte, Mangaluru, 575018, India
| | - Jeroen van Bergen
- Department of Immunohematology and Blood Transfusion, Leiden University Medical Center, Leiden, The Netherlands
| | - Shuo-Wang Qiao
- K.G. Jebsen Coeliac Disease Research Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Immunology, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Knut E A Lundin
- K.G. Jebsen Coeliac Disease Research Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Gastroenterology, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Ludvig M Sollid
- K.G. Jebsen Coeliac Disease Research Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Immunology, Oslo University Hospital, Rikshospitalet, Oslo, Norway
| | - Frits Koning
- Department of Immunohematology and Blood Transfusion, Leiden University Medical Center, Leiden, The Netherlands
| | - Cisca Wijmenga
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- K.G. Jebsen Coeliac Disease Research Centre, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Sebo Withoff
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Iris H Jonkers
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.
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32
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Shi C, Rattray M, Barton A, Bowes J, Orozco G. Using functional genomics to advance the understanding of psoriatic arthritis. Rheumatology (Oxford) 2021; 59:3137-3146. [PMID: 32778885 PMCID: PMC7590405 DOI: 10.1093/rheumatology/keaa283] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Revised: 04/17/2020] [Accepted: 04/28/2020] [Indexed: 01/03/2023] Open
Abstract
Psoriatic arthritis (PsA) is a complex disease where susceptibility is determined by genetic and environmental risk factors. Clinically, PsA involves inflammation of the joints and the skin, and, if left untreated, results in irreversible joint damage. There is currently no cure and the few treatments available to alleviate symptoms do not work in all patients. Over the past decade, genome-wide association studies (GWAS) have uncovered a large number of disease-associated loci but translating these findings into functional mechanisms and novel targets for therapeutic use is not straightforward. Most variants have been predicted to affect primarily long-range regulatory regions such as enhancers. There is now compelling evidence to support the use of chromatin conformation analysis methods to discover novel genes that can be affected by disease-associated variants. Here, we will review the studies published in the field that have given us a novel understanding of gene regulation in the context of functional genomics and how this relates to the study of PsA and its underlying disease mechanism.
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Affiliation(s)
- Chenfu Shi
- Division of Musculoskeletal and Dermatological Sciences, Faculty of Biology, Medicine and Health, Centre for Genetics and Genomics Versus Arthritis
| | - Magnus Rattray
- Division of Informatics, Imaging and Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester.,NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre
| | - Anne Barton
- Division of Musculoskeletal and Dermatological Sciences, Faculty of Biology, Medicine and Health, Centre for Genetics and Genomics Versus Arthritis.,NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre.,Lydia Becker Institute of Immunology and Inflammation, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - John Bowes
- Division of Musculoskeletal and Dermatological Sciences, Faculty of Biology, Medicine and Health, Centre for Genetics and Genomics Versus Arthritis.,NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre
| | - Gisela Orozco
- Division of Musculoskeletal and Dermatological Sciences, Faculty of Biology, Medicine and Health, Centre for Genetics and Genomics Versus Arthritis.,NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre.,Lydia Becker Institute of Immunology and Inflammation, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
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33
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Multi-level remodelling of chromatin underlying activation of human T cells. Sci Rep 2021; 11:528. [PMID: 33436846 PMCID: PMC7804404 DOI: 10.1038/s41598-020-80165-9] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2019] [Accepted: 12/15/2020] [Indexed: 02/06/2023] Open
Abstract
Remodelling of chromatin architecture is known to regulate gene expression and has been well characterized in cell lineage development but less so in response to cell perturbation. Activation of T cells, which triggers extensive changes in transcriptional programs, serves as an instructive model to elucidate how changes in chromatin architecture orchestrate gene expression in response to cell perturbation. To characterize coordinate changes at different levels of chromatin architecture, we analyzed chromatin accessibility, chromosome conformation and gene expression in activated human T cells. T cell activation was characterized by widespread changes in chromatin accessibility and interactions that were shared between activated CD4+ and CD8+ T cells, and with the formation of active regulatory regions associated with transcription factors relevant to T cell biology. Chromatin interactions that increased and decreased were coupled, respectively, with up- and down-regulation of corresponding target genes. Furthermore, activation was associated with disruption of long-range chromatin interactions and with partitioning of topologically associating domains (TADs) and remodelling of their TAD boundaries. Newly formed/strengthened TAD boundaries were associated with higher nucleosome occupancy and lower accessibility, linking changes in lower and higher order chromatin architecture. T cell activation exemplifies coordinate multi-level remodelling of chromatin underlying gene transcription.
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34
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González-Serna D, Villanueva-Martin G, Acosta-Herrera M, Márquez A, Martín J. Approaching Shared Pathophysiology in Immune-Mediated Diseases through Functional Genomics. Genes (Basel) 2020; 11:E1482. [PMID: 33317201 PMCID: PMC7762979 DOI: 10.3390/genes11121482] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 12/01/2020] [Accepted: 12/04/2020] [Indexed: 12/14/2022] Open
Abstract
Immune-mediated diseases (IMDs) are complex pathologies that are strongly influenced by environmental and genetic factors. Associations between genetic loci and susceptibility to these diseases have been widely studied, and hundreds of risk variants have emerged during the last two decades, with researchers observing a shared genetic pattern among them. Nevertheless, the pathological mechanism behind these associations remains a challenge that has just started to be understood thanks to functional genomic approaches. Transcriptomics, regulatory elements, chromatin interactome, as well as the experimental characterization of genomic findings, constitute key elements in the emerging understandings of how genetics affects the etiopathogenesis of IMDs. In this review, we will focus on the latest advances in the field of functional genomics, centering our attention on systemic rheumatic IMDs.
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Affiliation(s)
- David González-Serna
- Institute of Parasitology and Biomedicine López-Neyra, Consejo Superior de Investigaciones Científicas (IPBLN-CSIC), 18016 Granada, Spain; (D.G.-S.); (G.V.-M.); (M.A.-H.); (A.M.)
| | - Gonzalo Villanueva-Martin
- Institute of Parasitology and Biomedicine López-Neyra, Consejo Superior de Investigaciones Científicas (IPBLN-CSIC), 18016 Granada, Spain; (D.G.-S.); (G.V.-M.); (M.A.-H.); (A.M.)
| | - Marialbert Acosta-Herrera
- Institute of Parasitology and Biomedicine López-Neyra, Consejo Superior de Investigaciones Científicas (IPBLN-CSIC), 18016 Granada, Spain; (D.G.-S.); (G.V.-M.); (M.A.-H.); (A.M.)
| | - Ana Márquez
- Institute of Parasitology and Biomedicine López-Neyra, Consejo Superior de Investigaciones Científicas (IPBLN-CSIC), 18016 Granada, Spain; (D.G.-S.); (G.V.-M.); (M.A.-H.); (A.M.)
- Systemic Autoimmune Disease Unit, Hospital Clínico San Cecilio, Instituto de Investigación Biosanitaria ibs.GRANADA, 18016 Granada, Spain
| | - Javier Martín
- Institute of Parasitology and Biomedicine López-Neyra, Consejo Superior de Investigaciones Científicas (IPBLN-CSIC), 18016 Granada, Spain; (D.G.-S.); (G.V.-M.); (M.A.-H.); (A.M.)
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35
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Vyse TJ, Cunninghame Graham DS. Trans-Ancestral Fine-Mapping and Epigenetic Annotation as Tools to Delineate Functionally Relevant Risk Alleles at IKZF1 and IKZF3 in Systemic Lupus Erythematosus. Int J Mol Sci 2020; 21:ijms21218383. [PMID: 33182226 PMCID: PMC7664943 DOI: 10.3390/ijms21218383] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 10/09/2020] [Accepted: 10/13/2020] [Indexed: 12/19/2022] Open
Abstract
Background: Prioritizing tag-SNPs carried on extended risk haplotypes at susceptibility loci for common disease is a challenge. Methods: We utilized trans-ancestral exclusion mapping to reduce risk haplotypes at IKZF1 and IKZF3 identified in multiple ancestries from SLE GWAS and ImmunoChip datasets. We characterized functional annotation data across each risk haplotype from publicly available datasets including ENCODE, RoadMap Consortium, PC Hi-C data from 3D genome browser, NESDR NTR conditional eQTL database, GeneCards Genehancers and TF (transcription factor) binding sites from Haploregv4. Results: We refined the 60 kb associated haplotype upstream of IKZF1 to just 12 tag-SNPs tagging a 47.7 kb core risk haplotype. There was preferential enrichment of DNAse I hypersensitivity and H3K27ac modification across the 3′ end of the risk haplotype, with four tag-SNPs sharing allele-specific TF binding sites with promoter variants, which are eQTLs for IKZF1 in whole blood. At IKZF3, we refined a core risk haplotype of 101 kb (27 tag-SNPs) from an initial extended haplotype of 194 kb (282 tag-SNPs), which had widespread DNAse I hypersensitivity, H3K27ac modification and multiple allele-specific TF binding sites. Dimerization of Fox family TFs bound at the 3′ and promoter of IKZF3 may stabilize chromatin looping across the locus. Conclusions: We combined trans-ancestral exclusion mapping and epigenetic annotation to identify variants at both IKZF1 and IKZF3 with the highest likelihood of biological relevance. The approach will be of strong interest to other complex trait geneticists seeking to attribute biological relevance to risk alleles on extended risk haplotypes in their disease of interest.
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36
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Rovirosa L, Ramos-Morales A, Javierre BM. The Genome in a Three-Dimensional Context: Deciphering the Contribution of Noncoding Mutations at Enhancers to Blood Cancer. Front Immunol 2020; 11:592087. [PMID: 33117405 PMCID: PMC7575776 DOI: 10.3389/fimmu.2020.592087] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2020] [Accepted: 09/21/2020] [Indexed: 11/13/2022] Open
Abstract
Associations between blood cancer and genetic predisposition, including both inherited variants and acquired mutations and epimutations, have been well characterized. However, the majority of these variants affect noncoding regions, making their mechanisms difficult to hypothesize and hindering the translation of these insights into patient benefits. Fueled by unprecedented progress in next-generation sequencing and computational integrative analysis, studies have started applying combinations of epigenetic, genome architecture, and functional assays to bridge the gap between noncoding variants and blood cancer. These complementary tools have not only allowed us to understand the potential malignant role of these variants but also to differentiate key variants, cell-types, and conditions from misleading ones. Here, we briefly review recent studies that have provided fundamental insights into our understanding of how noncoding mutations at enhancers predispose and promote blood malignancies in the context of spatial genome architecture.
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Affiliation(s)
- Llorenç Rovirosa
- 3D Chromatin Organization Group, Josep Carreras Leukaemia Research Institute (IJC), Germans Trias i Pujol, Badalona, Spain
| | - Alberto Ramos-Morales
- 3D Chromatin Organization Group, Josep Carreras Leukaemia Research Institute (IJC), Germans Trias i Pujol, Badalona, Spain
| | - Biola M Javierre
- 3D Chromatin Organization Group, Josep Carreras Leukaemia Research Institute (IJC), Germans Trias i Pujol, Badalona, Spain.,Institute for Health Science Research Germans Trias i Pujol (IGTP), Badalona, Spain
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37
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Yang J, McGovern A, Martin P, Duffus K, Ge X, Zarrineh P, Morris AP, Adamson A, Fraser P, Rattray M, Eyre S. Analysis of chromatin organization and gene expression in T cells identifies functional genes for rheumatoid arthritis. Nat Commun 2020; 11:4402. [PMID: 32879318 PMCID: PMC7468106 DOI: 10.1038/s41467-020-18180-7] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 08/06/2020] [Indexed: 12/16/2022] Open
Abstract
Genome-wide association studies have identified genetic variation contributing to complex disease risk. However, assigning causal genes and mechanisms has been more challenging because disease-associated variants are often found in distal regulatory regions with cell-type specific behaviours. Here, we collect ATAC-seq, Hi-C, Capture Hi-C and nuclear RNA-seq data in stimulated CD4+ T cells over 24 h, to identify functional enhancers regulating gene expression. We characterise changes in DNA interaction and activity dynamics that correlate with changes in gene expression, and find that the strongest correlations are observed within 200 kb of promoters. Using rheumatoid arthritis as an example of T cell mediated disease, we demonstrate interactions of expression quantitative trait loci with target genes, and confirm assigned genes or show complex interactions for 20% of disease associated loci, including FOXO1, which we confirm using CRISPR/Cas9.
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Affiliation(s)
- Jing Yang
- Division of Informatics, Imaging & Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PT, UK
| | - Amanda McGovern
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, University of Manchester, Manchester, M13 9PT, UK
| | - Paul Martin
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, University of Manchester, Manchester, M13 9PT, UK
- Lydia Becker Institute of Immunology and Inflammation, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PT, UK
| | - Kate Duffus
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, University of Manchester, Manchester, M13 9PT, UK
| | - Xiangyu Ge
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, University of Manchester, Manchester, M13 9PT, UK
| | - Peyman Zarrineh
- Division of Informatics, Imaging & Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PT, UK
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, University of Manchester, Manchester, M13 9PT, UK
| | - Antony Adamson
- The Genome Editing Unit, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PT, UK
| | - Peter Fraser
- Department of Biological Science, Florida State University, Tallahassee, FL, 32306, USA
| | - Magnus Rattray
- Division of Informatics, Imaging & Data Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PT, UK.
| | - Stephen Eyre
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Manchester Academic Health Science Centre, University of Manchester, Manchester, M13 9PT, UK.
- NIHR Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester, UK.
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Cao C, Xu Q, Lin S, Zhi W, Lazare C, Meng Y, Wu P, Gao P, Li K, Wei J, Wu P, Li G. Mapping long-range contacts between risk loci and target genes in human diseases with Capture Hi-C. Clin Transl Med 2020; 10:e183. [PMID: 32997408 PMCID: PMC7520083 DOI: 10.1002/ctm2.183] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 09/13/2020] [Accepted: 09/14/2020] [Indexed: 12/11/2022] Open
Affiliation(s)
- Canhui Cao
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education)Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Department of Gynecologic OncologyTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Qian Xu
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
- Agricultural Bioinformatics Key Laboratory of Hubei ProvinceHubei Engineering Technology Research Center of Agricultural Big Data3D Genomics Research CenterCollege of InformaticsHuazhong Agricultural UniversityWuhanChina
| | - Shitong Lin
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education)Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Department of Gynecologic OncologyTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Wenhua Zhi
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education)Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Department of Gynecologic OncologyTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Cordelle Lazare
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education)Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Department of Gynecologic OncologyTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Yifan Meng
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education)Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Department of Gynecologic OncologyTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Ping Wu
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education)Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Department of Gynecologic OncologyTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Peipei Gao
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education)Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Department of Gynecologic OncologyTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Kezhen Li
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education)Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Department of Gynecologic OncologyTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Juncheng Wei
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education)Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Department of Gynecologic OncologyTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Peng Wu
- Cancer Biology Research Center (Key Laboratory of the Ministry of Education)Tongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
- Department of Gynecologic OncologyTongji HospitalTongji Medical CollegeHuazhong University of Science and TechnologyWuhanChina
| | - Guoliang Li
- National Key Laboratory of Crop Genetic ImprovementHuazhong Agricultural UniversityWuhanChina
- Agricultural Bioinformatics Key Laboratory of Hubei ProvinceHubei Engineering Technology Research Center of Agricultural Big Data3D Genomics Research CenterCollege of InformaticsHuazhong Agricultural UniversityWuhanChina
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39
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Turro E, Astle WJ, Megy K, Gräf S, Greene D, Shamardina O, Allen HL, Sanchis-Juan A, Frontini M, Thys C, Stephens J, Mapeta R, Burren OS, Downes K, Haimel M, Tuna S, Deevi SVV, Aitman TJ, Bennett DL, Calleja P, Carss K, Caulfield MJ, Chinnery PF, Dixon PH, Gale DP, James R, Koziell A, Laffan MA, Levine AP, Maher ER, Markus HS, Morales J, Morrell NW, Mumford AD, Ormondroyd E, Rankin S, Rendon A, Richardson S, Roberts I, Roy NBA, Saleem MA, Smith KGC, Stark H, Tan RYY, Themistocleous AC, Thrasher AJ, Watkins H, Webster AR, Wilkins MR, Williamson C, Whitworth J, Humphray S, Bentley DR, Kingston N, Walker N, Bradley JR, Ashford S, Penkett CJ, Freson K, Stirrups KE, Raymond FL, Ouwehand WH. Whole-genome sequencing of patients with rare diseases in a national health system. Nature 2020; 583:96-102. [PMID: 32581362 PMCID: PMC7610553 DOI: 10.1038/s41586-020-2434-2] [Citation(s) in RCA: 309] [Impact Index Per Article: 61.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2018] [Accepted: 05/05/2020] [Indexed: 02/02/2023]
Abstract
Most patients with rare diseases do not receive a molecular diagnosis and the aetiological variants and causative genes for more than half such disorders remain to be discovered1. Here we used whole-genome sequencing (WGS) in a national health system to streamline diagnosis and to discover unknown aetiological variants in the coding and non-coding regions of the genome. We generated WGS data for 13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to 1,138 of the 7,065 extensively phenotyped participants. We identified 95 Mendelian associations between genes and rare diseases, of which 11 have been discovered since 2015 and at least 79 are confirmed to be aetiological. By generating WGS data of UK Biobank participants2, we found that rare alleles can explain the presence of some individuals in the tails of a quantitative trait for red blood cells. Finally, we identified four novel non-coding variants that cause disease through the disruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates a synergy by using WGS for diagnosis and aetiological discovery in routine healthcare.
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Affiliation(s)
- Ernest Turro
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK.
- MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge, Cambridge, UK.
| | - William J Astle
- MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge, Cambridge, UK
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Karyn Megy
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Stefan Gräf
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
- Department of Medicine, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Daniel Greene
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge, Cambridge, UK
| | - Olga Shamardina
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Hana Lango Allen
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Alba Sanchis-Juan
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Mattia Frontini
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
- British Heart Foundation Cambridge Centre of Excellence, University of Cambridge, Cambridge, UK
| | - Chantal Thys
- Department of Cardiovascular Sciences, Center for Molecular and Vascular Biology, KU Leuven, Leuven, Belgium
| | - Jonathan Stephens
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Rutendo Mapeta
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Oliver S Burren
- Department of Medicine, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
| | - Kate Downes
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Matthias Haimel
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
- Department of Medicine, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Salih Tuna
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Sri V V Deevi
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Timothy J Aitman
- MRC Clinical Sciences Centre, Faculty of Medicine, Imperial College London, London, UK
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - David L Bennett
- The Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
| | - Paul Calleja
- High Performance Computing Service, University of Cambridge, Cambridge, UK
| | - Keren Carss
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Mark J Caulfield
- Genomics England Ltd, London, UK
- William Harvey Research Institute, NIHR Biomedical Research Centre at Barts, Queen Mary University of London, London, UK
| | - Patrick F Chinnery
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
- Department of Clinical Neurosciences, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- Medical Research Council Mitochondrial Biology Unit, Cambridge Biomedical Campus, Cambridge, UK
| | - Peter H Dixon
- Women and Children's Health, School of Life Course Sciences, King's College London, London, UK
| | - Daniel P Gale
- Department of Renal Medicine, University College London, London, UK
- Rare Renal Disease Registry, UK Renal Registry, Bristol, UK
| | - Roger James
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Ania Koziell
- King's College London, London, UK
- Department of Paediatric Nephrology, Evelina London Children's Hospital, Guy's & St Thomas' NHS Foundation Trust, London, UK
| | - Michael A Laffan
- Department of Haematology, Hammersmith Hospital, Imperial College Healthcare NHS Trust, London, UK
- Centre for Haematology, Imperial College London, London, UK
| | - Adam P Levine
- Department of Renal Medicine, University College London, London, UK
| | - Eamonn R Maher
- Department of Medical Genetics, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, Cambridge, UK
- Cancer Research UK Cambridge Centre, Cambridge Biomedical Campus, Cambridge, UK
| | - Hugh S Markus
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Bristol, UK
| | - Joannella Morales
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Cambridge, UK
| | - Nicholas W Morrell
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
- Department of Medicine, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
| | - Andrew D Mumford
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
- University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Elizabeth Ormondroyd
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
- Department of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Stuart Rankin
- High Performance Computing Service, University of Cambridge, Cambridge, UK
| | - Augusto Rendon
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- Genomics England Ltd, London, UK
| | - Sylvia Richardson
- MRC Biostatistics Unit, Cambridge Institute of Public Health, University of Cambridge, Cambridge, UK
| | - Irene Roberts
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
- Department of Paediatrics, Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
| | - Noemi B A Roy
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
- MRC Molecular Haematology Unit, MRC Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Moin A Saleem
- Bristol Renal and Children's Renal Unit, Bristol Medical School, University of Bristol, Bristol, UK
- Bristol Royal Hospital for Children, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Kenneth G C Smith
- Department of Medicine, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
| | - Hannah Stark
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Rhea Y Y Tan
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge Biomedical Campus, Bristol, UK
| | - Andreas C Themistocleous
- The Nuffield Department of Clinical Neurosciences, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | | | - Hugh Watkins
- Department of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Andrew R Webster
- Moorfields Eye Hospital NHS Trust, London, UK
- UCL Institute of Opthalmology, University College London, London, UK
| | | | - Catherine Williamson
- Women and Children's Health, School of Life Course Sciences, King's College London, London, UK
- Institute of Reproductive and Developmental Biology, Department of Surgery and Cancer, Faculty of Medicine, Hammersmith Hospital, Imperial College Healthcare NHS Trust, London, UK
| | - James Whitworth
- Department of Medical Genetics, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, Cambridge, UK
- Cancer Research UK Cambridge Centre, Cambridge Biomedical Campus, Cambridge, UK
| | | | | | - Nathalie Kingston
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Neil Walker
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - John R Bradley
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
- Department of Medicine, School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, Cambridge Biomedical Campus, Cambridge, UK
- Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Department of Renal Medicine, Addenbrookes Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Sofie Ashford
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Christopher J Penkett
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - Kathleen Freson
- Department of Cardiovascular Sciences, Center for Molecular and Vascular Biology, KU Leuven, Leuven, Belgium
| | - Kathleen E Stirrups
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK
| | - F Lucy Raymond
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK.
- Department of Medical Genetics, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
| | - Willem H Ouwehand
- Department of Haematology, University of Cambridge, Cambridge Biomedical Campus, Cambridge, UK.
- NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK.
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK.
- British Heart Foundation Cambridge Centre of Excellence, University of Cambridge, Cambridge, UK.
- Wellcome Sanger Institute, Cambridge, UK.
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40
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Thaventhiran JED, Lango Allen H, Burren OS, Rae W, Greene D, Staples E, Zhang Z, Farmery JHR, Simeoni I, Rivers E, Maimaris J, Penkett CJ, Stephens J, Deevi SVV, Sanchis-Juan A, Gleadall NS, Thomas MJ, Sargur RB, Gordins P, Baxendale HE, Brown M, Tuijnenburg P, Worth A, Hanson S, Linger RJ, Buckland MS, Rayner-Matthews PJ, Gilmour KC, Samarghitean C, Seneviratne SL, Sansom DM, Lynch AG, Megy K, Ellinghaus E, Ellinghaus D, Jorgensen SF, Karlsen TH, Stirrups KE, Cutler AJ, Kumararatne DS, Chandra A, Edgar JDM, Herwadkar A, Cooper N, Grigoriadou S, Huissoon AP, Goddard S, Jolles S, Schuetz C, Boschann F, Lyons PA, Hurles ME, Savic S, Burns SO, Kuijpers TW, Turro E, Ouwehand WH, Thrasher AJ, Smith KGC. Whole-genome sequencing of a sporadic primary immunodeficiency cohort. Nature 2020; 583:90-95. [PMID: 32499645 PMCID: PMC7334047 DOI: 10.1038/s41586-020-2265-1] [Citation(s) in RCA: 147] [Impact Index Per Article: 29.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2018] [Accepted: 02/26/2020] [Indexed: 12/19/2022]
Abstract
Primary immunodeficiency (PID) is characterized by recurrent and often life-threatening infections, autoimmunity and cancer, and it poses major diagnostic and therapeutic challenges. Although the most severe forms of PID are identified in early childhood, most patients present in adulthood, typically with no apparent family history and a variable clinical phenotype of widespread immune dysregulation: about 25% of patients have autoimmune disease, allergy is prevalent and up to 10% develop lymphoid malignancies1-3. Consequently, in sporadic (or non-familial) PID genetic diagnosis is difficult and the role of genetics is not well defined. Here we address these challenges by performing whole-genome sequencing in a large PID cohort of 1,318 participants. An analysis of the coding regions of the genome in 886 index cases of PID found that disease-causing mutations in known genes that are implicated in monogenic PID occurred in 10.3% of these patients, and a Bayesian approach (BeviMed4) identified multiple new candidate PID-associated genes, including IVNS1ABP. We also examined the noncoding genome, and found deletions in regulatory regions that contribute to disease causation. In addition, we used a genome-wide association study to identify loci that are associated with PID, and found evidence for the colocalization of-and interplay between-novel high-penetrance monogenic variants and common variants (at the PTPN2 and SOCS1 loci). This begins to explain the contribution of common variants to the variable penetrance and phenotypic complexity that are observed in PID. Thus, using a cohort-based whole-genome-sequencing approach in the diagnosis of PID can increase diagnostic yield and further our understanding of the key pathways that influence immune responsiveness in humans.
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Affiliation(s)
- James E D Thaventhiran
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK.
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK.
- Medical Research Council Toxicology Unit, School of Biological Sciences, University of Cambridge, Cambridge, UK.
| | - Hana Lango Allen
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
- Medical Research Council Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
| | - Oliver S Burren
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
| | - William Rae
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
| | - Daniel Greene
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
- Medical Research Council Biostatistics Unit, Cambridge Institute of Public Health, Cambridge Biomedical Campus, Cambridge, UK
| | - Emily Staples
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
| | - Zinan Zhang
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- Molecular Development of the Immune System Section, Laboratory of Immune System Biology and Clinical Genomics Program, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA
| | - James H R Farmery
- Medical Research Council Biostatistics Unit, Cambridge Institute of Public Health, Cambridge Biomedical Campus, Cambridge, UK
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK
| | - Ilenia Simeoni
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Elizabeth Rivers
- UCL Great Ormond Street Institute of Child Health, London, UK
- Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Jesmeen Maimaris
- UCL Great Ormond Street Institute of Child Health, London, UK
- Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Christopher J Penkett
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Jonathan Stephens
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Sri V V Deevi
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Alba Sanchis-Juan
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Nicholas S Gleadall
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
| | - Moira J Thomas
- Department of Immunology, Queen Elizabeth University Hospital, Glasgow, UK
- Gartnavel General Hospital, NHS Greater Glasgow and Clyde, Glasgow, UK
| | - Ravishankar B Sargur
- Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK
- Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK
| | - Pavels Gordins
- East Yorkshire Regional Adult Immunology and Allergy Unit, Hull Royal Infirmary, Hull and East Yorkshire Hospitals NHS Trust, Hull, UK
| | - Helen E Baxendale
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- Royal Papworth Hospital NHS Foundation Trust, Cambridge, UK
| | - Matthew Brown
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Paul Tuijnenburg
- Department of Pediatric Immunology, Rheumatology and Infectious Diseases, Emma Children's Hospital, Amsterdam, The Netherlands
- Department of Experimental Immunology, Amsterdam University Medical Center (AMC), University of Amsterdam, Amsterdam, The Netherlands
| | - Austen Worth
- UCL Great Ormond Street Institute of Child Health, London, UK
- Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Steven Hanson
- Institute of Immunity and Transplantation, University College London, London, UK
- Department of Immunology, Royal Free London NHS Foundation Trust, London, UK
| | - Rachel J Linger
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Matthew S Buckland
- Institute of Immunity and Transplantation, University College London, London, UK
- Department of Immunology, Royal Free London NHS Foundation Trust, London, UK
| | - Paula J Rayner-Matthews
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Kimberly C Gilmour
- UCL Great Ormond Street Institute of Child Health, London, UK
- Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Crina Samarghitean
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Suranjith L Seneviratne
- Institute of Immunity and Transplantation, University College London, London, UK
- Department of Immunology, Royal Free London NHS Foundation Trust, London, UK
| | - David M Sansom
- Institute of Immunity and Transplantation, University College London, London, UK
- Department of Immunology, Royal Free London NHS Foundation Trust, London, UK
| | - Andy G Lynch
- Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Cambridge, UK
- School of Mathematics and Statistics, University of St Andrews, St Andrews, UK
- School of Medicine, University of St Andrews, St Andrews, UK
| | - Karyn Megy
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Eva Ellinghaus
- K.G. Jebsen Inflammation Research Centre, Institute of Clinical Medicine, University of Oslo, Oslo University Hospital, Oslo, Norway
| | - David Ellinghaus
- Department of Transplantation, Institute of Clinical Medicine, University of Oslo, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Molecular Biology, Christian Albrechts University of Kiel, Kiel, Germany
| | - Silje F Jorgensen
- Section of Clinical Immunology and Infectious Diseases, Department of Rheumatology, Dermatology and Infectious Diseases, Oslo University Hospital, Oslo, Norway
- Research Institute of Internal Medicine, Division of Surgery, Inflammatory Diseases and Transplantation, Oslo University Hospital, Oslo, Norway
| | - Tom H Karlsen
- K.G. Jebsen Inflammation Research Centre, Institute of Clinical Medicine, University of Oslo, Oslo University Hospital, Oslo, Norway
| | - Kathleen E Stirrups
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Antony J Cutler
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Dinakantha S Kumararatne
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- Department of Clinical Biochemistry and Immunology, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - Anita Chandra
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- Department of Clinical Biochemistry and Immunology, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
| | - J David M Edgar
- St James's Hospital, Dublin, Ireland
- Trinity College Dublin, Dublin, Ireland
| | | | - Nichola Cooper
- Department of Medicine, Imperial College London, London, UK
| | | | - Aarnoud P Huissoon
- West Midlands Immunodeficiency Centre, University Hospitals Birmingham, Birmingham, UK
- Birmingham Heartlands Hospital, University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Sarah Goddard
- University Hospitals of North Midlands NHS Trust, Stoke-on-Trent, UK
| | - Stephen Jolles
- Immunodeficiency Centre for Wales, University Hospital of Wales, Cardiff, UK
| | - Catharina Schuetz
- Department of Pediatric Immunology, University Hospital Carl Gustav Carus, Dresden, Germany
| | - Felix Boschann
- Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Paul A Lyons
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
| | - Matthew E Hurles
- Department of Human Genetics, Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Sinisa Savic
- Department of Clinical Immunology and Allergy, St James's University Hospital, Leeds, UK
- The NIHR Leeds Biomedical Research Centre, Leeds, UK
- Leeds Institute of Rheumatic and Musculoskeletal Medicine, Leeds, UK
| | - Siobhan O Burns
- Institute of Immunity and Transplantation, University College London, London, UK
- Department of Immunology, Royal Free London NHS Foundation Trust, London, UK
| | - Taco W Kuijpers
- Department of Pediatric Immunology, Rheumatology and Infectious Diseases, Emma Children's Hospital, Amsterdam, The Netherlands
- Department of Experimental Immunology, Amsterdam University Medical Center (AMC), University of Amsterdam, Amsterdam, The Netherlands
- Department of Blood Cell Research, Sanquin, Amsterdam, The Netherlands
| | - Ernest Turro
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
- Medical Research Council Biostatistics Unit, Cambridge Institute of Public Health, Cambridge Biomedical Campus, Cambridge, UK
| | - Willem H Ouwehand
- Department of Haematology, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK
- NHS Blood and Transplant, Cambridge Biomedical Campus, Cambridge, UK
- NIHR BioResource, Cambridge University Hospitals, Cambridge Biomedical Campus, Cambridge, UK
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Adrian J Thrasher
- UCL Great Ormond Street Institute of Child Health, London, UK
- Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Kenneth G C Smith
- Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK.
- Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK.
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41
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Mitchelmore J, Grinberg NF, Wallace C, Spivakov M. Functional effects of variation in transcription factor binding highlight long-range gene regulation by epromoters. Nucleic Acids Res 2020; 48:2866-2879. [PMID: 32112106 PMCID: PMC7102942 DOI: 10.1093/nar/gkaa123] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2019] [Revised: 02/14/2020] [Accepted: 02/17/2020] [Indexed: 02/06/2023] Open
Abstract
Identifying DNA cis-regulatory modules (CRMs) that control the expression of specific genes is crucial for deciphering the logic of transcriptional control. Natural genetic variation can point to the possible gene regulatory function of specific sequences through their allelic associations with gene expression. However, comprehensive identification of causal regulatory sequences in brute-force association testing without incorporating prior knowledge is challenging due to limited statistical power and effects of linkage disequilibrium. Sequence variants affecting transcription factor (TF) binding at CRMs have a strong potential to influence gene regulatory function, which provides a motivation for prioritizing such variants in association testing. Here, we generate an atlas of CRMs showing predicted allelic variation in TF binding affinity in human lymphoblastoid cell lines and test their association with the expression of their putative target genes inferred from Promoter Capture Hi-C and immediate linear proximity. We reveal >1300 CRM TF-binding variants associated with target gene expression, the majority of them undetected with standard association testing. A large proportion of CRMs showing associations with the expression of genes they contact in 3D localize to the promoter regions of other genes, supporting the notion of 'epromoters': dual-action CRMs with promoter and distal enhancer activity.
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Affiliation(s)
- Joanna Mitchelmore
- Nuclear Dynamics Programme, Babraham Institute, Babraham Research Campus, Cambridge CB22 3AT, UK
| | - Nastasiya F Grinberg
- Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0AW, UK
| | - Chris Wallace
- Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0AW, UK
- MRC Biostatistics Unit, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0SR, UK
| | - Mikhail Spivakov
- Nuclear Dynamics Programme, Babraham Institute, Babraham Research Campus, Cambridge CB22 3AT, UK
- MRC London Institute of Medical Sciences, Du Cane Road, London W12 0NN, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College, Du Cane Road, London W12 0NN, UK
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42
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Spolski R, Li P, Leonard WJ. Biology and regulation of IL-2: from molecular mechanisms to human therapy. Nat Rev Immunol 2019; 18:648-659. [PMID: 30089912 DOI: 10.1038/s41577-018-0046-y] [Citation(s) in RCA: 401] [Impact Index Per Article: 66.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
IL-2 was first identified as a growth factor capable of driving the expansion of activated human T cell populations. In the more than 40 years since its discovery, a tremendous amount has been learned regarding the mechanisms that regulate the expression of both IL-2 and its cell surface receptor, its mechanisms of signalling and its range of biological actions. More recently, the mechanisms by which IL-2 regulates CD4+ T cell differentiation and function have been elucidated. IL-2 also regulates the effector and memory responses of CD8+ T cells, and the loss of IL-2 or responsiveness to IL-2 at least in part explains the exhausted phenotype that occurs during chronic viral infections and in tumour responses. These basic mechanistic studies have led to the therapeutic ability to manipulate the action of IL-2 on regulatory T (Treg) cells for the treatment of autoimmune disease and on CD8+ T cells for immunotherapy of cancer. IL-2 can have either positive or deleterious effects, and we discuss here recent ideas and approaches for manipulating the actions and overall net effects of IL-2 in disease settings, including cancer.
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Affiliation(s)
- Rosanne Spolski
- Laboratory of Molecular Immunology and The Immunology Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Peng Li
- Laboratory of Molecular Immunology and The Immunology Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Warren J Leonard
- Laboratory of Molecular Immunology and The Immunology Center, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
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43
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Asimit JL, Rainbow DB, Fortune MD, Grinberg NF, Wicker LS, Wallace C. Stochastic search and joint fine-mapping increases accuracy and identifies previously unreported associations in immune-mediated diseases. Nat Commun 2019; 10:3216. [PMID: 31324808 PMCID: PMC6642100 DOI: 10.1038/s41467-019-11271-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Accepted: 07/02/2019] [Indexed: 02/06/2023] Open
Abstract
Thousands of genetic variants are associated with human disease risk, but linkage disequilibrium (LD) hinders fine-mapping the causal variants. Both lack of power, and joint tagging of two or more distinct causal variants by a single non-causal SNP, lead to inaccuracies in fine-mapping, with stochastic search more robust than stepwise. We develop a computationally efficient multinomial fine-mapping (MFM) approach that borrows information between diseases in a Bayesian framework. We show that MFM has greater accuracy than single disease analysis when shared causal variants exist, and negligible loss of precision otherwise. MFM analysis of six immune-mediated diseases reveals causal variants undetected in individual disease analysis, including in IL2RA where we confirm functional effects of multiple causal variants using allele-specific expression in sorted CD4+ T cells from genotype-selected individuals. MFM has the potential to increase fine-mapping resolution in related diseases enabling the identification of associated cellular and molecular phenotypes.
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Affiliation(s)
- Jennifer L Asimit
- MRC Biostatistics Unit, University of Cambridge, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge Biomedical Campus, Cambridge, CB2 0SR, UK.
| | - Daniel B Rainbow
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Trust Center for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
| | - Mary D Fortune
- MRC Biostatistics Unit, University of Cambridge, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge Biomedical Campus, Cambridge, CB2 0SR, UK
| | - Nastasiya F Grinberg
- Department of Medicine, Cambridge Biomedical Campus, University of Cambridge, Box 157, Level 4, Cambridge, CB2 0QQ, UK
| | - Linda S Wicker
- JDRF/Wellcome Diabetes and Inflammation Laboratory, Wellcome Trust Center for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, OX3 7BN, UK
| | - Chris Wallace
- MRC Biostatistics Unit, University of Cambridge, Cambridge Institute of Public Health, Forvie Site, Robinson Way, Cambridge Biomedical Campus, Cambridge, CB2 0SR, UK.
- Department of Medicine, Cambridge Biomedical Campus, University of Cambridge, Box 157, Level 4, Cambridge, CB2 0QQ, UK.
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44
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Long-range interactions between proximal and distal regulatory regions in maize. Nat Commun 2019; 10:2633. [PMID: 31201330 PMCID: PMC6572780 DOI: 10.1038/s41467-019-10603-4] [Citation(s) in RCA: 77] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2018] [Accepted: 05/20/2019] [Indexed: 12/30/2022] Open
Abstract
Long-range chromatin interactions are important for transcriptional regulation of genes, many of which are related to complex agronomics traits. However, the pattern of three-dimensional chromatin interactions remains unclear in plants. Here we report the generation of chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) data and the construction of extensive H3K4me3- and H3K27ac-centered chromatin interaction maps in maize. Results show that the interacting patterns between proximal and distal regulatory regions of genes are highly complex and dynamic. Genes with chromatin interactions have higher expression levels than those without interactions. Genes with proximal-proximal interactions prefer to be transcriptionally coordinated. Tissue-specific proximal–distal interactions are associated with tissue-specific expression of genes. Interactions between proximal and distal regulatory regions further interweave into organized network communities that are enriched in specific biological functions. The high-resolution chromatin interaction maps will help to understand the transcription regulation of genes associated with complex agronomic traits of maize. Chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) can discover specific protein-centered chromatin interactions in high resolution. Here, the authors use ChIA-PET to reveal the complex and dynamic interactions between proximal and distal regulatory regions of genes in maize.
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45
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Li W, Wong WH, Jiang R. DeepTACT: predicting 3D chromatin contacts via bootstrapping deep learning. Nucleic Acids Res 2019; 47:e60. [PMID: 30869141 PMCID: PMC6547469 DOI: 10.1093/nar/gkz167] [Citation(s) in RCA: 83] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2018] [Revised: 02/08/2019] [Accepted: 02/28/2019] [Indexed: 12/20/2022] Open
Abstract
Interactions between regulatory elements are of crucial importance for the understanding of transcriptional regulation and the interpretation of disease mechanisms. Hi-C technique has been developed for genome-wide detection of chromatin contacts. However, unless extremely deep sequencing is performed on a very large number of input cells, which is technically limited and expensive, current Hi-C experiments do not have high enough resolution to resolve contacts between regulatory elements. Here, we develop DeepTACT, a bootstrapping deep learning model, to integrate genome sequences and chromatin accessibility data for the prediction of chromatin contacts between regulatory elements. DeepTACT can infer not only promoter-enhancer interactions, but also promoter-promoter interactions. In tests based on promoter capture Hi-C data, DeepTACT shows better performance over existing methods. DeepTACT analysis also identifies a class of hub promoters, which are correlated with transcriptional activation across cell lines, enriched in housekeeping genes, functionally related to fundamental biological processes, and capable of reflecting cell similarity. Finally, the utility of chromatin contacts in the study of human diseases is illustrated by the association of IFNA2 to coronary artery disease via an integrative analysis of GWAS data and interactions predicted by DeepTACT.
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Affiliation(s)
- Wenran Li
- MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, BNRist, Department of Automation, Tsinghua University, Beijing 100084, China
- Department of Statistics, Stanford University, Stanford, CA 94305, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Wing Hung Wong
- Department of Statistics, Stanford University, Stanford, CA 94305, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Rui Jiang
- MOE Key Laboratory of Bioinformatics, Bioinformatics Division and Center for Synthetic and Systems Biology, BNRist, Department of Automation, Tsinghua University, Beijing 100084, China
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46
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Krumm A, Duan Z. Understanding the 3D genome: Emerging impacts on human disease. Semin Cell Dev Biol 2019; 90:62-77. [PMID: 29990539 PMCID: PMC6329682 DOI: 10.1016/j.semcdb.2018.07.004] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Accepted: 07/03/2018] [Indexed: 12/13/2022]
Abstract
Recent burst of new technologies that allow for quantitatively delineating chromatin structure has greatly expanded our understanding of how the genome is organized in the three-dimensional (3D) space of the nucleus. It is now clear that the hierarchical organization of the eukaryotic genome critically impacts nuclear activities such as transcription, replication, as well as cellular and developmental events such as cell cycle, cell fate decision and embryonic development. In this review, we discuss new insights into how the structural features of the 3D genome hierarchy are established and maintained, how this hierarchy undergoes dynamic rearrangement during normal development and how its perturbation will lead to human disease, highlighting the accumulating evidence that links the diverse 3D genome architecture components to a multitude of human diseases and the emerging mechanisms by which 3D genome derangement causes disease phenotypes.
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Affiliation(s)
- Anton Krumm
- Department of Microbiology, University of Washington, USA.
| | - Zhijun Duan
- Institute for Stem Cell and Regenerative Medicine, University of Washington, USA; Division of Hematology, Department of Medicine, University of Washington, USA.
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47
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Yu J, Peng J, Chi H. Systems immunology: Integrating multi-omics data to infer regulatory networks and hidden drivers of immunity. ACTA ACUST UNITED AC 2019; 15:19-29. [PMID: 32789283 DOI: 10.1016/j.coisb.2019.03.003] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
The immune system is a highly complex and dynamic biological system. It operates through intracellular molecular networks and intercellular (cell-cell) interaction networks. Systems immunology is an emerging discipline that applies systems biology approaches of integrating high-throughput multi-omics measurements with computational network modeling to better understand immunity at various scales. In this review, we summarize key omics technologies and computational approaches used for immunological studies at both population and single-cell levels. We highlight the hidden driver analysis based on data-driven networks and comment on the potential of translating systems immunology discoveries to immunotherapy of cancer and other human diseases.
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Affiliation(s)
- Jiyang Yu
- Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Junmin Peng
- Department of Structural Biology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Department of Developmental Neurobiology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
- Center for Proteomics and Metabolomics, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Hongbo Chi
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, TN 38105, USA
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48
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Eijsbouts CQ, Burren OS, Newcombe PJ, Wallace C. Fine mapping chromatin contacts in capture Hi-C data. BMC Genomics 2019; 20:77. [PMID: 30674271 PMCID: PMC6343296 DOI: 10.1186/s12864-018-5314-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2018] [Accepted: 11/27/2018] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Hi-C and capture Hi-C (CHi-C) are used to map physical contacts between chromatin regions in cell nuclei using high-throughput sequencing. Analysis typically proceeds considering the evidence for contacts between each possible pair of fragments independent from other pairs. This can produce long runs of fragments which appear to all make contact with the same baited fragment of interest. RESULTS We hypothesised that these long runs could result from a smaller subset of direct contacts and propose a new method, based on a Bayesian sparse variable selection approach, which attempts to fine map these direct contacts. Our model is conceptually novel, exploiting the spatial pattern of counts in CHi-C data. Although we use only the CHi-C count data in fitting the model, we show that the fragments prioritised display biological properties that would be expected of true contacts: for bait fragments corresponding to gene promoters, we identify contact fragments with active chromatin and contacts that correspond to edges found in previously defined enhancer-target networks; conversely, for intergenic bait fragments, we identify contact fragments corresponding to promoters for genes expressed in that cell type. We show that long runs of apparently co-contacting fragments can typically be explained using a subset of direct contacts consisting of <10% of the number in the full run, suggesting that greater resolution can be extracted from existing datasets. CONCLUSIONS Our results appear largely complementary to those from a per-fragment analytical approach, suggesting that they provide an additional level of interpretation that may be used to increase resolution for mapping direct contacts in CHi-C experiments.
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Affiliation(s)
- Christiaan Q Eijsbouts
- Department of Medicine, University of Cambridge, Addenbrooke’s Hospital, Hills Road, Cambridge, UK
- MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge, UK
- Current address: Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Roosevelt Drive, Oxford, UK
| | - Oliver S Burren
- Department of Medicine, University of Cambridge, Addenbrooke’s Hospital, Hills Road, Cambridge, UK
| | - Paul J Newcombe
- MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge, UK
| | - Chris Wallace
- Department of Medicine, University of Cambridge, Addenbrooke’s Hospital, Hills Road, Cambridge, UK
- MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge, UK
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49
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Hansen P, Ali S, Blau H, Danis D, Hecht J, Kornak U, Lupiáñez DG, Mundlos S, Steinhaus R, Robinson PN. GOPHER: Generator Of Probes for capture Hi-C Experiments at high Resolution. BMC Genomics 2019; 20:40. [PMID: 30642251 PMCID: PMC6332836 DOI: 10.1186/s12864-018-5376-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Accepted: 12/16/2018] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Target enrichment combined with chromosome conformation capturing methodologies such as capture Hi-C (CHC) can be used to investigate spatial layouts of genomic regions with high resolution and at scalable costs. A common application of CHC is the investigation of regulatory elements that are in contact with promoters, but CHC can be used for a range of other applications. Therefore, probe design for CHC needs to be adapted to experimental needs, but no flexible tool is currently available for this purpose. RESULTS We present a Java desktop application called GOPHER (Generator Of Probes for capture Hi-C Experiments at high Resolution) that implements three strategies for CHC probe design. GOPHER's simple approach is similar to the probe design of previous approaches that employ CHC to investigate all promoters, with one probe being placed at each margin of a single digest that overlaps the transcription start site (TSS) of each promoter. GOPHER's simple-patched approach extends this methodology with a heuristic that improves coverage of viewpoints in which the TSS is located near to one of the boundaries of the digest. GOPHER's extended approach is intended mainly for focused investigations of smaller gene sets. GOPHER can also be used to design probes for regions other than TSS such as GWAS hits or large blocks of genomic sequence. GOPHER additionally provides a number of features that allow users to visualize and edit viewpoints, and outputs a range of files useful for documentation, ordering probes, and downstream analysis. CONCLUSION GOPHER is an easy-to-use and robust desktop application for CHC probe design. Source code and a precompiled executable can be downloaded from the GOPHER GitHub page at https://github.com/TheJacksonLaboratory/Gopher .
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Affiliation(s)
- Peter Hansen
- Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany
| | - Salaheddine Ali
- Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, Berlin, 14195, Germany
| | - Hannah Blau
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, 06032, CT, United States
| | - Daniel Danis
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, 06032, CT, United States
| | - Jochen Hecht
- Genomics Unit, Centre for Genomic Regulation, Carrer del Dr. Aiguader 88, Barcelona, 08003, Spain
| | - Uwe Kornak
- Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany.,Berlin Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany
| | - Darío G Lupiáñez
- Epigenetics and Sex Development Group, Berlin Institute for Medical Systems Biology, Max-Delbrück Center for Molecular Medicine, Berlin-Buch, 13125, Germany
| | - Stefan Mundlos
- Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany.,Max Planck Institute for Molecular Genetics, Ihnestr. 63-73, Berlin, 14195, Germany.,Berlin Brandenburg Center for Regenerative Therapies (BCRT), Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany
| | - Robin Steinhaus
- Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Augustenburger Platz 1, Berlin, 13353, Germany
| | - Peter N Robinson
- The Jackson Laboratory for Genomic Medicine, 10 Discovery Drive, Farmington, 06032, CT, United States. .,Institute for Systems Genomics, University of Connecticut, Farmington, 06032, CT, United States.
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50
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Zeng C, Chen L, Chen B, Cai Y, Li P, Yan L, Zeng D. Th17 cells were recruited and accumulated in the cerebrospinal fluid and correlated with the poor prognosis of anti-NMDAR encephalitis. Acta Biochim Biophys Sin (Shanghai) 2018; 50:1266-1273. [PMID: 30418472 DOI: 10.1093/abbs/gmy137] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2018] [Indexed: 12/24/2022] Open
Abstract
Anti-N-methyl-D-aspartate-receptor (NMDAR) encephalitis is an autoimmune disorder characterized by memory deficits, psychiatric symptoms, and autonomic instability. The lack of suitable biomarkers targeting anti-NMDAR encephalitis makes the immunotherapy and prognosis challenging. In this study, we found that the Th17 cells were significantly accumulated in the cerebrospinal fluid (CSF) of anti-NMDAR encephalitis patients than that of control individuals. The concentration of the cytokines and chemokines including interleukin (IL)-1β, IL-17, IL-6, and CXCL-13 were significantly increased in the CSF of anti-NMDAR encephalitis patients. IL-6 and IL-17 were found to promote the differentiation of CD4+ T cells into Th17 lineage. The chemotaxis assay showed that CCL20 and CCL22 play essential roles in the migration of Th17 cells. Notably, the correlation between the expression of IL-17 and the outcome of anti-NMDAR encephalitis patients was analyzed. The data showed that high level of IL-17 was significantly correlated with the limited response to the treatment and relapse of anti-NMDAR encephalitis patients. Our results suggested the potential important involvement of IL-17 in anti-NMDAR encephalitis.
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Affiliation(s)
- Chaosheng Zeng
- Department of Neurology, The Second Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Lin Chen
- Department of Neurology, The Second Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Bocan Chen
- Department of Neurology, The Second Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Yi Cai
- Department of Neurology, The Second Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Pengxiang Li
- Department of Neurology, The Second Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Limin Yan
- Department of Neurology, The Second Affiliated Hospital of Hainan Medical University, Haikou, China
| | - Dehua Zeng
- Department of Neurology, Haikou People’s Hospital, Haikou, China
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