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He J, Huo X, Pei G, Jia Z, Yan Y, Yu J, Qu H, Xie Y, Yuan J, Zheng Y, Hu Y, Shi M, You K, Li T, Ma T, Zhang MQ, Ding S, Li P, Li Y. Dual-role transcription factors stabilize intermediate expression levels. Cell 2024; 187:2746-2766.e25. [PMID: 38631355 DOI: 10.1016/j.cell.2024.03.023] [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: 06/09/2023] [Revised: 12/08/2023] [Accepted: 03/18/2024] [Indexed: 04/19/2024]
Abstract
Precise control of gene expression levels is essential for normal cell functions, yet how they are defined and tightly maintained, particularly at intermediate levels, remains elusive. Here, using a series of newly developed sequencing, imaging, and functional assays, we uncover a class of transcription factors with dual roles as activators and repressors, referred to as condensate-forming level-regulating dual-action transcription factors (TFs). They reduce high expression but increase low expression to achieve stable intermediate levels. Dual-action TFs directly exert activating and repressing functions via condensate-forming domains that compartmentalize core transcriptional unit selectively. Clinically relevant mutations in these domains, which are linked to a range of developmental disorders, impair condensate selectivity and dual-action TF activity. These results collectively address a fundamental question in expression regulation and demonstrate the potential of level-regulating dual-action TFs as powerful effectors for engineering controlled expression levels.
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Affiliation(s)
- Jinnan He
- The IDG/McGovern Institute for Brain Research, MOE Key Laboratory of Bioinformatics, State Key Lab of Molecular Oncology, Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China; School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China
| | - Xiangru Huo
- The IDG/McGovern Institute for Brain Research, MOE Key Laboratory of Bioinformatics, State Key Lab of Molecular Oncology, Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China; School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China
| | - Gaofeng Pei
- State Key Laboratory of Membrane Biology, Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing 100084, China; Tsinghua University-Peking University Joint Center for Life Sciences, Beijing 100084, China
| | - Zeran Jia
- The IDG/McGovern Institute for Brain Research, MOE Key Laboratory of Bioinformatics, State Key Lab of Molecular Oncology, Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China; School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China
| | - Yiming Yan
- The IDG/McGovern Institute for Brain Research, MOE Key Laboratory of Bioinformatics, State Key Lab of Molecular Oncology, Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China; School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China
| | - Jiawei Yu
- The IDG/McGovern Institute for Brain Research, MOE Key Laboratory of Bioinformatics, State Key Lab of Molecular Oncology, Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China; School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China
| | - Haozhi Qu
- The IDG/McGovern Institute for Brain Research, MOE Key Laboratory of Bioinformatics, State Key Lab of Molecular Oncology, Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China; School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China
| | - Yunxin Xie
- The IDG/McGovern Institute for Brain Research, MOE Key Laboratory of Bioinformatics, State Key Lab of Molecular Oncology, Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China; School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China
| | - Junsong Yuan
- The IDG/McGovern Institute for Brain Research, MOE Key Laboratory of Bioinformatics, State Key Lab of Molecular Oncology, Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China; School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China
| | - Yuan Zheng
- The IDG/McGovern Institute for Brain Research, MOE Key Laboratory of Bioinformatics, State Key Lab of Molecular Oncology, Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China; School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China
| | - Yanyan Hu
- School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China; Tsinghua University-Peking University Joint Center for Life Sciences, Beijing 100084, China
| | - Minglei Shi
- Bioinformatics Division, National Research Center for Information Science and Technology, School of Medicine, Tsinghua University, Beijing 100084, China
| | - Kaiqiang You
- Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Tingting Li
- Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - Tianhua Ma
- School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China; Tsinghua University-Peking University Joint Center for Life Sciences, Beijing 100084, China
| | - Michael Q Zhang
- Bioinformatics Division, National Research Center for Information Science and Technology, School of Medicine, Tsinghua University, Beijing 100084, China; Department of Biological Sciences, Center for Systems Biology, The University of Texas, Dallas, TX 75080-3021, USA
| | - Sheng Ding
- School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China; Tsinghua University-Peking University Joint Center for Life Sciences, Beijing 100084, China
| | - Pilong Li
- State Key Laboratory of Membrane Biology, Frontier Research Center for Biological Structure, School of Life Sciences, Tsinghua University, Beijing 100084, China; Tsinghua University-Peking University Joint Center for Life Sciences, Beijing 100084, China.
| | - Yinqing Li
- The IDG/McGovern Institute for Brain Research, MOE Key Laboratory of Bioinformatics, State Key Lab of Molecular Oncology, Center for Synthetic and Systems Biology, Tsinghua University, Beijing 100084, China; School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China.
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2
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Bakiri L, Hasenfuss SC, Guío-Carrión A, Thomsen MK, Hasselblatt P, Wagner EF. Liver cancer development driven by the AP-1/c-Jun~Fra-2 dimer through c-Myc. Proc Natl Acad Sci U S A 2024; 121:e2404188121. [PMID: 38657045 PMCID: PMC11067056 DOI: 10.1073/pnas.2404188121] [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: 02/28/2024] [Accepted: 03/26/2024] [Indexed: 04/26/2024] Open
Abstract
Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death. HCC incidence is on the rise, while treatment options remain limited. Thus, a better understanding of the molecular pathways involved in HCC development has become a priority to guide future therapies. While previous studies implicated the Activator Protein-1 (AP-1) (Fos/Jun) transcription factor family members c-Fos and c-Jun in HCC formation, the contribution of Fos-related antigens (Fra-) 1 and 2 is unknown. Here, we show that hepatocyte-restricted expression of a single chain c-Jun~Fra-2 protein, which functionally mimics the c-Jun/Fra-2 AP-1 dimer, results in spontaneous HCC formation in c-Jun~Fra-2hep mice. Several hallmarks of human HCC, such as cell cycle dysregulation and the expression of HCC markers are observed in liver tumors arising in c-Jun~Fra-2hep mice. Tumorigenesis occurs in the context of mild inflammation, low-grade fibrosis, and Pparγ-driven dyslipidemia. Subsequent analyses revealed increased expression of c-Myc, evidently under direct regulation by AP-1 through a conserved distal 3' enhancer. Importantly, c-Jun~Fra-2-induced tumors revert upon switching off transgene expression, suggesting oncogene addiction to the c-Jun~Fra-2 transgene. Tumors escaping reversion maintained c-Myc and c-Myc target gene expression, likely due to increased c-Fos. Interfering with c-Myc in established tumors using the Bromodomain and Extra-Terminal motif inhibitor JQ-1 diminished liver tumor growth in c-Jun~Fra-2 mutant mice. Thus, our data establish c-Jun~Fra-2hep mice as a model to study liver tumorigenesis and identify the c-Jun/Fra-2-Myc interaction as a potential target to improve HCC patient stratification and/or therapy.
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Affiliation(s)
- Latifa Bakiri
- Laboratory Genes and Disease, Department of Laboratory Medicine, Medical University of Vienna, 1090, Vienna, Austria
- Genes, Development and Disease Group, National Cancer Research Centre, 28029, Madrid, Spain
| | - Sebastian C. Hasenfuss
- Genes, Development and Disease Group, National Cancer Research Centre, 28029, Madrid, Spain
| | - Ana Guío-Carrión
- Genes, Development and Disease Group, National Cancer Research Centre, 28029, Madrid, Spain
| | - Martin K. Thomsen
- Department of Biomedicine, University of Aarhus, 8000, Aarhus, Denmark
| | - Peter Hasselblatt
- Department of Medicine II, University Hospital and Faculty of Medicine, 79106, Freiburg, Germany
| | - Erwin F. Wagner
- Laboratory Genes and Disease, Department of Laboratory Medicine, Medical University of Vienna, 1090, Vienna, Austria
- Laboratory Genes and Disease, Department of Dermatology, Medical University of Vienna, 1090, Vienna, Austria
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3
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Guimarães DSPSF, Barrios NMF, de Oliveira AG, Rizo-Roca D, Jollet M, Smith JAB, Araujo TR, da Cruz MV, Marconato E, Hirabara SM, Vieira AS, Krook A, Zierath JR, Silveira LR. Concerted regulation of skeletal muscle metabolism and contractile properties by the orphan nuclear receptor Nr2f6. J Cachexia Sarcopenia Muscle 2024. [PMID: 38682559 DOI: 10.1002/jcsm.13480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 02/27/2024] [Accepted: 03/19/2024] [Indexed: 05/01/2024] Open
Abstract
BACKGROUND The maintenance of skeletal muscle plasticity upon changes in the environment, nutrient supply, and exercise depends on regulatory mechanisms that couple structural and metabolic adaptations. The mechanisms that interconnect both processes at the transcriptional level remain underexplored. Nr2f6, a nuclear receptor, regulates metabolism and cell differentiation in peripheral tissues. However, its role in the skeletal muscle is still elusive. Here, we aimed to investigate the effects of Nr2f6 modulation on muscle biology in vivo and in vitro. METHODS Global RNA-seq was performed in Nr2f6 knockdown C2C12 myocytes (N = 4-5). Molecular and metabolic assays and proliferation experiments were performed using stable Nr2f6 knockdown and Nr2f6 overexpression C2C12 cell lines (N = 3-6). Nr2f6 content was evaluated in lipid overload models in vitro and in vivo (N = 3-6). In vivo experiments included Nr2f6 overexpression in mouse tibialis anterior muscle, followed by gene array transcriptomics and molecular assays (N = 4), ex vivo contractility experiments (N = 5), and histological analysis (N = 7). The conservation of Nr2f6 depletion effects was confirmed in primary skeletal muscle cells of humans and mice. RESULTS Nr2f6 knockdown upregulated genes associated with muscle differentiation, metabolism, and contraction, while cell cycle-related genes were downregulated. In human skeletal muscle cells, Nr2f6 knockdown significantly increased the expression of myosin heavy chain genes (two-fold to three-fold) and siRNA-mediated depletion of Nr2f6 increased maximal C2C12 myocyte's lipid oxidative capacity by 75% and protected against lipid-induced cell death. Nr2f6 content decreased by 40% in lipid-overloaded myotubes and by 50% in the skeletal muscle of mice fed a high-fat diet. Nr2f6 overexpression in mice resulted in an atrophic and hypoplastic state, characterized by a significant reduction in muscle mass (15%) and myofibre content (18%), followed by an impairment (50%) in force production. These functional phenotypes were accompanied by the establishment of an inflammation-like molecular signature and a decrease in the expression of genes involved in muscle contractility and oxidative metabolism, which was associated with the repression of the uncoupling protein 3 (20%) and PGC-1α (30%) promoters activity following Nr2f6 overexpression in vitro. Additionally, Nr2f6 regulated core components of the cell division machinery, effectively decoupling muscle cell proliferation from differentiation. CONCLUSIONS Our findings reveal a novel role for Nr2f6 as a molecular transducer that plays a crucial role in maintaining the balance between skeletal muscle contractile function and oxidative capacity. These results have significant implications for the development of potential therapeutic strategies for metabolic diseases and myopathies.
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Affiliation(s)
- Dimitrius Santiago P S F Guimarães
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Department of Structural and Functional Biology, University of Campinas, Campinas, Brazil
| | - Ninon M F Barrios
- Department of Structural and Functional Biology, University of Campinas, Campinas, Brazil
| | | | - David Rizo-Roca
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Maxence Jollet
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Jonathon A B Smith
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Thiago R Araujo
- Department of Structural and Functional Biology, University of Campinas, Campinas, Brazil
| | | | - Emilio Marconato
- Department of Structural and Functional Biology, University of Campinas, Campinas, Brazil
| | - Sandro M Hirabara
- Interdisciplinary Post-Graduate Program in Health Sciences, Cruzeiro do Sul University, São Paulo, Brazil
| | - André S Vieira
- Department of Structural and Functional Biology, University of Campinas, Campinas, Brazil
| | - Anna Krook
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Juleen R Zierath
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Leonardo R Silveira
- Department of Structural and Functional Biology, University of Campinas, Campinas, Brazil
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4
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Rachedi NS, Tang Y, Tai YY, Zhao J, Chauvet C, Grynblat J, Akoumia KKF, Estephan L, Torrino S, Sbai C, Ait-Mouffok A, Latoche JD, Al Aaraj Y, Brau F, Abélanet S, Clavel S, Zhang Y, Guillermier C, Kumar NVG, Tavakoli S, Mercier O, Risbano MG, Yao ZK, Yang G, Ouerfelli O, Lewis JS, Montani D, Humbert M, Steinhauser ML, Anderson CJ, Oldham WM, Perros F, Bertero T, Chan SY. Dietary intake and glutamine-serine metabolism control pathologic vascular stiffness. Cell Metab 2024:S1550-4131(24)00130-X. [PMID: 38701775 DOI: 10.1016/j.cmet.2024.04.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Revised: 02/15/2024] [Accepted: 04/12/2024] [Indexed: 05/05/2024]
Abstract
Perivascular collagen deposition by activated fibroblasts promotes vascular stiffening and drives cardiovascular diseases such as pulmonary hypertension (PH). Whether and how vascular fibroblasts rewire their metabolism to sustain collagen biosynthesis remains unknown. Here, we found that inflammation, hypoxia, and mechanical stress converge on activating the transcriptional coactivators YAP and TAZ (WWTR1) in pulmonary arterial adventitial fibroblasts (PAAFs). Consequently, YAP and TAZ drive glutamine and serine catabolism to sustain proline and glycine anabolism and promote collagen biosynthesis. Pharmacologic or dietary intervention on proline and glycine anabolic demand decreases vascular stiffening and improves cardiovascular function in PH rodent models. By identifying the limiting metabolic pathways for vascular collagen biosynthesis, our findings provide guidance for incorporating metabolic and dietary interventions for treating cardiopulmonary vascular disease.
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Affiliation(s)
- Nesrine S Rachedi
- Université Côte d'Azur, CNRS, INSERM, IPMC, IHU-RespirERA, Valbonne, France
| | - Ying Tang
- Center for Pulmonary Vascular Biology and Medicine, Pittsburgh Heart, Lung, and Blood Vascular Medicine Institute, Pittsburgh, PA, USA; Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA
| | - Yi-Yin Tai
- Center for Pulmonary Vascular Biology and Medicine, Pittsburgh Heart, Lung, and Blood Vascular Medicine Institute, Pittsburgh, PA, USA; Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA
| | - Jingsi Zhao
- Center for Pulmonary Vascular Biology and Medicine, Pittsburgh Heart, Lung, and Blood Vascular Medicine Institute, Pittsburgh, PA, USA; Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA
| | - Caroline Chauvet
- Université Côte d'Azur, CNRS, INSERM, IPMC, IHU-RespirERA, Valbonne, France
| | - Julien Grynblat
- Université Paris-Saclay, AP-HP, INSERM UMR_S 999, Service de Pneumologie et Soins Intensifs Respiratoires, Hôpital de Bicêtre, Le Kremlin Bicêtre, France; Pôle Thoracique, Vasculaire et Transplantations, Hôpital Marie Lannelongue, Le Plessis-Robinson, France
| | - Kouamé Kan Firmin Akoumia
- Université Paris-Saclay, AP-HP, INSERM UMR_S 999, Service de Pneumologie et Soins Intensifs Respiratoires, Hôpital de Bicêtre, Le Kremlin Bicêtre, France
| | - Leonard Estephan
- Center for Pulmonary Vascular Biology and Medicine, Pittsburgh Heart, Lung, and Blood Vascular Medicine Institute, Pittsburgh, PA, USA; Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA
| | - Stéphanie Torrino
- Université Côte d'Azur, CNRS, INSERM, IPMC, IHU-RespirERA, Valbonne, France
| | - Chaima Sbai
- Université Côte d'Azur, CNRS, INSERM, IPMC, IHU-RespirERA, Valbonne, France
| | - Amel Ait-Mouffok
- Université Côte d'Azur, CNRS, INSERM, IPMC, IHU-RespirERA, Valbonne, France
| | - Joseph D Latoche
- Hillman Cancer Center, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA
| | - Yassmin Al Aaraj
- Center for Pulmonary Vascular Biology and Medicine, Pittsburgh Heart, Lung, and Blood Vascular Medicine Institute, Pittsburgh, PA, USA; Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA
| | - Frederic Brau
- Université Côte d'Azur, CNRS, INSERM, IPMC, IHU-RespirERA, Valbonne, France
| | - Sophie Abélanet
- Université Côte d'Azur, CNRS, INSERM, IPMC, IHU-RespirERA, Valbonne, France
| | - Stephan Clavel
- Université Côte d'Azur, CNRS, INSERM, IPMC, IHU-RespirERA, Valbonne, France
| | - Yingze Zhang
- Center for Pulmonary Vascular Biology and Medicine, Pittsburgh Heart, Lung, and Blood Vascular Medicine Institute, Pittsburgh, PA, USA; Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA
| | - Christelle Guillermier
- Center for NanoImaging, Division of Genetics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Naveen V G Kumar
- Aging Institute, Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA
| | - Sina Tavakoli
- Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA; Department of Radiology, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA
| | - Olaf Mercier
- Université Paris-Saclay, AP-HP, INSERM UMR_S 999, Service de Pneumologie et Soins Intensifs Respiratoires, Hôpital de Bicêtre, Le Kremlin Bicêtre, France; Assistance PubliqueHôpitaux de Paris (AP-HP), Service de Pneumologie et Soins Intensifs Respiratoires, Centre de Référence de l'Hypertension Pulmonaire, Hôpital Bicêtre, 94270 Le Kremlin-Bicêtre, France
| | - Michael G Risbano
- Center for Pulmonary Vascular Biology and Medicine, Pittsburgh Heart, Lung, and Blood Vascular Medicine Institute, Pittsburgh, PA, USA; Division of Pulmonary and Critical Care Medicine, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA
| | - Zhong-Ke Yao
- Molecular Pharmacology and Chemistry Program and Organic Synthesis Core Facility, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Guangli Yang
- Molecular Pharmacology and Chemistry Program and Organic Synthesis Core Facility, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Ouathek Ouerfelli
- Molecular Pharmacology and Chemistry Program and Organic Synthesis Core Facility, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jason S Lewis
- Molecular Pharmacology and Chemistry Program and Organic Synthesis Core Facility, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - David Montani
- Pôle Thoracique, Vasculaire et Transplantations, Hôpital Marie Lannelongue, Le Plessis-Robinson, France; Assistance PubliqueHôpitaux de Paris (AP-HP), Service de Pneumologie et Soins Intensifs Respiratoires, Centre de Référence de l'Hypertension Pulmonaire, Hôpital Bicêtre, 94270 Le Kremlin-Bicêtre, France
| | - Marc Humbert
- Université Paris-Saclay, AP-HP, INSERM UMR_S 999, Service de Pneumologie et Soins Intensifs Respiratoires, Hôpital de Bicêtre, Le Kremlin Bicêtre, France; Assistance PubliqueHôpitaux de Paris (AP-HP), Service de Pneumologie et Soins Intensifs Respiratoires, Centre de Référence de l'Hypertension Pulmonaire, Hôpital Bicêtre, 94270 Le Kremlin-Bicêtre, France
| | - Matthew L Steinhauser
- Center for NanoImaging, Division of Genetics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Aging Institute, Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA
| | | | - William M Oldham
- Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Frédéric Perros
- Université Paris-Saclay, AP-HP, INSERM UMR_S 999, Service de Pneumologie et Soins Intensifs Respiratoires, Hôpital de Bicêtre, Le Kremlin Bicêtre, France; Laboratoire CarMeN, UMR INSERM U1060/INRA U1397, Université Claude Bernard Lyon1, 69310 Pierre-Bénite, France
| | - Thomas Bertero
- Université Côte d'Azur, CNRS, INSERM, IPMC, IHU-RespirERA, Valbonne, France.
| | - Stephen Y Chan
- Center for Pulmonary Vascular Biology and Medicine, Pittsburgh Heart, Lung, and Blood Vascular Medicine Institute, Pittsburgh, PA, USA; Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine and UPMC, Pittsburgh, PA, USA.
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5
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Fiorentino J, Armaos A, Colantoni A, Tartaglia G. Prediction of protein-RNA interactions from single-cell transcriptomic data. Nucleic Acids Res 2024; 52:e31. [PMID: 38364867 PMCID: PMC11014251 DOI: 10.1093/nar/gkae076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 01/12/2024] [Accepted: 01/26/2024] [Indexed: 02/18/2024] Open
Abstract
Proteins are crucial in regulating every aspect of RNA life, yet understanding their interactions with coding and noncoding RNAs remains limited. Experimental studies are typically restricted to a small number of cell lines and a limited set of RNA-binding proteins (RBPs). Although computational methods based on physico-chemical principles can predict protein-RNA interactions accurately, they often lack the ability to consider cell-type-specific gene expression and the broader context of gene regulatory networks (GRNs). Here, we assess the performance of several GRN inference algorithms in predicting protein-RNA interactions from single-cell transcriptomic data, and propose a pipeline, called scRAPID (single-cell transcriptomic-based RnA Protein Interaction Detection), that integrates these methods with the catRAPID algorithm, which can identify direct physical interactions between RBPs and RNA molecules. Our approach demonstrates that RBP-RNA interactions can be predicted from single-cell transcriptomic data, with performances comparable or superior to those achieved for the well-established task of inferring transcription factor-target interactions. The incorporation of catRAPID significantly enhances the accuracy of identifying interactions, particularly with long noncoding RNAs, and enables the identification of hub RBPs and RNAs. Additionally, we show that interactions between RBPs can be detected based on their inferred RNA targets. The software is freely available at https://github.com/tartaglialabIIT/scRAPID.
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Affiliation(s)
- Jonathan Fiorentino
- Center for Life Nano- and Neuro-Science, RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
| | - Alexandros Armaos
- Centre for Human Technologies (CHT), RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 16152 Genova, Italy
| | - Alessio Colantoni
- Center for Life Nano- and Neuro-Science, RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
- Department of Biology and Biotechnologies “Charles Darwin”, Sapienza University of Rome, 00185 Rome, Italy
| | - Gian Gaetano Tartaglia
- Center for Life Nano- and Neuro-Science, RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 00161 Rome, Italy
- Centre for Human Technologies (CHT), RNA Systems Biology Lab, Fondazione Istituto Italiano di Tecnologia (IIT), 16152 Genova, Italy
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6
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Esain-Garcia I, Kirchner A, Melidis L, Tavares RDCA, Dhir S, Simeone A, Yu Z, Madden SK, Hermann R, Tannahill D, Balasubramanian S. G-quadruplex DNA structure is a positive regulator of MYC transcription. Proc Natl Acad Sci U S A 2024; 121:e2320240121. [PMID: 38315865 PMCID: PMC10873556 DOI: 10.1073/pnas.2320240121] [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: 11/17/2023] [Accepted: 01/04/2024] [Indexed: 02/07/2024] Open
Abstract
DNA structure can regulate genome function. Four-stranded DNA G-quadruplex (G4) structures have been implicated in transcriptional regulation; however, previous studies have not directly addressed the role of an individual G4 within its endogenous cellular context. Using CRISPR to genetically abrogate endogenous G4 structure folding, we directly interrogate the G4 found within the upstream regulatory region of the critical human MYC oncogene. G4 loss leads to suppression of MYC transcription from the P1 promoter that is mediated by the deposition of a de novo nucleosome alongside alterations in RNA polymerase recruitment. We also show that replacement of the endogenous MYC G4 with a different G4 structure from the KRAS oncogene restores G4 folding and MYC transcription. Moreover, we demonstrate that the MYC G4 structure itself, rather than its sequence, recruits transcription factors and histone modifiers. Overall, our work establishes that G4 structures are important features of transcriptional regulation that coordinate recruitment of key chromatin proteins and the transcriptional machinery through interactions with DNA secondary structure, rather than primary sequence.
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Affiliation(s)
- Isabel Esain-Garcia
- Cancer Research UK Cambridge Institute, University of Cambridge, CambridgeCB2 0RE, United Kingdom
- Yusuf Hamied Department of Chemistry, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Angie Kirchner
- Cancer Research UK Cambridge Institute, University of Cambridge, CambridgeCB2 0RE, United Kingdom
- Yusuf Hamied Department of Chemistry, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Larry Melidis
- Cancer Research UK Cambridge Institute, University of Cambridge, CambridgeCB2 0RE, United Kingdom
- Yusuf Hamied Department of Chemistry, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | | | - Somdutta Dhir
- Cancer Research UK Cambridge Institute, University of Cambridge, CambridgeCB2 0RE, United Kingdom
- Yusuf Hamied Department of Chemistry, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Angela Simeone
- Cancer Research UK Cambridge Institute, University of Cambridge, CambridgeCB2 0RE, United Kingdom
- Yusuf Hamied Department of Chemistry, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Zutao Yu
- Yusuf Hamied Department of Chemistry, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Sarah K. Madden
- Yusuf Hamied Department of Chemistry, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - Regina Hermann
- Yusuf Hamied Department of Chemistry, University of Cambridge, CambridgeCB2 1EW, United Kingdom
| | - David Tannahill
- Cancer Research UK Cambridge Institute, University of Cambridge, CambridgeCB2 0RE, United Kingdom
| | - Shankar Balasubramanian
- Cancer Research UK Cambridge Institute, University of Cambridge, CambridgeCB2 0RE, United Kingdom
- Yusuf Hamied Department of Chemistry, University of Cambridge, CambridgeCB2 1EW, United Kingdom
- School of Clinical Medicine, University of Cambridge, CambridgeCB2 0SP, United Kingdom
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7
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Rogers BB, Anderson AG, Lauzon SN, Davis MN, Hauser RM, Roberts SC, Rodriguez-Nunez I, Trausch-Lowther K, Barinaga EA, Hall PI, Knuesel MT, Taylor JW, Mackiewicz M, Roberts BS, Cooper SJ, Rizzardi LF, Myers RM, Cochran JN. Neuronal MAPT expression is mediated by long-range interactions with cis-regulatory elements. Am J Hum Genet 2024; 111:259-279. [PMID: 38232730 PMCID: PMC10870142 DOI: 10.1016/j.ajhg.2023.12.015] [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: 11/28/2023] [Revised: 12/12/2023] [Accepted: 12/12/2023] [Indexed: 01/19/2024] Open
Abstract
Tauopathies are a group of neurodegenerative diseases defined by abnormal aggregates of tau, a microtubule-associated protein encoded by MAPT. MAPT expression is near absent in neural progenitor cells (NPCs) and increases during differentiation. This temporally dynamic expression pattern suggests that MAPT expression could be controlled by transcription factors and cis-regulatory elements specific to differentiated cell types. Given the relevance of MAPT expression to neurodegeneration pathogenesis, identification of such elements is relevant to understanding disease risk and pathogenesis. Here, we performed chromatin conformation assays (HiC & Capture-C), single-nucleus multiomics (RNA-seq+ATAC-seq), bulk ATAC-seq, and ChIP-seq for H3K27ac and CTCF in NPCs and differentiated neurons to nominate candidate cis-regulatory elements (cCREs). We assayed these cCREs using luciferase assays and CRISPR interference (CRISPRi) experiments to measure their effects on MAPT expression. Finally, we integrated cCRE annotations into an analysis of genetic variation in neurodegeneration-affected individuals and control subjects. We identified both proximal and distal regulatory elements for MAPT and confirmed the regulatory function for several regions, including three regions centromeric to MAPT beyond the H1/H2 haplotype inversion breakpoint. We also found that rare and predicted damaging genetic variation in nominated CREs was nominally depleted in dementia-affected individuals relative to control subjects, consistent with the hypothesis that variants that disrupt MAPT enhancer activity, and thereby reduced MAPT expression, may be protective against neurodegenerative disease. Overall, this study provides compelling evidence for pursuing detailed knowledge of CREs for genes of interest to permit better understanding of disease risk.
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Affiliation(s)
- Brianne B Rogers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA; University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | | | - Shelby N Lauzon
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - M Natalie Davis
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Rebecca M Hauser
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Sydney C Roberts
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | | | | | - Erin A Barinaga
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Paige I Hall
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | | | - Jared W Taylor
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Mark Mackiewicz
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Brian S Roberts
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | - Sara J Cooper
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA
| | | | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL 35806, USA.
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8
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Willemin A, Szabó D, Pombo A. Epigenetic regulatory layers in the 3D nucleus. Mol Cell 2024; 84:415-428. [PMID: 38242127 PMCID: PMC10872226 DOI: 10.1016/j.molcel.2023.12.032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 11/21/2023] [Accepted: 12/15/2023] [Indexed: 01/21/2024]
Abstract
Nearly 7 decades have elapsed since Francis Crick introduced the central dogma of molecular biology, as part of his ideas on protein synthesis, setting the fundamental rules of sequence information transfer from DNA to RNAs and proteins. We have since learned that gene expression is finely tuned in time and space, due to the activities of RNAs and proteins on regulatory DNA elements, and through cell-type-specific three-dimensional conformations of the genome. Here, we review major advances in genome biology and discuss a set of ideas on gene regulation and highlight how various biomolecular assemblies lead to the formation of structural and regulatory features within the nucleus, with roles in transcriptional control. We conclude by suggesting further developments that will help capture the complex, dynamic, and often spatially restricted events that govern gene expression in mammalian cells.
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Affiliation(s)
- Andréa Willemin
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Epigenetic Regulation and Chromatin Architecture Group, Berlin, Germany; Humboldt-Universität zu Berlin, Institute for Biology, Berlin, Germany.
| | - Dominik Szabó
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Epigenetic Regulation and Chromatin Architecture Group, Berlin, Germany; Humboldt-Universität zu Berlin, Institute for Biology, Berlin, Germany
| | - Ana Pombo
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin Institute for Medical Systems Biology (BIMSB), Epigenetic Regulation and Chromatin Architecture Group, Berlin, Germany; Humboldt-Universität zu Berlin, Institute for Biology, Berlin, Germany.
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9
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Kudron M, Gevirtzman L, Victorsen A, Lear BC, Gao J, Xu J, Samanta S, Frink E, Tran-Pearson A, Huynh C, Vafeados D, Hammonds A, Fisher W, Wall M, Wesseling G, Hernandez V, Lin Z, Kasparian M, White K, Allada R, Gerstein M, Hillier L, Celniker SE, Reinke V, Waterston RH. Binding profiles for 954 Drosophila and C. elegans transcription factors reveal tissue specific regulatory relationships. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.18.576242. [PMID: 38293065 PMCID: PMC10827215 DOI: 10.1101/2024.01.18.576242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2024]
Abstract
A catalog of transcription factor (TF) binding sites in the genome is critical for deciphering regulatory relationships. Here we present the culmination of the modERN (model organism Encyclopedia of Regulatory Networks) consortium that systematically assayed TF binding events in vivo in two major model organisms, Drosophila melanogaster (fly) and Caenorhabditis elegans (worm). We describe key features of these datasets, comprising 604 TFs identifying 3.6M sites in the fly and 350 TFs identifying 0.9 M sites in the worm. Applying a machine learning model to these data identifies sets of TFs with a prominent role in promoting target gene expression in specific cell types. TF binding data are available through the ENCODE Data Coordinating Center and at https://epic.gs.washington.edu/modERNresource, which provides access to processed and summary data, as well as widgets to probe cell type-specific TF-target relationships. These data are a rich resource that should fuel investigations into TF function during development.
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Affiliation(s)
- Michelle Kudron
- Department of Genetics, Yale University, New Haven, Connecticut 06520
| | - Louis Gevirtzman
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195
| | - Alec Victorsen
- Department of Laboratory Medicine & Pathology, University of Minnesota, Minneapolis, MN 55455
| | - Bridget C. Lear
- Department of Neurobiology, Northwestern University, Evanston IL 60208
| | - Jiahao Gao
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520
| | - Jinrui Xu
- Department of Biology, Howard University, Washington, District of Columbia 20059, USA
- Center for Applied Data Science and Analytics, Howard University, Washington, District of Columbia 20059, USA
| | - Swapna Samanta
- Department of Genetics, Yale University, New Haven, Connecticut 06520
| | - Emily Frink
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195
| | - Adri Tran-Pearson
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195
| | - Chau Huynh
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195
| | - Dionne Vafeados
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195
| | - Ann Hammonds
- Division of Biological Systems and Engineering, Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - William Fisher
- Division of Biological Systems and Engineering, Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - Martha Wall
- Institute for Genomics and Systems Biology, Department of Human Genetics, University of Chicago, Illinois 60637
| | - Greg Wesseling
- Department of Neurobiology, Northwestern University, Evanston IL 60208
| | - Vanessa Hernandez
- Department of Neurobiology, Northwestern University, Evanston IL 60208
| | - Zhichun Lin
- Department of Neurobiology, Northwestern University, Evanston IL 60208
| | - Mary Kasparian
- Department of Neurobiology, Northwestern University, Evanston IL 60208
| | - Kevin White
- Department of Biochemistry and Precision Medicine Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117597
| | - Ravi Allada
- Department of Neurobiology, Northwestern University, Evanston IL 60208
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06520
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, Connecticut 06520
- Department of Statistics and Data Science, Yale University, New Haven, Connecticut 06520, USA
| | - LaDeana Hillier
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195
| | - Susan E. Celniker
- Division of Biological Systems and Engineering, Lawrence Berkeley National Laboratory, Berkeley, California 94720
| | - Valerie Reinke
- Department of Genetics, Yale University, New Haven, Connecticut 06520
| | - Robert H. Waterston
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, Washington 98195
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10
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Loell KJ, Friedman RZ, Myers CA, Corbo JC, Cohen BA, White MA. Transcription factor interactions explain the context-dependent activity of CRX binding sites. PLoS Comput Biol 2024; 20:e1011802. [PMID: 38227575 PMCID: PMC10817189 DOI: 10.1371/journal.pcbi.1011802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 01/26/2024] [Accepted: 01/06/2024] [Indexed: 01/18/2024] Open
Abstract
The effects of transcription factor binding sites (TFBSs) on the activity of a cis-regulatory element (CRE) depend on the local sequence context. In rod photoreceptors, binding sites for the transcription factor (TF) Cone-rod homeobox (CRX) occur in both enhancers and silencers, but the sequence context that determines whether CRX binding sites contribute to activation or repression of transcription is not understood. To investigate the context-dependent activity of CRX sites, we fit neural network-based models to the activities of synthetic CREs composed of photoreceptor TFBSs. The models revealed that CRX binding sites consistently make positive, independent contributions to CRE activity, while negative homotypic interactions between sites cause CREs composed of multiple CRX sites to function as silencers. The effects of negative homotypic interactions can be overcome by the presence of other TFBSs that either interact cooperatively with CRX sites or make independent positive contributions to activity. The context-dependent activity of CRX sites is thus determined by the balance between positive heterotypic interactions, independent contributions of TFBSs, and negative homotypic interactions. Our findings explain observed patterns of activity among genomic CRX-bound enhancers and silencers, and suggest that enhancers may require diverse TFBSs to overcome negative homotypic interactions between TFBSs.
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Affiliation(s)
- Kaiser J. Loell
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States of America
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States of America
| | - Ryan Z. Friedman
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States of America
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States of America
| | - Connie A. Myers
- Department of Pathology and Immunology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States of America
| | - Joseph C. Corbo
- Department of Pathology and Immunology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States of America
| | - Barak A. Cohen
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States of America
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States of America
| | - Michael A. White
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States of America
- The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, Missouri, United States of America
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11
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Perez AA, Goronzy IN, Blanco MR, Guo JK, Guttman M. ChIP-DIP: A multiplexed method for mapping hundreds of proteins to DNA uncovers diverse regulatory elements controlling gene expression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.14.571730. [PMID: 38187704 PMCID: PMC10769186 DOI: 10.1101/2023.12.14.571730] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Gene expression is controlled by the dynamic localization of thousands of distinct regulatory proteins to precise regions of DNA. Understanding this cell-type specific process has been a goal of molecular biology for decades yet remains challenging because most current DNA-protein mapping methods study one protein at a time. To overcome this, we developed ChIP-DIP (ChIP Done In Parallel), a split-pool based method that enables simultaneous, genome-wide mapping of hundreds of diverse regulatory proteins in a single experiment. We demonstrate that ChIP-DIP generates highly accurate maps for all classes of DNA-associated proteins, including histone modifications, chromatin regulators, transcription factors, and RNA Polymerases. Using these data, we explore quantitative combinations of protein localization on genomic DNA to define distinct classes of regulatory elements and their functional activity. Our data demonstrate that ChIP-DIP enables the generation of 'consortium level', context-specific protein localization maps within any molecular biology lab.
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12
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Hudaiberdiev S, Ovcharenko I. Sequence characteristics and an accurate model of abundant hyperactive loci in the human genome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.05.527203. [PMID: 36945558 PMCID: PMC10028745 DOI: 10.1101/2023.02.05.527203] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Enhancers and promoters are classically considered to be bound by a small set of TFs in a sequence-specific manner. This assumption has come under increasing skepticism as the datasets of ChIP-seq assays of TFs have expanded. In particular, high-occupancy target (HOT) loci attract hundreds of TFs with seemingly no detectable correlation between ChIP-seq peaks and DNA-binding motif presence. Here, we used a set of 1,003 TF ChIP-seq datasets (HepG2, K562, H1) to analyze the patterns of ChIP-seq peak co-occurrence in combination with functional genomics datasets. We identified 43,891 HOT loci forming at the promoter (53%) and enhancer (47%) regions. HOT promoters regulate housekeeping genes, whereas HOT enhancers are involved in tissue-specific process regulation. HOT loci form the foundation of human super-enhancers and evolve under strong negative selection, with some of these loci being located in ultraconserved regions. Sequence-based classification analysis of HOT loci suggested that their formation is driven by the sequence features, and the density of mapped ChIP-seq peaks across TF-bound loci correlates with sequence features and the expression level of flanking genes. Based on the affinities to bind to promoters and enhancers we detected 5 distinct clusters of TFs that form the core of the HOT loci. We report an abundance of HOT loci in the human genome and a commitment of 51% of all TF ChIP-seq binding events to HOT locus formation thus challenging the classical model of enhancer activity and propose a model of HOT locus formation based on the existence of large transcriptional condensates.
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Affiliation(s)
- Sanjarbek Hudaiberdiev
- National Institute for Biotechnology and Information, National Library of Medicine, National Institutes of Health. Bethesda, MD
| | - Ivan Ovcharenko
- National Institute for Biotechnology and Information, National Library of Medicine, National Institutes of Health. Bethesda, MD
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13
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Ozenberger BB, Li L, Wilson ER, Lazar AJ, Barrott JJ, Jones KB. EWSR1::ATF1 Orchestrates the Clear Cell Sarcoma Transcriptome in Human Tumors and a Mouse Genetic Model. Cancers (Basel) 2023; 15:5750. [PMID: 38136296 PMCID: PMC10742207 DOI: 10.3390/cancers15245750] [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: 11/01/2023] [Revised: 12/03/2023] [Accepted: 12/04/2023] [Indexed: 12/24/2023] Open
Abstract
Clear cell sarcoma (CCS) is a rare, aggressive malignancy that most frequently arises in the soft tissues of the extremities. It is defined and driven by expression of one member of a family of related translocation-generated fusion oncogenes, the most common of which is EWSR1::ATF1. The EWSR1::ATF1 fusion oncoprotein reprograms transcription. However, the binding distribution of EWSR1::ATF1 across the genome and its target genes remain unclear. Here, we interrogated the genomic distribution of V5-tagged EWSR1::ATF1 in tumors it had induced upon expression in mice that also recapitulated the transcriptome of human CCS. ChIP-sequencing of V5-EWSR1::ATF1 identified previously unreported motifs including the AP1 motif and motif comprised of TGA repeats that resemble GGAA-repeating microsatellites bound by EWSR1::FLI1 in Ewing sarcoma. ChIP-sequencing of H3K27ac identified super enhancers in the mouse model and human contexts of CCS, which showed a shared super enhancer structure that associates with activated genes.
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Affiliation(s)
- Benjamin B. Ozenberger
- Department of Oncological Sciences, University of Utah School of Medicine, Salt Lake City, UT 84132, USA; (B.B.O.); (L.L.); (E.R.W.)
- Department of Orthopaedics, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - Li Li
- Department of Oncological Sciences, University of Utah School of Medicine, Salt Lake City, UT 84132, USA; (B.B.O.); (L.L.); (E.R.W.)
- Department of Orthopaedics, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - Emily R. Wilson
- Department of Oncological Sciences, University of Utah School of Medicine, Salt Lake City, UT 84132, USA; (B.B.O.); (L.L.); (E.R.W.)
| | - Alexander J. Lazar
- Department of Pathology, Genomic Medicine and Dermatology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA;
| | - Jared J. Barrott
- Department of Biology, Brigham Young University, Provo, UT 84602, USA;
| | - Kevin B. Jones
- Department of Oncological Sciences, University of Utah School of Medicine, Salt Lake City, UT 84132, USA; (B.B.O.); (L.L.); (E.R.W.)
- Department of Orthopaedics, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
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14
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Owen DJ, Aguilar-Martinez E, Ji Z, Li Y, Sharrocks AD. ZMYM2 controls human transposable element transcription through distinct co-regulatory complexes. eLife 2023; 12:RP86669. [PMID: 37934570 PMCID: PMC10629813 DOI: 10.7554/elife.86669] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2023] Open
Abstract
ZMYM2 is a zinc finger transcriptional regulator that plays a key role in promoting and maintaining cell identity. It has been implicated in several diseases such as congenital anomalies of the kidney where its activity is diminished and cancer where it participates in oncogenic fusion protein events. ZMYM2 is thought to function through promoting transcriptional repression and here we provide more evidence to support this designation. Here we studied ZMYM2 function in human cells and demonstrate that ZMYM2 is part of distinct chromatin-bound complexes including the established LSD1-CoREST-HDAC1 corepressor complex. We also identify new functional and physical interactions with ADNP and TRIM28/KAP1. The ZMYM2-TRIM28 complex forms in a SUMO-dependent manner and is associated with repressive chromatin. ZMYM2 and TRIM28 show strong functional similarity and co-regulate a large number of genes. However, there are no strong links between ZMYM2-TRIM28 binding events and nearby individual gene regulation. Instead, ZMYM2-TRIM28 appears to regulate genes in a more regionally defined manner within TADs where it can directly regulate co-associated retrotransposon expression. We find that different types of ZMYM2 binding complex associate with and regulate distinct subclasses of retrotransposons, with ZMYM2-ADNP complexes at SINEs and ZMYM2-TRIM28 complexes at LTR elements. We propose a model whereby ZMYM2 acts directly through retrotransposon regulation, which may then potentially affect the local chromatin environment and associated coding gene expression.
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Affiliation(s)
- Danielle J Owen
- Faculty of Biology, Medicine and Health, University of Manchester, Michael Smith Building, Oxford RoadManchesterUnited Kingdom
| | - Elisa Aguilar-Martinez
- Faculty of Biology, Medicine and Health, University of Manchester, Michael Smith Building, Oxford RoadManchesterUnited Kingdom
| | - Zongling Ji
- Faculty of Biology, Medicine and Health, University of Manchester, Michael Smith Building, Oxford RoadManchesterUnited Kingdom
| | - Yaoyong Li
- Faculty of Biology, Medicine and Health, University of Manchester, Michael Smith Building, Oxford RoadManchesterUnited Kingdom
| | - Andrew D Sharrocks
- Faculty of Biology, Medicine and Health, University of Manchester, Michael Smith Building, Oxford RoadManchesterUnited Kingdom
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15
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Moyers BA, Partridge EC, Mackiewicz M, Betti MJ, Darji R, Meadows SK, Newberry KM, Brandsmeier LA, Wold BJ, Mendenhall EM, Myers RM. Characterization of human transcription factor function and patterns of gene regulation in HepG2 cells. Genome Res 2023; 33:gr.278205.123. [PMID: 37852782 PMCID: PMC10760452 DOI: 10.1101/gr.278205.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 10/13/2023] [Indexed: 10/20/2023]
Abstract
Transcription factors (TFs) are trans-acting proteins that bind cis-regulatory elements (CREs) in DNA to control gene expression. Here, we analyzed the genomic localization profiles of 529 sequence-specific TFs and 151 cofactors and chromatin regulators in the human cancer cell line HepG2, for a total of 680 broadly termed DNA-associated proteins (DAPs). We used this deep collection to model each TF's impact on gene expression, and identified a cohort of 26 candidate transcriptional repressors. We examine high occupancy target (HOT) sites in the context of three-dimensional genome organization and show biased motif placement in distal-promoter connections involving HOT sites. We also found a substantial number of closed chromatin regions with multiple DAPs bound, and explored their properties, finding that a MAFF/MAFK TF pair correlates with transcriptional repression. Altogether, these analyses provide novel insights into the regulatory logic of the human cell line HepG2 genome and show the usefulness of large genomic analyses for elucidation of individual TF functions.
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Affiliation(s)
- Belle A Moyers
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
| | | | - Mark Mackiewicz
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
| | - Michael J Betti
- Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
| | - Roshan Darji
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
| | - Sarah K Meadows
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA
| | | | | | - Barbara J Wold
- Merkin Institute for Translational Research, California Institute of Technology, Pasadena, California 91125, USA
| | - Eric M Mendenhall
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA;
| | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806, USA;
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16
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Torres HM, Yeo D, Westendorf JJ. Pulling rank with RNA: RANKL promotes the association of PGC-1β/RNA complexes with NCoR/HDAC3 to activate gene expression in osteoclasts. Mol Cell 2023; 83:3397-3399. [PMID: 37802020 PMCID: PMC10835765 DOI: 10.1016/j.molcel.2023.09.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 09/12/2023] [Accepted: 09/12/2023] [Indexed: 10/08/2023]
Abstract
In this issue, Abe et al1 report a novel mechanism by which RANKL stimulates osteoclast differentiation and bone resorption through non-coding RNAs that bind PGC-1β and convert the NCoR/HDAC3 co-repressor complex into a co-activator of AP-1- and NFκB-regulated genes.
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Affiliation(s)
- Haydee M Torres
- Departments of Orthopedic Surgery and Biochemistry and Molecular Biology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Dongwook Yeo
- Departments of Orthopedic Surgery and Biochemistry and Molecular Biology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA
| | - Jennifer J Westendorf
- Departments of Orthopedic Surgery and Biochemistry and Molecular Biology, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA.
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17
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Örd T, Örd D, Adler P, Örd T. Genome-wide census of ATF4 binding sites and functional profiling of trait-associated genetic variants overlapping ATF4 binding motifs. PLoS Genet 2023; 19:e1011014. [PMID: 37906604 PMCID: PMC10637723 DOI: 10.1371/journal.pgen.1011014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 11/10/2023] [Accepted: 10/11/2023] [Indexed: 11/02/2023] Open
Abstract
Activating Transcription Factor 4 (ATF4) is an important regulator of gene expression in stress responses and developmental processes in many cell types. Here, we catalogued ATF4 binding sites in the human genome and identified overlaps with trait-associated genetic variants. We probed these genetic variants for allelic regulatory activity using a massively parallel reporter assay (MPRA) in HepG2 hepatoma cells exposed to tunicamycin to induce endoplasmic reticulum stress and ATF4 upregulation. The results revealed that in the majority of cases, the MPRA allelic activity of these SNPs was in agreement with the nucleotide preference seen in the ATF4 binding motif from ChIP-Seq. Luciferase and electrophoretic mobility shift assays in additional cellular models further confirmed ATF4-dependent regulatory effects for the SNPs rs532446 (GADD45A intronic; linked to hematological parameters), rs7011846 (LPL upstream; myocardial infarction), rs2718215 (diastolic blood pressure), rs281758 (psychiatric disorders) and rs6491544 (educational attainment). CRISPR-Cas9 disruption and/or deletion of the regulatory elements harboring rs532446 and rs7011846 led to the downregulation of GADD45A and LPL, respectively. Thus, these SNPs could represent examples of GWAS genetic variants that affect gene expression by altering ATF4-mediated transcriptional activation.
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Affiliation(s)
- Tiit Örd
- Institute of Genomics, University of Tartu, Tartu, Estonia
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Daima Örd
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Priit Adler
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Tõnis Örd
- Institute of Genomics, University of Tartu, Tartu, Estonia
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18
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Zhu I, Landsman D. Clustered and diverse transcription factor binding underlies cell type specificity of enhancers for housekeeping genes. Genome Res 2023; 33:1662-1672. [PMID: 37884340 PMCID: PMC10691539 DOI: 10.1101/gr.278130.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 09/12/2023] [Indexed: 10/28/2023]
Abstract
Housekeeping genes are considered to be regulated by common enhancers across different tissues. Here we report that most of the commonly expressed mouse or human genes across different cell types, including more than half of the previously identified housekeeping genes, are associated with cell type-specific enhancers. Furthermore, the binding of most transcription factors (TFs) is cell type-specific. We reason that these cell type specificities are causally related to the collective TF recruitment at regulatory sites, as TFs tend to bind to regions associated with many other TFs and each cell type has a unique repertoire of expressed TFs. Based on binding profiles of hundreds of TFs from HepG2, K562, and GM12878 cells, we show that 80% of all TF peaks overlapping H3K27ac signals are in the top 20,000-23,000 most TF-enriched H3K27ac peak regions, and approximately 12,000-15,000 of these peaks are enhancers (nonpromoters). Those enhancers are mainly cell type-specific and include those linked to the majority of commonly expressed genes. Moreover, we show that the top 15,000 most TF-enriched regulatory sites in HepG2 cells, associated with about 200 TFs, can be predicted largely from the binding profile of as few as 30 TFs. Through motif analysis, we show that major enhancers harbor diverse and clustered motifs from a combination of available TFs uniquely present in each cell type. We propose a mechanism that explains how the highly focused TF binding at regulatory sites results in cell type specificity of enhancers for housekeeping and commonly expressed genes.
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Affiliation(s)
- Iris Zhu
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
| | - David Landsman
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland 20894, USA
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19
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Ryu J, Barkal S, Yu T, Jankowiak M, Zhou Y, Francoeur M, Phan QV, Li Z, Tognon M, Brown L, Love MI, Lettre G, Ascher DB, Cassa CA, Sherwood RI, Pinello L. Joint genotypic and phenotypic outcome modeling improves base editing variant effect quantification. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.08.23295253. [PMID: 37732177 PMCID: PMC10508837 DOI: 10.1101/2023.09.08.23295253] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
CRISPR base editing screens are powerful tools for studying disease-associated variants at scale. However, the efficiency and precision of base editing perturbations vary, confounding the assessment of variant-induced phenotypic effects. Here, we provide an integrated pipeline that improves the estimation of variant impact in base editing screens. We perform high-throughput ABE8e-SpRY base editing screens with an integrated reporter construct to measure the editing efficiency and outcomes of each gRNA alongside their phenotypic consequences. We introduce BEAN, a Bayesian network that accounts for per-guide editing outcomes and target site chromatin accessibility to estimate variant impacts. We show this pipeline attains superior performance compared to existing tools in variant classification and effect size quantification. We use BEAN to pinpoint common variants that alter LDL uptake, implicating novel genes. Additionally, through saturation base editing of LDLR, we enable accurate quantitative prediction of the effects of missense variants on LDL-C levels, which aligns with measurements in UK Biobank individuals, and identify structural mechanisms underlying variant pathogenicity. This work provides a widely applicable approach to improve the power of base editor screens for disease-associated variant characterization.
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Affiliation(s)
- Jayoung Ryu
- Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Sam Barkal
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Tian Yu
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Yunzhuo Zhou
- School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Matthew Francoeur
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Quang Vinh Phan
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Zhijian Li
- Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Manuel Tognon
- Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Computer Science Department, University of Verona, Verona, Italy
| | - Lara Brown
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Michael I. Love
- Department of Genetics, Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Guillaume Lettre
- Montreal Heart Institute, Montréal, QC H1T 1C8, Canada
- Faculté de Médecine, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - David B. Ascher
- School of Chemistry and Molecular Biosciences, The University of Queensland, Brisbane, Australia
- Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Christopher A. Cassa
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Richard I. Sherwood
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Luca Pinello
- Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Pathology, Harvard Medical School, Boston, MA, USA
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20
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Pop RT, Pisante A, Nagy D, Martin PCN, Mikheeva L, Hayat A, Ficz G, Zabet NR. Identification of mammalian transcription factors that bind to inaccessible chromatin. Nucleic Acids Res 2023; 51:8480-8495. [PMID: 37486787 PMCID: PMC10484684 DOI: 10.1093/nar/gkad614] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 07/11/2023] [Indexed: 07/26/2023] Open
Abstract
Transcription factors (TFs) are proteins that affect gene expression by binding to regulatory regions of DNA in a sequence specific manner. The binding of TFs to DNA is controlled by many factors, including the DNA sequence, concentration of TF, chromatin accessibility and co-factors. Here, we systematically investigated the binding mechanism of hundreds of TFs by analysing ChIP-seq data with our explainable statistical model, ChIPanalyser. This tool uses as inputs the DNA sequence binding motif; the capacity to distinguish between strong and weak binding sites; the concentration of TF; and chromatin accessibility. We found that approximately one third of TFs are predicted to bind the genome in a DNA accessibility independent fashion, which includes TFs that can open the chromatin, their co-factors and TFs with similar motifs. Our model predicted this to be the case when the TF binds to its strongest binding regions in the genome, and only a small number of TFs have the capacity to bind dense chromatin at their weakest binding regions, such as CTCF, USF2 and CEBPB. Our study demonstrated that the binding of hundreds of human and mouse TFs is predicted by ChIPanalyser with high accuracy and showed that many TFs can bind dense chromatin.
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Affiliation(s)
- Romana T Pop
- School of Life Sciences, University of Essex, Colchester CO4 3SQ, UK
- Centre for Molecular Medicine Norway (NCMM), Nordic EMBL Partnership, University of Oslo, Oslo, Norway
| | - Alessandra Pisante
- School of Life Sciences, University of Essex, Colchester CO4 3SQ, UK
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
| | - Dorka Nagy
- School of Life Sciences, University of Essex, Colchester CO4 3SQ, UK
- National Heart and Lung Institute, Imperial College London, London SW3 6LY, UK
| | | | | | - Ateequllah Hayat
- Institute of Medical and Biomedical Education, St George's, University of London, Cranmer Terrace, Tooting SW17 0RE, London
| | - Gabriella Ficz
- Centre for Haemato-Oncology, Barts Cancer Institute, Queen Mary University of London, London EC1M 6BQ, UK
| | - Nicolae Radu Zabet
- School of Life Sciences, University of Essex, Colchester CO4 3SQ, UK
- Blizard Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London E1 2AT, UK
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21
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Choudalakis M, Kungulovski G, Mauser R, Bashtrykov P, Jeltsch A. Refined read-out: The hUHRF1 Tandem-Tudor domain prefers binding to histone H3 tails containing K4me1 in the context of H3K9me2/3. Protein Sci 2023; 32:e4760. [PMID: 37593997 PMCID: PMC10464304 DOI: 10.1002/pro.4760] [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: 07/13/2023] [Revised: 08/11/2023] [Accepted: 08/13/2023] [Indexed: 08/19/2023]
Abstract
UHRF1 is an essential chromatin protein required for DNA methylation maintenance, mammalian development, and gene regulation. We investigated the Tandem-Tudor domain (TTD) of human UHRF1 that is known to bind H3K9me2/3 histones and is a major driver of UHRF1 localization in cells. We verified binding to H3K9me2/3 but unexpectedly discovered stronger binding to H3 peptides and mononucleosomes containing K9me2/3 with additional K4me1. We investigated the combined binding of TTD to H3K4me1-K9me2/3 versus H3K9me2/3 alone, engineered mutants with specific and differential changes of binding, and discovered a novel read-out mechanism for H3K4me1 in an H3K9me2/3 context that is based on the interaction of R207 with the H3K4me1 methyl group and on counting the H-bond capacity of H3K4. Individual TTD mutants showed up to a 10,000-fold preference for the double-modified peptides, suggesting that after a conformational change, WT TTD could exhibit similar effects. The frequent appearance of H3K4me1-K9me2 regions in human chromatin demonstrated in our TTD chromatin pull-down and ChIP-western blot data suggests that it has specific biological roles. Chromatin pull-down of TTD from HepG2 cells and full-length murine UHRF1 ChIP-seq data correlate with H3K4me1 profiles indicating that the H3K4me1-K9me2/3 interaction of TTD influences chromatin binding of full-length UHRF1. We demonstrate the H3K4me1-K9me2/3 specific binding of UHRF1-TTD to enhancers and promoters of cell-type-specific genes at the flanks of cell-type-specific transcription factor binding sites, and provided evidence supporting an H3K4me1-K9me2/3 dependent and TTD mediated downregulation of these genes by UHRF1. All these findings illustrate the important physiological function of UHRF1-TTD binding to H3K4me1-K9me2/3 double marks in a cellular context.
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Affiliation(s)
- Michel Choudalakis
- Department of BiochemistryInstitute of Biochemistry and Technical Biochemistry, University of StuttgartStuttgartGermany
| | - Goran Kungulovski
- Department of BiochemistryInstitute of Biochemistry and Technical Biochemistry, University of StuttgartStuttgartGermany
| | - Rebekka Mauser
- Department of BiochemistryInstitute of Biochemistry and Technical Biochemistry, University of StuttgartStuttgartGermany
| | - Pavel Bashtrykov
- Department of BiochemistryInstitute of Biochemistry and Technical Biochemistry, University of StuttgartStuttgartGermany
| | - Albert Jeltsch
- Department of BiochemistryInstitute of Biochemistry and Technical Biochemistry, University of StuttgartStuttgartGermany
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22
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de Tribolet-Hardy J, Thorball CW, Forey R, Planet E, Duc J, Coudray A, Khubieh B, Offner S, Pulver C, Fellay J, Imbeault M, Turelli P, Trono D. Genetic features and genomic targets of human KRAB-zinc finger proteins. Genome Res 2023; 33:1409-1423. [PMID: 37730438 PMCID: PMC10547255 DOI: 10.1101/gr.277722.123] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 07/18/2023] [Indexed: 09/22/2023]
Abstract
Krüppel-associated box (KRAB) domain-containing zinc finger proteins (KZFPs) are one of the largest groups of transcription factors encoded by tetrapods, with 378 members in human alone. KZFP genes are often grouped in clusters reflecting amplification by gene and segment duplication since the gene family first emerged more than 400 million years ago. Previous work has revealed that many KZFPs recognize transposable element (TE)-embedded sequences as genomic targets, and that KZFPs facilitate the co-option of the regulatory potential of TEs for the benefit of the host. Here, we present a comprehensive survey of the genetic features and genomic targets of human KZFPs, notably completing past analyses by adding data on close to a hundred family members. General principles emerge from our study of the TE-KZFP regulatory system, which point to multipronged evolutionary mechanisms underlaid by highly complex and combinatorial modes of action with strong influences on human speciation.
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Affiliation(s)
- Jonas de Tribolet-Hardy
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Christian W Thorball
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Romain Forey
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Evarist Planet
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Julien Duc
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Alexandre Coudray
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Bara Khubieh
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Sandra Offner
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Cyril Pulver
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Jacques Fellay
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
- Precision Medicine Unit, Lausanne University Hospital (CHUV) and University of Lausanne, 1010 Lausanne, Switzerland
| | - Michael Imbeault
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Priscilla Turelli
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Didier Trono
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland;
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23
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Zheng Y, Jun J, Brennan K, Gevaert O. EpiMix is an integrative tool for epigenomic subtyping using DNA methylation. CELL REPORTS METHODS 2023; 3:100515. [PMID: 37533639 PMCID: PMC10391348 DOI: 10.1016/j.crmeth.2023.100515] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 04/12/2023] [Accepted: 06/01/2023] [Indexed: 08/04/2023]
Abstract
DNA methylation (DNAme) is a major epigenetic factor influencing gene expression with alterations leading to cancer and immunological and cardiovascular diseases. Recent technological advances have enabled genome-wide profiling of DNAme in large human cohorts. There is a need for analytical methods that can more sensitively detect differential methylation profiles present in subsets of individuals from these heterogeneous, population-level datasets. We developed an end-to-end analytical framework named "EpiMix" for population-level analysis of DNAme and gene expression. Compared with existing methods, EpiMix showed higher sensitivity in detecting abnormal DNAme that was present in only small patient subsets. We extended the model-based analyses of EpiMix to cis-regulatory elements within protein-coding genes, distal enhancers, and genes encoding microRNAs and long non-coding RNAs (lncRNAs). Using cell-type-specific data from two separate studies, we discover epigenetic mechanisms underlying childhood food allergy and survival-associated, methylation-driven ncRNAs in non-small cell lung cancer.
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Affiliation(s)
- Yuanning Zheng
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - John Jun
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Kevin Brennan
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Olivier Gevaert
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
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24
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DeForest N, Kavitha B, Hu S, Isaac R, Krohn L, Wang M, Du X, De Arruda Saldanha C, Gylys J, Merli E, Abagyan R, Najmi L, Mohan V, Flannick J, Peloso GM, Gordts PL, Heinz S, Deaton AM, Khera AV, Olefsky J, Radha V, Majithia AR. Human gain-of-function variants in HNF1A confer protection from diabetes but independently increase hepatic secretion of atherogenic lipoproteins. CELL GENOMICS 2023; 3:100339. [PMID: 37492105 PMCID: PMC10363808 DOI: 10.1016/j.xgen.2023.100339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Revised: 02/08/2023] [Accepted: 05/03/2023] [Indexed: 07/27/2023]
Abstract
Loss-of-function mutations in hepatocyte nuclear factor 1A (HNF1A) are known to cause rare forms of diabetes and alter hepatic physiology through unclear mechanisms. In the general population, 1:100 individuals carry a rare, protein-coding HNF1A variant, most of unknown functional consequence. To characterize the full allelic series, we performed deep mutational scanning of 11,970 protein-coding HNF1A variants in human hepatocytes and clinical correlation with 553,246 exome-sequenced individuals. Surprisingly, we found that ∼1:5 rare protein-coding HNF1A variants in the general population cause molecular gain of function (GOF), increasing the transcriptional activity of HNF1A by up to 50% and conferring protection from type 2 diabetes (odds ratio [OR] = 0.77, p = 0.007). Increased hepatic expression of HNF1A promoted a pro-atherogenic serum profile mediated in part by enhanced transcription of risk genes including ANGPTL3 and PCSK9. In summary, ∼1:300 individuals carry a GOF variant in HNF1A that protects carriers from diabetes but enhances hepatic secretion of atherogenic lipoproteins.
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Affiliation(s)
- Natalie DeForest
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Babu Kavitha
- Department of Molecular Genetics, Madras Diabetes Research Foundation, ICMR Centre for Advanced Research on Diabetes, Affiliated with University of Madras, Chennai, India
| | - Siqi Hu
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Roi Isaac
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | | | - Minxian Wang
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Xiaomi Du
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Camila De Arruda Saldanha
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Jenny Gylys
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Edoardo Merli
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Ruben Abagyan
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Laeya Najmi
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Diabetes Research, Department of Clinical Science, University of Bergen, 5020 Bergen, Norway
| | - Viswanathan Mohan
- Department of Diabetology, Dr. Mohan’s Diabetes Specialties Centre (IDF Centre of Education) & Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India
| | - Alnylam Human Genetics
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
- Department of Molecular Genetics, Madras Diabetes Research Foundation, ICMR Centre for Advanced Research on Diabetes, Affiliated with University of Madras, Chennai, India
- Alnylam Pharmaceuticals, Cambridge, MA, USA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
- Center for Diabetes Research, Department of Clinical Science, University of Bergen, 5020 Bergen, Norway
- Department of Diabetology, Dr. Mohan’s Diabetes Specialties Centre (IDF Centre of Education) & Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India
- Department of Pediatrics, Boston Children’s Hospital, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Glycobiology Research and Training Center, University of California, San Diego, La Jolla, CA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - AMP-T2D Consortium
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
- Department of Molecular Genetics, Madras Diabetes Research Foundation, ICMR Centre for Advanced Research on Diabetes, Affiliated with University of Madras, Chennai, India
- Alnylam Pharmaceuticals, Cambridge, MA, USA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
- Center for Diabetes Research, Department of Clinical Science, University of Bergen, 5020 Bergen, Norway
- Department of Diabetology, Dr. Mohan’s Diabetes Specialties Centre (IDF Centre of Education) & Madras Diabetes Research Foundation (ICMR Centre for Advanced Research on Diabetes), Chennai, India
- Department of Pediatrics, Boston Children’s Hospital, Boston, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Glycobiology Research and Training Center, University of California, San Diego, La Jolla, CA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jason Flannick
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Pediatrics, Boston Children’s Hospital, Boston, MA, USA
| | - Gina M. Peloso
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Philip L.S.M. Gordts
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
- Glycobiology Research and Training Center, University of California, San Diego, La Jolla, CA, USA
| | - Sven Heinz
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | | | - Amit V. Khera
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Jerrold Olefsky
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Venkatesan Radha
- Department of Molecular Genetics, Madras Diabetes Research Foundation, ICMR Centre for Advanced Research on Diabetes, Affiliated with University of Madras, Chennai, India
| | - Amit R. Majithia
- Division of Endocrinology, Department of Medicine, University of California San Diego, La Jolla, CA, USA
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25
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Chalise JP, Ehsani A, Lemecha M, Hung YW, Zhang G, Larson GP, Itakura K. ARID5B regulates fatty acid metabolism and proliferation at the Pre-B cell stage during B cell development. Front Immunol 2023; 14:1170475. [PMID: 37483604 PMCID: PMC10360657 DOI: 10.3389/fimmu.2023.1170475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 06/15/2023] [Indexed: 07/25/2023] Open
Abstract
During B cell development in bone marrow, large precursor B cells (large Pre-B cells) proliferate rapidly, exit the cell cycle, and differentiate into non-proliferative (quiescent) small Pre-B cells. Dysregulation of this process may result in the failure to produce functional B cells and pose a risk of leukemic transformation. Here, we report that AT rich interacting domain 5B (ARID5B), a B cell acute lymphoblastic leukemia (B-ALL) risk gene, regulates B cell development at the Pre-B stage. In both mice and humans, we observed a significant upregulation of ARID5B expression that initiates at the Pre-B stage and is maintained throughout later stages of B cell development. In mice, deletion of Arid5b in vivo and ex vivo exhibited a significant reduction in the proportion of immature B cells but an increase in large and small Pre-B cells. Arid5b inhibition ex vivo also led to an increase in proliferation of both Pre-B cell populations. Metabolic studies in mouse and human bone marrow revealed that fatty acid uptake peaked in proliferative B cells then decreased during non-proliferative stages. We showed that Arid5b ablation enhanced fatty acid uptake and oxidation in Pre-B cells. Furthermore, decreased ARID5B expression was observed in tumor cells from B-ALL patients when compared to B cells from non-leukemic individuals. In B-ALL patients, ARID5B expression below the median was associated with decreased survival particularly in subtypes originating from Pre-B cells. Collectively, our data indicated that Arid5b regulates fatty acid metabolism and proliferation of Pre-B cells in mice, and reduced expression of ARID5B in humans is a risk factor for B cell leukemia.
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Affiliation(s)
- Jaya Prakash Chalise
- Center for RNA Biology and Therapeutics, Beckman Research Institute, City of Hope, Duarte, CA, United States
| | - Ali Ehsani
- Center for RNA Biology and Therapeutics, Beckman Research Institute, City of Hope, Duarte, CA, United States
| | - Mengistu Lemecha
- Center for RNA Biology and Therapeutics, Beckman Research Institute, City of Hope, Duarte, CA, United States
| | - Yu-Wen Hung
- Immunology and Theranostics, Beckman Research Institute, City of Hope, Duarte, CA, United States
| | - Guoxiang Zhang
- Center for RNA Biology and Therapeutics, Beckman Research Institute, City of Hope, Duarte, CA, United States
| | - Garrett P. Larson
- Center for RNA Biology and Therapeutics, Beckman Research Institute, City of Hope, Duarte, CA, United States
| | - Keiichi Itakura
- Center for RNA Biology and Therapeutics, Beckman Research Institute, City of Hope, Duarte, CA, United States
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26
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Nepal C, Andersen JB. Alternative promoters in CpG depleted regions are prevalently associated with epigenetic misregulation of liver cancer transcriptomes. Nat Commun 2023; 14:2712. [PMID: 37169774 PMCID: PMC10175279 DOI: 10.1038/s41467-023-38272-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 04/24/2023] [Indexed: 05/13/2023] Open
Abstract
Transcriptional regulation is commonly governed by alternative promoters. However, the regulatory architecture in alternative and reference promoters, and how they differ, remains elusive. In 100 CAGE-seq libraries from hepatocellular carcinoma patients, here we annotate 4083 alternative promoters in 2926 multi-promoter genes, which are largely undetected in normal livers. These genes are enriched in oncogenic processes and predominantly show association with overall survival. Alternative promoters are narrow nucleosome depleted regions, CpG island depleted, and enriched for tissue-specific transcription factors. Globally tumors lose DNA methylation. We show hierarchical retention of intragenic DNA methylation with CG-poor regions rapidly losing methylation, while CG-rich regions retain it, a process mediated by differential SETD2, H3K36me3, DNMT3B, and TET1 binding. This mechanism is validated in SETD2 knockdown cells and SETD2-mutated patients. Selective DNA methylation loss in CG-poor regions makes the chromatin accessible for alternative transcription. We show alternative promoters can control tumor transcriptomes and their regulatory architecture.
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Affiliation(s)
- Chirag Nepal
- Biotech Research and Innovation Centre (BRIC), Department of Health and Medical Sciences, University of Copenhagen, Ole Maaløes Vej 5, Copenhagen N, DK-2200, Denmark.
- Center for Genomics, School of Medicine, Loma Linda University, Loma Linda, CA, 92350, USA.
| | - Jesper B Andersen
- Biotech Research and Innovation Centre (BRIC), Department of Health and Medical Sciences, University of Copenhagen, Ole Maaløes Vej 5, Copenhagen N, DK-2200, Denmark.
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27
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Hamilton MC, Fife JD, Akinci E, Yu T, Khowpinitchai B, Cha M, Barkal S, Thi TT, Yeo GH, Ramos Barroso JP, Francoeur MJ, Velimirovic M, Gifford DK, Lettre G, Yu H, Cassa CA, Sherwood RI. Systematic elucidation of genetic mechanisms underlying cholesterol uptake. CELL GENOMICS 2023; 3:100304. [PMID: 37228746 PMCID: PMC10203276 DOI: 10.1016/j.xgen.2023.100304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Revised: 12/02/2022] [Accepted: 03/24/2023] [Indexed: 05/27/2023]
Abstract
Genetic variation contributes greatly to LDL cholesterol (LDL-C) levels and coronary artery disease risk. By combining analysis of rare coding variants from the UK Biobank and genome-scale CRISPR-Cas9 knockout and activation screening, we substantially improve the identification of genes whose disruption alters serum LDL-C levels. We identify 21 genes in which rare coding variants significantly alter LDL-C levels at least partially through altered LDL-C uptake. We use co-essentiality-based gene module analysis to show that dysfunction of the RAB10 vesicle transport pathway leads to hypercholesterolemia in humans and mice by impairing surface LDL receptor levels. Further, we demonstrate that loss of function of OTX2 leads to robust reduction in serum LDL-C levels in mice and humans by increasing cellular LDL-C uptake. Altogether, we present an integrated approach that improves our understanding of the genetic regulators of LDL-C levels and provides a roadmap for further efforts to dissect complex human disease genetics.
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Affiliation(s)
- Marisa C. Hamilton
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - James D. Fife
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Ersin Akinci
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Tian Yu
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Benyapa Khowpinitchai
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Minsun Cha
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Sammy Barkal
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Thi Tun Thi
- Precision Medicine Research Programme, Cardiovascular Disease Research Programme, and Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Grace H.T. Yeo
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Biological Engineering, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Juan Pablo Ramos Barroso
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Matthew Jake Francoeur
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Minja Velimirovic
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - David K. Gifford
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Biological Engineering, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Guillaume Lettre
- Montreal Heart Institute, Montréal, QC H1T 1C8, Canada
- Faculté de Médecine, Université de Montréal, Montréal, QC H3T 1J4, Canada
| | - Haojie Yu
- Precision Medicine Research Programme, Cardiovascular Disease Research Programme, and Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Christopher A. Cassa
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Richard I. Sherwood
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
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28
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Morin A, Chu ECP, Sharma A, Adrian-Hamazaki A, Pavlidis P. Characterizing the targets of transcription regulators by aggregating ChIP-seq and perturbation expression data sets. Genome Res 2023; 33:763-778. [PMID: 37308292 PMCID: PMC10317128 DOI: 10.1101/gr.277273.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Accepted: 04/26/2023] [Indexed: 06/14/2023]
Abstract
Mapping the gene targets of chromatin-associated transcription regulators (TRs) is a major goal of genomics research. ChIP-seq of TRs and experiments that perturb a TR and measure the differential abundance of gene transcripts are a primary means by which direct relationships are tested on a genomic scale. It has been reported that there is a poor overlap in the evidence across gene regulation strategies, emphasizing the need for integrating results from multiple experiments. Although research consortia interested in gene regulation have produced a valuable trove of high-quality data, there is an even greater volume of TR-specific data throughout the literature. In this study, we show a workflow for the identification, uniform processing, and aggregation of ChIP-seq and TR perturbation experiments for the ultimate purpose of ranking human and mouse TR-target interactions. Focusing on an initial set of eight regulators (ASCL1, HES1, MECP2, MEF2C, NEUROD1, PAX6, RUNX1, and TCF4), we identified 497 experiments suitable for analysis. We used this corpus to examine data concordance, to identify systematic patterns of the two data types, and to identify putative orthologous interactions between human and mouse. We build upon commonly used strategies to forward a procedure for aggregating and combining these two genomic methodologies, assessing these rankings against independent literature-curated evidence. Beyond a framework extensible to other TRs, our work also provides empirically ranked TR-target listings, as well as transparent experiment-level gene summaries for community use.
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Affiliation(s)
- Alexander Morin
- Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
- Graduate Program in Bioinformatics, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
| | - Eric Ching-Pan Chu
- Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
- Graduate Program in Bioinformatics, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
| | - Aman Sharma
- Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
| | - Alex Adrian-Hamazaki
- Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
- Graduate Program in Bioinformatics, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
| | - Paul Pavlidis
- Michael Smith Laboratories, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada;
- Department of Psychiatry, University of British Columbia, Vancouver, British Columbia V6T 1Z4, Canada
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29
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Sullivan PF, Meadows JRS, Gazal S, Phan BN, Li X, Genereux DP, Dong MX, Bianchi M, Andrews G, Sakthikumar S, Nordin J, Roy A, Christmas MJ, Marinescu VD, Wang C, Wallerman O, Xue J, Yao S, Sun Q, Szatkiewicz J, Wen J, Huckins LM, Lawler A, Keough KC, Zheng Z, Zeng J, Wray NR, Li Y, Johnson J, Chen J, Paten B, Reilly SK, Hughes GM, Weng Z, Pollard KS, Pfenning AR, Forsberg-Nilsson K, Karlsson EK, Lindblad-Toh K. Leveraging base-pair mammalian constraint to understand genetic variation and human disease. Science 2023; 380:eabn2937. [PMID: 37104612 PMCID: PMC10259825 DOI: 10.1126/science.abn2937] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Accepted: 02/09/2023] [Indexed: 04/29/2023]
Abstract
Thousands of genomic regions have been associated with heritable human diseases, but attempts to elucidate biological mechanisms are impeded by an inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function, agnostic to cell type or disease mechanism. Single-base phyloP scores from 240 mammals identified 3.3% of the human genome as significantly constrained and likely functional. We compared phyloP scores to genome annotation, association studies, copy-number variation, clinical genetics findings, and cancer data. Constrained positions are enriched for variants that explain common disease heritability more than other functional annotations. Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.
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Affiliation(s)
- Patrick F. Sullivan
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, 17177 Stockholm, Sweden
| | - Jennifer R. S. Meadows
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - Steven Gazal
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
- Center for Genetic Epidemiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - BaDoi N. Phan
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Xue Li
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Diane P. Genereux
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Michael X. Dong
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - Matteo Bianchi
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - Gregory Andrews
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Sharadha Sakthikumar
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
| | - Jessika Nordin
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - Ananya Roy
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, 75185 Uppsala, Sweden
| | - Matthew J. Christmas
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - Voichita D. Marinescu
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - Chao Wang
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - Ola Wallerman
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
| | - James Xue
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Center for System Biology, Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA 02138, USA
| | - Shuyang Yao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, 17177 Stockholm, Sweden
| | - Quan Sun
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
| | - Jin Szatkiewicz
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
| | - Jia Wen
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
| | - Laura M. Huckins
- Department of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Alyssa Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Kathleen C. Keough
- Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, USA
| | - Zhili Zheng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072, Australia
| | - Jian Zeng
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072, Australia
| | - Naomi R. Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD 4072, Australia
| | - Yun Li
- Department of Genetics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
| | - Jessica Johnson
- Department of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina Medical School, Chapel Hill, NC 27599, USA
| | | | - Benedict Paten
- UC Santa Cruz Genomics Institute, Santa Cruz, CA 95064, USA
| | - Steven K. Reilly
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Graham M. Hughes
- School of Biology and Environmental Science, University College Dublin, Belfield, Dublin 4, Ireland
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Katherine S. Pollard
- Gladstone Institutes, San Francisco, CA 94158, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, USA
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
| | - Andreas R. Pfenning
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Karin Forsberg-Nilsson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, 75185 Uppsala, Sweden
- Biodiscovery Institute, University of Nottingham, Nottingham NG7 2RD, UK
| | - Elinor K. Karlsson
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA 01605, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
- Program in Molecular Medicine, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Kerstin Lindblad-Toh
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University, 75132 Uppsala, Sweden
- Broad Institute of MIT and Harvard, Cambridge, MA 02139, USA
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30
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Rogers BB, Anderson AG, Lauzon SN, Davis MN, Hauser RM, Roberts SC, Rodriguez-Nunez I, Trausch-Lowther K, Barinaga EA, Taylor JW, Mackiewicz M, Roberts BS, Cooper SJ, Rizzardi LF, Myers RM, Cochran JN. MAPT expression is mediated by long-range interactions with cis-regulatory elements. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.07.531520. [PMID: 37090552 PMCID: PMC10120716 DOI: 10.1101/2023.03.07.531520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Background Tauopathies are a group of neurodegenerative diseases driven by abnormal aggregates of tau, a microtubule associated protein encoded by the MAPT gene. MAPT expression is absent in neural progenitor cells (NPCs) and increases during differentiation. This temporally dynamic expression pattern suggests that MAPT expression is controlled by transcription factors and cis-regulatory elements specific to differentiated cell types. Given the relevance of MAPT expression to neurodegeneration pathogenesis, identification of such elements is relevant to understanding genetic risk factors. Methods We performed HiC, chromatin conformation capture (Capture-C), single-nucleus multiomics (RNA-seq+ATAC-seq), bulk ATAC-seq, and ChIP-seq for H3K27Ac and CTCF in NPCs and neurons differentiated from human iPSC cultures. We nominated candidate cis-regulatory elements (cCREs) for MAPT in human NPCs, differentiated neurons, and pure cultures of inhibitory and excitatory neurons. We then assayed these cCREs using luciferase assays and CRISPR interference (CRISPRi) experiments to measure their effects on MAPT expression. Finally, we integrated cCRE annotations into an analysis of genetic variation in AD cases and controls. Results Using orthogonal genomics approaches, we nominated 94 cCREs for MAPT, including the identification of cCREs specifically active in differentiated neurons. Eleven regions enhanced reporter gene transcription in luciferase assays. Using CRISPRi, 5 of the 94 regions tested were identified as necessary for MAPT expression as measured by RT-qPCR and RNA-seq. Rare and predicted damaging genetic variation in both nominated and confirmed CREs was depleted in AD cases relative to controls (OR = 0.40, p = 0.004), consistent with the hypothesis that variants that disrupt MAPT enhancer activity, and thereby reduce MAPT expression, may be protective against neurodegenerative disease. Conclusions We identified both proximal and distal regulatory elements for MAPT and confirmed the regulatory function for several regions, including three regions centromeric to MAPT beyond the well-described H1/H2 haplotype inversion breakpoint. This study provides compelling evidence for pursuing detailed knowledge of CREs for genes of interest to permit better understanding of disease risk.
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Affiliation(s)
- Brianne B. Rogers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
- University of Alabama at Birmingham, Birmingham, AL, USA
| | | | | | | | | | | | | | | | | | - Jared W. Taylor
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Mark Mackiewicz
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | - Sara J. Cooper
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
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31
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DelRosso N, Tycko J, Suzuki P, Andrews C, Aradhana, Mukund A, Liongson I, Ludwig C, Spees K, Fordyce P, Bassik MC, Bintu L. Large-scale mapping and mutagenesis of human transcriptional effector domains. Nature 2023; 616:365-372. [PMID: 37020022 PMCID: PMC10484233 DOI: 10.1038/s41586-023-05906-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 03/01/2023] [Indexed: 04/07/2023]
Abstract
Human gene expression is regulated by more than 2,000 transcription factors and chromatin regulators1,2. Effector domains within these proteins can activate or repress transcription. However, for many of these regulators we do not know what type of effector domains they contain, their location in the protein, their activation and repression strengths, and the sequences that are necessary for their functions. Here, we systematically measure the effector activity of more than 100,000 protein fragments tiling across most chromatin regulators and transcription factors in human cells (2,047 proteins). By testing the effect they have when recruited at reporter genes, we annotate 374 activation domains and 715 repression domains, roughly 80% of which are new and have not been previously annotated3-5. Rational mutagenesis and deletion scans across all the effector domains reveal aromatic and/or leucine residues interspersed with acidic, proline, serine and/or glutamine residues are necessary for activation domain activity. Furthermore, most repression domain sequences contain sites for small ubiquitin-like modifier (SUMO)ylation, short interaction motifs for recruiting corepressors or are structured binding domains for recruiting other repressive proteins. We discover bifunctional domains that can both activate and repress, some of which dynamically split a cell population into high- and low-expression subpopulations. Our systematic annotation and characterization of effector domains provide a rich resource for understanding the function of human transcription factors and chromatin regulators, engineering compact tools for controlling gene expression and refining predictive models of effector domain function.
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Affiliation(s)
| | - Josh Tycko
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Peter Suzuki
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Cecelia Andrews
- Department of Developmental Biology, Stanford University, Stanford, CA, USA
| | - Aradhana
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Adi Mukund
- Biophysics Program, Stanford University, Stanford, CA, USA
| | - Ivan Liongson
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Connor Ludwig
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Kaitlyn Spees
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Polly Fordyce
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- ChEM-H Institute, Stanford University, Stanford, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | | | - Lacramioara Bintu
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
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32
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Sullivan PF, Meadows JRS, Gazal S, Phan BN, Li X, Genereux DP, Dong MX, Bianchi M, Andrews G, Sakthikumar S, Nordin J, Roy A, Christmas MJ, Marinescu VD, Wallerman O, Xue JR, Li Y, Yao S, Sun Q, Szatkiewicz J, Wen J, Huckins LM, Lawler AJ, Keough KC, Zheng Z, Zeng J, Wray NR, Johnson J, Chen J, Paten B, Reilly SK, Hughes GM, Weng Z, Pollard KS, Pfenning AR, Forsberg-Nilsson K, Karlsson EK, Lindblad-Toh K. Leveraging Base Pair Mammalian Constraint to Understand Genetic Variation and Human Disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.10.531987. [PMID: 36945512 PMCID: PMC10028973 DOI: 10.1101/2023.03.10.531987] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/13/2023]
Abstract
Although thousands of genomic regions have been associated with heritable human diseases, attempts to elucidate biological mechanisms are impeded by a general inability to discern which genomic positions are functionally important. Evolutionary constraint is a powerful predictor of function that is agnostic to cell type or disease mechanism. Here, single base phyloP scores from the whole genome alignment of 240 placental mammals identified 3.5% of the human genome as significantly constrained, and likely functional. We compared these scores to large-scale genome annotation, genome-wide association studies (GWAS), copy number variation, clinical genetics findings, and cancer data sets. Evolutionarily constrained positions are enriched for variants explaining common disease heritability (more than any other functional annotation). Our results improve variant annotation but also highlight that the regulatory landscape of the human genome still needs to be further explored and linked to disease.
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Affiliation(s)
- Patrick F. Sullivan
- Department of Genetics, University of North Carolina Medical School; Chapel Hill, NC 27599, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet; Stockholm, Sweden
| | - Jennifer R. S. Meadows
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
| | - Steven Gazal
- Keck School of Medicine, University of Southern California; Los Angeles, CA 90033, USA
| | - BaDoi N. Phan
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine; Pittsburgh, PA 15261, USA
- Neuroscience Institute, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Xue Li
- Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA
- Morningside Graduate School of Biomedical Sciences, UMass Chan Medical School; Worcester, MA 01605, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School; Worcester, MA 01605, USA
| | | | - Michael X. Dong
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
| | - Matteo Bianchi
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
| | - Gregory Andrews
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School; Worcester, MA 01605, USA
| | - Sharadha Sakthikumar
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
- Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA
| | - Jessika Nordin
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University; Uppsala, 751 85, Sweden
| | - Ananya Roy
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University; Uppsala, 751 85, Sweden
| | - Matthew J. Christmas
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
| | - Voichita D. Marinescu
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
| | - Ola Wallerman
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
| | - James R. Xue
- Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA
- Department of Organismic and Evolutionary Biology, Harvard University; Cambridge, MA 02138, USA
| | - Yun Li
- Department of Genetics, University of North Carolina Medical School; Chapel Hill, NC 27599, USA
| | - Shuyang Yao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet; Stockholm, Sweden
| | - Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA
| | - Jin Szatkiewicz
- Department of Genetics, University of North Carolina Medical School; Chapel Hill, NC 27599, USA
| | - Jia Wen
- Department of Genetics, University of North Carolina Medical School; Chapel Hill, NC 27599, USA
| | - Laura M. Huckins
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
| | - Alyssa J. Lawler
- Neuroscience Institute, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA
- Department of Biological Sciences, Mellon College of Science, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Kathleen C. Keough
- Department of Epidemiology & Biostatistics, University of California San Francisco; San Francisco, CA 94158, USA
- Fauna Bio Incorporated; Emeryville, CA 94608, USA
- Gladstone Institutes; San Francisco, CA 94158, USA
| | - Zhili Zheng
- Institute for Molecular Bioscience, University of Queensland; Brisbane, Queensland, Australia
| | - Jian Zeng
- Institute for Molecular Bioscience, University of Queensland; Brisbane, Queensland, Australia
| | - Naomi R. Wray
- Institute for Molecular Bioscience, University of Queensland; Brisbane, Queensland, Australia
- Queensland Brain Institute, University of Queensland; Brisbane, Queensland, Australia
| | - Jessica Johnson
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai; New York, NY 10029, USA
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill; Chapel Hill, NC, USA
| | | | - Benedict Paten
- Genomics Institute, University of California Santa Cruz; Santa Cruz, CA 95064, USA
| | - Steven K. Reilly
- Department of Genetics, Yale School of Medicine; New Haven, CT 06510, USA
| | - Graham M. Hughes
- School of Biology and Environmental Science, University College Dublin; Belfield, Dublin 4, Ireland
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School; Worcester, MA 01605, USA
| | - Katherine S. Pollard
- Department of Epidemiology & Biostatistics, University of California San Francisco; San Francisco, CA 94158, USA
- Gladstone Institutes; San Francisco, CA 94158, USA
- Chan Zuckerberg Biohub; San Francisco, CA 94158, USA
| | - Andreas R. Pfenning
- Department of Computational Biology, School of Computer Science, Carnegie Mellon University; Pittsburgh, PA 15213, USA
- Neuroscience Institute, Carnegie Mellon University; Pittsburgh, PA 15213, USA
| | - Karin Forsberg-Nilsson
- Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University; Uppsala, 751 85, Sweden
- Biodiscovery Institute, University of Nottingham; Nottingham, UK
| | - Elinor K. Karlsson
- Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA
- Program in Bioinformatics and Integrative Biology, UMass Chan Medical School; Worcester, MA 01605, USA
- Program in Molecular Medicine, UMass Chan Medical School; Worcester, MA 01605, USA
| | - Kerstin Lindblad-Toh
- Department of Medical Biochemistry and Microbiology, Science for Life Laboratory, Uppsala University; Uppsala, 751 32, Sweden
- Broad Institute of MIT and Harvard; Cambridge, MA 02139, USA
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Disrupting the phase separation of KAT8-IRF1 diminishes PD-L1 expression and promotes antitumor immunity. NATURE CANCER 2023; 4:382-400. [PMID: 36894639 PMCID: PMC10042735 DOI: 10.1038/s43018-023-00522-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 02/02/2023] [Indexed: 03/11/2023]
Abstract
Immunotherapies targeting the PD-1/PD-L1 axis have become first-line treatments in multiple cancers. However, only a limited subset of individuals achieves durable benefits because of the elusive mechanisms regulating PD-1/PD-L1. Here, we report that in cells exposed to interferon-γ (IFNγ), KAT8 undergoes phase separation with induced IRF1 and forms biomolecular condensates to upregulate PD-L1. Multivalency from both the specific and promiscuous interactions between IRF1 and KAT8 is required for condensate formation. KAT8-IRF1 condensation promotes IRF1 K78 acetylation and binding to the CD247 (PD-L1) promoter and further enriches the transcription apparatus to promote transcription of PD-L1 mRNA. Based on the mechanism of KAT8-IRF1 condensate formation, we identified the 2142-R8 blocking peptide, which disrupts KAT8-IRF1 condensate formation and consequently inhibits PD-L1 expression and enhances antitumor immunity in vitro and in vivo. Our findings reveal a key role of KAT8-IRF1 condensates in PD-L1 regulation and provide a competitive peptide to enhance antitumor immune responses.
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Cook TW, Wilstermann AM, Mitchell JT, Arnold NE, Rajasekaran S, Bupp CP, Prokop JW. Understanding Insulin in the Age of Precision Medicine and Big Data: Under-Explored Nature of Genomics. Biomolecules 2023; 13:257. [PMID: 36830626 PMCID: PMC9953665 DOI: 10.3390/biom13020257] [Citation(s) in RCA: 1] [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: 12/06/2022] [Revised: 01/20/2023] [Accepted: 01/26/2023] [Indexed: 01/31/2023] Open
Abstract
Insulin is amongst the human genome's most well-studied genes/proteins due to its connection to metabolic health. Within this article, we review literature and data to build a knowledge base of Insulin (INS) genetics that influence transcription, transcript processing, translation, hormone maturation, secretion, receptor binding, and metabolism while highlighting the future needs of insulin research. The INS gene region has 2076 unique variants from population genetics. Several variants are found near the transcriptional start site, enhancers, and following the INS transcripts that might influence the readthrough fusion transcript INS-IGF2. This INS-IGF2 transcript splice site was confirmed within hundreds of pancreatic RNAseq samples, lacks drift based on human genome sequencing, and has possible elevated expression due to viral regulation within the liver. Moreover, a rare, poorly characterized African population-enriched variant of INS-IGF2 results in a loss of the stop codon. INS transcript UTR variants rs689 and rs3842753, associated with type 1 diabetes, are found in many pancreatic RNAseq datasets with an elevation of the 3'UTR alternatively spliced INS transcript. Finally, by combining literature, evolutionary profiling, and structural biology, we map rare missense variants that influence preproinsulin translation, proinsulin processing, dimer/hexamer secretory storage, receptor activation, and C-peptide detection for quasi-insulin blood measurements.
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Affiliation(s)
- Taylor W. Cook
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824, USA
| | | | - Jackson T. Mitchell
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824, USA
| | - Nicholas E. Arnold
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824, USA
| | - Surender Rajasekaran
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Office of Research, Corewell Health, Grand Rapids, MI 49503, USA
| | - Caleb P. Bupp
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Division of Medical Genetics, Corewell Health, Grand Rapids, MI 49503, USA
| | - Jeremy W. Prokop
- Department of Pediatrics and Human Development, College of Human Medicine, Michigan State University, Grand Rapids, MI 49503, USA
- Department of Pharmacology and Toxicology, Michigan State University, East Lansing, MI 48824, USA
- Office of Research, Corewell Health, Grand Rapids, MI 49503, USA
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Hamilton MC, Fife JD, Akinci E, Yu T, Khowpinitchai B, Cha M, Barkal S, Thi TT, Yeo GH, Ramos Barroso JP, Jake Francoeur M, Velimirovic M, Gifford DK, Lettre G, Yu H, Cassa CA, Sherwood RI. Systematic elucidation of genetic mechanisms underlying cholesterol uptake. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.09.500804. [PMID: 36711952 PMCID: PMC9881906 DOI: 10.1101/2023.01.09.500804] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/09/2023]
Abstract
Genetic variation contributes greatly to LDL cholesterol (LDL-C) levels and coronary artery disease risk. By combining analysis of rare coding variants from the UK Biobank and genome-scale CRISPR-Cas9 knockout and activation screening, we have substantially improved the identification of genes whose disruption alters serum LDL-C levels. We identify 21 genes in which rare coding variants significantly alter LDL-C levels at least partially through altered LDL-C uptake. We use co-essentiality-based gene module analysis to show that dysfunction of the RAB10 vesicle transport pathway leads to hypercholesterolemia in humans and mice by impairing surface LDL receptor levels. Further, we demonstrate that loss of function of OTX2 leads to robust reduction in serum LDL-C levels in mice and humans by increasing cellular LDL-C uptake. Altogether, we present an integrated approach that improves our understanding of genetic regulators of LDL-C levels and provides a roadmap for further efforts to dissect complex human disease genetics.
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Affiliation(s)
- Marisa C. Hamilton
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - James D. Fife
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Ersin Akinci
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Tian Yu
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Benyapa Khowpinitchai
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Minsun Cha
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Sammy Barkal
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Thi Tun Thi
- Precision Medicine Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Cardiovascular Disease Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Grace H.T. Yeo
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Juan Pablo Ramos Barroso
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Matthew Jake Francoeur
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Minja Velimirovic
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - David K. Gifford
- Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- Department of Biological Engineering, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Guillaume Lettre
- Montreal Heart Institute, Montréal, Québec, H1T 1C8, Canada
- Faculté de Médecine, Université de Montréal, Montréal, Québec, H3T 1J4, Canada
| | - Haojie Yu
- Precision Medicine Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Cardiovascular Disease Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Address correspondence to , ,
| | - Christopher A. Cassa
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
- Address correspondence to , ,
| | - Richard I. Sherwood
- Division of Genetics, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA
- Address correspondence to , ,
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Zheng Y, Jun J, Brennan K, Gevaert O. EpiMix: an integrative tool for epigenomic subtyping using DNA methylation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.03.522660. [PMID: 36711917 PMCID: PMC9881910 DOI: 10.1101/2023.01.03.522660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
DNA methylation (DNAme) is a major epigenetic factor influencing gene expression with alterations leading to cancer, immunological, and cardiovascular diseases. Recent technological advances enable genome-wide quantification of DNAme in large human cohorts. So far, existing methods have not been evaluated to identify differential DNAme present in large and heterogeneous patient cohorts. We developed an end-to-end analytical framework named "EpiMix" for population-level analysis of DNAme and gene expression. Compared to existing methods, EpiMix showed higher sensitivity in detecting abnormal DNAme that was present in only small patient subsets. We extended the model-based analyses of EpiMix to cis-regulatory elements within protein-coding genes, distal enhancers, and genes encoding microRNAs and lncRNAs. Using cell-type specific data from two separate studies, we discovered novel epigenetic mechanisms underlying childhood food allergy and survival-associated, methylation-driven non-coding RNAs in non-small cell lung cancer.
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Affiliation(s)
- Yuanning Zheng
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - John Jun
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Kevin Brennan
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Olivier Gevaert
- Stanford Center for Biomedical Informatics Research (BMIR), Department of Medicine & Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
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Hwang HJ, Lee KH, Cho JY. ABCA9, an ER cholesterol transporter, inhibits breast cancer cell proliferation via SREBP-2 signaling. Cancer Sci 2022; 114:1451-1463. [PMID: 36576228 PMCID: PMC10067411 DOI: 10.1111/cas.15710] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 12/15/2022] [Accepted: 12/21/2022] [Indexed: 12/29/2022] Open
Abstract
The association between cholesterol metabolism and cancer development and progression has been recently highlighted. However, the role and function of many cholesterol transporters remain largely unknown. Here, we focused on the ATP-binding cassette subfamily A member 9 (ABCA9) transporter given that its expression is significantly downregulated in both canine mammary tumors and human breast cancers, which in breast cancer patients correlates with poor prognosis. We found that ABCA9 is mainly present in the endoplasmic reticulum (ER) and is responsible for promoting cholesterol accumulation in this structure. Accordingly, ABCA9 inhibited sterol-regulatory element binding protein-2 (SREBP-2) translocation from the ER to the nucleus, a crucial step for cholesterol synthesis, resulting in the downregulation of cholesterol synthesis gene expression. ABCA9 expression in breast cancer cells attenuated cell proliferation and reduced their colony-forming abilities. We identified ABCA9 expression to be regulated by Forkhead box O1 (FOXO1). Inhibition of PI3K induced enhanced ABCA9 expression through the activation of the PI3K-Akt-FOXO1 pathway in breast cancer cells. Altogether, our study suggests that ABCA9 functions as an ER cholesterol transporter that suppresses cholesterol synthesis via the inhibition of SREBP-2 signaling and that its restoration halts breast cancer cell proliferation. Our findings provide novel insight into the vital role of ABCA9 in breast cancer progression.
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Affiliation(s)
- Hyeon-Ji Hwang
- Department of Biochemistry, BK21 Plus and Research Institute for Veterinary Science, College of Veterinary Medicine, Seoul National University, Seoul, Korea.,Comparative Medicine Disease Research Center, Seoul National University, Seoul, Korea
| | - Kang-Hoon Lee
- Department of Biochemistry, BK21 Plus and Research Institute for Veterinary Science, College of Veterinary Medicine, Seoul National University, Seoul, Korea
| | - Je-Yoel Cho
- Department of Biochemistry, BK21 Plus and Research Institute for Veterinary Science, College of Veterinary Medicine, Seoul National University, Seoul, Korea.,Comparative Medicine Disease Research Center, Seoul National University, Seoul, Korea
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Interplay Between the Histone Variant H2A.Z and the Epigenome in Pancreatic Cancer. Arch Med Res 2022; 53:840-858. [PMID: 36470770 DOI: 10.1016/j.arcmed.2022.11.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2022] [Revised: 10/25/2022] [Accepted: 11/18/2022] [Indexed: 12/03/2022]
Abstract
BACKGROUND The oncogenic process is orchestrated by a complex network of chromatin remodeling elements that shape the cancer epigenome. Histone variant H2A.Z regulates DNA control elements such as promoters and enhancers in different types of cancer; however, the interplay between H2A.Z and the pancreatic cancer epigenome is unknown. OBJECTIVE This study analyzed the role of H2A.Z in different DNA regulatory elements. METHODS We performed Chromatin Immunoprecipitation Sequencing assays (ChiP-seq) with total H2A.Z and acetylated H2A.Z (acH2A.Z) antibodies and analyzed published data from ChIP-seq, RNA-seq, bromouridine labeling-UV and sequencing (BruUV-seq), Hi-C and ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) in the pancreatic cancer cell line PANC-1. RESULTS The results indicate that total H2A.Z facilitates the recruitment of RNA polymerase II and transcription factors at promoters and enhancers allowing the expression of pro-oncogenic genes. Interestingly, we demonstrated that H2A.Z is enriched in super-enhancers (SEs) contributing to the transcriptional activation of key genes implicated in tumor development. Importantly, we established that H2A.Z contributes to the three-dimensional (3D) genome organization of pancreatic cancer and that it is a component of the Topological Associated Domains (TADs) boundaries in PANC-1 and that total H2A.Z and acH2A.Z are associated with A and B compartments, respectively. CONCLUSIONS H2A.Z participates in the biology and development of pancreatic cancer by generating a pro-oncogenic transcriptome through its posttranslational modifications, interactions with different partners, and regulatory elements, contributing to the oncogenic 3D genome organization. These data allow us to understand the molecular mechanisms that promote an oncogenic transcriptome in pancreatic cancer mediated by H2A.Z.
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Demos C, Johnson J, Andueza A, Park C, Kim Y, Villa-Roel N, Kang DW, Kumar S, Jo H. Sox13 is a novel flow-sensitive transcription factor that prevents inflammation by repressing chemokine expression in endothelial cells. Front Cardiovasc Med 2022; 9:979745. [PMID: 36247423 PMCID: PMC9561411 DOI: 10.3389/fcvm.2022.979745] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 08/29/2022] [Indexed: 11/13/2022] Open
Abstract
Atherosclerosis is a chronic inflammatory disease and occurs preferentially in arterial regions exposed to disturbed blood flow (d-flow) while the stable flow (s-flow) regions are spared. D-flow induces endothelial inflammation and atherosclerosis by regulating endothelial gene expression partly through the flow-sensitive transcription factors (FSTFs). Most FSTFs, including the well-known Kruppel-like factors KLF2 and KLF4, have been identified from in vitro studies using cultured endothelial cells (ECs). Since many flow-sensitive genes and pathways are lost or dysregulated in ECs during culture, we hypothesized that many important FSTFs in ECs in vivo have not been identified. We tested the hypothesis by analyzing our recent gene array and single-cell RNA sequencing (scRNAseq) and chromatin accessibility sequencing (scATACseq) datasets generated using the mouse partial carotid ligation model. From the analyses, we identified 30 FSTFs, including the expected KLF2/4 and novel FSTFs. They were further validated in mouse arteries in vivo and cultured human aortic ECs (HAECs). These results revealed 8 FSTFs, SOX4, SOX13, SIX2, ZBTB46, CEBPβ, NFIL3, KLF2, and KLF4, that are conserved in mice and humans in vivo and in vitro. We selected SOX13 for further studies because of its robust flow-sensitive regulation, preferential expression in ECs, and unknown flow-dependent function. We found that siRNA-mediated knockdown of SOX13 increased endothelial inflammatory responses even under the unidirectional laminar shear stress (ULS, mimicking s-flow) condition. To understand the underlying mechanisms, we conducted an RNAseq study in HAECs treated with SOX13 siRNA under shear conditions (ULS vs. oscillatory shear mimicking d-flow). We found 94 downregulated and 40 upregulated genes that changed in a shear- and SOX13-dependent manner. Several cytokines, including CXCL10 and CCL5, were the most strongly upregulated genes in HAECs treated with SOX13 siRNA. The robust induction of CXCL10 and CCL5 was further validated by qPCR and ELISA in HAECs. Moreover, the treatment of HAECs with Met-CCL5, a specific CCL5 receptor antagonist, prevented the endothelial inflammation responses induced by siSOX13. In addition, SOX13 overexpression prevented the endothelial inflammation responses. In summary, SOX13 is a novel conserved FSTF, which represses the expression of pro-inflammatory chemokines in ECs under s-flow. Reduction of endothelial SOX13 triggers chemokine expression and inflammatory responses, a major proatherogenic pathway.
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Affiliation(s)
- Catherine Demos
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Janie Johnson
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Aitor Andueza
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Christian Park
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Yerin Kim
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Nicolas Villa-Roel
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Dong-Won Kang
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Sandeep Kumar
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
| | - Hanjoong Jo
- Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Emory University, Atlanta, GA, United States
- Division of Cardiology, Department of Medicine, Emory University, Atlanta, GA, United States
- *Correspondence: Hanjoong Jo,
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Lebeau B, Zhao K, Jangal M, Zhao T, Guerra M, Greenwood CMT, Witcher M. Single base-pair resolution analysis of DNA binding motif with MoMotif reveals an oncogenic function of CTCF zinc-finger 1 mutation. Nucleic Acids Res 2022; 50:8441-8458. [PMID: 35947648 PMCID: PMC9410893 DOI: 10.1093/nar/gkac658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Accepted: 07/21/2022] [Indexed: 12/24/2022] Open
Abstract
Defining the impact of missense mutations on the recognition of DNA motifs is highly dependent on bioinformatic tools that define DNA binding elements. However, classical motif analysis tools remain limited in their capacity to identify subtle changes in complex binding motifs between distinct conditions. To overcome this limitation, we developed a new tool, MoMotif, that facilitates a sensitive identification, at the single base-pair resolution, of complex, or subtle, alterations to core binding motifs, discerned from ChIP-seq data. We employed MoMotif to define the previously uncharacterized recognition motif of CTCF zinc-finger 1 (ZF1), and to further define the impact of CTCF ZF1 mutation on its association with chromatin. Mutations of CTCF ZF1 are exclusive to breast cancer and are associated with metastasis and therapeutic resistance, but the underlying mechanisms are unclear. Using MoMotif, we identified an extension of the CTCF core binding motif, necessitating a functional ZF1 to bind appropriately. Using a combination of ChIP-Seq and RNA-Seq, we discover that the inability to bind this extended motif drives an altered transcriptional program associated with the oncogenic phenotypes observed clinically. Our study demonstrates that MoMotif is a powerful new tool for comparative ChIP-seq analysis and characterising DNA-protein contacts.
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Affiliation(s)
| | | | - Maika Jangal
- Lady Davis Institute, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
| | - Tiejun Zhao
- Lady Davis Institute, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
| | - Maria Guerra
- Lady Davis Institute, Jewish General Hospital, Montréal, Québec H3T 1E2, Canada
| | - Celia M T Greenwood
- Correspondence may also be addressed to Celia Greenwood. Tel: +1 514 340 8222 (Ext 28397);
| | - Michael Witcher
- To whom correspondence should be addressed. Tel: +1 514 340 8222 (Ext 23363);
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Yoo HS, Rodriguez A, You D, Lee RA, Cockrum MA, Grimes JA, Wang JC, Kang S, Napoli JL. The glucocorticoid receptor represses, whereas C/EBPβ can enhance or repress CYP26A1 transcription. iScience 2022; 25:104564. [PMID: 35789854 PMCID: PMC9249609 DOI: 10.1016/j.isci.2022.104564] [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: 11/19/2021] [Revised: 05/12/2022] [Accepted: 06/06/2022] [Indexed: 11/24/2022] Open
Abstract
Retinoic acid (RA) counters insulin's metabolic actions. Insulin reduces liver RA biosynthesis by exporting FoxO1 from nuclei. RA induces its catabolism, catalyzed by CYP26A1. A CYP26A1 contribution to RA homeostasis with changes in energy status had not been investigated. We found that glucagon, cortisol, and dexamethasone decrease RA-induced CYP26A1 transcription, thereby reducing RA oxidation during fasting. Interaction between the glucocorticoid receptor and the RAR/RXR coactivation complex suppresses CYP26A1 expression, increasing RA's elimination half-life. Interaction between CCAAT-enhancer-binding protein beta (C/EBPβ) and the major allele of SNP rs2068888 enhances CYP26A1 expression; the minor allele restricts the C/EBPβ effect on CYP26A1. The major and minor alleles associate with impaired human health or reduction in blood triglycerides, respectively. Thus, regulating CYP26A1 transcription contributes to adapting RA to coordinate energy availability with metabolism. These results enhance insight into CYP26A1 effects on RA during changes in energy status and glucocorticoid receptor modification of RAR-regulated gene expression.
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Affiliation(s)
- Hong Sik Yoo
- Department of Nutritional Sciences and Toxicology, Graduate Program in Metabolic Biology, The University of California, Berkeley Berkeley, CA 94720, USA
| | - Adrienne Rodriguez
- Department of Nutritional Sciences and Toxicology, Graduate Program in Metabolic Biology, The University of California, Berkeley Berkeley, CA 94720, USA
| | - Dongjoo You
- Department of Nutritional Sciences and Toxicology, Graduate Program in Metabolic Biology, The University of California, Berkeley Berkeley, CA 94720, USA
| | - Rebecca A. Lee
- Department of Nutritional Sciences and Toxicology, Graduate Program in Metabolic Biology, The University of California, Berkeley Berkeley, CA 94720, USA
| | - Michael A. Cockrum
- Department of Nutritional Sciences and Toxicology, Graduate Program in Metabolic Biology, The University of California, Berkeley Berkeley, CA 94720, USA
| | - Jack A. Grimes
- Department of Nutritional Sciences and Toxicology, Graduate Program in Metabolic Biology, The University of California, Berkeley Berkeley, CA 94720, USA
| | - Jen-Chywan Wang
- Department of Nutritional Sciences and Toxicology, Graduate Program in Metabolic Biology, The University of California, Berkeley Berkeley, CA 94720, USA
| | - Sona Kang
- Department of Nutritional Sciences and Toxicology, Graduate Program in Metabolic Biology, The University of California, Berkeley Berkeley, CA 94720, USA
| | - Joseph L. Napoli
- Department of Nutritional Sciences and Toxicology, Graduate Program in Metabolic Biology, The University of California, Berkeley Berkeley, CA 94720, USA
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Tian H, He Y, Xue Y, Gao YQ. Expression regulation of genes is linked to their CpG density distributions around transcription start sites. Life Sci Alliance 2022; 5:5/9/e202101302. [PMID: 35580989 PMCID: PMC9113945 DOI: 10.26508/lsa.202101302] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 05/07/2022] [Accepted: 05/09/2022] [Indexed: 11/24/2022] Open
Abstract
The CpG dinucleotide and its methylation behaviors play vital roles in gene regulation. Previous studies have divided genes into several categories based on the CpG intensity around transcription starting sites and found that housekeeping genes tend to possess high CpG density, whereas tissue-specific genes are generally characterized by low CpG density. In this study, we investigated how the CpG density distribution of a gene affects its transcription and regulation pattern. Based on the CpG density distribution around transcription starting site, by means of a semi-supervised neural network we designed, which took data augmentation into account, we divided the human genes into three categories, and genes within each cluster shared similar CpG density distribution. Not only sequence properties, these different clusters exhibited distinctly different structural features, regulatory mechanisms, correlation patterns between the expression level and CpG/TpG density, and expression and epigenetic mark variations during tumorigenesis. For instance, the activation of cluster 3 genes relies more on 3D genome reorganization, compared with cluster 1 and 2 genes, whereas cluster 2 genes showed the strongest correlation between gene expression and H3K27me3. Genes exhibiting uncoupled correlation between gene regulation and histone modifications are mainly in cluster 3. These results emphasized that the usage of epigenetic marks in gene regulation is partially rooted in the sequence property of genes such as their CpG density distribution and explained to some extent why the relation between epigenetic marks and gene expression is controversial.
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Affiliation(s)
- Hao Tian
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Yueying He
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Yue Xue
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Yi Qin Gao
- Beijing National Laboratory for Molecular Sciences, College of Chemistry and Molecular Engineering, Peking University, Beijing, China .,Biomedical Pioneering Innovation Center (BIOPIC), Peking University, Beijing, China.,Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
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43
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Ma H, de Zwaan E, Guo YE, Cejas P, Thiru P, van de Bunt M, Jeppesen JF, Syamala S, Dall'Agnese A, Abraham BJ, Fu D, Garrett-Engele C, Lee TI, Long HW, Griffith LG, Young RA, Jaenisch R. The nuclear receptor THRB facilitates differentiation of human PSCs into more mature hepatocytes. Cell Stem Cell 2022; 29:795-809.e11. [PMID: 35452598 PMCID: PMC9466295 DOI: 10.1016/j.stem.2022.03.015] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 11/23/2021] [Accepted: 03/28/2022] [Indexed: 12/15/2022]
Abstract
To understand the mechanisms regulating the in vitro maturation of hPSC-derived hepatocytes, we developed a 3D differentiation system and compared gene regulatory elements in human primary hepatocytes with those in hPSC-hepatocytes that were differentiated in 2D or 3D conditions by RNA-seq, ATAC-seq, and H3K27Ac ChIP-seq. Regulome comparisons showed a reduced enrichment of thyroid receptor THRB motifs in accessible chromatin and active enhancers without a reduced transcription of THRB. The addition of thyroid hormone T3 increased the binding of THRB to the CYP3A4 proximal enhancer, restored the super-enhancer status and gene expression of NFIC, and reduced the expression of AFP. The resultant hPSC-hepatocytes showed gene expression, epigenetic status, and super-enhancer landscape closer to primary hepatocytes and activated regulatory regions including non-coding SNPs associated with liver-related diseases. Transplanting the hPSC-hepatocytes resulted in the engraftment of human hepatocytes into the mouse liver without disrupting normal liver histology. This work implicates the environmental factor-nuclear receptor axis in regulating the maturation of hPSC-hepatocytes.
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Affiliation(s)
- Haiting Ma
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | - Esmée de Zwaan
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | - Yang Eric Guo
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | - Paloma Cejas
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Prathapan Thiru
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | | | - Jacob F Jeppesen
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA; Global Drug Discovery, Novo Nordisk, Cambridge, MA 02142, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Sudeepa Syamala
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | | | - Brian J Abraham
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA; Computational Biology, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Dongdong Fu
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | | | - Tong Ihn Lee
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | - Henry W Long
- Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Linda G Griffith
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Richard A Young
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Rudolf Jaenisch
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA.
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44
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Napoli JL. Retinoic Acid: Sexually Dimorphic, Anti-Insulin and Concentration-Dependent Effects on Energy. Nutrients 2022; 14:1553. [PMID: 35458115 PMCID: PMC9027308 DOI: 10.3390/nu14081553] [Citation(s) in RCA: 2] [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: 03/11/2022] [Revised: 04/01/2022] [Accepted: 04/05/2022] [Indexed: 12/26/2022] Open
Abstract
This review addresses the fasting vs. re-feeding effects of retinoic acid (RA) biosynthesis and functions, and sexually dimorphic RA actions. It also discusses other understudied topics essential for understanding RA activities-especially interactions with energy-balance-regulating hormones, including insulin and glucagon, and sex hormones. This report will introduce RA homeostasis and hormesis to provide context. Essential context also will encompass RA effects on adiposity, muscle function and pancreatic islet development and maintenance. These comments provide background for explaining interactions among insulin, glucagon and cortisol with RA homeostasis and function. One aim would clarify the often apparent RA contradictions related to pancreagenesis vs. pancreas hormone functions. The discussion also will explore the adverse effects of RA on estrogen action, in contrast to the enhancing effects of estrogen on RA action, the adverse effects of androgens on RA receptors, and the RA induction of androgen biosynthesis.
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Affiliation(s)
- Joseph L Napoli
- Graduate Program in Metabolic Biology, Department of Nutritional Sciences and Toxicology, The University of California-Berkeley, Berkeley, CA 94704, USA
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45
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Abstract
DNA can determine where and when genes are expressed, but the full set of sequence determinants that control gene expression is unknown. Here, we measured the transcriptional activity of DNA sequences that represent an ~100 times larger sequence space than the human genome using massively parallel reporter assays (MPRAs). Machine learning models revealed that transcription factors (TFs) generally act in an additive manner with weak grammar and that most enhancers increase expression from a promoter by a mechanism that does not appear to involve specific TF–TF interactions. The enhancers themselves can be classified into three types: classical, closed chromatin and chromatin dependent. We also show that few TFs are strongly active in a cell, with most activities being similar between cell types. Individual TFs can have multiple gene regulatory activities, including chromatin opening and enhancing, promoting and determining transcription start site (TSS) activity, consistent with the view that the TF binding motif is the key atomic unit of gene expression. Analysis of massively parallel reporter assays measuring the transcriptional activity of DNA sequences indicates that most transcription factor (TF) activity is additive and does not rely on specific TF–TF interactions. Individual TFs can have different gene regulatory activities.
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46
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Jansen C, Paraiso KD, Zhou JJ, Blitz IL, Fish MB, Charney RM, Cho JS, Yasuoka Y, Sudou N, Bright AR, Wlizla M, Veenstra GJC, Taira M, Zorn AM, Mortazavi A, Cho KWY. Uncovering the mesendoderm gene regulatory network through multi-omic data integration. Cell Rep 2022; 38:110364. [PMID: 35172134 PMCID: PMC8917868 DOI: 10.1016/j.celrep.2022.110364] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2020] [Revised: 10/30/2021] [Accepted: 01/19/2022] [Indexed: 01/01/2023] Open
Abstract
Mesendodermal specification is one of the earliest events in embryogenesis, where cells first acquire distinct identities. Cell differentiation is a highly regulated process that involves the function of numerous transcription factors (TFs) and signaling molecules, which can be described with gene regulatory networks (GRNs). Cell differentiation GRNs are difficult to build because existing mechanistic methods are low throughput, and high-throughput methods tend to be non-mechanistic. Additionally, integrating highly dimensional data composed of more than two data types is challenging. Here, we use linked self-organizing maps to combine chromatin immunoprecipitation sequencing (ChIP-seq)/ATAC-seq with temporal, spatial, and perturbation RNA sequencing (RNA-seq) data from Xenopus tropicalis mesendoderm development to build a high-resolution genome scale mechanistic GRN. We recover both known and previously unsuspected TF-DNA/TF-TF interactions validated through reporter assays. Our analysis provides insights into transcriptional regulation of early cell fate decisions and provides a general approach to building GRNs using highly dimensional multi-omic datasets.
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Affiliation(s)
- Camden Jansen
- Department of Developmental and Cell Biology, University of California, Irvine, CA, USA; Center for Complex Biological Systems, University of California, Irvine, CA, USA
| | - Kitt D Paraiso
- Department of Developmental and Cell Biology, University of California, Irvine, CA, USA; Center for Complex Biological Systems, University of California, Irvine, CA, USA
| | - Jeff J Zhou
- Department of Developmental and Cell Biology, University of California, Irvine, CA, USA
| | - Ira L Blitz
- Department of Developmental and Cell Biology, University of California, Irvine, CA, USA
| | - Margaret B Fish
- Department of Developmental and Cell Biology, University of California, Irvine, CA, USA
| | - Rebekah M Charney
- Department of Developmental and Cell Biology, University of California, Irvine, CA, USA
| | - Jin Sun Cho
- Department of Developmental and Cell Biology, University of California, Irvine, CA, USA
| | - Yuuri Yasuoka
- Laboratory for Comprehensive Genomic Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Norihiro Sudou
- Department of Anatomy, School of Medicine, Toho University, Tokyo, Japan
| | - Ann Rose Bright
- Department of Molecular Developmental Biology, Radboud University, Nijmegen, the Netherlands
| | - Marcin Wlizla
- Division of Developmental Biology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Gert Jan C Veenstra
- Department of Molecular Developmental Biology, Radboud University, Nijmegen, the Netherlands
| | - Masanori Taira
- Department of Biological Sciences, Chuo University, Tokyo, Japan
| | - Aaron M Zorn
- Division of Developmental Biology, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Ali Mortazavi
- Department of Developmental and Cell Biology, University of California, Irvine, CA, USA; Center for Complex Biological Systems, University of California, Irvine, CA, USA.
| | - Ken W Y Cho
- Department of Developmental and Cell Biology, University of California, Irvine, CA, USA; Center for Complex Biological Systems, University of California, Irvine, CA, USA.
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47
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Salbert G, Sérandour AA, Staels B, Lefebvre P, Eeckhoute J. The conundrum of the functional relationship between transcription factors and chromatin. Epigenomics 2022; 14:223-225. [PMID: 35034474 DOI: 10.2217/epi-2021-0509] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Affiliation(s)
- Gilles Salbert
- Université de Rennes 1, UMR6290 CNRS, Institut de Génétique et Développement de Rennes, Campus de Beaulieu, 35042, Rennes Cedex, France
| | | | - Bart Staels
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, F-59000, Lille, France
| | - Philippe Lefebvre
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, F-59000, Lille, France
| | - Jérôme Eeckhoute
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, F-59000, Lille, France
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48
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Wang R, Chen F, Chen Q, Wan X, Shi M, Chen AK, Ma Z, Li G, Wang M, Ying Y, Liu Q, Li H, Zhang X, Ma J, Zhong J, Chen M, Zhang MQ, Zhang Y, Chen Y, Zhu D. MyoD is a 3D genome structure organizer for muscle cell identity. Nat Commun 2022; 13:205. [PMID: 35017543 PMCID: PMC8752600 DOI: 10.1038/s41467-021-27865-6] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 12/15/2021] [Indexed: 12/15/2022] Open
Abstract
The genome exists as an organized, three-dimensional (3D) dynamic architecture, and each cell type has a unique 3D genome organization that determines its cell identity. An unresolved question is how cell type-specific 3D genome structures are established during development. Here, we analyzed 3D genome structures in muscle cells from mice lacking the muscle lineage transcription factor (TF), MyoD, versus wild-type mice. We show that MyoD functions as a “genome organizer” that specifies 3D genome architecture unique to muscle cell development, and that H3K27ac is insufficient for the establishment of MyoD-induced chromatin loops in muscle cells. Moreover, we present evidence that other cell lineage-specific TFs might also exert functional roles in orchestrating lineage-specific 3D genome organization during development. Pioneer transcription factors (TFs) have been proposed to act as protein anchors to orchestrate cell type-specific 3D genome architecture. MyoD is a pioneer TF for myogenic lineage specification. Here the authors provide further support for the role of MyoD in 3D genome architecture in muscle stem cells by comparing MyoD knockout and wild-type mice.
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Affiliation(s)
- Ruiting Wang
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, 5 Dong Dan San Tiao, 100005, Beijing, China
| | - Fengling Chen
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Bioinformatics Division, BNRist, Department of Automation, Tsinghua University, 100084, Beijing, China
| | - Qian Chen
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, 5 Dong Dan San Tiao, 100005, Beijing, China
| | - Xin Wan
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, 5 Dong Dan San Tiao, 100005, Beijing, China
| | - Minglei Shi
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Medicine, Tsinghua University, 100084, Beijing, China
| | - Antony K Chen
- Department of Biomedical Engineering, College of Future Technology, Peking University, 100871, Beijing, China
| | - Zhao Ma
- Department of Biomedical Engineering, College of Future Technology, Peking University, 100871, Beijing, China.,Department of Biomedical Engineering, College of Engineering, Peking University, 100871, Beijing, China
| | - Guohong Li
- National Laboratory of Biomacromolecules, CAS Center for Excellent in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China.,University of Chinese Academy of Science, 100049, Beijing, China
| | - Min Wang
- National Laboratory of Biomacromolecules, CAS Center for Excellent in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, 100101, Beijing, China.,University of Chinese Academy of Science, 100049, Beijing, China
| | - Yachen Ying
- Department of Biomedical Engineering, College of Future Technology, Peking University, 100871, Beijing, China.,Department of Biomedical Engineering, College of Engineering, Peking University, 100871, Beijing, China
| | - Qinyao Liu
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, 5 Dong Dan San Tiao, 100005, Beijing, China
| | - Hu Li
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, 5 Dong Dan San Tiao, 100005, Beijing, China.,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), 510320, Guangzhou, China
| | - Xu Zhang
- Beijing institute of collaborative innovation, 100094, Beijing, China
| | - Jinbiao Ma
- State Key Laboratory of Genetic Engineering, Department of Biochemistry, School of Life Sciences, Fudan University, 200438, Shanghai, China
| | - Jiayun Zhong
- State Key Laboratory of Genetic Engineering, Department of Biochemistry, School of Life Sciences, Fudan University, 200438, Shanghai, China
| | - Meihong Chen
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, 5 Dong Dan San Tiao, 100005, Beijing, China
| | - Michael Q Zhang
- MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Bioinformatics Division, BNRist, Department of Automation, Tsinghua University, 100084, Beijing, China. .,MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Medicine, Tsinghua University, 100084, Beijing, China. .,Department of Biological Sciences, Center for Systems Biology, The University of Texas, Dallas 800 West Campbell Road, RL11, Richardson, TX, 75080-3021, USA.
| | - Yong Zhang
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, 5 Dong Dan San Tiao, 100005, Beijing, China.
| | - Yang Chen
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, 5 Dong Dan San Tiao, 100005, Beijing, China. .,MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, Bioinformatics Division, BNRist, Department of Automation, Tsinghua University, 100084, Beijing, China. .,MOE Key Laboratory of Bioinformatics, Center for Synthetic and Systems Biology, School of Medicine, Tsinghua University, 100084, Beijing, China.
| | - Dahai Zhu
- The State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, 5 Dong Dan San Tiao, 100005, Beijing, China. .,Bioland Laboratory (Guangzhou Regenerative Medicine and Health Guangdong Laboratory), 510320, Guangzhou, China.
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49
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Hansen JL, Loell KJ, Cohen BA. A test of the pioneer factor hypothesis using ectopic liver gene activation. eLife 2022; 11:73358. [PMID: 34984978 PMCID: PMC8849321 DOI: 10.7554/elife.73358] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 01/04/2022] [Indexed: 01/07/2023] Open
Abstract
The pioneer factor hypothesis (PFH) states that pioneer factors (PFs) are a subclass of transcription factors (TFs) that bind to and open inaccessible sites and then recruit non-pioneer factors (non-PFs) that activate batteries of silent genes. The PFH predicts that ectopic gene activation requires the sequential activity of qualitatively different TFs. We tested the PFH by expressing the endodermal PF FOXA1 and non-PF HNF4A in K562 lymphoblast cells. While co-expression of FOXA1 and HNF4A activated a burst of endoderm-specific gene expression, we found no evidence for a functional distinction between these two TFs. When expressed independently, both TFs bound and opened inaccessible sites, activated endodermal genes, and ‘pioneered’ for each other, although FOXA1 required fewer copies of its motif for binding. A subset of targets required both TFs, but the predominant mode of action at these targets did not conform to the sequential activity predicted by the PFH. From these results, we hypothesize an alternative to the PFH where ‘pioneer activity’ depends not on categorically different TFs but rather on the affinity of interaction between TF and DNA. Cells only use a fraction of their genetic information to make the proteins they need. The rest is carefully packaged away and tightly bundled in structures called nucleosomes. This physically shields the DNA from being accessed by transcription factors – the molecular actors that can read genes and kickstart the protein production process. Effectively, the genetic sequences inside nucleosomes are being silenced. However, during development, transcription factors must overcome this nucleosome barrier and activate silent genes to program cells. The pioneer factor hypothesis describes how this may be possible: first, ‘pioneer’ transcription factors can bind to and ‘open up’ nucleosomes to make target genes accessible. Then, non-pioneer factors can access the genetic sequence and recruit cofactors that begin copying the now-exposed genetic information. The widely accepted theory is based on studies of two proteins – FOXA1, an archetypal pioneer factor, and HNF4A, a non-pioneer factor – but the predictions of the pioneer factor hypothesis have yet to be explicitly tested. To do so, Hansen et al. expressed FOXA1 and HNF4A, separately and together, in cells which do not usually make these proteins. They then assessed how the proteins could bind to DNA and impact gene accessibility and transcription. The experiments demonstrate that FOXA1 and HNF4A do not necessarily follow the two-step activation predicted by the pioneer factor hypothesis. When expressed independently, both transcription factors bound and opened inaccessible sites, activated target genes, and ‘pioneered’ for each other. Similar patterns were observed across the genome. The only notable distinction between the two factors was that FOXA1, the archetypal pioneering factor, required fewer copies of its target sequence to bind DNA than HNF4A. These findings led Hansen et al. to propose an alternative theory to the pioneer factor hypothesis which eliminates the categorical distinction between pioneer and non-pioneer factors. Overall, this work has implications for how biologists understand the way that transcription factors activate silent genes during development.
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Affiliation(s)
- Jeffrey L Hansen
- Edison Center for Genome Sciences and Systems Biology, Washington University in St. Louis, St. Louis, United States.,Department of Genetics, Washington University in St. Louis, St. Louis, United States.,Medical Scientist Training Program, Washington University in St. Louis, St. Louis, United States
| | - Kaiser J Loell
- Edison Center for Genome Sciences and Systems Biology, Washington University in St. Louis, St. Louis, United States.,Department of Genetics, Washington University in St. Louis, St. Louis, United States
| | - Barak A Cohen
- Edison Center for Genome Sciences and Systems Biology, Washington University in St. Louis, St. Louis, United States.,Department of Genetics, Washington University in St. Louis, St. Louis, United States
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50
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Tost J. Current and Emerging Technologies for the Analysis of the Genome-Wide and Locus-Specific DNA Methylation Patterns. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2022; 1389:395-469. [DOI: 10.1007/978-3-031-11454-0_16] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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