1
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Zhao S, Yang Q, Yu Z, Chu C, Dai S, Li H, Diao M, Feng L, Ke J, Xue Y, Zhou Q, Liu Y, Ma H, Lin CP, Yao YG, Zhong G. Deciphering enhancers of hearing loss genes for efficient and targeted gene therapy of hereditary deafness. Neuron 2025; 113:1579-1596.e5. [PMID: 40262614 DOI: 10.1016/j.neuron.2025.03.023] [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: 12/22/2024] [Revised: 02/23/2025] [Accepted: 03/18/2025] [Indexed: 04/24/2025]
Abstract
Hereditary hearing loss accounts for about 60% of congenital deafness. Although adeno-associated virus (AAV)-mediated gene therapy shows substantial potential for treating genetic hearing impairments, there remain significant concerns regarding the specificity and safety of AAV vectors. The sophisticated nature of the cochlea further complicates the challenge of precisely targeting gene delivery. Here, we introduced an AAV-reporter-based in vivo transcriptional enhancer reconstruction (ARBITER) workflow, enabling efficient and reliable dissection of enhancers. With ARBITER, we successfully demonstrated that the conserved non-coding elements (CNEs) within the gene locus collaboratively regulate the expression of Slc26a5, which was further validated using knockout mouse models. We also assessed the potential of identified enhancers to treat hereditary hearing loss by conducting gene therapy in Slc26a5 mutant mice. Based on the original Slc26a5 enhancer with limited efficiency, we engineered a highly efficient and outer hair cell (OHC)-specific enhancer, B8, which successfully restored hearing of Slc26a5 knockout mice.
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Affiliation(s)
- Simeng Zhao
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China.
| | - Qiuxiang Yang
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Zehua Yu
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Cenfeng Chu
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China
| | - Shengqi Dai
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Hongli Li
- State Key Laboratory of Genetic Evolution and Animal Models, Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Yunnan Engineering Center on Brain Disease Models, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650204, China; National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), and National Resource Center for Non-Human Primates, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, Yunnan, China
| | - Min Diao
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China
| | - Lingyue Feng
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Junzi Ke
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Yilin Xue
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Qifang Zhou
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Yan Liu
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China
| | - Hanhui Ma
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Chao-Po Lin
- School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China
| | - Yong-Gang Yao
- State Key Laboratory of Genetic Evolution and Animal Models, Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Yunnan Engineering Center on Brain Disease Models, KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650204, China; National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), and National Resource Center for Non-Human Primates, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650107, Yunnan, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming 650204, Yunnan, China
| | - Guisheng Zhong
- iHuman Institute, ShanghaiTech University, Shanghai 201210, China; School of Life Science and Technology, ShanghaiTech University, Shanghai 201210, China; Shanghai Clinical Research and Trial Center, Shanghai 201210, China; Shanghai Key Laboratory of High-Resolution Electron Microscopy, ShanghaiTech University, Shanghai 201210, China; Shanghai Key Laboratory of Gene Editing and Cell Therapy for Rare Diseases, Fudan University, Shanghai 20031, China.
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2
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Xie Y, Tucciarone L, Farah EN, Chang L, Yang Q, Shankar TS, Elison W, Tran S, Djulamsah J, Lie A, Loe T, Holman AR, Corban S, Buchanan J, Mamde S, Zhou H, Elgamal RM, Tseliou E, Huang V, Wang Z, Chiu J, Melton R, Griffin E, Zhang Q, Lucero J, Navankasattusas S, Li D, Seng C, Destici E, Selzman CH, D’Antonio-Chronowska A, Wang T, Wang A, Drakos SG, Gaulton KJ, Ren B, Chi NC. Single cell multiomics and 3D genome architecture reveal novel pathways of human heart failure. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.05.08.25327176. [PMID: 40385400 PMCID: PMC12083629 DOI: 10.1101/2025.05.08.25327176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 05/20/2025]
Abstract
Heart failure is a leading cause of morbidity and mortality; yet gene regulatory mechanisms driving cell type-specific pathologic responses remain undefined. Here, we present the cell type-resolved transcriptomes, chromatin accessibility, histone modifications and chromatin organization of 36 non-failing and failing human hearts profiled from 776,479 cells spanning all cardiac chambers. Integrative analyses revealed dynamic changes in cell type composition, gene regulatory programs and chromatin organization, which expanded the annotation of cardiac cis-regulatory sequences by ten-fold and mapped cell type-specific enhancer-gene interactions. Cardiomyocytes and fibroblasts particularly exhibited complex disease-associated cellular states, gene regulatory programs and global chromatin reorganization. Mapping genetic association data onto cell type-specific regulatory programs revealed likely causal genetic contributors to heart failure. Together, these findings provide comprehensive, multimodal gene regulatory maps of the human heart in health and disease, offering a valuable framework for designing precise cell type-targeted therapies for treating heart failure.
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Affiliation(s)
- Yang Xie
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Luca Tucciarone
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Elie N. Farah
- Department of Medicine, Division of Cardiology, University of California San Diego, La Jolla, CA, USA
| | - Lei Chang
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Qian Yang
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Thirupura S. Shankar
- Nora Eccles Harrison Cardiovascular Research and Training Institute (CVRTI), University of Utah, Salt Lake City, UT, USA
| | - Weston Elison
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA
| | - Shaina Tran
- Department of Medicine, Division of Cardiology, University of California San Diego, La Jolla, CA, USA
| | - Jovina Djulamsah
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Audrey Lie
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Timothy Loe
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Alyssa R. Holman
- Department of Medicine, Division of Cardiology, University of California San Diego, La Jolla, CA, USA
| | - Sierra Corban
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Justin Buchanan
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Sainath Mamde
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Bioengineering Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Haowen Zhou
- Department of Medicine, Division of Cardiology, University of California San Diego, La Jolla, CA, USA
| | - Ruth M. Elgamal
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA
| | - Eleni Tseliou
- Nora Eccles Harrison Cardiovascular Research and Training Institute (CVRTI), University of Utah, Salt Lake City, UT, USA
- Division of Cardiovascular Medicine, University of Utah, Salt Lake City, UT, USA
| | - Vincent Huang
- Nora Eccles Harrison Cardiovascular Research and Training Institute (CVRTI), University of Utah, Salt Lake City, UT, USA
- Division of Cardiovascular Medicine, University of Utah, Salt Lake City, UT, USA
| | - Zhaoning Wang
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Jeffery Chiu
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA
| | - Rebecca Melton
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA
| | - Emily Griffin
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Qingquan Zhang
- Department of Medicine, Division of Cardiology, University of California San Diego, La Jolla, CA, USA
| | - Jacinta Lucero
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Sutip Navankasattusas
- Nora Eccles Harrison Cardiovascular Research and Training Institute (CVRTI), University of Utah, Salt Lake City, UT, USA
| | - Daofeng Li
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Chanrung Seng
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
| | - Eugin Destici
- Department of Medicine, Division of Cardiology, University of California San Diego, La Jolla, CA, USA
| | - Craig H. Selzman
- Nora Eccles Harrison Cardiovascular Research and Training Institute (CVRTI), University of Utah, Salt Lake City, UT, USA
- Division of Cardiothoracic Surgery, University of Utah, Salt Lake City, UT, USA
| | - Agnieszka D’Antonio-Chronowska
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Ting Wang
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO, USA
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA
| | - Allen Wang
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Stavros G. Drakos
- Nora Eccles Harrison Cardiovascular Research and Training Institute (CVRTI), University of Utah, Salt Lake City, UT, USA
- Division of Cardiovascular Medicine, University of Utah, Salt Lake City, UT, USA
| | - Kyle J. Gaulton
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, School of Medicine, University of California San Diego, La Jolla, CA, USA
- Moores Cancer Center, University of California San Diego, La Jolla, CA, USA
- New York Genome Center, New York, NY, USA
- Department of Genetics and Development, Systems Biology, Biochemistry and Molecular Biophysics, Columbia University Irving Medical Center, New York, NY, USA
| | - Neil C. Chi
- Department of Medicine, Division of Cardiology, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, School of Medicine, University of California San Diego, La Jolla, CA, USA
- Institute of Engineering in Medicine, University of California, San Diego, La Jolla, CA
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3
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Dincer TU, Ernst J. ChromActivity: integrative epigenomic and functional characterization assay based annotation of regulatory activity across diverse human cell types. Genome Biol 2025; 26:123. [PMID: 40346707 PMCID: PMC12063466 DOI: 10.1186/s13059-025-03579-6] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 04/15/2025] [Indexed: 05/11/2025] Open
Abstract
We introduce ChromActivity, a computational framework for predicting and annotating regulatory activity across the genome through integration of multiple epigenomic maps and various functional characterization datasets. ChromActivity generates genomewide predictions of regulatory activity associated with each functional characterization dataset across many cell types based on available epigenomic data. It then for each cell type produces ChromScoreHMM genome annotations based on the combinatorial and spatial patterns within these predictions and ChromScore tracks of overall predicted regulatory activity. ChromActivity provides a resource for analyzing and interpreting the human regulatory genome across diverse cell types.
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Affiliation(s)
- Tevfik Umut Dincer
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Jason Ernst
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Department of Biological Chemistry, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research at University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Computer Science Department, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
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4
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Iyer AR, Gurumurthy A, Chu SCA, Kodgule R, Aguilar AR, Saari T, Ramzan A, Rosa J, Gupta J, Emmanuel A, Hall CN, Runge JS, Owczarczyk AB, Cho JW, Weiss MB, Anyoha R, Sikkink K, Gemus S, Fulco CP, Perry AM, Schmitt AD, Engreitz JM, Brown NA, Cieslik MP, Ryan RJ. Selective Enhancer Dependencies in MYC-Intact and MYC-Rearranged Germinal Center B-cell Diffuse Large B-cell Lymphoma. Blood Cancer Discov 2025; 6:233-253. [PMID: 40067173 PMCID: PMC12050968 DOI: 10.1158/2643-3230.bcd-24-0126] [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: 05/27/2024] [Revised: 12/28/2024] [Accepted: 03/10/2025] [Indexed: 03/15/2025] Open
Abstract
SIGNIFICANCE Aberrant MYC activity defines the most aggressive GCB-DLBCLs. We characterized a mechanism of MYC transcriptional activation via a native enhancer that is active in MYC-intact GCB-DLBCL, establishing fitness-sustaining cis- and trans-regulatory circuitry in GCB-DLBCL models that lack MYC enhancer-hijacking rearrangement. See related commentary by Mulet-Lazaro and Delwel, p. 149.
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Affiliation(s)
- Ashwin R. Iyer
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Aishwarya Gurumurthy
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Shih-Chun A. Chu
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Rohan Kodgule
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Athalee R. Aguilar
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Travis Saari
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Abdullah Ramzan
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Jan Rosa
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Juhi Gupta
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Arvind Emmanuel
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Cody N. Hall
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - John S. Runge
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Anna B. Owczarczyk
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Jang W. Cho
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Matthew B. Weiss
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Rockwell Anyoha
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
| | | | | | - Charles P. Fulco
- Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts
| | - Anamarija M. Perry
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | | | - Jesse M. Engreitz
- Department of Genetics, Stanford University School of Medicine, Stanford, California
- BASE Initiative, Betty Irene Moore Children’s Heart Center, Lucile Packard Children’s Hospital, Stanford, California
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Noah A. Brown
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Marcin P. Cieslik
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Russell J.H. Ryan
- Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan
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5
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Hossain MJ, Romanov KA, Jian J, Swaby LC, Bandyopadhyay S, Guan I, Thomas SM, Olive AJ, O’Connor TJ. Bacterial pathogens hijack host cell peroxisomes for replication vacuole expansion and integrity. SCIENCE ADVANCES 2025; 11:eadr8005. [PMID: 40305606 PMCID: PMC12042894 DOI: 10.1126/sciadv.adr8005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/16/2024] [Accepted: 03/26/2025] [Indexed: 05/02/2025]
Abstract
Pathogens manipulate host cell organelles to establish infection. There is extensive evidence of pathogen modulation of the endoplasmic reticulum, Golgi apparatus, mitochondria, endosomes, lysosomes, and nucleus. However, one organelle that has been largely overlooked in connection with bacterial pathogenesis is peroxisomes. Here, we demonstrate that Legionella actively recruits peroxisomes to its replication vacuole using a secreted bacterial effector protein. Defects in peroxisome metabolic function restrict expansion of the Legionella vacuole membrane and cause rupture of this compartment, inhibiting bacterial replication and leading to bacterial degradation. Similarly, peroxisome dysfunction causes Salmonella replication vacuole destabilization and reduced bacterial burden within host cells. Thus, these two intracellular bacterial pathogens exploit host cell peroxisomes to maintain their replication compartments, establishing a critical role for this organelle in disease.
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Affiliation(s)
- Mohammad J. Hossain
- Department of Biological Chemistry, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Katerina A. Romanov
- Department of Biological Chemistry, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jeffrey Jian
- Department of Biological Chemistry, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Louis C. Swaby
- Department of Biological Chemistry, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Saumya Bandyopadhyay
- Department of Biological Chemistry, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ivan Guan
- Department of Biological Chemistry, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Sean M. Thomas
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
| | - Andrew J. Olive
- Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, USA
| | - Tamara J. O’Connor
- Department of Biological Chemistry, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
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6
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Roy J, Kumar A, Chakravarty S, Biswas NK, Goswami S, Mazumder A. Dynamic interaction of MYC enhancer RNA with YEATS2 protein regulates MYC gene transcription in pancreatic cancer. EMBO Rep 2025; 26:2519-2544. [PMID: 40216980 PMCID: PMC12117045 DOI: 10.1038/s44319-025-00446-0] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2024] [Revised: 03/26/2025] [Accepted: 03/31/2025] [Indexed: 05/29/2025] Open
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is one of the most prevalent and aggressive forms of pancreatic cancer with low survival rates and limited treatment options. Aberrant expression of the MYC oncogene promotes PDAC progression. Recent reports have established a role for enhancer RNAs (eRNAs), originating from active enhancers, in controlling gene transcription. Here we show that a novel MYC eRNA regulates MYC gene expression during chronic inflammatory conditions in pancreatic cancer cells. A higher amount of MYC eRNA is observed in chronic pancreatitis and in pancreatic cancer patients. We show that MYC eRNA interacts with YEATS2, a histone reader protein of the ATAC-HAT complex, and augments the association of YEATS2-containing ATAC complexes with MYC promoter/enhancer regions and thus increases MYC gene expression. TNF-α induced Tyrosine dephosphorylation of the YEATS domain increases MYC eRNA binding to the YEATS2 protein in pancreatic cancer cells. Our study adds another regulatory layer of MYC gene expression by enhancer-driven transcription.
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Affiliation(s)
- Jayita Roy
- Biotechnology Research and Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, West Bengal, 741251, India
- Regional Centre for Biotechnology, Faridabad, Haryana, 121001, India
| | - Aniket Kumar
- Biotechnology Research and Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, West Bengal, 741251, India
- Regional Centre for Biotechnology, Faridabad, Haryana, 121001, India
| | - Shouvik Chakravarty
- Biotechnology Research and Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, West Bengal, 741251, India
- Regional Centre for Biotechnology, Faridabad, Haryana, 121001, India
| | - Nidhan K Biswas
- Biotechnology Research and Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, West Bengal, 741251, India
- Regional Centre for Biotechnology, Faridabad, Haryana, 121001, India
| | - Srikanta Goswami
- Biotechnology Research and Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, West Bengal, 741251, India.
- Regional Centre for Biotechnology, Faridabad, Haryana, 121001, India.
| | - Anup Mazumder
- Biotechnology Research and Innovation Council-National Institute of Biomedical Genomics (BRIC-NIBMG), Kalyani, West Bengal, 741251, India.
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7
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Martyn GE, Montgomery MT, Jones H, Guo K, Doughty BR, Linder J, Bisht D, Xia F, Cai XS, Chen Z, Cochran K, Lawrence KA, Munson G, Pampari A, Fulco CP, Sahni N, Kelley DR, Lander ES, Kundaje A, Engreitz JM. Rewriting regulatory DNA to dissect and reprogram gene expression. Cell 2025:S0092-8674(25)00352-6. [PMID: 40245860 DOI: 10.1016/j.cell.2025.03.034] [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: 12/20/2023] [Revised: 12/16/2024] [Accepted: 03/19/2025] [Indexed: 04/19/2025]
Abstract
Regulatory DNA provides a platform for transcription factor binding to encode cell-type-specific patterns of gene expression. However, the effects and programmability of regulatory DNA sequences remain difficult to map or predict. Here, we develop variant effects from flow-sorting experiments with CRISPR targeting screens (Variant-EFFECTS) to introduce hundreds of designed edits to endogenous regulatory DNA and quantify their effects on gene expression. We systematically dissect and reprogram 3 regulatory elements for 2 genes in 2 cell types. These data reveal endogenous binding sites with effects specific to genomic context, transcription factor motifs with cell-type-specific activities, and limitations of computational models for predicting the effect sizes of variants. We identify small edits that can tune gene expression over a large dynamic range, suggesting new possibilities for prime-editing-based therapeutics targeting regulatory DNA. Variant-EFFECTS provides a generalizable tool to dissect regulatory DNA and to identify genome editing reagents that tune gene expression in an endogenous context.
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Affiliation(s)
- Gabriella E Martyn
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA 94305, USA
| | - Michael T Montgomery
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA 94305, USA
| | - Hank Jones
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA 94305, USA
| | - Katherine Guo
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA 94305, USA
| | - Benjamin R Doughty
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Johannes Linder
- Calico Life Sciences LLC, South San Francisco, CA 94080, USA
| | - Deepa Bisht
- Department of Genitourinary Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA
| | - Fan Xia
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA 94305, USA
| | - Xiangmeng S Cai
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA 94305, USA; Department of Bioengineering, Stanford University, Stanford, CA 94305, USA
| | - Ziwei Chen
- Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Kelly Cochran
- Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Kathryn A Lawrence
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Glen Munson
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Anusri Pampari
- Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Charles P Fulco
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Nidhi Sahni
- Department of Epigenetics and Molecular Carcinogenesis, The University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA; Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77230, USA; Quantitative and Computational Biosciences Program, Baylor College of Medicine, Houston, TX 77030, USA
| | - David R Kelley
- Calico Life Sciences LLC, South San Francisco, CA 94080, USA
| | - Eric S Lander
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Biology, MIT, Cambridge, MA 02139, USA; Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | - Jesse M Engreitz
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA; Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA 94305, USA; Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Stanford Cardiovascular Institute, Stanford University, Stanford, CA 94305, USA.
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8
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Saini A, Hopkins LS, Serna VA, McCullen MVD, Selner NG, Bhattarai B, Fachi JL, Glynn R, Hayer KE, Bassing CH, Colonna M, Oltz EM. Cell type-specific enhancers regulate IL-22 expression in innate and adaptive lymphoid cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.04.02.646834. [PMID: 40291691 PMCID: PMC12026504 DOI: 10.1101/2025.04.02.646834] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/30/2025]
Abstract
IL-22, a signature cytokine of type 3 lymphoid cells, mediates epithelial homeostasis and protective pathogen responses in barrier tissues, while its deregulated expression drives chronic inflammation associated with colitis and psoriasis. Despite its therapeutic value, little is known about regulatory elements for IL-22 expression. We identify two conserved enhancers, E22-1 and E22-2, which differentially regulate Il22 in type 3 lymphoid subsets. These enhancers are required for steady-state expression of gut antimicrobial peptides, protection from C. rodentium infection, and development of IL-22-mediated psoriasis. E22-1 resembles many known enhancers, functioning in both Th-ILC counterparts. However, E22-2 is only required for IL-22 expression in ILC3s. Its ILC3 restriction relies on multiple Runx3 sites, combined with the lack of a functional RORγt motif, which is present in E22-1. Thus, although responding to similar stimuli, type 3 lymphoid cells use distinct cis-elements for IL-22 expression, with E22-2 likely serving as a homeostatic enhancer in barrier tissues.
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9
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Breves SL, Di Giammartino DC, Nicholson J, Cirigliano S, Mahmood SR, Lee UJ, Martinez-Fundichely A, Jungverdorben J, Singhania R, Rajkumar S, Kirou R, Studer L, Khurana E, Polyzos A, Fine HA, Apostolou E. Three-dimensional regulatory hubs support oncogenic programs in glioblastoma. Mol Cell 2025; 85:1330-1348.e6. [PMID: 40147440 PMCID: PMC12009607 DOI: 10.1016/j.molcel.2025.03.007] [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: 04/29/2024] [Revised: 12/18/2024] [Accepted: 03/05/2025] [Indexed: 03/29/2025]
Abstract
Dysregulation of enhancer-promoter communication in the three-dimensional (3D) nucleus is increasingly recognized as a potential driver of oncogenic programs. Here, we profiled the 3D enhancer-promoter networks of patient-derived glioblastoma stem cells to identify central regulatory nodes. We focused on hyperconnected 3D hubs and demonstrated that hub-interacting genes exhibit high and coordinated expression at the single-cell level and are associated with oncogenic programs that distinguish glioblastoma from low-grade glioma. Epigenetic silencing of a recurrent hub-with an uncharacterized role in glioblastoma-was sufficient to cause downregulation of hub-connected genes, shifts in transcriptional states, and reduced clonogenicity. Integration of datasets across 16 cancers identified "universal" and cancer-type-specific 3D hubs that enrich for oncogenic programs and factors associated with worse prognosis. Genetic alterations could explain only a small fraction of hub hyperconnectivity and increased activity. Overall, our study provides strong support for the potential central role of 3D regulatory hubs in controlling oncogenic programs and properties.
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Affiliation(s)
- Sarah L Breves
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Physiology, Biophysics and Systems Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, NY, USA; Department of Surgery, New York-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA; Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Dafne Campigli Di Giammartino
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - James Nicholson
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Meyer Cancer Center, Division of Neuro-Oncology, Department of Neurology, Sandra and Edward Meyer Cancer Center, New York-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA
| | - Stefano Cirigliano
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Meyer Cancer Center, Division of Neuro-Oncology, Department of Neurology, Sandra and Edward Meyer Cancer Center, New York-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA
| | - Syed Raza Mahmood
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Uk Jin Lee
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Alexander Martinez-Fundichely
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA; Caryl and Israel Englander Institute for Precision Medicine, New York-Presbyterian Hospital, Weill Cornell Medicine, New York, NY 10065, USA; Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY 10065, USA
| | - Johannes Jungverdorben
- Center for Stem Cell Biology, Developmental Biology Program, Sloan Kettering Institute for Cancer Research, New York, NY, USA
| | - Richa Singhania
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Meyer Cancer Center, Division of Neuro-Oncology, Department of Neurology, Sandra and Edward Meyer Cancer Center, New York-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA
| | - Sandy Rajkumar
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Raphael Kirou
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Lorenz Studer
- Center for Stem Cell Biology, Developmental Biology Program, Sloan Kettering Institute for Cancer Research, New York, NY, USA
| | - Ekta Khurana
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY 10021, USA; Caryl and Israel Englander Institute for Precision Medicine, New York-Presbyterian Hospital, Weill Cornell Medicine, New York, NY 10065, USA; Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY 10065, USA
| | - Alexander Polyzos
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Howard A Fine
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Meyer Cancer Center, Division of Neuro-Oncology, Department of Neurology, Sandra and Edward Meyer Cancer Center, New York-Presbyterian Hospital, Weill Cornell Medicine, New York, NY, USA.
| | - Effie Apostolou
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA; Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA.
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10
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Linder J, Srivastava D, Yuan H, Agarwal V, Kelley DR. Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation. Nat Genet 2025; 57:949-961. [PMID: 39779956 PMCID: PMC11985352 DOI: 10.1038/s41588-024-02053-6] [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: 08/28/2023] [Accepted: 12/04/2024] [Indexed: 01/11/2025]
Abstract
Sequence-based machine-learning models trained on genomics data improve genetic variant interpretation by providing functional predictions describing their impact on the cis-regulatory code. However, current tools do not predict RNA-seq expression profiles because of modeling challenges. Here, we introduce Borzoi, a model that learns to predict cell-type-specific and tissue-specific RNA-seq coverage from DNA sequence. Using statistics derived from Borzoi's predicted coverage, we isolate and accurately score DNA variant effects across multiple layers of regulation, including transcription, splicing and polyadenylation. Evaluated on quantitative trait loci, Borzoi is competitive with and often outperforms state-of-the-art models trained on individual regulatory functions. By applying attribution methods to the derived statistics, we extract cis-regulatory motifs driving RNA expression and post-transcriptional regulation in normal tissues. The wide availability of RNA-seq data across species, conditions and assays profiling specific aspects of regulation emphasizes the potential of this approach to decipher the mapping from DNA sequence to regulatory function.
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Affiliation(s)
| | | | - Han Yuan
- Calico Life Sciences LLC, South San Francisco, CA, USA
| | - Vikram Agarwal
- mRNA Center of Excellence, Sanofi Pasteur Inc., Cambridge, MA, USA
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11
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Villegas NK, Gaudreault YR, Keller A, Kearns P, Stapleton JA, Plesa C. Optimizing in vitro Transcribed CRISPR-Cas9 Single-Guide RNA Libraries for Improved Uniformity and Affordability. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.03.24.644170. [PMID: 40196484 PMCID: PMC11974757 DOI: 10.1101/2025.03.24.644170] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 04/09/2025]
Abstract
We describe a scalable and cost-effective sgRNA synthesis workflow that reduces costs by over 70% through the use of large pools of microarray-derived oligos encoding unique sgRNA spacers. These subpool oligos are assembled into full-length dsDNA templates via Golden Gate Assembly before in vitro transcription with T7 RNA polymerase. RNA-seq analysis reveals severe biases in spacer representation, with some spacers being highly overrepresented while others are completely absent. Consistent with previous studies, we identify guanine-rich sequences within the first four nucleotides of the spacer, immediately downstream of the T7 promoter, as the primary driver of this bias. To address this issue, we introduced a guanine tetramer upstream of all spacers, which reduced bias by an average of 19% in sgRNA libraries containing 389 spacers. However, this modification also increased the presence of high-molecular-weight RNA species after transcription. We also tested two alternative bias-reduction strategies: compartmentalizing spacers within emulsions and optimizing DNA input and reaction volumes. Both methods independently reduced bias in 2,626-plex sgRNA libraries, though to a lesser extent than the guanine tetramer approach. These advancements enhance both the affordability and uniformity of sgRNA libraries, with broad implications for improving CRISPR-Cas9 screens and optimizing guide RNA design for other CRISPR and nuclease systems.
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Affiliation(s)
- Natanya K. Villegas
- Department of Bioengineering, Phil and Penny Knight Campus for Accelerating Scientific Impact, University of Oregon, 1505 Franklin Blvd., Eugene, OR 97403, USA
- Institute of Molecular Biology, University of Oregon 1229 University of Oregon, 1318 Franklin Blvd., Room 273, Onyx Bridge, Eugene, OR 97403, USA
- Biology Department, University of Oregon 1210 University of Oregon, 77 Klamath Hall, Eugene, OR 97403, USA
| | - Yukiko R. Gaudreault
- Department of Bioengineering, Phil and Penny Knight Campus for Accelerating Scientific Impact, University of Oregon, 1505 Franklin Blvd., Eugene, OR 97403, USA
| | - Abigail Keller
- Department of Bioengineering, Phil and Penny Knight Campus for Accelerating Scientific Impact, University of Oregon, 1505 Franklin Blvd., Eugene, OR 97403, USA
| | - Phillip Kearns
- Department of Bioengineering, Phil and Penny Knight Campus for Accelerating Scientific Impact, University of Oregon, 1505 Franklin Blvd., Eugene, OR 97403, USA
| | - James A. Stapleton
- Department of Bioengineering, Phil and Penny Knight Campus for Accelerating Scientific Impact, University of Oregon, 1505 Franklin Blvd., Eugene, OR 97403, USA
| | - Calin Plesa
- Department of Bioengineering, Phil and Penny Knight Campus for Accelerating Scientific Impact, University of Oregon, 1505 Franklin Blvd., Eugene, OR 97403, USA
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12
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Paramo MI, Leung AKY, Shah SR, Zhang J, Tippens ND, Liang J, Yao L, Jin Y, Pan X, Ozer A, Lis JT, Yu H. Simultaneous measurement of intrinsic promoter and enhancer potential reveals principles of functional duality and regulatory reciprocity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.03.14.643265. [PMID: 40161809 PMCID: PMC11952525 DOI: 10.1101/2025.03.14.643265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/02/2025]
Abstract
Growing evidence indicates that transcriptional regulatory elements can exert both promoter and enhancer activity; however, the relationship and determinants of this dual functionality remain poorly understood. We developed a massively parallel dual reporter assay that enables simultaneous assessment of the intrinsic promoter and enhancer potential exerted by the same sequence. Parallel quantification for thousands of elements reveals that canonical human promoters and enhancers can act as both promoters and enhancers under the same contexts, and that promoter activity may be necessary but not sufficient for enhancer function. We find that regulatory potential is intrinsic to element sequences, irrespective of downstream features typically associated with distinct element classes. Perturbations to element transcription factor binding motifs lead to disruptions in both activities, implicating a shared syntax for the two regulatory functions. Combinations of elements with different minimal promoters reveal reciprocal activity modulation between associated elements and a strong positive correlation between promoter and enhancer functions imply a bidirectional feedback loop used to maintain environments of high transcriptional activity. Finally, our results indicate that the magnitude and balance between promoter and enhancer functions are shaped by both intrinsic sequence properties and contextual regulatory influences, suggesting a degree of plasticity in regulatory action. Our approach provides a new lens for understanding fundamental principles of regulatory element biology.
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13
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Agarwal V, Inoue F, Schubach M, Penzar D, Martin BK, Dash PM, Keukeleire P, Zhang Z, Sohota A, Zhao J, Georgakopoulos-Soares I, Noble WS, Yardımcı GG, Kulakovskiy IV, Kircher M, Shendure J, Ahituv N. Massively parallel characterization of transcriptional regulatory elements. Nature 2025; 639:411-420. [PMID: 39814889 PMCID: PMC11903340 DOI: 10.1038/s41586-024-08430-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Accepted: 11/20/2024] [Indexed: 01/18/2025]
Abstract
The human genome contains millions of candidate cis-regulatory elements (cCREs) with cell-type-specific activities that shape both health and many disease states1. However, we lack a functional understanding of the sequence features that control the activity and cell-type-specific features of these cCREs. Here we used lentivirus-based massively parallel reporter assays (lentiMPRAs) to test the regulatory activity of more than 680,000 sequences, representing an extensive set of annotated cCREs among three cell types (HepG2, K562 and WTC11), and found that 41.7% of these sequences were active. By testing sequences in both orientations, we find promoters to have strand-orientation biases and their 200-nucleotide cores to function as non-cell-type-specific 'on switches' that provide similar expression levels to their associated gene. By contrast, enhancers have weaker orientation biases, but increased tissue-specific characteristics. Utilizing our lentiMPRA data, we develop sequence-based models to predict cCRE function and variant effects with high accuracy, delineate regulatory motifs and model their combinatorial effects. Testing a lentiMPRA library encompassing 60,000 cCREs in all three cell types further identified factors that determine cell-type specificity. Collectively, our work provides an extensive catalogue of functional CREs in three widely used cell lines and showcases how large-scale functional measurements can be used to dissect regulatory grammar.
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Affiliation(s)
- Vikram Agarwal
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- mRNA Center of Excellence, Sanofi, Waltham, MA, USA.
| | - Fumitaka Inoue
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan
| | - Max Schubach
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Dmitry Penzar
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia
- Institute of Protein Research, Russian Academy of Sciences, Pushchino, Russia
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, Moscow, Russia
| | - Beth K Martin
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Pyaree Mohan Dash
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Pia Keukeleire
- Institute of Human Genetics, University Medical Center Schleswig-Holstein, University of Lübeck, Lübeck, Germany
| | - Zicong Zhang
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan
| | - Ajuni Sohota
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Jingjing Zhao
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Ilias Georgakopoulos-Soares
- Institute for Personalized Medicine, Department of Biochemistry and Molecular Biology, The Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - William S Noble
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
| | - Galip Gürkan Yardımcı
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Knight Cancer Institute, Oregon Health and Science University, Portland, OR, USA
- Cancer Early Detection Advanced Research Center, Oregon Health and Science University, Portland, OR, USA
| | - Ivan V Kulakovskiy
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia
- Institute of Protein Research, Russian Academy of Sciences, Pushchino, Russia
- Life Improvement by Future Technologies (LIFT) Center, Moscow, Russia
| | - Martin Kircher
- Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
- Institute of Human Genetics, University Medical Center Schleswig-Holstein, University of Lübeck, Lübeck, Germany
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- Howard Hughes Medical Institute, Seattle, WA, USA.
- Brotman Baty Institute for Precision Medicine, University of Washington, Seattle, WA, USA.
- Seattle Hub for Synthetic Biology, Seattle, Washington, USA.
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA.
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
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14
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Pacalin NM, Steinhart Z, Shi Q, Belk JA, Dorovskyi D, Kraft K, Parker KR, Shy BR, Marson A, Chang HY. Bidirectional epigenetic editing reveals hierarchies in gene regulation. Nat Biotechnol 2025; 43:355-368. [PMID: 38760566 PMCID: PMC11569274 DOI: 10.1038/s41587-024-02213-3] [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: 11/15/2022] [Accepted: 03/19/2024] [Indexed: 05/19/2024]
Abstract
CRISPR perturbation methods are limited in their ability to study non-coding elements and genetic interactions. In this study, we developed a system for bidirectional epigenetic editing, called CRISPRai, in which we apply activating (CRISPRa) and repressive (CRISPRi) perturbations to two loci simultaneously in the same cell. We developed CRISPRai Perturb-seq by coupling dual perturbation gRNA detection with single-cell RNA sequencing, enabling study of pooled perturbations in a mixed single-cell population. We applied this platform to study the genetic interaction between two hematopoietic lineage transcription factors, SPI1 and GATA1, and discovered novel characteristics of their co-regulation on downstream target genes, including differences in SPI1 and GATA1 occupancy at genes that are regulated through different modes. We also studied the regulatory landscape of IL2 (interleukin-2) in Jurkat T cells, primary T cells and chimeric antigen receptor (CAR) T cells and elucidated mechanisms of enhancer-mediated IL2 gene regulation. CRISPRai facilitates investigation of context-specific genetic interactions, provides new insights into gene regulation and will enable exploration of non-coding disease-associated variants.
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Affiliation(s)
- Naomi M Pacalin
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Zachary Steinhart
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
| | - Quanming Shi
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Julia A Belk
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Dmytro Dorovskyi
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Katerina Kraft
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - Kevin R Parker
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
- Program in Epithelial Biology, Stanford University School of Medicine, Stanford, CA, USA
- Cartography Biosciences, Inc., South San Francisco, CA, USA
| | - Brian R Shy
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Alexander Marson
- Gladstone-UCSF Institute of Genomic Immunology, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Parker Institute for Cancer Immunotherapy, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, CA, USA
- Diabetes Center, University of California, San Francisco, San Francisco, CA, USA
- Innovative Genomics Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
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15
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Hsiung CCS, Wilson CM, Sambold NA, Dai R, Chen Q, Teyssier N, Misiukiewicz S, Arab A, O'Loughlin T, Cofsky JC, Shi J, Gilbert LA. Engineered CRISPR-Cas12a for higher-order combinatorial chromatin perturbations. Nat Biotechnol 2025; 43:369-383. [PMID: 38760567 PMCID: PMC11919711 DOI: 10.1038/s41587-024-02224-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Accepted: 03/28/2024] [Indexed: 05/19/2024]
Abstract
Multiplexed genetic perturbations are critical for testing functional interactions among coding or non-coding genetic elements. Compared to double-stranded DNA cutting, repressive chromatin formation using CRISPR interference (CRISPRi) avoids genotoxicity and is more effective for perturbing non-coding regulatory elements in pooled assays. However, current CRISPRi pooled screening approaches are limited to targeting one to three genomic sites per cell. We engineer an Acidaminococcus Cas12a (AsCas12a) variant, multiplexed transcriptional interference AsCas12a (multiAsCas12a), that incorporates R1226A, a mutation that stabilizes the ribonucleoprotein-DNA complex via DNA nicking. The multiAsCas12a-KRAB fusion improves CRISPRi activity over DNase-dead AsCas12a-KRAB fusions, often rescuing the activities of lentivirally delivered CRISPR RNAs (crRNA) that are inactive when used with the latter. multiAsCas12a-KRAB supports CRISPRi using 6-plex crRNA arrays in high-throughput pooled screens. Using multiAsCas12a-KRAB, we discover enhancer elements and dissect the combinatorial function of cis-regulatory elements in human cells. These results instantiate a group testing framework for efficiently surveying numerous combinations of chromatin perturbations for biological discovery and engineering.
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Affiliation(s)
- C C-S Hsiung
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
- Department of Urology, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Arc Institute, Palo Alto, CA, USA
| | - C M Wilson
- Department of Urology, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Arc Institute, Palo Alto, CA, USA
- Tetrad Graduate Program, University of California, San Francisco, CA, USA
| | | | - R Dai
- Department of Urology, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Arc Institute, Palo Alto, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - Q Chen
- Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - N Teyssier
- Biological and Medical Informatics Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - S Misiukiewicz
- Department of Urology, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA
| | - A Arab
- Arc Institute, Palo Alto, CA, USA
| | - T O'Loughlin
- Department of Urology, University of California, San Francisco, CA, USA
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - J C Cofsky
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, USA
| | - J Shi
- Department of Cancer Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - L A Gilbert
- Department of Urology, University of California, San Francisco, CA, USA.
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
- Arc Institute, Palo Alto, CA, USA.
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16
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Caragine CM, Le VT, Mustafa M, Diaz BJ, Morris JA, Müller S, Mendez-Mancilla A, Geller E, Liscovitch-Brauer N, Sanjana NE. Comprehensive dissection of cis-regulatory elements in a 2.8 Mb topologically associated domain in six human cancers. Nat Commun 2025; 16:1611. [PMID: 39948336 PMCID: PMC11825950 DOI: 10.1038/s41467-025-56568-5] [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: 11/14/2023] [Accepted: 01/22/2025] [Indexed: 02/16/2025] Open
Abstract
Cis-regulatory elements (CREs), such as enhancers and promoters, are fundamental regulators of gene expression and, across different cell types, the MYC locus utilizes a diverse regulatory architecture driven by multiple CREs. To better understand differences in CRE function, we perform pooled CRISPR inhibition (CRISPRi) screens to comprehensively probe the 2.8 Mb topologically-associated domain containing MYC in 6 human cancer cell lines with nucleotide resolution. We map 32 CREs where inhibition leads to changes in cell growth, including 8 that overlap previously identified enhancers. Targeting specific CREs decreases MYC expression by as much as 60%, and cell growth by as much as 50%. Using 3-D enhancer contact mapping, we find that these CREs almost always contact MYC but less than 10% of total MYC contacts impact growth when silenced, highlighting the utility of our approach to identify phenotypically-relevant CREs. We also detect an enrichment of lineage-specific transcription factors (TFs) at MYC CREs and, for some of these TFs, find a strong, tumor-specific correlation between TF and MYC expression not found in normal tissue. Taken together, these CREs represent systematically identified, functional regulatory regions and demonstrate how the same region of the human genome can give rise to complex, tissue-specific gene regulation.
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Affiliation(s)
- Christina M Caragine
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA
| | - Victoria T Le
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA
| | - Meer Mustafa
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA
| | - Bianca Jay Diaz
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA
| | - John A Morris
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA
| | - Simon Müller
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA
| | - Alejandro Mendez-Mancilla
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA
| | - Evan Geller
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA
| | - Noa Liscovitch-Brauer
- New York Genome Center, New York, NY, USA
- Department of Biology, New York University, New York, NY, USA
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA
| | - Neville E Sanjana
- New York Genome Center, New York, NY, USA.
- Department of Biology, New York University, New York, NY, USA.
- Department of Neuroscience and Physiology, New York University School of Medicine, New York, NY, USA.
- Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA.
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17
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Rohm D, Black JB, McCutcheon SR, Barrera A, Berry SS, Morone DJ, Nuttle X, de Esch CE, Tai DJC, Talkowski ME, Iglesias N, Gersbach CA. Activation of the imprinted Prader-Willi syndrome locus by CRISPR-based epigenome editing. CELL GENOMICS 2025; 5:100770. [PMID: 39947136 PMCID: PMC11872474 DOI: 10.1016/j.xgen.2025.100770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Revised: 10/01/2024] [Accepted: 01/17/2025] [Indexed: 02/19/2025]
Abstract
Epigenome editing with DNA-targeting technologies such as CRISPR-dCas9 can be used to dissect gene regulatory mechanisms and potentially treat associated disorders. For example, Prader-Willi syndrome (PWS) results from loss of paternally expressed imprinted genes on chromosome 15q11.2-q13.3, although the maternal allele is intact but epigenetically silenced. Using CRISPR repression and activation screens in human induced pluripotent stem cells (iPSCs), we identified genomic elements that control the expression of the PWS gene SNRPN from the paternal and maternal chromosomes. We showed that either targeted transcriptional activation or DNA demethylation can activate the silenced maternal SNRPN and downstream PWS transcripts. However, these two approaches function at unique regions, preferentially activating different transcript variants and involving distinct epigenetic reprogramming mechanisms. Remarkably, transient expression of the targeted demethylase leads to stable, long-term maternal SNRPN expression in PWS iPSCs. This work uncovers targeted epigenetic manipulations to reprogram a disease-associated imprinted locus and suggests possible therapeutic interventions.
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Affiliation(s)
- Dahlia Rohm
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA; Center for Advanced Genomic Technologies, Duke University, Durham, NC 27708, USA
| | - Joshua B Black
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA; Center for Advanced Genomic Technologies, Duke University, Durham, NC 27708, USA
| | - Sean R McCutcheon
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA; Center for Advanced Genomic Technologies, Duke University, Durham, NC 27708, USA
| | - Alejandro Barrera
- Center for Advanced Genomic Technologies, Duke University, Durham, NC 27708, USA; Department of Biostatistics and Bioinformatics, Duke University, Durham, NC 27708, USA
| | - Shanté S Berry
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA; Center for Advanced Genomic Technologies, Duke University, Durham, NC 27708, USA
| | - Daniel J Morone
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA; Center for Advanced Genomic Technologies, Duke University, Durham, NC 27708, USA
| | - Xander Nuttle
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Celine E de Esch
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Derek J C Tai
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Michael E Talkowski
- Center for Genomic Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Program in Medical and Population Genetics and Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Nahid Iglesias
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA; Center for Advanced Genomic Technologies, Duke University, Durham, NC 27708, USA
| | - Charles A Gersbach
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA; Center for Advanced Genomic Technologies, Duke University, Durham, NC 27708, USA; Department of Surgery, Duke University Medical Center, Durham, NC 27710, USA.
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18
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Moore MM, Wekhande S, Issner R, Collins A, Cruz AJ, Liu YV, Javed N, Casaní-Galdón S, Buenrostro JD, Epstein CB, Mattei E, Doench JG, Bernstein BE, Shoresh N, Najm FJ. Multi-locus CRISPRi targeting with a single truncated guide RNA. Nat Commun 2025; 16:1357. [PMID: 39905017 PMCID: PMC11794626 DOI: 10.1038/s41467-025-56144-x] [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: 11/02/2023] [Accepted: 01/10/2025] [Indexed: 02/06/2025] Open
Abstract
A critical goal in functional genomics is evaluating which non-coding elements contribute to gene expression, cellular function, and disease. Functional characterization remains a challenge due to the abundance and complexity of candidate elements. Here, we develop a CRISPRi-based approach for multi-locus screening of putative transcription factor binding sites with a single truncated guide. A truncated guide with hundreds of sequence match sites can reliably disrupt enhancer activity, which expands the targeting scope of CRISPRi while maintaining repressive efficacy. We screen over 13,000 possible CTCF binding sites with 24 guides at 10 nucleotides in spacer length. These truncated guides direct CRISPRi-mediated deposition of repressive H3K9me3 marks and disrupt transcription factor binding at most sequence match target sites. This approach can be a valuable screening step for testing transcription factor binding motifs or other repeated genomic sequences and is easily implemented with existing tools.
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Affiliation(s)
- Molly M Moore
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Siddarth Wekhande
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Robbyn Issner
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Alejandro Collins
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Anna J Cruz
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yanjing V Liu
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nauman Javed
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
- Departments of Cell Biology and Pathology, Harvard Medical School, Boston, MA, USA
| | - Salvador Casaní-Galdón
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
- Departments of Cell Biology and Pathology, Harvard Medical School, Boston, MA, USA
| | - Jason D Buenrostro
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Charles B Epstein
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Eugenio Mattei
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - John G Doench
- Genetic Perturbation Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Bradley E Bernstein
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA
- Departments of Cell Biology and Pathology, Harvard Medical School, Boston, MA, USA
| | - Noam Shoresh
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Fadi J Najm
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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19
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Chen X, Zheng M, Lin S, Huang M, Chen S, Chen S. The application of CRISPR/Cas9-based genome-wide screening to disease research. Mol Cell Probes 2025; 79:102004. [PMID: 39709065 DOI: 10.1016/j.mcp.2024.102004] [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: 10/11/2024] [Revised: 12/16/2024] [Accepted: 12/17/2024] [Indexed: 12/23/2024]
Abstract
High-throughput genetic screening serves as an indispensable approach for deciphering gene functions and the intricate relationships between phenotypes and genotypes. The CRISPR/Cas9 system, with its ability to precisely edit genomes on a large scale, has revolutionized the field by enabling the construction of comprehensive genomic libraries. This technology has become a cornerstone for genome-wide screenings in disease research. This review offers a comprehensive examination of how CRISPR/Cas9-based genetic screening has been leveraged to uncover genes that play a role in disease mechanisms, focusing on areas such as cancer development and viral replication processes. The insights presented in this review hold promise for the development of novel therapeutic strategies and precision medicine approaches.
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Affiliation(s)
- Xiuqin Chen
- Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Science, Fuzhou, Fujian, 350013, China; Fujian Animal Diseases Control Technology Development Center, Fuzhou, Fujian, 350013, China
| | - Min Zheng
- Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Science, Fuzhou, Fujian, 350013, China; Fujian Animal Diseases Control Technology Development Center, Fuzhou, Fujian, 350013, China
| | - Su Lin
- Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Science, Fuzhou, Fujian, 350013, China; Fujian Animal Diseases Control Technology Development Center, Fuzhou, Fujian, 350013, China
| | - Meiqing Huang
- Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Science, Fuzhou, Fujian, 350013, China; Fujian Animal Diseases Control Technology Development Center, Fuzhou, Fujian, 350013, China
| | - Shaoying Chen
- Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Science, Fuzhou, Fujian, 350013, China; Fujian Animal Diseases Control Technology Development Center, Fuzhou, Fujian, 350013, China
| | - Shilong Chen
- Institute of Animal Husbandry and Veterinary Medicine, Fujian Academy of Agricultural Science, Fuzhou, Fujian, 350013, China; Fujian Animal Diseases Control Technology Development Center, Fuzhou, Fujian, 350013, China.
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20
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Greenwood E, Cao M, Lee CM, Liu A, Moyo B, Bao G, Gibson G. Haplotype rather than single causal variants effects contribute to regulatory gene expression associations in human myeloid cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.01.30.635675. [PMID: 39975189 PMCID: PMC11838257 DOI: 10.1101/2025.01.30.635675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/21/2025]
Abstract
Genome-wide association studies typically identify hundreds to thousands of loci, many of which harbor multiple independent peaks, each parsimoniously assumed to be due to the activity of a single causal variant. Fine-mapping of such variants has become a priority and since most associations are located within regulatory regions, it is also assumed that they colocalize with regulatory variants that influence the expression of nearby genes. Here we examine these assumptions by using a moderate throughput expression CROPseq protocol in which Cas9 nuclease is used to induce small insertions and deletions across the credible set of SNPs that may account for expression quantitative trait loci (eQTL) for genes associated with inflammatory bowel disease (IBD). Of the 4,384 SNPs targeted in 88 loci (an average of 50 per locus), 439 were significant and further examined for validation. From these, 98 significantly altered target gene expression in HL-60 myeloid cell line, 74 in induced macrophages from these HL-60 cells, and 78 in induced neutrophils for a total of 201 validated effects (46%), 43 of which were observed in at least two of the cell types. Considering the observed sensitivity and specificity of the controls, we estimate that there are at least 150 true positives per cell type, an average of almost 2.4 for each of the 64 eQTL for which putative causal variants have been fine-mapped. This implies that haplotype effects are likely to explain many of the associations. We also demonstrate that the same approach can be used to investigate the activity of very rare variants in regulatory regions for 89 genes, providing a rapid strategy for establishing clinical relevance of non-coding mutations.
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Affiliation(s)
- Emily Greenwood
- School of Biological Sciences, Georgia Institute of Technology, Atlanta GA 30332, USA
| | - Mingming Cao
- Department of Bioengineering, Rice University, Houston TX 77005, USA
| | - Ciaran M. Lee
- School of Biochemistry and Cell Biology, University College Cork, Cork, Ireland
| | - Aidi Liu
- Department of Bioengineering, Rice University, Houston TX 77005, USA
| | - Buhle Moyo
- Department of Bioengineering, Rice University, Houston TX 77005, USA
| | - Gang Bao
- Department of Bioengineering, Rice University, Houston TX 77005, USA
| | - Greg Gibson
- School of Biological Sciences, Georgia Institute of Technology, Atlanta GA 30332, USA
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21
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Lin H, Ye X, Chen W, Hong D, Liu L, Chen F, Sun N, Ye K, Hong J, Zhang Y, Lu F, Li L, Huang J. Modular organization of enhancer network provides transcriptional robustness in mammalian development. Nucleic Acids Res 2025; 53:gkae1323. [PMID: 39817516 PMCID: PMC11736433 DOI: 10.1093/nar/gkae1323] [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: 08/16/2024] [Revised: 11/27/2024] [Accepted: 12/30/2024] [Indexed: 01/18/2025] Open
Abstract
Enhancer clusters, pivotal in mammalian development and diseases, can organize as enhancer networks to control cell identity and disease genes; however, the underlying mechanism remains largely unexplored. Here, we introduce eNet 2.0, a comprehensive tool for enhancer networks analysis during development and diseases based on single-cell chromatin accessibility data. eNet 2.0 extends our previous work eNet 1.0 by adding network topology, comparison and dynamics analyses to its network construction function. We reveal modularly organized enhancer networks, where inter-module interactions synergistically affect gene expression. Moreover, network alterations correlate with abnormal and dynamic gene expression in disease and development. eNet 2.0 is robust across diverse datasets. To facilitate application, we introduce eNetDB (https://enetdb.huanglabxmu.com), an enhancer network database leveraging extensive scATAC-seq (single-cell assay for transposase-accessible chromatin sequencing) datasets from human and mouse tissues. Together, our work provides a powerful computational tool and reveals that modularly organized enhancer networks contribute to gene expression robustness in mammalian development and diseases.
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Affiliation(s)
- Hongli Lin
- State Key Laboratory of Cellular Stress Biology, Xiang’an Hospital, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, No. 4221, Xiang’an South Road, Xiamen, Fujian 361102, China
| | - Xinyun Ye
- State Key Laboratory of Cellular Stress Biology, Xiang’an Hospital, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, No. 4221, Xiang’an South Road, Xiamen, Fujian 361102, China
| | - Wenyan Chen
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Guangqiao Road, Shenzhen 518055, China
| | - Danni Hong
- State Key Laboratory of Cellular Stress Biology, Xiang’an Hospital, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, No. 4221, Xiang’an South Road, Xiamen, Fujian 361102, China
| | - Lifang Liu
- State Key Laboratory of Cellular Stress Biology, Xiang’an Hospital, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, No. 4221, Xiang’an South Road, Xiamen, Fujian 361102, China
| | - Feng Chen
- Chengdu Wiser Matrix Technology Co. Ltd, No. 399, Fucheng Road, Chengdu, Sichuan 614001, China
| | - Ning Sun
- Chengdu Wiser Matrix Technology Co. Ltd, No. 399, Fucheng Road, Chengdu, Sichuan 614001, China
| | - Keying Ye
- State Key Laboratory of Cellular Stress Biology, Xiang’an Hospital, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, No. 4221, Xiang’an South Road, Xiamen, Fujian 361102, China
| | - Jizhou Hong
- State Key Laboratory of Cellular Stress Biology, Xiang’an Hospital, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, No. 4221, Xiang’an South Road, Xiamen, Fujian 361102, China
| | - Yalin Zhang
- State Key Laboratory of Cellular Stress Biology, Xiang’an Hospital, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, No. 4221, Xiang’an South Road, Xiamen, Fujian 361102, China
| | - Falong Lu
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, No. 2, Beichen West Road, Beijing 100101, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, No. 1, Yanqihu East Road, Beijing 101408, China
| | - Lei Li
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Guangqiao Road, Shenzhen 518055, China
| | - Jialiang Huang
- State Key Laboratory of Cellular Stress Biology, Xiang’an Hospital, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, No. 4221, Xiang’an South Road, Xiamen, Fujian 361102, China
- National Institute for Data Science in Health and Medicine, Xiamen University, No. 4221, Xiang’an South Road, Xiamen, Fujian 361102, China
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22
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Morgens DW, Gulyas L, Mao X, Rivera-Madera A, Souza AS, Glaunsinger BA. Enhancers and genome conformation provide complex transcriptional control of a herpesviral gene. Mol Syst Biol 2025; 21:30-58. [PMID: 39562742 PMCID: PMC11696879 DOI: 10.1038/s44320-024-00075-0] [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: 05/08/2024] [Revised: 10/28/2024] [Accepted: 10/31/2024] [Indexed: 11/21/2024] Open
Abstract
Complex transcriptional control is a conserved feature of both eukaryotes and the viruses that infect them. Despite viral genomes being smaller and more gene dense than their hosts, we generally lack a sense of scope for the features governing the transcriptional output of individual viral genes. Even having a seemingly simple expression pattern does not imply that a gene's underlying regulation is straightforward. Here, we illustrate this by combining high-density functional genomics, expression profiling, and viral-specific chromosome conformation capture to define with unprecedented detail the transcriptional regulation of a single gene from Kaposi's sarcoma-associated herpesvirus (KSHV). We used as our model KSHV ORF68 - which has simple, early expression kinetics and is essential for viral genome packaging. We first identified seven cis-regulatory regions involved in ORF68 expression by densely tiling the ~154 kb KSHV genome with dCas9 fused to a transcriptional repressor domain (CRISPRi). A parallel Cas9 nuclease screen indicated that three of these regions act as promoters of genes that regulate ORF68. RNA expression profiling demonstrated that three more of these regions act by either repressing or enhancing other distal viral genes involved in ORF68 transcriptional regulation. Finally, we tracked how the 3D structure of the viral genome changes during its lifecycle, revealing that these enhancing regulatory elements are physically closer to their targets when active, and that disrupting some elements caused large-scale changes to the 3D genome. These data enable us to construct a complete model revealing that the mechanistic diversity of this essential regulatory circuit matches that of human genes.
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Affiliation(s)
- David W Morgens
- Department of Plant and Microbial Biology, UC Berkeley, Berkeley, CA, USA.
| | - Leah Gulyas
- Department of Plant and Microbial Biology, UC Berkeley, Berkeley, CA, USA
| | - Xiaowen Mao
- Department of Plant and Microbial Biology, UC Berkeley, Berkeley, CA, USA
| | | | - Annabelle S Souza
- Department of Molecular and Cell Biology, UC Berkeley, Berkeley, CA, USA
| | - Britt A Glaunsinger
- Department of Plant and Microbial Biology, UC Berkeley, Berkeley, CA, USA.
- Department of Molecular and Cell Biology, UC Berkeley, Berkeley, CA, USA.
- Howard Hughes Medical Institute, UC Berkeley, Berkeley, CA, USA.
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23
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Wu Y, Zhong A, Sidharta M, Kim TW, Ramirez B, Persily B, Studer L, Zhou T. Robust and inducible genome editing via an all-in-one prime editor in human pluripotent stem cells. Nat Commun 2024; 15:10824. [PMID: 39737975 PMCID: PMC11685797 DOI: 10.1038/s41467-024-55104-1] [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] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2024] [Accepted: 11/27/2024] [Indexed: 01/01/2025] Open
Abstract
Prime editing (PE) allows for precise genome editing in human pluripotent stem cells (hPSCs), such as introducing single nucleotide modifications, small insertions or deletions at a specific genomic locus. Here, we systematically compare a panel of prime editing conditions in hPSCs and generate a potent prime editor, "PE-Plus", through co-inhibition of mismatch repair and p53-mediated cellular stress responses. We further establish an inducible prime editing platform in hPSCs by incorporating the PE-Plus into a safe-harbor locus and demonstrated temporal control of precise editing in both hPSCs and differentiated cells. By evaluating disease-associated mutations, we show that this platform allows efficient creation of both monoallelic and biallelic disease-relevant mutations in hPSCs. In addition, this platform enables the efficient introduction of single or multiple edits in one step, demonstrating potential for multiplex editing. Our method presents an efficient and controllable multiplex prime editing tool in hPSCs and their differentiated progeny.
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Affiliation(s)
- Youjun Wu
- The SKI Stem Cell Research Facility, The Center for Stem Cell Biology and Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, 1275 York Avenue, New York, NY, USA
| | - Aaron Zhong
- The SKI Stem Cell Research Facility, The Center for Stem Cell Biology and Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, 1275 York Avenue, New York, NY, USA
| | - Mega Sidharta
- The SKI Stem Cell Research Facility, The Center for Stem Cell Biology and Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, 1275 York Avenue, New York, NY, USA
| | - Tae Wan Kim
- The Center for Stem Cell Biology and Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, 1275 York Avenue, New York, NY, USA
| | - Bernny Ramirez
- The SKI Stem Cell Research Facility, The Center for Stem Cell Biology and Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, 1275 York Avenue, New York, NY, USA
| | - Benjamin Persily
- The SKI Stem Cell Research Facility, The Center for Stem Cell Biology and Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, 1275 York Avenue, New York, NY, USA
| | - Lorenz Studer
- The Center for Stem Cell Biology and Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, 1275 York Avenue, New York, NY, USA.
| | - Ting Zhou
- The SKI Stem Cell Research Facility, The Center for Stem Cell Biology and Developmental Biology Program, Sloan-Kettering Institute for Cancer Research, 1275 York Avenue, New York, NY, USA.
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24
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Fleming TJ, Antoszewski M, Lambo S, Gundry MC, Piussi R, Wahlster L, Shah S, Reed FE, Dong KD, Paulo JA, Gygi SP, Mimoso C, Goldman SR, Adelman K, Perry JA, Pikman Y, Stegmaier K, Barrachina MN, Machlus KR, Hovestadt V, Arruda A, Minden MD, Voit RA, Sankaran VG. CEBPA repression by MECOM blocks differentiation to drive aggressive leukemias. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.12.30.630680. [PMID: 39803492 PMCID: PMC11722404 DOI: 10.1101/2024.12.30.630680] [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: 01/18/2025]
Abstract
Acute myeloid leukemias (AMLs) have an overall poor prognosis with many high-risk cases co-opting stem cell gene regulatory programs, yet the mechanisms through which this occurs remain poorly understood. Increased expression of the stem cell transcription factor, MECOM, underlies one key driver mechanism in largely incurable AMLs. How MECOM results in such aggressive AML phenotypes remains unknown. To address existing experimental limitations, we engineered and applied targeted protein degradation with functional genomic readouts to demonstrate that MECOM promotes malignant stem cell-like states by directly repressing pro-differentiation gene regulatory programs. Remarkably and unexpectedly, a single node in this network, a MECOM-bound cis-regulatory element located 42 kb downstream of the myeloid differentiation regulator CEBPA, is both necessary and sufficient for maintaining MECOM-driven leukemias. Importantly, targeted activation of this regulatory element promotes differentiation of these aggressive AMLs and reduces leukemia burden in vivo, suggesting a broadly applicable differentiation-based approach for improving therapy.
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Affiliation(s)
- Travis J. Fleming
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Howard Hughes Medical Institute, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Mateusz Antoszewski
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Howard Hughes Medical Institute, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- These authors contributed equally to this work
| | - Sander Lambo
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- These authors contributed equally to this work
| | - Michael C. Gundry
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Howard Hughes Medical Institute, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Riccardo Piussi
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Howard Hughes Medical Institute, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Lara Wahlster
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Howard Hughes Medical Institute, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Sanjana Shah
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Howard Hughes Medical Institute, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Fiona E. Reed
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Howard Hughes Medical Institute, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Kevin D. Dong
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Joao A. Paulo
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Steven P. Gygi
- Department of Cell Biology, Harvard Medical School, Boston, MA 02115, USA
| | - Claudia Mimoso
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, 02115, USA
| | - Seth R. Goldman
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, 02115, USA
| | - Karen Adelman
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, 02115, USA
| | - Jennifer A. Perry
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Yana Pikman
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Kimberly Stegmaier
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Maria N. Barrachina
- Vascular Biology Program, Boston Children’s Hospital, Boston, MA 02115, USA
- Department of Surgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Kellie R. Machlus
- Vascular Biology Program, Boston Children’s Hospital, Boston, MA 02115, USA
- Department of Surgery, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Volker Hovestadt
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Andrea Arruda
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
| | - Mark D. Minden
- Princess Margaret Cancer Centre, University Health Network, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Richard A. Voit
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Howard Hughes Medical Institute, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Present Address: UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Vijay G. Sankaran
- Division of Hematology/Oncology, Boston Children’s Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA 02115, USA
- Howard Hughes Medical Institute, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Harvard Stem Cell Institute, Cambridge, MA 02142, USA
- Lead contact
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25
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Breves SL, Di Giammartino DC, Nicholson J, Cirigliano S, Mahmood SR, Lee UJ, Martinez-Fundichely A, Jungverdorben J, Singhania R, Rajkumar S, Kirou R, Studer L, Khurana E, Polyzos A, Fine HA, Apostolou E. Three-dimensional regulatory hubs support oncogenic programs in glioblastoma. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.12.20.629544. [PMID: 40034649 PMCID: PMC11875237 DOI: 10.1101/2024.12.20.629544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 03/05/2025]
Abstract
Dysregulation of enhancer-promoter communication in the context of the three-dimensional (3D) nucleus is increasingly recognized as a potential driver of oncogenic programs. Here, we profiled the 3D enhancer-promoter networks of primary patient-derived glioblastoma stem cells (GSCs) in comparison with neuronal stem cells (NSCs) to identify potential central nodes and vulnerabilities in the regulatory logic of this devastating cancer. Specifically, we focused on hyperconnected 3D regulatory hubs and demonstrated that hub-interacting genes exhibit high and coordinated expression at the single-cell level and strong association with oncogenic programs that distinguish IDH-wt glioblastoma patients from low-grade glioma. Epigenetic silencing of a recurrent 3D enhancer hub-with an uncharacterized role in glioblastoma-was sufficient to cause concordant downregulation of multiple hub-connected genes along with significant shifts in transcriptional states and reduced clonogenicity. By integrating published datasets from other cancer types, we also identified both universal and cancer type-specific 3D regulatory hubs which enrich for varying oncogenic programs and nominate specific factors associated with worse outcomes. Genetic alterations, such as focal duplications, could explain only a small fraction of the detected hyperconnected hubs and their increased activity. Overall, our study provides computational and experimental support for the potential central role of 3D regulatory hubs in controlling oncogenic programs and properties.
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Affiliation(s)
- Sarah L. Breves
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
- Physiology, Biophysics and Systems Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, NY, USA
- Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Dafne Campigli Di Giammartino
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
- Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
- 3D Chromatin Conformation and RNA genomics laboratory, Istituto Italiano di Tecnologia (IIT), Center for Human Technologies (CHT), Genova, Italy (current affiliation)
| | - James Nicholson
- Meyer Cancer Center, Division of Neuro-Oncology, Department of Neurology, Sandra and Edward Meyer Cancer Center, New York-Presbyterian Hospital/Weill Cornell Medicine, New York, NY, USA
| | - Stefano Cirigliano
- Meyer Cancer Center, Division of Neuro-Oncology, Department of Neurology, Sandra and Edward Meyer Cancer Center, New York-Presbyterian Hospital/Weill Cornell Medicine, New York, NY, USA
| | - Syed Raza Mahmood
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
- Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Uk Jin Lee
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
- Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Alexander Martinez-Fundichely
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, 10021, USA
- Meyer Cancer Center, Sandra and Edward Meyer Cancer Center, New York-Presbyterian Hospital/Weill Cornell Medicine, New York, NY, USA
- Caryl and Israel Englander Institute for Precision Medicine, New York Presbyterian Hospital, Weill Cornell Medicine, New York, NY 10065, USA
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY 10065, USA
| | - Johannes Jungverdorben
- The Center for Stem Cell Biology, Developmental Biology Program, Sloan Kettering Institute for Cancer Research, New York, NY, USA
| | - Richa Singhania
- Meyer Cancer Center, Division of Neuro-Oncology, Department of Neurology, Sandra and Edward Meyer Cancer Center, New York-Presbyterian Hospital/Weill Cornell Medicine, New York, NY, USA
| | - Sandy Rajkumar
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
- Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Raphael Kirou
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
- Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Lorenz Studer
- The Center for Stem Cell Biology, Developmental Biology Program, Sloan Kettering Institute for Cancer Research, New York, NY, USA
| | - Ekta Khurana
- Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, 10021, USA
- Meyer Cancer Center, Sandra and Edward Meyer Cancer Center, New York-Presbyterian Hospital/Weill Cornell Medicine, New York, NY, USA
- Caryl and Israel Englander Institute for Precision Medicine, New York Presbyterian Hospital, Weill Cornell Medicine, New York, NY 10065, USA
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY 10065, USA
| | - Alexander Polyzos
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
- Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
| | - Howard A. Fine
- 3D Chromatin Conformation and RNA genomics laboratory, Istituto Italiano di Tecnologia (IIT), Center for Human Technologies (CHT), Genova, Italy (current affiliation)
| | - Effie Apostolou
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
- Division of Hematology/Oncology, Department of Medicine, Weill Cornell Medicine, Cornell University, New York, NY, USA
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26
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Golov AK, Gavrilov AA, Kaplan N, Razin SV. A genome-wide nucleosome-resolution map of promoter-centered interactions in human cells corroborates the enhancer-promoter looping model. eLife 2024; 12:RP91596. [PMID: 39688903 DOI: 10.7554/elife.91596] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2024] Open
Abstract
The enhancer-promoter looping model, in which enhancers activate their target genes via physical contact, has long dominated the field of gene regulation. However, the ubiquity of this model has been questioned due to evidence of alternative mechanisms and the lack of its systematic validation, primarily owing to the absence of suitable experimental techniques. In this study, we present a new MNase-based proximity ligation method called MChIP-C, allowing for the measurement of protein-mediated chromatin interactions at single-nucleosome resolution on a genome-wide scale. By applying MChIP-C to study H3K4me3 promoter-centered interactions in K562 cells, we found that it had greatly improved resolution and sensitivity compared to restriction endonuclease-based C-methods. This allowed us to identify EP300 histone acetyltransferase and the SWI/SNF remodeling complex as potential candidates for establishing and/or maintaining enhancer-promoter interactions. Finally, leveraging data from published CRISPRi screens, we found that most functionally verified enhancers do physically interact with their cognate promoters, supporting the enhancer-promoter looping model.
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Affiliation(s)
- Arkadiy K Golov
- Institute of Gene Biology, Russian Academy of Sciences, Moscow, Russian Federation
- Department of Physiology, Biophysics & Systems Biology, Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel
| | - Alexey A Gavrilov
- Institute of Gene Biology, Russian Academy of Sciences, Moscow, Russian Federation
| | - Noam Kaplan
- Department of Physiology, Biophysics & Systems Biology, Rappaport Faculty of Medicine, Technion - Israel Institute of Technology, Haifa, Israel
| | - Sergey V Razin
- Institute of Gene Biology, Russian Academy of Sciences, Moscow, Russian Federation
- Faculty of Biology, Lomonosov Moscow State University, Moscow, Russian Federation
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27
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Rahmat M, Clement K, Alberge JB, Sklavenitis-Pistofidis R, Kodgule R, Fulco CP, Heilpern-Mallory D, Nilsson K, Dorfman D, Engreitz JM, Getz G, Pinello L, Ryan RJH, Ghobrial IM. Selective Enhancer Gain-of-Function Deregulates MYC Expression in Multiple Myeloma. Cancer Res 2024; 84:4173-4183. [PMID: 39312195 PMCID: PMC11649448 DOI: 10.1158/0008-5472.can-24-1440] [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: 05/07/2024] [Revised: 07/17/2024] [Accepted: 09/11/2024] [Indexed: 12/17/2024]
Abstract
MYC deregulation occurs in the majority of multiple myeloma cases and is associated with progression and worse prognosis. Enhanced MYC expression occurs in about 70% of patients with multiple myeloma, but it is known to be driven by translocation or amplification events in only ∼40% of myelomas. Here, we used CRISPR interference to uncover an epigenetic mechanism of MYC regulation whereby increased accessibility of a plasma cell-type-specific enhancer leads to increased MYC expression. This native enhancer activity was not associated with enhancer hijacking events but led to specific binding of cMAF, IRF4, and SPIB transcription factors that activated MYC expression in the absence of known genetic aberrations. In addition, focal amplification was another mechanism of activation of this enhancer in approximately 3.4% of patients with multiple myeloma. Together, these findings define an epigenetic mechanism of MYC deregulation in multiple myeloma beyond known translocations or amplifications and point to the importance of noncoding regulatory elements and their associated transcription factor networks as drivers of multiple myeloma progression. Significance: The discovery of a native developmental enhancer that sustains the expression of MYC in a subset of myelomas could help identify predictive biomarkers and therapeutic targets to improve the outcomes of patients with multiple myeloma.
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Affiliation(s)
- Mahshid Rahmat
- Dana-Farber Cancer Institute, Boston MA, USA
- Harvard Medical School, Boston MA, USA
| | - Kendell Clement
- Harvard Medical School, Boston MA, USA
- Department of Pathology, Massachusetts General Hospital, Boston MA, USA
| | - Jean-Baptiste Alberge
- Dana-Farber Cancer Institute, Boston MA, USA
- Harvard Medical School, Boston MA, USA
- Broad Institute of MIT and Harvard, Cambridge MA, USA
| | - Romanos Sklavenitis-Pistofidis
- Dana-Farber Cancer Institute, Boston MA, USA
- Harvard Medical School, Boston MA, USA
- Broad Institute of MIT and Harvard, Cambridge MA, USA
| | - Rohan Kodgule
- Department of Pathology and Immunology, Washington University School of Medicine, St Louis, Missouri, USA
| | - Charles P. Fulco
- Broad Institute of MIT and Harvard, Cambridge MA, USA
- Current address: Bristol Myers Squibb, Cambridge MA, USA
| | | | - Katarina Nilsson
- Department of Biochemistry, Northeastern University, Boston MA, USA
| | - David Dorfman
- Department of Pathology, Brigham and Women's Hospital, Boston MA, USA
| | - Jesse M. Engreitz
- Broad Institute of MIT and Harvard, Cambridge MA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford CA, USA
- BASE Initiative, Betty Irene Moore Children’s Heart Center, Lucile Packard Children’s Hospital, Stanford CA, USA
| | - Gad Getz
- Harvard Medical School, Boston MA, USA
- Department of Pathology, Massachusetts General Hospital, Boston MA, USA
- Broad Institute of MIT and Harvard, Cambridge MA, USA
- Cancer Center, Massachusetts General Hospital, Charlestown MA, USA
| | - Luca Pinello
- Harvard Medical School, Boston MA, USA
- Department of Pathology, Massachusetts General Hospital, Boston MA, USA
- Broad Institute of MIT and Harvard, Cambridge MA, USA
| | | | - Irene M. Ghobrial
- Dana-Farber Cancer Institute, Boston MA, USA
- Harvard Medical School, Boston MA, USA
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28
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Lai JCY, Hsu KW, Wu KJ. Interrogation of the interplay between DNA N6-methyladenosine (6mA) and hypoxia-induced chromatin accessibility by a randomized empirical model (EnrichShuf). Nucleic Acids Res 2024; 52:13605-13624. [PMID: 39565191 DOI: 10.1093/nar/gkae1152] [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: 02/29/2024] [Revised: 09/12/2024] [Accepted: 11/05/2024] [Indexed: 11/21/2024] Open
Abstract
N 6-Methyladenosine (6mA) is an epigenetic mark in eukaryotes regulating development, stress response and tumor progression. METTL4 has been reported as a 6mA methyltransferase induced by hypoxia. The detection and annotation of 6mA signals in mammalian cells have been hampered by the techniques and analytical methods developed so far. Here we developed a 6mA-ChIP-exo-5.1-seq to improve the sensitivity of detecting 6mAs in human cell lines. Furthermore, an EnrichShuf analysis tool for comprehensively comparing 6mA-ChIP-exo-5.1-seq, ATAC-seq, ChIP-seq and RNA-seq has been developed to annotate the functional relevance of 6mA in relation to chromatin accessibility and histone marks. Using a hypoxia-induced 6mA induction system as a model, we showed that hypoxic 6mA signals positively correlated with accessible chromatin regions. These 6mA signals correlate with their regulation by METTL4 under hypoxia, consistent with previous results. 6mAs also co-exist with H3K4me1, a histone mark for enhancers. Further analysis of enhancers using an ABC (active-by-contact) model shows that hypoxia-inducible factor-1α-induced H3K4me3 surrounds the 6mA/H3K4me1 site to augment active enhancers. These results suggest that correlation between 6mA and accessible chromatin regions plays a significant role in enhancer-promoter interactions during hypoxia-induced gene expression.
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Affiliation(s)
- Joseph Chieh-Yu Lai
- Graduate Institute of Biomedical Sciences, China Medical University, Taichung 406, Taiwan
- Cancer Genome Research Center, Chang Gung Memorial Hospital at Linkou, Taoyuan 333, Taiwan
| | - Kai-Wen Hsu
- Institute of Translational Medicine & New Drug Development, China Medical University, Taichung 404, Taiwan
| | - Kou-Juey Wu
- Cancer Genome Research Center, Chang Gung Memorial Hospital at Linkou, Taoyuan 333, Taiwan
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29
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Zhang Y, David NL, Pesaresi T, Andrews RE, Kumar GN, Chen H, Qiao W, Yang J, Patel K, Amorim T, Sharma AX, Liu S, Steinhauser ML. Noncoding variation near UBE2E2 orchestrates cardiometabolic pathophenotypes through polygenic effectors. JCI Insight 2024; 10:e184140. [PMID: 39656538 PMCID: PMC11790016 DOI: 10.1172/jci.insight.184140] [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: 06/21/2024] [Accepted: 11/26/2024] [Indexed: 01/24/2025] Open
Abstract
Mechanisms underpinning signals from genome-wide association studies remain poorly understood, particularly for noncoding variation and for complex diseases such as type 2 diabetes mellitus (T2D) where pathogenic mechanisms in multiple different tissues may be disease driving. One approach is to study relevant endophenotypes, a strategy we applied to the UBE2E2 locus where noncoding single nucleotide variants (SNVs) are associated with both T2D and visceral adiposity (a pathologic endophenotype). We integrated CRISPR targeting of SNV-containing regions and unbiased CRISPR interference (CRISPRi) screening to establish candidate cis-regulatory regions, complemented by genetic loss of function in murine diet-induced obesity or ex vivo adipogenesis assays. Nomination of a single causal gene was complicated, however, because targeting of multiple genes near UBE2E2 attenuated adipogenesis in vitro; CRISPR excision of SNV-containing noncoding regions and a CRISPRi regulatory screen across the locus suggested concomitant regulation of UBE2E2, the more distant UBE2E1, and other neighborhood genes; and compound heterozygous loss of function of both Ube2e2 and Ube2e1 better replicated pathological adiposity and metabolic phenotypes compared with homozygous loss of either gene in isolation. This study advances a model whereby regulatory effects of noncoding variation not only extend beyond the nearest gene but may also drive complex diseases through polygenic regulatory effects.
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Affiliation(s)
- Yang Zhang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
- Aging Institute, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Natalie L. David
- Aging Institute, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Tristan Pesaresi
- Aging Institute, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Rosemary E. Andrews
- Aging Institute, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - G.V. Naveen Kumar
- Aging Institute, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Hongyin Chen
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Wanning Qiao
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Jinzhao Yang
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Kareena Patel
- Aging Institute, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Department of Human Genetics, University of Pittsburgh, School of Public Health, Pittsburgh, Pennsylvania, USA
| | - Tania Amorim
- Aging Institute, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Division of Endocrinology and Metabolism, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Ankit X. Sharma
- Aging Institute, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Silvia Liu
- Department of Pathology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Pittsburgh Liver Research Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Matthew L. Steinhauser
- Aging Institute, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Division of Cardiology, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
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30
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Nasser J, Nam KM, Gunawardena J. A mathematical model clarifies the ABC Score formula used in enhancer-gene prediction. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.11.29.626072. [PMID: 39677755 PMCID: PMC11642778 DOI: 10.1101/2024.11.29.626072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 12/17/2024]
Abstract
Enhancers are discrete DNA elements that regulate the expression of eukaryotic genes. They are important not only for their regulatory function, but also as loci that are frequently associated with disease traits. Despite their significance, our conceptual understanding of how enhancers work remains limited. CRISPR-interference methods have recently provided the means to systematically screen for enhancers in cell culture, from which a formula for predicting whether an enhancer regulates a gene, the Activity-by-Contact (ABC) Score, has emerged and has been widely adopted. While useful as a binary classifier, it is less effective at predicting the quantitative effect of an enhancer on gene expression. It is also unclear how the algebraic form of the ABC Score arises from the underlying molecular mechanisms and what assumptions are needed for it to hold. Here, we use the graph-theoretic linear framework, previously introduced to analyze gene regulation, to formulate the default model, a mathematical model of how multiple enhancers independently regulate a gene. We show that the algebraic form of the ABC Score arises from this model. However, the default model assumptions also imply that enhancers act additively on steady-state gene expression. This is known to be false for certain genes and we show how modifying the assumptions can accommodate this discrepancy. Overall, our approach lays a rigorous, biophysical foundation for future studies of enhancer-gene regulation.
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Affiliation(s)
- Joseph Nasser
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Current address: Department of Physics, Brandeis University, Waltham, MA, USA
| | - Kee-Myoung Nam
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
- Current address: Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT, USA
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31
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Martin H, Wassef M. [Targeted epigenome engineering]. Med Sci (Paris) 2024; 40:955-962. [PMID: 39705566 DOI: 10.1051/medsci/2024182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2024] Open
Abstract
Cellular differentiation and homeostasis rely on complex mechanisms to control gene expression, enabling the different cell lineages of an organism to establish and then "memorize" different epigenetic states. The processes that control gene expression are centered on chromatin, a complex of DNA, histone proteins and RNA, whose structure is finely regulated. Targeted epigenomic engineering tools make it possible to interfere with and study these processes, revealing the logic of epigenetic memory mechanisms. This article reviews the main classes of targeted epigenome modification tools and illustrates how they can be used to better understand and modify the epigenome of cells, paving the way for potentially revolutionary therapeutic prospects.
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Affiliation(s)
- Hedvika Martin
- Institut Curie, Paris Sciences et Lettres, Sorbonne Université, Paris, France - Inserm U934/CNRS UMR 3215, Paris, France
| | - Michel Wassef
- Institut Curie, Paris Sciences et Lettres, Sorbonne Université, Paris, France - Inserm U934/CNRS UMR 3215, Paris, France
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Wang F, Li R, Xu JY, Bai X, Wang Y, Chen XR, Pan C, Chen S, Zhou K, Heng BC, Wu X, Guo W, Song Z, Jin SC, Zhou J, Zou XH, Ouyang HW, Liu H. Downregulating human leucocyte antigens on mesenchymal stromal cells by epigenetically repressing a β 2-microglobulin super-enhancer. Nat Biomed Eng 2024; 8:1682-1699. [PMID: 39433971 DOI: 10.1038/s41551-024-01264-w] [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: 12/01/2022] [Accepted: 09/13/2024] [Indexed: 10/23/2024]
Abstract
Immune rejection caused by mismatches in human leucocyte antigens (HLAs) remains a major obstacle to the success of allogeneic cell therapies. Current strategies for the generation of 'universal' immune-compatible cells, particularly the editing of HLA class I (HLA-I) genes or the modulation of proteins that inhibit natural killer cells, often result in genomic instability or cellular cytotoxicity. Here we show that a β2-microglobulin super-enhancer (B2M-SE) that is responsive to interferon-γ is a critical regulator of the expression of HLA-I on mesenchymal stromal cells (MSCs). Targeted epigenetic repression of B2M-SE in MSCs reduced the surface expression of HLA-I below the threshold required to activate allogenic T cells while maintaining levels sufficient to evade cytotoxicity mediated by natural killer cells. In a humanized mouse model, the epigenetically edited MSCs demonstrated improved survival by evading the immune system, allowing them to exert enhanced therapeutic effects on LPS-induced acute lung injury. Targeted epigenetic repression of B2M-SE may facilitate the development of off-the-shelf cell sources for allogeneic cell therapy.
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Affiliation(s)
- Fei Wang
- Department of Sports Medicine of the Second Affiliated Hospital, and Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, China
- Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cells and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, China
| | - Ran Li
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, Hangzhou City University School of Medicine, Hangzhou, China
| | - Jing Yi Xu
- Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cells and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiaoxia Bai
- The Women's Hospital, Zhejiang University School of Medicine and Key Laboratory of Women's Reproduction Health of Zhejiang Province, Hangzhou, China
| | - Ying Wang
- Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cells and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, China
| | - Xu Ri Chen
- Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cells and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, China
| | - Chen Pan
- Key Laboratory of Novel Targets and Drug Study for Neural Repair of Zhejiang Province, Hangzhou City University School of Medicine, Hangzhou, China
| | - Shen Chen
- Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou, China
| | - Ke Zhou
- Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cells and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, China
| | - Boon Chin Heng
- Central Laboratories, Peking University School of Stomatology, Beijing, China
| | - Xuewei Wu
- Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Haining, China
| | - Wei Guo
- Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Haining, China
| | - Zhe Song
- Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cells and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, China
| | - Shu Cheng Jin
- Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cells and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, China
| | - Jing Zhou
- Department of Sports Medicine of the Second Affiliated Hospital, and Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, China
- Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cells and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, China
| | - Xiao Hui Zou
- Central laboratory, The First Affiliated Hospital School of Medicine, Zhejiang University, Hangzhou, China.
| | - Hong Wei Ouyang
- Department of Sports Medicine of the Second Affiliated Hospital, and Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, China.
- Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cells and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, China.
- Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Haining, China.
- China Orthopedic Regenerative Medicine Group (CORMed), Hangzhou, China.
| | - Hua Liu
- Department of Sports Medicine of the Second Affiliated Hospital, and Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, China.
- Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cells and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, China.
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Fair T, Pavlovic BJ, Swope D, Castillo OE, Schaefer NK, Pollen AA. Mapping cis- and trans-regulatory target genes of human-specific deletions. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.12.27.573461. [PMID: 38234800 PMCID: PMC10793408 DOI: 10.1101/2023.12.27.573461] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Deletion of functional sequence is predicted to represent a fundamental mechanism of molecular evolution1,2. Comparative genetic studies of primates2,3 have identified thousands of human-specific deletions (hDels), and the cis-regulatory potential of short (≤31 base pairs) hDels has been assessed using reporter assays4. However, how structural variant-sized (≥50 base pairs) hDels influence molecular and cellular processes in their native genomic contexts remains unexplored. Here, we design genome-scale libraries of single-guide RNAs targeting 7.2 megabases of sequence in 6,358 hDels and present a systematic CRISPR interference (CRISPRi) screening approach to identify hDels that modify cellular proliferation in chimpanzee pluripotent stem cells. By intersecting hDels with chromatin state features and performing single-cell CRISPRi (Perturb-seq) to identify their cis- and trans-regulatory target genes, we discovered 20 hDels controlling gene expression. We highlight two hDels, hDel_2247 and hDel_585, with tissue-specific activity in the brain. Our findings reveal a molecular and cellular role for sequences lost in the human lineage and establish a framework for functionally interrogating human-specific genetic variants.
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Affiliation(s)
- Tyler Fair
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Bryan J Pavlovic
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Dani Swope
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Octavio E Castillo
- Quantitative Biosciences Institute, University of California, San Francisco, San Francisco, CA, USA
| | - Nathan K Schaefer
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Alex A Pollen
- Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
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34
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Zhou JL, Guruvayurappan K, Toneyan S, Chen HV, Chen AR, Koo P, McVicker G. Analysis of single-cell CRISPR perturbations indicates that enhancers predominantly act multiplicatively. CELL GENOMICS 2024; 4:100672. [PMID: 39406234 PMCID: PMC11605691 DOI: 10.1016/j.xgen.2024.100672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 07/08/2024] [Accepted: 09/16/2024] [Indexed: 10/30/2024]
Abstract
A single gene may have multiple enhancers, but how they work in concert to regulate transcription is poorly understood. To analyze enhancer interactions throughout the genome, we developed a generalized linear modeling framework, GLiMMIRS, for interrogating enhancer effects from single-cell CRISPR experiments. We applied GLiMMIRS to a published dataset and tested for interactions between 46,166 enhancer pairs and corresponding genes, including 264 "high-confidence" enhancer pairs. We found that enhancer effects combine multiplicatively but with limited evidence for further interactions. Only 31 enhancer pairs exhibited significant interactions (false discovery rate <0.1), none of which came from the high-confidence set, and 20 were driven by outlier expression values. Additional analyses of a second CRISPR dataset and in silico enhancer perturbations with Enformer both support a multiplicative model of enhancer effects without interactions. Altogether, our results indicate that enhancer interactions are uncommon or have small effects that are difficult to detect.
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Affiliation(s)
- Jessica L Zhou
- Integrative Biology Laboratory, Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, CA 92037, USA; Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92093, USA; Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA
| | - Karthik Guruvayurappan
- Integrative Biology Laboratory, Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, CA 92037, USA; School of Biological Sciences, University of California, San Diego, La Jolla, CA 92037, USA; Halicioglu Data Science Institute, University of California, San Diego, La Jolla, CA 92093, USA; Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY 10065, USA
| | - Shushan Toneyan
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA
| | - Hsiuyi V Chen
- Integrative Biology Laboratory, Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, CA 92037, USA
| | - Aaron R Chen
- Integrative Biology Laboratory, Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, CA 92037, USA
| | - Peter Koo
- Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724, USA
| | - Graham McVicker
- Integrative Biology Laboratory, Salk Institute for Biological Studies, 10010 N. Torrey Pines Road, La Jolla, CA 92037, USA.
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35
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Toneyan S, Koo PK. Interpreting cis-regulatory interactions from large-scale deep neural networks. Nat Genet 2024; 56:2517-2527. [PMID: 39284975 PMCID: PMC12065635 DOI: 10.1038/s41588-024-01923-3] [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: 07/28/2023] [Accepted: 08/21/2024] [Indexed: 09/25/2024]
Abstract
The rise of large-scale, sequence-based deep neural networks (DNNs) for predicting gene expression has introduced challenges in their evaluation and interpretation. Current evaluations align DNN predictions with orthogonal experimental data, providing insights into generalization but offering limited insights into their decision-making process. Existing model explainability tools focus mainly on motif analysis, which becomes complex when interpreting longer sequences. Here we present cis-regulatory element model explanations (CREME), an in silico perturbation toolkit that interprets the rules of gene regulation learned by a genomic DNN. Applying CREME to Enformer, a state-of-the-art DNN, we identify cis-regulatory elements that enhance or silence gene expression and characterize their complex interactions. CREME can provide interpretations across multiple scales of genomic organization, from cis-regulatory elements to fine-mapped functional sequence elements within them, offering high-resolution insights into the regulatory architecture of the genome. CREME provides a powerful toolkit for translating the predictions of genomic DNNs into mechanistic insights of gene regulation.
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Affiliation(s)
- Shushan Toneyan
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, New York, NY, USA
| | - Peter K Koo
- Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, New York, NY, USA.
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36
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Tycko J, Van MV, Aradhana, DelRosso N, Ye H, Yao D, Valbuena R, Vaughan-Jackson A, Xu X, Ludwig C, Spees K, Liu K, Gu M, Khare V, Mukund AX, Suzuki PH, Arana S, Zhang C, Du PP, Ornstein TS, Hess GT, Kamber RA, Qi LS, Khalil AS, Bintu L, Bassik MC. Development of compact transcriptional effectors using high-throughput measurements in diverse contexts. Nat Biotechnol 2024:10.1038/s41587-024-02442-6. [PMID: 39487265 PMCID: PMC12043968 DOI: 10.1038/s41587-024-02442-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 09/20/2024] [Indexed: 11/04/2024]
Abstract
Transcriptional effectors are protein domains known to activate or repress gene expression; however, a systematic understanding of which effector domains regulate transcription across genomic, cell type and DNA-binding domain (DBD) contexts is lacking. Here we develop dCas9-mediated high-throughput recruitment (HT-recruit), a pooled screening method for quantifying effector function at endogenous target genes and test effector function for a library containing 5,092 nuclear protein Pfam domains across varied contexts. We also map context dependencies of effectors drawn from unannotated protein regions using a larger library tiling chromatin regulators and transcription factors. We find that many effectors depend on target and DBD contexts, such as HLH domains that can act as either activators or repressors. To enable efficient perturbations, we select context-robust domains, including ZNF705 KRAB, that improve CRISPRi tools to silence promoters and enhancers. We engineer a compact human activator called NFZ, by combining NCOA3, FOXO3 and ZNF473 domains, which enables efficient CRISPRa with better viral delivery and inducible control of chimeric antigen receptor T cells.
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Affiliation(s)
- Josh Tycko
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Mike V Van
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Aradhana
- Department of Genetics, Stanford University, Stanford, CA, USA
| | | | - Hanrong Ye
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, USA
| | - David Yao
- Department of Genetics, Stanford University, Stanford, CA, USA
| | | | - Alun Vaughan-Jackson
- Department of Genetics, Stanford University, Stanford, CA, USA
- Chan Zuckerberg Biohub-San Francisco, San Francisco, CA, USA
| | - Xiaoshu Xu
- Department of Bioengineering, 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
| | - Katherine Liu
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Mingxin Gu
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Venya Khare
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, USA
| | | | - Peter H Suzuki
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Sophia Arana
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Catherine Zhang
- Department of Cancer Biology, Stanford University, Stanford, CA, USA
| | - Peter P Du
- Department of Cancer Biology, Stanford University, Stanford, CA, USA
| | - Thea S Ornstein
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, USA
| | - Gaelen T Hess
- Department of Biomolecular Chemistry and Center for Human Genomics and Precision Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Roarke A Kamber
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Lei S Qi
- Chan Zuckerberg Biohub-San Francisco, San Francisco, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Sarafan ChEM-H, Stanford University, Stanford, CA, USA
| | - Ahmad S Khalil
- Department of Biomedical Engineering and Biological Design Center, Boston University, Boston, MA, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA
| | - Lacramioara Bintu
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
| | - Michael C Bassik
- Department of Genetics, Stanford University, Stanford, CA, USA.
- Sarafan ChEM-H, Stanford University, Stanford, CA, USA.
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37
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Tan M, Sun S, Liu Y, Perreault AA, Phanstiel DH, Dou L, Pang B. Targeting the 3D genome by anthracyclines for chemotherapeutic effects. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.15.614434. [PMID: 39463926 PMCID: PMC11507702 DOI: 10.1101/2024.10.15.614434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/29/2024]
Abstract
The chromatins are folded into three-dimensional (3D) structures inside cells, which coordinates the regulation of gene transcription by the non-coding regulatory elements. Aberrant chromatin 3D folding has been shown in many diseases, such as acute myeloid leukemia (AML), and may contribute to tumorigenesis. The anthracycline topoisomerase II inhibitors can induce histone eviction and DNA damage. We performed genome-wide high-resolution mapping of the chemotherapeutic effects of various clinically used anthracycline drugs. ATAC-seq was used to profile the histone eviction effects of different anthracyclines. TOP2A ChIP-seq was used to profile the potential DNA damage regions. Integrated analyses show that different anthracyclines have distinct target selectivity on epigenomic regions, based on their respective ATAC-seq and ChIP-seq profiles. We identified the underlying molecular mechanism that unique anthracycline variants selectively target chromatin looping anchors via disrupting CTCF binding, suggesting an additional potential therapeutic effect on the 3D genome. We further performed Hi-C experiments, and data from K562 cells treated with the selective anthracycline drugs indicate that the 3D chromatin organization is disrupted. Furthermore, AML patients receiving anthracycline drugs showed altered chromatin structures around potential looping anchors, which linked to distinct clinical outcomes. Our data indicate that anthracyclines are potent and selective epigenomic targeting drugs and can target the 3D genome for anticancer therapy, which could be used for personalized medicine to treat tumors with aberrant 3D chromatin structures.
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Gosai SJ, Castro RI, Fuentes N, Butts JC, Mouri K, Alasoadura M, Kales S, Nguyen TTL, Noche RR, Rao AS, Joy MT, Sabeti PC, Reilly SK, Tewhey R. Machine-guided design of cell-type-targeting cis-regulatory elements. Nature 2024; 634:1211-1220. [PMID: 39443793 PMCID: PMC11525185 DOI: 10.1038/s41586-024-08070-z] [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] [Received: 07/26/2023] [Accepted: 09/18/2024] [Indexed: 10/25/2024]
Abstract
Cis-regulatory elements (CREs) control gene expression, orchestrating tissue identity, developmental timing and stimulus responses, which collectively define the thousands of unique cell types in the body1-3. While there is great potential for strategically incorporating CREs in therapeutic or biotechnology applications that require tissue specificity, there is no guarantee that an optimal CRE for these intended purposes has arisen naturally. Here we present a platform to engineer and validate synthetic CREs capable of driving gene expression with programmed cell-type specificity. We take advantage of innovations in deep neural network modelling of CRE activity across three cell types, efficient in silico optimization and massively parallel reporter assays to design and empirically test thousands of CREs4-8. Through large-scale in vitro validation, we show that synthetic sequences are more effective at driving cell-type-specific expression in three cell lines compared with natural sequences from the human genome and achieve specificity in analogous tissues when tested in vivo. Synthetic sequences exhibit distinct motif vocabulary associated with activity in the on-target cell type and a simultaneous reduction in the activity of off-target cells. Together, we provide a generalizable framework to prospectively engineer CREs from massively parallel reporter assay models and demonstrate the required literacy to write fit-for-purpose regulatory code.
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Affiliation(s)
- Sager J Gosai
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Harvard Graduate Program in Biological and Biomedical Science, Boston, MA, USA.
- Department Of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA.
- Howard Hughes Medical Institute, Chevy Chase, MD, USA.
| | | | - Natalia Fuentes
- The Jackson Laboratory, Bar Harbor, ME, USA
- Harvard College, Harvard University, Cambridge, MA, USA
| | - John C Butts
- The Jackson Laboratory, Bar Harbor, ME, USA
- Graduate School of Biomedical Sciences and Engineering, University of Maine, Orono, ME, USA
| | | | | | | | | | - Ramil R Noche
- Department of Comparative Medicine, Yale School of Medicine, New Haven, CT, USA
- Yale Zebrafish Research Core, Yale School of Medicine, New Haven, CT, USA
| | - Arya S Rao
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Mary T Joy
- The Jackson Laboratory, Bar Harbor, ME, USA
| | - Pardis C Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department Of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Steven K Reilly
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, USA.
| | - Ryan Tewhey
- The Jackson Laboratory, Bar Harbor, ME, USA.
- Graduate School of Biomedical Sciences and Engineering, University of Maine, Orono, ME, USA.
- Graduate School of Biomedical Sciences, Tufts University School of Medicine, Boston, MA, USA.
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Woo BJ, Moussavi-Baygi R, Karner H, Karimzadeh M, Yousefi H, Lee S, Garcia K, Joshi T, Yin K, Navickas A, Gilbert LA, Wang B, Asgharian H, Feng FY, Goodarzi H. Integrative identification of non-coding regulatory regions driving metastatic prostate cancer. Cell Rep 2024; 43:114764. [PMID: 39276353 PMCID: PMC11466230 DOI: 10.1016/j.celrep.2024.114764] [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: 06/13/2023] [Revised: 07/08/2024] [Accepted: 08/29/2024] [Indexed: 09/17/2024] Open
Abstract
Large-scale sequencing efforts have been undertaken to understand the mutational landscape of the coding genome. However, the vast majority of variants occur within non-coding genomic regions. We designed an integrative computational and experimental framework to identify recurrently mutated non-coding regulatory regions that drive tumor progression. Applying this framework to sequencing data from a large prostate cancer patient cohort revealed a large set of candidate drivers. We used (1) in silico analyses, (2) massively parallel reporter assays, and (3) in vivo CRISPR interference screens to systematically validate metastatic castration-resistant prostate cancer (mCRPC) drivers. One identified enhancer region, GH22I030351, acts on a bidirectional promoter to simultaneously modulate expression of the U2-associated splicing factor SF3A1 and chromosomal protein CCDC157. SF3A1 and CCDC157 promote tumor growth in vivo. We nominated a number of transcription factors, notably SOX6, to regulate expression of SF3A1 and CCDC157. Our integrative approach enables the systematic detection of non-coding regulatory regions that drive human cancers.
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Affiliation(s)
- Brian J Woo
- Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA; Arc Institute, Palo Alto, CA 94305, USA
| | - Ruhollah Moussavi-Baygi
- Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Heather Karner
- Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA; Arc Institute, Palo Alto, CA 94305, USA
| | - Mehran Karimzadeh
- Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA; Vector Institute, Toronto, ON, Canada; Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada; Arc Institute, Palo Alto, CA 94305, USA
| | - Hassan Yousefi
- Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA; Arc Institute, Palo Alto, CA 94305, USA
| | - Sean Lee
- Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA; Arc Institute, Palo Alto, CA 94305, USA
| | - Kristle Garcia
- Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Tanvi Joshi
- Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Keyi Yin
- Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Albertas Navickas
- Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA
| | - Luke A Gilbert
- Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA; Arc Institute, Palo Alto, CA 94305, USA
| | - Bo Wang
- Vector Institute, Toronto, ON, Canada; Peter Munk Cardiac Centre, University Health Network, Toronto, ON, Canada
| | - Hosseinali Asgharian
- Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
| | - Felix Y Feng
- Department of Urology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA; Department of Radiation Oncology, University of California, San Francisco, San Francisco, CA, USA.
| | - Hani Goodarzi
- Department of Biochemistry & Biophysics, University of California, San Francisco, San Francisco, CA, USA; Department of Urology, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA; Arc Institute, Palo Alto, CA 94305, USA; Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, CA, USA.
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40
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Goell J, Li J, Mahata B, Ma AJ, Kim S, Shah S, Shah S, Contreras M, Misra S, Reed D, Bedford GC, Escobar M, Hilton IB. Tailoring a CRISPR/Cas-based Epigenome Editor for Programmable Chromatin Acylation and Decreased Cytotoxicity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.22.611000. [PMID: 39345554 PMCID: PMC11429961 DOI: 10.1101/2024.09.22.611000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
Engineering histone acylation states can inform mechanistic epigenetics and catalyze therapeutic epigenome editing opportunities. Here, we developed engineered lysine acyltransferases that enable the programmable deposition of acetylation and longer-chain acylations. We show that targeting an engineered lysine crotonyltransferase results in weak levels of endogenous enhancer activation yet retains potency when targeted to promoters. We further identify a single mutation within the catalytic core of human p300 that preserves enzymatic activity while substantially reducing cytotoxicity, enabling improved viral delivery. We leveraged these capabilities to perform single-cell CRISPR activation screening and map enhancers to the genes they regulate in situ. We also discover acylation-specific interactions and find that recruitment of p300, regardless of catalytic activity, to prime editing sites can improve editing efficiency. These new programmable epigenome editing tools and insights expand our ability to understand the mechanistic role of lysine acylation in epigenetic and cellular processes and perform functional genomic screens.
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Affiliation(s)
- Jacob Goell
- Department of Bioengineering, Rice University, Houston, TX 77030, USA
| | - Jing Li
- Department of Bioengineering, Rice University, Houston, TX 77030, USA
| | - Barun Mahata
- Department of Bioengineering, Rice University, Houston, TX 77030, USA
| | - Alex J Ma
- Department of Bioengineering, Rice University, Houston, TX 77030, USA
| | - Sunghwan Kim
- Department of Bioengineering, Rice University, Houston, TX 77030, USA
| | - Spencer Shah
- Department of Bioengineering, Rice University, Houston, TX 77030, USA
| | - Shriya Shah
- Department of Bioengineering, Rice University, Houston, TX 77030, USA
| | - Maria Contreras
- Department of Bioengineering, Rice University, Houston, TX 77030, USA
| | - Suchir Misra
- Department of Biosciences, Rice University, Houston, TX 77030, USA
| | - Daniel Reed
- Department of Bioengineering, Rice University, Houston, TX 77030, USA
| | - Guy C Bedford
- Department of Bioengineering, Rice University, Houston, TX 77030, USA
| | - Mario Escobar
- Department of Bioengineering, Rice University, Houston, TX 77030, USA
| | - Isaac B Hilton
- Department of Bioengineering, Rice University, Houston, TX 77030, USA
- Department of Biosciences, Rice University, Houston, TX 77030, USA
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Taghbalout A, Tung CH, Clow PA, Wang P, Tjong H, Wong CH, Mao DD, Maurya R, Huang MF, Ngan CY, Kim AH, Wei CL. Extrachromosomal DNA Associates with Nuclear Condensates and Reorganizes Chromatin Structures to Enhance Oncogenic Transcription. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.17.613488. [PMID: 39345460 PMCID: PMC11429754 DOI: 10.1101/2024.09.17.613488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/01/2024]
Abstract
Extrachromosomal, circular DNA (ecDNA) is a prevalent oncogenic alteration in cancer genomes, often associated with aggressive tumor behavior and poor patient outcome. While previous studies proposed a chromatin-based mobile enhancer model for ecDNA-driven oncogenesis, its precise mechanism and impact remains unclear across diverse cancer types. Our study, utilizing advanced multi-omics profiling, epigenetic editing, and imaging approaches in three cancer models, reveals that ecDNA hubs are an integrated part of nuclear condensates and exhibit cancer-type specific chromatin connectivity. Epigenetic silencing of the ecDNA-specific regulatory modules or chemically disrupting liquid-liquid phase separation breaks down ecDNA hubs, displaces MED1 co-activator binding, inhibits oncogenic transcription, and promotes cell death. These findings substantiate the trans -activator function of ecDNA and underscore a structural mechanism driving oncogenesis. This refined understanding expands our views of oncogene regulation and opens potential avenues for novel therapeutic strategies in cancer treatment.
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Chardon FM, McDiarmid TA, Page NF, Daza RM, Martin BK, Domcke S, Regalado SG, Lalanne JB, Calderon D, Li X, Starita LM, Sanders SJ, Ahituv N, Shendure J. Multiplex, single-cell CRISPRa screening for cell type specific regulatory elements. Nat Commun 2024; 15:8209. [PMID: 39294132 PMCID: PMC11411074 DOI: 10.1038/s41467-024-52490-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Accepted: 09/10/2024] [Indexed: 09/20/2024] Open
Abstract
CRISPR-based gene activation (CRISPRa) is a strategy for upregulating gene expression by targeting promoters or enhancers in a tissue/cell-type specific manner. Here, we describe an experimental framework that combines highly multiplexed perturbations with single-cell RNA sequencing (sc-RNA-seq) to identify cell-type-specific, CRISPRa-responsive cis-regulatory elements and the gene(s) they regulate. Random combinations of many gRNAs are introduced to each of many cells, which are then profiled and partitioned into test and control groups to test for effect(s) of CRISPRa perturbations of both enhancers and promoters on the expression of neighboring genes. Applying this method to a library of 493 gRNAs targeting candidate cis-regulatory elements in both K562 cells and iPSC-derived excitatory neurons, we identify gRNAs capable of specifically upregulating intended target genes and no other neighboring genes within 1 Mb, including gRNAs yielding upregulation of six autism spectrum disorder (ASD) and neurodevelopmental disorder (NDD) risk genes in neurons. A consistent pattern is that the responsiveness of individual enhancers to CRISPRa is restricted by cell type, implying a dependency on either chromatin landscape and/or additional trans-acting factors for successful gene activation. The approach outlined here may facilitate large-scale screens for gRNAs that activate genes in a cell type-specific manner.
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Affiliation(s)
- Florence M Chardon
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | - Troy A McDiarmid
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | - Nicholas F Page
- Department of Psychiatry and Behavioral Sciences, Kavli Institute for Fundamental Neuroscience, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | - Riza M Daza
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | - Beth K Martin
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | - Silvia Domcke
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Samuel G Regalado
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | | | - Diego Calderon
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Xiaoyi Li
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | - Lea M Starita
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
| | - Stephan J Sanders
- Department of Psychiatry and Behavioral Sciences, Kavli Institute for Fundamental Neuroscience, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Institute of Developmental and Regenerative Medicine, Department of Paediatrics, University of Oxford, Oxford, OX3 7TY, UK
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA.
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
- Seattle Hub for Synthetic Biology, Seattle, WA, USA.
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA.
- Howard Hughes Medical Institute, Seattle, WA, USA.
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA.
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Thomas SM, Ankley LM, Conner KN, Rapp AW, McGee AP, LeSage F, Tanner CD, Vielma TE, Scheeres EC, Obar JJ, Olive AJ. TGFβ primes alveolar-like macrophages to induce type I IFN following TLR2 activation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.09.04.611226. [PMID: 39282428 PMCID: PMC11398362 DOI: 10.1101/2024.09.04.611226] [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: 09/20/2024]
Abstract
Alveolar macrophages (AMs) are key mediators of lung function and are potential targets for therapies during respiratory infections. TGFβ is an important regulator of AM differentiation and maintenance, but how TGFβ directly modulates the innate immune responses of AMs remains unclear. This shortcoming prevents effective targeting of AMs to improve lung function in health and disease. Here we leveraged an optimized ex vivo AM model system, fetal-liver derived alveolar-like macrophages (FLAMs), to dissect the role of TGFβ in AMs. Using transcriptional analysis, we first globally defined how TGFβ regulates gene expression of resting FLAMs. We found that TGFβ maintains the baseline metabolic state of AMs by driving lipid metabolism through oxidative phosphorylation and restricting inflammation. To better understand inflammatory regulation in FLAMs, we next directly tested how TGFβ alters the response to TLR2 agonists. While both TGFβ (+) and TGFβ (-) FLAMs robustly responded to TLR2 agonists, we found an unexpected activation of type I interferon (IFN) responses in FLAMs and primary AMs in a TGFβ-dependent manner. Surprisingly, mitochondrial antiviral signaling protein and the interferon regulator factors 3 and 7 were required for IFN production by TLR2 agonists. Together, these data suggest that TGFβ modulates AM metabolic networks and innate immune signaling cascades to control inflammatory pathways in AMs.
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Affiliation(s)
- Sean M. Thomas
- Department of Microbiology, Genetics, and Immunology, College of Osteopathic Medicine, Michigan State University, East Lansing, MI
| | - Laurisa M. Ankley
- Department of Microbiology, Genetics, and Immunology, College of Osteopathic Medicine, Michigan State University, East Lansing, MI
| | - Kayla N. Conner
- Department of Microbiology, Genetics, and Immunology, College of Osteopathic Medicine, Michigan State University, East Lansing, MI
| | - Alexander W. Rapp
- Department of Microbiology & Immunology, Geisel School of Medicine at Dartmouth, Lebanon, NH
| | - Abigail P. McGee
- Department of Microbiology & Immunology, Geisel School of Medicine at Dartmouth, Lebanon, NH
| | - Francois LeSage
- Department of Microbiology & Immunology, Geisel School of Medicine at Dartmouth, Lebanon, NH
| | - Christopher D. Tanner
- Department of Microbiology & Immunology, Geisel School of Medicine at Dartmouth, Lebanon, NH
| | - Taryn E. Vielma
- Department of Microbiology, Genetics, and Immunology, College of Osteopathic Medicine, Michigan State University, East Lansing, MI
| | - Eleanor C. Scheeres
- Department of Microbiology, Genetics, and Immunology, College of Osteopathic Medicine, Michigan State University, East Lansing, MI
| | - Joshua J. Obar
- Department of Microbiology & Immunology, Geisel School of Medicine at Dartmouth, Lebanon, NH
| | - Andrew J. Olive
- Department of Microbiology, Genetics, and Immunology, College of Osteopathic Medicine, Michigan State University, East Lansing, MI
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IGVF Consortium, Writing group (ordered by contribution), Engreitz JM, Lawson HA, Singh H, Starita LM, Hon GC, Carter H, Sahni N, Reddy TE, Lin X, Li Y, Munshi NV, Chahrour MH, Boyle AP, Hitz BC, Mortazavi A, Craven M, Mohlke KL, Pinello L, Wang T, Steering Committee Co-Chairs (alphabetical by last name), Kundaje A, Yue F, Code of Conduct Committee (alphabetical by last name), Cody S, Farrell NP, Love MI, Muffley LA, Pazin MJ, Reese F, Van Buren E, Working Group and Focus Group Co-Chairs (alphabetical by last name), Catalog, Dey KK, Characterization, Kircher M, Computational Analysis, Modeling, and Prediction, Ma J, Radivojac P, Project Design, Balliu B, Mapping, Williams BA, Networks, Huangfu D, Standards and Pipelines, Cardiometabolic, Park CY, Quertermous T, Cellular Programs and Networks, Das J, Coding Variants, Calderwood MA, Fowler DM, Vidal M, CRISPR, Ferreira L, Defining and Systematizing Function, Mooney SD, Pejaver V, Enumerating Variants, Zhao J, Evolution, Gazal S, Koch E, Reilly SK, Sunyaev S, Imaging, Carpenter AE, Immune, Buenrostro JD, Leslie CS, Savage RE, Impact on Diverse Populations, Giric S, iPSC, Luo C, Plath K, MPRA, Barrera A, Schubach M, Noncoding Variants, Gschwind AR, Moore JE, Neuro, Ahituv N, Phenotypic Impact and Function, Yi SS, QTL/Statgen, Hallgrimsdottir I, Gaulton KJ, Sakaue S, Single Cell, Booeshaghi S, Mattei E, Nair S, Pachter L, Wang AT, Characterization Awards (contact PI, MPIs (alphabetical by last name), other members (alphabetical by last name)), et alIGVF Consortium, Writing group (ordered by contribution), Engreitz JM, Lawson HA, Singh H, Starita LM, Hon GC, Carter H, Sahni N, Reddy TE, Lin X, Li Y, Munshi NV, Chahrour MH, Boyle AP, Hitz BC, Mortazavi A, Craven M, Mohlke KL, Pinello L, Wang T, Steering Committee Co-Chairs (alphabetical by last name), Kundaje A, Yue F, Code of Conduct Committee (alphabetical by last name), Cody S, Farrell NP, Love MI, Muffley LA, Pazin MJ, Reese F, Van Buren E, Working Group and Focus Group Co-Chairs (alphabetical by last name), Catalog, Dey KK, Characterization, Kircher M, Computational Analysis, Modeling, and Prediction, Ma J, Radivojac P, Project Design, Balliu B, Mapping, Williams BA, Networks, Huangfu D, Standards and Pipelines, Cardiometabolic, Park CY, Quertermous T, Cellular Programs and Networks, Das J, Coding Variants, Calderwood MA, Fowler DM, Vidal M, CRISPR, Ferreira L, Defining and Systematizing Function, Mooney SD, Pejaver V, Enumerating Variants, Zhao J, Evolution, Gazal S, Koch E, Reilly SK, Sunyaev S, Imaging, Carpenter AE, Immune, Buenrostro JD, Leslie CS, Savage RE, Impact on Diverse Populations, Giric S, iPSC, Luo C, Plath K, MPRA, Barrera A, Schubach M, Noncoding Variants, Gschwind AR, Moore JE, Neuro, Ahituv N, Phenotypic Impact and Function, Yi SS, QTL/Statgen, Hallgrimsdottir I, Gaulton KJ, Sakaue S, Single Cell, Booeshaghi S, Mattei E, Nair S, Pachter L, Wang AT, Characterization Awards (contact PI, MPIs (alphabetical by last name), other members (alphabetical by last name)), UM1HG011966, Shendure J, Agarwal V, Blair A, Chalkiadakis T, Chardon FM, Dash PM, Deng C, Hamazaki N, Keukeleire P, Kubo C, Lalanne JB, Maass T, Martin B, McDiarmid TA, Nobuhara M, Page NF, Regalado S, Sims J, Ushiki A, UM1HG011969, Best SM, Boyle G, Camp N, Casadei S, Da EY, Dawood M, Dawson SC, Fayer S, Hamm A, James RG, Jarvik GP, McEwen AE, Moore N, Pendyala S, Popp NA, Post M, Rubin AF, Smith NT, Stone J, Tejura M, Wang ZR, Wheelock MK, Woo I, Zapp BD, UM1HG011972, Amgalan D, Aradhana A, Arana SM, Bassik MC, Bauman JR, Bhattacharya A, Cai XS, Chen Z, Conley S, Deshpande S, Doughty BR, Du PP, Galante JA, Gifford C, Greenleaf WJ, Guo K, Gupta R, Isobe S, Jagoda E, Jain N, Jones H, Kang HY, Kim SH, Kim Y, Klemm S, Kundu R, Kundu S, Lago-Docampo M, Lee-Yow YC, Levin-Konigsberg R, Li DY, Lindenhofer D, Ma XR, Marinov GK, Martyn GE, McCreery CV, Metzl-Raz E, Monteiro JP, Montgomery MT, Mualim KS, Munger C, Munson G, Nguyen TC, Nguyen T, Palmisano BT, Pampari A, Rabinovitch M, Ramste M, Ray J, Roy KR, Rubio OM, Schaepe JM, Schnitzler G, Schreiber J, Sharma D, Sheth MU, Shi H, Singh V, Sinha R, Steinmetz LM, Tan J, Tan A, Tycko J, Valbuena RC, Amiri VVP, van Kooten MJFM, Vaughan-Jackson A, Venida A, Weldy CS, Worssam MD, Xia F, Yao D, Zeng T, Zhao Q, Zhou R, UM1HG011989, Chen ZS, Cimini BA, Coppin G, Coté AG, Haghighi M, Hao T, Hill DE, Lacoste J, Laval F, Reno C, Roth FP, Singh S, Spirohn-Fitzgerald K, Taipale M, Teelucksingh T, Tixhon M, Yadav A, Yang Z, UM1HG011996, Kraus WL, Armendariz DA, Dederich AE, Gogate A, El Hayek L, Goetsch SC, Kaur K, Kim HB, McCoy MK, Nzima MZ, Pinzón-Arteaga CA, Posner BA, Schmitz DA, Sivakumar S, Sundarrajan A, Wang L, Wang Y, Wu J, Xu L, Xu J, Yu L, Zhang Y, Zhao H, Zhou Q, UM1HG012003, Won H, Bell JL, Broadaway KA, Degner KN, Etheridge AS, Koller BH, Mah W, Mu W, Ritola KD, Rosen JD, Schoenrock SA, Sharp RA, UM1HG012010, Bauer D, Lettre G, Sherwood R, Becerra B, Blaine LJ, Che E, Francoeur MJ, Gibbs EN, Kim N, King EM, Kleinstiver BP, Lecluze E, Li Z, Patel ZM, Phan QV, Ryu J, Starr ML, Wu T, UM1HG012053, Gersbach CA, Crawford GE, Allen AS, Majoros WH, Iglesias N, Rai R, Venukuttan R, Li B, Anglen T, Bounds LR, Hamilton MC, Liu S, McCutcheon SR, McRoberts Amador CD, Reisman SJ, ter Weele MA, Bodle JC, Streff HL, Siklenka K, Strouse K, Mapping Awards (contact PI, MPIs (alphabetical by last name), other members (alphabetical by last name)), UM1HG011986, Bernstein BE, Babu J, Corona GB, Dong K, Duarte FM, Durand NC, Epstein CB, Fan K, Gaskell E, Hall AW, Ham AM, Knudson MK, Shoresh N, Wekhande S, White CM, Xi W, UM1HG012076, Satpathy AT, Corces MR, Chang SH, Chin IM, Gardner JM, Gardell ZA, Gutierrez JC, Johnson AW, Kampman L, Kasowski M, Lareau CA, Liu V, Ludwig LS, McGinnis CS, Menon S, Qualls A, Sandor K, Turner AW, Ye CJ, Yin Y, Zhang W, UM1HG012077, Wold BJ, Carilli M, Cheong D, Filibam G, Green K, Kawauchi S, Kim C, Liang H, Loving R, Luebbert L, MacGregor G, Merchan AG, Rebboah E, Rezaie N, Sakr J, Sullivan DK, Swarna N, Trout D, Upchurch S, Weber R, Predictive Modeling Awards (contact PI, MPIs (alphabetical by last name), other members (alphabetical by last name)), U01HG011952, Castro CP, Chou E, Feng F, Guerra A, Huang Y, Jiang L, Liu J, Mills RE, Qian W, Qin T, Sartor MA, Sherpa RN, Wang J, Wang Y, Welch JD, Zhang Z, Zhao N, U01HG011967, Mukherjee S, Page CD, Clarke S, Doty RW, Duan Y, Gordan R, Ko KY, Li S, Li B, Thomson A, U01HG012009, Raychaudhuri S, Price A, Ali TA, Dey KK, Durvasula A, Kellis M, U01HG012022, Iakoucheva LM, Kakati T, Chen Y, Benazouz M, Jain S, Zeiberg D, De Paolis Kaluza MC, Velyunskiy M, U01HG012039, Gasch A, Huang K, Jin Y, Lu Q, Miao J, Ohtake M, Scopel E, Steiner RD, Sverchkov Y, U01HG012064, Weng Z, Garber M, Fu Y, Haas N, Li X, Phalke N, Shan SC, Shedd N, Yu T, Zhang Y, Zhou H, U01HG012069, Battle A, Jerby L, Kotler E, Kundu S, Marderstein AR, Montgomery SB, Nigam A, Padhi EM, Patel A, Pritchard J, Raine I, Ramalingam V, Rodrigues KB, Schreiber JM, Singhal A, Sinha R, Wang AT, Network Projects (contact PI, MPIs (alphabetical by last name), other members (alphabetical by last name)), U01HG012041, Abundis M, Bisht D, Chakraborty T, Fan J, Hall DR, Rarani ZH, Jain AK, Kaundal B, Keshari S, McGrail D, Pease NA, Yi VF, U01HG012047, Wu H, Kannan S, Song H, Cai J, Gao Z, Kurzion R, Leu JI, Li F, Liang D, Ming GL, Musunuru K, Qiu Q, Shi J, Su Y, Tishkoff S, Xie N, Yang Q, Yang W, Zhang H, Zhang Z, U01HG012051, Beer MA, Hadjantonakis AK, Adeniyi S, Cho H, Cutler R, Glenn RA, Godovich D, Hu N, Jovanic S, Luo R, Oh JW, Razavi-Mohseni M, Shigaki D, Sidoli S, Vierbuchen T, Wang X, Williams B, Yan J, Yang D, Yang Y, U01HG012059, Sander M, Gaulton KJ, Ren B, Bartosik W, Indralingam HS, Klie A, Mummey H, Okino ML, Wang G, Zemke NR, Zhang K, Zhu H, U01HG012079, Zaitlen N, Ernst J, Langerman J, Li T, Sun Y, U01HG012103, Rudensky AY, Periyakoil PK, Gao VR, Smith MH, Thomas NM, Donlin LT, Lakhanpal A, Southard KM, Ardy RC, Data and Administrative Coordinating Center Awards (contact PI, MPIs (alphabetical by last name), other members (alphabetical by last name)), U24HG012012, Cherry JM, Gerstein MB, Andreeva K, Assis PR, Borsari B, Douglass E, Dong S, Gabdank I, Graham K, Jolanki O, Jou J, Kagda MS, Lee JW, Li M, Lin K, Miyasato SR, Rozowsky J, Small C, Spragins E, Tanaka FY, Whaling IM, Youngworth IA, Sloan CA, U24HG012070, Belter E, Chen X, Chisholm RL, Dickson P, Fan C, Fulton L, Li D, Lindsay T, Luan Y, Luo Y, Lyu H, Ma X, Macias-Velasco J, Miga KH, Quaid K, Stitziel N, Stranger BE, Tomlinson C, Wang J, Zhang W, Zhang B, Zhao G, Zhuo X, IGVF Affiliate Member Projects (contact PIs, other members (alphabetical by last name)), Brennand lab, Brennand K, Ciccia lab, Ciccia A, Hayward SB, Huang JW, Leuzzi G, Taglialatela A, Thakar T, Vaitsiankova A, Dey lab, Dey KK, Ali TA, Gazal lab, Kim A, Grimes lab, Grimes HL, Salomonis N, Gupta lab, Gupta R, Fang S, Lee-Kim V, Heinig lab, Heinig M, Losert C, Jones lab, Jones TR, Donnard E, Murphy M, Roberts E, Song S, Moore lab, Mostafavi lab, Mostafavi S, Sasse A, Spiro A, Pennacchio and Visel lab, Pennacchio LA, Kato M, Kosicki M, Mannion B, Slaven N, Visel A, Pollard lab, Pollard KS, Drusinsky S, Whalen S, Ray lab, Ray J, Harten IA, Ho CH, Reilly lab, Sanjana lab, Sanjana NE, Caragine C, Morris JA, Seruggia lab, Seruggia D, Kutschat AP, Wittibschlager S, Xu lab, Xu H, Fu R, He W, Zhang L, Yi lab, Osorio D, NHGRI Program Management (alphabetical by last name), Bly Z, Calluori S, Gilchrist DA, Hutter CM, Morris SA, Samer EK. Deciphering the impact of genomic variation on function. Nature 2024; 633:47-57. [PMID: 39232149 PMCID: PMC11973978 DOI: 10.1038/s41586-024-07510-0] [Show More Authors] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 05/02/2024] [Indexed: 09/06/2024]
Abstract
Our genomes influence nearly every aspect of human biology-from molecular and cellular functions to phenotypes in health and disease. Studying the differences in DNA sequence between individuals (genomic variation) could reveal previously unknown mechanisms of human biology, uncover the basis of genetic predispositions to diseases, and guide the development of new diagnostic tools and therapeutic agents. Yet, understanding how genomic variation alters genome function to influence phenotype has proved challenging. To unlock these insights, we need a systematic and comprehensive catalogue of genome function and the molecular and cellular effects of genomic variants. Towards this goal, the Impact of Genomic Variation on Function (IGVF) Consortium will combine approaches in single-cell mapping, genomic perturbations and predictive modelling to investigate the relationships among genomic variation, genome function and phenotypes. IGVF will create maps across hundreds of cell types and states describing how coding variants alter protein activity, how noncoding variants change the regulation of gene expression, and how such effects connect through gene-regulatory and protein-interaction networks. These experimental data, computational predictions and accompanying standards and pipelines will be integrated into an open resource that will catalyse community efforts to explore how our genomes influence biology and disease across populations.
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Mateyko N, de Boer CG. Culture Wars: Empirically Determining the Best Approach for Plasmid Library Amplification. ACS Synth Biol 2024; 13:2328-2334. [PMID: 39038190 DOI: 10.1021/acssynbio.4c00377] [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] [Indexed: 07/24/2024]
Abstract
DNA libraries are critical components of many biological assays. These libraries are often kept in plasmids that are amplified in E. coli to generate sufficient material for an experiment. Library uniformity is critical for ensuring that every element in the library is tested similarly and is thought to be influenced by the culture approach used during library amplification. We tested five commonly used culturing methods for their ability to uniformly amplify plasmid libraries: liquid, semisolid agar, cell spreader-spread plates with high or low colony density, and bead-spread plates. Each approach was evaluated with two library types: a random 80-mer library, representing high complexity and low coverage of similar sequence lengths, and a human TF ORF library, representing low complexity and high coverage of diverse sequence lengths. We found that no method was better than liquid culture, which produced relatively uniform libraries regardless of library type. However, when libraries were transformed with high coverage, the culturing method had minimal impact on uniformity or amplification bias. Plating libraries was the worst approach by almost every measure for both library types and, counterintuitively, produced the strongest biases against long sequence representation. Semisolid agar amplified most elements of the library uniformly but also included outliers with orders of magnitude higher abundance. For amplifying DNA libraries, liquid culture, the simplest method, appears to be best.
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Affiliation(s)
- Nicholas Mateyko
- Genome Science and Technology Graduate Program, University of British Columbia, 2222 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada
| | - Carl G de Boer
- School of Biomedical Engineering, University of British Columbia, 2222 Health Sciences Mall, Vancouver, BC V6T 1Z3, Canada
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Xiong S, Zhou J, Tan TK, Chung TH, Tan TZ, Toh SHM, Tang NXN, Jia Y, See YX, Fullwood MJ, Sanda T, Chng WJ. Super enhancer acquisition drives expression of oncogenic PPP1R15B that regulates protein homeostasis in multiple myeloma. Nat Commun 2024; 15:6810. [PMID: 39122682 PMCID: PMC11316114 DOI: 10.1038/s41467-024-50910-z] [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: 06/30/2023] [Accepted: 07/25/2024] [Indexed: 08/12/2024] Open
Abstract
Multiple myeloma is a hematological malignancy arising from immunoglobulin-secreting plasma cells. It remains poorly understood how chromatin rewiring of regulatory elements contributes to tumorigenesis and therapy resistance in myeloma. Here we generate a high-resolution contact map of myeloma-associated super-enhancers by integrating H3K27ac ChIP-seq and HiChIP from myeloma cell lines, patient-derived myeloma cells and normal plasma cells. Our comprehensive transcriptomic and phenomic analyses prioritize candidate genes with biological and clinical implications in myeloma. We show that myeloma cells frequently acquire SE that transcriptionally activate an oncogene PPP1R15B, which encodes a regulatory subunit of the holophosphatase complex that dephosphorylates translation initiation factor eIF2α. Epigenetic silencing or knockdown of PPP1R15B activates pro-apoptotic eIF2α-ATF4-CHOP pathway, while inhibiting protein synthesis and immunoglobulin production. Pharmacological inhibition of PPP1R15B using Raphin1 potentiates the anti-myeloma effect of bortezomib. Our study reveals that myeloma cells are vulnerable to perturbation of PPP1R15B-dependent protein homeostasis, highlighting a promising therapeutic strategy.
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Affiliation(s)
- Sinan Xiong
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Jianbiao Zhou
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore.
- NUS Centre for Cancer Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
| | - Tze King Tan
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Tae-Hoon Chung
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Tuan Zea Tan
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Sabrina Hui-Min Toh
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Nicole Xin Ning Tang
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Yunlu Jia
- Department of Surgical Oncology, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China
| | - Yi Xiang See
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Melissa Jane Fullwood
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
- NUS Centre for Cancer Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
- Institute of Molecular and Cell Biology, Agency for Science, Technology and Research, Singapore, Singapore
| | - Takaomi Sanda
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | - Wee-Joo Chng
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore.
- NUS Centre for Cancer Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Department of Hematology-Oncology, National University Cancer Institute of Singapore (NCIS), National University Health System (NUHS), Singapore, Singapore.
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47
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Li T, Li S, Kang Y, Zhou J, Yi M. Harnessing the evolving CRISPR/Cas9 for precision oncology. J Transl Med 2024; 22:749. [PMID: 39118151 PMCID: PMC11312220 DOI: 10.1186/s12967-024-05570-4] [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: 04/30/2024] [Accepted: 08/04/2024] [Indexed: 08/10/2024] Open
Abstract
The Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/Cas9 system, a groundbreaking innovation in genetic engineering, has revolutionized our approach to surmounting complex diseases, culminating in CASGEVY™ approved for sickle cell anemia. Derived from a microbial immune defense mechanism, CRISPR/Cas9, characterized as precision, maneuverability and universality in gene editing, has been harnessed as a versatile tool for precisely manipulating DNA in mammals. In the process of applying it to practice, the consecutive exploitation of novel orthologs and variants never ceases. It's conducive to understanding the essentialities of diseases, particularly cancer, which is crucial for diagnosis, prevention, and treatment. CRISPR/Cas9 is used not only to investigate tumorous genes functioning but also to model disparate cancers, providing valuable insights into tumor biology, resistance, and immune evasion. Upon cancer therapy, CRISPR/Cas9 is instrumental in developing individual and precise cancer therapies that can selectively activate or deactivate genes within tumor cells, aiming to cripple tumor growth and invasion and sensitize cancer cells to treatments. Furthermore, it facilitates the development of innovative treatments, enhancing the targeting efficiency of reprogrammed immune cells, exemplified by advancements in CAR-T regimen. Beyond therapy, it is a potent tool for screening susceptible genes, offering the possibility of intervening before the tumor initiative or progresses. However, despite its vast potential, the application of CRISPR/Cas9 in cancer research and therapy is accompanied by significant efficacy, efficiency, technical, and safety considerations. Escalating technology innovations are warranted to address these issues. The CRISPR/Cas9 system is revolutionizing cancer research and treatment, opening up new avenues for advancements in our understanding and management of cancers. The integration of this evolving technology into clinical practice promises a new era of precision oncology, with targeted, personalized, and potentially curative therapies for cancer patients.
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Affiliation(s)
- Tianye Li
- Department of Gynecology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310009, People's Republic of China
- Zhejiang Provincial Clinical Research Center for Obstetrics and Gynecology, Hangzhou, 310000, People's Republic of China
| | - Shuiquan Li
- Department of Rehabilitation and Traditional Chinese Medicine, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310009, People's Republic of China
| | - Yue Kang
- Department of Obstetrics and Gynecology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, People's Republic of China
| | - Jianwei Zhou
- Department of Gynecology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310009, People's Republic of China.
- Zhejiang Provincial Clinical Research Center for Obstetrics and Gynecology, Hangzhou, 310000, People's Republic of China.
| | - Ming Yi
- Department of Breast Surgery, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, 310000, People's Republic of China.
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48
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Lin J, Luo R, Pinello L. EPInformer: a scalable deep learning framework for gene expression prediction by integrating promoter-enhancer sequences with multimodal epigenomic data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.01.606099. [PMID: 39131276 PMCID: PMC11312614 DOI: 10.1101/2024.08.01.606099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Transcriptional regulation, critical for cellular differentiation and adaptation to environmental changes, involves coordinated interactions among DNA sequences, regulatory proteins, and chromatin architecture. Despite extensive data from consortia like ENCODE, understanding the dynamics of cis-regulatory elements (CREs) in gene expression remains challenging. Deep learning is a powerful tool for learning gene expression and epigenomic signals from DNA sequences, exhibiting superior performance compared to conventional machine learning approaches. However, even the most advanced deep learning-based methods may fall short in capturing the regulatory effects of distal elements such as enhancers, limiting their predictive accuracy. In addition, these methods may require significant resources to train or to adapt to newly generated data. To address these challenges, we present EPInformer, a scalable deep-learning framework for predicting gene expression by integrating promoter-enhancer interactions with their sequences, epigenomic signals, and chromatin contacts. Our model outperforms existing gene expression prediction models in rigorous cross-chromosome validation, accurately recapitulates enhancer-gene interactions validated by CRISPR perturbation experiments, and identifies crucial transcription factor motifs within regulatory sequences. EPInformer is available as open-source software at https://github.com/pinellolab/EPInformer.
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Affiliation(s)
- Jiecong Lin
- Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Department of Pathology, Harvard Medical School, Boston, Massachusetts 02129, USA
- Department of Computer Science, The University of Hong Kong, Hong Kong, China
| | - Ruibang Luo
- Department of Computer Science, The University of Hong Kong, Hong Kong, China
| | - Luca Pinello
- Molecular Pathology Unit, Center for Cancer Research, Massachusetts General Hospital, Department of Pathology, Harvard Medical School, Boston, Massachusetts 02129, USA
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49
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McCutcheon SR, Rohm D, Iglesias N, Gersbach CA. Epigenome editing technologies for discovery and medicine. Nat Biotechnol 2024; 42:1199-1217. [PMID: 39075148 DOI: 10.1038/s41587-024-02320-1] [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: 11/14/2023] [Accepted: 06/19/2024] [Indexed: 07/31/2024]
Abstract
Epigenome editing has rapidly evolved in recent years, with diverse applications that include elucidating gene regulation mechanisms, annotating coding and noncoding genome functions and programming cell state and lineage specification. Importantly, given the ubiquitous role of epigenetics in complex phenotypes, epigenome editing has unique potential to impact a broad spectrum of diseases. By leveraging powerful DNA-targeting technologies, such as CRISPR, epigenome editing exploits the heritable and reversible mechanisms of epigenetics to alter gene expression without introducing DNA breaks, inducing DNA damage or relying on DNA repair pathways.
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Affiliation(s)
- Sean R McCutcheon
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA
| | - Dahlia Rohm
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA
| | - Nahid Iglesias
- Department of Biomedical Engineering, Duke University, Durham, NC, USA
- Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA
| | - Charles A Gersbach
- Department of Biomedical Engineering, Duke University, Durham, NC, USA.
- Center for Advanced Genomic Technologies, Duke University, Durham, NC, USA.
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50
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Liu W, Zhong W, Giusti-Rodríguez P, Jiang Z, Wang GW, Sun H, Hu M, Li Y. SnapHiC-G: identifying long-range enhancer-promoter interactions from single-cell Hi-C data via a global background model. Brief Bioinform 2024; 25:bbae426. [PMID: 39222061 PMCID: PMC11367764 DOI: 10.1093/bib/bbae426] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Revised: 07/05/2024] [Accepted: 08/13/2024] [Indexed: 09/04/2024] Open
Abstract
Harnessing the power of single-cell genomics technologies, single-cell Hi-C (scHi-C) and its derived technologies provide powerful tools to measure spatial proximity between regulatory elements and their target genes in individual cells. Using a global background model, we propose SnapHiC-G, a computational method, to identify long-range enhancer-promoter interactions from scHi-C data. We applied SnapHiC-G to scHi-C datasets generated from mouse embryonic stem cells and human brain cortical cells. SnapHiC-G achieved high sensitivity in identifying long-range enhancer-promoter interactions. Moreover, SnapHiC-G can identify putative target genes for noncoding genome-wide association study (GWAS) variants, and the genetic heritability of neuropsychiatric diseases is enriched for single-nucleotide polymorphisms (SNPs) within SnapHiC-G-identified interactions in a cell-type-specific manner. In sum, SnapHiC-G is a powerful tool for characterizing cell-type-specific enhancer-promoter interactions from complex tissues and can facilitate the discovery of chromatin interactions important for gene regulation in biologically relevant cell types.
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Affiliation(s)
- Weifang Liu
- Department of Biostatistics, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Wujuan Zhong
- Biostatistics and Research Decision Sciences, Merck & Co., Inc., 126 East Lincoln Ave, Rahway, New Jersey 07065, United States
| | - Paola Giusti-Rodríguez
- Department of Psychiatry, University of Florida, 1149 Newel Dr., Gainesville, FL 32611, United States
| | - Zhiyun Jiang
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599, United States
| | - Geoffery W Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
| | - Huaigu Sun
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599, United States
| | - Ming Hu
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, 9500 Euclid Avenue, Cleveland, OH 44196, United States
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, 135 Dauer Drive, Chapel Hill, NC 27599, United States
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599, United States
- Department of Computer Science, University of North Carolina at Chapel Hill, 201 S. Columbia St, Chapel Hill, NC 27599, United States
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