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Chmykhalo VK, Deev RV, Tokarev AT, Polunina YA, Xue L, Shidlovskii YV. SWI/SNF Complex Connects Signaling and Epigenetic State in Cells of Nervous System. Mol Neurobiol 2024:10.1007/s12035-024-04355-6. [PMID: 39002058 DOI: 10.1007/s12035-024-04355-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2024] [Accepted: 07/06/2024] [Indexed: 07/15/2024]
Abstract
SWI/SNF protein complexes are evolutionarily conserved epigenetic regulators described in all eukaryotes. In metameric animals, the complexes are involved in all processes occurring in the nervous system, from neurogenesis to higher brain functions. On the one hand, the range of roles is wide because the SWI/SNF complexes act universally by mobilizing the nucleosomes in a chromatin template at multiple loci throughout the genome. On the other hand, the complexes mediate the action of multiple signaling pathways that control most aspects of neural tissue development and function. The issues are discussed to provide insight into the molecular basis of the multifaceted role of SWI/SNFs in cell cycle regulation, DNA repair, activation of immediate-early genes, neurogenesis, and brain and connectome formation. An overview is additionally provided for the molecular basis of nervous system pathologies associated with the SWI/SNF complexes and their contribution to neuroinflammation and neurodegeneration. Finally, we discuss the idea that SWI/SNFs act as an integration platform to connect multiple signaling and genetic programs.
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Affiliation(s)
- Victor K Chmykhalo
- Laboratory of Gene Expression Regulation in Development, Institute of Gene Biology, Russian Academy of Sciences, 34/5 Vavilova St, Moscow, 119334, Russia.
| | - Roman V Deev
- Laboratory of Gene Expression Regulation in Development, Institute of Gene Biology, Russian Academy of Sciences, 34/5 Vavilova St, Moscow, 119334, Russia
| | - Artemiy T Tokarev
- Laboratory of Gene Expression Regulation in Development, Institute of Gene Biology, Russian Academy of Sciences, 34/5 Vavilova St, Moscow, 119334, Russia
| | - Yulia A Polunina
- Laboratory of Gene Expression Regulation in Development, Institute of Gene Biology, Russian Academy of Sciences, 34/5 Vavilova St, Moscow, 119334, Russia
| | - Lei Xue
- School of Life Science and Technology, The First Rehabilitation Hospital of Shanghai, Tongji University, Shanghai, China
| | - Yulii V Shidlovskii
- Laboratory of Gene Expression Regulation in Development, Institute of Gene Biology, Russian Academy of Sciences, 34/5 Vavilova St, Moscow, 119334, Russia
- Department of Biology and General Genetics, Sechenov University, Moscow, Russia
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2
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Pletenev I, Bazarevich M, Zagirova D, Kononkova A, Cherkasov A, Efimova O, Tiukacheva E, Morozov K, Ulianov K, Komkov D, Tvorogova A, Golimbet V, Kondratyev N, Razin S, Khaitovich P, Ulianov S, Khrameeva E. Extensive long-range polycomb interactions and weak compartmentalization are hallmarks of human neuronal 3D genome. Nucleic Acids Res 2024; 52:6234-6252. [PMID: 38647066 PMCID: PMC11194087 DOI: 10.1093/nar/gkae271] [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: 11/07/2023] [Revised: 03/21/2024] [Accepted: 04/06/2024] [Indexed: 04/25/2024] Open
Abstract
Chromatin architecture regulates gene expression and shapes cellular identity, particularly in neuronal cells. Specifically, polycomb group (PcG) proteins enable establishment and maintenance of neuronal cell type by reorganizing chromatin into repressive domains that limit the expression of fate-determining genes and sustain distinct gene expression patterns in neurons. Here, we map the 3D genome architecture in neuronal and non-neuronal cells isolated from the Wernicke's area of four human brains and comprehensively analyze neuron-specific aspects of chromatin organization. We find that genome segregation into active and inactive compartments is greatly reduced in neurons compared to other brain cells. Furthermore, neuronal Hi-C maps reveal strong long-range interactions, forming a specific network of PcG-mediated contacts in neurons that is nearly absent in other brain cells. These interacting loci contain developmental transcription factors with repressed expression in neurons and other mature brain cells. But only in neurons, they are rich in bivalent promoters occupied by H3K4me3 histone modification together with H3K27me3, which points to a possible functional role of PcG contacts in neurons. Importantly, other layers of chromatin organization also exhibit a distinct structure in neurons, characterized by an increase in short-range interactions and a decrease in long-range ones.
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Affiliation(s)
- Ilya A Pletenev
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Maria Bazarevich
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Diana R Zagirova
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
- A.A. Kharkevich Institute for Information Transmission Problems, Moscow 127051, Russia
| | - Anna D Kononkova
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Alexander V Cherkasov
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Olga I Efimova
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Eugenia A Tiukacheva
- Department of Biological and Medical Physics, Moscow Institute of Physics and Technology, Moscow 141700, Russia
- Department of Molecular Biology, Faculty of Biology, M.V. Lomonosov Moscow State University, Moscow 119991, Russia
- CNRS UMR9018, Institut Gustave Roussy, Villejuif 94805, France
- Koltzov Institute of Developmental Biology, Russian Academy of Sciences, Moscow 119334, Russia
- Department of Cellular Genomics, Institute of Gene Biology, Russian Academy of Sciences, Moscow 119334, Russia
| | - Kirill V Morozov
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Kirill A Ulianov
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Dmitriy Komkov
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Institute of Gene Biology, Russian Academy of Sciences, Moscow 119334, Russia
| | - Anna V Tvorogova
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Institute of Gene Biology, Russian Academy of Sciences, Moscow 119334, Russia
| | - Vera E Golimbet
- Laboratory of Clinical Genetics, Mental Health Research Center, Moscow 115522, Russia
| | - Nikolay V Kondratyev
- Laboratory of Clinical Genetics, Mental Health Research Center, Moscow 115522, Russia
| | - Sergey V Razin
- Department of Molecular Biology, Faculty of Biology, M.V. Lomonosov Moscow State University, Moscow 119991, Russia
- Department of Cellular Genomics, Institute of Gene Biology, Russian Academy of Sciences, Moscow 119334, Russia
| | - Philipp Khaitovich
- Vladimir Zelman Center for Neurobiology and Brain Rehabilitation, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
| | - Sergey V Ulianov
- Department of Molecular Biology, Faculty of Biology, M.V. Lomonosov Moscow State University, Moscow 119991, Russia
- Department of Cellular Genomics, Institute of Gene Biology, Russian Academy of Sciences, Moscow 119334, Russia
| | - Ekaterina E Khrameeva
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Moscow 121205, Russia
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3
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Palmisano I, Liu T, Gao W, Zhou L, Merkenschlager M, Müller F, Chadwick J, Rivolta RT, Kong G, King JWD, Al-jibury E, Yan Y, Carlino A, Collison B, De Vitis E, Gongala S, De Virgiliis F, Wang Z, Di Giovanni S. Three-dimensional chromatin mapping of sensory neurons reveals that cohesin-dependent genomic domains are required for axonal regeneration. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.09.597974. [PMID: 38895406 PMCID: PMC11185766 DOI: 10.1101/2024.06.09.597974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/21/2024]
Abstract
The in vivo three-dimensional genomic architecture of adult mature neurons at homeostasis and after medically relevant perturbations such as axonal injury remains elusive. Here we address this knowledge gap by mapping the three-dimensional chromatin architecture and gene expression programme at homeostasis and after sciatic nerve injury in wild-type and cohesin-deficient mouse sensory dorsal root ganglia neurons via combinatorial Hi-C and RNA-seq. We find that cohesin is required for the full induction of the regenerative transcriptional program, by organising 3D genomic domains required for the activation of regenerative genes. Importantly, loss of cohesin results in disruption of chromatin architecture at regenerative genes and severely impaired nerve regeneration. Together, these data provide an original three-dimensional chromatin map of adult sensory neurons in vivo and demonstrate a role for cohesin-dependent chromatin interactions in neuronal regeneration.
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Affiliation(s)
- Ilaria Palmisano
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
- Department of Neuroscience, The Ohio State University, Columbus, 43210, OH, USA
| | - Tong Liu
- Department of Computer Science, University of Miami, 330M Ungar Building, 1365 Memorial Drive, Coral Gables, FL 33124-4245 Miami, FL, USA
| | - Wei Gao
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - Luming Zhou
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | | | - Franziska Müller
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - Jessica Chadwick
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - Rebecca Toscano Rivolta
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - Guiping Kong
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - James WD King
- MRC LMS, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
| | - Ediem Al-jibury
- MRC LMS, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
| | - Yuyang Yan
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - Alessandro Carlino
- Department of Neuroscience, The Ohio State University, Columbus, 43210, OH, USA
| | - Bryce Collison
- Department of Neuroscience, The Ohio State University, Columbus, 43210, OH, USA
| | - Eleonora De Vitis
- Department of Neuroscience, The Ohio State University, Columbus, 43210, OH, USA
| | - Sree Gongala
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - Francesco De Virgiliis
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
| | - Zheng Wang
- Department of Computer Science, University of Miami, 330M Ungar Building, 1365 Memorial Drive, Coral Gables, FL 33124-4245 Miami, FL, USA
| | - Simone Di Giovanni
- Department of Medicine, Division of Brain Sciences, Centre for Restorative Neuroscience, Imperial College London, London, W12 0NN, UK
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4
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Birnbaum R, Weinberger DR. The Genesis of Schizophrenia: An Origin Story. Am J Psychiatry 2024; 181:482-492. [PMID: 38822584 DOI: 10.1176/appi.ajp.20240305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/03/2024]
Abstract
Schizophrenia is routinely referred to as a neurodevelopmental disorder, but the role of brain development in a disorder typically diagnosed during early adult life is enigmatic. The authors revisit the neurodevelopmental model of schizophrenia with genomic insights from the most recent schizophrenia clinical genetic association studies, transcriptomic and epigenomic analyses from human postmortem brain studies, and analyses from cellular models that recapitulate neurodevelopment. Emerging insights into schizophrenia genetic risk continue to converge on brain development, particularly stages of early brain development, that may be perturbed to deviate from a typical, normative course, resulting in schizophrenia clinical symptomatology. As the authors explicate, schizophrenia genetic risk is likely dynamic and context dependent, with effects of genetic risk varying spatiotemporally, across the neurodevelopmental continuum. Optimizing therapeutic strategies for the heterogeneous collective of individuals with schizophrenia may likely be guided by leveraging markers of genetic risk and derivative functional insights, well before the emergence of psychosis. Ultimately, rather than a focus on therapeutic intervention during adolescence or adulthood, principles of prediction and prophylaxis in the pre- and perinatal and neonatal stages may best comport with the biology of schizophrenia to address the early-stage perturbations that alter the normative neurodevelopmental trajectory.
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Affiliation(s)
- Rebecca Birnbaum
- Departments of Psychiatry, Genetics, and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York (Birnbaum); Lieber Institute of Brain Development, Maltz Research Laboratory, and Departments of Psychiatry, Neurology, Neuroscience, and Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore (Weinberger)
| | - Daniel R Weinberger
- Departments of Psychiatry, Genetics, and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York (Birnbaum); Lieber Institute of Brain Development, Maltz Research Laboratory, and Departments of Psychiatry, Neurology, Neuroscience, and Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore (Weinberger)
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5
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Zhang L, Bartosovic M. Single-cell mapping of cell-type specific chromatin architecture in the central nervous system. Curr Opin Struct Biol 2024; 86:102824. [PMID: 38723561 DOI: 10.1016/j.sbi.2024.102824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 03/22/2024] [Accepted: 04/08/2024] [Indexed: 05/19/2024]
Abstract
Determining how chromatin is structured in the nucleus is critical to studying its role in gene regulation. Recent advances in the analysis of single-cell chromatin architecture have considerably improved our understanding of cell-type-specific chromosome conformation and nuclear architecture. In this review, we discuss the methods used for analysis of 3D chromatin conformation, including sequencing-based methods, imaging-based techniques, and computational approaches. We further review the application of these methods in the study of the role of chromatin topology in neural development and disorders.
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Affiliation(s)
- Letian Zhang
- Department of Biochemistry and Biophysics, Svante Arrhenius väg 16C, 162 53, Stockholm, Sweden. https://twitter.com/LetianZHANG_
| | - Marek Bartosovic
- Department of Biochemistry and Biophysics, Svante Arrhenius väg 16C, 162 53, Stockholm, Sweden.
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6
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Tan Q, Xu X, Zhou H, Jia J, Jia Y, Tu H, Zhou D, Wu X. A multi-ancestry cerebral cortex transcriptome-wide association study identifies genes associated with smoking behaviors. Mol Psychiatry 2024:10.1038/s41380-024-02605-6. [PMID: 38816585 DOI: 10.1038/s41380-024-02605-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 04/30/2024] [Accepted: 05/09/2024] [Indexed: 06/01/2024]
Abstract
Transcriptome-wide association studies (TWAS) have provided valuable insight in identifying genes that may impact cigarette smoking. Most of previous studies, however, mainly focused on European ancestry. Limited TWAS studies have been conducted across multiple ancestries to explore genes that may impact smoking behaviors. In this study, we used cis-eQTL data of cerebral cortex from multiple ancestries in MetaBrain, including European, East Asian, and African samples, as reference panels to perform multi-ancestry TWAS analyses on ancestry-matched GWASs of four smoking behaviors including smoking initiation, smoking cessation, age of smoking initiation, and number of cigarettes per day in GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN). Multiple-ancestry fine-mapping approach was conducted to identify credible gene sets associated with these four traits. Enrichment and module network analyses were further performed to explore the potential roles of these identified gene sets. A total of 719 unique genes were identified to be associated with at least one of the four smoking traits across ancestries. Among those, 249 genes were further prioritized as putative causal genes in multiple ancestry-based fine-mapping approach. Several well-known smoking-related genes, including PSMA4, IREB2, and CHRNA3, showed high confidence across ancestries. Some novel genes, e.g., TSPAN3 and ANK2, were also identified in the credible sets. The enrichment analysis identified a series of critical pathways related to smoking such as synaptic transmission and glutamate receptor activity. Leveraging the power of the latest multi-ancestry GWAS and eQTL data sources, this study revealed hundreds of genes and relevant biological processes related to smoking behaviors. These findings provide new insights for future functional studies on smoking behaviors.
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Affiliation(s)
- Qilong Tan
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, 310058, China
| | - Xiaohang Xu
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, 310058, China
| | - Hanyi Zhou
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, 310058, China
| | - Junlin Jia
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, 310058, China
| | - Yubing Jia
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, 310058, China
| | - Huakang Tu
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, 310058, China
- National Institute for Data Science in Health and Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Dan Zhou
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, 310058, China
- Cancer Center, Zhejiang University, Hangzhou, 310058, China
| | - Xifeng Wu
- Department of Big Data in Health Science School of Public Health, Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, 310058, China.
- School of Medicine and Health Science, George Washington University, Washington, DC, USA.
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7
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Pratt HE, Andrews G, Shedd N, Phalke N, Li T, Pampari A, Jensen M, Wen C, Consortium P, Gandal MJ, Geschwind DH, Gerstein M, Moore J, Kundaje A, Colubri A, Weng Z. Using a comprehensive atlas and predictive models to reveal the complexity and evolution of brain-active regulatory elements. SCIENCE ADVANCES 2024; 10:eadj4452. [PMID: 38781344 PMCID: PMC11114231 DOI: 10.1126/sciadv.adj4452] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 04/25/2024] [Indexed: 05/25/2024]
Abstract
Most genetic variants associated with psychiatric disorders are located in noncoding regions of the genome. To investigate their functional implications, we integrate epigenetic data from the PsychENCODE Consortium and other published sources to construct a comprehensive atlas of candidate brain cis-regulatory elements. Using deep learning, we model these elements' sequence syntax and predict how binding sites for lineage-specific transcription factors contribute to cell type-specific gene regulation in various types of glia and neurons. The elements' evolutionary history suggests that new regulatory information in the brain emerges primarily via smaller sequence mutations within conserved mammalian elements rather than entirely new human- or primate-specific sequences. However, primate-specific candidate elements, particularly those active during fetal brain development and in excitatory neurons and astrocytes, are implicated in the heritability of brain-related human traits. Additionally, we introduce PsychSCREEN, a web-based platform offering interactive visualization of PsychENCODE-generated genetic and epigenetic data from diverse brain cell types in individuals with psychiatric disorders and healthy controls.
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Affiliation(s)
- Henry E. Pratt
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Gregory Andrews
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Nicole Shedd
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Nishigandha Phalke
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Tongxin Li
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
- Khoury College of Computer Science, Northeastern University, Boston, MA 02115, USA
| | - Anusri Pampari
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Matthew Jensen
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Cindy Wen
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | | | - Michael J. Gandal
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, The Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Daniel H. Geschwind
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Mark Gerstein
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Jill Moore
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, 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
| | - Andrés Colubri
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Zhiping Weng
- Department of Genomics and Computational Biology, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
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8
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Emani PS, Liu JJ, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee CY, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken TE, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard JF, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman GE, Huang A, Jiang Y, Jin T, Jorstad NL, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran JR, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan AS, Riesenmy TR, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini KJ, Wamsley B, Wang G, Xia Y, Xiao S, Yang AC, Zheng S, Gandal MJ, Lee D, Lein ES, Roussos P, Sestan N, Weng Z, White KP, Won H, Girgenti MJ, Zhang J, Wang D, Geschwind D, Gerstein M. Single-cell genomics and regulatory networks for 388 human brains. Science 2024; 384:eadi5199. [PMID: 38781369 DOI: 10.1126/science.adi5199] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Accepted: 04/05/2024] [Indexed: 05/25/2024]
Abstract
Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.
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Affiliation(s)
- Prashant S Emani
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Jason J Liu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Declan Clarke
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Matthew Jensen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Chirag Gupta
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Ran Meng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Che Yu Lee
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Siwei Xu
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Cagatay Dursun
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Shaoke Lou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Yuhang Chen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Zhiyuan Chu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Timur Galeev
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Ahyeon Hwang
- Department of Computer Science, University of California, Irvine, CA 92697, USA
- Mathematical, Computational and Systems Biology, University of California, Irvine, CA 92697, USA
| | - Yunyang Li
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
| | - Pengyu Ni
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Xiao Zhou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | | | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Lucy Bicks
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Tanima Chatterjee
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | | | - Yuyan Cheng
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Yi Dai
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Ziheng Duan
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | | | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Michael Gancz
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Diego Garrido-Martín
- Department of Genetics, Microbiology and Statistics, Universitat de Barcelona, Barcelona 08028, Spain
| | - Sophia Gaynor-Gillett
- Tempus Labs, Chicago, IL 60654, USA
- Department of Biology, Cornell College, Mount Vernon, IA 52314, USA
| | - Jennifer Grundman
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Natalie Hawken
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Ella Henry
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Ao Huang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
| | - Yunzhe Jiang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Ting Jin
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | | | - Riki Kawaguchi
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA 90095, USA
| | - Saniya Khullar
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Jianyin Liu
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Junhao Liu
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Shuang Liu
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Shaojie Ma
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | - Samantha Mazariegos
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Jill Moore
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | | | - Eric Nguyen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Nishigandha Phalke
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Milos Pjanic
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Henry Pratt
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Diana Quintero
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | | | - Tiernon R Riesenmy
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
| | - Nicole Shedd
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | | | | | - Rosemarie Terwilliger
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06520, USA
| | | | - Brie Wamsley
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Gaoyuan Wang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Yan Xia
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Shaohua Xiao
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Andrew C Yang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Suchen Zheng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
| | - Michael J Gandal
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles CA, 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA 98109, USA
- Department of Neurological Surgery, University of Washington, Seattle, WA 98195, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale University, New Haven, CT 06510, USA
| | - Zhiping Weng
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA 01605, USA
| | - Kevin P White
- Yong Loo Lin School of Medicine, National University of Singapore, 117597 Singapore
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Matthew J Girgenti
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06520, USA
- Clinical Neuroscience Division, National Center for Posttraumatic Stress Disorder, Veterans Affairs Connecticut Healthcare System, West Haven, CT 06516, USA
| | - Jing Zhang
- Department of Computer Science, University of California, Irvine, CA 92697, USA
| | - Daifeng Wang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI 53705, USA
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Daniel Geschwind
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, CA 90095, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT 06520, USA
- Department of Computer Science, Yale University, New Haven, CT 06520, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT 06520, USA
- Department of Biomedical Informatics & Data Science, Yale University, New Haven, CT 06520, USA
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9
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Zeng B, Bendl J, Deng C, Lee D, Misir R, Reach SM, Kleopoulos SP, Auluck P, Marenco S, Lewis DA, Haroutunian V, Ahituv N, Fullard JF, Hoffman GE, Roussos P. Genetic regulation of cell type-specific chromatin accessibility shapes brain disease etiology. Science 2024; 384:eadh4265. [PMID: 38781378 DOI: 10.1126/science.adh4265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 12/20/2023] [Indexed: 05/25/2024]
Abstract
Nucleotide variants in cell type-specific gene regulatory elements in the human brain are risk factors for human disease. We measured chromatin accessibility in 1932 aliquots of sorted neurons and non-neurons from 616 human postmortem brains and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci (caQTLs). Only 10.4% of caQTLs are shared between neurons and non-neurons, which supports cell type-specific genetic regulation of the brain regulome. Incorporating allele-specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms that underlie disease risk. Using massively parallel reporter assays in induced excitatory neurons, we screened 19,893 brain QTLs and identified the functional impact of 476 regulatory variants. Combined, this comprehensive resource captures variation in the human brain regulome and provides insights into disease etiology.
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Affiliation(s)
- Biao Zeng
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Chengyu Deng
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ruth Misir
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sarah M Reach
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Steven P Kleopoulos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Pavan Auluck
- Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD 20892, USA
| | - Stefano Marenco
- Human Brain Collection Core, National Institute of Mental Health-Intramural Research Program, Bethesda, MD 20892, USA
| | - David A Lewis
- Translational Neuroscience Program, Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213, USA
| | - Vahram Haroutunian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research, Education and Clinical Centers, James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Nadav Ahituv
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA 94158, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA 94158, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research, Education and Clinical Centers, James J. Peters VA Medical Center, Bronx, NY 10468, USA
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10
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Zagirova D, Kononkova A, Vaulin N, Khrameeva E. From compartments to loops: understanding the unique chromatin organization in neuronal cells. Epigenetics Chromatin 2024; 17:18. [PMID: 38783373 PMCID: PMC11112951 DOI: 10.1186/s13072-024-00538-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Accepted: 04/17/2024] [Indexed: 05/25/2024] Open
Abstract
The three-dimensional organization of the genome plays a central role in the regulation of cellular functions, particularly in the human brain. This review explores the intricacies of chromatin organization, highlighting the distinct structural patterns observed between neuronal and non-neuronal brain cells. We integrate findings from recent studies to elucidate the characteristics of various levels of chromatin organization, from differential compartmentalization and topologically associating domains (TADs) to chromatin loop formation. By defining the unique chromatin landscapes of neuronal and non-neuronal brain cells, these distinct structures contribute to the regulation of gene expression specific to each cell type. In particular, we discuss potential functional implications of unique neuronal chromatin organization characteristics, such as weaker compartmentalization, neuron-specific TAD boundaries enriched with active histone marks, and an increased number of chromatin loops. Additionally, we explore the role of Polycomb group (PcG) proteins in shaping cell-type-specific chromatin patterns. This review further emphasizes the impact of variations in chromatin architecture between neuronal and non-neuronal cells on brain development and the onset of neurological disorders. It highlights the need for further research to elucidate the details of chromatin organization in the human brain in order to unravel the complexities of brain function and the genetic mechanisms underlying neurological disorders. This research will help bridge a significant gap in our comprehension of the interplay between chromatin structure and cell functions.
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Affiliation(s)
- Diana Zagirova
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard 30, Build.1, Moscow, 121205, Russia
- Research and Training Center on Bioinformatics, Institute for Information Transmission Problems (Kharkevich Institute) RAS, Bolshoy Karetny per. 19, Build.1, Moscow, 127051, Russia
| | - Anna Kononkova
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard 30, Build.1, Moscow, 121205, Russia
| | - Nikita Vaulin
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard 30, Build.1, Moscow, 121205, Russia
| | - Ekaterina Khrameeva
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard 30, Build.1, Moscow, 121205, Russia.
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11
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Meng X, Zhang S, Zhou S, Ma Y, Yu X, Guan L. Putative Risk Biomarkers of Bipolar Disorder in At-risk Youth. Neurosci Bull 2024:10.1007/s12264-024-01219-w. [PMID: 38710851 DOI: 10.1007/s12264-024-01219-w] [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: 11/23/2023] [Accepted: 03/08/2024] [Indexed: 05/08/2024] Open
Abstract
Bipolar disorder is a highly heritable and functionally impairing disease. The recognition and intervention of BD especially that characterized by early onset remains challenging. Risk biomarkers for predicting BD transition among at-risk youth may improve disease prognosis. We reviewed the more recent clinical studies to find possible pre-diagnostic biomarkers in youth at familial or (and) clinical risk of BD. Here we found that putative biomarkers for predicting conversion to BD include findings from multiple sample sources based on different hypotheses. Putative risk biomarkers shown by perspective studies are higher bipolar polygenetic risk scores, epigenetic alterations, elevated immune parameters, front-limbic system deficits, and brain circuit dysfunction associated with emotion and reward processing. Future studies need to enhance machine learning integration, make clinical detection methods more objective, and improve the quality of cohort studies.
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Affiliation(s)
- Xinyu Meng
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Shengmin Zhang
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Shuzhe Zhou
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Yantao Ma
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Xin Yu
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China
| | - Lili Guan
- Peking University Institute of Mental Health, NHC Key Laboratory of Mental Health (Peking University), National Clinical Research Center for Mental Disorders (Peking University Sixth Hospital), Beijing, 100191, China.
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12
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Zhu B, Ainsworth RI, Wang Z, Liu Z, Sierra S, Deng C, Callado LF, Meana JJ, Wang W, Lu C, González-Maeso J. Antipsychotic-induced epigenomic reorganization in frontal cortex of individuals with schizophrenia. eLife 2024; 12:RP92393. [PMID: 38648100 PMCID: PMC11034945 DOI: 10.7554/elife.92393] [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: 04/25/2024] Open
Abstract
Genome-wide association studies have revealed >270 loci associated with schizophrenia risk, yet these genetic factors do not seem to be sufficient to fully explain the molecular determinants behind this psychiatric condition. Epigenetic marks such as post-translational histone modifications remain largely plastic during development and adulthood, allowing a dynamic impact of environmental factors, including antipsychotic medications, on access to genes and regulatory elements. However, few studies so far have profiled cell-specific genome-wide histone modifications in postmortem brain samples from schizophrenia subjects, or the effect of antipsychotic treatment on such epigenetic marks. Here, we conducted ChIP-seq analyses focusing on histone marks indicative of active enhancers (H3K27ac) and active promoters (H3K4me3), alongside RNA-seq, using frontal cortex samples from antipsychotic-free (AF) and antipsychotic-treated (AT) individuals with schizophrenia, as well as individually matched controls (n=58). Schizophrenia subjects exhibited thousands of neuronal and non-neuronal epigenetic differences at regions that included several susceptibility genetic loci, such as NRG1, DISC1, and DRD3. By analyzing the AF and AT cohorts separately, we identified schizophrenia-associated alterations in specific transcription factors, their regulatees, and epigenomic and transcriptomic features that were reversed by antipsychotic treatment; as well as those that represented a consequence of antipsychotic medication rather than a hallmark of schizophrenia in postmortem human brain samples. Notably, we also found that the effect of age on epigenomic landscapes was more pronounced in frontal cortex of AT-schizophrenics, as compared to AF-schizophrenics and controls. Together, these data provide important evidence of epigenetic alterations in the frontal cortex of individuals with schizophrenia, and remark for the first time on the impact of age and antipsychotic treatment on chromatin organization.
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Affiliation(s)
- Bohan Zhu
- Department of Chemical Engineering, Virginia TechBlacksburgUnited States
| | - Richard I Ainsworth
- Department of Chemistry and Biochemistry, University of California, San DiegoLa JollaUnited States
| | - Zengmiao Wang
- Department of Chemistry and Biochemistry, University of California, San DiegoLa JollaUnited States
| | - Zhengzhi Liu
- Department of Biomedical Engineering and Mechanics, Virginia TechBlacksburgUnited States
| | - Salvador Sierra
- Department of Physiology and Biophysics, Virginia Commonwealth University School of MedicineRichmondUnited States
| | - Chengyu Deng
- Department of Chemical Engineering, Virginia TechBlacksburgUnited States
| | - Luis F Callado
- Department of Pharmacology, University of the Basque Country UPV/EHU, CIBERSAM, Biocruces Health Research InstituteBizkaiaSpain
| | - J Javier Meana
- Department of Pharmacology, University of the Basque Country UPV/EHU, CIBERSAM, Biocruces Health Research InstituteBizkaiaSpain
| | - Wei Wang
- Department of Chemistry and Biochemistry, University of California, San DiegoLa JollaUnited States
- Department of Cellular and Molecular Medicine, University of California, San DiegoLa JollaUnited States
| | - Chang Lu
- Department of Chemical Engineering, Virginia TechBlacksburgUnited States
| | - Javier González-Maeso
- Department of Physiology and Biophysics, Virginia Commonwealth University School of MedicineRichmondUnited States
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13
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Emani PS, Liu JJ, Clarke D, Jensen M, Warrell J, Gupta C, Meng R, Lee CY, Xu S, Dursun C, Lou S, Chen Y, Chu Z, Galeev T, Hwang A, Li Y, Ni P, Zhou X, Bakken TE, Bendl J, Bicks L, Chatterjee T, Cheng L, Cheng Y, Dai Y, Duan Z, Flaherty M, Fullard JF, Gancz M, Garrido-Martín D, Gaynor-Gillett S, Grundman J, Hawken N, Henry E, Hoffman GE, Huang A, Jiang Y, Jin T, Jorstad NL, Kawaguchi R, Khullar S, Liu J, Liu J, Liu S, Ma S, Margolis M, Mazariegos S, Moore J, Moran JR, Nguyen E, Phalke N, Pjanic M, Pratt H, Quintero D, Rajagopalan AS, Riesenmy TR, Shedd N, Shi M, Spector M, Terwilliger R, Travaglini KJ, Wamsley B, Wang G, Xia Y, Xiao S, Yang AC, Zheng S, Gandal MJ, Lee D, Lein ES, Roussos P, Sestan N, Weng Z, White KP, Won H, Girgenti MJ, Zhang J, Wang D, Geschwind D, Gerstein M. Single-cell genomics and regulatory networks for 388 human brains. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.18.585576. [PMID: 38562822 PMCID: PMC10983939 DOI: 10.1101/2024.03.18.585576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.
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Affiliation(s)
- Prashant S Emani
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jason J Liu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Declan Clarke
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Matthew Jensen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Jonathan Warrell
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Chirag Gupta
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Ran Meng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Che Yu Lee
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Siwei Xu
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Cagatay Dursun
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Shaoke Lou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Yuhang Chen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Zhiyuan Chu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Timur Galeev
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Ahyeon Hwang
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
- Mathematical, Computational and Systems Biology, University of California, Irvine, CA, 92697, USA
| | - Yunyang Li
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA
| | - Pengyu Ni
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Xiao Zhou
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | | | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Lucy Bicks
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Tanima Chatterjee
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | | | - Yuyan Cheng
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Department of Opthalmology, Perlman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Yi Dai
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Ziheng Duan
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | | | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Michael Gancz
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Diego Garrido-Martín
- Department of Genetics, Microbiology and Statistics, Universitat de Barcelona, Barcelona, 08028, Spain
| | - Sophia Gaynor-Gillett
- Tempus Labs, Inc., Chicago, IL, 60654, USA
- Department of Biology, Cornell College, Mount Vernon, IA, 52314, USA
| | - Jennifer Grundman
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Natalie Hawken
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Ella Henry
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Ao Huang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
| | - Yunzhe Jiang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Ting Jin
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | | | - Riki Kawaguchi
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA, 90095, USA
| | - Saniya Khullar
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Jianyin Liu
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Junhao Liu
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Shuang Liu
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
| | - Shaojie Ma
- Department of Neuroscience, Yale University, New Haven, CT, 06510, USA
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Michael Margolis
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Samantha Mazariegos
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Jill Moore
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | | | - Eric Nguyen
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Nishigandha Phalke
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Milos Pjanic
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Henry Pratt
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Diana Quintero
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | | | - Tiernon R Riesenmy
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA
| | - Nicole Shedd
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Manman Shi
- Tempus Labs, Inc., Chicago, IL, 60654, USA
| | | | - Rosemarie Terwilliger
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06520, USA
| | | | - Brie Wamsley
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Gaoyuan Wang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Yan Xia
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Shaohua Xiao
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Andrew C Yang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Suchen Zheng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
| | - Michael J Gandal
- Interdepartmental Program in Bioinformatics, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia, Philadelphia, PA, 19104, USA
| | - Donghoon Lee
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA, 98109, USA
- Department of Neurological Surgery, University of Washington, Seattle, WA, 98195, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, 98195, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mental Illness Research Education and Clinical Center, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
- Center for Precision Medicine and Translational Therapeutics, James J. Peters VA Medical Center, Bronx, NY, 10468, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale University, New Haven, CT, 06510, USA
| | - Zhiping Weng
- Department of Genomics and Computational Biology, UMass Chan Medical School, Worcester, MA, 01605, USA
| | - Kevin P White
- Yong Loo Lin School of Medicine, National University of Singapore, 117597, Singapore
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Matthew J Girgenti
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT, 06520, USA
- Clinical Neuroscience Division, National Center for Posttraumatic Stress Disorder, Veterans Affairs Connecticut Healthcare System, West Haven, CT, 06516, USA
| | - Jing Zhang
- Department of Computer Science, University of California, Irvine, CA, 92697, USA
| | - Daifeng Wang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53705, USA
- Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Daniel Geschwind
- Program in Neurogenetics, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
- Center for Autism Research and Treatment, Semel Institute, University of California, Los Angeles, CA, 90095, USA
- Department of Psychiatry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Institute for Precision Health, David Geffen School of Medicine, University of California, Los Angeles, CA, 90095, USA
| | - Mark Gerstein
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, 06520, USA
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06520, USA
- Department of Computer Science, Yale University, New Haven, CT, 06520, USA
- Department of Statistics & Data Science, Yale University, New Haven, CT, 06520, USA
- Department of Biomedical Informatics & Data Science, Yale University, New Haven, CT, 06520, USA
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14
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Wahl N, Espeso-Gil S, Chietera P, Nagel A, Laighneach A, Morris DW, Rajarajan P, Akbarian S, Dechant G, Apostolova G. SATB2 organizes the 3D genome architecture of cognition in cortical neurons. Mol Cell 2024; 84:621-639.e9. [PMID: 38244545 PMCID: PMC10923151 DOI: 10.1016/j.molcel.2023.12.024] [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: 01/27/2023] [Revised: 10/02/2023] [Accepted: 12/15/2023] [Indexed: 01/22/2024]
Abstract
The DNA-binding protein SATB2 is genetically linked to human intelligence. We studied its influence on the three-dimensional (3D) epigenome by mapping chromatin interactions and accessibility in control versus SATB2-deficient cortical neurons. We find that SATB2 affects the chromatin looping between enhancers and promoters of neuronal-activity-regulated genes, thus influencing their expression. It also alters A/B compartments, topologically associating domains, and frequently interacting regions. Genes linked to SATB2-dependent 3D genome changes are implicated in highly specialized neuronal functions and contribute to cognitive ability and risk for neuropsychiatric and neurodevelopmental disorders. Non-coding DNA regions with a SATB2-dependent structure are enriched for common variants associated with educational attainment, intelligence, and schizophrenia. Our data establish SATB2 as a cell-type-specific 3D genome modulator, which operates both independently and in cooperation with CCCTC-binding factor (CTCF) to set up the chromatin landscape of pyramidal neurons for cognitive processes.
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Affiliation(s)
- Nico Wahl
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria.
| | - Sergio Espeso-Gil
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria; Department of Psychiatry, Friedman Brain Institute, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Paola Chietera
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria
| | - Amelie Nagel
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria
| | - Aodán Laighneach
- Centre for Neuroimaging, Cognition and Genomics (NICOG), School of Biological and Chemical Sciences, University of Galway, Galway, H91 TK33, Ireland
| | - Derek W Morris
- Centre for Neuroimaging, Cognition and Genomics (NICOG), School of Biological and Chemical Sciences, University of Galway, Galway, H91 TK33, Ireland
| | - Prashanth Rajarajan
- Department of Psychiatry, Friedman Brain Institute, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Schahram Akbarian
- Department of Psychiatry, Friedman Brain Institute, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Georg Dechant
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria.
| | - Galina Apostolova
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria.
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15
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Hu B, Zhuang XL, Zhou L, Zhang G, Cooper DN, Wu DD. Deciphering the Role of Rapidly Evolving Conserved Elements in Primate Brain Development and Exploring Their Potential Involvement in Alzheimer's Disease. Mol Biol Evol 2024; 41:msae001. [PMID: 38175672 PMCID: PMC10798191 DOI: 10.1093/molbev/msae001] [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: 08/30/2023] [Revised: 12/27/2023] [Accepted: 12/29/2023] [Indexed: 01/05/2024] Open
Abstract
Although previous studies have identified human-specific accelerated regions as playing a key role in the recent evolution of the human brain, the characteristics and cellular functions of rapidly evolving conserved elements (RECEs) in ancestral primate lineages remain largely unexplored. Here, based on large-scale primate genome assemblies, we identify 888 RECEs that have been highly conserved in primates that exhibit significantly accelerated substitution rates in the ancestor of the Simiiformes. This primate lineage exhibits remarkable morphological innovations, including an expanded brain mass. Integrative multiomic analyses reveal that RECEs harbor sequences with potential cis-regulatory functions that are activated in the adult human brain. Importantly, genes linked to RECEs exhibit pronounced expression trajectories in the adult brain relative to the fetal stage. Furthermore, we observed an increase in the chromatin accessibility of RECEs in oligodendrocytes from individuals with Alzheimer's disease (AD) compared to that of a control group, indicating that these RECEs may contribute to brain aging and AD. Our findings serve to expand our knowledge of the genetic underpinnings of brain function during primate evolution.
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Affiliation(s)
- Benxia Hu
- Key Laboratory of Genetic Evolution & Animal Models, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Xiao-Lin Zhuang
- Key Laboratory of Genetic Evolution & Animal Models, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Long Zhou
- Center of Evolutionary and Organismal Biology, and Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, Guangdong, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Guangdong, China
| | - Guojie Zhang
- Center of Evolutionary and Organismal Biology, and Women’s Hospital, Zhejiang University School of Medicine, Hangzhou, Guangdong, China
- Liangzhu Laboratory, Zhejiang University Medical Center, Hangzhou, Guangdong, China
| | - David N Cooper
- Institute of Medical Genetics, School of Medicine, Cardiff University, Cardiff, UK
| | - Dong-Dong Wu
- Key Laboratory of Genetic Evolution & Animal Models, Kunming Natural History Museum of Zoology, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- National Resource Center for Non-Human Primates, Kunming Primate Research Center, and National Research Facility for Phenotypic and Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
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16
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Kundakovic M, Tickerhoof M. Epigenetic mechanisms underlying sex differences in the brain and behavior. Trends Neurosci 2024; 47:18-35. [PMID: 37968206 PMCID: PMC10841872 DOI: 10.1016/j.tins.2023.09.007] [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: 06/05/2023] [Revised: 08/21/2023] [Accepted: 09/26/2023] [Indexed: 11/17/2023]
Abstract
Sex differences are found across brain regions, behaviors, and brain diseases. Sexual differentiation of the brain is initiated prenatally but it continues throughout life, as a result of the interaction of three major factors: gonadal hormones, sex chromosomes, and the environment. These factors are thought to act, in part, via epigenetic mechanisms which control chromatin and transcriptional states in brain cells. In this review, we discuss evidence that epigenetic mechanisms underlie sex-specific neurobehavioral changes during critical organizational periods, across the estrous cycle, and in response to diverse environments throughout life. We further identify future directions for the field that will provide novel mechanistic insights into brain sex differences, inform brain disease treatments and women's brain health in particular, and apply to people across genders.
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Affiliation(s)
- Marija Kundakovic
- Department of Biological Sciences, Fordham University, Bronx, NY 10458, USA.
| | - Maria Tickerhoof
- Department of Biological Sciences, Fordham University, Bronx, NY 10458, USA
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17
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Rahman S, Dong P, Apontes P, Fernando M, Kosoy R, Townsley KG, Girdhar K, Bendl J, Shao Z, Misir R, Tsankova N, Kleopoulos S, Brennand K, Fullard J, Roussos P. Lineage specific 3D genome structure in the adult human brain and neurodevelopmental changes in the chromatin interactome. Nucleic Acids Res 2023; 51:11142-11161. [PMID: 37811875 PMCID: PMC10639075 DOI: 10.1093/nar/gkad798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 08/18/2023] [Accepted: 09/19/2023] [Indexed: 10/10/2023] Open
Abstract
The human brain is a complex organ comprised of distinct cell types, and the contribution of the 3D genome to lineage specific gene expression remains poorly understood. To decipher cell type specific genome architecture, and characterize fine scale changes in the chromatin interactome across neural development, we compared the 3D genome of the human fetal cortical plate to that of neurons and glia isolated from the adult prefrontal cortex. We found that neurons have weaker genome compartmentalization compared to glia, but stronger TADs, which emerge during fetal development. Furthermore, relative to glia, the neuronal genome shifts more strongly towards repressive compartments. Neurons have differential TAD boundaries that are proximal to active promoters involved in neurodevelopmental processes. CRISPRi on CNTNAP2 in hIPSC-derived neurons reveals that transcriptional inactivation correlates with loss of insulation at the differential boundary. Finally, re-wiring of chromatin loops during neural development is associated with transcriptional and functional changes. Importantly, differential loops in the fetal cortex are associated with autism GWAS loci, suggesting a neuropsychiatric disease mechanism affecting the chromatin interactome. Furthermore, neural development involves gaining enhancer-promoter loops that upregulate genes that control synaptic activity. Altogether, our study provides multi-scale insights on the 3D genome in the human brain.
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Affiliation(s)
- Samir Rahman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Pengfei Dong
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Pasha Apontes
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY 10468, USA
| | - Michael B Fernando
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Roman Kosoy
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kayla G Townsley
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kiran Girdhar
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Zhiping Shao
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ruth Misir
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Nadia Tsankova
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Pathology, Molecular, and Cell-based Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Steven P Kleopoulos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kristen J Brennand
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY 10468, USA
- Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY 10962, USA
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18
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Mastropasqua F, Oksanen M, Soldini C, Alatar S, Arora A, Ballarino R, Molinari M, Agostini F, Poulet A, Watts M, Rabkina I, Becker M, Li D, Anderlid BM, Isaksson J, Lundin Remnelius K, Moslem M, Jacob Y, Falk A, Crosetto N, Bienko M, Santini E, Borgkvist A, Bölte S, Tammimies K. Deficiency of the Heterogeneous Nuclear Ribonucleoprotein U locus leads to delayed hindbrain neurogenesis. Biol Open 2023; 12:bio060113. [PMID: 37815090 PMCID: PMC10581386 DOI: 10.1242/bio.060113] [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: 08/25/2023] [Accepted: 09/04/2023] [Indexed: 10/11/2023] Open
Abstract
Genetic variants affecting Heterogeneous Nuclear Ribonucleoprotein U (HNRNPU) have been identified in several neurodevelopmental disorders (NDDs). HNRNPU is widely expressed in the human brain and shows the highest postnatal expression in the cerebellum. Recent studies have investigated the role of HNRNPU in cerebral cortical development, but the effects of HNRNPU deficiency on cerebellar development remain unknown. Here, we describe the molecular and cellular outcomes of HNRNPU locus deficiency during in vitro neural differentiation of patient-derived and isogenic neuroepithelial stem cells with a hindbrain profile. We demonstrate that HNRNPU deficiency leads to chromatin remodeling of A/B compartments, and transcriptional rewiring, partly by impacting exon inclusion during mRNA processing. Genomic regions affected by the chromatin restructuring and host genes of exon usage differences show a strong enrichment for genes implicated in epilepsies, intellectual disability, and autism. Lastly, we show that at the cellular level HNRNPU downregulation leads to an increased fraction of neural progenitors in the maturing neuronal population. We conclude that the HNRNPU locus is involved in delayed commitment of neural progenitors to differentiate in cell types with hindbrain profile.
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Affiliation(s)
- Francesca Mastropasqua
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute, Region Stockholm, 17164 Stockholm, Sweden
- Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, 17164 Stockholm, Sweden
| | - Marika Oksanen
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute, Region Stockholm, 17164 Stockholm, Sweden
- Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, 17164 Stockholm, Sweden
| | - Cristina Soldini
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute, Region Stockholm, 17164 Stockholm, Sweden
- Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, 17164 Stockholm, Sweden
| | - Shemim Alatar
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute, Region Stockholm, 17164 Stockholm, Sweden
- Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, 17164 Stockholm, Sweden
| | - Abishek Arora
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute, Region Stockholm, 17164 Stockholm, Sweden
- Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, 17164 Stockholm, Sweden
| | - Roberto Ballarino
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 17164 Stockholm, Sweden
- Science for Life Laboratory, Tomtebodavägen 23A, 17165 Solna, Sweden
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, 17165 Stockholm, Sweden
| | - Maya Molinari
- Department of Neuroscience, Karolinska Institutet, 17176 Solna, Sweden
| | - Federico Agostini
- Science for Life Laboratory, Tomtebodavägen 23A, 17165 Solna, Sweden
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, 17165 Stockholm, Sweden
| | - Axel Poulet
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA
| | - Michelle Watts
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute, Region Stockholm, 17164 Stockholm, Sweden
- Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, 17164 Stockholm, Sweden
| | - Ielyzaveta Rabkina
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute, Region Stockholm, 17164 Stockholm, Sweden
- Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, 17164 Stockholm, Sweden
| | - Martin Becker
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute, Region Stockholm, 17164 Stockholm, Sweden
- Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, 17164 Stockholm, Sweden
| | - Danyang Li
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute, Region Stockholm, 17164 Stockholm, Sweden
- Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, 17164 Stockholm, Sweden
| | - Britt-Marie Anderlid
- Department of Molecular Medicine and Surgery, Karolinska Institutet, 17177 Stockholm, Sweden
- Department of Clinical Genetics, Karolinska University Hospital, 17164 Stockholm, Sweden
| | - Johan Isaksson
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute, Region Stockholm, 17164 Stockholm, Sweden
- Department of Medical Sciences, Child and Adolescent Psychiatry Unit, Uppsala University, 75309 Uppsala, Sweden
| | - Karl Lundin Remnelius
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute, Region Stockholm, 17164 Stockholm, Sweden
| | - Mohsen Moslem
- Department of Neuroscience, Karolinska Institutet, 17176 Solna, Sweden
| | - Yannick Jacob
- Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06511, USA
| | - Anna Falk
- Department of Neuroscience, Karolinska Institutet, 17176 Solna, Sweden
- Lund Stem Cell Center, Lund University, 22100 Lund, Sweden
| | - Nicola Crosetto
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 17164 Stockholm, Sweden
- Science for Life Laboratory, Tomtebodavägen 23A, 17165 Solna, Sweden
- Human Technopole, Viale Rita Levi-Montalcini 1, 20157 Milan, Italy
| | - Magda Bienko
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, 17164 Stockholm, Sweden
- Science for Life Laboratory, Tomtebodavägen 23A, 17165 Solna, Sweden
- Human Technopole, Viale Rita Levi-Montalcini 1, 20157 Milan, Italy
| | - Emanuela Santini
- Department of Neuroscience, Karolinska Institutet, 17176 Solna, Sweden
| | - Anders Borgkvist
- Department of Neuroscience, Karolinska Institutet, 17176 Solna, Sweden
| | - Sven Bölte
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute, Region Stockholm, 17164 Stockholm, Sweden
- Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, 17164 Stockholm, Sweden
- Curtin Autism Research Group, Curtin School of Allied Health, Curtin University, 6845 Perth, Western Australia
- Child and Adolescent Psychiatry, Stockholm Health Care Services, Region Stockholm, 10431 Stockholm, Sweden
| | - Kristiina Tammimies
- Center of Neurodevelopmental Disorders (KIND), Centre for Psychiatry Research, Department of Women's and Children's Health, Karolinska Institute, Region Stockholm, 17164 Stockholm, Sweden
- Astrid Lindgren Children's Hospital, Karolinska University Hospital, Region Stockholm, 17164 Stockholm, Sweden
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19
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Tian W, Zhou J, Bartlett A, Zeng Q, Liu H, Castanon RG, Kenworthy M, Altshul J, Valadon C, Aldridge A, Nery JR, Chen H, Xu J, Johnson ND, Lucero J, Osteen JK, Emerson N, Rink J, Lee J, Li Y, Siletti K, Liem M, Claffey N, O’Connor C, Yanny AM, Nyhus J, Dee N, Casper T, Shapovalova N, Hirschstein D, Ding SL, Hodge R, Levi BP, Keene CD, Linnarsson S, Lein E, Ren B, Behrens MM, Ecker JR. Single-cell DNA methylation and 3D genome architecture in the human brain. Science 2023; 382:eadf5357. [PMID: 37824674 PMCID: PMC10572106 DOI: 10.1126/science.adf5357] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 09/05/2023] [Indexed: 10/14/2023]
Abstract
Delineating the gene-regulatory programs underlying complex cell types is fundamental for understanding brain function in health and disease. Here, we comprehensively examined human brain cell epigenomes by probing DNA methylation and chromatin conformation at single-cell resolution in 517 thousand cells (399 thousand neurons and 118 thousand non-neurons) from 46 regions of three adult male brains. We identified 188 cell types and characterized their molecular signatures. Integrative analyses revealed concordant changes in DNA methylation, chromatin accessibility, chromatin organization, and gene expression across cell types, cortical areas, and basal ganglia structures. We further developed single-cell methylation barcodes that reliably predict brain cell types using the methylation status of select genomic sites. This multimodal epigenomic brain cell atlas provides new insights into the complexity of cell-type-specific gene regulation in adult human brains.
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Affiliation(s)
- Wei Tian
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jingtian Zhou
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92037, USA
| | - Anna Bartlett
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Qiurui Zeng
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92037, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Rosa G. Castanon
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Mia Kenworthy
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jordan Altshul
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Cynthia Valadon
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Andrew Aldridge
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Joseph R. Nery
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Huaming Chen
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jiaying Xu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Nicholas D. Johnson
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jacinta Lucero
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Julia K. Osteen
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Nora Emerson
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jon Rink
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jasper Lee
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Yang Li
- Ludwig Institute for Cancer Research, La Jolla, CA 92037, USA
| | - Kimberly Siletti
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet; 171 77 Stockholm, Sweden
| | - Michelle Liem
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Naomi Claffey
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Caz O’Connor
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | | | - Julie Nyhus
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Nick Dee
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Tamara Casper
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | | | | | - Song-Lin Ding
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Rebecca Hodge
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Boaz P. Levi
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - C. Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - Sten Linnarsson
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet; 171 77 Stockholm, Sweden
| | - Ed Lein
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Bing Ren
- Ludwig Institute for Cancer Research, La Jolla, CA 92037, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA 92037, USA
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA 92037, USA
- Institute of Genomic Medicine, University of California, San Diego School of Medicine, La Jolla, CA 92037, USA
- Moores Cancer Center, University of California, San Diego School of Medicine, La Jolla, CA 92037, USA
| | - M. Margarita Behrens
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Joseph R. Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
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20
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McAfee JC, Lee S, Lee J, Bell JL, Krupa O, Davis J, Insigne K, Bond ML, Zhao N, Boyle AP, Phanstiel DH, Love MI, Stein JL, Ruzicka WB, Davila-Velderrain J, Kosuri S, Won H. Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants. CELL GENOMICS 2023; 3:100404. [PMID: 37868037 PMCID: PMC10589626 DOI: 10.1016/j.xgen.2023.100404] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 02/23/2023] [Accepted: 08/21/2023] [Indexed: 10/24/2023]
Abstract
Genome-wide association studies (GWASs) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium makes it challenging to discern causal variants. We performed a massively parallel reporter assay (MPRA) on 5,173 fine-mapped schizophrenia GWAS variants in primary human neural progenitors and identified 439 variants with allelic regulatory effects (MPRA-positive variants). Transcription factor binding had modest predictive power, while fine-map posterior probability, enhancer overlap, and evolutionary conservation failed to predict MPRA-positive variants. Furthermore, 64% of MPRA-positive variants did not exhibit expressive quantitative trait loci signature, suggesting that MPRA could identify yet unexplored variants with regulatory potentials. To predict the combinatorial effect of MPRA-positive variants on gene regulation, we propose an accessibility-by-contact model that combines MPRA-measured allelic activity with neuronal chromatin architecture.
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Affiliation(s)
- Jessica C. McAfee
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Sool Lee
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jiseok Lee
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jessica L. Bell
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Oleh Krupa
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jessica Davis
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
- UCLA-DOE Institute for Genomics and Proteomics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Quantitative and Computational Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Kimberly Insigne
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
- UCLA-DOE Institute for Genomics and Proteomics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Quantitative and Computational Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Marielle L. Bond
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Nanxiang Zhao
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Alan P. Boyle
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Douglas H. Phanstiel
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Michael I. Love
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jason L. Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - W. Brad Ruzicka
- Laboratory for Epigenomics in Human Psychopathology, McLean Hospital, Belmont, MA 02141, USA
- Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Sriram Kosuri
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA 90095, USA
- UCLA-DOE Institute for Genomics and Proteomics, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Quantitative and Computational Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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21
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Signal B, Pérez Suárez TG, Taberlay PC, Woodhouse A. Cellular specificity is key to deciphering epigenetic changes underlying Alzheimer's disease. Neurobiol Dis 2023; 186:106284. [PMID: 37683959 DOI: 10.1016/j.nbd.2023.106284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 08/23/2023] [Accepted: 09/05/2023] [Indexed: 09/10/2023] Open
Abstract
Different cell types in the brain play distinct roles in Alzheimer's disease (AD) progression. Late onset AD (LOAD) is a complex disease, with a large genetic component, but many risk loci fall in non-coding genome regions. Epigenetics implicates the non-coding genome with control of gene expression. The epigenome is highly cell-type specific and dynamically responds to the environment. Therefore, epigenetic mechanisms are well placed to explain genetic and environmental factors that are associated with AD. However, given this cellular specificity, purified cell populations or single cells need to be profiled to avoid effect masking. Here we review the current state of cell-type specific genome-wide profiling in LOAD, covering DNA methylation (CpG, CpH, and hydroxymethylation), histone modifications, and chromatin changes. To date, these data reveal that distinct cell types contribute and react differently to AD progression through epigenetic alterations. This review addresses the current gap in prior bulk-tissue derived work by spotlighting cell-specific changes that govern the complex interplay of cells throughout disease progression and are critical in understanding and developing effective treatments for AD.
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Affiliation(s)
- Brandon Signal
- School of Medicine, College of Health and Medicine, University of Tasmania, Hobart, TAS, Australia.
| | | | - Phillippa C Taberlay
- School of Medicine, College of Health and Medicine, University of Tasmania, Hobart, TAS, Australia
| | - Adele Woodhouse
- Wicking Dementia Research and Education Centre, University of Tasmania, Hobart, TAS, Australia
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22
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Dileep V, Boix CA, Mathys H, Marco A, Welch GM, Meharena HS, Loon A, Jeloka R, Peng Z, Bennett DA, Kellis M, Tsai LH. Neuronal DNA double-strand breaks lead to genome structural variations and 3D genome disruption in neurodegeneration. Cell 2023; 186:4404-4421.e20. [PMID: 37774679 PMCID: PMC10697236 DOI: 10.1016/j.cell.2023.08.038] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2022] [Revised: 04/02/2023] [Accepted: 08/29/2023] [Indexed: 10/01/2023]
Abstract
Persistent DNA double-strand breaks (DSBs) in neurons are an early pathological hallmark of neurodegenerative diseases including Alzheimer's disease (AD), with the potential to disrupt genome integrity. We used single-nucleus RNA-seq in human postmortem prefrontal cortex samples and found that excitatory neurons in AD were enriched for somatic mosaic gene fusions. Gene fusions were particularly enriched in excitatory neurons with DNA damage repair and senescence gene signatures. In addition, somatic genome structural variations and gene fusions were enriched in neurons burdened with DSBs in the CK-p25 mouse model of neurodegeneration. Neurons enriched for DSBs also had elevated levels of cohesin along with progressive multiscale disruption of the 3D genome organization aligned with transcriptional changes in synaptic, neuronal development, and histone genes. Overall, this study demonstrates the disruption of genome stability and the 3D genome organization by DSBs in neurons as pathological steps in the progression of neurodegenerative diseases.
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Affiliation(s)
- Vishnu Dileep
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| | - Carles A Boix
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Hansruedi Mathys
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Asaf Marco
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Gwyneth M Welch
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Hiruy S Meharena
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Anjanet Loon
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Ritika Jeloka
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Zhuyu Peng
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | | | - Manolis Kellis
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Li-Huei Tsai
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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23
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Mulvey B, Selmanovic D, Dougherty JD. Sex Significantly Impacts the Function of Major Depression-Linked Variants In Vivo. Biol Psychiatry 2023; 94:466-478. [PMID: 36803612 PMCID: PMC10425576 DOI: 10.1016/j.biopsych.2023.02.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Revised: 01/19/2023] [Accepted: 02/07/2023] [Indexed: 02/17/2023]
Abstract
BACKGROUND Genome-wide association studies have discovered blocks of common variants-likely transcriptional-regulatory-associated with major depressive disorder (MDD), though the functional subset and their biological impacts remain unknown. Likewise, why depression occurs in females more frequently than males is unclear. We therefore tested the hypothesis that risk-associated functional variants interact with sex and produce greater impact in female brains. METHODS We developed techniques to directly measure regulatory variant activity and sex interactions using massively parallel reporter assays in the mouse brain in vivo, in a cell type-specific manner, and applied these approaches to measure activity of >1000 variants from >30 MDD loci. RESULTS We identified extensive sex-by-allele effects in mature hippocampal neurons, suggesting that sex-differentiated impacts of genetic risk may underlie sex bias in disease. Unbiased informatics approaches indicated that functional MDD variants recurrently disrupt a number of transcription factor binding motifs, including those of sex hormone receptors. We confirmed a role for the latter by performing massively parallel reporter assays in neonatal mice on the day of birth (during a sex-differentiating hormone surge) and hormonally quiescent juveniles. CONCLUSIONS Our study provides novel insights into the influence of age, biological sex, and cell type on regulatory variant function and provides a framework for in vivo parallel assays to functionally define interactions between organismal variables such as sex and regulatory variation. Moreover, we experimentally demonstrate that a portion of the sex differences seen in MDD occurrence may be a product of sex-differentiated effects at associated regulatory variants.
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Affiliation(s)
- Bernard Mulvey
- Division of Biology and Biomedical Sciences, Washington University in St. Louis School of Medicine, St. Louis, Missouri; Department of Genetics, Washington University in St. Louis School of Medicine, St. Louis, Missouri
| | - Din Selmanovic
- Department of Genetics, Washington University in St. Louis School of Medicine, St. Louis, Missouri
| | - Joseph D Dougherty
- Department of Genetics, Washington University in St. Louis School of Medicine, St. Louis, Missouri; Department of Psychiatry, Washington University in St. Louis School of Medicine, St. Louis, Missouri; Intellectual and Developmental Disabilities Research Center, Washington University in St. Louis School of Medicine, St. Louis, Missouri.
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24
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Warrier V, Stauffer EM, Huang QQ, Wigdor EM, Slob EAW, Seidlitz J, Ronan L, Valk SL, Mallard TT, Grotzinger AD, Romero-Garcia R, Baron-Cohen S, Geschwind DH, Lancaster MA, Murray GK, Gandal MJ, Alexander-Bloch A, Won H, Martin HC, Bullmore ET, Bethlehem RAI. Genetic insights into human cortical organization and development through genome-wide analyses of 2,347 neuroimaging phenotypes. Nat Genet 2023; 55:1483-1493. [PMID: 37592024 PMCID: PMC10600728 DOI: 10.1038/s41588-023-01475-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Accepted: 07/13/2023] [Indexed: 08/19/2023]
Abstract
Our understanding of the genetics of the human cerebral cortex is limited both in terms of the diversity and the anatomical granularity of brain structural phenotypes. Here we conducted a genome-wide association meta-analysis of 13 structural and diffusion magnetic resonance imaging-derived cortical phenotypes, measured globally and at 180 bilaterally averaged regions in 36,663 individuals and identified 4,349 experiment-wide significant loci. These phenotypes include cortical thickness, surface area, gray matter volume, measures of folding, neurite density and water diffusion. We identified four genetic latent structures and causal relationships between surface area and some measures of cortical folding. These latent structures partly relate to different underlying gene expression trajectories during development and are enriched for different cell types. We also identified differential enrichment for neurodevelopmental and constrained genes and demonstrate that common genetic variants associated with cortical expansion are associated with cephalic disorders. Finally, we identified complex interphenotype and inter-regional genetic relationships among the 13 phenotypes, reflecting the developmental differences among them. Together, these analyses identify distinct genetic organizational principles of the cortex and their correlates with neurodevelopment.
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Affiliation(s)
- Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Department of Psychology, University of Cambridge, Cambridge, UK.
| | | | | | | | - Eric A W Slob
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Jakob Seidlitz
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Lisa Ronan
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Sofie L Valk
- Institute of Neuroscience and Medicine, Brain & Behaviour (INM-7), Research Centre Jülich, FZ Jülich, Jülich, Germany
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Otto Hahn Group Cognitive Neurogenetics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Andrew D Grotzinger
- Department of Psychology and Neuroscience, University of Colorado at Boulder, Boulder, CO, USA
- Institute for Behavioral Genetics, University of Colorado at Boulder, Boulder, CO, USA
| | - Rafael Romero-Garcia
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Instituto de Biomedicina de Sevilla (IBiS) HUVR/CSIC/Universidad de Sevilla/CIBERSAM, ISCIII, Dpto. de Fisiología Médica y Biofísica, Seville, Spain
| | - Simon Baron-Cohen
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Department of Psychology, University of Cambridge, Cambridge, UK
| | - Daniel H Geschwind
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
- Program in Neurogenetics, Department of Neurology, University of California, Los Angeles, CA, USA
- Center for Autism Research and Treatment, Jane and TerrySemel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
- Institute of Precision Health, University of California, Los Angeles, CA, USA
| | - Madeline A Lancaster
- MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Francis Crick Avenue, Cambridge, UK
| | - Graham K Murray
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Trust, Cambridge, UK
- Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, Australia
| | - Michael J Gandal
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
| | - Aaron Alexander-Bloch
- Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Lifespan Brain Institute, The Children's Hospital of Philadelphia and Penn Medicine, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
| | - Hyejung Won
- Department of Genetics and the Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Edward T Bullmore
- Department of Psychiatry, University of Cambridge, Cambridge, UK
- Cambridgeshire and Peterborough NHS Trust, Cambridge, UK
| | - Richard A I Bethlehem
- Department of Psychiatry, University of Cambridge, Cambridge, UK.
- Department of Psychology, University of Cambridge, Cambridge, UK.
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25
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Bond ML, Davis ES, Quiroga IY, Dey A, Kiran M, Love MI, Won H, Phanstiel DH. Chromatin loop dynamics during cellular differentiation are associated with changes to both anchor and internal regulatory features. Genome Res 2023; 33:1258-1268. [PMID: 37699658 PMCID: PMC10547260 DOI: 10.1101/gr.277397.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 07/07/2023] [Indexed: 09/14/2023]
Abstract
Three-dimensional (3D) chromatin structure has been shown to play a role in regulating gene transcription during biological transitions. Although our understanding of loop formation and maintenance is rapidly improving, much less is known about the mechanisms driving changes in looping and the impact of differential looping on gene transcription. One limitation has been a lack of well-powered differential looping data sets. To address this, we conducted a deeply sequenced Hi-C time course of megakaryocyte development comprising four biological replicates and 6 billion reads per time point. Statistical analysis revealed 1503 differential loops. Gained loop anchors were enriched for AP-1 occupancy and were characterized by large increases in histone H3K27ac (over 11-fold) but relatively small increases in CTCF and RAD21 binding (1.26- and 1.23-fold, respectively). Linear modeling revealed that changes in histone H3K27ac, chromatin accessibility, and JUN binding were better correlated with changes in looping than RAD21 and almost as well correlated as CTCF. Changes to epigenetic features between-rather than at-boundaries were highly predictive of changes in looping. Together these data suggest that although CTCF and RAD21 may be the core machinery dictating where loops form, other features (both at the anchors and within the loop boundaries) may play a larger role than previously anticipated in determining the relative loop strength across cell types and conditions.
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Affiliation(s)
- Marielle L Bond
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Eric S Davis
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Ivana Y Quiroga
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Anubha Dey
- Department of Systems and Computational Biology, University of Hyderabad, Hyderabad 500046, Telangana, India
| | - Manjari Kiran
- Department of Systems and Computational Biology, University of Hyderabad, Hyderabad 500046, Telangana, India
| | - Michael I Love
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514, USA
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27514, USA;
- Neuroscience Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Douglas H Phanstiel
- Curriculum in Genetics and Molecular Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA;
- Curriculum in Bioinformatics and Computational Biology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Thurston Arthritis Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
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26
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Musolino E, Pagiatakis C, Pierin F, Sabatino D, Finzi G, Gornati R, Bernardini G, Papait R. A chromEM-staining protocol optimized for cardiac tissue. Front Cell Dev Biol 2023; 11:1123114. [PMID: 37476155 PMCID: PMC10354428 DOI: 10.3389/fcell.2023.1123114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 06/23/2023] [Indexed: 07/22/2023] Open
Abstract
Three-dimensional (3D) chromatin organization has a key role in defining the transcription program of cells during development. Its alteration is the cause of gene expression changes responsible for several diseases. Thus, we need new tools to study this aspect of gene expression regulation. To this end, ChromEM was recently developed: this is an electron-microscopy staining technique that selectively marks nuclear DNA without altering its structure and, thus, allows better visualization of 3D chromatin conformation. However, despite increasingly frequent application of this staining technique on cells, it has not yet been applied to visualize chromatin ultrastructure in tissues. Here, we provide a protocol to carry out ChromEM on myocardial tissue harvested from the left ventricles of C57BL/6J mice and use this in combination with transmission electron microscopy (TEM) to measure some morphological parameters of peripheral heterochromatin in cardiomyocytes. This protocol could also be used, in combination with electron tomography, to study 3D chromatin organization in cardiomyocytes in different aspects of heart pathobiology (e.g., heart development, cardiac aging, and heart failure) as well as help to set-up ChromEM in other tissues.
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Affiliation(s)
- Elettra Musolino
- Department of Biotechnology and Life Sciences, University of Insubria, Varese, Italy
| | - Christina Pagiatakis
- Department of Biotechnology and Life Sciences, University of Insubria, Varese, Italy
- Department of Cardiovascular Medicine, Humanitas Research Hospital–IRCCS, Rozzano (MI), Italy
| | - Federica Pierin
- Department of Biotechnology and Life Sciences, University of Insubria, Varese, Italy
| | | | - Giovanna Finzi
- Department of Pathology, ASST Sette Laghi, Varese, Italy
| | - Rosalba Gornati
- Department of Biotechnology and Life Sciences, University of Insubria, Varese, Italy
| | - Giovanni Bernardini
- Department of Biotechnology and Life Sciences, University of Insubria, Varese, Italy
| | - Roberto Papait
- Department of Biotechnology and Life Sciences, University of Insubria, Varese, Italy
- Department of Cardiovascular Medicine, Humanitas Research Hospital–IRCCS, Rozzano (MI), Italy
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27
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Kalinowski A, Tian L, Pattni R, Ollila H, Khan M, Manko C, Silverman M, Ma M, Columbo L, Farhadian B, Swedo S, Murphy T, Johnson M, Fernell E, Gillberg C, Thienemann M, Mellins ED, Levinson DF, Urban AE, Frankovich J. Evaluation of C4 Gene Copy Number in Pediatric Acute Neuropsychiatric Syndrome. Dev Neurosci 2023; 45:315-324. [PMID: 37379808 DOI: 10.1159/000531707] [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: 01/11/2023] [Accepted: 06/16/2023] [Indexed: 06/30/2023] Open
Abstract
Pediatric acute-onset neuropsychiatric syndrome (PANS) is an abrupt-onset neuropsychiatric disorder. PANS patients have an increased prevalence of comorbid autoimmune illness, most commonly arthritis. In addition, an estimated one-third of PANS patients present with low serum C4 protein, suggesting decreased production or increased consumption of C4 protein. To test the possibility that copy number (CN) variation contributes to risk of PANS illness, we compared mean total C4A and total C4B CN in ethnically matched subjects from PANS DNA samples and controls (192 cases and 182 controls). Longitudinal data from the Stanford PANS cohort (n = 121) were used to assess whether the time to juvenile idiopathic arthritis (JIA) or autoimmune disease (AI) onset was a function of total C4A or C4B CN. Lastly, we performed several hypothesis-generating analyses to explore the correlation between individual C4 gene variants, sex, specific genotypes, and age of PANS onset. Although the mean total C4A or C4B CN did not differ in PANS compared to controls, PANS patients with low C4B CN were at increased risk for subsequent JIA diagnosis (hazard ratio = 2.7, p value = 0.004). We also observed a possible increase in risk for AI in PANS patients and a possible correlation between lower C4B and PANS age of onset. An association between rheumatoid arthritis and low C4B CN has been reported previously. However, patients with PANS develop different types of JIA: enthesitis-related arthritis, spondyloarthritis, and psoriatic arthritis. This suggests that C4B plays a role that spans these arthritis types.
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Affiliation(s)
- Agnieszka Kalinowski
- Stanford University Department of Psychiatry and Behavioral Sciences, Stanford, California, USA
- Sierra Pacific Mental Illness Research Education and Clinical Center (MIRECC), VA Palo Alto Health Care System, Palo Alto, California, USA
| | - Lu Tian
- Stanford University Department of Biomedical Data Science, Stanford, California, USA
| | - Reenal Pattni
- Stanford University Department of Psychiatry and Behavioral Sciences, Stanford, California, USA
- Stanford University Department of Genetics, Stanford, California, USA
| | - Hanna Ollila
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Broad Institute of MIT and Harvard, Boston, Massachusetts, USA
| | - Maroof Khan
- Immune Behavioral Health Clinic, Stanford University Department of Pediatrics, Stanford, California, USA
| | - Cindy Manko
- Immune Behavioral Health Clinic, Stanford University Department of Pediatrics, Stanford, California, USA
| | - Melissa Silverman
- Stanford University Department of Psychiatry and Behavioral Sciences, Stanford, California, USA
- Immune Behavioral Health Clinic, Stanford University Department of Pediatrics, Stanford, California, USA
| | - Meiqian Ma
- Immune Behavioral Health Clinic, Stanford University Department of Pediatrics, Stanford, California, USA
| | - Laurie Columbo
- Immune Behavioral Health Clinic, Stanford University Department of Pediatrics, Stanford, California, USA
| | - Bahare Farhadian
- Immune Behavioral Health Clinic, Stanford University Department of Pediatrics, Stanford, California, USA
| | - Susan Swedo
- National Institutes of Health, Pediatrics and Developmental Neuroscience Branch, Bethesda, Maryland, USA
| | - Tanya Murphy
- Department of Pediatrics and Department of Psychiatry and Neurosciences, University of South Florida, Tampa, Florida, USA
- John Hopkins Medicine, Baltimore, Maryland, USA
| | - Mats Johnson
- Gillberg Neuropsychiatry Centre, University of Gothenburg, Gothenburg, Sweden
| | - Elisabeth Fernell
- Gillberg Neuropsychiatry Centre, University of Gothenburg, Gothenburg, Sweden
| | | | - Margo Thienemann
- Stanford University Department of Psychiatry and Behavioral Sciences, Stanford, California, USA
- Immune Behavioral Health Clinic, Stanford University Department of Pediatrics, Stanford, California, USA
| | - Elizabeth D Mellins
- Immune Behavioral Health Clinic, Stanford University Department of Pediatrics, Stanford, California, USA
| | - Douglas F Levinson
- Stanford University Department of Psychiatry and Behavioral Sciences, Stanford, California, USA
| | - Alexander E Urban
- Stanford University Department of Psychiatry and Behavioral Sciences, Stanford, California, USA
- Stanford University Department of Genetics, Stanford, California, USA
| | - Jennifer Frankovich
- Immune Behavioral Health Clinic, Stanford University Department of Pediatrics, Stanford, California, USA
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28
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Pancaldi V. Network models of chromatin structure. Curr Opin Genet Dev 2023; 80:102051. [PMID: 37245241 DOI: 10.1016/j.gde.2023.102051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2022] [Revised: 04/13/2023] [Accepted: 04/14/2023] [Indexed: 05/30/2023]
Abstract
Increasing numbers of datasets and experimental assays that capture the organization of chromatin inside the nucleus warrant an effort to develop tools to visualize and analyze these structures. Alongside polymer physics or constraint-based modeling, network theory approaches to describe 3D epigenome organization have gained in popularity. Representing genomic regions as nodes in a network enables visualization of 1D epigenomics datasets in the context of chromatin structure maps, while network theory metrics can be used to describe 3D epigenome organization and dynamics. In this review, we summarize the most salient applications of network theory to the study of chromatin contact maps, demonstrating its potential in revealing epigenomic patterns and relating them to cellular phenotypes.
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Affiliation(s)
- Vera Pancaldi
- CRCT, Université de Toulouse, Inserm, CNRS, Université Toulouse III-Paul Sabatier, Centre de Recherches en Cancérologie de Toulouse, Toulouse, France.
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29
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D'Incal CP, Van Rossem KE, De Man K, Konings A, Van Dijck A, Rizzuti L, Vitriolo A, Testa G, Gozes I, Vanden Berghe W, Kooy RF. Chromatin remodeler Activity-Dependent Neuroprotective Protein (ADNP) contributes to syndromic autism. Clin Epigenetics 2023; 15:45. [PMID: 36945042 PMCID: PMC10031977 DOI: 10.1186/s13148-023-01450-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 02/16/2023] [Indexed: 03/23/2023] Open
Abstract
BACKGROUND Individuals affected with autism often suffer additional co-morbidities such as intellectual disability. The genes contributing to autism cluster on a relatively limited number of cellular pathways, including chromatin remodeling. However, limited information is available on how mutations in single genes can result in such pleiotropic clinical features in affected individuals. In this review, we summarize available information on one of the most frequently mutated genes in syndromic autism the Activity-Dependent Neuroprotective Protein (ADNP). RESULTS Heterozygous and predicted loss-of-function ADNP mutations in individuals inevitably result in the clinical presentation with the Helsmoortel-Van der Aa syndrome, a frequent form of syndromic autism. ADNP, a zinc finger DNA-binding protein has a role in chromatin remodeling: The protein is associated with the pericentromeric protein HP1, the SWI/SNF core complex protein BRG1, and other members of this chromatin remodeling complex and, in murine stem cells, with the chromodomain helicase CHD4 in a ChAHP complex. ADNP has recently been shown to possess R-loop processing activity. In addition, many additional functions, for instance, in association with cytoskeletal proteins have been linked to ADNP. CONCLUSIONS We here present an integrated evaluation of all current aspects of gene function and evaluate how abnormalities in chromatin remodeling might relate to the pleiotropic clinical presentation in individual"s" with Helsmoortel-Van der Aa syndrome.
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Affiliation(s)
- Claudio Peter D'Incal
- Department of Medical Genetics, University of Antwerp, Prins Boudewijnlaan 43/6, 2650, Edegem, Belgium
- Protein Chemistry, Proteomics and Epigenetic Signaling (PPES), Epigenetic Signaling Lab (PPES), Department of Biomedical Sciences, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium
| | - Kirsten Esther Van Rossem
- Department of Medical Genetics, University of Antwerp, Prins Boudewijnlaan 43/6, 2650, Edegem, Belgium
| | - Kevin De Man
- Protein Chemistry, Proteomics and Epigenetic Signaling (PPES), Epigenetic Signaling Lab (PPES), Department of Biomedical Sciences, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium
| | - Anthony Konings
- Protein Chemistry, Proteomics and Epigenetic Signaling (PPES), Epigenetic Signaling Lab (PPES), Department of Biomedical Sciences, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium
| | - Anke Van Dijck
- Department of Medical Genetics, University of Antwerp, Prins Boudewijnlaan 43/6, 2650, Edegem, Belgium
| | - Ludovico Rizzuti
- High Definition Disease Modelling Lab, Stem Cell and Organoid Epigenetics, IEO, European Institute of Oncology, IRCCS, 20141, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, 20122, Milan, Italy
- Human Technopole, V. Le Rita Levi-Montalcini, 1, 20157, Milan, Italy
| | - Alessandro Vitriolo
- High Definition Disease Modelling Lab, Stem Cell and Organoid Epigenetics, IEO, European Institute of Oncology, IRCCS, 20141, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, 20122, Milan, Italy
- Human Technopole, V. Le Rita Levi-Montalcini, 1, 20157, Milan, Italy
| | - Giuseppe Testa
- High Definition Disease Modelling Lab, Stem Cell and Organoid Epigenetics, IEO, European Institute of Oncology, IRCCS, 20141, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, 20122, Milan, Italy
- Human Technopole, V. Le Rita Levi-Montalcini, 1, 20157, Milan, Italy
| | - Illana Gozes
- Elton Laboratory for Molecular Neuroendocrinology, Department of Human Molecular Genetics and Biochemistry, Faculty of Medicine, Adams Super Center for Brain Studies and Sagol School of Neuroscience, Tel Aviv University, Sackler School of Medicine, 727, 69978, Tel Aviv, Israel
| | - Wim Vanden Berghe
- Protein Chemistry, Proteomics and Epigenetic Signaling (PPES), Epigenetic Signaling Lab (PPES), Department of Biomedical Sciences, University of Antwerp, Universiteitsplein 1, 2610, Wilrijk, Belgium.
| | - R Frank Kooy
- Department of Medical Genetics, University of Antwerp, Prins Boudewijnlaan 43/6, 2650, Edegem, Belgium.
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30
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Anderson AG, Rogers BB, Loupe JM, Rodriguez-Nunez I, Roberts SC, White LM, Brazell JN, Bunney WE, Bunney BG, Watson SJ, Cochran JN, Myers RM, Rizzardi LF. Single nucleus multiomics identifies ZEB1 and MAFB as candidate regulators of Alzheimer's disease-specific cis-regulatory elements. CELL GENOMICS 2023; 3:100263. [PMID: 36950385 PMCID: PMC10025452 DOI: 10.1016/j.xgen.2023.100263] [Citation(s) in RCA: 22] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 12/06/2022] [Accepted: 01/12/2023] [Indexed: 02/05/2023]
Abstract
Cell type-specific transcriptional differences between brain tissues from donors with Alzheimer's disease (AD) and unaffected controls have been well documented, but few studies have rigorously interrogated the regulatory mechanisms responsible for these alterations. We performed single nucleus multiomics (snRNA-seq plus snATAC-seq) on 105,332 nuclei isolated from cortical tissues from 7 AD and 8 unaffected donors to identify candidate cis-regulatory elements (CREs) involved in AD-associated transcriptional changes. We detected 319,861 significant correlations, or links, between gene expression and cell type-specific transposase accessible regions enriched for active CREs. Among these, 40,831 were unique to AD tissues. Validation experiments confirmed the activity of many regions, including several candidate regulators of APP expression. We identified ZEB1 and MAFB as candidate transcription factors playing important roles in AD-specific gene regulation in neurons and microglia, respectively. Microglia links were globally enriched for heritability of AD risk and previously identified active regulatory regions.
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Affiliation(s)
| | - Brianne B. Rogers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
- University of Alabama at Birmingham, Birmingham, AL, USA
| | - Jacob M. Loupe
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | | | - Lauren M. White
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | | | - William E. Bunney
- Department of Psychiatry and Human Behavior, College of Medicine, University of California, Irvine, Irvine, CA, USA
| | - Blynn G. Bunney
- Department of Psychiatry and Human Behavior, College of Medicine, University of California, Irvine, Irvine, CA, USA
| | - Stanley J. Watson
- Mental Health Research Institute, University of Michigan, Ann Arbor, MI, USA
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31
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Rheinberger M, Costa AL, Kampmann M, Glavas D, Shytaj IL, Sreeram S, Penzo C, Tibroni N, Garcia-Mesa Y, Leskov K, Fackler OT, Vlahovicek K, Karn J, Lucic B, Herrmann C, Lusic M. Genomic profiling of HIV-1 integration in microglia cells links viral integration to the topologically associated domains. Cell Rep 2023; 42:112110. [PMID: 36790927 DOI: 10.1016/j.celrep.2023.112110] [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: 06/09/2022] [Revised: 12/15/2022] [Accepted: 01/30/2023] [Indexed: 02/16/2023] Open
Abstract
HIV-1 encounters the hierarchically organized host chromatin to stably integrate and persist in anatomically distinct latent reservoirs. The contribution of genome organization in HIV-1 infection has been largely understudied across different HIV-1 targets. Here, we determine HIV-1 integration sites (ISs), associate them with chromatin and expression signatures at different genomic scales in a microglia cell model, and profile them together with the primary T cell reservoir. HIV-1 insertions into introns of actively transcribed genes with IS hotspots in genic and super-enhancers, characteristic of blood cells, are maintained in the microglia cell model. Genome organization analysis reveals dynamic CCCTC-binding factor (CTCF) clusters in cells with active and repressed HIV-1 transcription, whereas CTCF removal impairs viral integration. We identify CTCF-enriched topologically associated domain (TAD) boundaries with signatures of transcriptionally active chromatin as HIV-1 integration determinants in microglia and CD4+ T cells, highlighting the importance of host genome organization in HIV-1 infection.
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Affiliation(s)
- Mona Rheinberger
- Department of Infectious Diseases, Integrative Virology, Heidelberg University Hospital, 69120 Heidelberg, Germany; German Center for Infection Research (DZIF), 69120 Heidelberg, Germany
| | - Ana Luisa Costa
- Health Data Science Unit, Medical Faculty University Heidelberg and BioQuant, 69120 Heidelberg, Germany
| | - Martin Kampmann
- Department of Infectious Diseases, Integrative Virology, Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Dunja Glavas
- Bioinformatics Group, Division of Molecular Biology, Department of Biology, Faculty of Science, University of Zagreb, 10000 Zagreb, Croatia
| | - Iart Luca Shytaj
- Department of Infectious Diseases, Integrative Virology, Heidelberg University Hospital, 69120 Heidelberg, Germany; German Center for Infection Research (DZIF), 69120 Heidelberg, Germany
| | - Sheetal Sreeram
- Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Carlotta Penzo
- Department of Infectious Diseases, Integrative Virology, Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Nadine Tibroni
- Department of Infectious Diseases, Integrative Virology, Heidelberg University Hospital, 69120 Heidelberg, Germany
| | - Yoelvis Garcia-Mesa
- Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Konstantin Leskov
- Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Oliver T Fackler
- Department of Infectious Diseases, Integrative Virology, Heidelberg University Hospital, 69120 Heidelberg, Germany; German Center for Infection Research (DZIF), 69120 Heidelberg, Germany
| | - Kristian Vlahovicek
- Bioinformatics Group, Division of Molecular Biology, Department of Biology, Faculty of Science, University of Zagreb, 10000 Zagreb, Croatia
| | - Jonathan Karn
- Department of Molecular Biology and Microbiology, Case Western Reserve University, Cleveland, OH 44106, USA
| | - Bojana Lucic
- Department of Infectious Diseases, Integrative Virology, Heidelberg University Hospital, 69120 Heidelberg, Germany; German Center for Infection Research (DZIF), 69120 Heidelberg, Germany.
| | - Carl Herrmann
- Health Data Science Unit, Medical Faculty University Heidelberg and BioQuant, 69120 Heidelberg, Germany.
| | - Marina Lusic
- Department of Infectious Diseases, Integrative Virology, Heidelberg University Hospital, 69120 Heidelberg, Germany; German Center for Infection Research (DZIF), 69120 Heidelberg, Germany.
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32
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Sey NYA, Pratt BM, Won H. Annotating genetic variants to target genes using H-MAGMA. Nat Protoc 2023; 18:22-35. [PMID: 36289406 PMCID: PMC10026181 DOI: 10.1038/s41596-022-00745-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Accepted: 06/28/2022] [Indexed: 01/14/2023]
Abstract
An outstanding goal in modern genomics is to systematically predict the functional outcome of noncoding variation associated with complex traits. To address this, we developed Hi-C-coupled multi-marker analysis of genomic annotation (H-MAGMA), which builds on traditional MAGMA-a gene-based analysis tool that assigns variants to their target genes-by incorporating 3D chromatin configuration in assigning variants to their putative target genes. Applying this approach, we identified key biological pathways implicated in a wide range of brain disorders and showed its utility in complementing other functional genomic resources such as expression quantitative trait loci-based variant annotation. Here, we provide a detailed protocol for generating the H-MAGMA variant-gene annotation file by using chromatin interaction data from the adult human brain. In addition, we provide an example of how H-MAGMA is run by using genome-wide association study summary statistics of Parkinson's disease. Lastly, we generated variant-gene annotation files for 28 tissues and cell types, with the hope of contributing a resource for researchers studying a broad set of complex genetic disorders. H-MAGMA can be performed in <2 h for any cell type in which Hi-C data are available.
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Affiliation(s)
- Nancy Y A Sey
- UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Brandon M Pratt
- Department of Pharmacology, University of North Carolina, Chapel Hill, NC, USA
| | - Hyejung Won
- UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC, USA.
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
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33
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Levchenko A, Plotnikova M. Genomic regulatory sequences in the pathogenesis of bipolar disorder. Front Psychiatry 2023; 14:1115924. [PMID: 36824672 PMCID: PMC9941178 DOI: 10.3389/fpsyt.2023.1115924] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 01/23/2023] [Indexed: 02/10/2023] Open
Abstract
The lifetime prevalence of bipolar disorder is estimated to be about 2%. Epigenetics defines regulatory mechanisms that determine relatively stable patterns of gene expression by controlling all key steps, from DNA to messenger RNA to protein. This Mini Review highlights recent discoveries of modified epigenetic control resulting from genetic variants associated with bipolar disorder in genome-wide association studies. The revealed epigenetic abnormalities implicate gene transcription and post-transcriptional regulation. In the light of these discoveries, the Mini Review focuses on the genes PACS1, MCHR1, DCLK3, HAPLN4, LMAN2L, TMEM258, GNL3, LRRC57, CACNA1C, CACNA1D, and NOVA2 and their potential biological role in the pathogenesis of bipolar disorder. Molecular mechanisms under control of these genes do not translate into a unified picture and substantially more research is needed to fill the gaps in knowledge and to solve current limitations in prognosis and treatment of bipolar disorder. In conclusion, the genetic and functional studies confirm the complex nature of bipolar disorder and indicate future research directions to explore possible targeted treatment options, eventually working toward a personalized approach.
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Affiliation(s)
- Anastasia Levchenko
- Institute of Translational Biomedicine, Saint Petersburg State University, Saint Petersburg, Russia
| | - Maria Plotnikova
- Vavilov Institute of General Genetics, Russian Academy of Sciences, Moscow, Russia.,Center for Genetics and Life Science, Sirius University of Science and Technology, Sochi, Russia
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34
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The Role of Epigenetics in Neuroinflammatory-Driven Diseases. Int J Mol Sci 2022; 23:ijms232315218. [PMID: 36499544 PMCID: PMC9740629 DOI: 10.3390/ijms232315218] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 11/24/2022] [Accepted: 11/29/2022] [Indexed: 12/12/2022] Open
Abstract
Neurodegenerative disorders are characterized by the progressive loss of central and/or peripheral nervous system neurons. Within this context, neuroinflammation comes up as one of the main factors linked to neurodegeneration progression. In fact, neuroinflammation has been recognized as an outstanding factor for Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), and multiple sclerosis (MS). Interestingly, neuroinflammatory diseases are characterized by dramatic changes in the epigenetic profile, which might provide novel prognostic and therapeutic factors towards neuroinflammatory treatment. Deep changes in DNA and histone methylation, along with histone acetylation and altered non-coding RNA expression, have been reported at the onset of inflammatory diseases. The aim of this work is to review the current knowledge on this field.
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35
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Plaza-Jennings A, Valada A, Akbarian S. 3D Genome Plasticity in Normal and Diseased Neurodevelopment. Genes (Basel) 2022; 13:1999. [PMID: 36360237 PMCID: PMC9690570 DOI: 10.3390/genes13111999] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 10/18/2022] [Accepted: 10/26/2022] [Indexed: 10/17/2023] Open
Abstract
Non-random spatial organization of the chromosomal material inside the nuclei of brain cells emerges as an important regulatory layer of genome organization and function in health and disease. Here, we discuss how integrative approaches assessing chromatin in context of the 3D genome is providing new insights into normal and diseased neurodevelopment. Studies in primate (incl. human) and rodent brain have confirmed that chromosomal organization in neurons and glia undergoes highly dynamic changes during pre- and early postnatal development, with potential for plasticity across a much wider age window. For example, neuronal 3D genomes from juvenile and adult cerebral cortex and hippocampus undergo chromosomal conformation changes at hundreds of loci in the context of learning and environmental enrichment, viral infection, and neuroinflammation. Furthermore, locus-specific structural DNA variations, such as micro-deletions, duplications, repeat expansions, and retroelement insertions carry the potential to disrupt the broader epigenomic and transcriptional landscape far beyond the boundaries of the site-specific variation, highlighting the critical importance of long-range intra- and inter-chromosomal contacts for neuronal and glial function.
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Affiliation(s)
- Amara Plaza-Jennings
- Graduate School of Biomedical Sciences, Medical Scientist Training Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Aditi Valada
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Schahram Akbarian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
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36
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Won H, Huguet G, Jacquemont S. Rare and common autism risk variants converge across 16p. Nat Genet 2022; 54:1587-1588. [PMID: 36303073 DOI: 10.1038/s41588-022-01219-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Hyejung Won
- Department of Genetics and the Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Guillaume Huguet
- Sainte Justine University Hospital Research Center, Montreal, Quebec, Canada
| | - Sébastien Jacquemont
- Sainte Justine University Hospital Research Center, Montreal, Quebec, Canada. .,Department of Pediatrics, University of Montreal, Montreal, Quebec, Canada.
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37
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Jones IR, Ren X, Shen Y. High-throughput CRISPRi and CRISPRa technologies in 3D genome regulation for neuropsychiatric diseases. Hum Mol Genet 2022; 31:R47-R53. [PMID: 35972825 PMCID: PMC9585669 DOI: 10.1093/hmg/ddac193] [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: 07/14/2022] [Revised: 08/05/2022] [Accepted: 08/09/2022] [Indexed: 11/13/2022] Open
Abstract
Advances in genomics have led to the identification of many risk loci with hundreds of genes and thousands of DNA variants associated with neuropsychiatric disorders. A significant barrier to understanding the genetic underpinnings of complex diseases is the lack of functional characterization of risk genes and variants in biological systems relevant to human health and connecting disease-associated variants to pathological phenotypes. Characterizing gene and DNA variant functions requires genetic perturbations followed by molecular and cellular assays of neurobiological phenotypes. However, generating null or mutant alleles is low throughput, making it impossible to characterize disease-associated variants in large quantities efficiently. CRISPR interference (CRISPRi) and CRISPR activation (CRISPRa) screens can be leveraged to dissect the biological consequences of the tested genes and variants in their native context. Nevertheless, testing non-coding variants associated with complex diseases remains non-trivial. In this review, we first discuss the current challenges of interpreting the function of the non-coding genome and approaches to prioritizing disease-associated variants in the context of the 3D epigenome. Second, we provide a brief overview of high-throughput CRISPRi and CRISPRa screening strategies applicable for characterizing non-coding sequences in appropriate biological systems. Lastly, we discuss the promising prospects of using CRISPR-based technologies to dissect DNA sequences associated with neuropsychiatric diseases.
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Affiliation(s)
- Ian R Jones
- Institute for Human Genetics, University of California, San Francisco, CA, USA
| | - Xingjie Ren
- Institute for Human Genetics, University of California, San Francisco, CA, USA
| | - Yin Shen
- Institute for Human Genetics, University of California, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, CA, USA
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38
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Bendl J, Hauberg ME, Girdhar K, Im E, Vicari JM, Rahman S, Fernando MB, Townsley KG, Dong P, Misir R, Kleopoulos SP, Reach SM, Apontes P, Zeng B, Zhang W, Voloudakis G, Brennand KJ, Nixon RA, Haroutunian V, Hoffman GE, Fullard JF, Roussos P. The three-dimensional landscape of cortical chromatin accessibility in Alzheimer's disease. Nat Neurosci 2022; 25:1366-1378. [PMID: 36171428 PMCID: PMC9581463 DOI: 10.1038/s41593-022-01166-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Accepted: 08/16/2022] [Indexed: 02/06/2023]
Abstract
To characterize the dysregulation of chromatin accessibility in Alzheimer's disease (AD), we generated 636 ATAC-seq libraries from neuronal and nonneuronal nuclei isolated from the superior temporal gyrus and entorhinal cortex of 153 AD cases and 56 controls. By analyzing a total of ~20 billion read pairs, we expanded the repertoire of known open chromatin regions (OCRs) in the human brain and identified cell-type-specific enhancer-promoter interactions. We show that interindividual variability in OCRs can be leveraged to identify cis-regulatory domains (CRDs) that capture the three-dimensional structure of the genome (3D genome). We identified AD-associated effects on chromatin accessibility, the 3D genome and transcription factor (TF) regulatory networks. For one of the most AD-perturbed TFs, USF2, we validated its regulatory effect on lysosomal genes. Overall, we applied a systematic approach to understanding the role of the 3D genome in AD. We provide all data as an online resource for widespread community-based analysis.
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Affiliation(s)
- Jaroslav Bendl
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Mads E Hauberg
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative of Integrative Psychiatric Research (iPSYCH), Aarhus University, Aarhus, Denmark
- Centre for Integrative Sequencing (iSEQ), Aarhus University, Aarhus, Denmark
| | - Kiran Girdhar
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eunju Im
- Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Department of Psychiatry, New York University Langone Health, New York, NY, USA
| | - James M Vicari
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Graduate School of Biomedical Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Samir Rahman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael B Fernando
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Graduate School of Biomedical Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kayla G Townsley
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Graduate School of Biomedical Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pengfei Dong
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ruth Misir
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Steven P Kleopoulos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sarah M Reach
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pasha Apontes
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Biao Zeng
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Wen Zhang
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Georgios Voloudakis
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kristen J Brennand
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Yale University, New Haven, CT, USA
| | - Ralph A Nixon
- Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
- Department of Psychiatry, New York University Langone Health, New York, NY, USA
- Department of Cell Biology, New York University Langone Health, New York, NY, USA
- New York University Neuroscience Institute, New York, NY, USA
| | - Vahram Haroutunian
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY, USA
| | - Gabriel E Hoffman
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Panos Roussos
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Icahn Institute for Data Science and Genomic Technology, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Genetics and Genomic Science, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA.
- Mental Illness Research Education and Clinical Center (MIRECC), James J. Peters VA Medical Center, Bronx, NY, USA.
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39
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Afridi R, Rahman MH, Suk K. Implications of glial metabolic dysregulation in the pathophysiology of neurodegenerative diseases. Neurobiol Dis 2022; 174:105874. [PMID: 36154877 DOI: 10.1016/j.nbd.2022.105874] [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: 12/13/2021] [Revised: 08/28/2022] [Accepted: 09/21/2022] [Indexed: 11/16/2022] Open
Abstract
Glial cells are the most abundant cells of the brain, outnumbering neurons. These multifunctional cells are crucial for maintaining brain homeostasis by providing trophic and nutritional support to neurons, sculpting synapses, and providing an immune defense. Glia are highly plastic and undergo both structural and functional alterations in response to changes in the brain microenvironment. Glial phenotypes are intimately regulated by underlying metabolic machinery, which dictates the effector functions of these cells. Altered brain energy metabolism and chronic neuroinflammation are common features of several neurodegenerative diseases. Microglia and astrocytes are the major glial cells fueling the ongoing neuroinflammatory process, exacerbating neurodegeneration. Distinct metabolic perturbations in microglia and astrocytes, including altered carbohydrate, lipid, and amino acid metabolism have been documented in neurodegenerative diseases. These disturbances aggravate the neurodegenerative process by potentiating the inflammatory activation of glial cells. This review covers the recent advances in the molecular aspects of glial metabolic changes in the pathophysiology of neurodegenerative diseases. Finally, we discuss studies exploiting glial metabolism as a potential therapeutic avenue in neurodegenerative diseases.
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Affiliation(s)
- Ruqayya Afridi
- Department of Pharmacology, School of Medicine, Kyungpook National University, Daegu 41944, Republic of Korea; BK21 Plus KNU Biomedical Convergence Program, Department of Biomedical Sciences, School of Medicine, Kyungpook National University, Daegu 41944, Republic of Korea
| | - Md Habibur Rahman
- Department of Pharmacology, School of Medicine, Kyungpook National University, Daegu 41944, Republic of Korea; Department of Neurology, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Kyoungho Suk
- Department of Pharmacology, School of Medicine, Kyungpook National University, Daegu 41944, Republic of Korea; BK21 Plus KNU Biomedical Convergence Program, Department of Biomedical Sciences, School of Medicine, Kyungpook National University, Daegu 41944, Republic of Korea; Brain Science and Engineering Institute, Kyungpook National University, Daegu 41944, Republic of Korea.
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40
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McAfee JC, Bell JL, Krupa O, Matoba N, Stein JL, Won H. Focus on your locus with a massively parallel reporter assay. J Neurodev Disord 2022; 14:50. [PMID: 36085003 PMCID: PMC9463819 DOI: 10.1186/s11689-022-09461-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 09/01/2022] [Indexed: 01/01/2023] Open
Abstract
A growing number of variants associated with risk for neurodevelopmental disorders have been identified by genome-wide association and whole genome sequencing studies. As common risk variants often fall within large haplotype blocks covering long stretches of the noncoding genome, the causal variants within an associated locus are often unknown. Similarly, the effect of rare noncoding risk variants identified by whole genome sequencing on molecular traits is seldom known without functional assays. A massively parallel reporter assay (MPRA) is an assay that can functionally validate thousands of regulatory elements simultaneously using high-throughput sequencing and barcode technology. MPRA has been adapted to various experimental designs that measure gene regulatory effects of genetic variants within cis- and trans-regulatory elements as well as posttranscriptional processes. This review discusses different MPRA designs that have been or could be used in the future to experimentally validate genetic variants associated with neurodevelopmental disorders. Though MPRA has limitations such as it does not model genomic context, this assay can help narrow down the underlying genetic causes of neurodevelopmental disorders by screening thousands of sequences in one experiment. We conclude by describing future directions of this technique such as applications of MPRA for gene-by-environment interactions and pharmacogenetics.
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Affiliation(s)
- Jessica C. McAfee
- grid.10698.360000000122483208Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA ,grid.10698.360000000122483208UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Jessica L. Bell
- grid.10698.360000000122483208Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA ,grid.10698.360000000122483208UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Oleh Krupa
- grid.10698.360000000122483208Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA ,grid.10698.360000000122483208UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Nana Matoba
- grid.10698.360000000122483208Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA ,grid.10698.360000000122483208UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Jason L. Stein
- grid.10698.360000000122483208Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA ,grid.10698.360000000122483208UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA. .,UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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41
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Pang D, Yu S, Yang X. A mini-review of the role of condensin in human nervous system diseases. Front Mol Neurosci 2022; 15:889796. [PMID: 35992200 PMCID: PMC9386267 DOI: 10.3389/fnmol.2022.889796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 07/07/2022] [Indexed: 01/10/2023] Open
Abstract
Mitosis and meiosis are crucial life activities that transmit eukaryotic genetic information to progeny in a stable and orderly manner. The formation and appearance of chromosomes, which are derived from chromatin, are the preconditions and signs of mitosis. When entering mitosis, interphase loose chromatin is highly spiralized and folded to form compact chromosomes. In recent years, it has been found that in addition to the well-known DNA, histones, and topoisomerase, a large protein complex called condensin plays an important role in the process of chromosome formation. Numerous studies have shown that the abnormal function of condensin can lead to incomplete or excessive concentration of chromatin, as well as disorder of genome organization process, abnormal transmission of genetic information, and ultimately lead to various diseases of individual, especially in nervous system diseases. In this review, the biological function of condensin and the potential pathogenic mechanism of condensin in nervous system diseases are briefly summarized. Therefore, the investigation of these mechanisms makes a significant contribution to the understanding of those related diseases and provides new ideas for clinical treatments.
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Affiliation(s)
- Du Pang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin Neurological Institute, Tianjin, China
| | - Shengping Yu
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin Neurological Institute, Tianjin, China
- *Correspondence: Shengping Yu Xuejun Yang
| | - Xuejun Yang
- Department of Neurosurgery, Beijing Tsinghua Changgung Hospital, Affiliated Hospital of Tsinghua University, Beijing, China
- *Correspondence: Shengping Yu Xuejun Yang
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42
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Raznahan A, Won H, Glahn DC, Jacquemont S. Convergence and Divergence of Rare Genetic Disorders on Brain Phenotypes: A Review. JAMA Psychiatry 2022; 79:818-828. [PMID: 35767289 DOI: 10.1001/jamapsychiatry.2022.1450] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
IMPORTANCE Rare genetic disorders modulating gene expression-as exemplified by gene dosage disorders (GDDs)-represent a collectively common set of high-risk factors for neuropsychiatric illness. Research on GDDs is rapidly expanding because these variants have high effect sizes and a known genetic basis. Moreover, the prevalence of recurrent GDDs (encompassing aneuploidies and certain copy number variations) enables genetic-first phenotypic characterization of the same GDD across multiple individuals, thereby offering a unique window into genetic influences on the human brain and behavior. However, the rapid growth of GDD research has unveiled perplexing phenotypic convergences and divergences across genomic loci; while phenotypic profiles may be specifically associated with a genomic variant, individual behavioral and neuroimaging traits appear to be nonspecifically influenced by most GDDs. OBSERVATIONS This complexity is addressed by (1) providing an accessible survey of genotype-phenotype mappings across different GDDs, focusing on psychopathology, cognition, and brain anatomy, and (2) detailing both methodological and mechanistic sources for observed phenotypic convergences and divergences. This effort yields methodological recommendations for future comparative phenotypic research on GDDs as well as a set of new testable hypotheses regarding aspects of early brain patterning that might govern the complex mapping of genetic risk onto phenotypic variation in neuropsychiatric disorders. CONCLUSIONS AND RELEVANCE A roadmap is provided to boost accurate measurement and mechanistic interrogation of phenotypic convergence and divergence across multiple GDDs. Pursuing the questions posed by GDDs could substantially improve our taxonomical, neurobiological, and translational understanding of neuropsychiatric illness.
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Affiliation(s)
- Armin Raznahan
- Section on Developmental Neurogenomics, Human Genetics Branch, National Institute of Mental Health Intramural Research Program, Bethesda, Maryland
| | - Hyejung Won
- Department of Genetics and the Neuroscience Center, University of North Carolina at Chapel Hill
| | - David C Glahn
- Tommy Fuss Center for Neuropsychiatric Disease Research, Boston Children's Hospital, Boston, Massachusetts.,Department of Psychiatry, Harvard Medical School, Boston, Massachusetts
| | - Sébastien Jacquemont
- Sainte Justine University Hospital Research Center, Montreal, Quebec, Canada.,Department of Pediatrics, University of Montreal, Sainte Justine Research Center, Montreal, Quebec, Canada
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Ballarino R, Bouwman BAM, Agostini F, Harbers L, Diekmann C, Wernersson E, Bienko M, Crosetto N. An atlas of endogenous DNA double-strand breaks arising during human neural cell fate determination. Sci Data 2022; 9:400. [PMID: 35821502 PMCID: PMC9276747 DOI: 10.1038/s41597-022-01508-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 06/22/2022] [Indexed: 11/25/2022] Open
Abstract
Endogenous DNA double-strand breaks (DSBs) occurring in neural cells have been implicated in the pathogenesis of neurodevelopmental disorders (NDDs). Currently, a genomic map of endogenous DSBs arising during human neurogenesis is missing. Here, we applied in-suspension Breaks Labeling In Situ and Sequencing (sBLISS), RNA-Seq, and Hi-C to chart the genomic landscape of DSBs and relate it to gene expression and genome architecture in 2D cultures of human neuroepithelial stem cells (NES), neural progenitor cells (NPC), and post-mitotic neural cells (NEU). Endogenous DSBs were enriched at the promoter and along the gene body of transcriptionally active genes, at the borders of topologically associating domains (TADs), and around chromatin loop anchors. NDD risk genes harbored significantly more DSBs in comparison to other protein-coding genes, especially in NEU cells. We provide sBLISS, RNA-Seq, and Hi-C datasets for each differentiation stage, and all the scripts needed to reproduce our analyses. Our datasets and tools represent a unique resource that can be harnessed to investigate the role of genome fragility in the pathogenesis of NDDs. Measurement(s) | DNA Double Strand Break • Transcriptome • Whole Genome Sequencing • Chromosome conformation capture assay • Tumor Suppressor p53-Binding Protein 1 | Technology Type(s) | sBLISS - Genome-wide detection of DNA double-strand breaks by in-suspension breaks labeling in situ and sequencing • RNA-seq of total RNA • copy number variation profiling assay • Hi-C • Immunocytochemistry | Factor Type(s) | Human Neural Cell Fate Specification | Sample Characteristic - Organism | Homo sapiens | Sample Characteristic - Environment | cell culture |
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Affiliation(s)
- Roberto Ballarino
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, SE-17165, Sweden.,Science for Life Laboratory, Tomtebodavägen 23 A, Solna, SE-17165, Sweden.,Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, SE-17165, Sweden
| | - Britta A M Bouwman
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, SE-17165, Sweden.,Science for Life Laboratory, Tomtebodavägen 23 A, Solna, SE-17165, Sweden
| | - Federico Agostini
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, SE-17165, Sweden.,Science for Life Laboratory, Tomtebodavägen 23 A, Solna, SE-17165, Sweden
| | - Luuk Harbers
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, SE-17165, Sweden.,Science for Life Laboratory, Tomtebodavägen 23 A, Solna, SE-17165, Sweden
| | - Constantin Diekmann
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, SE-17165, Sweden.,Science for Life Laboratory, Tomtebodavägen 23 A, Solna, SE-17165, Sweden
| | - Erik Wernersson
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, SE-17165, Sweden.,Science for Life Laboratory, Tomtebodavägen 23 A, Solna, SE-17165, Sweden
| | - Magda Bienko
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, SE-17165, Sweden. .,Science for Life Laboratory, Tomtebodavägen 23 A, Solna, SE-17165, Sweden. .,Human Technopole, Viale Rita Levi-Montalcini 1, 20157, Milan, Italy.
| | - Nicola Crosetto
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, SE-17165, Sweden. .,Science for Life Laboratory, Tomtebodavägen 23 A, Solna, SE-17165, Sweden. .,Human Technopole, Viale Rita Levi-Montalcini 1, 20157, Milan, Italy.
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44
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Kundakovic M, Rocks D. Sex hormone fluctuation and increased female risk for depression and anxiety disorders: From clinical evidence to molecular mechanisms. Front Neuroendocrinol 2022; 66:101010. [PMID: 35716803 PMCID: PMC9715398 DOI: 10.1016/j.yfrne.2022.101010] [Citation(s) in RCA: 64] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Revised: 05/18/2022] [Accepted: 06/10/2022] [Indexed: 11/18/2022]
Abstract
Women are at twice the risk for anxiety and depression disorders as men are, although the underlying biological factors and mechanisms are largely unknown. In this review, we address this sex disparity at both the etiological and mechanistic level. We dissect the role of fluctuating sex hormones as a critical biological factor contributing to the increased depression and anxiety risk in women. We provide parallel evidence in humans and rodents that brain structure and function vary with naturally-cycling ovarian hormones. This female-unique brain plasticity and associated vulnerability are primarily driven by estrogen level changes. For the first time, we provide a sex hormone-driven molecular mechanism, namely chromatin organizational changes, that regulates neuronal gene expression and brain plasticity but may also prime the (epi)genome for psychopathology. Finally, we map out future directions including experimental and clinical studies that will facilitate novel sex- and gender-informed approaches to treat depression and anxiety disorders.
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Affiliation(s)
- Marija Kundakovic
- Department of Biological Sciences, Fordham University, Bronx, NY, USA.
| | - Devin Rocks
- Department of Biological Sciences, Fordham University, Bronx, NY, USA
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45
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Sey NYA, Hu B, Iskhakova M, Lee S, Sun H, Shokrian N, Ben Hutta G, Marks JA, Quach BC, Johnson EO, Hancock DB, Akbarian S, Won H. Chromatin architecture in addiction circuitry identifies risk genes and potential biological mechanisms underlying cigarette smoking and alcohol use traits. Mol Psychiatry 2022; 27:3085-3094. [PMID: 35422469 PMCID: PMC9853312 DOI: 10.1038/s41380-022-01558-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 03/21/2022] [Accepted: 03/30/2022] [Indexed: 01/25/2023]
Abstract
Cigarette smoking and alcohol use are among the most prevalent substances used worldwide and account for a substantial proportion of preventable morbidity and mortality, underscoring the public health significance of understanding their etiology. Genome-wide association studies (GWAS) have successfully identified genetic variants associated with cigarette smoking and alcohol use traits. However, the vast majority of risk variants reside in non-coding regions of the genome, and their target genes and neurobiological mechanisms are unknown. Chromosomal conformation mappings can address this knowledge gap by charting the interaction profiles of risk-associated regulatory variants with target genes. To investigate the functional impact of common variants associated with cigarette smoking and alcohol use traits, we applied Hi-C coupled MAGMA (H-MAGMA) built upon cortical and newly generated midbrain dopaminergic neuronal Hi-C datasets to GWAS summary statistics of nicotine dependence, cigarettes per day, problematic alcohol use, and drinks per week. The identified risk genes mapped to key pathways associated with cigarette smoking and alcohol use traits, including drug metabolic processes and neuronal apoptosis. Risk genes were highly expressed in cortical glutamatergic, midbrain dopaminergic, GABAergic, and serotonergic neurons, suggesting them as relevant cell types in understanding the mechanisms by which genetic risk factors influence cigarette smoking and alcohol use. Lastly, we identified pleiotropic genes between cigarette smoking and alcohol use traits under the assumption that they may reveal substance-agnostic, shared neurobiological mechanisms of addiction. The number of pleiotropic genes was ~26-fold higher in dopaminergic neurons than in cortical neurons, emphasizing the critical role of ascending dopaminergic pathways in mediating general addiction phenotypes. Collectively, brain region- and neuronal subtype-specific 3D genome architecture helps refine neurobiological hypotheses for smoking, alcohol, and general addiction phenotypes by linking genetic risk factors to their target genes.
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Affiliation(s)
- Nancy Y A Sey
- UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC, 27599, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Benxia Hu
- UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC, 27599, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Marina Iskhakova
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Sool Lee
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Huaigu Sun
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Neda Shokrian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Gabriella Ben Hutta
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Jesse A Marks
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, Chapel Hill, NC, 27709, USA
| | - Bryan C Quach
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, Chapel Hill, NC, 27709, USA
| | - Eric O Johnson
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, Chapel Hill, NC, 27709, USA
- Fellow Program, RTI International, Research Triangle Park, Chapel Hill, NC, 27709, USA
| | - Dana B Hancock
- GenOmics, Bioinformatics, and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, Chapel Hill, NC, 27709, USA
| | - Schahram Akbarian
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
| | - Hyejung Won
- UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC, 27599, USA.
- Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA.
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46
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Liu W, Zhong W, Chen J, Huang B, Hu M, Li Y. Understanding Regulatory Mechanisms of Brain Function and Disease through 3D Genome Organization. Genes (Basel) 2022; 13:genes13040586. [PMID: 35456393 PMCID: PMC9027261 DOI: 10.3390/genes13040586] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Revised: 03/17/2022] [Accepted: 03/23/2022] [Indexed: 02/01/2023] Open
Abstract
The human genome has a complex and dynamic three-dimensional (3D) organization, which plays a critical role for gene regulation and genome function. The importance of 3D genome organization in brain development and function has been well characterized in a region- and cell-type-specific fashion. Recent technological advances in chromosome conformation capture (3C)-based techniques, imaging approaches, and ligation-free methods, along with computational methods to analyze the data generated, have revealed 3D genome features at different scales in the brain that contribute to our understanding of genetic mechanisms underlying neuropsychiatric diseases and other brain-related traits. In this review, we discuss how these advances aid in the genetic dissection of brain-related traits.
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Affiliation(s)
- Weifang Liu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; (W.L.); (J.C.)
| | - Wujuan Zhong
- Biostatistics and Research Decision Sciences, Merck & Co., Inc., Rahway, NJ 07065, USA;
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; (W.L.); (J.C.)
| | - Bo Huang
- Department of Pharmaceutical Chemistry, University of California, San Francisco, CA 94143, USA;
- Chan Zuckerberg Biohub, San Francisco, CA 94158, USA
- Department of Biochemistry and Biophysics, University of California, San Francisco, CA 94143, USA
| | - Ming Hu
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH 44195, USA
- Correspondence: (M.H.); (Y.L.)
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; (W.L.); (J.C.)
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Correspondence: (M.H.); (Y.L.)
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47
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Microglial transcriptomics meets genetics: new disease leads. Nat Rev Neurol 2022; 18:191-192. [DOI: 10.1038/s41582-022-00633-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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48
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Pratt BM, Won H. Advances in profiling chromatin architecture shed light on the regulatory dynamics underlying brain disorders. Semin Cell Dev Biol 2022; 121:153-160. [PMID: 34483043 PMCID: PMC8761161 DOI: 10.1016/j.semcdb.2021.08.013] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 08/18/2021] [Accepted: 08/23/2021] [Indexed: 01/03/2023]
Abstract
Understanding the exquisitely complex nature of the three-dimensional organization of the genome and how it affects gene regulation remains a central question in biology. Recent advances in sequencing- and imaging-based approaches in decoding the three-dimensional chromatin landscape have enabled a systematic characterization of gene regulatory architecture. In this review, we outline how chromatin architecture provides a reference atlas to predict the functional consequences of non-coding variants associated with human traits and disease. High-throughput perturbation assays such as massively parallel reporter assays (MPRA) and CRISPR-based genome engineering in combination with a reference atlas opened an avenue for going beyond observational studies to experimentally validating the regulatory principles of the genome. We conclude by providing a suggested path forward by calling attention to barriers that can be addressed for a more complete understanding of the regulatory landscape of the human brain.
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Affiliation(s)
- Brandon M Pratt
- Department of Pharmacology, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Hyejung Won
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA; UNC Neuroscience Center, University of North Carolina, Chapel Hill, NC 27599, USA.
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49
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Limited Association between Schizophrenia Genetic Risk Factors and Transcriptomic Features. Genes (Basel) 2021; 12:genes12071062. [PMID: 34356078 PMCID: PMC8304922 DOI: 10.3390/genes12071062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 06/29/2021] [Accepted: 07/08/2021] [Indexed: 11/16/2022] Open
Abstract
Schizophrenia is a polygenic disorder with many genomic regions contributing to schizophrenia risk. The majority of genetic variants associated with schizophrenia lie in the non-coding genome and are thought to contribute to transcriptional regulation. Extensive transcriptomic dysregulation has been detected from postmortem brain samples of schizophrenia-affected individuals. However, the relationship between schizophrenia genetic risk factors and transcriptomic features has yet to be explored. Herein, we examined whether varying gene expression features, including differentially expressed genes (DEGs), co-expression networks, and central hubness of genes, contribute to the heritability of schizophrenia. We leveraged quantitative trait loci and chromatin interaction profiles to identify schizophrenia risk variants assigned to the genes that represent different transcriptomic features. We then performed stratified linkage disequilibrium score regression analysis on these variants to estimate schizophrenia heritability enrichment for different gene expression features. Notably, DEGs and co-expression networks showed nominal heritability enrichment. This nominal association can be partly explained by cellular heterogeneity, as DEGs were associated with the genetic risk of schizophrenia in a cell type-specific manner. Moreover, DEGs were enriched for target genes of schizophrenia-associated transcription factors, suggesting that the transcriptomic signatures of schizophrenia are the result of transcriptional regulatory cascades elicited by genetic risk factors.
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