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Nobori T. Exploring the untapped potential of single-cell and spatial omics in plant biology. THE NEW PHYTOLOGIST 2025. [PMID: 40398874 DOI: 10.1111/nph.70220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2025] [Accepted: 04/24/2025] [Indexed: 05/23/2025]
Abstract
Advances in single-cell and spatial omics technologies have revolutionised biology by revealing the diverse molecular states of individual cells and their spatial organization within tissues. The field of plant biology has widely adopted single-cell transcriptome and chromatin accessibility profiling and spatial transcriptomics, which extend traditional cell biology and genomics analyses and provide unique opportunities to reveal molecular and cellular dynamics of tissues. Using these technologies, comprehensive cell atlases have been generated in several model plant species, providing valuable platforms for discovery and tool development. Other emerging technologies related to single-cell and spatial omics, such as multiomics, lineage tracing, molecular recording, and high-content genetic and chemical perturbation phenotyping, offer immense potential for deepening our understanding of plant biology yet remain underutilised due to unique technical challenges and resource availability. Overcoming plant-specific barriers, such as cell wall complexity and limited antibody resources, alongside community-driven efforts in developing more complete reference atlases and computational tools, will accelerate progress. The synergy between technological innovation and targeted biological questions is poised to drive significant discoveries, advancing plant science. This review highlights the current applications of single-cell and spatial omics technologies in plant research and introduces emerging approaches with the potential to transform the field.
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Affiliation(s)
- Tatsuya Nobori
- The Sainsbury Laboratory, University of East Anglia, Norwich Research Park, Norwich, NR4 7UH, UK
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2
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Bougnères P, Le Stunff C. Revisiting the Pathogenesis of X-Linked Adrenoleukodystrophy. Genes (Basel) 2025; 16:590. [PMID: 40428412 PMCID: PMC12111468 DOI: 10.3390/genes16050590] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2025] [Revised: 05/11/2025] [Accepted: 05/15/2025] [Indexed: 05/29/2025] Open
Abstract
BACKGROUND X-ALD is a white matter (WM) disease caused by mutations in the ABCD1 gene encoding the transporter of very-long-chain fatty acids (VLCFAs) into peroxisomes. Strikingly, the same ABCD1 mutation causes either devastating brain inflammatory demyelination during childhood or, more often, progressive spinal cord axonopathy starting in middle-aged adults. The accumulation of undegraded VLCFA in glial cell membranes and myelin has long been thought to be the central mechanism of X-ALD. METHODS This review discusses studies in mouse and drosophila models that have modified our views of X-ALD pathogenesis. RESULTS In the Abcd1 knockout (KO) mouse that mimics the spinal cord disease, the late manifestations of axonopathy are rapidly reversed by ABCD1 gene transfer into spinal cord oligodendrocytes (OLs). In a peroxin-5 KO mouse model, the selective impairment of peroxisomal biogenesis in OLs achieves an almost perfect phenocopy of cerebral ALD. A drosophila knockout model revealed that VLCFA accumulation in glial myelinating cells causes the production of a toxic lipid able to poison axons and activate inflammatory cells. Other mouse models showed the critical role of OLs in providing energy substrates to axons. In addition, studies on microglial changing substates have improved our understanding of neuroinflammation. CONCLUSIONS Animal models supporting a primary role of OLs and axonal pathology and a secondary role of microglia allow us to revisit of X-ALD mechanisms. Beyond ABCD1 mutations, pathogenesis depends on unidentified contributors, such as genetic background, cell-specific epigenomics, potential environmental triggers, and stochasticity of crosstalk between multiple cell types among billions of glial cells and neurons.
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Affiliation(s)
- Pierre Bougnères
- MIRCen Institute, Commissariat à l’Energie Atomique, Laboratoire des Maladies Neurodégénératives, 92260 Fontenay-aux-Roses, France
- NEURATRIS, 92260 Fontenay-aux-Roses, France
- Therapy Design Consulting, 94300 Vincennes, France
| | - Catherine Le Stunff
- MIRCen Institute, Commissariat à l’Energie Atomique, Laboratoire des Maladies Neurodégénératives, 92260 Fontenay-aux-Roses, France
- NEURATRIS, 92260 Fontenay-aux-Roses, France
- UMR1195 Inserm, University Paris Saclay, 94270 Le Kremlin-Bicêtre, France
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3
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Sun Y, Li M, Ning C, Gao L, Liu Z, Zhong S, Lv J, Ke Y, Wang X, Ma Q, Liu Z, Wu S, Yu H, Zhao F, Zhang J, Gong Q, Liu J, Wu Q, Wang X, Chen X. Spatiotemporal 3D chromatin organization across multiple brain regions during human fetal development. Cell Discov 2025; 11:50. [PMID: 40374600 DOI: 10.1038/s41421-025-00798-w] [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: 05/08/2024] [Accepted: 02/21/2025] [Indexed: 05/17/2025] Open
Abstract
Elucidating the regulatory mechanisms underlying the development of different brain regions in humans is essential for understanding advanced cognition and neuropsychiatric disorders. However, the spatiotemporal organization of three-dimensional (3D) chromatin structure and its regulatory functions across different brain regions remain poorly understood. Here, we generated an atlas of high-resolution 3D chromatin structure across six developing human brain regions, including the prefrontal cortex (PFC), primary visual cortex (V1), cerebellum (CB), subcortical corpus striatum (CS), thalamus (TL), and hippocampus (HP), spanning gestational weeks 11-26. We found that the spatial and temporal dynamics of 3D chromatin organization play a key role in regulating brain region development. We also identified H3K27ac-marked super-enhancers as key contributors to shaping brain region-specific 3D chromatin structures and gene expression patterns. Finally, we uncovered hundreds of neuropsychiatric GWAS SNP-linked genes, shedding light on critical molecules in various neuropsychiatric disorders. In summary, our findings provide important insights into the 3D chromatin regulatory mechanisms governing brain region-specific development and can serve as a valuable resource for advancing our understanding of neuropsychiatric disorders.
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Affiliation(s)
- Yaoyu Sun
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangdong, China
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Min Li
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | - Chao Ning
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | - Lei Gao
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | - Zhenbo Liu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | - Suijuan Zhong
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, New Cornerstone Science Laboratory, Beijing Normal University, Beijing, China
| | - Junjie Lv
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangdong, China
- College of Biological Science, China Agricultural University, Beijing, China
| | - Yuwen Ke
- College of Biological Science, China Agricultural University, Beijing, China
| | - Xinxin Wang
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangdong, China
| | - Qiang Ma
- University of Chinese Academy of Sciences, Beijing, China
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | | | - Shuaishuai Wu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | - Hao Yu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | - Fangqi Zhao
- Obstetrics and Gynecology Medical Center of Severe Cardiovascular of Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Jun Zhang
- Obstetrics and Gynecology Medical Center of Severe Cardiovascular of Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Qian Gong
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangdong, China
| | - Jiang Liu
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
- National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Science, Beijing, China
| | - Qian Wu
- State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China
- IDG/McGovern Institute for Brain Research, New Cornerstone Science Laboratory, Beijing Normal University, Beijing, China
| | - Xiaoqun Wang
- State Key Laboratory of Brain and Cognitive Science, Institute of Biophysics, Chinese Academy of Science, Beijing, China.
- IDG/McGovern Institute for Brain Research, New Cornerstone Science Laboratory, Beijing Normal University, Beijing, China.
- Changping Laboratory, Beijing, China.
| | - Xuepeng Chen
- GMU-GIBH Joint School of Life Sciences, The Guangdong-Hong Kong-Macau Joint Laboratory for Cell Fate Regulation and Diseases, Guangzhou National Laboratory, Guangzhou Medical University, Guangdong, China.
- The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangdong, China.
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4
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Wu Y, Wu BZ, Ellenbogen Y, Kant JBY, Yu P, Li X, Caloren L, Sotov V, Tran C, Restrepo M, Kushida M, Ayyadhury S, Kossinna P, Lau R, Habibi P, Mansouri S, Regala J, Durbic T, Aboualizadeh F, Tsao J, Ketela T, Pugh T, Butler MO, Wang BX, Dirks PB, Gao A, Zadeh G, Gaiti F. Neurodevelopmental hijacking of oligodendrocyte lineage programs drives glioblastoma infiltration. Dev Cell 2025:S1534-5807(25)00260-6. [PMID: 40381621 DOI: 10.1016/j.devcel.2025.04.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2024] [Revised: 02/06/2025] [Accepted: 04/25/2025] [Indexed: 05/20/2025]
Abstract
Glioblastoma (GBM) is an aggressive brain tumor with a highly invasive nature. Despite the clinical relevance of this behavior, the molecular underpinnings of infiltrating GBM cells in the peritumoral zone remain underexplored in patients. Here, we show that peritumoral progenitor-like GBM cells activate transcriptional programs associated with increased invasivity, synaptic activity, and NOTCH signaling. These cells spatially colocalize with neurons and exhibit an increased propensity for neuronal crosstalk. The epigenetic encoding of these infiltrative cells mirrors that of uncommitted oligodendrocyte progenitor cells (OPCs) in the developing human brain, a neurodevelopmental state marked by increased synaptic and migratory potential. Functional perturbation of a nominated regulatory factor, ZEB1, confirmed its role in maintaining the invasive and uncommitted developmental potential of infiltrative GBM cells. Our findings provide insights into the neurodevelopmental hijacking that drives GBM infiltration in patients, rationalizing further investigation into targeting differentiation potential as a therapeutic strategy.
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Affiliation(s)
- Yiyan Wu
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Benson Z Wu
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Yosef Ellenbogen
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada; MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, ON, Canada
| | - Joan B Y Kant
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Pengcheng Yu
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Xuyao Li
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Loïc Caloren
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Valentin Sotov
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Christine Tran
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Michelle Restrepo
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Michelle Kushida
- Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, ON, Canada
| | - Shamini Ayyadhury
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Donnelly Centre, University of Toronto, Toronto, ON, Canada
| | - Pathum Kossinna
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Ruth Lau
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Parnian Habibi
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada
| | - Sheila Mansouri
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, ON, Canada
| | - Johanna Regala
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Tanja Durbic
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | | | - Julissa Tsao
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Troy Ketela
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Trevor Pugh
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Ontario Institute for Cancer Research, Toronto, ON, Canada
| | - Marcus O Butler
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Department of Immunology, University of Toronto, Toronto, ON, Canada
| | - Ben X Wang
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada
| | - Peter B Dirks
- Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada; Arthur and Sonia Labatt Brain Tumour Research Centre, The Hospital for Sick Children, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada; Developmental and Stem Cell Biology Department, The Hospital for Sick Children, Toronto, ON, Canada
| | - Andrew Gao
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
| | - Gelareh Zadeh
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, ON, Canada; MacFeeters Hamilton Neuro-Oncology Program, Princess Margaret Cancer Centre, University Health Network and University of Toronto, Toronto, ON, Canada; Department of Neurologic Surgery, Mayo Clinic, Rochester, MN, USA.
| | - Federico Gaiti
- Princess Margaret Cancer Centre, University Health Network, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada; Ontario Institute for Cancer Research, Toronto, ON, Canada; Vector Institute, Toronto, ON, Canada.
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5
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Konstantinides N, Desplan C. Neuronal Circuit Evolution: From Development to Structure and Adaptive Significance. Cold Spring Harb Perspect Biol 2025; 17:a041493. [PMID: 38951021 PMCID: PMC11688512 DOI: 10.1101/cshperspect.a041493] [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] [Indexed: 07/03/2024]
Abstract
Neuronal circuits represent the functional units of the brain. Understanding how the circuits are generated to perform computations will help us understand how the brain functions. Nevertheless, neuronal circuits are not engineered, but have formed through millions of years of animal evolution. We posit that it is necessary to study neuronal circuit evolution to comprehensively understand circuit function. Here, we review our current knowledge regarding the mechanisms that underlie circuit evolution. First, we describe the possible genetic and developmental mechanisms that have contributed to circuit evolution. Then, we discuss the structural changes of circuits during evolution and how these changes affected circuit function. Finally, we try to put circuit evolution in an ecological context and assess the adaptive significance of specific examples. We argue that, thanks to the advent of new tools and technologies, evolutionary neurobiology now allows us to address questions regarding the evolution of circuitry and behavior that were unimaginable until very recently.
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Affiliation(s)
| | - Claude Desplan
- Department of Biology, New York University, New York, New York 10003, USA
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6
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Chai H, Huang X, Xiong G, Huang J, Pels KK, Meng L, Han J, Tang D, Pan G, Deng L, Xiao Q, Wang X, Zhang M, Banecki K, Plewczynski D, Wei CL, Ruan Y. Tri-omic single-cell mapping of the 3D epigenome and transcriptome in whole mouse brains throughout the lifespan. Nat Methods 2025; 22:994-1007. [PMID: 40301621 DOI: 10.1038/s41592-025-02658-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2024] [Accepted: 03/13/2025] [Indexed: 05/01/2025]
Abstract
Exploring the genomic basis of transcriptional programs has been a long-standing research focus. Here we report a single-cell method, ChAIR, to map chromatin accessibility, chromatin interactions and RNA expression simultaneously. After validating in cultured cells, we applied ChAIR to whole mouse brains and delineated the concerted dynamics of epigenome, three-dimensional (3D) genome and transcriptome during maturation and aging. In particular, gene-centric chromatin interactions and open chromatin states provided 3D epigenomic mechanism underlying cell-type-specific transcription and revealed spatially resolved specificity. Importantly, the composition of short-range and ultralong chromatin contacts in individual cells is remarkably correlated with transcriptional activity, open chromatin state and genome folding density. This genomic property, along with associated cellular properties, differs in neurons and non-neuronal cells across different anatomic regions throughout the lifespan, implying divergent nuclear mechano-genomic mechanisms at play in brain cells. Our results demonstrate ChAIR's robustness in revealing single-cell 3D epigenomic states of cell-type-specific transcription in complex tissues.
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Affiliation(s)
- Haoxi Chai
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Xingyu Huang
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Guangzhou Xiong
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Jiaxiang Huang
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Katarzyna Karolina Pels
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Lingyun Meng
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Jin Han
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Dongmei Tang
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Guanjing Pan
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Liang Deng
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Qin Xiao
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Xiaotao Wang
- Obstetrics and Gynecology Hospital, Institute of Reproduction and Development, Shanghai Key Laboratory of Reproduction and Development, Fudan University, Shanghai, China
| | - Meng Zhang
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Krzysztof Banecki
- Laboratory of Bioinformatics and Computational Genomics, Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland
| | - Dariusz Plewczynski
- Laboratory of Bioinformatics and Computational Genomics, Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland
| | - Chia-Lin Wei
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Yijun Ruan
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, China.
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7
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Sugo N, Atsumi Y, Yamamoto N. Transcription and epigenetic factor dynamics in neuronal activity-dependent gene regulation. Trends Genet 2025; 41:425-436. [PMID: 39875312 DOI: 10.1016/j.tig.2024.12.008] [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: 09/19/2024] [Revised: 12/20/2024] [Accepted: 12/20/2024] [Indexed: 01/30/2025]
Abstract
Neuronal activity, including sensory-evoked and spontaneous firing, regulates the expression of a subset of genes known as activity-dependent genes. A key issue in this process is the activation and accumulation of transcription factors (TFs), which bind to cis-elements at specific enhancers and promoters, ultimately driving RNA synthesis through transcription machinery. Epigenetic factors such as histone modifiers also play a crucial role in facilitating the specific binding of TFs. Recent evidence from epigenome analyses and imaging studies have revealed intriguing mechanisms: the default chromatin structure at activity-dependent genes is formed independently of neuronal activity, while neuronal activity modulates spatiotemporal dynamics of TFs and their interactions with epigenetic factors (EFs). In this article we review new insights into activity-dependent gene regulation that affects brain development and plasticity.
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Affiliation(s)
- Noriyuki Sugo
- Graduate School of Frontier Biosciences, Osaka University, Suita, Osaka 565-0871, Japan.
| | - Yuri Atsumi
- Graduate School of Frontier Biosciences, Osaka University, Suita, Osaka 565-0871, Japan
| | - Nobuhiko Yamamoto
- Graduate School of Frontier Biosciences, Osaka University, Suita, Osaka 565-0871, Japan; Institute of Neurological and Psychiatric Disorders, Shenzhen Bay Laboratory, Shenzhen, Guangdong 518132, China.
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8
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Wang J, Ye F, Chai H, Jiang Y, Wang T, Ran X, Xia Q, Xu Z, Fu Y, Zhang G, Wu H, Guo G, Guo H, Ruan Y, Wang Y, Xing D, Xu X, Zhang Z. Advances and applications in single-cell and spatial genomics. SCIENCE CHINA. LIFE SCIENCES 2025; 68:1226-1282. [PMID: 39792333 DOI: 10.1007/s11427-024-2770-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/20/2024] [Accepted: 10/10/2024] [Indexed: 01/12/2025]
Abstract
The applications of single-cell and spatial technologies in recent times have revolutionized the present understanding of cellular states and the cellular heterogeneity inherent in complex biological systems. These advancements offer unprecedented resolution in the examination of the functional genomics of individual cells and their spatial context within tissues. In this review, we have comprehensively discussed the historical development and recent progress in the field of single-cell and spatial genomics. We have reviewed the breakthroughs in single-cell multi-omics technologies, spatial genomics methods, and the computational strategies employed toward the analyses of single-cell atlas data. Furthermore, we have highlighted the advances made in constructing cellular atlases and their clinical applications, particularly in the context of disease. Finally, we have discussed the emerging trends, challenges, and opportunities in this rapidly evolving field.
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Affiliation(s)
- Jingjing Wang
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Fang Ye
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Haoxi Chai
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, 310058, China
| | - Yujia Jiang
- BGI Research, Shenzhen, 518083, China
- BGI Research, Hangzhou, 310030, China
| | - Teng Wang
- Biomedical Pioneering Innovation Center (BIOPIC) and School of Life Sciences, Peking University, Beijing, 100871, China
- Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, 100871, China
| | - Xia Ran
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Institute of Hematology, Zhejiang University, Hangzhou, 310000, China
| | - Qimin Xia
- Biomedical Pioneering Innovation Center (BIOPIC) and School of Life Sciences, Peking University, Beijing, 100871, China
| | - Ziye Xu
- Department of Laboratory Medicine of The First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Yuting Fu
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Guodong Zhang
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Hanyu Wu
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Guoji Guo
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- Center for Stem Cell and Regenerative Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- Zhejiang Provincial Key Lab for Tissue Engineering and Regenerative Medicine, Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cell and Regenerative Medicine, Hangzhou, 310058, China.
- Institute of Hematology, Zhejiang University, Hangzhou, 310000, China.
| | - Hongshan Guo
- Bone Marrow Transplantation Center of the First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- Institute of Hematology, Zhejiang University, Hangzhou, 310000, China.
| | - Yijun Ruan
- Life Sciences Institute and The Second Affiliated Hospital, Zhejiang University, Hangzhou, 310058, China.
| | - Yongcheng Wang
- Department of Laboratory Medicine of The First Affiliated Hospital & Liangzhu Laboratory, Zhejiang University School of Medicine, Hangzhou, 310058, China.
| | - Dong Xing
- Biomedical Pioneering Innovation Center (BIOPIC) and School of Life Sciences, Peking University, Beijing, 100871, China.
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, 100871, China.
| | - Xun Xu
- BGI Research, Shenzhen, 518083, China.
- BGI Research, Hangzhou, 310030, China.
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI Research, Shenzhen, 518083, China.
| | - Zemin Zhang
- Biomedical Pioneering Innovation Center (BIOPIC) and School of Life Sciences, Peking University, Beijing, 100871, China.
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9
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Papetti AV, Jin M, Ma Z, Stillitano AC, Jiang P. Chimeric brain models: Unlocking insights into human neural development, aging, diseases, and cell therapies. Neuron 2025:S0896-6273(25)00256-9. [PMID: 40300597 DOI: 10.1016/j.neuron.2025.03.036] [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: 01/26/2025] [Revised: 03/07/2025] [Accepted: 03/31/2025] [Indexed: 05/01/2025]
Abstract
Human-rodent chimeric brain models serve as a unique platform for investigating the pathophysiology of human cells within a living brain environment. These models are established by transplanting human tissue- or human pluripotent stem cell (hPSC)-derived macroglial, microglial, or neuronal lineage cells, as well as cerebral organoids, into the brains of host animals. This approach has opened new avenues for exploring human brain development, disease mechanisms, and regenerative processes. Here, we highlight recent advancements in using chimeric models to study human neural development, aging, and disease. Additionally, we explore the potential applications of these models for studying human glial cell-replacement therapies, studying in vivo human glial-to-neuron reprogramming, and harnessing single-cell omics and advanced functional assays to uncover detailed insights into human neurobiology. Finally, we discuss strategies to enhance the precision and translational relevance of these models, expanding their impact in stem cell and neuroscience research.
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Affiliation(s)
- Ava V Papetti
- Department of Cell Biology and Neuroscience, Rutgers University-New Brunswick, Piscataway, NJ 08854, USA
| | - Mengmeng Jin
- Department of Cell Biology and Neuroscience, Rutgers University-New Brunswick, Piscataway, NJ 08854, USA
| | - Ziyuan Ma
- Department of Cell Biology and Neuroscience, Rutgers University-New Brunswick, Piscataway, NJ 08854, USA
| | - Alessandro C Stillitano
- Department of Cell Biology and Neuroscience, Rutgers University-New Brunswick, Piscataway, NJ 08854, USA
| | - Peng Jiang
- Department of Cell Biology and Neuroscience, Rutgers University-New Brunswick, Piscataway, NJ 08854, USA.
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10
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Yuan Y, Biswas P, Zemke NR, Dang K, Wu Y, D’Antonio M, Xie Y, Yang Q, Dong K, Lau PK, Li D, Seng C, Bartosik W, Buchanan J, Lin L, Lancione R, Wang K, Lee S, Gibbs Z, Ecker J, Frazer K, Wang T, Preissl S, Wang A, Ayyagari R, Ren B. Single-cell analysis of the epigenome and 3D chromatin architecture in the human retina. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.12.28.630634. [PMID: 39764062 PMCID: PMC11703273 DOI: 10.1101/2024.12.28.630634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/11/2025]
Abstract
Most genetic risk variants linked to ocular diseases are non-protein coding and presumably contribute to disease through dysregulation of gene expression, however, deeper understanding of their mechanisms of action has been impeded by an incomplete annotation of the transcriptional regulatory elements across different retinal cell types. To address this knowledge gap, we carried out single-cell multiomics assays to investigate gene expression, chromatin accessibility, DNA methylome and 3D chromatin architecture in human retina, macula, and retinal pigment epithelium (RPE)/choroid. We identified 420,824 unique candidate regulatory elements and characterized their chromatin states in 23 sub-classes of retinal cells. Comparative analysis of chromatin landscapes between human and mouse retina cells further revealed both evolutionarily conserved and divergent retinal gene-regulatory programs. Leveraging the rapid advancements in deep-learning techniques, we developed sequence-based predictors to interpret non-coding risk variants of retina diseases. Our study establishes retina-wide, single-cell transcriptome, epigenome, and 3D genome atlases, and provides a resource for studying the gene regulatory programs of the human retina and relevant diseases.
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Affiliation(s)
- Ying Yuan
- Department of Material Science, UC San Diego, La Jolla, CA 92037, USA
| | - Pooja Biswas
- Ophthalmology, Shiley Eye Institute, UC San Diego, La Jolla, CA 92037, USA
| | - Nathan R. Zemke
- Center for Epigenomics, UC San Diego, La Jolla, CA 92037, USA
| | - Kelsey Dang
- Center for Epigenomics, UC San Diego, La Jolla, CA 92037, USA
| | - Yue Wu
- Department of Biological Science, UC San Diego, La Jolla, CA 92037, USA
| | - Matteo D’Antonio
- Department of Biomedical Informatics, UC San Diego, La Jolla, CA 92037, USA
| | - Yang Xie
- Department of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA 92037, USA
| | - Qian Yang
- Center for Epigenomics, UC San Diego, La Jolla, CA 92037, USA
| | - Keyi Dong
- Center for Epigenomics, UC San Diego, La Jolla, CA 92037, USA
| | - Pik Ki Lau
- Center for Epigenomics, UC San Diego, La Jolla, CA 92037, USA
| | - Daofeng Li
- Department of Genetics, Washington University School of Medicine in St.Louis, St. Louis, MO 63130, USA
| | - Chad Seng
- Department of Genetics, Washington University School of Medicine in St.Louis, St. Louis, MO 63130, USA
| | | | - Justin Buchanan
- Center for Epigenomics, UC San Diego, La Jolla, CA 92037, USA
| | - Lin Lin
- Center for Epigenomics, UC San Diego, La Jolla, CA 92037, USA
| | - Ryan Lancione
- Center for Epigenomics, UC San Diego, La Jolla, CA 92037, USA
| | - Kangli Wang
- Department of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA 92037, USA
| | - Seoyeon Lee
- Department of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA 92037, USA
| | - Zane Gibbs
- Department of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA 92037, USA
| | - Joseph Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA,USA
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Kelly Frazer
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
- Institute of Genomic Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Ting Wang
- Department of Genetics, Washington University School of Medicine in St.Louis, St. Louis, MO 63130, USA
| | | | - Allen Wang
- Center for Epigenomics, UC San Diego, La Jolla, CA 92037, USA
| | - Radha Ayyagari
- Ophthalmology, Shiley Eye Institute, UC San Diego, La Jolla, CA 92037, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, UC San Diego, La Jolla, CA 92037, USA
- Center for Epigenomics, UC San Diego, La Jolla, CA 92037, USA
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11
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Zhou J, Wu Y, Liu H, Tian W, Castanon RG, Bartlett A, Zhang Z, Yao G, Shi D, Clock B, Marcotte S, Nery JR, Liem M, Claffey N, Boggeman L, Barragan C, Drigo RAE, Weimer AK, Shi M, Cooper-Knock J, Zhang S, Snyder MP, Preissl S, Ren B, O’Connor C, Chen S, Luo C, Dixon JR, Ecker JR. Human Body Single-Cell Atlas of 3D Genome Organization and DNA Methylation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.03.23.644697. [PMID: 40196612 PMCID: PMC11974725 DOI: 10.1101/2025.03.23.644697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 04/09/2025]
Abstract
Higher-order chromatin structure and DNA methylation are critical for gene regulation, but how these vary across the human body remains unclear. We performed multi-omic profiling of 3D genome structure and DNA methylation for 86,689 single nuclei across 16 human tissues, identifying 35 major and 206 cell subtypes. We revealed extensive changes in CG and non-CG methylation across almost all cell types and characterized 3D chromatin structure at an unprecedented cellular resolution. Intriguingly, extensive discrepancies exist between cell types delineated by DNA methylation and genome structure, indicating that the role of distinct epigenomic features in maintaining cell identity may vary by lineage. This study expands our understanding of the diversity of DNA methylation and chromatin structure and offers an extensive reference for exploring gene regulation in human health and disease.
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Affiliation(s)
- Jingtian Zhou
- Arc Institute, Palo Alto, CA, USA
- Genomic Analysis Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA
| | - Yue Wu
- Genomic Analysis Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
- Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
- Society of Fellows, Harvard University, Cambridge, MA, USA
| | - Wei Tian
- Genomic Analysis Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Rosa G Castanon
- Genomic Analysis Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Anna Bartlett
- Genomic Analysis Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Zuolong Zhang
- School of Software, Henan University, Kaifeng, Henan, China
| | - Guocong Yao
- School of Computer and Information Engineering, Henan University, Kaifeng, Henan, China
| | - Dengxiaoyu Shi
- Genomic Analysis Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Ben Clock
- Gene Expression Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Samantha Marcotte
- Gene Expression Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Joseph R. Nery
- Genomic Analysis Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Michelle Liem
- Flow Cytometry Core Facility, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Naomi Claffey
- Flow Cytometry Core Facility, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Lara Boggeman
- Flow Cytometry Core Facility, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Cesar Barragan
- Genomic Analysis Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Rafael Arrojo e Drigo
- Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN
- Center for Computational Systems Biology, Vanderbilt University, Nashville, TN
- Diabetes Research and Training Center (DRTC), Vanderbilt University Medical Center, Nashville, TN, 37235
| | - Annika K. Weimer
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
- Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Minyi Shi
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
| | - Johnathan Cooper-Knock
- Sheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield, UK
| | - Sai Zhang
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
- Department of Epidemiology, University of Florida, Gainesville, FL, USA
- Departments of Biostatistics & Biomedical Engineering, Genetics Institute, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
| | - Michael P. Snyder
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
| | - Sebastian Preissl
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
- Institute of Experimental and Clinical Pharmacology and Toxicology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- Institute of Pharmaceutical Sciences, Pharmacology & Toxicology, University of Graz, Graz, Austria
- Field of Excellence BioHealth, University of Graz, Graz, Austria
| | - Bing Ren
- Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Carolyn O’Connor
- Flow Cytometry Core Facility, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Shengbo Chen
- School of Software, Nanchang University, Nanchang, Jiangxi, China
| | - Chongyuan Luo
- Department of Human Genetics, University of California Los Angeles, Los Angeles, CA, USA
| | - Jesse R. Dixon
- Gene Expression Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Joseph R. Ecker
- Genomic Analysis Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
- Howard Hughes Medical Institute, Salk Institute for Biological Studies, La Jolla, CA, USA
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12
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Gao R, Ferraro TN, Chen L, Zhang S, Chen Y. Enhancing Single-Cell and Bulk Hi-C Data Using a Generative Transformer Model. BIOLOGY 2025; 14:288. [PMID: 40136544 PMCID: PMC11940666 DOI: 10.3390/biology14030288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2025] [Revised: 03/01/2025] [Accepted: 03/10/2025] [Indexed: 03/27/2025]
Abstract
The 3D organization of chromatin in the nucleus plays a critical role in regulating gene expression and maintaining cellular functions in eukaryotic cells. High-throughput chromosome conformation capture (Hi-C) and its derivative technologies have been developed to map genome-wide chromatin interactions at the population and single-cell levels. However, insufficient sequencing depth and high noise levels in bulk Hi-C data, particularly in single-cell Hi-C (scHi-C) data, result in low-resolution contact matrices, thereby limiting diverse downstream computational analyses in identifying complex chromosomal organizations. To address these challenges, we developed a transformer-based deep learning model, HiCENT, to impute and enhance both scHi-C and Hi-C contact matrices. Validation experiments on large-scale bulk Hi-C and scHi-C datasets demonstrated that HiCENT achieves superior enhancement effects compared to five popular methods. When applied to real Hi-C data from the GM12878 cell line, HiCENT effectively enhanced 3D structural features at the scales of topologically associated domains and chromosomal loops. Furthermore, when applied to scHi-C data from five human cell lines, it significantly improved clustering performance, outperforming five widely used methods. The adaptability of HiCENT across different datasets and its capacity to improve the quality of chromatin interaction data will facilitate diverse downstream computational analyses in 3D genome research, single-cell studies and other large-scale omics investigations.
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Affiliation(s)
- Ruoying Gao
- College of Computer and Information Engineering, Tianjin Normal University, Tianjin 300387, China; (R.G.); (L.C.)
| | - Thomas N. Ferraro
- Department of Biomedical Sciences, Cooper Medical School of Rowan University, Camden, NJ 08103, USA;
| | - Liang Chen
- College of Computer and Information Engineering, Tianjin Normal University, Tianjin 300387, China; (R.G.); (L.C.)
| | - Shaoqiang Zhang
- College of Computer and Information Engineering, Tianjin Normal University, Tianjin 300387, China; (R.G.); (L.C.)
| | - Yong Chen
- Department of Biological and Biomedical Sciences, Rowan University, Glassboro, NJ 08028, USA
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13
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Dougherty JD, Sarafinovska S, Chaturvedi SM, Law TE, Akinwe TM, Gabel HW. Single-cell technology grows up: Leveraging high-resolution omics approaches to understand neurodevelopmental disorders. Curr Opin Neurobiol 2025; 92:102990. [PMID: 40036988 DOI: 10.1016/j.conb.2025.102990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2024] [Revised: 01/30/2025] [Accepted: 02/05/2025] [Indexed: 03/06/2025]
Abstract
The identification of hundreds of neurodevelopmental disorder (NDD) genes in the last decade led to numerous genetic models for understanding NDD gene mutation consequences and delineating putative neurobiological mediators of disease. In parallel, single-cell and single-nucleus genomic technologies have been developed and implemented to create high-resolution atlases of cell composition, gene expression, and circuit connectivity in the brain. Here, we discuss the opportunities to leverage mutant models (or human tissue, where available) and genomics approaches to systematically define NDD etiology at cellular resolution. We review progress in applying single-cell and spatial transcriptomics to interrogate developmental trajectories, cellular composition, circuit activity, and connectivity across human tissue and NDD models. We discuss considerations for implementing these approaches at scale to maximize insights and facilitate reproducibility. Finally, we highlight how standardized application of these technologies promises to not only define etiologies of individual disorders but also identify molecular, cellular, and circuit level convergence across NDDs.
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Affiliation(s)
- Joseph D Dougherty
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA; Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA; Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, Saint Louis, MO, USA.
| | - Simona Sarafinovska
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA; Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA; Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Sneha M Chaturvedi
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA; Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA; Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Travis E Law
- Department of Neuroscience, Washington University School of Medicine, Saint Louis, MO, USA; Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, Saint Louis, MO, USA
| | - Titilope M Akinwe
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA; Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Harrison W Gabel
- Department of Neuroscience, Washington University School of Medicine, Saint Louis, MO, USA; Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, Saint Louis, MO, USA
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14
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Liu Z, Gu A, Bao Y, Lin GN. Epigenetic Impacts of Non-Coding Mutations Deciphered Through Pre-Trained DNA Language Model at Single-Cell Resolution. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025; 12:e2413571. [PMID: 39888214 PMCID: PMC11924033 DOI: 10.1002/advs.202413571] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/24/2024] [Revised: 01/20/2025] [Indexed: 02/01/2025]
Abstract
DNA methylation plays a critical role in gene regulation, affecting cellular differentiation and disease progression, particularly in non-coding regions. However, predicting the epigenetic consequences of non-coding mutations at single-cell resolution remains a challenge. Existing tools have limited prediction capacity and struggle to capture dynamic, cell-type-specific regulatory changes that are crucial for understanding disease mechanisms. Here, Methven, a deep learning framework designed is presented to predict the effects of non-coding mutations on DNA methylation at single-cell resolution. Methven integrates DNA sequence with single-cell ATAC-seq data and models SNP-CpG interactions over 100 kbp genomic distances. By using a divide-and-conquer approach, Methven accurately predicts both short- and long-range regulatory interactions and leverages the pre-trained DNA language model for enhanced precision in classification and regression tasks. Methven outperforms existing methods and demonstrates robust generalizability to monocyte datasets. Importantly, it identifies CpG sites associated with rheumatoid arthritis, revealing key pathways involved in immune regulation and disease progression. Methven's ability to detect progressive epigenetic changes provides crucial insights into gene regulation in complex diseases. These findings demonstrate Methven's potential as a powerful tool for basic research and clinical applications, advancing this understanding of non-coding mutations and their role in disease, while offering new opportunities for personalized medicine.
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Affiliation(s)
- Zhe Liu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200230China
| | - An Gu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200230China
| | - Yihang Bao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200230China
| | - Guan Ning Lin
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, School of Biomedical EngineeringShanghai Jiao Tong UniversityShanghai200230China
- Shanghai Key Laboratory of Psychotic DisordersShanghai200230China
- Engineering Research Center of Digital Medicine of the Ministry of EducationShanghai200230China
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15
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Sun W, Hewitt SM, Wright H, Keller C, Barr FG. DNA methylation patterns are influenced by Pax3::Foxo1 expression and developmental lineage in rhabdomyosarcoma tumours forming in genetically engineered mouse models. J Pathol 2025; 265:316-329. [PMID: 39812007 PMCID: PMC11794984 DOI: 10.1002/path.6386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Revised: 10/21/2024] [Accepted: 11/28/2024] [Indexed: 01/16/2025]
Abstract
Rhabdomyosarcoma (RMS) is a family of phenotypically myogenic paediatric cancers consisting of two major subtypes: fusion-positive (FP) RMS, most commonly involving the PAX3::FOXO1 fusion gene, formed by the fusion of paired box 3 (PAX3) and forkhead box O1 (FOXO1) genes, and fusion-negative (FN) RMS, lacking these gene fusions. In humans, DNA methylation patterns distinguish these two subtypes as well as mutation-associated subsets within these subtypes. To investigate the biological factors responsible for these methylation differences, we profiled DNA methylation in RMS tumours derived from genetically engineered mouse models (GEMMs) in which various driver mutations were introduced into different myogenic lineages. Our unsupervised analyses of DNA methylation patterns in these GEMM tumours yielded two major clusters, corresponding to high and no/low expression of Pax3::Foxo1, which mirrored the results for human FP and FN RMS tumours. Two distinct methylation-defined subsets were found for GEMM RMS tumours with no/low Pax3::Foxo1 expression: one subset enriched in Pax7 lineage tumours and a second subset enriched in myogenic factor 5 (Myf5) lineage tumours. Integrative analysis of DNA methylation and transcriptomic data in mouse and human RMS revealed a common group of differentially methylated and differentially expressed genes, highlighting a conserved set of genes functioning in both human RMS models and GEMMs of RMS. In conclusion, these studies provide insight into the roles of oncogenic fusion proteins and developmental lineages in establishing DNA methylation patterns in FP and FN RMS respectively. © 2025 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.
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Affiliation(s)
- Wenyue Sun
- Laboratory of Pathology, Center for Cancer ResearchNCIBethesdaMDUSA
| | - Stephen M Hewitt
- Laboratory of Pathology, Center for Cancer ResearchNCIBethesdaMDUSA
| | - Hollis Wright
- Children's Cancer Therapy Development InstituteHillsboroORUSA
| | - Charles Keller
- Children's Cancer Therapy Development InstituteHillsboroORUSA
| | - Frederic G Barr
- Laboratory of Pathology, Center for Cancer ResearchNCIBethesdaMDUSA
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16
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O'Dea MR, Hasel P. Are we there yet? Exploring astrocyte heterogeneity one cell at a time. Glia 2025; 73:619-631. [PMID: 39308429 PMCID: PMC11784854 DOI: 10.1002/glia.24621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 09/02/2024] [Accepted: 09/14/2024] [Indexed: 02/01/2025]
Abstract
Astrocytes are a highly abundant cell type in the brain and spinal cord. Like neurons, astrocytes can be molecularly and functionally distinct to fulfill specialized roles. Recent technical advances in sequencing-based single cell assays have driven an explosion of omics data characterizing astrocytes in the healthy, aged, injured, and diseased central nervous system. In this review, we will discuss recent studies which have furthered our understanding of astrocyte biology and heterogeneity, as well as discuss the limitations and challenges of sequencing-based single cell and spatial genomics methods and their potential future utility.
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Affiliation(s)
- Michael R. O'Dea
- Neuroscience InstituteNYU Grossman School of MedicineNew YorkNew YorkUSA
| | - Philip Hasel
- UK Dementia Research Institute at the University of EdinburghEdinburghScotlandUK
- Centre for Discovery Brain Sciences, School of Biomedical Sciences, College of Medicine and Veterinary MedicineThe University of EdinburghEdinburghScotlandUK
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17
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Liu S, Wang CY, Zheng P, Jia BB, Zemke NR, Ren P, Park HL, Ren B, Zhuang X. Cell type-specific 3D-genome organization and transcription regulation in the brain. SCIENCE ADVANCES 2025; 11:eadv2067. [PMID: 40009678 PMCID: PMC11864200 DOI: 10.1126/sciadv.adv2067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/11/2024] [Accepted: 01/23/2025] [Indexed: 02/28/2025]
Abstract
3D organization of the genome plays a critical role in regulating gene expression. How 3D-genome organization differs among different cell types and relates to cell type-dependent transcriptional regulation remains unclear. Here, we used genome-scale DNA and RNA imaging to investigate 3D-genome organization in transcriptionally distinct cell types in the mouse cerebral cortex. We uncovered a wide spectrum of differences in the nuclear architecture and 3D-genome organization among different cell types, ranging from the size of the cell nucleus to higher-order chromosome structures and radial positioning of chromatin loci within the nucleus. These cell type-dependent variations in nuclear architecture and chromatin organization exhibit strong correlations with both the total transcriptional activity of the cell and transcriptional regulation of cell type-specific marker genes. Moreover, we found that the methylated DNA binding protein MeCP2 promotes active-inactive chromatin segregation and regulates transcription in a nuclear radial position-dependent manner that is highly correlated with its function in modulating active-inactive chromatin compartmentalization.
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Affiliation(s)
- Shiwei Liu
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
| | - Cosmos Yuqi Wang
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
| | - Pu Zheng
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
- Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA
| | - Bojing Blair Jia
- Bioinformatics and Systems Biology Graduate Program, Medical Scientist Training Program, University of California San Diego, La Jolla, CA, USA
| | - Nathan R. Zemke
- Department of Cellular and Molecular Medicine and Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Peter Ren
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
- Graduate Program in Biophysics, Harvard University, Cambridge, MA, USA
| | - Hannah L. Park
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine and Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Xiaowei Zhuang
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, Harvard University, Cambridge, MA, USA
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18
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Goldberg DC, Cloud C, Lee SM, Barnes B, Gruber S, Kim E, Pottekat A, Westphal MS, McAuliffe L, Majounie E, KalayilManian M, Zhu Q, Tran C, Hansen M, Stojakovic J, Parker JB, Kohli RM, Porecha R, Renke N, Zhou W. Scalable Screening of Ternary-Code DNA Methylation Dynamics Associated with Human Traits. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.05.17.594606. [PMID: 38826316 PMCID: PMC11142114 DOI: 10.1101/2024.05.17.594606] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Epigenome-wide association studies (EWAS) are transforming our understanding of the interplay between epigenetics and complex human traits and phenotypes. We introduce the Methylation Screening Array (MSA), a new iteration of the Infinium technology for scalable and quantitative screening of trait associations of nuanced ternary-code cytosine modifications in larger, more inclusive, and stratified human populations. MSA integrates EWAS, single-cell, and cell-type-resolved methylome profiles, covering diverse human traits and diseases. Our first MSA applications yield multiple biological insights: we revealed a previously unappreciated role of 5-hydroxymethylcytosine (5hmC) in trait associations and epigenetic clocks. We demonstrated that 5hmCs complement 5-methylcytosines (5mCs) in defining tissues and cells' epigenetic identities. In-depth analyses highlighted the cell type context of EWAS and GWAS hits. Using this platform, we conducted a comprehensive human 5hmC aging EWAS, discovering tissue-invariant and tissue-specific aging dynamics, including distinct tissue-specific rates of mitotic hyper- and hypomethylation rates. These findings chart a landscape of the complex interplay of the two forms of cytosine modifications in diverse human tissues and their roles in health and disease.
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Affiliation(s)
- David C Goldberg
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
| | - Cameron Cloud
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
| | - Sol Moe Lee
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
| | | | | | - Elliot Kim
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
| | | | | | | | | | | | | | | | | | | | - Jared B Parker
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Rahul M Kohli
- Department of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | | | | | - Wanding Zhou
- Center for Computational and Genomic Medicine, The Children’s Hospital of Philadelphia, PA, 19104, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
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19
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Yan M, Zhang XM, Yang Z, Jia M, Liao R, Li J. Visualization of chromosomal reorganization induced by heterologous fusions in the mammalian nucleus. Nat Commun 2025; 16:1485. [PMID: 39929797 PMCID: PMC11811026 DOI: 10.1038/s41467-024-55582-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2024] [Accepted: 12/09/2024] [Indexed: 02/13/2025] Open
Abstract
Chromosomes are spatially organized and functionally folded into a specific macro-structure in the nucleus. Recently, we and others created haploid cells with chromosome fusions. However, there is still lack of an effective strategy for precisely investigating how the genome copes with fusions. Here, we developed a down-sampling method to convert the populational Hi-C dataset into single cell-like Khimaira Matrix (K-matrix). K-matrix preserves not only the most prominent functional genomic features but also cell-to-cell variations. K-matrix-originated genome 3D models display spatial approach of fused chromosomes and minor global structure alterations. Combined with a layered positional decomposition analysis, our models indicate slight re-adjustment of chromosome distributions accordingly with an increasing tendency following more fusions involved. Nevertheless, the radial distribution of the A/B compartment is not affected dramatically. By contrast, natural populations harboring Rb fusions display significant alterations of chromosome radial location. Overall, K-matrix-originated models enable visualization of chromosomal reorganization with high resolution.
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Affiliation(s)
- Meng Yan
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, Zhejiang, China.
- Key Laboratory of Multi-Cell Systems, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, CAS Center for Excellence in Molecular Cell Science, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
| | - Xiaoyu Merlin Zhang
- Key Laboratory of Multi-Cell Systems, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, CAS Center for Excellence in Molecular Cell Science, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Zhenhua Yang
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China
| | - Miao Jia
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, Zhejiang, China
| | - Rongyu Liao
- Key Laboratory of Multi-Cell Systems, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, CAS Center for Excellence in Molecular Cell Science, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Jinsong Li
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, Zhejiang, China.
- Key Laboratory of Multi-Cell Systems, Shanghai Key Laboratory of Molecular Andrology, Shanghai Institute of Biochemistry and Cell Biology, CAS Center for Excellence in Molecular Cell Science, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
- School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
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20
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Zhou H, Clark E, Guan D, Lagarrigue S, Fang L, Cheng H, Tuggle CK, Kapoor M, Wang Y, Giuffra E, Egidy G. Comparative Genomics and Epigenomics of Transcriptional Regulation. Annu Rev Anim Biosci 2025; 13:73-98. [PMID: 39565835 DOI: 10.1146/annurev-animal-111523-102217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2024]
Abstract
Transcriptional regulation in response to diverse physiological cues involves complicated biological processes. Recent initiatives that leverage whole genome sequencing and annotation of regulatory elements significantly contribute to our understanding of transcriptional gene regulation. Advances in the data sets available for comparative genomics and epigenomics can identify evolutionarily constrained regulatory variants and shed light on noncoding elements that influence transcription in different tissues and developmental stages across species. Most epigenomic data, however, are generated from healthy subjects at specific developmental stages. To bridge the genotype-phenotype gap, future research should focus on generating multidimensional epigenomic data under diverse physiological conditions. Farm animal species offer advantages in terms of feasibility, cost, and experimental design for such integrative analyses in comparison to humans. Deep learning modeling and cutting-edge technologies in sequencing and functional screening and validation also provide great promise for better understanding transcriptional regulation in this dynamic field.
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Affiliation(s)
- Huaijun Zhou
- Department of Animal Science, University of California, Davis, California, USA; , , ,
| | - Emily Clark
- The Roslin Institute, University of Edinburgh, Edinburgh, Midlothian, United Kingdom;
| | - Dailu Guan
- Department of Animal Science, University of California, Davis, California, USA; , , ,
| | | | - Lingzhao Fang
- Center for Quantitative Genetics and Genomics, Aarhus University, Aarhus, Denmark;
| | - Hao Cheng
- Department of Animal Science, University of California, Davis, California, USA; , , ,
| | | | - Muskan Kapoor
- Department of Animal Science, Iowa State University, Ames, Iowa, USA; ,
| | - Ying Wang
- Department of Animal Science, University of California, Davis, California, USA; , , ,
| | | | - Giorgia Egidy
- GABI, AgroParisTech, INRAE, Jouy-en-Josas, France; ,
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21
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Wu H, Wang M, Zheng Y, Xie XS. Droplet-based high-throughput 3D genome structure mapping of single cells with simultaneous transcriptomics. Cell Discov 2025; 11:8. [PMID: 39837831 PMCID: PMC11751028 DOI: 10.1038/s41421-025-00770-8] [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: 11/20/2024] [Accepted: 12/30/2024] [Indexed: 01/23/2025] Open
Abstract
Single-cell three-dimensional (3D) genome techniques have advanced our understanding of cell-type-specific chromatin structures in complex tissues, yet current methodologies are limited in cell throughput. Here we introduce a high-throughput single-cell Hi-C (dscHi-C) approach and its transcriptome co-assay (dscHi-C-multiome) using droplet microfluidics. Using dscHi-C, we investigate chromatin structural changes during mouse brain aging by profiling 32,777 single cells across three developmental stages (3 months, 12 months, and 23 months), yielding a median of 78,220 unique contacts. Our results show that genes with significant structural changes are enriched in pathways related to metabolic process and morphology change in neurons, and innate immune response in glial cells, highlighting the role of 3D genome organization in physiological brain aging. Furthermore, our multi-omics joint assay, dscHi-C-multiome, enables precise cell type identification in the adult mouse brain and uncovers the intricate relationship between genome architecture and gene expression. Collectively, we developed the sensitive, high-throughput dscHi-C and its multi-omics derivative, dscHi-C-multiome, demonstrating their potential for large-scale cell atlas studies in development and disease.
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Affiliation(s)
- Honggui Wu
- Biomedical Pioneering Innovation Center (BIOPIC), and School of Life Sciences, Peking University, Beijing, China
- Changping Laboratory, Beijing, China
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Maoxu Wang
- Biomedical Pioneering Innovation Center (BIOPIC), and School of Life Sciences, Peking University, Beijing, China
- Changping Laboratory, Beijing, China
| | - Yinghui Zheng
- Biomedical Pioneering Innovation Center (BIOPIC), and School of Life Sciences, Peking University, Beijing, China
- Changping Laboratory, Beijing, China
| | - X Sunney Xie
- Biomedical Pioneering Innovation Center (BIOPIC), and School of Life Sciences, Peking University, Beijing, China.
- Changping Laboratory, Beijing, China.
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22
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Nichols RV, Rylaarsdam LE, O'Connell BL, Shipony Z, Iremadze N, Acharya SN, Adey AC. Atlas-scale single-cell DNA methylation profiling with sciMETv3. CELL GENOMICS 2025; 5:100726. [PMID: 39719707 PMCID: PMC11770211 DOI: 10.1016/j.xgen.2024.100726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/03/2024] [Revised: 10/25/2024] [Accepted: 11/26/2024] [Indexed: 12/26/2024]
Abstract
Single-cell methods to assess DNA methylation have not achieved the same level of cell throughput per experiment compared to other modalities, with large-scale datasets requiring extensive automation, time, and other resources. Here, we describe sciMETv3, a combinatorial indexing-based technique that enables atlas-scale libraries to be produced in a single experiment. To reduce the sequencing burden, we demonstrate the compatibility of sciMETv3 with capture techniques to enrich regulatory regions, as well as the ability to leverage enzymatic conversion, which can yield higher library diversity. We showcase the throughput of sciMETv3 by producing a >140,000 cell library from human middle frontal gyrus split across four multiplexed individuals using both Illumina and Ultima sequencing instrumentation. Finally, we introduce sciMET+ATAC to enable high-throughput exploration of the interplay between chromatin accessibility and DNA methylation within the same cell.
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Affiliation(s)
- Ruth V Nichols
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA
| | - Lauren E Rylaarsdam
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA
| | - Brendan L O'Connell
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA; Cancer Early Detection Advanced Research Institute, Oregon Health & Science University, Portland, OR, USA
| | | | | | - Sonia N Acharya
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA
| | - Andrew C Adey
- Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA; Cancer Early Detection Advanced Research Institute, Oregon Health & Science University, Portland, OR, USA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland, OR, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA.
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23
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Mori FK, Shimosawa T. The Fetal Environment and the Development of Hypertension-The Epigenetic Modification by Glucocorticoids. Int J Mol Sci 2025; 26:420. [PMID: 39796274 PMCID: PMC11720225 DOI: 10.3390/ijms26010420] [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: 11/23/2024] [Revised: 12/18/2024] [Accepted: 01/02/2025] [Indexed: 01/13/2025] Open
Abstract
Intrauterine growth restriction (IUGR) is a risk factor for postnatal cardiovascular, metabolic, and psychiatric disorders. In most IUGR models, placental dysfunction that causes reduced 11β-hydroxysteroid dehydrogenase 2 (11βHSD2) activity, which degrades glucocorticoids (GCs) in the placenta, resulting in fetal GC overexposure. This overexposure to GCs continues to affect not only intrauterine fetal development itself, but also the metabolic status and neural activity in adulthood through epigenetic changes such as microRNA change, histone modification, and DNA methylation. We have shown that the IUGR model induced DNA hypomethylation in the paraventricular nucleus (PVN) in the brain, which in turn activates sympathetic activities, the renin-angiotensin system (RAS), contributing to the development of salt-sensitive hypertension. Even in adulthood, strong stress and/or exogenous steroids have been shown to induce epigenetic changes in the brain. Furthermore, DNA hypomethylation in the PVN is also observed in other hypertensive rat models, which suggests that it contributes significantly to the origins of elevated blood pressure. These findings suggest that if we can alter epigenetic changes in the brain, we can treat or prevent hypertension.
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Affiliation(s)
| | - Tatsuo Shimosawa
- Department of Clinical Laboratory, School of Medicine, International University of Health and Welfare, Otawara 324-8501, Japan;
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24
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Westphal M, Drexler R, Maire C, Ricklefs F, Lamszus K. Cancer neuroscience and glioma: clinical implications. Acta Neurochir (Wien) 2025; 167:2. [PMID: 39752006 PMCID: PMC11698767 DOI: 10.1007/s00701-024-06406-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2024] [Accepted: 12/19/2024] [Indexed: 01/04/2025]
Abstract
In recent years, it has been increasingly recognized that tumor growth relies not only on support from the surrounding microenvironment but also on the tumors capacity to adapt to - and actively manipulate - its niche. While targeting angiogenesis and modulating the local immune environment have been explored as therapeutic approaches, these strategies have yet to yield effective treatments for brain tumors and remain under refinement. More recently, the nervous system itself has been explored as a critical environmental support for cancer, with extensive neuro-tumoral interactions observed both intracranially and in extracranial sites containing neural components. In the brain, interactions between glioma cells as well as metastatic lesions with neural components have clinical implications for diagnostics, risk assessments, neurological sequelae, and the development of innovative therapeutics. Here, we review these neuro-tumoral dynamics, emphasizing aspects relevant to neurosurgical practice.
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Affiliation(s)
- Manfred Westphal
- Institute for Tumorbiology, University Hospital Hamburg Eppendorf, W29 - R34, Hamburg, 20246, Germany.
| | - Richard Drexler
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Cecile Maire
- Department of Neurosurgery, University Hospital Eppendorf, Hamburg, Germany
| | - Franz Ricklefs
- Department of Neurosurgery, University Hospital Eppendorf, Hamburg, Germany
| | - Katrin Lamszus
- Department of Neurosurgery, University Hospital Eppendorf, Hamburg, Germany
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25
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Weymouth L, Smith AR, Lunnon K. DNA Methylation in Alzheimer's Disease. Curr Top Behav Neurosci 2025; 69:149-178. [PMID: 39455499 DOI: 10.1007/7854_2024_530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2024]
Abstract
To date, DNA methylation is the best characterized epigenetic modification in Alzheimer's disease. Involving the addition of a methyl group to the fifth carbon of the cytosine pyrimidine base, DNA methylation is generally thought to be associated with the silencing of gene expression. It has been hypothesized that epigenetics may mediate the interaction between genes and the environment in the manifestation of Alzheimer's disease, and therefore studies investigating DNA methylation could elucidate novel disease mechanisms. This chapter comprehensively reviews epigenomic studies, undertaken in human brain tissue and purified brain cell types, focusing on global methylation levels, candidate genes, epigenome wide approaches, and recent meta-analyses. We discuss key differentially methylated genes and pathways that have been highlighted to date, with a discussion on how new technologies and the integration of multiomic data may further advance the field.
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Affiliation(s)
- Luke Weymouth
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Adam R Smith
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Katie Lunnon
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
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26
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Ma J, Qi R, Wang J, Berto S, Wang GZ. Human-unique brain cell clusters are associated with learning disorders and human episodic memory activity. Mol Psychiatry 2025; 30:353-359. [PMID: 39227435 DOI: 10.1038/s41380-024-02722-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 08/16/2024] [Accepted: 08/22/2024] [Indexed: 09/05/2024]
Abstract
The advanced evolution of the human cerebral cortex forms the basis for our high-level cognitive functions. Through a comparative analysis of single-nucleus transcriptome data from the human neocortex and that of chimpanzees, macaques, and marmosets, we discovered 20 subgroups of cell types unique to the human brain, which include 11 types of excitatory neurons. Many of these human-unique cell clusters exhibit significant overexpression of genes regulated by human-specific enhancers. Notably, these specific cell clusters also express genes associated with disease risk, particularly those related to brain dysfunctions like learning disorders. Furthermore, genes linked to cortical thickness and human episodic memory encoding activities show heightened expression within these cell subgroups. These findings underscore the critical role of human brain-unique cell clusters in the evolution of human brain functions.
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Affiliation(s)
- Junjie Ma
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Ruicheng Qi
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jing Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Stefano Berto
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, 29425, USA
| | - Guang-Zhong Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
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27
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Davie JR, Sattarifard H, Sudhakar SRN, Roberts CT, Beacon TH, Muker I, Shahib AK, Rastegar M. Basic Epigenetic Mechanisms. Subcell Biochem 2025; 108:1-49. [PMID: 39820859 DOI: 10.1007/978-3-031-75980-2_1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2025]
Abstract
The human genome consists of 23 chromosome pairs (22 autosomes and one pair of sex chromosomes), with 46 chromosomes in a normal cell. In the interphase nucleus, the 2 m long nuclear DNA is assembled with proteins forming chromatin. The typical mammalian cell nucleus has a diameter between 5 and 15 μm in which the DNA is packaged into an assortment of chromatin assemblies. The human brain has over 3000 cell types, including neurons, glial cells, oligodendrocytes, microglial, and many others. Epigenetic processes are involved in directing the organization and function of the genome of each one of the 3000 brain cell types. We refer to epigenetics as the study of changes in gene function that do not involve changes in DNA sequence. These epigenetic processes include histone modifications, DNA modifications, nuclear RNA, and transcription factors. In the interphase nucleus, the nuclear DNA is organized into different structures that are permissive or a hindrance to gene expression. In this chapter, we will review the epigenetic mechanisms that give rise to cell type-specific gene expression patterns.
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Affiliation(s)
- James R Davie
- Department of Biochemistry and Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.
| | - Hedieh Sattarifard
- Department of Biochemistry and Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Sadhana R N Sudhakar
- Department of Biochemistry and Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Chris-Tiann Roberts
- Department of Biochemistry and Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Tasnim H Beacon
- Department of Biochemistry and Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Ishdeep Muker
- Department of Biochemistry and Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Ashraf K Shahib
- Department of Biochemistry and Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
| | - Mojgan Rastegar
- Department of Biochemistry and Medical Genetics, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
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28
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Twa GM, Phillips RA, Robinson NJ, Day JJ. Accurate sample deconvolution of pooled snRNA-seq using sex-dependent gene expression patterns. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.11.29.626066. [PMID: 39677603 PMCID: PMC11642824 DOI: 10.1101/2024.11.29.626066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/17/2024]
Abstract
Single nucleus RNA sequencing (snRNA-seq) technology offers unprecedented resolution for studying cell type-specific gene expression patterns. However, snRNA-seq poses high costs and technical limitations, often requiring the pooling of independent biological samples and loss of individual sample-level data. Deconvolution of sample identity using inherent features would enable the incorporation of pooled barcoding and sequencing protocols, thereby increasing data throughput and analytical sample size without requiring increases in experimental sample size and sequencing costs. In this study, we demonstrate a proof of concept that sex-dependent gene expression patterns can be leveraged for the deconvolution of pooled snRNA-seq data. Using previously published snRNA-seq data from the rat ventral tegmental area, we trained a range of machine learning models to classify cell sex using genes differentially expressed in cells from male and female rats. Models that used sex-dependent gene expression predicted cell sex with high accuracy (90-92%) and outperformed simple classification models using only sex chromosome gene expression (69-89%). The generalizability of these models to other brain regions was assessed using an additional published data set from the rat nucleus accumbens. Within this data set, model performance remained highly accurate in cell sex classification (89-90% accuracy) with no additional re-training. This work provides a model for future snRNA-seq studies to perform sample deconvolution using a two-sex pooled sample sequencing design and benchmarks the performance of various machine learning approaches to deconvolve sample identification from inherent sample features.
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Affiliation(s)
- Guy M. Twa
- Department of Neurobiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Robert A. Phillips
- Department of Neurobiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
- Present affiliation: Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD 21205, USA
| | - Nathaniel J. Robinson
- Department of Neurobiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Jeremy J. Day
- Department of Neurobiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA
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29
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Pressl C, Baffuto M, Darnell P, Wang C, Carroll TS, Heintz N, Mätlik K. Isolation and Molecular Profiling of Nuclei of Specific Neuronal Types from Human Cerebral Cortex and Striatum. Curr Protoc 2024; 4:e70067. [PMID: 39651942 PMCID: PMC11627125 DOI: 10.1002/cpz1.70067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2024]
Abstract
Most pathological conditions of the central nervous system do not affect all cell types to the same extent. Delineation of molecular events underlying disease symptoms, including genetic, epigenetic, and transcriptional changes, thus relies on the ability to characterize a specific cell type separately from others. We have developed a methodology for the collection of nuclear RNA and genomic DNA of specific cell types from frozen post-mortem striatum and cerebral cortex. This allows deep transcriptomic profiling of specific cell populations and characterization of their genomes and epigenetic properties. The method is based on the purification of cell nuclei, followed by fluorescence-activated sorting of nuclei (FANS) labeled with nucleic acid probes or antibodies binding to targets present in specific cell types. The protocol describes in detail the procedure for isolating and labeling neuronal and glial nuclei from human brain tissue, the steps that can be taken to extract RNA and genomic DNA, a way to combine the procedure with ATAC-seq to yield information about chromatin accessibility, as well as computational measures for assessing the quality of cell type-specific RNA-seq and ATAC-seq datasets. © 2024 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Tissue homogenization, isolation of cell nuclei by ultracentrifugation and formaldehyde-fixation Basic Protocol 2: Antibody-based labeling and isolation of nuclei of specific neocortical neuron types Support Protocol 1: Generation of ATAC-seq libraries from the nuclei of specific neuron types of the cerebral cortex Basic Protocol 3: Nucleic acid hybridization-based labeling and isolation of nuclei of specific striatal projection neuron types Alternate Protocol 1: Labeling and isolation of nuclei of specific striatal interneuron types Support Protocol 2: Generation of ATAC-seq libraries from the nuclei of specific striatal neuron types Basic Protocol 4: Extraction of genomic DNA and nuclear RNA and preparation of sequencing libraries Basic Protocol 5: Processing and quality control of FANS-seq and ATAC-seq data.
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Affiliation(s)
- Christina Pressl
- Laboratory of Molecular BiologyThe Rockefeller UniversityNew YorkNew YorkUSA
| | - Matthew Baffuto
- Laboratory of Molecular BiologyThe Rockefeller UniversityNew YorkNew YorkUSA
| | - Paul Darnell
- Laboratory of Molecular BiologyThe Rockefeller UniversityNew YorkNew YorkUSA
| | - Cuidong Wang
- Laboratory of Molecular BiologyThe Rockefeller UniversityNew YorkNew YorkUSA
| | - Thomas S. Carroll
- Bioinformatics Resource CenterThe Rockefeller UniversityNew YorkNew YorkUSA
| | - Nathaniel Heintz
- Laboratory of Molecular BiologyThe Rockefeller UniversityNew YorkNew YorkUSA
| | - Kert Mätlik
- Laboratory of Molecular BiologyThe Rockefeller UniversityNew YorkNew YorkUSA
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Gabitto MI, Travaglini KJ, Rachleff VM, Kaplan ES, Long B, Ariza J, Ding Y, Mahoney JT, Dee N, Goldy J, Melief EJ, Agrawal A, Kana O, Zhen X, Barlow ST, Brouner K, Campos J, Campos J, Carr AJ, Casper T, Chakrabarty R, Clark M, Cool J, Dalley R, Darvas M, Ding SL, Dolbeare T, Egdorf T, Esposito L, Ferrer R, Fleckenstein LE, Gala R, Gary A, Gelfand E, Gloe J, Guilford N, Guzman J, Hirschstein D, Ho W, Hupp M, Jarsky T, Johansen N, Kalmbach BE, Keene LM, Khawand S, Kilgore MD, Kirkland A, Kunst M, Lee BR, Leytze M, Mac Donald CL, Malone J, Maltzer Z, Martin N, McCue R, McMillen D, Mena G, Meyerdierks E, Meyers KP, Mollenkopf T, Montine M, Nolan AL, Nyhus JK, Olsen PA, Pacleb M, Pagan CM, Peña N, Pham T, Pom CA, Postupna N, Rimorin C, Ruiz A, Saldi GA, Schantz AM, Shapovalova NV, Sorensen SA, Staats B, Sullivan M, Sunkin SM, Thompson C, Tieu M, Ting JT, Torkelson A, Tran T, Valera Cuevas NJ, Walling-Bell S, Wang MQ, Waters J, Wilson AM, Xiao M, Haynor D, Gatto NM, Jayadev S, Mufti S, Ng L, Mukherjee S, Crane PK, Latimer CS, Levi BP, Smith KA, et alGabitto MI, Travaglini KJ, Rachleff VM, Kaplan ES, Long B, Ariza J, Ding Y, Mahoney JT, Dee N, Goldy J, Melief EJ, Agrawal A, Kana O, Zhen X, Barlow ST, Brouner K, Campos J, Campos J, Carr AJ, Casper T, Chakrabarty R, Clark M, Cool J, Dalley R, Darvas M, Ding SL, Dolbeare T, Egdorf T, Esposito L, Ferrer R, Fleckenstein LE, Gala R, Gary A, Gelfand E, Gloe J, Guilford N, Guzman J, Hirschstein D, Ho W, Hupp M, Jarsky T, Johansen N, Kalmbach BE, Keene LM, Khawand S, Kilgore MD, Kirkland A, Kunst M, Lee BR, Leytze M, Mac Donald CL, Malone J, Maltzer Z, Martin N, McCue R, McMillen D, Mena G, Meyerdierks E, Meyers KP, Mollenkopf T, Montine M, Nolan AL, Nyhus JK, Olsen PA, Pacleb M, Pagan CM, Peña N, Pham T, Pom CA, Postupna N, Rimorin C, Ruiz A, Saldi GA, Schantz AM, Shapovalova NV, Sorensen SA, Staats B, Sullivan M, Sunkin SM, Thompson C, Tieu M, Ting JT, Torkelson A, Tran T, Valera Cuevas NJ, Walling-Bell S, Wang MQ, Waters J, Wilson AM, Xiao M, Haynor D, Gatto NM, Jayadev S, Mufti S, Ng L, Mukherjee S, Crane PK, Latimer CS, Levi BP, Smith KA, Close JL, Miller JA, Hodge RD, Larson EB, Grabowski TJ, Hawrylycz M, Keene CD, Lein ES. Integrated multimodal cell atlas of Alzheimer's disease. Nat Neurosci 2024; 27:2366-2383. [PMID: 39402379 PMCID: PMC11614693 DOI: 10.1038/s41593-024-01774-5] [Show More Authors] [Citation(s) in RCA: 31] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Accepted: 08/28/2024] [Indexed: 10/19/2024]
Abstract
Alzheimer's disease (AD) is the leading cause of dementia in older adults. Although AD progression is characterized by stereotyped accumulation of proteinopathies, the affected cellular populations remain understudied. Here we use multiomics, spatial genomics and reference atlases from the BRAIN Initiative to study middle temporal gyrus cell types in 84 donors with varying AD pathologies. This cohort includes 33 male donors and 51 female donors, with an average age at time of death of 88 years. We used quantitative neuropathology to place donors along a disease pseudoprogression score. Pseudoprogression analysis revealed two disease phases: an early phase with a slow increase in pathology, presence of inflammatory microglia, reactive astrocytes, loss of somatostatin+ inhibitory neurons, and a remyelination response by oligodendrocyte precursor cells; and a later phase with exponential increase in pathology, loss of excitatory neurons and Pvalb+ and Vip+ inhibitory neuron subtypes. These findings were replicated in other major AD studies.
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Affiliation(s)
- Mariano I Gabitto
- Allen Institute for Brain Science, Seattle, WA, USA
- Department of Statistics, University of Washington, Seattle, WA, USA
| | | | - Victoria M Rachleff
- Allen Institute for Brain Science, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | | | - Brian Long
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Jeanelle Ariza
- Allen Institute for Brain Science, Seattle, WA, USA
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Yi Ding
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Nick Dee
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Jeff Goldy
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Erica J Melief
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Anamika Agrawal
- Center for Data-Driven Discovery for Biology, Allen Institute, Seattle, WA, USA
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Omar Kana
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | - John Campos
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | | | | | | | | | - Jonah Cool
- Chan Zuckerberg Initiative, Redwood City, CA, USA
| | | | - Martin Darvas
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | | | - Tim Dolbeare
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Tom Egdorf
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Rohan Gala
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Amanda Gary
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Jessica Gloe
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Windy Ho
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Madison Hupp
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Tim Jarsky
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Brian E Kalmbach
- Allen Institute for Brain Science, Seattle, WA, USA
- Department of Physiology and Biophysics, University of Washington, Seattle, WA, USA
| | - Lisa M Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Sarah Khawand
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Mitchell D Kilgore
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Amanda Kirkland
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | | | - Brian R Lee
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Zoe Maltzer
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Naomi Martin
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Rachel McCue
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Gonzalo Mena
- Department of Statistics and Data Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | | | - Kelly P Meyers
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | | | - Mark Montine
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Amber L Nolan
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | | | - Paul A Olsen
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Maiya Pacleb
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | | | | | | | | | - Nadia Postupna
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | | | | | | | - Aimee M Schantz
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | | | | | - Brian Staats
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Michael Tieu
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | - Tracy Tran
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | - Jack Waters
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Angela M Wilson
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Ming Xiao
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - David Haynor
- Department of Radiology, University of Washington, Seattle, WA, USA
| | - Nicole M Gatto
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Suman Jayadev
- Department of Neurology, University of Washington, Seattle, WA, USA
| | - Shoaib Mufti
- Allen Institute for Brain Science, Seattle, WA, USA
| | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | - Paul K Crane
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Caitlin S Latimer
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA
| | - Boaz P Levi
- Allen Institute for Brain Science, Seattle, WA, USA
| | | | | | | | | | - Eric B Larson
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Thomas J Grabowski
- Department of Radiology, University of Washington, Seattle, WA, USA
- Department of Neurology, University of Washington, Seattle, WA, USA
| | | | - C Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA, USA.
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31
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Aldridge AI, West AE. Epigenetics and the timing of neuronal differentiation. Curr Opin Neurobiol 2024; 89:102915. [PMID: 39277975 PMCID: PMC11611672 DOI: 10.1016/j.conb.2024.102915] [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: 06/16/2024] [Revised: 08/19/2024] [Accepted: 08/21/2024] [Indexed: 09/17/2024]
Abstract
Epigenetic regulation of the genome is required for cell-type differentiation during organismal development and is especially important to generate the panoply of specialized cell types that comprise the brain. Here, we review how progressive changes in the chromatin landscape, both in neural progenitors and in postmitotic neurons, orchestrate the timing of gene expression programs that underlie first neurogenesis and then functional neuronal maturation. We discuss how disease-associated mutations in chromatin regulators can change brain composition by impairing the timing of neurogenesis. Further, we highlight studies that are beginning to show how chromatin modifications are integrated at the level of chromatin architecture to coordinate changing transcriptional programs across developmental including in postmitotic neurons.
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Affiliation(s)
- Andrew I Aldridge
- Duke University School of Medicine, Department of Neurobiology, Durham, NC 27710, USA
| | - Anne E West
- Duke University School of Medicine, Department of Neurobiology, Durham, NC 27710, USA.
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32
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Li M, Flack N, Larsen PA. Multifaceted Role of Specialized Neuropeptide-Intensive Neurons on the Selective Vulnerability to Alzheimer's Disease in the Human Brain. Biomolecules 2024; 14:1518. [PMID: 39766225 PMCID: PMC11673071 DOI: 10.3390/biom14121518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2024] [Revised: 10/11/2024] [Accepted: 11/21/2024] [Indexed: 01/11/2025] Open
Abstract
Regarding Alzheimer's disease (AD), specific neuronal populations and brain regions exhibit selective vulnerability. Understanding the basis of this selective neuronal and regional vulnerability is essential to elucidate the molecular mechanisms underlying AD pathology. However, progress in this area is currently hindered by the incomplete understanding of the intricate functional and spatial diversity of neuronal subtypes in the human brain. Previous studies have demonstrated that neuronal subpopulations with high neuropeptide (NP) co-expression are disproportionately absent in the entorhinal cortex of AD brains at the single-cell level, and there is a significant decline in hippocampal NP expression in naturally aging human brains. Given the role of NPs in neuroprotection and the maintenance of microenvironments, we hypothesize that neurons expressing higher levels of NPs (HNP neurons) possess unique functional characteristics that predispose them to cellular abnormalities, which can manifest as degeneration in AD with aging. To test this hypothesis, multiscale and spatiotemporal transcriptome data from ~1900 human brain samples were analyzed using publicly available datasets. The results indicate that HNP neurons experienced greater metabolic burden and were more prone to protein misfolding. The observed decrease in neuronal abundance during stages associated with a higher risk of AD, coupled with the age-related decline in the expression of AD-associated neuropeptides (ADNPs), provides temporal evidence supporting the role of NPs in the progression of AD. Additionally, the localization of ADNP-producing HNP neurons in AD-associated brain regions provides neuroanatomical support for the concept that cellular/neuronal composition is a key factor in regional AD vulnerability. This study offers novel insights into the molecular and cellular basis of selective neuronal and regional vulnerability to AD in human brains.
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Affiliation(s)
- Manci Li
- Department of Electrical and Computer Engineering, College of Science and Engineering, University of Minnesota, Minneapolis, MN 55455, USA
- Department of Veterinary and Biomedical Sciences, College of Veterinary Medicine, University of Minnesota, St. Paul, MN 55108, USA
| | - Nicole Flack
- Department of Veterinary and Biomedical Sciences, College of Veterinary Medicine, University of Minnesota, St. Paul, MN 55108, USA
- Minnesota Center for Prion Research and Outreach, College of Veterinary Medicine, University of Minnesota, St. Paul, MN 55108, USA
| | - Peter A. Larsen
- Department of Veterinary and Biomedical Sciences, College of Veterinary Medicine, University of Minnesota, St. Paul, MN 55108, USA
- Minnesota Center for Prion Research and Outreach, College of Veterinary Medicine, University of Minnesota, St. Paul, MN 55108, USA
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33
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Shibata D. Human Brain Ancestral Barcodes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.14.603450. [PMID: 39071290 PMCID: PMC11275915 DOI: 10.1101/2024.07.14.603450] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Abstract
Dynamic CpG methylation "barcodes" were read from 15,000 to 21,000 single cells from three human male brains. To overcome sparse sequencing coverage, the barcode had ~31,000 rapidly fluctuating X-chromosome CpG sites (fCpGs), with at least 500 covered sites per cell and at least 30 common sites between cell pairs (average of ~48). Barcodes appear to start methylated and record mitotic ages because excitatory neurons and glial cells that emerge later in development were less methylated. Barcodes are different between most cells, with average pairwise differences (PWDs) of ~0.5 between cells. About 10 cell pairs per million were more closely related with PWDs < 0.05. Barcodes appear to record ancestry and reconstruct trees where more related cells had similar phenotypes, albeit some pairs had phenotypic differences. Inhibitory neurons showed more evidence of tangential migration than excitatory neurons, with related cells in different cortical regions. fCpG barcodes become polymorphic during development and can distinguish between thousands of human cells.
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34
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Chen ZJ, Das SS, Kar A, Lee SHT, Abuhanna KD, Alvarez M, Sukhatme MG, Gelev KZ, Heffel MG, Zhang Y, Avram O, Rahmani E, Sankararaman S, Heinonen S, Peltoniemi H, Halperin E, Pietiläinen KH, Luo C, Pajukanta P. Single-cell DNA methylome and 3D genome atlas of the human subcutaneous adipose tissue. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.11.02.621694. [PMID: 39554055 PMCID: PMC11566006 DOI: 10.1101/2024.11.02.621694] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/19/2024]
Abstract
Human subcutaneous adipose tissue (SAT) contains a diverse array of cell-types; however, the epigenomic landscape among the SAT cell-types has remained elusive. Our integrative analysis of single-cell resolution DNA methylation and chromatin conformation profiles (snm3C-seq), coupled with matching RNA expression (snRNA-seq), systematically cataloged the epigenomic, 3D topology, and transcriptomic dynamics across the SAT cell-types. We discovered that the SAT CG methylation (mCG) landscape is characterized by pronounced hyper-methylation in myeloid cells and hypo-methylation in adipocytes and adipose stem and progenitor cells (ASPCs), driving nearly half of the 705,063 detected differentially methylated regions (DMRs). In addition to the enriched cell-type-specific transcription factor binding motifs, we identified TET1 and DNMT3A as plausible candidates for regulating cell-type level mCG profiles. Furthermore, we observed that global mCG profiles closely correspond to SAT lineage, which is also reflected in cell-type-specific chromosome compartmentalization. Adipocytes, in particular, display significantly more short-range chromosomal interactions, facilitating the formation of complex local 3D genomic structures that regulate downstream transcriptomic activity, including those associated with adipogenesis. Finally, we discovered that variants in cell-type level DMRs and A compartments significantly predict and are enriched for variance explained in abdominal obesity. Together, our multimodal study characterizes human SAT epigenomic landscape at the cell-type resolution and links partitioned polygenic risk of abdominal obesity to SAT epigenome.
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35
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Heffel MG, Zhou J, Zhang Y, Lee DS, Hou K, Pastor-Alonso O, Abuhanna KD, Galasso J, Kern C, Tai CY, Garcia-Padilla C, Nafisi M, Zhou Y, Schmitt AD, Li T, Haeussler M, Wick B, Zhang MJ, Xie F, Ziffra RS, Mukamel EA, Eskin E, Nowakowski TJ, Dixon JR, Pasaniuc B, Ecker JR, Zhu Q, Bintu B, Paredes MF, Luo C. Temporally distinct 3D multi-omic dynamics in the developing human brain. Nature 2024; 635:481-489. [PMID: 39385032 PMCID: PMC11560841 DOI: 10.1038/s41586-024-08030-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 09/06/2024] [Indexed: 10/11/2024]
Abstract
The human hippocampus and prefrontal cortex play critical roles in learning and cognition1,2, yet the dynamic molecular characteristics of their development remain enigmatic. Here we investigated the epigenomic and three-dimensional chromatin conformational reorganization during the development of the hippocampus and prefrontal cortex, using more than 53,000 joint single-nucleus profiles of chromatin conformation and DNA methylation generated by single-nucleus methyl-3C sequencing (snm3C-seq3)3. The remodelling of DNA methylation is temporally separated from chromatin conformation dynamics. Using single-cell profiling and multimodal single-molecule imaging approaches, we have found that short-range chromatin interactions are enriched in neurons, whereas long-range interactions are enriched in glial cells and non-brain tissues. We reconstructed the regulatory programs of cell-type development and differentiation, finding putatively causal common variants for schizophrenia strongly overlapping with chromatin loop-connected, cell-type-specific regulatory regions. Our data provide multimodal resources for studying gene regulatory dynamics in brain development and demonstrate that single-cell three-dimensional multi-omics is a powerful approach for dissecting neuropsychiatric risk loci.
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Affiliation(s)
- Matthew G Heffel
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jingtian Zhou
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA, USA
- Arc Institute, Palo Alto, CA, USA
| | - Yi Zhang
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Dong-Sung Lee
- Department of Biomedical Sciences, Seoul National University Graduate School, Seoul, Republic of Korea
- Genomic Medicine Institute, Medical Research Center, Seoul National University, Seoul, Republic of Korea
| | - Kangcheng Hou
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Oier Pastor-Alonso
- Department of Neurology, University of California, San Francisco, San Francisco, CA, USA
| | - Kevin D Abuhanna
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Joseph Galasso
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Colin Kern
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Chu-Yi Tai
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Carlos Garcia-Padilla
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Mahsa Nafisi
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Yi Zhou
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | | | - Terence Li
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
- Bioinformatics Interdepartmental Program, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Brittney Wick
- Genomics Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Martin Jinye Zhang
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Fangming Xie
- Department of Biological Chemistry, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
| | - Ryan S Ziffra
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Department of Anatomy, University of California, San Francisco, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
| | - Eran A Mukamel
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
| | - Eleazar Eskin
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Tomasz J Nowakowski
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, USA
- Department of Anatomy, University of California, San Francisco, San Francisco, CA, USA
- Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, San Francisco, CA, USA
- Eli and Edythe Broad Center for Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA, USA
| | - Jesse R Dixon
- Gene Expression Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Bogdan Pasaniuc
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Joseph R Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Quan Zhu
- Center for Epigenomics, Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Bogdan Bintu
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Mercedes F Paredes
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
- Neuroscience Graduate Program, University of California, San Francisco, San Francisco, CA, USA.
- Developmental Stem Cell Biology, University of California, San Francisco, San Francisco, CA, USA.
| | - Chongyuan Luo
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA.
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Fan S, Dang D, Gao L, Zhang S. ImputeHiFI: An Imputation Method for Multiplexed DNA FISH Data by Utilizing Single-Cell Hi-C and RNA FISH Data. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2406364. [PMID: 39264290 PMCID: PMC11558076 DOI: 10.1002/advs.202406364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2024] [Revised: 08/03/2024] [Indexed: 09/13/2024]
Abstract
Although multiplexed DNA fluorescence in situ hybridization (FISH) enables tracking the spatial localization of thousands of genomic loci using probes within individual cells, the high rates of undetected probes impede the depiction of 3D chromosome structures. Current data imputation methods neither utilize single-cell Hi-C data, which elucidate 3D genome architectures using sequencing nor leverage multimodal RNA FISH data that reflect cell-type information, limiting the effectiveness of these methods in complex tissues such as the mouse brain. To this end, a novel multiplexed DNA FISH imputation method named ImputeHiFI is proposed, which fully utilizes the complementary structural information from single-cell Hi-C data and the cell type signature from RNA FISH data to obtain a high-fidelity and complete spatial location of chromatin loci. ImputeHiFI enhances cell clustering, compartment identification, and cell subtype detection at the single-cell level in the mouse brain. ImputeHiFI improves the recognition of cell-type-specific loops in three high-resolution datasets. In short, ImputeHiFI is a powerful tool capable of imputing multiplexed DNA FISH data from various resolutions and imaging protocols, facilitating studies of 3D genome structures and functions.
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Affiliation(s)
- Shichen Fan
- School of Computer Science and TechnologyXidian UniversityXi'an710071China
| | - Dachang Dang
- School of AutomationNorthwestern Polytechnical UniversityXi'an710072China
| | - Lin Gao
- School of Computer Science and TechnologyXidian UniversityXi'an710071China
| | - Shihua Zhang
- NCMIS, CEMS, RCSDSAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing100190China
- School of Mathematical SciencesUniversity of Chinese Academy of SciencesBeijing100049China
- Key Laboratory of Systems BiologyHangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesChinese Academy of SciencesHangzhou310024China
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37
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Rahman S, Roussos P. The 3D Genome in Brain Development: An Exploration of Molecular Mechanisms and Experimental Methods. Neurosci Insights 2024; 19:26331055241293455. [PMID: 39494115 PMCID: PMC11528596 DOI: 10.1177/26331055241293455] [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: 02/09/2024] [Accepted: 10/08/2024] [Indexed: 11/05/2024] Open
Abstract
The human brain contains multiple cell types that are spatially organized into functionally distinct regions. The proper development of the brain requires complex gene regulation mechanisms in both neurons and the non-neuronal cell types that support neuronal function. Studies across the last decade have discovered that the 3D nuclear organization of the genome is instrumental in the regulation of gene expression in the diverse cell types of the brain. In this review, we describe the fundamental biochemical mechanisms that regulate the 3D genome, and comprehensively describe in vitro and ex vivo studies on mouse and human brain development that have characterized the roles of the 3D genome in gene regulation. We highlight the significance of the 3D genome in linking distal enhancers to their target promoters, which provides insights on the etiology of psychiatric and neurological disorders, as the genetic variants associated with these disorders are primarily located in noncoding regulatory regions. We also describe the molecular mechanisms that regulate chromatin folding and gene expression in neurons. Furthermore, we describe studies with an evolutionary perspective, which have investigated features that are conserved from mice to human, as well as human gained 3D chromatin features. Although most of the insights on disease and molecular mechanisms have been obtained from bulk 3C based experiments, we also highlight other approaches that have been developed recently, such as single cell 3C approaches, as well as non-3C based approaches. In our future perspectives, we highlight the gaps in our current knowledge and emphasize the need for 3D genome engineering and live cell imaging approaches to elucidate mechanisms and temporal dynamics of chromatin interactions, respectively.
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Affiliation(s)
- 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 Sciences, 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 Sciences, 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
- Center for Dementia Research, Nathan Kline Institute for Psychiatric Research, Orangeburg, NY, USA
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Gordon JA, Dzirasa K, Petzschner FH. The neuroscience of mental illness: Building toward the future. Cell 2024; 187:5858-5870. [PMID: 39423804 PMCID: PMC11490687 DOI: 10.1016/j.cell.2024.09.028] [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: 09/13/2024] [Revised: 09/16/2024] [Accepted: 09/16/2024] [Indexed: 10/21/2024]
Abstract
Mental illnesses arise from dysfunction in the brain. Although numerous extraneural factors influence these illnesses, ultimately, it is the science of the brain that will lead to novel therapies. Meanwhile, our understanding of this complex organ is incomplete, leading to the oft-repeated trope that neuroscience has yet to make significant contributions to the care of individuals with mental illnesses. This review seeks to counter this narrative, using specific examples of how neuroscientific advances have contributed to progress in mental health care in the past and how current achievements set the stage for further progress in the future.
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Affiliation(s)
- Joshua A Gordon
- Department of Psychiatry, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA; New York State Psychiatric Institute, New York, NY, USA.
| | - Kafui Dzirasa
- Departments of Psychiatry and Behavioral Sciences, Neurology, and Biomedical Engineering, Duke University Medical Center, Durham, NC, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA
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Zemke NR, Lee S, Mamde S, Yang B, Berchtold N, Maximiliano Garduño B, Indralingam HS, Bartosik WM, Lau PK, Dong K, Yang A, Tani Y, Chen C, Zeng Q, Ajith V, Tong L, Seng C, Li D, Wang T, Xu X, Ren B. Epigenetic and 3D genome reprogramming during the aging of human hippocampus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.14.618338. [PMID: 39463924 PMCID: PMC11507755 DOI: 10.1101/2024.10.14.618338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/29/2024]
Abstract
Age-related cognitive decline is associated with altered physiology of the hippocampus. While changes in gene expression have been observed in aging brain, the regulatory mechanisms underlying these changes remain underexplored. We generated single-nucleus gene expression, chromatin accessibility, DNA methylation, and 3D genome data from 40 human hippocampal tissues spanning adult lifespan. We observed a striking loss of astrocytes, OPC, and endothelial cells during aging, including astrocytes that play a role in regulating synapses. Microglia undergo a dramatic switch from a homeostatic state to a primed inflammatory state through DNA methylome and 3D genome reprogramming. Aged cells experience erosion of their 3D genome architecture. Our study identifies age-associated changes in cell types/states and gene regulatory features that provide insight into cognitive decline during human aging.
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Affiliation(s)
- Nathan R. Zemke
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Seoyeon Lee
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Sainath Mamde
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Bing Yang
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Nicole Berchtold
- Department of Anatomy and Neurobiology, University of California, Irvine School of Medicine; Irvine, CA, USA
- Immunis Inc, 18301 Von Karman Ave; Irvine, CA, USA
| | - B. Maximiliano Garduño
- Department of Anatomy and Neurobiology, University of California, Irvine School of Medicine; Irvine, CA, USA
| | - Hannah S. Indralingam
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Weronika M. Bartosik
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Pik Ki Lau
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Keyi Dong
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Amanda Yang
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Yasmine Tani
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Chumo Chen
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Qiurui Zeng
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
| | - Varun Ajith
- Department of Anatomy and Neurobiology, University of California, Irvine School of Medicine; Irvine, CA, USA
| | - Liqi Tong
- Department of Anatomy and Neurobiology, University of California, Irvine School of Medicine; Irvine, CA, USA
| | - Chanrung Seng
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine; St. Louis, MO, USA
| | - Daofeng Li
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine; St. Louis, MO, USA
| | - Ting Wang
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine; St. Louis, MO, USA
- McDonnell Genome Institute, Washington University School of Medicine; St. Louis, MO, USA
| | - Xiangmin Xu
- Department of Anatomy and Neurobiology, University of California, Irvine School of Medicine; Irvine, CA, USA
- The Center for Neural Circuit Mapping, University of California; Irvine, CA, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine; La Jolla, CA, USA
- Center for Epigenomics, University of California, San Diego School of Medicine; La Jolla, CA, USA
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40
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Pedrotti S, Castiglioni I, Perez-Estrada C, Zhao L, Chen JP, Crosetto N, Bienko M. Emerging methods and applications in 3D genomics. Curr Opin Cell Biol 2024; 90:102409. [PMID: 39178735 DOI: 10.1016/j.ceb.2024.102409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 07/21/2024] [Accepted: 07/22/2024] [Indexed: 08/26/2024]
Abstract
Since the advent of Hi-C in 2009, a plethora of high-throughput sequencing methods have emerged to profile the three-dimensional (3D) organization of eukaryotic genomes, igniting the era of 3D genomics. In recent years, the genomic resolution achievable by these approaches has dramatically increased and several single-cell versions of Hi-C have been developed. Moreover, a new repertoire of tools not based on proximity ligation of digested chromatin has emerged, enabling the investigation of the higher-order organization of chromatin in the nucleus. In this review, we summarize the expanding portfolio of 3D genomic technologies, highlighting recent developments and applications from the past three years. Lastly, we present an outlook of where this technology-driven field might be headed.
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Affiliation(s)
- Simona Pedrotti
- Human Technopole, Viale Rita Levi-Montalcini 1, 20157, Milan, Italy
| | | | - Cynthia Perez-Estrada
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17165, Sweden; Science for Life Laboratory, Solna, 17165, Sweden
| | - Linxuan Zhao
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17165, Sweden; Science for Life Laboratory, Solna, 17165, Sweden
| | - Jinxin Phaedo Chen
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17165, Sweden; Science for Life Laboratory, Solna, 17165, Sweden
| | - Nicola Crosetto
- Human Technopole, Viale Rita Levi-Montalcini 1, 20157, Milan, Italy; Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17165, Sweden; Science for Life Laboratory, Solna, 17165, Sweden.
| | - Magda Bienko
- Human Technopole, Viale Rita Levi-Montalcini 1, 20157, Milan, Italy; Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17165, Sweden; Science for Life Laboratory, Solna, 17165, Sweden.
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41
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Sullivan PF, Yao S, Hjerling-Leffler J. Schizophrenia genomics: genetic complexity and functional insights. Nat Rev Neurosci 2024; 25:611-624. [PMID: 39030273 DOI: 10.1038/s41583-024-00837-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/04/2024] [Indexed: 07/21/2024]
Abstract
Determining the causes of schizophrenia has been a notoriously intractable problem, resistant to a multitude of investigative approaches over centuries. In recent decades, genomic studies have delivered hundreds of robust findings that implicate nearly 300 common genetic variants (via genome-wide association studies) and more than 20 rare variants (via whole-exome sequencing and copy number variant studies) as risk factors for schizophrenia. In parallel, functional genomic and neurobiological studies have provided exceptionally detailed information about the cellular composition of the brain and its interconnections in neurotypical individuals and, increasingly, in those with schizophrenia. Taken together, these results suggest unexpected complexity in the mechanisms that drive schizophrenia, pointing to the involvement of ensembles of genes (polygenicity) rather than single-gene causation. In this Review, we describe what we now know about the genetics of schizophrenia and consider the neurobiological implications of this information.
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Affiliation(s)
- Patrick F Sullivan
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA.
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA.
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
| | - Shuyang Yao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jens Hjerling-Leffler
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
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42
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Marumo T, Yoshida N, Inoue N, Yamanouchi M, Ubara Y, Urakami S, Fujii T, Takazawa Y, Ohashi K, Kawarazaki W, Nishimoto M, Ayuzawa N, Hirohama D, Nagae G, Fujimoto M, Arai E, Kanai Y, Hoshino J, Fujita T. Aberrant proximal tubule DNA methylation underlies phenotypic changes related to kidney dysfunction in patients with diabetes. Am J Physiol Renal Physiol 2024; 327:F397-F411. [PMID: 38961842 DOI: 10.1152/ajprenal.00124.2024] [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: 04/22/2024] [Revised: 06/17/2024] [Accepted: 06/25/2024] [Indexed: 07/05/2024] Open
Abstract
Epigenetic mechanisms are considered to contribute to diabetic nephropathy by maintaining memory of poor glycemic control during the early stages of diabetes. However, DNA methylation changes in the human kidney are poorly characterized, because of the lack of cell type-specific analysis. We examined DNA methylation in proximal tubules (PTs) purified from patients with diabetic nephropathy and identified differentially methylated CpG sites, given the critical role of proximal tubules in the kidney injury. Hypermethylation was observed at CpG sites annotated to genes responsible for proximal tubule functions, including gluconeogenesis, nicotinamide adenine dinucleotide synthesis, transporters of glucose, water, phosphate, and drugs, in diabetic kidneys, whereas genes involved in oxidative stress and the cytoskeleton exhibited demethylation. Methylation levels of CpG sites annotated to ACTN1, BCAR1, MYH9, UBE4B, AFMID, TRAF2, TXNIP, FOXO3, and HNF4A were correlated with the estimated glomerular filtration rate, whereas methylation of the CpG site in RUNX1 was associated with interstitial fibrosis and tubular atrophy. Hypermethylation of G6PC and HNF4A was accompanied by decreased expression in diabetic kidneys. Proximal tubule-specific hypomethylation of metabolic genes related to HNF4A observed in control kidneys was compromised in diabetic kidneys, suggesting a role for aberrant DNA methylation in the dedifferentiation process. Multiple genes with aberrant DNA methylation in diabetes overlapped genes with altered expressions in maladaptive proximal tubule cells, including transcription factors PPARA and RREB1. In conclusion, DNA methylation derangement in the proximal tubules of patients with diabetes may drive phenotypic changes, characterized by inflammatory and fibrotic features, along with impaired function in metabolism and transport.NEW & NOTEWORTHY Cell type-specific DNA methylation patterns in the human kidney are not known. We examined DNA methylation in proximal tubules of patients with diabetic nephropathy and revealed that oxidative stress, cytoskeleton, and metabolism genes were aberrantly methylated. The results indicate that aberrant DNA methylation in proximal tubules underlies kidney dysfunction in diabetic nephropathy. Aberrant methylation could be a target for reversing memory of poor glycemic control.
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Affiliation(s)
- Takeshi Marumo
- Department of Pharmacology, School of Medicine, International University of Health and Welfare, Chiba, Japan
- Division of Clinical Epigenetics, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Naoto Yoshida
- Department of Pharmacology, School of Medicine, International University of Health and Welfare, Chiba, Japan
| | - Noriko Inoue
- Nephrology Center, Toranomon Hospital, Tokyo, Japan
| | | | | | | | - Takeshi Fujii
- Department of Pathology, Toranomon Hospital, Tokyo, Japan
| | | | - Kenichi Ohashi
- Department of Human Pathology, Tokyo Medical and Dental University, Tokyo, Japan
| | - Wakako Kawarazaki
- Department of Pharmacology, School of Medicine, International University of Health and Welfare, Chiba, Japan
- Division of Clinical Epigenetics, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Mitsuhiro Nishimoto
- Division of Clinical Epigenetics, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Nobuhiro Ayuzawa
- Division of Clinical Epigenetics, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Daigoro Hirohama
- Division of Clinical Epigenetics, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Genta Nagae
- Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Mao Fujimoto
- Department of Pathology, Keio University School of Medicine, Tokyo, Japan
| | - Eri Arai
- Department of Pathology, Keio University School of Medicine, Tokyo, Japan
| | - Yae Kanai
- Department of Pathology, Keio University School of Medicine, Tokyo, Japan
| | - Junichi Hoshino
- Nephrology Center, Toranomon Hospital, Tokyo, Japan
- Deparment of Nephrology, Tokyo Women's Medical University, Tokyo, Japan
| | - Toshiro Fujita
- Division of Clinical Epigenetics, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, Japan
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Chien JF, Liu H, Wang BA, Luo C, Bartlett A, Castanon R, Johnson ND, Nery JR, Osteen J, Li J, Altshul J, Kenworthy M, Valadon C, Liem M, Claffey N, O'Connor C, Seeker LA, Ecker JR, Behrens MM, Mukamel EA. Cell-type-specific effects of age and sex on human cortical neurons. Neuron 2024; 112:2524-2539.e5. [PMID: 38838671 DOI: 10.1016/j.neuron.2024.05.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2023] [Revised: 03/29/2024] [Accepted: 05/09/2024] [Indexed: 06/07/2024]
Abstract
Altered transcriptional and epigenetic regulation of brain cell types may contribute to cognitive changes with advanced age. Using single-nucleus multi-omic DNA methylation and transcriptome sequencing (snmCT-seq) in frontal cortex from young adult and aged donors, we found widespread age- and sex-related variation in specific neuron types. The proportion of inhibitory SST- and VIP-expressing neurons was reduced in aged donors. Excitatory neurons had more profound age-related changes in their gene expression and DNA methylation than inhibitory cells. Hundreds of genes involved in synaptic activity, including EGR1, were less expressed in aged adults. Genes located in subtelomeric regions increased their expression with age and correlated with reduced telomere length. We further mapped cell-type-specific sex differences in gene expression and X-inactivation escape genes. Multi-omic single-nucleus epigenomes and transcriptomes provide new insight into the effects of age and sex on human neurons.
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Affiliation(s)
- Jo-Fan Chien
- Department of Physics, University of California, San Diego, La Jolla, CA 92037, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Bang-An Wang
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Chongyuan Luo
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Anna Bartlett
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Rosa Castanon
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Nicholas D Johnson
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92037, USA; Computational Neurobiology Laboratory, Salk Institute, La Jolla, CA 92037, USA
| | - Joseph R Nery
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Julia Osteen
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Junhao Li
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92037, USA
| | - Jordan Altshul
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Mia Kenworthy
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Cynthia Valadon
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA
| | - Michelle Liem
- Flow Cytometry Core Facility, Salk Institute, La Jolla, CA 92037, USA
| | - Naomi Claffey
- Flow Cytometry Core Facility, Salk Institute, La Jolla, CA 92037, USA
| | - Carolyn O'Connor
- Flow Cytometry Core Facility, Salk Institute, La Jolla, CA 92037, USA
| | - Luise A Seeker
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Joseph R Ecker
- Genomic Analysis Laboratory, Salk Institute, La Jolla, CA 92037, USA; Howard Hughes Medical Institute, Salk Institute, La Jolla, CA 92037, USA.
| | - M Margarita Behrens
- Department of Psychiatry, University of California, San Diego, La Jolla, CA 92037, USA; Computational Neurobiology Laboratory, Salk Institute, La Jolla, CA 92037, USA.
| | - Eran A Mukamel
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA 92037, USA.
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Wei X, Li J, Cheng Z, Wei S, Yu G, Olsen ML. Decoding the Epigenetic Landscape: Insights into 5mC and 5hmC Patterns in Mouse Cortical Cell Types. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.06.602342. [PMID: 39026756 PMCID: PMC11257419 DOI: 10.1101/2024.07.06.602342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/20/2024]
Abstract
The DNA modifications, 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC), represent powerful epigenetic regulators of temporal and spatial gene expression. Yet, how the cooperation of these genome-wide, epigenetic marks determine unique transcriptional signatures across different brain cell populations is unclear. Here we applied Nanopore sequencing of native DNA to obtain a complete, genome-wide, single-base resolution atlas of 5mC and 5hmC modifications in neurons, astrocytes and microglia in the mouse cortex (99% genome coverage, 40 million CpG sites). In tandem with RNA sequencing, analysis of 5mC and 5hmC patterns across cell types reveals astrocytes drive uniquely high brain 5hmC levels and support two decades of research regarding methylation patterns, gene expression and alternative splicing, benchmarking this resource. As such, we provide the most comprehensive DNA methylation data in mouse brain as an interactive, online tool (NAM-Me, https://olsenlab.shinyapps.io/NAMME/) to serve as a resource dataset for those interested in the methylome landscape.
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Affiliation(s)
- Xiaoran Wei
- Biomedical and Veterinary Sciences Graduate Program, Virginia Tech, Blacksburg, VA, the United States
- School of Neuroscience, Virginia Tech, Blacksburg, VA, the United States
| | - Jiangtao Li
- School of Neuroscience, Virginia Tech, Blacksburg, VA, the United States
- Genetics, Bioinformatics and Computational Biology Graduate Program, Virginia Tech, Blacksburg, VA, the United States
| | - Zuolin Cheng
- Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, the United States
| | - Songtao Wei
- Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, the United States
| | - Guoqiang Yu
- Bradley Department of Electrical and Computer Engineering, Virginia Tech, Arlington, VA, the United States
| | - Michelle L Olsen
- School of Neuroscience, Virginia Tech, Blacksburg, VA, the United States
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45
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Chen R, Nie P, Wang J, Wang GZ. Deciphering brain cellular and behavioral mechanisms: Insights from single-cell and spatial RNA sequencing. WILEY INTERDISCIPLINARY REVIEWS. RNA 2024; 15:e1865. [PMID: 38972934 DOI: 10.1002/wrna.1865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Revised: 05/05/2024] [Accepted: 05/14/2024] [Indexed: 07/09/2024]
Abstract
The brain is a complex computing system composed of a multitude of interacting neurons. The computational outputs of this system determine the behavior and perception of every individual. Each brain cell expresses thousands of genes that dictate the cell's function and physiological properties. Therefore, deciphering the molecular expression of each cell is of great significance for understanding its characteristics and role in brain function. Additionally, the positional information of each cell can provide crucial insights into their involvement in local brain circuits. In this review, we briefly overview the principles of single-cell RNA sequencing and spatial transcriptomics, the potential issues and challenges in their data processing, and their applications in brain research. We further outline several promising directions in neuroscience that could be integrated with single-cell RNA sequencing, including neurodevelopment, the identification of novel brain microstructures, cognition and behavior, neuronal cell positioning, molecules and cells related to advanced brain functions, sleep-wake cycles/circadian rhythms, and computational modeling of brain function. We believe that the deep integration of these directions with single-cell and spatial RNA sequencing can contribute significantly to understanding the roles of individual cells or cell types in these specific functions, thereby making important contributions to addressing critical questions in those fields. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA in Disease and Development > RNA in Development RNA in Disease and Development > RNA in Disease.
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Affiliation(s)
- Renrui Chen
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Pengxing Nie
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Jing Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
| | - Guang-Zhong Wang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
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46
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Tian W, Ding W, Shen J, Li D, Wang T, Ecker JR. BAllC and BAllCools: efficient formatting and operating for single-cell DNA methylation data. Bioinformatics 2024; 40:btae404. [PMID: 38905499 PMCID: PMC11216754 DOI: 10.1093/bioinformatics/btae404] [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: 09/22/2023] [Revised: 03/27/2024] [Accepted: 06/20/2024] [Indexed: 06/23/2024] Open
Abstract
MOTIVATION With single-cell DNA methylation studies yielding vast datasets, existing data formats struggle with the unique challenges of storage and efficient operations, highlighting a need for improved solutions. RESULTS BAllC (Binary All Cytosines) emerges as a tailored format for methylation data, addressing these challenges. BAllCools, its complementary software toolkit, enhances parsing, indexing, and querying capabilities, promising superior operational speeds and reduced storage needs. AVAILABILITY AND IMPLEMENTATION https://github.com/jksr/ballcools.
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Affiliation(s)
- Wei Tian
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, United States
| | - Wubin Ding
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, United States
| | - Jiawei Shen
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO 63110, United States
| | - Daofeng Li
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO 63110, United States
| | - Ting Wang
- Department of Genetics, The Edison Family Center for Genome Sciences & Systems Biology, Washington University School of Medicine, St Louis, MO 63110, United States
- McDonnell Genome Institute, Washington University School of Medicine, St Louis, MO 63108, United States
| | - Joseph R Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, United States
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, CA 92037, United States
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47
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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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48
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Outeiro TF, Kalia LV, Bezard E, Ferrario J, Lin CH, Salama M, Standaert DG, Taiwo L, Takahashi R, Vila M, Mollenhauer B, Svenningsson P. Basic Science in Movement Disorders: Fueling the Engine of Translation into Clinical Practice. Mov Disord 2024; 39:929-933. [PMID: 38576081 DOI: 10.1002/mds.29802] [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: 02/21/2024] [Revised: 03/11/2024] [Accepted: 03/15/2024] [Indexed: 04/06/2024] Open
Abstract
Basic Science is crucial for the advancement of clinical care for Movement Disorders. Here, we provide brief updates on how basic science is important for understanding disease mechanisms, disease prevention, disease diagnosis, development of novel therapies and to establish the basis for personalized medicine. We conclude the viewpoint by a call to action to further improve interactions between clinician and basic scientists. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Tiago F Outeiro
- Department of Experimental Neurodegeneration, Center for Biostructural Imaging of Neurodegeneration, University Medical Center Göttingen, Göttingen, Germany
- Max Planck Institute for Multidisciplinary Sciences, Göttingen, Germany
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK
- Scientific employee with an honorary contract at Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Göttingen, Germany
| | - Lorraine V Kalia
- Krembil Research Institute, Toronto Western Hospital, University Health Network, Toronto, Canada
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, Canada
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
| | - Erwan Bezard
- Université de Bordeaux, Institut des Maladies Neurodégénératives, Bordeaux, France
- Centre National de la Recherche Scientifique Unité Mixte de Recherche 5293, Institut des Maladies Neurodégénératives, Bordeaux, France
| | - Juan Ferrario
- Universidad de Buenos Aires, Facultad de Ciencias Exactas y Naturales, Instituto de Biociencias, Biotecnología y Biología traslacional (iB3) and CONICET, Buenos Aires, Argentina
| | - Chin-Hsien Lin
- Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan
- Institute of Molecular Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
- Department of Biomedical Engineering, National Taiwan University, Taipei, Taiwan
| | - Mohamed Salama
- Institute of Global Health and Human Ecology, The American University in Cairo, Cairo, Egypt
- Faculty of Medicine, Mansoura University, Dakahleya, Egypt
| | - David G Standaert
- Department of Neurology, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Lolade Taiwo
- Department of Neurology, University College Hospital, Ibadan, Nigeria
| | - Ryosuke Takahashi
- Department of Neurology, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Miquel Vila
- Neurodegenerative Diseases Research Group, Vall d'Hebron Research Institute (VHIR), Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Autonomous University of Barcelona (UAB), Barcelona, Spain
- Catalan Institution for Research and Advanced Studies (ICREA), Barcelona, Spain
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, Maryland, USA
| | - Brit Mollenhauer
- Scientific employee with an honorary contract at Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE), Göttingen, Germany
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, Maryland, USA
- Paracelsus-Elena-Klinik, Kassel, Germany; University Medical Center Goettingen, Institute of Neurology, Goettingen, Germany
| | - Per Svenningsson
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, Maryland, USA
- Department of Clinical Neuroscience and Neurology, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
- Department of Basic and Clinical Neuroscience, King's College London, London, UK
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49
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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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50
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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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