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Logeman BL, Grieco SF, Holmes TC, Xu X. Unfolding neural diversity: how dynamic three-dimensional genome architecture regulates brain function and disease. Mol Psychiatry 2025:10.1038/s41380-025-03056-3. [PMID: 40410418 DOI: 10.1038/s41380-025-03056-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2025] [Revised: 05/01/2025] [Accepted: 05/12/2025] [Indexed: 05/25/2025]
Abstract
The advent of single cell multi-omic technologies has ushered in a revolution in how we study the impact of three-dimensional genome organization on brain cellular composition and function. Transcriptomic and epigenomic studies reveal enormous cellular diversity that is present in mammalian nervous systems, raising the question, "how does this diversity arise and for what is its use?" Advances in the field of three-dimensional nuclear architecture have illuminated our understanding of how genome folding gives rise to dynamic gene expression programs important in healthy brain function and in disease. In this review we highlight recent work defining how neuronal identity, maturation, and plasticity are shaped by genome architecture. We discuss how newly identified genetic variations influence genome architecture and contribute to the evolution of species-unique neuronal and behavioral functional traits. We include examples for both humans and model organisms in which maladaptive genomic architecture is a causal agent in disease. Finally, we make conclusions and address future perspectives of dynamic three-dimensional genome (4D nucelome) research.
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Affiliation(s)
- Brandon L Logeman
- Department of Molecular and Cellular Biology, Howard Hughes Medical Institute, Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Steven F Grieco
- Department of Anatomy and Neurobiology, School of Medicine, University of California, Irvine, CA, 92697, USA
- Center for Neural Circuit Mapping, University of California, Irvine, CA, USA
| | - Todd C Holmes
- Center for Neural Circuit Mapping, University of California, Irvine, CA, USA
- Department of Physiology and Biophysics, School of Medicine, University of California, Irvine, CA, USA
| | - Xiangmin Xu
- Department of Anatomy and Neurobiology, School of Medicine, University of California, Irvine, CA, 92697, USA.
- Center for Neural Circuit Mapping, University of California, Irvine, CA, USA.
- Department of Microbiology and Molecular Genetics, University of California, Irvine, CA, USA.
- Department of Biomedical Engineering, University of California, Irvine, CA, USA.
- Department of Computer Science, University of California, Irvine, CA, USA.
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2
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Fink EE, Zhang Y, Santo B, Siddavatam A, Ou R, Nanavaty V, Lee BH, Ting AH. Heat shock induces alternative polyadenylation through dynamic DNA methylation and chromatin looping. Cell Stress Chaperones 2025:100084. [PMID: 40412548 DOI: 10.1016/j.cstres.2025.100084] [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: 04/30/2025] [Revised: 05/18/2025] [Accepted: 05/21/2025] [Indexed: 05/27/2025] Open
Abstract
Alternative cleavage and polyadenylation (APA) is a gene regulatory mechanism used by cells under stress to upregulate proteostasis-promoting transcripts, but how cells achieve this remains poorly understood. Previously, we elucidated a DNA methylation-regulated APA mechanism, in which gene body DNA methylation enhances distal poly(A) isoform expression by blocking CTCF binding and chromatin loop formation at APA control regions. We hypothesized that DNA methylation-regulated APA is one mechanism cells employ to induce proteostasis-promoting poly(A) isoforms. At the DNAJB6 co-chaperone locus, acute heat shock resulted in binding of stress response transcription factors HSF1, ATF6, and YY1 at the APA control region and an increase in the expression of the proximal poly(A) isoform known to prevent protein aggregation. Furthermore, TET1 was recruited to rapidly demethylate DNA, facilitating CTCF binding and chromatin loop formation, thereby reinforcing preferential proximal poly(A) isoform expression. As cells recovered, the transcription factors vacated the APA control region, and DNMT1 was recruited to remethylate the region. This process resolved chromatin looping and reset the poly(A) isoform expression pattern. Our findings unveil an epigenetic mechanism enabling cells to dynamically modulate poly(A) isoforms in response to stress while shedding light on the interplay between DNA methylation, transcription factor binding, and chromatin looping.
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Affiliation(s)
- Emily E Fink
- Genomic Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, 44195, USA
| | - Yi Zhang
- Department of Epigenetics and Molecular Carcinogenesis, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA; Department Gastrointestinal Surgery, Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221000, China
| | - Briana Santo
- Department of Epigenetics and Molecular Carcinogenesis, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Anwita Siddavatam
- Department of Epigenetics and Molecular Carcinogenesis, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Rosie Ou
- Department of Epigenetics and Molecular Carcinogenesis, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Vishal Nanavaty
- Genomic Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, 44195, USA; Department of Life Science, Food and Nutrition Science, Gujarat University, Ahmedabad, Gujarat, 380009, India; Neuberg Center for Genomic Medicine, Neuberg Supratec Reference Laboratory, Ahmedabad, Gujarat, 380009, India; Sandip Bhavini Research Institute, Ahmedabad, Gujarat, 380009, India
| | - Byron H Lee
- Department of Urology, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Angela H Ting
- Genomic Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, 44195, USA; Department of Epigenetics and Molecular Carcinogenesis, University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.
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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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Liu R, Zhang Z, Won H, Marron JS. Significance in scale space for Hi-C data. Bioinformatics 2025; 41:btaf026. [PMID: 40036585 PMCID: PMC11879645 DOI: 10.1093/bioinformatics/btaf026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2024] [Revised: 01/02/2025] [Accepted: 02/25/2025] [Indexed: 03/06/2025] Open
Abstract
MOTIVATION Hi-C technology has been developed to profile genome-wide chromosome conformation. So far Hi-C data have been generated from a large compendium of different cell types and different tissue types. Among different chromatin conformation units, chromatin loops were found to play a key role in gene regulation across different cell types. While many different loop calling algorithms have been developed, most loop callers identified shared loops as opposed to cell-type-specific loops. RESULTS We propose SSSHiC, a new loop calling algorithm based on significance in scale space, which can be used to understand data at different levels of resolution. By applying SSSHiC to neuronal and glial Hi-C data, we detected more loops that are potentially engaged in cell-type-specific gene regulation. Compared with other loop callers, such as Mustache, these loops were more frequently anchored to gene promoters of cellular marker genes and had better APA scores. Therefore, our results suggest that SSSHiC can effectively capture loops that contain more gene regulatory information. AVAILABILITY AND IMPLEMENTATION The Hi-C data used in this study can be accessed through the PsychENCODE Knowledge Portal at https://www.synapse.org/#! Synapse: syn21760712. The code utilized for Curvature SSS cited in this study is available at https://github.com/jsmarron/MarronMatlabSoftware/blob/master/Matlab9/Matlab9Combined.zip. All custom code used in this research can be found in the GitHub repository: https://github.com/jerryliu01998/HiC. The code has also been submitted to Code Ocean with the doi: 10.24433/CO.1912913.v1.
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Affiliation(s)
- Rui Liu
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Zhengwu Zhang
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Hyejung Won
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - J S Marron
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
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5
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Yoshihara M, Coschiera A, Bachmann JA, Pucci M, Li H, Bhagat S, Murakawa Y, Weltner J, Jouhilahti EM, Swoboda P, Sahlén P, Kere J. Transcriptional enhancers in human neuronal differentiation provide clues to neuronal disorders. EMBO Rep 2025; 26:1212-1237. [PMID: 39948187 PMCID: PMC11893885 DOI: 10.1038/s44319-025-00372-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2024] [Revised: 12/28/2024] [Accepted: 01/09/2025] [Indexed: 03/12/2025] Open
Abstract
Genome-wide association studies (GWASs) have identified thousands of variants associated with complex phenotypes, including neuropsychiatric disorders. To better understand their pathogenesis, it is necessary to identify the functional roles of these variants, which are largely located in non-coding DNA regions. Here, we employ a human mesencephalic neuronal cell differentiation model, LUHMES, with sensitive and high-resolution methods to discover enhancers (NET-CAGE), perform DNA conformation analysis (Capture Hi-C) to link enhancers to their target genes, and finally validate selected interactions. We expand the number of known enhancers active in differentiating human LUHMES neurons to 47,350, and find overlap with GWAS variants for Parkinson's disease and schizophrenia. Our findings reveal a fine-tuned regulation of human neuronal differentiation, even between adjacent developmental stages; provide a valuable resource for further studies on neuronal development, regulation, and disorders; and emphasize the importance of exploring the vast regulatory potential of non-coding DNA and enhancers.
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Affiliation(s)
- Masahito Yoshihara
- Department of Medicine Huddinge (MedH), Biosciences and Nutrition Unit, Karolinska Institutet, Stockholm, Sweden
- Institute for Advanced Academic Research, Chiba University, Chiba, Japan
- Department of Artificial Intelligence Medicine, Graduate School of Medicine, Chiba University, Chiba, Japan
- Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Suita, Osaka, Japan
| | - Andrea Coschiera
- Department of Medicine Huddinge (MedH), Biosciences and Nutrition Unit, Karolinska Institutet, Stockholm, Sweden
| | - Jörg A Bachmann
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Mariangela Pucci
- Department of Medicine Huddinge (MedH), Biosciences and Nutrition Unit, Karolinska Institutet, Stockholm, Sweden
- Department of Bioscience and Technology for Food, Agriculture and Environment, University of Teramo, Teramo, Italy
| | - Haonan Li
- Department of Medicine Huddinge (MedH), Biosciences and Nutrition Unit, Karolinska Institutet, Stockholm, Sweden
| | - Shruti Bhagat
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
| | - Yasuhiro Murakawa
- Institute for the Advanced Study of Human Biology, Kyoto University, Kyoto, Japan
- RIKEN-IFOM Joint Laboratory for Cancer Genomics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
- IFOM - the FIRC Institute of Molecular Oncology, Milan, Italy
- Department of Medical Systems Genomics, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Jere Weltner
- Folkhälsan Research Centre, Helsinki, Finland
- Stem Cells and Metabolism Research Program, University of Helsinki, Helsinki, Finland
| | - Eeva-Mari Jouhilahti
- Folkhälsan Research Centre, Helsinki, Finland
- Stem Cells and Metabolism Research Program, University of Helsinki, Helsinki, Finland
| | - Peter Swoboda
- Department of Medicine Huddinge (MedH), Biosciences and Nutrition Unit, Karolinska Institutet, Stockholm, Sweden.
| | - Pelin Sahlén
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden.
| | - Juha Kere
- Department of Medicine Huddinge (MedH), Biosciences and Nutrition Unit, Karolinska Institutet, Stockholm, Sweden.
- Folkhälsan Research Centre, Helsinki, Finland.
- Stem Cells and Metabolism Research Program, University of Helsinki, Helsinki, Finland.
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6
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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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7
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Du L, Farooq H, Delafrouz P, Liang J. Structural basis of differential gene expression at eQTLs loci from high-resolution ensemble models of 3D single-cell chromatin conformations. Bioinformatics 2025; 41:btaf050. [PMID: 39891345 PMCID: PMC11835231 DOI: 10.1093/bioinformatics/btaf050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2024] [Revised: 12/18/2024] [Accepted: 01/29/2025] [Indexed: 02/03/2025] Open
Abstract
MOTIVATION Techniques such as high-throughput chromosome conformation capture (Hi-C) have provided a wealth of information on nucleus organization and genome important for understanding gene expression regulation. Genome-Wide Association Studies have identified numerous loci associated with complex traits. Expression quantitative trait loci (eQTL) studies have further linked the genetic variants to alteration in expression levels of associated target genes across individuals. However, the functional roles of many eQTLs in noncoding regions remain unclear. Current joint analyses of Hi-C and eQTLs data lack advanced computational tools, limiting what can be learned from these data. RESULTS We developed a computational method for simultaneous analysis of Hi-C and eQTL data, capable of identifying a small set of nonrandom interactions from all Hi-C interactions. Using these nonrandom interactions, we reconstructed large ensembles (×105) of high-resolution single-cell 3D chromatin conformations with thorough sampling, accurately replicating Hi-C measurements. Our results revealed many-body interactions in chromatin conformation at the single-cell level within eQTL loci, providing a detailed view of how 3D chromatin structures form the physical foundation for gene regulation, including how genetic variants of eQTLs affect the expression of associated eGenes. Furthermore, our method can deconvolve chromatin heterogeneity and investigate the spatial associations of eQTLs and eGenes at subpopulation level, revealing their regulatory impacts on gene expression. Together, ensemble modeling of thoroughly sampled single-cell chromatin conformations combined with eQTL data, helps decipher how 3D chromatin structures provide the physical basis for gene regulation, expression control, and aid in understanding the overall structure-function relationships of genome organization. AVAILABILITY AND IMPLEMENTATION It is available at https://github.com/uic-liang-lab/3DChromFolding-eQTL-Loci.
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Affiliation(s)
- Lin Du
- Center for Bioinformatics and Quantitative Biology, Richard and Loan Hill Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60612, United States
| | - Hammad Farooq
- Center for Bioinformatics and Quantitative Biology, Richard and Loan Hill Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60612, United States
| | - Pourya Delafrouz
- Center for Bioinformatics and Quantitative Biology, Richard and Loan Hill Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60612, United States
| | - Jie Liang
- Center for Bioinformatics and Quantitative Biology, Richard and Loan Hill Department of Biomedical Engineering, University of Illinois at Chicago, Chicago, IL 60612, United States
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8
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Su Z, Tian M, Shibata E, Shibata Y, Yang T, Wang Z, Jin F, Zang C, Dutta A. Regulation of epigenetics and chromosome structure by human ORC2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2024.12.18.629220. [PMID: 39829907 PMCID: PMC11741241 DOI: 10.1101/2024.12.18.629220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2025]
Abstract
The six subunit Origin Recognition Complex (ORC) is a DNA replication initiator that also promotes heterochromatinization in some species. A multi-omics study in a human cell line with mutations in three subunits of ORC, reveals that the subunits bind to DNA independent of each other rather than as part of a common six-subunit ORC. While DNA-bound ORC2 was seen to compact chromatin and attract repressive histone marks, the activation of chromatin and protection from repressive marks was seen at a large number of sites. The epigenetic changes regulate hundreds of genes, including some epigenetic regulators, adding an indirect mechanism by which ORC2 regulates epigenetics without local binding. DNA-bound ORC2 also prevents the acquisition of CTCF at focal sites in the genome to regulate chromatin loops. Thus, individual ORC subunits are major regulators, in both directions, of epigenetics, gene expression and chromosome structure, independent of the role of ORC in replication.
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9
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Zhegalova I, Ulianov S, Galitsyna A, Pletenev I, Tsoy O, Luzhin A, Vasiluev P, Bulavko E, Ivankov D, Gavrilov A, Khrameeva E, Gelfand M, Razin S. Convergent pairs of highly transcribed genes restrict chromatin looping in Dictyostelium discoideum. Nucleic Acids Res 2025; 53:gkaf006. [PMID: 39844457 PMCID: PMC11754127 DOI: 10.1093/nar/gkaf006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2024] [Revised: 12/25/2024] [Accepted: 01/06/2025] [Indexed: 01/24/2025] Open
Abstract
Dictyostelium discoideum is a unicellular slime mold, developing into a multicellular fruiting body upon starvation. Development is accompanied by large-scale shifts in gene expression program, but underlying features of chromatin spatial organization remain unknown. Here, we report that the Dictyostelium 3D genome is organized into positionally conserved, largely consecutive, non-hierarchical and weakly insulated loops at the onset of multicellular development. The transcription level within the loop interior tends to be higher than in adjacent regions. Loop interiors frequently contain functionally linked genes and genes which coherently change expression level during development. Loop anchors are predominantly positioned by the genes in convergent orientation. Results of polymer simulations and Hi-C-based observations suggest that the loop profile may arise from the interplay between transcription and extrusion-driven chromatin folding. In this scenario, a convergent gene pair serves as a bidirectional extrusion barrier or a 'diode' that controls passage of the cohesin extruder by relative transcription level of paired genes.
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Affiliation(s)
- Irina V Zhegalova
- Laboratory of Structural and Functional Organization of Chromosomes, Institute of Gene Biology, Russian Academy of Sciences, 34/5 Vavilov St., 119334 Moscow, Russia
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard, 30, bld. 1, 121205 Moscow, Russia
| | - Sergey V Ulianov
- Laboratory of Structural and Functional Organization of Chromosomes, Institute of Gene Biology, Russian Academy of Sciences, 34/5 Vavilov St., 119334 Moscow, Russia
- Department of Molecular Biology, Faculty of Biology, M.V. Lomonosov Moscow State University, Leninskie gory, 1, bld. 12, 119991 Moscow, Russia
| | - Aleksandra A Galitsyna
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard, 30, bld. 1, 121205 Moscow, Russia
| | - Ilya A Pletenev
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard, 30, bld. 1, 121205 Moscow, Russia
| | - Olga V Tsoy
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard, 30, bld. 1, 121205 Moscow, Russia
| | - Artem V Luzhin
- Laboratory of Structural and Functional Organization of Chromosomes, Institute of Gene Biology, Russian Academy of Sciences, 34/5 Vavilov St., 119334 Moscow, Russia
| | - Petr A Vasiluev
- Research Centre for Medical Genetics, 1 Moskvorechye St., 115522 Moscow, Russia
| | - Egor S Bulavko
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard, 30, bld. 1, 121205 Moscow, Russia
- Laboratory of Bioelectrochemistry, A.N. Frumkin Institute of Physical Chemistry and Electrochemistry, Russian Academy of Sciences, 31/4 Leninskiy Prospekt, 119071 Moscow, Russia
| | - Dmitry N Ivankov
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard, 30, bld. 1, 121205 Moscow, Russia
| | - Alexey A Gavrilov
- Laboratory of Structural and Functional Organization of Chromosomes, Institute of Gene Biology, Russian Academy of Sciences, 34/5 Vavilov St., 119334 Moscow, Russia
| | - Ekaterina E Khrameeva
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard, 30, bld. 1, 121205 Moscow, Russia
| | - Mikhail S Gelfand
- Center for Molecular and Cellular Biology, Skolkovo Institute of Science and Technology, Bolshoy Boulevard, 30, bld. 1, 121205 Moscow, Russia
| | - Sergey V Razin
- Laboratory of Structural and Functional Organization of Chromosomes, Institute of Gene Biology, Russian Academy of Sciences, 34/5 Vavilov St., 119334 Moscow, Russia
- Department of Molecular Biology, Faculty of Biology, M.V. Lomonosov Moscow State University, Leninskie gory, 1, bld. 12, 119991 Moscow, Russia
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10
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Sun C, Zhao Y, Guo L, Qiu J, Peng Q. The interplay between histone modifications and nuclear lamina in genome regulation. J Genet Genomics 2025; 52:24-38. [PMID: 39426590 DOI: 10.1016/j.jgg.2024.10.005] [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: 06/19/2024] [Revised: 10/08/2024] [Accepted: 10/09/2024] [Indexed: 10/21/2024]
Abstract
Gene expression is regulated by chromatin architecture and epigenetic remodeling in cell homeostasis and pathologies. Histone modifications act as the key factors to modulate the chromatin accessibility. Different histone modifications are strongly associated with the localization of chromatin. Heterochromatin primarily localizes at the nuclear periphery, where it interacts with lamina proteins to suppress gene expression. In this review, we summarize the potential bridges that have regulatory functions of histone modifications in chromatin organization and transcriptional regulation at the nuclear periphery. We use lamina-associated domains (LADs) as examples to elucidate the biological roles of the interactions between histone modifications and nuclear lamina in cell differentiation and development. In the end, we highlight the technologies that are currently used to identify and visualize histone modifications and LADs, which could provide spatiotemporal information for understanding their regulatory functions in gene expression and discovering new targets for diseases.
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Affiliation(s)
- Chang Sun
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518132, China; Faculty of Medicine and Health Sciences, Barcelona University, Barcelona, Spain
| | - Yanjing Zhao
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518132, China; Division of Life Science, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Liping Guo
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518132, China; School of Biology and Biological Engineering, South China University of Technology, Guangzhou, Guangdong 510006, China
| | - Juhui Qiu
- Key Laboratory for Biorheological Science and Technology of Ministry of Education, State and Local Joint Engineering Laboratory for Vascular Implants, College of Bioengineering, Chongqing University, Chongqing 400030, China.
| | - Qin Peng
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen 518132, China.
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11
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Aherrahrou R, Kaikkonen MU. Technological advancements in functional interpretation of genome-wide association studies (GWAS) findings: bridging the gap to clinical translation. FEBS Lett 2024; 598:2852-2853. [PMID: 38683017 PMCID: PMC11627003 DOI: 10.1002/1873-3468.14884] [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: 09/07/2023] [Revised: 11/17/2023] [Accepted: 12/16/2023] [Indexed: 05/01/2024]
Abstract
Genome-wide association studies (GWAS) significantly advanced our understanding of the genetic underpinnings of diseases. However, challenges persist, particularly in interpreting non-coding variants in linkage disequilibrium that affect genes in disease-relevant cells. Addressing key obstacles-identifying causal variants, uncovering target genes, and understanding their network impact-is crucial. This graphical review navigates advanced techniques to fully leverage GWAS for future therapeutic breakthroughs.
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Affiliation(s)
- Redouane Aherrahrou
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Finland
- Institute for Cardiogenetics, Universität zu Lübeck; DZHK (German Centre for Cardiovascular Research), Partner Site Hamburg/Kiel/Lübeck, Germany; University Heart Centre Lübeck, 23562, Lübeck, Germany
| | - Minna U Kaikkonen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Finland
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12
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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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13
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Ahmed N, Cavattoni I, Villiers W, Cugno C, Deola S, Mifsud B. Multi-omic analysis of longitudinal acute myeloid leukemia patient samples reveals potential prognostic markers linked to disease progression. Front Genet 2024; 15:1442539. [PMID: 39399221 PMCID: PMC11466779 DOI: 10.3389/fgene.2024.1442539] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2024] [Accepted: 09/09/2024] [Indexed: 10/15/2024] Open
Abstract
Relapse remains a determinant of treatment failure and contributes significantly to mortality in acute myeloid leukemia (AML) patients. Despite efforts to understand AML progression and relapse mechanisms, findings on acquired gene mutations in relapse vary, suggesting inherent genetic heterogeneity and emphasizing the role of epigenetic modifications. We conducted a multi-omic analysis using Omni-C, ATAC-seq, and RNA-seq on longitudinal samples from two adult AML patients at diagnosis and relapse. Herein, we characterized genetic and epigenetic changes in AML progression to elucidate the underlying mechanisms of relapse. Differential interaction analysis showed significant 3D chromatin landscape reorganization between relapse and diagnosis samples. Comparing global open chromatin profiles revealed that relapse samples had significantly fewer accessible chromatin regions than diagnosis samples. In addition, we discovered that relapse-related upregulation was achieved either by forming new active enhancer contacts or by losing interactions with poised enhancers/potential silencers. Altogether, our study highlights the impact of genetic and epigenetic changes on AML progression, underlining the importance of multi-omic approaches in understanding disease relapse mechanisms and guiding potential therapeutic interventions.
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Affiliation(s)
- Nisar Ahmed
- College of Health and Life Sciences, Genomics and Precision Medicine, Hamad Bin Khalifa University, Doha, Qatar
| | - Irene Cavattoni
- Hematology and Bone Marrow Transplant Unit, Ospedale Centrale Bolzano, Bolzano, Italy
| | - William Villiers
- College of Health and Life Sciences, Genomics and Precision Medicine, Hamad Bin Khalifa University, Doha, Qatar
- Department of Medical and Molecular Genetics, King’s College London, London, United Kingdom
| | - Chiara Cugno
- Advanced Cell Therapy Core, Research, Sidra Medicine, Doha, Qatar
| | - Sara Deola
- Advanced Cell Therapy Core, Research, Sidra Medicine, Doha, Qatar
| | - Borbala Mifsud
- College of Health and Life Sciences, Genomics and Precision Medicine, Hamad Bin Khalifa University, Doha, Qatar
- William Harvey Research Institute, Queen Mary University London, London, United Kingdom
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14
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Strom AR, Kim Y, Zhao H, Chang YC, Orlovsky ND, Košmrlj A, Storm C, Brangwynne CP. Condensate interfacial forces reposition DNA loci and probe chromatin viscoelasticity. Cell 2024; 187:5282-5297.e20. [PMID: 39168125 DOI: 10.1016/j.cell.2024.07.034] [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: 02/27/2023] [Revised: 04/22/2024] [Accepted: 07/19/2024] [Indexed: 08/23/2024]
Abstract
Biomolecular condensates assemble in living cells through phase separation and related phase transitions. An underappreciated feature of these dynamic molecular assemblies is that they form interfaces with other cellular structures, including membranes, cytoskeleton, DNA and RNA, and other membraneless compartments. These interfaces are expected to give rise to capillary forces, but there are few ways of quantifying and harnessing these forces in living cells. Here, we introduce viscoelastic chromatin tethering and organization (VECTOR), which uses light-inducible biomolecular condensates to generate capillary forces at targeted DNA loci. VECTOR can be utilized to programmably reposition genomic loci on a timescale of seconds to minutes, quantitatively revealing local heterogeneity in the viscoelastic material properties of chromatin. These synthetic condensates are built from components that naturally form liquid-like structures in living cells, highlighting the potential role for native condensates to generate forces and do work to reorganize the genome and impact chromatin architecture.
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Affiliation(s)
- Amy R Strom
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA
| | - Yoonji Kim
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
| | - Hongbo Zhao
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA; Department of Mechanical and Aerospace Engineering, Princeton, NJ 08544, USA; Omenn-Darling Bioengineering Institute, Princeton University, Princeton, NJ 08544, USA
| | - Yi-Che Chang
- Department of Chemistry, Princeton University, Princeton, NJ 08544, USA
| | - Natalia D Orlovsky
- Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA
| | - Andrej Košmrlj
- Department of Mechanical and Aerospace Engineering, Princeton, NJ 08544, USA; Omenn-Darling Bioengineering Institute, Princeton University, Princeton, NJ 08544, USA; Princeton Materials Institute, Princeton University, Princeton, NJ 08544, USA
| | - Cornelis Storm
- Eindhoven University of Technology, Department of Applied Physics and Science Education, Eindhoven, the Netherlands
| | - Clifford P Brangwynne
- Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ 08544, USA; Omenn-Darling Bioengineering Institute, Princeton University, Princeton, NJ 08544, USA; Princeton Materials Institute, Princeton University, Princeton, NJ 08544, USA; Howard Hughes Medical Institute, Chevy Chase, MD 21044, USA.
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15
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Shao L, Yu H, Wang M, Chen L, Ji B, Wu T, Teng X, Su M, Han X, Shi W, Hu X, Wang Z, He H, Han G, Zhang Y, Wu Q. DKK1-SE recruits AP1 to activate the target gene DKK1 thereby promoting pancreatic cancer progression. Cell Death Dis 2024; 15:566. [PMID: 39107271 PMCID: PMC11303742 DOI: 10.1038/s41419-024-06915-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 07/15/2024] [Accepted: 07/16/2024] [Indexed: 08/09/2024]
Abstract
Super-enhancers are a class of DNA cis-regulatory elements that can regulate cell identity, cell fate, stem cell pluripotency, and even tumorigenesis. Increasing evidence shows that epigenetic modifications play an important role in the pathogenesis of various types of cancer. However, the current research is far from enough to reveal the complex mechanism behind it. This study found a super-enhancer enriched with abnormally active histone modifications in pancreatic ductal adenocarcinoma (PDAC), called DKK1-super-enhancer (DKK1-SE). The major active component of DKK1-SE is component enhancer e1. Mechanistically, AP1 induces chromatin remodeling in component enhancer e1 and activates the transcriptional activity of DKK1. Moreover, DKK1 was closely related to the malignant clinical features of PDAC. Deletion or knockdown of DKK1-SE significantly inhibited the proliferation, colony formation, motility, migration, and invasion of PDAC cells in vitro, and these phenomena were partly mitigated upon rescuing DKK1 expression. In vivo, DKK1-SE deficiency not only inhibited tumor proliferation but also reduced the complexity of the tumor microenvironment. This study identifies that DKK1-SE drives DKK1 expression by recruiting AP1 transcription factors, exerting oncogenic effects in PDAC, and enhancing the complexity of the tumor microenvironment.
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Affiliation(s)
- Lan Shao
- School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, China
| | - Haoran Yu
- School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, China
| | - Mengyun Wang
- School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, China
| | - Lu Chen
- Department of Pathology, the Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Boshu Ji
- Department of Pathology, the Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Tong Wu
- School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, China
| | - Xiangqi Teng
- School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, China
| | - Mu Su
- School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, China
| | - Xiao Han
- School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, China
| | - Weikai Shi
- School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, China
| | - Xin Hu
- School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, China
| | - Ziwen Wang
- School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, China
| | - Hongjuan He
- School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, China
| | - Guiping Han
- Department of Pathology, the Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Yan Zhang
- School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, China
| | - Qiong Wu
- School of Life Science and Technology, State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin, China.
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16
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Ray NR, Kunkle BW, Hamilton‐Nelson K, Kurup JT, Rajabli F, Qiao M, Vardarajan BN, Cosacak MI, Kizil C, Jean‐Francois M, Cuccaro M, Reyes‐Dumeyer D, Cantwell L, Kuzma A, Vance JM, Gao S, Hendrie HC, Baiyewu O, Ogunniyi A, Akinyemi RO, Alzheimer's Disease Genetics Consortium, Lee W, Martin ER, Wang L, Beecham GW, Bush WS, Xu W, Jin F, Wang L, Farrer LA, Haines JL, Byrd GS, Schellenberg GD, Mayeux R, Pericak‐Vance MA, Reitz C. Extended genome-wide association study employing the African genome resources panel identifies novel susceptibility loci for Alzheimer's disease in individuals of African ancestry. Alzheimers Dement 2024; 20:5247-5261. [PMID: 38958117 PMCID: PMC11350055 DOI: 10.1002/alz.13880] [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: 09/20/2023] [Revised: 04/03/2024] [Accepted: 04/12/2024] [Indexed: 07/04/2024]
Abstract
INTRODUCTION Despite a two-fold risk, individuals of African ancestry have been underrepresented in Alzheimer's disease (AD) genomics efforts. METHODS Genome-wide association studies (GWAS) of 2,903 AD cases and 6,265 controls of African ancestry. Within-dataset results were meta-analyzed, followed by functional genomics analyses. RESULTS A novel AD-risk locus was identified in MPDZ on chromosome (chr) 9p23 (rs141610415, MAF = 0.002, p = 3.68×10-9). Two additional novel common and nine rare loci were identified with suggestive associations (P < 9×10-7). Comparison of association and linkage disequilibrium (LD) patterns between datasets with higher and lower degrees of African ancestry showed differential association patterns at chr12q23.2 (ASCL1), suggesting that this association is modulated by regional origin of local African ancestry. DISCUSSION These analyses identified novel AD-associated loci in individuals of African ancestry and suggest that degree of African ancestry modulates some associations. Increased sample sets covering as much African genetic diversity as possible will be critical to identify additional loci and deconvolute local genetic ancestry effects. HIGHLIGHTS Genetic ancestry significantly impacts risk of Alzheimer's Disease (AD). Although individuals of African ancestry are twice as likely to develop AD, they are vastly underrepresented in AD genomics studies. The Alzheimer's Disease Genetics Consortium has previously identified 16 common and rare genetic loci associated with AD in African American individuals. The current analyses significantly expand this effort by increasing the sample size and extending ancestral diversity by including populations from continental Africa. Single variant meta-analysis identified a novel genome-wide significant AD-risk locus in individuals of African ancestry at the MPDZ gene, and 11 additional novel loci with suggestive genome-wide significance at p < 9×10-7. Comparison of African American datasets with samples of higher degree of African ancestry demonstrated differing patterns of association and linkage disequilibrium at one of these loci, suggesting that degree and/or geographic origin of African ancestry modulates the effect at this locus. These findings illustrate the importance of increasing number and ancestral diversity of African ancestry samples in AD genomics studies to fully disentangle the genetic architecture underlying AD, and yield more effective ancestry-informed genetic screening tools and therapeutic interventions.
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Grants
- P30 AG013854 NIA NIH HHS
- International Parkinson Fonds
- P50 MH060451 NIMH NIH HHS
- P30 AG066444 NIA NIH HHS
- R01 AG28786-01A1 North Carolina A&T University
- U01AG46161 NIA NIH HHS
- AG05128 Duke University
- Medical Research Council
- U01AG057659 NIH HHS
- R01 DK131437 NIDDK NIH HHS
- R01 AG022374 NIA NIH HHS
- U19 AG074865 NIA NIH HHS
- P50 AG023501 NIA NIH HHS
- U01 AG046152 NIA NIH HHS
- P30 AG010124 NIA NIH HHS
- U01 HG006375 NHGRI NIH HHS
- Biogen
- U01 AG058654 NIA NIH HHS
- NIMH MH60451 NINDS NIH HHS
- U54 AG052427 NIA NIH HHS
- P30 AG066518 NIA NIH HHS
- UO1 HG004610 Group Health Research Institute
- RC2 AG036528 NIA NIH HHS
- P30 AG028377 NIA NIH HHS
- R01AG048927 NIH HHS
- UO1 HG006375 Group Health Research Institute
- R01 AG22018 Rush University
- U01AG46152 NIA NIH HHS
- P50 AG008671 NIA NIH HHS
- P30 AG10133 Indiana University
- P50 AG005142 NIA NIH HHS
- U01 AG10483 Boston University
- Higher Education Funding Council for England
- R01 AG035137 NIA NIH HHS
- R01 AG009029 NIA NIH HHS
- P50 AG005131 NIA NIH HHS
- P50 AG005128 NIA NIH HHS
- P30 AG010133 NIA NIH HHS
- U24 AG021886 NIA NIH HHS
- R01 AG031581 NIA NIH HHS
- 5R01AG012101 New York University
- R01 AG009956 NIA NIH HHS
- P50 AG016574 NIA NIH HHS
- P50 AG005146 NIA NIH HHS
- U01AG058654 NIH HHS
- AG025688 Emory University
- P30AG10161 NIA NIH HHS
- Alzheimer's Drug Discovery Foundation
- U01 AG061356 NIA NIH HHS
- RC2 AG036650 NIA NIH HHS
- Servier
- Janssen Alzheimer Immunotherapy Research & Development, LLC.
- U01 AG032984 NIA NIH HHS
- U01 HG008657 NHGRI NIH HHS
- Brain Net Europe
- R01 AG019085 NIA NIH HHS
- Lumosity
- R01 AG013616 NIA NIH HHS
- U01 AG024904 NIA NIH HHS
- R01 HG012384 NHGRI NIH HHS
- Translational Genomics Research Institute
- P50 AG008702 NIA NIH HHS
- Bristol-Myers Squibb Company
- R01 AG030146 NIA NIH HHS
- R01AG041797 NIA FBS (Columbia University)
- U01 AG072579 NIA NIH HHS
- Piramal Imaging
- DeNDRoN
- UL1 RR029893 NCRR NIH HHS
- Takeda Pharmaceutical Company
- 1R01AG035137 New York University
- R01 AG15819 Rush University
- R01AG30146 NIA NIH HHS
- R01AG15819 NIA NIH HHS
- P50 NS039764 NINDS NIH HHS
- P01 AG003991 NIA NIH HHS
- Office of Research and Development
- Genentech, Inc.
- U01 AG016976 NIA NIH HHS
- US Department of Veterans Affairs Administration
- P30 AG008051 NIA NIH HHS
- P50 AG005681 NIA NIH HHS
- P30 AG013846 NIA NIH HHS
- U24 AG056270 NIA NIH HHS
- RC2 AG036502 NIA NIH HHS
- P01 AG026276 NIA NIH HHS
- R01 AG017917 NIA NIH HHS
- Araclon Biotech
- U01 AG057659 NIA NIH HHS
- R01 MH080295 NIMH NIH HHS
- Hersenstichting Nederland Breinbrekend Werk
- R01 CA267872 NCI NIH HHS
- R01 AG026390 NIA NIH HHS
- R01 AG028786 NIA NIH HHS
- KL2 RR024151 NCRR NIH HHS
- Internationale Stiching Alzheimer Onderzoek
- P30AG066462 NIH HHS
- U24 AG026390 NIA FBS (Columbia University)
- Novartis Pharmaceuticals Corporation
- P50 AG005136 NIA NIH HHS
- Meso Scale Diagnostics, LLC.
- CereSpir, Inc.
- P30 AG012300 NIA NIH HHS
- P01 AG03991 University of Washington
- RF1AG059018 NIH HHS
- Canadian Institute of Health Research
- RF1 AG059018 NIA NIH HHS
- BioClinica, Inc.
- UG3 NS132061 NINDS NIH HHS
- U01 AG062943 NIA NIH HHS
- R01 AG012101 NIA NIH HHS
- GE Healthcare
- P50 AG016573 NIA NIH HHS
- U24 AG21886 National Cell Repository for Alzheimer's Disease (NCRAD)
- P50 AG016570 NIA NIH HHS
- P50 AG005134 NIA NIH HHS
- P30 AG066462 NIA NIH HHS
- Stichting MS Research
- P30 AG008017 NIA NIH HHS
- R01AG33193 Boston University
- Howard Hughes Medical Institute
- R01 AG042437 NIA NIH HHS
- U24 AG041689 NIA NIH HHS
- P01 AG019724 NIA NIH HHS
- R01AG36042 NIA NIH HHS
- RC2AG036547 NIA NIH HHS
- R01 AG036042 NIA NIH HHS
- P30 AG010161 NIA NIH HHS
- AG019757 University of Miami
- Kronos Science
- P30 AG08051 New York University
- IIRG-05-14147 Alzheimer's Association
- AG010491 University of Miami
- R01 AG033193 NIA NIH HHS
- P50 AG025688 NIA NIH HHS
- IIRG-08-89720 Alzheimer's Association
- AbbVie
- R37 AG015473 NIA NIH HHS
- U24 AG026395 NIA NIH HHS
- R01 AG032990 NIA NIH HHS
- North Bristol NHS Trust Research and Innovation Department
- AG021547 University of Miami
- R01 AG01101 Rush University
- Transition Therapeutics
- R01 AG072547 NIA NIH HHS
- AG027944 University of Miami
- AG041232 NIA NIH HHS
- A2111048 BrightFocus Foundation
- U01 AG052410 NIA NIH HHS
- Johnson & Johnson Pharmaceutical Research & Development LLC.
- R01 CA129769 NCI NIH HHS
- P50 AG005133 NIA NIH HHS
- U01 AG010483 NIA NIH HHS
- UO1 AG006781 Group Health Research Institute
- Merck & Co., Inc.
- U01AG32984 NIA NIH HHS
- U01 AG024904 NIH HHS
- RC2 AG036547 NIA NIH HHS
- P01 AG002219 NIA NIH HHS
- R01 AG17917 Rush University
- U01 AG006781 NIA NIH HHS
- R01 AG041797 NIA NIH HHS
- NIBIB NIH HHS
- P01 AG010491 NIA NIH HHS
- P50 AG005144 NIA NIH HHS
- U01AG062943 NIH HHS
- R01 AG064614 NIA NIH HHS
- Glaxo Smith Kline
- U01AG072579 NIH HHS
- Biomedical Laboratory Research Program
- U19AG074865 NIH HHS
- R01 AG048927 NIA NIH HHS
- RF1 AG057473 NIA NIH HHS
- R01 AG037212 NIA NIH HHS
- R01 AG022018 NIA NIH HHS
- U24AG056270 NIH HHS
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- R01 AG041232 NIA NIH HHS
- P50 AG005138 NIA NIH HHS
- RF1AG57473 NIA NIH HHS
- R01 AG019757 NIA NIH HHS
- R01 AG020688 NIA NIH HHS
- AG07562 University of Pittsburgh
- R01AG072547 NIH HHS
- Alzheimer's Research Trust
- Pfizer Inc.
- Illinois Department of Public Health
- Elan Pharmaceuticals, Inc.
- NHS trusts
- R01 AG030653 NIA NIH HHS
- R01 HG009658 NHGRI NIH HHS
- AG052410 NIA NIH HHS
- P20 MD000546 NIMHD NIH HHS
- R01 AG027944 NIA NIH HHS
- Eli Lilly and Company
- R01 AG017173 NIA NIH HHS
- R01 AG025259 NIA NIH HHS
- U01 HG004610 NHGRI NIH HHS
- U24-AG041689 University of Pennsylvania
- P30 AG010129 NIA NIH HHS
- U01 AG046161 NIA NIH HHS
- Wellcome Trust
- P30 AG019610 NIA NIH HHS
- IXICO Ltd.
- P50 AG016582 NIA NIH HHS
- R01 AG048015 NIA NIH HHS
- NeuroRx Research
- R01AG17917 NIA NIH HHS
- U01AG61356 NIA NIH HHS
- R01AG36836 NIA NIH HHS
- 5R01AG022374 New York University
- EuroImmun; F. Hoffmann-La Roche Ltd
- R01 AG041718 NIA NIH HHS
- 1RC2AG036502 New York University
- Newcastle University
- R01 AG072474 NIA NIH HHS
- AG041718 University of Pittsburgh
- P30 AG028383 NIA NIH HHS
- AG05144 University of Kentucky
- AG030653 University of Pittsburgh
- R01AG48015 NIA NIH HHS
- R01 AG026916 NIA NIH HHS
- P50 AG033514 NIA NIH HHS
- R01 NS059873 NINDS NIH HHS
- # NS39764 NINDS NIH HHS
- ADGC National Institutes of Health, National Institute on Aging (NIH-NIA)
- Neurotrack Technologies
- Fujirebio
- Lundbeck
- MP-V BrightFocus Foundation
- BRACE
- R01 AG015819 NIA NIH HHS
- R01 AG036836 NIA NIH HHS
- Eisai Inc.
- 5R01AG013616 New York University
- W81XWH-12-2-0012 Department of Defense
- R01AG064614 NIH HHS
- AG02365 University of Pittsburgh
- NIH
- University of Pennsylvania
- NACC
- Boston University
- Columbia University
- Duke University
- Emory University
- Indiana University
- Johns Hopkins University
- Massachusetts General Hospital
- Mayo Clinic
- New York University
- Northwestern University
- Oregon Health & Science University
- Rush University
- NIA
- University of Alabama at Birmingham
- University of Arizona
- University of California, Davis
- University of California, Irvine
- University of California, Los Angeles
- University of California, San Diego
- University of California, San Francisco
- University of Kentucky
- University of Michigan
- University of Pittsburgh
- University of Southern California
- University of Miami
- University of Washington
- Vanderbilt University
- NINDS
- Alzheimer's Association
- Office of Research and Development
- BrightFocus Foundation
- Wellcome Trust
- Howard Hughes Medical Institute
- Medical Research Council
- Newcastle University
- Higher Education Funding Council for England
- Alzheimer's Research Trust
- BRACE
- Stichting MS Research
- Department of Defense
- National Institute of Biomedical Imaging and Bioengineering
- AbbVie
- Alzheimer's Drug Discovery Foundation
- BioClinica, Inc.
- Biogen
- Bristol‐Myers Squibb Company
- Eli Lilly and Company
- Genentech, Inc.
- Fujirebio
- GE Healthcare
- Lundbeck
- Merck & Co., Inc.
- Novartis Pharmaceuticals Corporation
- Pfizer Inc.
- Servier
- Takeda Pharmaceutical Company
- Illinois Department of Public Health
- Translational Genomics Research Institute
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17
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Lin G, Huang Z, Yue T, Chai J, Li Y, Yang H, Qin W, Yang G, Murphy RW, Zhang YP, Zhang Z, Zhou W, Luo J. Puzzle Hi-C: An accurate scaffolding software. PLoS One 2024; 19:e0298564. [PMID: 39008464 PMCID: PMC11249255 DOI: 10.1371/journal.pone.0298564] [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: 01/26/2024] [Accepted: 06/25/2024] [Indexed: 07/17/2024] Open
Abstract
High-quality, chromosome-scale genomes are essential for genomic analyses. Analyses, including 3D genomics, epigenetics, and comparative genomics rely on a high-quality genome assembly, which is often accomplished with the assistance of Hi-C data. Curation of genomes reveal that current Hi-C-assisted scaffolding algorithms either generate ordering and orientation errors or fail to assemble high-quality chromosome-level scaffolds. Here, we offer the software Puzzle Hi-C, which uses Hi-C reads to accurately assign contigs or scaffolds to chromosomes. Puzzle Hi-C uses the triangle region instead of the square region to count interactions in a Hi-C heatmap. This strategy dramatically diminishes scaffolding interference caused by long-range interactions. This software also introduces a dynamic, triangle window strategy during assembly. Initially small, the window expands with interactions to produce more effective clustering. Puzzle Hi-C outperforms available scaffolding tools.
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Affiliation(s)
- Guoliang Lin
- State Key Laboratory for Conservation and Utilization of Bio-resource, School of Ecology and Environment, School of Life Sciences and School of Medicine, Yunnan University, Kunming, Yunnan, China
| | - Zhiru Huang
- Department of Biology, University of Waterloo, Waterloo, ON, Canada
| | - Tingsong Yue
- State Key Laboratory for Conservation and Utilization of Bio-resource, School of Ecology and Environment, School of Life Sciences and School of Medicine, Yunnan University, Kunming, Yunnan, China
| | - Jing Chai
- State Key Laboratory for Conservation and Utilization of Bio-resource, School of Ecology and Environment, School of Life Sciences and School of Medicine, Yunnan University, Kunming, Yunnan, China
| | - Yan Li
- State Key Laboratory for Conservation and Utilization of Bio-resource, School of Ecology and Environment, School of Life Sciences and School of Medicine, Yunnan University, Kunming, Yunnan, China
| | - Huimin Yang
- State Key Laboratory for Conservation and Utilization of Bio-resource, School of Ecology and Environment, School of Life Sciences and School of Medicine, Yunnan University, Kunming, Yunnan, China
| | - Wanting Qin
- State Key Laboratory for Conservation and Utilization of Bio-resource, School of Ecology and Environment, School of Life Sciences and School of Medicine, Yunnan University, Kunming, Yunnan, China
| | - Guobing Yang
- State Key Laboratory for Conservation and Utilization of Bio-resource, School of Ecology and Environment, School of Life Sciences and School of Medicine, Yunnan University, Kunming, Yunnan, China
| | | | - Ya-ping Zhang
- State Key Laboratory for Conservation and Utilization of Bio-resource, School of Ecology and Environment, School of Life Sciences and School of Medicine, Yunnan University, Kunming, Yunnan, China
- Southwest United Graduate School, Yunnan University, Kunming, Yunnan, China
| | - Zijie Zhang
- State Key Laboratory for Conservation and Utilization of Bio-resource, School of Ecology and Environment, School of Life Sciences and School of Medicine, Yunnan University, Kunming, Yunnan, China
- Southwest United Graduate School, Yunnan University, Kunming, Yunnan, China
| | - Wei Zhou
- National Pilot School of Software, Yunnan University, Kunming, Yunnan, China
| | - Jing Luo
- State Key Laboratory for Conservation and Utilization of Bio-resource, School of Ecology and Environment, School of Life Sciences and School of Medicine, Yunnan University, Kunming, Yunnan, China
- Southwest United Graduate School, Yunnan University, Kunming, Yunnan, China
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18
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Zhao Y, Yang M, Gong F, Pan Y, Hu M, Peng Q, Lu L, Lyu X, Sun K. Accelerating 3D genomics data analysis with Microcket. Commun Biol 2024; 7:675. [PMID: 38824179 PMCID: PMC11144199 DOI: 10.1038/s42003-024-06382-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 05/24/2024] [Indexed: 06/03/2024] Open
Abstract
The three-dimensional (3D) organization of genome is fundamental to cell biology. To explore 3D genome, emerging high-throughput approaches have produced billions of sequencing reads, which is challenging and time-consuming to analyze. Here we present Microcket, a package for mapping and extracting interacting pairs from 3D genomics data, including Hi-C, Micro-C, and derivant protocols. Microcket utilizes a unique read-stitch strategy that takes advantage of the long read cycles in modern DNA sequencers; benchmark evaluations reveal that Microcket runs much faster than the current tools along with improved mapping efficiency, and thus shows high potential in accelerating and enhancing the biological investigations into 3D genome. Microcket is freely available at https://github.com/hellosunking/Microcket .
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Affiliation(s)
- Yu Zhao
- Molecular Cancer Research Center, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, 518107, China
| | - Mengqi Yang
- Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China
- Department of Chemical and Biological Engineering, Division of Life Science, Hong Kong University of Science and Technology, Hong Kong SAR, 999077, China
| | - Fanglei Gong
- Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China
| | - Yuqi Pan
- Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China
- Department of Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Minghui Hu
- Molecular Cancer Research Center, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, 518107, China
| | - Qin Peng
- Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen, 518132, China
| | - Leina Lu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Xiaowen Lyu
- State Key Laboratory of Cellular Stress Biology, Fujian Provincial Key Laboratory of Reproductive Health Research, Fujian Provincial Key Laboratory of Organ and Tissue Regeneration, School of Medicine, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, 361102, China
| | - Kun Sun
- Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China.
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19
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Xu W, Kim JS, Yang T, Ya A, Sadzewicz L, Tallon L, Harris BT, Sarkaria J, Jin F, Waldman T. STAG2 mutations regulate 3D genome organization, chromatin loops, and Polycomb signaling in glioblastoma multiforme. J Biol Chem 2024; 300:107341. [PMID: 38705393 PMCID: PMC11157269 DOI: 10.1016/j.jbc.2024.107341] [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: 02/14/2024] [Revised: 04/18/2024] [Accepted: 04/25/2024] [Indexed: 05/07/2024] Open
Abstract
Inactivating mutations of genes encoding the cohesin complex are common in a wide range of human cancers. STAG2 is the most commonly mutated subunit. Here we report the impact of stable correction of endogenous, naturally occurring STAG2 mutations on gene expression, 3D genome organization, chromatin loops, and Polycomb signaling in glioblastoma multiforme (GBM). In two GBM cell lines, correction of their STAG2 mutations significantly altered the expression of ∼10% of all expressed genes. Virtually all the most highly regulated genes were negatively regulated by STAG2 (i.e., expressed higher in STAG2-mutant cells), and one of them-HEPH-was regulated by STAG2 in uncultured GBM tumors as well. While STAG2 correction had little effect on large-scale features of 3D genome organization (A/B compartments, TADs), STAG2 correction did alter thousands of individual chromatin loops, some of which controlled the expression of adjacent genes. Loops specific to STAG2-mutant cells, which were regulated by STAG1-containing cohesin complexes, were very large, supporting prior findings that STAG1-containing cohesin complexes have greater loop extrusion processivity than STAG2-containing cohesin complexes and suggesting that long loops may be a general feature of STAG2-mutant cancers. Finally, STAG2 mutation activated Polycomb activity leading to increased H3K27me3 marks, identifying Polycomb signaling as a potential target for therapeutic intervention in STAG2-mutant GBM tumors. Together, these findings illuminate the landscape of STAG2-regulated genes, A/B compartments, chromatin loops, and pathways in GBM, providing important clues into the largely still unknown mechanism of STAG2 tumor suppression.
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Affiliation(s)
- Wanying Xu
- Department of Genetics and Genome Sciences, Case Comprehensive Cancer Center, Case Western Reserve School of Medicine, Cleveland, Ohio, USA; The Biomedical Sciences Training Program, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Jung-Sik Kim
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University School of Medicine, Washington, District of Columbia, USA
| | - Tianyi Yang
- Department of Genetics and Genome Sciences, Case Comprehensive Cancer Center, Case Western Reserve School of Medicine, Cleveland, Ohio, USA; The Biomedical Sciences Training Program, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Alvin Ya
- MD/PhD Program, Georgetown University School of Medicine, Washington, District of Columbia, USA; Tumor Biology Training Program, Georgetown University School of Medicine, Washington, District of Columbia, USA
| | - Lisa Sadzewicz
- Institute for Genome Sciences, University of Maryland, Baltimore, Maryland, USA
| | - Luke Tallon
- Institute for Genome Sciences, University of Maryland, Baltimore, Maryland, USA
| | - Brent T Harris
- Departments of Neurology and Pathology, Georgetown University School of Medicine, Washington, District of Columbia, USA
| | - Jann Sarkaria
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota, USA
| | - Fulai Jin
- Department of Genetics and Genome Sciences, Case Comprehensive Cancer Center, Case Western Reserve School of Medicine, Cleveland, Ohio, USA; Department of Computer and Data Sciences, Department of Population and Quantitative Health Sciences, Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, Ohio, USA.
| | - Todd Waldman
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University School of Medicine, Washington, District of Columbia, USA.
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20
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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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21
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Wu C, Huang J. Enhancer selectivity across cell types delineates three functionally distinct enhancer-promoter regulation patterns. BMC Genomics 2024; 25:483. [PMID: 38750461 PMCID: PMC11097474 DOI: 10.1186/s12864-024-10408-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 05/13/2024] [Indexed: 05/18/2024] Open
Abstract
BACKGROUND Multiple enhancers co-regulating the same gene is prevalent and plays a crucial role during development and disease. However, how multiple enhancers coordinate the same gene expression across various cell types remains largely unexplored at genome scale. RESULTS We develop a computational approach that enables the quantitative assessment of enhancer specificity and selectivity across diverse cell types, leveraging enhancer-promoter (E-P) interactions data. We observe two well-known gene regulation patterns controlled by enhancer clusters, which regulate the same gene either in a limited number of cell types (Specific pattern, Spe) or in the majority of cell types (Conserved pattern, Con), both of which are enriched for super-enhancers (SEs). We identify a previously overlooked pattern (Variable pattern, Var) that multiple enhancers link to the same gene, but rarely coexist in the same cell type. These three patterns control the genes associating with distinct biological function and exhibit unique epigenetic features. Specifically, we discover a subset of Var patterns contains Shared enhancers with stable enhancer-promoter interactions in the majority of cell types, which might contribute to maintaining gene expression by recruiting abundant CTCF. CONCLUSIONS Together, our findings reveal three distinct E-P regulation patterns across different cell types, providing insights into deciphering the complexity of gene transcriptional regulation.
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Affiliation(s)
- Chengyi Wu
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, 361102, Fujian, China
| | - Jialiang Huang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, 361102, Fujian, China.
- National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, Fujian, China.
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22
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Camerino M, Chang W, Cvekl A. Analysis of long-range chromatin contacts, compartments and looping between mouse embryonic stem cells, lens epithelium and lens fibers. Epigenetics Chromatin 2024; 17:10. [PMID: 38643244 PMCID: PMC11031936 DOI: 10.1186/s13072-024-00533-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 03/08/2024] [Indexed: 04/22/2024] Open
Abstract
BACKGROUND Nuclear organization of interphase chromosomes involves individual chromosome territories, "open" and "closed" chromatin compartments, topologically associated domains (TADs) and chromatin loops. The DNA- and RNA-binding transcription factor CTCF together with the cohesin complex serve as major organizers of chromatin architecture. Cellular differentiation is driven by temporally and spatially coordinated gene expression that requires chromatin changes of individual loci of various complexities. Lens differentiation represents an advantageous system to probe transcriptional mechanisms underlying tissue-specific gene expression including high transcriptional outputs of individual crystallin genes until the mature lens fiber cells degrade their nuclei. RESULTS Chromatin organization between mouse embryonic stem (ES) cells, newborn (P0.5) lens epithelium and fiber cells were analyzed using Hi-C. Localization of CTCF in both lens chromatins was determined by ChIP-seq and compared with ES cells. Quantitative analyses show major differences between number and size of TADs and chromatin loop size between these three cell types. In depth analyses show similarities between lens samples exemplified by overlaps between compartments A and B. Lens epithelium-specific CTCF peaks are found in mostly methylated genomic regions while lens fiber-specific and shared peaks occur mostly within unmethylated DNA regions. Major differences in TADs and loops are illustrated at the ~ 500 kb Pax6 locus, encoding the critical lens regulatory transcription factor and within a larger ~ 15 Mb WAGR locus, containing Pax6 and other loci linked to human congenital diseases. Lens and ES cell Hi-C data (TADs and loops) together with ATAC-seq, CTCF, H3K27ac, H3K27me3 and ENCODE cis-regulatory sites are shown in detail for the Pax6, Sox1 and Hif1a loci, multiple crystallin genes and other important loci required for lens morphogenesis. The majority of crystallin loci are marked by unexpectedly high CTCF-binding across their transcribed regions. CONCLUSIONS Our study has generated the first data on 3-dimensional (3D) nuclear organization in lens epithelium and lens fibers and directly compared these data with ES cells. These findings generate novel insights into lens-specific transcriptional gene control, open new research avenues to study transcriptional condensates in lens fiber cells, and enable studies of non-coding genetic variants linked to cataract and other lens and ocular abnormalities.
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Affiliation(s)
- Michael Camerino
- The Departments Genetics, Albert Einstein College of Medicine, NY10461, Bronx, USA
| | - William Chang
- Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, NY10461, Bronx, USA
| | - Ales Cvekl
- The Departments Genetics, Albert Einstein College of Medicine, NY10461, Bronx, USA.
- Ophthalmology and Visual Sciences, Albert Einstein College of Medicine, NY10461, Bronx, USA.
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23
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Casey C, Fullard JF, Sleator RD. Unravelling the genetic basis of Schizophrenia. Gene 2024; 902:148198. [PMID: 38266791 DOI: 10.1016/j.gene.2024.148198] [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: 09/01/2023] [Revised: 12/07/2023] [Accepted: 01/19/2024] [Indexed: 01/26/2024]
Abstract
Neuronal development is a highly regulated mechanism that is central to organismal function in animals. In humans, disruptions to this process can lead to a range of neurodevelopmental phenotypes, including Schizophrenia (SCZ). SCZ has a significant genetic component, whereby an individual with an SCZ affected family member is eight times more likely to develop the disease than someone with no family history of SCZ. By examining a combination of genomic, transcriptomic and epigenomic datasets, large-scale 'omics' studies aim to delineate the relationship between genetic variation and abnormal cellular activity in the SCZ brain. Herein, we provide a brief overview of some of the key omics methods currently being used in SCZ research, including RNA-seq, the assay for transposase-accessible chromatin with high-throughput sequencing (ATAC-seq) and high-throughput chromosome conformation capture (3C) approaches (e.g., Hi-C), as well as single-cell/nuclei iterations of these methods. We also discuss how these techniques are being employed to further our understanding of the genetic basis of SCZ, and to identify associated molecular pathways, biomarkers, and candidate drug targets.
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Affiliation(s)
- Clara Casey
- Department of Biological Sciences, Munster Technological University, Bishopstown, Cork, Ireland; Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
| | - John F Fullard
- Center for Disease Neurogenomics, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, United States
| | - Roy D Sleator
- Department of Biological Sciences, Munster Technological University, Bishopstown, Cork, Ireland.
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24
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Chen XF, Duan YY, Jia YY, Dong QH, Shi W, Zhang Y, Dong SS, Li M, Liu Z, Chen F, Huang XT, Hao RH, Zhu DL, Jing RH, Guo Y, Yang TL. Integrative high-throughput enhancer surveying and functional verification divulges a YY2-condensed regulatory axis conferring risk for osteoporosis. CELL GENOMICS 2024; 4:100501. [PMID: 38335956 PMCID: PMC10943593 DOI: 10.1016/j.xgen.2024.100501] [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: 05/16/2023] [Revised: 08/23/2023] [Accepted: 01/10/2024] [Indexed: 02/12/2024]
Abstract
The precise roles of chromatin organization at osteoporosis risk loci remain largely elusive. Here, we combined chromatin interaction conformation (Hi-C) profiling and self-transcribing active regulatory region sequencing (STARR-seq) to qualify enhancer activities of prioritized osteoporosis-associated single-nucleotide polymorphisms (SNPs). We identified 319 SNPs with biased allelic enhancer activity effect (baaSNPs) that linked to hundreds of candidate target genes through chromatin interactions across 146 loci. Functional characterizations revealed active epigenetic enrichment for baaSNPs and prevailing osteoporosis-relevant regulatory roles for their chromatin interaction genes. Further motif enrichment and network mapping prioritized several putative, key transcription factors (TFs) controlling osteoporosis binding to baaSNPs. Specifically, we selected one top-ranked TF and deciphered that an intronic baaSNP (rs11202530) could allele-preferentially bind to YY2 to augment PAPSS2 expression through chromatin interactions and promote osteoblast differentiation. Our results underline the roles of TF-mediated enhancer-promoter contacts for osteoporosis, which may help to better understand the intricate molecular regulatory mechanisms underlying osteoporosis risk loci.
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Affiliation(s)
- Xiao-Feng Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Yuan-Yuan Duan
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Ying-Ying Jia
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Qian-Hua Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Wei Shi
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Yan Zhang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Shan-Shan Dong
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Meng Li
- Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi, China
| | - Zhongbo Liu
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an 710004, Shaanxi, China
| | - Fei Chen
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Xiao-Ting Huang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Ruo-Han Hao
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Dong-Li Zhu
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China
| | - Rui-Hua Jing
- Department of Ophthalmology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710000, Shaanxi, China
| | - Yan Guo
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China.
| | - Tie-Lin Yang
- Key Laboratory of Biomedical Information Engineering of Ministry of Education, Key Laboratory of Biology Multiomics and Diseases in Shaanxi Province Higher Education Institutions, Biomedical Informatics and Genomics Center, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an 710049, Shaanxi, China; Department of Orthopedics, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, Shaanxi, China.
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Wahl N, Espeso-Gil S, Chietera P, Nagel A, Laighneach A, Morris DW, Rajarajan P, Akbarian S, Dechant G, Apostolova G. SATB2 organizes the 3D genome architecture of cognition in cortical neurons. Mol Cell 2024; 84:621-639.e9. [PMID: 38244545 PMCID: PMC10923151 DOI: 10.1016/j.molcel.2023.12.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Revised: 10/02/2023] [Accepted: 12/15/2023] [Indexed: 01/22/2024]
Abstract
The DNA-binding protein SATB2 is genetically linked to human intelligence. We studied its influence on the three-dimensional (3D) epigenome by mapping chromatin interactions and accessibility in control versus SATB2-deficient cortical neurons. We find that SATB2 affects the chromatin looping between enhancers and promoters of neuronal-activity-regulated genes, thus influencing their expression. It also alters A/B compartments, topologically associating domains, and frequently interacting regions. Genes linked to SATB2-dependent 3D genome changes are implicated in highly specialized neuronal functions and contribute to cognitive ability and risk for neuropsychiatric and neurodevelopmental disorders. Non-coding DNA regions with a SATB2-dependent structure are enriched for common variants associated with educational attainment, intelligence, and schizophrenia. Our data establish SATB2 as a cell-type-specific 3D genome modulator, which operates both independently and in cooperation with CCCTC-binding factor (CTCF) to set up the chromatin landscape of pyramidal neurons for cognitive processes.
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Affiliation(s)
- Nico Wahl
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria.
| | - Sergio Espeso-Gil
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria; Department of Psychiatry, Friedman Brain Institute, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Paola Chietera
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria
| | - Amelie Nagel
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria
| | - Aodán Laighneach
- Centre for Neuroimaging, Cognition and Genomics (NICOG), School of Biological and Chemical Sciences, University of Galway, Galway, H91 TK33, Ireland
| | - Derek W Morris
- Centre for Neuroimaging, Cognition and Genomics (NICOG), School of Biological and Chemical Sciences, University of Galway, Galway, H91 TK33, Ireland
| | - Prashanth Rajarajan
- Department of Psychiatry, Friedman Brain Institute, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Schahram Akbarian
- Department of Psychiatry, Friedman Brain Institute, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Georg Dechant
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria.
| | - Galina Apostolova
- Institute for Neuroscience, Medical University of Innsbruck, Innsbruck 6020, Austria.
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Wang Z, Zhang Z, Luo S, Zhou T, Zhang J. Power-law behavior of transcriptional bursting regulated by enhancer-promoter communication. Genome Res 2024; 34:106-118. [PMID: 38171575 PMCID: PMC10903953 DOI: 10.1101/gr.278631.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 12/18/2023] [Indexed: 01/05/2024]
Abstract
Revealing how transcriptional bursting kinetics are genomically encoded is challenging because genome structures are stochastic at the organization level and are suggestively linked to gene transcription. To address this challenge, we develop a generic theoretical framework that integrates chromatin dynamics, enhancer-promoter (E-P) communication, and gene-state switching to study transcriptional bursting. The theory predicts that power law can be a general rule to quantitatively describe bursting modulations by E-P spatial communication. Specifically, burst frequency and burst size are up-regulated by E-P communication strength, following power laws with positive exponents. Analysis of the scaling exponents further reveals that burst frequency is preferentially regulated. Bursting kinetics are down-regulated by E-P genomic distance with negative power-law exponents, and this negative modulation desensitizes at large distances. The mutual information between burst frequency (or burst size) and E-P spatial distance further reveals essential characteristics of the information transfer from E-P communication to transcriptional bursting kinetics. These findings, which are in agreement with experimental observations, not only reveal fundamental principles of E-P communication in transcriptional bursting but also are essential for understanding cellular decision-making.
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Affiliation(s)
- Zihao Wang
- Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou 510275, P.R. China
- School of Mathematics, Sun Yat-sen University, Guangzhou 510275, P.R. China
| | - Zhenquan Zhang
- Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou 510275, P.R. China
- School of Mathematics, Sun Yat-sen University, Guangzhou 510275, P.R. China
| | - Songhao Luo
- Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou 510275, P.R. China
- School of Mathematics, Sun Yat-sen University, Guangzhou 510275, P.R. China
| | - Tianshou Zhou
- Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou 510275, P.R. China;
- School of Mathematics, Sun Yat-sen University, Guangzhou 510275, P.R. China
| | - Jiajun Zhang
- Guangdong Province Key Laboratory of Computational Science, Sun Yat-sen University, Guangzhou 510275, P.R. China;
- School of Mathematics, Sun Yat-sen University, Guangzhou 510275, P.R. China
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27
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Zhang Y, Shen Y, Jin P, Zhu B, Lin Y, Jiang T, Huang X, Wang Y, Zhao Z, Li S. A trade-off in evolution: the adaptive landscape of spiders without venom glands. Gigascience 2024; 13:giae048. [PMID: 39101784 PMCID: PMC11299198 DOI: 10.1093/gigascience/giae048] [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: 09/13/2023] [Revised: 01/26/2024] [Accepted: 06/26/2024] [Indexed: 08/06/2024] Open
Abstract
BACKGROUND Venom glands play a key role in the predation and defense strategies of almost all spider groups. However, the spider family Uloboridae lacks venom glands and has evolved an adaptive strategy: they excessively wrap their prey directly with spider silk instead of paralyzing it first with toxins. This shift in survival strategy is very fascinating, but the genetic underpinnings behind it are poorly understood. RESULTS Spanning multiple spider groups, we conducted multiomics analyses on Octonoba sinensis and described the adaptive evolution of the Uloboridae family at the genome level. We observed the coding genes of myosin and twitchin in muscles are under positive selection, energy metabolism functions are enhanced, and gene families related to tracheal development and tissue mechanical strength are expanded or emerged, all of which are related to the unique anatomical structure and predatory behavior of spiders in the family Uloboridae. In addition, we also scanned the elements that are absent or under relaxed purifying selection, as well as toxin gene homologs in the genomes of 2 species in this family. The results show that the absence of regions and regions under relaxed selection in these spiders' genomes are concentrated in areas related to development and neurosystem. The search for toxin homologs reveals possible gene function shift between toxins and nontoxins and confirms that there are no reliable toxin genes in the genome of this group. CONCLUSIONS This study demonstrates the trade-off between different predation strategies in spiders, using either chemical or physical strategy, and provides insights into the possible mechanism underlying this trade-off. Venomless spiders need to mobilize multiple developmental and metabolic pathways related to motor function and limb mechanical strength to cover the decline in adaptability caused by the absence of venom glands.
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Affiliation(s)
- Yiming Zhang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Hebei Key Laboratory of Animal Diversity, College of Life Sciences, Langfang Normal University, Langfang 065000, China
- University of Chinese Academy of Sciences, Beijing 101408, China
| | - Yunxiao Shen
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 101408, China
| | - Pengyu Jin
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Bingyue Zhu
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 101408, China
| | - Yejie Lin
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- Hebei Key Laboratory of Animal Diversity, College of Life Sciences, Langfang Normal University, Langfang 065000, China
| | - Tongyao Jiang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 101408, China
| | - Xianting Huang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 101408, China
| | - Yang Wang
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
- University of Chinese Academy of Sciences, Beijing 101408, China
| | - Zhe Zhao
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
| | - Shuqiang Li
- Key Laboratory of Zoological Systematics and Evolution, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China
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28
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Xu D, Zhang C, Bi X, Xu J, Guo S, Li P, Shen Y, Cai J, Zhang N, Tian G, Zhang H, Wang H, Li Q, Jiang H, Wang B, Li X, Li Y, Li K. Mapping enhancer and chromatin accessibility landscapes charts the regulatory network of Alzheimer's disease. Comput Biol Med 2024; 168:107802. [PMID: 38056211 DOI: 10.1016/j.compbiomed.2023.107802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2023] [Revised: 10/20/2023] [Accepted: 11/29/2023] [Indexed: 12/08/2023]
Abstract
BACKGROUND Enhancers are regulatory elements that target and modulate gene expression and play a role in human health and disease. However, the roles of enhancer regulatory circuit abnormalities driven by epigenetic alterations in Alzheimer's disease (AD) are unclear. METHODS In this study, a multiomic integrative analysis was performed to map enhancer and chromatin accessibility landscapes and identify regulatory network abnormalities in AD. We identified differentially methylated enhancers and constructed regulatory networks across brain regions using AD brain tissue samples. Through the integration of snATAC-seq and snRNA-seq datasets, we mapped enhancers with DNA methylation alterations (DMA) and chromatin accessibility landscapes. Core regulatory triplets that contributed to AD neuropathology in specific cell types were further prioritized. RESULTS We revealed widespread DNA methylation alterations (DMA) in the enhancers of AD patients across different brain regions. In addition, the genome-wide transcription factor (TF) binding profiles showed that enhancers with DMA are pervasively regulated by TFs. The TF-enhancer-gene regulatory network analysis identified core regulatory triplets that are associated with brain and immune cell proportions and play important roles in AD pathogenesis. Enhancer regulatory circuits with DMA exhibited distinct chromatin accessibility patterns, which were further characterized at single-cell resolutions. CONCLUSIONS Our study comprehensively investigated DNA methylation-mediated regulatory circuit abnormalities and provided novel insights into the potential pathogenesis of AD.
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Affiliation(s)
- Dahua Xu
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China
| | - Chunrui Zhang
- Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100020, China
| | - Xiaoman Bi
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China
| | - Jiankai Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin 150081, China
| | - Shengnan Guo
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China
| | - Peihu Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China
| | - Yutong Shen
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China
| | - Jiale Cai
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China
| | - Nihui Zhang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China
| | - Guanghui Tian
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China
| | - Haifei Zhang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China
| | - Hong Wang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China
| | - Qifu Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China
| | - Hongyan Jiang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China
| | - Bo Wang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.
| | - Xia Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.
| | - Yongsheng Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.
| | - Kongning Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan General Hospital, Hainan Affiliated Hospital, Hainan Medical University, Haikou 571199, China.
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29
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Nuytemans K, Rajabli F, Jean-Francois M, Kurup JT, Adams LD, Starks TD, Whitehead PL, Kunkle BW, Caban-Holt A, Haines JL, Cuccaro ML, Vance JM, Byrd GS, Beecham GW, Reitz C, Pericak-Vance MA. Genetic analyses in multiplex families confirms chromosome 5q35 as a risk locus for Alzheimer's Disease in individuals of African Ancestry. Neurobiol Aging 2024; 133:125-133. [PMID: 37952397 PMCID: PMC11131578 DOI: 10.1016/j.neurobiolaging.2023.10.010] [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: 04/18/2023] [Revised: 10/23/2023] [Accepted: 10/25/2023] [Indexed: 11/14/2023]
Abstract
There is a paucity of genetic studies of Alzheimer Disease (AD) in individuals of African Ancestry, despite evidence suggesting increased risk of AD in the African American (AA) population. We performed whole-genome sequencing (WGS) and multipoint linkage analyses in 51 multi-generational AA AD families ascertained through the Research in African American Alzheimer Disease Initiative (REAAADI) and the National Institute on Aging Late Onset Alzheimer's disease (NIA-LOAD) Family Based Study. Variants were prioritized on minor allele frequency (<0.01), functional potential of coding and noncoding variants, co-segregation with AD and presence in multi-ancestry ADSP release 3 WGS data. We identified a significant linkage signal on chromosome 5q35 (HLOD=3.3) driven by nine families. Haplotype segregation analysis in the family with highest LOD score identified a 3'UTR variant in INSYN2B with the most functional evidence. Four other linked AA families harbor within-family shared variants located in INSYN2B's promoter or enhancer regions. This AA family-based finding shows the importance of diversifying population-level genetic data to better understand the genetic determinants of AD on a global scale.
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Affiliation(s)
- Karen Nuytemans
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Farid Rajabli
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Melissa Jean-Francois
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Jiji Thulaseedhara Kurup
- Gertrude H. Sergievsky Center, Taub Institute for Research on the Aging Brain, Departments of Neurology, Psychiatry, and Epidemiology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Larry D Adams
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Takiyah D Starks
- Maya Angelou Center for Health Equity, Wake Forest University, Winston-Salem, NC, USA
| | - Patrice L Whitehead
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Brian W Kunkle
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Allison Caban-Holt
- Maya Angelou Center for Health Equity, Wake Forest University, Winston-Salem, NC, USA
| | - Jonathan L Haines
- Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Michael L Cuccaro
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Jeffery M Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Goldie S Byrd
- Maya Angelou Center for Health Equity, Wake Forest University, Winston-Salem, NC, USA
| | - Gary W Beecham
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Christiane Reitz
- Gertrude H. Sergievsky Center, Taub Institute for Research on the Aging Brain, Departments of Neurology, Psychiatry, and Epidemiology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Margaret A Pericak-Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA.
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30
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Liu S, Zheng P, Wang CY, Jia BB, Zemke NR, Ren B, Zhuang X. Cell-type-specific 3D-genome organization and transcription regulation in the brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.04.570024. [PMID: 38105994 PMCID: PMC10723369 DOI: 10.1101/2023.12.04.570024] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
3D organization of the genome plays a critical role in regulating gene expression. However, it remains unclear how chromatin organization differs among different cell types in the brain. Here we used genome-scale DNA and RNA imaging to investigate 3D-genome organization in transcriptionally distinct cell types in the primary motor cortex of the mouse brain. We uncovered a wide spectrum of differences in the nuclear architecture and 3D-genome organization among different cell types, ranging from the physical size of the cell nucleus to the active-inactive chromatin compartmentalization and radial positioning of chromatin loci within the nucleus. These cell-type-dependent variations in nuclear architecture and chromatin organization exhibited strong correlation with both 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 regulates transcription in a divergent manner, depending on the nuclear radial positions of chromatin loci, through 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
| | - 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
| | - Cosmos Yuqi Wang
- Howard Hughes Medical Institute, Department of Chemistry and Chemical Biology, Department of Physics, 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
| | - 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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31
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Noack F, Vangelisti S, Ditzer N, Chong F, Albert M, Bonev B. Joint epigenome profiling reveals cell-type-specific gene regulatory programmes in human cortical organoids. Nat Cell Biol 2023; 25:1873-1883. [PMID: 37996647 PMCID: PMC10709149 DOI: 10.1038/s41556-023-01296-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 10/17/2023] [Indexed: 11/25/2023]
Abstract
Gene expression is regulated by multiple epigenetic mechanisms, which are coordinated in development and disease. However, current multiomics methods are frequently limited to one or two modalities at a time, making it challenging to obtain a comprehensive gene regulatory signature. Here, we describe a method-3D genome, RNA, accessibility and methylation sequencing (3DRAM-seq)-that simultaneously interrogates spatial genome organization, chromatin accessibility and DNA methylation genome-wide and at high resolution. We combine 3DRAM-seq with immunoFACS and RNA sequencing in cortical organoids to map the cell-type-specific regulatory landscape of human neural development across multiple epigenetic layers. Finally, we apply a massively parallel reporter assay to profile cell-type-specific enhancer activity in organoids and to functionally assess the role of key transcription factors for human enhancer activation and function. More broadly, 3DRAM-seq can be used to profile the multimodal epigenetic landscape in rare cell types and different tissues.
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Affiliation(s)
- Florian Noack
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany
| | - Silvia Vangelisti
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany
| | - Nora Ditzer
- Center for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany
| | - Faye Chong
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany
| | - Mareike Albert
- Center for Regenerative Therapies Dresden, Technische Universität Dresden, Dresden, Germany
| | - Boyan Bonev
- Helmholtz Pioneer Campus, Helmholtz Zentrum München, Neuherberg, Germany.
- Physiological Genomics, Biomedical Center, Ludwig-Maximilians-Universität München, Munich, Germany.
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32
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Wang Z, Luo S, Zhang Z, Zhou T, Zhang J. 4D nucleome equation predicts gene expression controlled by long-range enhancer-promoter interaction. PLoS Comput Biol 2023; 19:e1011722. [PMID: 38109463 PMCID: PMC10760824 DOI: 10.1371/journal.pcbi.1011722] [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: 04/14/2023] [Revised: 01/02/2024] [Accepted: 11/28/2023] [Indexed: 12/20/2023] Open
Abstract
Recent experimental evidence strongly supports that three-dimensional (3D) long-range enhancer-promoter (E-P) interactions have important influences on gene-expression dynamics, but it is unclear how the interaction information is translated into gene expression over time (4D). To address this question, we developed a general theoretical framework (named as a 4D nucleome equation), which integrates E-P interactions on chromatin and biochemical reactions of gene transcription. With this equation, we first present the distribution of mRNA counts as a function of the E-P genomic distance and then reveal a power-law scaling of the expression level in this distance. Interestingly, we find that long-range E-P interactions can induce bimodal and trimodal mRNA distributions. The 4D nucleome equation also allows for model selection and parameter inference. When this equation is applied to the mouse embryonic stem cell smRNA-FISH data and the E-P genomic-distance data, the predicted E-P contact probability and mRNA distribution are in good agreement with experimental results. Further statistical inference indicates that the E-P interactions prefer to modulate the mRNA level by controlling promoter activation and transcription initiation rates. Our model and results provide quantitative insights into both spatiotemporal gene-expression determinants (i.e., long-range E-P interactions) and cellular fates during development.
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Affiliation(s)
- Zihao Wang
- Guangdong Province Key Laboratory of Computational, Sun Yat-sen University, Guangzhou, People’s Republic of China
- School of Mathematics, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Songhao Luo
- Guangdong Province Key Laboratory of Computational, Sun Yat-sen University, Guangzhou, People’s Republic of China
- School of Mathematics, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Zhenquan Zhang
- Guangdong Province Key Laboratory of Computational, Sun Yat-sen University, Guangzhou, People’s Republic of China
- School of Mathematics, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Tianshou Zhou
- Guangdong Province Key Laboratory of Computational, Sun Yat-sen University, Guangzhou, People’s Republic of China
- School of Mathematics, Sun Yat-Sen University, Guangzhou, People’s Republic of China
| | - Jiajun Zhang
- Guangdong Province Key Laboratory of Computational, Sun Yat-sen University, Guangzhou, People’s Republic of China
- School of Mathematics, Sun Yat-Sen University, Guangzhou, People’s Republic of China
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33
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Michalski C, Wen Z. Leveraging iPSC technology to assess neuro-immune interactions in neurological and psychiatric disorders. Front Psychiatry 2023; 14:1291115. [PMID: 38025464 PMCID: PMC10672983 DOI: 10.3389/fpsyt.2023.1291115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Accepted: 10/19/2023] [Indexed: 12/01/2023] Open
Abstract
Communication between the immune and the nervous system is essential for human brain development and homeostasis. Disruption of this intricately regulated crosstalk can lead to neurodevelopmental, psychiatric, or neurodegenerative disorders. While animal models have been essential in characterizing the role of neuroimmunity in development and disease, they come with inherent limitations due to species specific differences, particularly with regard to microglia, the major subset of brain resident immune cells. The advent of induced pluripotent stem cell (iPSC) technology now allows the development of clinically relevant models of the central nervous system that adequately reflect human genetic architecture. This article will review recent publications that have leveraged iPSC technology to assess neuro-immune interactions. First, we will discuss the role of environmental stressors such as neurotropic viruses or pro-inflammatory cytokines on neuronal and glial function. Next, we will review how iPSC models can be used to study genetic risk factors in neurological and psychiatric disorders. Lastly, we will evaluate current challenges and future potential for iPSC models in the field of neuroimmunity.
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Affiliation(s)
- Christina Michalski
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
| | - Zhexing Wen
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, United States
- Department of Cell Biology, Emory University School of Medicine, Atlanta, GA, United States
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, United States
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Salih A, Ardissino M, Wagen AZ, Bard A, Szabo L, Ryten M, Petersen SE, Altmann A, Raisi‐Estabragh Z. Genome-Wide Association Study of Pericardial Fat Area in 28 161 UK Biobank Participants. J Am Heart Assoc 2023; 12:e030661. [PMID: 37889180 PMCID: PMC10727393 DOI: 10.1161/jaha.123.030661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 09/06/2023] [Indexed: 10/28/2023]
Abstract
BACKGROUND Pericardial adipose tissue (PAT) is the visceral adipose tissue compartment surrounding the heart. Experimental and observational research has suggested that greater PAT deposition might mediate cardiovascular disease, independent of general or subcutaneous adiposity. We characterize the genetic architecture of adiposity-adjusted PAT and identify causal associations between PAT and adverse cardiac magnetic resonance imaging measures of cardiac structure and function in 28 161 UK Biobank participants. METHODS AND RESULTS The PAT phenotype was extracted from cardiac magnetic resonance images using an automated image analysis tool previously developed and validated in this cohort. A genome-wide association study was performed with PAT area set as the phenotype, adjusting for age, sex, and other measures of obesity. Functional mapping and Bayesian colocalization were used to understand the biologic role of identified variants. Mendelian randomization analysis was used to examine potential causal links between genetically determined PAT and cardiac magnetic resonance-derived measures of left ventricular structure and function. We discovered 12 genome-wide significant variants, with 2 independent sentinel variants (rs6428792, P=4.20×10-9 and rs11992444, P=1.30×10-12) at 2 distinct genomic loci, that were mapped to 3 potentially causal genes: T-box transcription factor 15 (TBX15), tryptophanyl tRNA synthetase 2, mitochondrial (WARS2) and early B-cell factor-2 (EBF2) through functional annotation. Bayesian colocalization additionally suggested a role of RP4-712E4.1. Genetically predicted differences in adiposity-adjusted PAT were causally associated with adverse left ventricular remodeling. CONCLUSIONS This study provides insights into the genetic architecture determining differential PAT deposition, identifies causal links with left structural and functional parameters, and provides novel data about the pathophysiological importance of adiposity distribution.
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Affiliation(s)
- Ahmed Salih
- William Harvey Research Institute, National Institute for Health and Care Research (NIHR) Barts Biomedical Research CentreQueen Mary University of London, Charterhouse SquareLondonUnited Kingdom
| | - Maddalena Ardissino
- National Heart and Lung Institute, Imperial College LondonLondonUnited Kingdom
- Heart and Lung Research Institute, University of CambridgeCambridgeUnited Kingdom
| | - Aaron Z. Wagen
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child HealthUniversity College LondonLondonUnited Kingdom
- Department of Clinical and Movement NeurosciencesQueen Square Institute of NeurologyLondonUnited Kingdom
- Neurodegeneration Biology LaboratoryThe Francis Crick InstituteLondonUnited Kingdom
| | - Andrew Bard
- William Harvey Research Institute, National Institute for Health and Care Research (NIHR) Barts Biomedical Research CentreQueen Mary University of London, Charterhouse SquareLondonUnited Kingdom
| | - Liliana Szabo
- William Harvey Research Institute, National Institute for Health and Care Research (NIHR) Barts Biomedical Research CentreQueen Mary University of London, Charterhouse SquareLondonUnited Kingdom
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health National Health Service (NHS) Trust, West SmithfieldLondonUnited Kingdom
- Semmelweis University, Heart and Vascular CenterBudapestHungary
| | - Mina Ryten
- Genetics and Genomic Medicine, Great Ormond Street Institute of Child HealthUniversity College LondonLondonUnited Kingdom
- NIHR Great Ormond Street Hospital Biomedical Research CentreUniversity College LondonLondonUnited Kingdom
| | - Steffen E. Petersen
- William Harvey Research Institute, National Institute for Health and Care Research (NIHR) Barts Biomedical Research CentreQueen Mary University of London, Charterhouse SquareLondonUnited Kingdom
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health National Health Service (NHS) Trust, West SmithfieldLondonUnited Kingdom
- Health Data Research UKLondonUnited Kingdom
- Alan Turing InstituteLondonUnited Kingdom
| | - André Altmann
- Centre for Medical Image Computing, Department of Medical Physics and Biomedical EngineeringUniversity College LondonLondonUnited Kingdom
| | - Zahra Raisi‐Estabragh
- William Harvey Research Institute, National Institute for Health and Care Research (NIHR) Barts Biomedical Research CentreQueen Mary University of London, Charterhouse SquareLondonUnited Kingdom
- Barts Heart Centre, St Bartholomew’s Hospital, Barts Health National Health Service (NHS) Trust, West SmithfieldLondonUnited Kingdom
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Calandrelli R, Wen X, Charles Richard JL, Luo Z, Nguyen TC, Chen CJ, Qi Z, Xue S, Chen W, Yan Z, Wu W, Zaleta-Rivera K, Hu R, Yu M, Wang Y, Li W, Ma J, Ren B, Zhong S. Genome-wide analysis of the interplay between chromatin-associated RNA and 3D genome organization in human cells. Nat Commun 2023; 14:6519. [PMID: 37845234 PMCID: PMC10579264 DOI: 10.1038/s41467-023-42274-7] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 10/05/2023] [Indexed: 10/18/2023] Open
Abstract
The interphase genome is dynamically organized in the nucleus and decorated with chromatin-associated RNA (caRNA). It remains unclear whether the genome architecture modulates the spatial distribution of caRNA and vice versa. Here, we generate a resource of genome-wide RNA-DNA and DNA-DNA contact maps in human cells. These maps reveal the chromosomal domains demarcated by locally transcribed RNA, hereafter termed RNA-defined chromosomal domains. Further, the spreading of caRNA is constrained by the boundaries of topologically associating domains (TADs), demonstrating the role of the 3D genome structure in modulating the spatial distribution of RNA. Conversely, stopping transcription or acute depletion of RNA induces thousands of chromatin loops genome-wide. Activation or suppression of the transcription of specific genes suppresses or creates chromatin loops straddling these genes. Deletion of a specific caRNA-producing genomic sequence promotes chromatin loops that straddle the interchromosomal target sequences of this caRNA. These data suggest a feedback loop where the 3D genome modulates the spatial distribution of RNA, which in turn affects the dynamic 3D genome organization.
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Affiliation(s)
- Riccardo Calandrelli
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Xingzhao Wen
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA
| | | | - Zhifei Luo
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Tri C Nguyen
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Chien-Ju Chen
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA
| | - Zhijie Qi
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Shuanghong Xue
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Weizhong Chen
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Zhangming Yan
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Weixin Wu
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Kathia Zaleta-Rivera
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Rong Hu
- Department of Cellular and Molecular Medicine, Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
| | - Miao Yu
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
| | - Yuchuan Wang
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Wenbo Li
- Department of Biochemistry and Molecular Biology, McGovern Medical School, University of Texas Health Science Center, Houston, TX, USA
| | - Jian Ma
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
| | - Sheng Zhong
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
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36
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Wei X, Tran D, Diao Y. HiCAR: Analysis of Open Chromatin Associated Long-range Chromatin Interaction Using Low-Input Materials. Curr Protoc 2023; 3:e899. [PMID: 37818863 PMCID: PMC10575683 DOI: 10.1002/cpz1.899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/13/2023]
Abstract
Cis-regulatory elements (cREs) and their long-range interactions are crucial for spatial-temporal gene regulation. While cREs can be characterized as accessible chromatin sequences, comprehensively identifying their spatial interactions remains a challenge. We recently developed a method, HiCAR (Hi-C on Accessible Regulatory DNA), which combines Tn5 transposase and chromatin proximity ligation to analyze open chromatin-anchored interactions in low-input cells. Application of HiCAR in human embryonic stem cells and lymphoblastoid cells reveals high-resolution chromatin contacts with efficiency comparable to in situ Hi-C across various distance ranges. Moreover, HiCAR was successfully applied to 30,000 primary human muscle stem cells, showcasing its potential for analyzing chromatin accessibility and looping in low-input primary cells and clinical samples. Here, we provide a detailed step-by-step protocol to perform the updated HiCAR experiments. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Tn5 Transposase Assembly Basic Protocol 2: HiCAR Library Preparation.
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Affiliation(s)
- Xiaolin Wei
- Department of Cell Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Duc Tran
- Department of Cell Biology, Duke University Medical Center, Durham, NC 27710, USA
| | - Yarui Diao
- Department of Cell Biology, Duke University Medical Center, Durham, NC 27710, USA
- Duke Regeneration Center, Duke University Medical Center, Durham, NC 27710, USA
- Center for Advanced Genomic Technologies, Duke University, Durham, NC 27708, USA
- Department of Orthopaedics Surgery, Duke University Medical Center, Durham, NC 27710, USA
- Department of Pathology, Duke University Medical Center, Durham, NC 27710, USA
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37
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Weng C, Gu A, Zhang S, Lu L, Ke L, Gao P, Liu X, Wang Y, Hu P, Plummer D, MacDonald E, Zhang S, Xi J, Lai S, Leskov K, Yuan K, Jin F, Li Y. Single cell multiomic analysis reveals diabetes-associated β-cell heterogeneity driven by HNF1A. Nat Commun 2023; 14:5400. [PMID: 37669939 PMCID: PMC10480445 DOI: 10.1038/s41467-023-41228-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Accepted: 08/29/2023] [Indexed: 09/07/2023] Open
Abstract
Broad heterogeneity in pancreatic β-cell function and morphology has been widely reported. However, determining which components of this cellular heterogeneity serve a diabetes-relevant function remains challenging. Here, we integrate single-cell transcriptome, single-nuclei chromatin accessibility, and cell-type specific 3D genome profiles from human islets and identify Type II Diabetes (T2D)-associated β-cell heterogeneity at both transcriptomic and epigenomic levels. We develop a computational method to explicitly dissect the intra-donor and inter-donor heterogeneity between single β-cells, which reflect distinct mechanisms of T2D pathogenesis. Integrative transcriptomic and epigenomic analysis identifies HNF1A as a principal driver of intra-donor heterogeneity between β-cells from the same donors; HNF1A expression is also reduced in β-cells from T2D donors. Interestingly, HNF1A activity in single β-cells is significantly associated with lower Na+ currents and we nominate a HNF1A target, FXYD2, as the primary mitigator. Our study demonstrates the value of investigating disease-associated single-cell heterogeneity and provides new insights into the pathogenesis of T2D.
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Affiliation(s)
- Chen Weng
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Anniya Gu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- Medical Scientist Training Program (MSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Shanshan Zhang
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Leina Lu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Luxin Ke
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Peidong Gao
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Xiaoxiao Liu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Yuntong Wang
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Peinan Hu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Dylan Plummer
- Department of Computer and Data Sciences, School of Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Elise MacDonald
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Saixian Zhang
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Jiajia Xi
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Sisi Lai
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- The Biomedical Sciences Training Program (BSTP), School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Konstantin Leskov
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Kyle Yuan
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
- Department of Biochemistry, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA
| | - Fulai Jin
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA.
- Department of Computer and Data Sciences, School of Engineering, Case Western Reserve University, Cleveland, OH, 44106, USA.
- Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, 44106, USA.
- Department of Population and Quantitative Health Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA.
| | - Yan Li
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, 44106, USA.
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38
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Liu H, Tsai H, Yang M, Li G, Bian Q, Ding G, Wu D, Dai J. Three-dimensional genome structure and function. MedComm (Beijing) 2023; 4:e326. [PMID: 37426677 PMCID: PMC10329473 DOI: 10.1002/mco2.326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Revised: 05/31/2023] [Accepted: 06/09/2023] [Indexed: 07/11/2023] Open
Abstract
Linear DNA undergoes a series of compression and folding events, forming various three-dimensional (3D) structural units in mammalian cells, including chromosomal territory, compartment, topologically associating domain, and chromatin loop. These structures play crucial roles in regulating gene expression, cell differentiation, and disease progression. Deciphering the principles underlying 3D genome folding and the molecular mechanisms governing cell fate determination remains a challenge. With advancements in high-throughput sequencing and imaging techniques, the hierarchical organization and functional roles of higher-order chromatin structures have been gradually illuminated. This review systematically discussed the structural hierarchy of the 3D genome, the effects and mechanisms of cis-regulatory elements interaction in the 3D genome for regulating spatiotemporally specific gene expression, the roles and mechanisms of dynamic changes in 3D chromatin conformation during embryonic development, and the pathological mechanisms of diseases such as congenital developmental abnormalities and cancer, which are attributed to alterations in 3D genome organization and aberrations in key structural proteins. Finally, prospects were made for the research about 3D genome structure, function, and genetic intervention, and the roles in disease development, prevention, and treatment, which may offer some clues for precise diagnosis and treatment of related diseases.
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Affiliation(s)
- Hao Liu
- Department of Oral and Cranio‐Maxillofacial SurgeryShanghai Ninth People's Hospital, Shanghai Jiao Tong University School of MedicineCollege of Stomatology, Shanghai Jiao Tong UniversityNational Center for StomatologyNational Clinical Research Center for Oral DiseasesShanghai Key Laboratory of StomatologyShanghaiChina
- School of StomatologyWeifang Medical UniversityWeifangChina
| | - Hsiangyu Tsai
- Department of Oral and Cranio‐Maxillofacial SurgeryShanghai Ninth People's Hospital, Shanghai Jiao Tong University School of MedicineCollege of Stomatology, Shanghai Jiao Tong UniversityNational Center for StomatologyNational Clinical Research Center for Oral DiseasesShanghai Key Laboratory of StomatologyShanghaiChina
| | - Maoquan Yang
- School of Clinical MedicineWeifang Medical UniversityWeifangChina
| | - Guozhi Li
- Department of Oral and Cranio‐Maxillofacial SurgeryShanghai Ninth People's Hospital, Shanghai Jiao Tong University School of MedicineCollege of Stomatology, Shanghai Jiao Tong UniversityNational Center for StomatologyNational Clinical Research Center for Oral DiseasesShanghai Key Laboratory of StomatologyShanghaiChina
| | - Qian Bian
- Shanghai Institute of Precision MedicineShanghaiChina
| | - Gang Ding
- School of StomatologyWeifang Medical UniversityWeifangChina
| | - Dandan Wu
- Department of Oral and Cranio‐Maxillofacial SurgeryShanghai Ninth People's Hospital, Shanghai Jiao Tong University School of MedicineCollege of Stomatology, Shanghai Jiao Tong UniversityNational Center for StomatologyNational Clinical Research Center for Oral DiseasesShanghai Key Laboratory of StomatologyShanghaiChina
| | - Jiewen Dai
- Department of Oral and Cranio‐Maxillofacial SurgeryShanghai Ninth People's Hospital, Shanghai Jiao Tong University School of MedicineCollege of Stomatology, Shanghai Jiao Tong UniversityNational Center for StomatologyNational Clinical Research Center for Oral DiseasesShanghai Key Laboratory of StomatologyShanghaiChina
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Armendariz DA, Sundarrajan A, Hon GC. Breaking enhancers to gain insights into developmental defects. eLife 2023; 12:e88187. [PMID: 37497775 PMCID: PMC10374278 DOI: 10.7554/elife.88187] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 07/19/2023] [Indexed: 07/28/2023] Open
Abstract
Despite ground-breaking genetic studies that have identified thousands of risk variants for developmental diseases, how these variants lead to molecular and cellular phenotypes remains a gap in knowledge. Many of these variants are non-coding and occur at enhancers, which orchestrate key regulatory programs during development. The prevailing paradigm is that non-coding variants alter the activity of enhancers, impacting gene expression programs, and ultimately contributing to disease risk. A key obstacle to progress is the systematic functional characterization of non-coding variants at scale, especially since enhancer activity is highly specific to cell type and developmental stage. Here, we review the foundational studies of enhancers in developmental disease and current genomic approaches to functionally characterize developmental enhancers and their variants at scale. In the coming decade, we anticipate systematic enhancer perturbation studies to link non-coding variants to molecular mechanisms, changes in cell state, and disease phenotypes.
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Affiliation(s)
- Daniel A Armendariz
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
| | - Anjana Sundarrajan
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
| | - Gary C Hon
- Cecil H. and Ida Green Center for Reproductive Biology Sciences, University of Texas Southwestern Medical Center, Dallas, United States
- Hamon Center for Regenerative Science and Medicine, University of Texas Southwestern Medical Center, Dallas, United States
- Lyda Hill Department of Bioinformatics, Department of Obstetrics and Gynecology, University of Texas Southwestern Medical Center, Dallas, United States
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40
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Li H, He X, Kurowski L, Zhang R, Zhao D, Zeng J. Improving comparative analyses of Hi-C data via contrastive self-supervised learning. Brief Bioinform 2023; 24:bbad193. [PMID: 37287135 DOI: 10.1093/bib/bbad193] [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: 02/06/2023] [Revised: 04/12/2023] [Accepted: 04/27/2023] [Indexed: 06/09/2023] Open
Abstract
Hi-C is a widely applied chromosome conformation capture (3C)-based technique, which has produced a large number of genomic contact maps with high sequencing depths for a wide range of cell types, enabling comprehensive analyses of the relationships between biological functionalities (e.g. gene regulation and expression) and the three-dimensional genome structure. Comparative analyses play significant roles in Hi-C data studies, which are designed to make comparisons between Hi-C contact maps, thus evaluating the consistency of replicate Hi-C experiments (i.e. reproducibility measurement) and detecting statistically differential interacting regions with biological significance (i.e. differential chromatin interaction detection). However, due to the complex and hierarchical nature of Hi-C contact maps, it remains challenging to conduct systematic and reliable comparative analyses of Hi-C data. Here, we proposed sslHiC, a contrastive self-supervised representation learning framework, for precisely modeling the multi-level features of chromosome conformation and automatically producing informative feature embeddings for genomic loci and their interactions to facilitate comparative analyses of Hi-C contact maps. Comprehensive computational experiments on both simulated and real datasets demonstrated that our method consistently outperformed the state-of-the-art baseline methods in providing reliable measurements of reproducibility and detecting differential interactions with biological meanings.
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Affiliation(s)
- Han Li
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
| | - Xuan He
- Machine Learning Department, Silexon AI Technology Co., Ltd., 210000 Nanjing, China
| | - Lawrence Kurowski
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
| | - Ruotian Zhang
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
| | - Dan Zhao
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
| | - Jianyang Zeng
- Institute for Interdisciplinary Information Sciences, Tsinghua University, 100084 Beijing, China
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41
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Koo B, Lee KH, Ming GL, Yoon KJ, Song H. Setting the clock of neural progenitor cells during mammalian corticogenesis. Semin Cell Dev Biol 2023; 142:43-53. [PMID: 35644876 PMCID: PMC9699901 DOI: 10.1016/j.semcdb.2022.05.013] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 05/06/2022] [Accepted: 05/16/2022] [Indexed: 10/18/2022]
Abstract
Radial glial cells (RGCs) as primary neural stem cells in the developing mammalian cortex give rise to diverse types of neurons and glial cells according to sophisticated developmental programs with remarkable spatiotemporal precision. Recent studies suggest that regulation of the temporal competence of RGCs is a key mechanism for the highly conserved and predictable development of the cerebral cortex. Various types of epigenetic regulations, such as DNA methylation, histone modifications, and 3D chromatin architecture, play a key role in shaping the gene expression pattern of RGCs. In addition, epitranscriptomic modifications regulate temporal pre-patterning of RGCs by affecting the turnover rate and function of cell-type-specific transcripts. In this review, we summarize epigenetic and epitranscriptomic regulatory mechanisms that control the temporal competence of RGCs during mammalian corticogenesis. Furthermore, we discuss various developmental elements that also dynamically regulate the temporal competence of RGCs, including biochemical reaction speed, local environmental changes, and subcellular organelle remodeling. Finally, we discuss the underlying mechanisms that regulate the interspecies developmental tempo contributing to human-specific features of brain development.
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Affiliation(s)
- Bonsang Koo
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
| | - Ki-Heon Lee
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea
| | - Guo-Li Ming
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School for Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Psychiatry, Perelman School for Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Ki-Jun Yoon
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), 291 Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea.
| | - Hongjun Song
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School for Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Department of Cell and Developmental Biology, Perelman School for Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; Institute for Regenerative Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA; The Epigenetics Institute, Perelman School for Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.
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42
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Guo Q, Wu S, Geschwind DH. Characterization of Gene Regulatory Elements in Human Fetal Cortical Development: Enhancing Our Understanding of Neurodevelopmental Disorders and Evolution. Dev Neurosci 2023; 46:69-83. [PMID: 37231806 DOI: 10.1159/000530929] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 04/24/2023] [Indexed: 05/27/2023] Open
Abstract
The neocortex is the region that most distinguishes human brain from other mammals and primates [Annu Rev Genet. 2021 Nov;55(1):555-81]. Studying the development of human cortex is important in understanding the evolutionary changes occurring in humans relative to other primates, as well as in elucidating mechanisms underlying neurodevelopmental disorders. Cortical development is a highly regulated process, spatially and temporally coordinated by expression of essential transcriptional factors in response to signaling pathways [Neuron. 2019 Sep;103(6):980-1004]. Enhancers are the most well-understood cis-acting, non-protein-coding regulatory elements that regulate gene expression [Nat Rev Genet. 2014 Apr;15(4):272-86]. Importantly, given the conservation of both DNA sequence and molecular function of the majority of proteins across mammals [Genome Res. 2003 Dec;13(12):2507-18], enhancers [Science. 2015 Mar;347(6226):1155-9], which are far more divergent at the sequence level, likely account for the phenotypes that distinguish the human brain by changing the regulation of gene expression. In this review, we will revisit the conceptual framework of gene regulation during human brain development, as well as the evolution of technologies to study transcriptional regulation, with recent advances in genome biology that open a window allowing us to systematically characterize cis-regulatory elements in developing human brain [Hum Mol Genet. 2022 Oct;31(R1):R84-96]. We provide an update on work to characterize the suite of all enhancers in the developing human brain and the implications for understanding neuropsychiatric disorders. Finally, we discuss emerging therapeutic ideas that utilize our emerging knowledge of enhancer function.
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Affiliation(s)
- Qiuyu Guo
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, California, USA
- Center for Autism Research and Treatment, Semel Institute, University of California Los Angeles, Los Angeles, California, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Sarah Wu
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, California, USA
| | - Daniel H Geschwind
- Center for Neurobehavioral Genetics, Jane and Terry Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, California, USA
- Center for Autism Research and Treatment, Semel Institute, University of California Los Angeles, Los Angeles, California, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Institute of Precision Health, University of California Los Angeles, Los Angeles, California, USA
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Fu C, Ngo J, Zhang S, Lu L, Miron A, Schafer S, Gage FH, Jin F, Schumacher FR, Wynshaw-Boris A. Novel correlative analysis identifies multiple genomic variations impacting ASD with macrocephaly. Hum Mol Genet 2023; 32:1589-1606. [PMID: 36519762 PMCID: PMC10162433 DOI: 10.1093/hmg/ddac300] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 12/06/2022] [Accepted: 12/07/2022] [Indexed: 12/23/2022] Open
Abstract
Autism spectrum disorders (ASD) display both phenotypic and genetic heterogeneity, impeding the understanding of ASD and development of effective means of diagnosis and potential treatments. Genes affected by genomic variations for ASD converge in dozens of gene ontologies (GOs), but the relationship between the variations at the GO level have not been well elucidated. In the current study, multiple types of genomic variations were mapped to GOs and correlations among GOs were measured in ASD and control samples. Several ASD-unique GO correlations were found, suggesting the importance of co-occurrence of genomic variations in genes from different functional categories in ASD etiology. Combined with experimental data, several variations related to WNT signaling, neuron development, synapse morphology/function and organ morphogenesis were found to be important for ASD with macrocephaly, and novel co-occurrence patterns of them in ASD patients were found. Furthermore, we applied this gene ontology correlation analysis method to find genomic variations that contribute to ASD etiology in combination with changes in gene expression and transcription factor binding, providing novel insights into ASD with macrocephaly and a new methodology for the analysis of genomic variation.
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Affiliation(s)
- Chen Fu
- Department of Genetics and Genomic Science, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Justine Ngo
- Department of Genetics and Genomic Science, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Shanshan Zhang
- Department of Genetics and Genomic Science, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Leina Lu
- Department of Genetics and Genomic Science, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Alexander Miron
- Department of Genetics and Genomic Science, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Simon Schafer
- The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Fred H Gage
- The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Fulai Jin
- Department of Genetics and Genomic Science, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Fredrick R Schumacher
- Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
| | - Anthony Wynshaw-Boris
- Department of Genetics and Genomic Science, Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
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Kalluchi A, Harris HL, Reznicek TE, Rowley MJ. Considerations and caveats for analyzing chromatin compartments. Front Mol Biosci 2023; 10:1168562. [PMID: 37091873 PMCID: PMC10113542 DOI: 10.3389/fmolb.2023.1168562] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 03/27/2023] [Indexed: 04/08/2023] Open
Abstract
Genomes are organized into nuclear compartments, separating active from inactive chromatin. Chromatin compartments are readily visible in a large number of species by experiments that map chromatin conformation genome-wide. When analyzing these maps, a common step is the identification of genomic intervals that interact within A (active) and B (inactive) compartments. It has also become increasingly common to identify and analyze subcompartments. We review different strategies to identify A/B and subcompartment intervals, including a discussion of various machine-learning approaches to predict these features. We then discuss the strengths and limitations of current strategies and examine how these aspects of analysis may have impacted our understanding of chromatin compartments.
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Affiliation(s)
| | | | | | - M. Jordan Rowley
- Department of Genetics, Cell Biology and Anatomy, University of Nebraska Medical Center, Omaha, NE, United States
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45
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Zhang Z, Wang X, Park S, Song H, Ming GL. Development and Application of Brain Region-Specific Organoids for Investigating Psychiatric Disorders. Biol Psychiatry 2023; 93:594-605. [PMID: 36759261 PMCID: PMC9998354 DOI: 10.1016/j.biopsych.2022.12.015] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Revised: 11/14/2022] [Accepted: 12/12/2022] [Indexed: 12/25/2022]
Abstract
Human society has been burdened by psychiatric disorders throughout the course of its history. The emergence and rapid advances of human brain organoid technology provide unprecedented opportunities for investigation of potential disease mechanisms and development of targeted or even personalized treatments for various psychiatric disorders. In this review, we summarize recent advances for generating organoids from human pluripotent stem cells to model distinct brain regions and diverse cell types. We also highlight recent progress, discuss limitations, and propose potential improvements in using patient-derived or genetically engineered brain region-specific organoids for investigating various psychiatric disorders.
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Affiliation(s)
- Zhijian Zhang
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Xin Wang
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Sean Park
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Hongjun Song
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Institute for Regenerative Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Guo-Li Ming
- Department of Neuroscience and Mahoney Institute for Neurosciences, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Cell and Developmental Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Institute for Regenerative Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania.
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Chen J, Fuhler NA, Noguchi KK, Dougherty JD. MYT1L is required for suppressing earlier neuronal development programs in the adult mouse brain. Genome Res 2023; 33:541-556. [PMID: 37100461 PMCID: PMC10234307 DOI: 10.1101/gr.277413.122] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 03/09/2023] [Indexed: 04/28/2023]
Abstract
In vitro studies indicate the neurodevelopmental disorder gene myelin transcription factor 1-like (MYT1L) suppresses non-neuronal lineage genes during fibroblast-to-neuron direct differentiation. However, MYT1L's molecular and cellular functions in the adult mammalian brain have not been fully characterized. Here, we found that MYT1L loss leads to up-regulated deep layer (DL) gene expression, corresponding to an increased ratio of DL/UL neurons in the adult mouse cortex. To define potential mechanisms, we conducted Cleavage Under Targets & Release Using Nuclease (CUT&RUN) to map MYT1L binding targets and epigenetic changes following MYT1L loss in mouse developing cortex and adult prefrontal cortex (PFC). We found MYT1L mainly binds to open chromatin, but with different transcription factor co-occupancies between promoters and enhancers. Likewise, multiomic data set integration revealed that, at promoters, MYT1L loss does not change chromatin accessibility but increases H3K4me3 and H3K27ac, activating both a subset of earlier neuronal development genes as well as Bcl11b, a key regulator for DL neuron development. Meanwhile, we discovered that MYT1L normally represses the activity of neurogenic enhancers associated with neuronal migration and neuronal projection development by closing chromatin structures and promoting removal of active histone marks. Further, we showed that MYT1L interacts with HDAC2 and transcriptional repressor SIN3B in vivo, providing potential mechanisms underlying repressive effects on histone acetylation and gene expression. Overall, our findings provide a comprehensive map of MYT1L binding in vivo and mechanistic insights into how MYT1L loss leads to aberrant activation of earlier neuronal development programs in the adult mouse brain.
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Affiliation(s)
- Jiayang Chen
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Nicole A Fuhler
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Kevin K Noguchi
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Joseph D Dougherty
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA;
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, Missouri 63108, USA
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Kobets VA, Ulianov SV, Galitsyna AA, Doronin SA, Mikhaleva EA, Gelfand MS, Shevelyov YY, Razin SV, Khrameeva EE. HiConfidence: a novel approach uncovering the biological signal in Hi-C data affected by technical biases. Brief Bioinform 2023; 24:bbad044. [PMID: 36759336 PMCID: PMC10025441 DOI: 10.1093/bib/bbad044] [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: 10/12/2022] [Revised: 01/04/2023] [Accepted: 01/20/2023] [Indexed: 02/11/2023] Open
Abstract
The chromatin interaction assays, particularly Hi-C, enable detailed studies of genome architecture in multiple organisms and model systems, resulting in a deeper understanding of gene expression regulation mechanisms mediated by epigenetics. However, the analysis and interpretation of Hi-C data remain challenging due to technical biases, limiting direct comparisons of datasets obtained in different experiments and laboratories. As a result, removing biases from Hi-C-generated chromatin contact matrices is a critical data analysis step. Our novel approach, HiConfidence, eliminates biases from the Hi-C data by weighing chromatin contacts according to their consistency between replicates so that low-quality replicates do not substantially influence the result. The algorithm is effective for the analysis of global changes in chromatin structures such as compartments and topologically associating domains. We apply the HiConfidence approach to several Hi-C datasets with significant technical biases, that could not be analyzed effectively using existing methods, and obtain meaningful biological conclusions. In particular, HiConfidence aids in the study of how changes in histone acetylation pattern affect chromatin organization in Drosophila melanogaster S2 cells. The method is freely available at GitHub: https://github.com/victorykobets/HiConfidence.
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Affiliation(s)
- Victoria A Kobets
- Skolkovo Institute of Science and Technology, Moscow, 121205, Russia
| | - Sergey V Ulianov
- Institute of Gene Biology, Russian Academy of Sciences, Moscow, 119334, Russia
- Faculty of Biology, M.V. Lomonosov Moscow State University, Moscow, 119992, Russia
| | - Aleksandra A Galitsyna
- Skolkovo Institute of Science and Technology, Moscow, 121205, Russia
- Institute of Gene Biology, Russian Academy of Sciences, Moscow, 119334, Russia
- A.A. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, 127051, Russia
| | - Semen A Doronin
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Moscow, 123182, Russia
| | - Elena A Mikhaleva
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Moscow, 123182, Russia
| | - Mikhail S Gelfand
- Skolkovo Institute of Science and Technology, Moscow, 121205, Russia
- A.A. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, 127051, Russia
| | - Yuri Y Shevelyov
- Institute of Molecular Genetics of National Research Centre "Kurchatov Institute", Moscow, 123182, Russia
| | - Sergey V Razin
- Institute of Gene Biology, Russian Academy of Sciences, Moscow, 119334, Russia
- Faculty of Biology, M.V. Lomonosov Moscow State University, Moscow, 119992, Russia
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van Mierlo G, Pushkarev O, Kribelbauer JF, Deplancke B. Chromatin modules and their implication in genomic organization and gene regulation. Trends Genet 2023; 39:140-153. [PMID: 36549923 DOI: 10.1016/j.tig.2022.11.003] [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: 06/08/2022] [Revised: 11/04/2022] [Accepted: 11/27/2022] [Indexed: 12/24/2022]
Abstract
Regulation of gene expression is a complex but highly guided process. While genomic technologies and computational approaches have allowed high-throughput mapping of cis-regulatory elements (CREs) and their interactions in 3D, their precise role in regulating gene expression remains obscure. Recent complementary observations revealed that interactions between CREs frequently result in the formation of small-scale functional modules within topologically associating domains. Such chromatin modules likely emerge from a complex interplay between regulatory machineries assembled at CREs, including site-specific binding of transcription factors. Here, we review the methods that allow identifying chromatin modules, summarize possible mechanisms that steer CRE interactions within these modules, and discuss outstanding challenges to uncover how chromatin modules fit in our current understanding of the functional 3D genome.
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Affiliation(s)
- Guido van Mierlo
- Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Olga Pushkarev
- Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Judith F Kribelbauer
- Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Bart Deplancke
- Laboratory of Systems Biology and Genetics, Institute of Bioengineering, School of Life Sciences, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland; Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland.
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49
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Margasyuk SD, Vlasenok MA, Li G, Cao C, Pervouchine DD. RNAcontacts: A Pipeline for Predicting Contacts from RNA Proximity Ligation Assays. Acta Naturae 2023; 15:51-57. [PMID: 37153509 PMCID: PMC10154773 DOI: 10.32607/actanaturae.11893] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 02/20/2023] [Indexed: 05/09/2023] Open
Abstract
High-throughput RNA proximity ligation assays are molecular methods that are used to simultaneously analyze the spatial proximity of many RNAs in living cells. Their principle is based on cross-linking, fragmentation, and subsequent religation of RNAs, followed by high-throughput sequencing. The generated fragments have two different types of splits, one resulting from pre-mRNA splicing and the other formed by the ligation of spatially close RNA strands. Here, we present RNAcontacts, a universal pipeline for detecting RNA-RNA contacts in high-throughput RNA proximity ligation assays. RNAcontacts circumvents the inherent problem of mapping sequences with two distinct types of splits using a two-pass alignment, in which splice junctions are inferred from a control RNA-seq experiment on the first pass and then provided to the aligner as bona fide introns on the second pass. Compared to previously developed methods, our approach allows for a more sensitive detection of RNA contacts and has a higher specificity with respect to splice junctions that are present in the biological sample. RNAcontacts automatically extracts contacts, clusters their ligation points, computes the read support, and generates tracks for visualizing through the UCSC Genome Browser. The pipeline is implemented in Snakemake, a reproducible and scalable workflow management system for rapid and uniform processing of multiple datasets. RNAcontacts is a generic pipeline for the detection of RNA contacts that can be used with any proximity ligation method as long as one of the interacting partners is RNA. RNAcontacts is available via the GitHub repository https://github.com/smargasyuk/ RNAcontacts/.
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Affiliation(s)
- S. D. Margasyuk
- Skolkovo Institute of Science and Technology, Moscow, 121205 Russian Federation
| | - M. A. Vlasenok
- Skolkovo Institute of Science and Technology, Moscow, 121205 Russian Federation
| | - G. Li
- College of Life Sciences, Zhejiang University, Hangzhou, Zhejiang, ZJ310058 China
| | - Ch. Cao
- Key Laboratory of RNA Biology, Institute of Biophysics, Chinese Academy of Sciences, Beijing, 100101 China
| | - D. D. Pervouchine
- Skolkovo Institute of Science and Technology, Moscow, 121205 Russian Federation
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50
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Abstract
Chromosome conformation capture technology and its derivatives have been widely used to study genome organization. Among them, Hi-C (chromosome conformation capture coupling with high-throughput sequencing) is popular in dissecting chromatin architecture on the genome-wide level. However, the intrinsic limitations prevent its application when it comes to rare samples. Here, we present easy Hi-C, a biotin-free technology that dramatically reduces DNA loss and is suitable for low-input samples.
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Affiliation(s)
- Leina Lu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA.
| | - Fulai Jin
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Cleveland, OH, USA. .,Department of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH, USA. .,Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, OH, USA.
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