1
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Zhang L, Bartosovic M. Single-cell mapping of cell-type specific chromatin architecture in the central nervous system. Curr Opin Struct Biol 2024; 86:102824. [PMID: 38723561 DOI: 10.1016/j.sbi.2024.102824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 03/22/2024] [Accepted: 04/08/2024] [Indexed: 05/19/2024]
Abstract
Determining how chromatin is structured in the nucleus is critical to studying its role in gene regulation. Recent advances in the analysis of single-cell chromatin architecture have considerably improved our understanding of cell-type-specific chromosome conformation and nuclear architecture. In this review, we discuss the methods used for analysis of 3D chromatin conformation, including sequencing-based methods, imaging-based techniques, and computational approaches. We further review the application of these methods in the study of the role of chromatin topology in neural development and disorders.
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Affiliation(s)
- Letian Zhang
- Department of Biochemistry and Biophysics, Svante Arrhenius väg 16C, 162 53, Stockholm, Sweden. https://twitter.com/LetianZHANG_
| | - Marek Bartosovic
- Department of Biochemistry and Biophysics, Svante Arrhenius väg 16C, 162 53, Stockholm, Sweden.
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2
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Zhou T, Zhang R, Jia D, Doty RT, Munday AD, Gao D, Xin L, Abkowitz JL, Duan Z, Ma J. GAGE-seq concurrently profiles multiscale 3D genome organization and gene expression in single cells. Nat Genet 2024:10.1038/s41588-024-01745-3. [PMID: 38744973 DOI: 10.1038/s41588-024-01745-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 04/05/2024] [Indexed: 05/16/2024]
Abstract
The organization of mammalian genomes features a complex, multiscale three-dimensional (3D) architecture, whose functional significance remains elusive because of limited single-cell technologies that can concurrently profile genome organization and transcriptional activities. Here, we introduce genome architecture and gene expression by sequencing (GAGE-seq), a scalable, robust single-cell co-assay measuring 3D genome structure and transcriptome simultaneously within the same cell. Applied to mouse brain cortex and human bone marrow CD34+ cells, GAGE-seq characterized the intricate relationships between 3D genome and gene expression, showing that multiscale 3D genome features inform cell-type-specific gene expression and link regulatory elements to target genes. Integration with spatial transcriptomic data revealed in situ 3D genome variations in mouse cortex. Observations in human hematopoiesis unveiled discordant changes between 3D genome organization and gene expression, underscoring a complex, temporal interplay at the single-cell level. GAGE-seq provides a powerful, cost-effective approach for exploring genome structure and gene expression relationships at the single-cell level across diverse biological contexts.
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Affiliation(s)
- Tianming Zhou
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ruochi Zhang
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
- Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Deyong Jia
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Raymond T Doty
- Division of Hematology and Oncology, Department of Medicine/Fred Hutch Cancer Center, University of Washington, Seattle, WA, USA
| | - Adam D Munday
- Division of Hematology and Oncology, Department of Medicine/Fred Hutch Cancer Center, University of Washington, Seattle, WA, USA
| | - Daniel Gao
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
- Department of Chemistry, Pomona College, Claremont, CA, USA
| | - Li Xin
- Department of Urology, University of Washington, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - Janis L Abkowitz
- Division of Hematology and Oncology, Department of Medicine/Fred Hutch Cancer Center, University of Washington, Seattle, WA, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA
| | - Zhijun Duan
- Division of Hematology and Oncology, Department of Medicine/Fred Hutch Cancer Center, University of Washington, Seattle, WA, USA.
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA, USA.
| | - Jian Ma
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
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3
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Irastorza-Azcarate I, Kukalev A, Kempfer R, Thieme CJ, Mastrobuoni G, Markowski J, Loof G, Sparks TM, Brookes E, Natarajan KN, Sauer S, Fisher AG, Nicodemi M, Ren B, Schwarz RF, Kempa S, Pombo A. Extensive folding variability between homologous chromosomes in mammalian cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.08.591087. [PMID: 38766012 PMCID: PMC11100664 DOI: 10.1101/2024.05.08.591087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Genetic variation and 3D chromatin structure have major roles in gene regulation. Due to challenges in mapping chromatin conformation with haplotype-specific resolution, the effects of genetic sequence variation on 3D genome structure and gene expression imbalance remain understudied. Here, we applied Genome Architecture Mapping (GAM) to a hybrid mouse embryonic stem cell (mESC) line with high density of single nucleotide polymorphisms (SNPs). GAM resolved haplotype-specific 3D genome structures with high sensitivity, revealing extensive allelic differences in chromatin compartments, topologically associating domains (TADs), long-range enhancer-promoter contacts, and CTCF loops. Architectural differences often coincide with allele-specific differences in gene expression, mediated by Polycomb repression. We show that histone genes are expressed with allelic imbalance in mESCs, are involved in haplotype-specific chromatin contact marked by H3K27me3, and are targets of Polycomb repression through conditional knockouts of Ezh2 or Ring1b. Our work reveals highly distinct 3D folding structures between homologous chromosomes, and highlights their intricate connections with allelic gene expression.
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4
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Xiong K, Zhang R, Ma J. scGHOST: identifying single-cell 3D genome subcompartments. Nat Methods 2024; 21:814-822. [PMID: 38589516 PMCID: PMC11127718 DOI: 10.1038/s41592-024-02230-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 03/01/2024] [Indexed: 04/10/2024]
Abstract
Single-cell Hi-C (scHi-C) technologies allow for probing of genome-wide cell-to-cell variability in three-dimensional (3D) genome organization from individual cells. Computational methods have been developed to reveal single-cell 3D genome features based on scHi-C, including A/B compartments, topologically associating domains and chromatin loops. However, no method exists for annotating single-cell subcompartments, which is important for understanding chromosome spatial localization in single cells. Here we present scGHOST, a single-cell subcompartment annotation method using graph embedding with constrained random walk sampling. Applications of scGHOST to scHi-C data and contact maps derived from single-cell 3D genome imaging demonstrate reliable identification of single-cell subcompartments, offering insights into cell-to-cell variability of nuclear subcompartments. Using scHi-C data from complex tissues, scGHOST identifies cell-type-specific or allele-specific subcompartments linked to gene transcription across various cell types and developmental stages, suggesting functional implications of single-cell subcompartments. scGHOST is an effective method for annotating single-cell 3D genome subcompartments in a broad range of biological contexts.
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Affiliation(s)
- Kyle Xiong
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ruochi Zhang
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
- Eric and Wendy Schmidt Center, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jian Ma
- Ray and Stephanie Lane Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
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5
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Prince GS, Reynolds M, Martina V, Sun H. Gene-environmental regulation of the postnatal post-mitotic neuronal maturation. Trends Genet 2024:S0168-9525(24)00068-4. [PMID: 38658255 DOI: 10.1016/j.tig.2024.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/20/2024] [Accepted: 03/21/2024] [Indexed: 04/26/2024]
Abstract
Embryonic neurodevelopment, particularly neural progenitor differentiation into post-mitotic neurons, has been extensively studied. While the number and composition of post-mitotic neurons remain relatively constant from birth to adulthood, the brain undergoes significant postnatal maturation marked by major property changes frequently disrupted in neural diseases. This review first summarizes recent characterizations of the functional and molecular maturation of the postnatal nervous system. We then review regulatory mechanisms controlling the precise gene expression changes crucial for the intricate sequence of maturation events, highlighting experience-dependent versus cell-intrinsic genetic timer mechanisms. Despite significant advances in understanding of the gene-environmental regulation of postnatal neuronal maturation, many aspects remain unknown. The review concludes with our perspective on exciting future research directions in the next decade.
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Affiliation(s)
- Gabrielle S Prince
- Department of Cell, Developmental, and Integrative Biology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Molly Reynolds
- Department of Cell, Developmental, and Integrative Biology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Verdion Martina
- Department of Cell, Developmental, and Integrative Biology, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - HaoSheng Sun
- Department of Cell, Developmental, and Integrative Biology, The University of Alabama at Birmingham, Birmingham, AL, USA; Freeman Hrabowski Scholar, Howard Hughes Medical Institute, Chevy Chase, MD, USA.
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6
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Chang L, Xie Y, Taylor B, Wang Z, Sun J, Tan TR, Bejar R, Chen CC, Furnari FB, Hu M, Ren B. Droplet Hi-C for Fast and Scalable Profiling of Chromatin Architecture in Single Cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.18.590148. [PMID: 38712075 PMCID: PMC11071305 DOI: 10.1101/2024.04.18.590148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Comprehensive analysis of chromatin architecture is crucial for understanding the gene regulatory programs during development and in disease pathogenesis, yet current methods often inadequately address the unique challenges presented by analysis of heterogeneous tissue samples. Here, we introduce Droplet Hi-C, which employs a commercial microfluidic device for high-throughput, single-cell chromatin conformation profiling in droplets. Using Droplet Hi-C, we mapped the chromatin architecture at single-cell resolution from the mouse cortex and analyzed gene regulatory programs in major cortical cell types. Additionally, we used this technique to detect copy number variation (CNV), structural variations (SVs) and extrachromosomal DNA (ecDNA) in cancer cells, revealing clonal dynamics and other oncogenic events during treatment. We further refined this technique to allow for joint profiling of chromatin architecture and transcriptome in single cells, facilitating a more comprehensive exploration of the links between chromatin architecture and gene expression in both normal tissues and tumors. Thus, Droplet Hi-C not only addresses critical gaps in chromatin analysis of heterogeneous tissues but also emerges as a versatile tool enhancing our understanding of gene regulation in health and disease.
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Affiliation(s)
- Lei Chang
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Yang Xie
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA, USA
| | - Brett Taylor
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Medical Scientist Training Program, University of California, San Diego, La Jolla, CA, USA
| | - Zhaoning Wang
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Jiachen Sun
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
- Department of Systems Biology and Bioinformatics, Case Western Reserve University School of Medicine, Cleveland, OH, USA
| | - Tuyet R. Tan
- Moores Cancer Center, UC San Diego, La Jolla, CA, USA
| | - Rafael Bejar
- Moores Cancer Center, UC San Diego, La Jolla, CA, USA
| | - Clark C. Chen
- Department of Neurosurgery, University of Minnesota, Minneapolis, MN, USA
| | - Frank B. Furnari
- Department of Medicine, University of California, San Diego School of Medicine, La Jolla, CA, USA
| | - Ming Hu
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Center for Epigenomics, Institute for Genomic Medicine, Moores Cancer Center, University of California, San Diego, School of Medicine, La Jolla, CA, USA
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7
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Lando D, Ma X, Cao Y, Jartseva A, Stevens TJ, Boucher W, Reynolds N, Montibus B, Hall D, Lackner A, Ragheb R, Leeb M, Hendrich BD, Laue ED. Enhancer-promoter interactions are reconfigured through the formation of long-range multiway hubs as mouse ES cells exit pluripotency. Mol Cell 2024; 84:1406-1421.e8. [PMID: 38490199 DOI: 10.1016/j.molcel.2024.02.015] [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: 02/02/2023] [Revised: 12/19/2023] [Accepted: 02/14/2024] [Indexed: 03/17/2024]
Abstract
Enhancers bind transcription factors, chromatin regulators, and non-coding transcripts to modulate the expression of target genes. Here, we report 3D genome structures of single mouse ES cells as they are induced to exit pluripotency and transition through a formative stage prior to undergoing neuroectodermal differentiation. We find that there is a remarkable reorganization of 3D genome structure where inter-chromosomal intermingling increases dramatically in the formative state. This intermingling is associated with the formation of a large number of multiway hubs that bring together enhancers and promoters with similar chromatin states from typically 5-8 distant chromosomal sites that are often separated by many Mb from each other. In the formative state, genes important for pluripotency exit establish contacts with emerging enhancers within these multiway hubs, suggesting that the structural changes we have observed may play an important role in modulating transcription and establishing new cell identities.
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Affiliation(s)
- David Lando
- Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK
| | - Xiaoyan Ma
- Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK
| | - Yang Cao
- Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK
| | | | - Tim J Stevens
- MRC Laboratory of Molecular Biology, Cambridge Biomedical Campus, Cambridge CB2 0QH, UK
| | - Wayne Boucher
- Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK
| | - Nicola Reynolds
- Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge CB2 0AW, UK
| | - Bertille Montibus
- Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge CB2 0AW, UK
| | - Dominic Hall
- Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK; Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge CB2 0AW, UK
| | - Andreas Lackner
- Max Perutz Laboratories Vienna, University of Vienna, Vienna Biocenter, Vienna, Austria
| | - Ramy Ragheb
- Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge CB2 0AW, UK
| | - Martin Leeb
- Max Perutz Laboratories Vienna, University of Vienna, Vienna Biocenter, Vienna, Austria
| | - Brian D Hendrich
- Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK; Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge CB2 0AW, UK.
| | - Ernest D Laue
- Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK; Cambridge Stem Cell Institute, Jeffrey Cheah Biomedical Centre, Cambridge CB2 0AW, UK.
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8
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Wu H, Zhang J, Jian F, Chen JP, Zheng Y, Tan L, Sunney Xie X. Simultaneous single-cell three-dimensional genome and gene expression profiling uncovers dynamic enhancer connectivity underlying olfactory receptor choice. Nat Methods 2024:10.1038/s41592-024-02239-0. [PMID: 38622459 DOI: 10.1038/s41592-024-02239-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 03/07/2024] [Indexed: 04/17/2024]
Abstract
The simultaneous measurement of three-dimensional (3D) genome structure and gene expression of individual cells is critical for understanding a genome's structure-function relationship, yet this is challenging for existing methods. Here we present 'Linking mRNA to Chromatin Architecture (LiMCA)', which jointly profiles the 3D genome and transcriptome with exceptional sensitivity and from low-input materials. Combining LiMCA and our high-resolution scATAC-seq assay, METATAC, we successfully characterized chromatin accessibility, as well as paired 3D genome structures and gene expression information, of individual developing olfactory sensory neurons. We expanded the repertoire of known olfactory receptor (OR) enhancers and discovered unexpected rules of their dynamics: OR genes and their enhancers are most accessible during early differentiation. Furthermore, we revealed the dynamic spatial relationship between ORs and enhancers behind stepwise OR expression. These findings offer valuable insights into how 3D connectivity of ORs and enhancers dynamically orchestrate the 'one neuron-one receptor' selection process.
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Affiliation(s)
- Honggui Wu
- Biomedical Pioneering Innovation Center (BIOPIC), and School of Life Sciences, Peking University, Beijing, China
- Changping Laboratory, Beijing, China
| | - Jiankun Zhang
- Biomedical Pioneering Innovation Center (BIOPIC), and School of Life Sciences, Peking University, Beijing, China
- Changping Laboratory, Beijing, China
| | - Fanchong Jian
- Biomedical Pioneering Innovation Center (BIOPIC), and School of Life Sciences, Peking University, Beijing, China
- Changping Laboratory, Beijing, China
- College of Chemistry and Molecular Engineering, Peking University, Beijing, China
| | - Jinxin Phaedo Chen
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm, Sweden
| | - Yinghui Zheng
- Biomedical Pioneering Innovation Center (BIOPIC), and School of Life Sciences, Peking University, Beijing, China
| | - Longzhi Tan
- Department of Neurobiology, Stanford University, Stanford, CA, USA.
| | - X Sunney Xie
- Biomedical Pioneering Innovation Center (BIOPIC), and School of Life Sciences, Peking University, Beijing, China.
- Changping Laboratory, Beijing, China.
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9
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Li J, Lin Y, Li D, He M, Kui H, Bai J, Chen Z, Gou Y, Zhang J, Wang T, Tang Q, Kong F, Jin L, Li M. Building Haplotype-Resolved 3D Genome Maps of Chicken Skeletal Muscle. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2305706. [PMID: 38582509 DOI: 10.1002/advs.202305706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 03/07/2024] [Indexed: 04/08/2024]
Abstract
Haplotype-resolved 3D chromatin architecture related to allelic differences in avian skeletal muscle development has not been addressed so far, although chicken husbandry for meat consumption has been prevalent feature of cultures on every continent for more than thousands of years. Here, high-resolution Hi-C diploid maps (1.2-kb maximum resolution) are generated for skeletal muscle tissues in chicken across three developmental stages (embryonic day 15 to day 30 post-hatching). The sequence features governing spatial arrangement of chromosomes and characterize homolog pairing in the nucleus, are identified. Multi-scale characterization of chromatin reorganization between stages from myogenesis in the fetus to myofiber hypertrophy after hatching show concordant changes in transcriptional regulation by relevant signaling pathways. Further interrogation of parent-of-origin-specific chromatin conformation supported that genomic imprinting is absent in birds. This study also reveals promoter-enhancer interaction (PEI) differences between broiler and layer haplotypes in skeletal muscle development-related genes are related to genetic variation between breeds, however, only a minority of breed-specific variations likely contribute to phenotypic divergence in skeletal muscle potentially via allelic PEI rewiring. Beyond defining the haplotype-specific 3D chromatin architecture in chicken, this study provides a rich resource for investigating allelic regulatory divergence among chicken breeds.
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Affiliation(s)
- Jing Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yu Lin
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Diyan Li
- School of Pharmacy, Chengdu University, Chengdu, 610106, China
| | - Mengnan He
- Wildlife Conservation Research Department, Chengdu Research Base of Giant Panda Breeding, Chengdu, 610057, China
| | - Hua Kui
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jingyi Bai
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Ziyu Chen
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Yuwei Gou
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jiaman Zhang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Tao Wang
- School of Pharmacy, Chengdu University, Chengdu, 610106, China
| | - Qianzi Tang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Fanli Kong
- College of Life Science, Sichuan Agricultural University, Ya'an, 625014, China
| | - Long Jin
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Mingzhou Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
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10
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Lin Y, Li J, Gu Y, Jin L, Bai J, Zhang J, Wang Y, Liu P, Long K, He M, Li D, Liu C, Han Z, Zhang Y, Li X, Zeng B, Lu L, Kong F, Sun Y, Fan Y, Wang X, Wang T, Jiang A, Ma J, Shen L, Zhu L, Jiang Y, Tang G, Fan X, Liu Q, Li H, Wang J, Chen L, Ge L, Li X, Tang Q, Li M. Haplotype-resolved 3D chromatin architecture of the hybrid pig. Genome Res 2024; 34:310-325. [PMID: 38479837 PMCID: PMC10984390 DOI: 10.1101/gr.278101.123] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 02/15/2024] [Indexed: 03/22/2024]
Abstract
In diploid mammals, allele-specific three-dimensional (3D) genome architecture may lead to imbalanced gene expression. Through ultradeep in situ Hi-C sequencing of three representative somatic tissues (liver, skeletal muscle, and brain) from hybrid pigs generated by reciprocal crosses of phenotypically and physiologically divergent Berkshire and Tibetan pigs, we uncover extensive chromatin reorganization between homologous chromosomes across multiple scales. Haplotype-based interrogation of multi-omic data revealed the tissue dependence of 3D chromatin conformation, suggesting that parent-of-origin-specific conformation may drive gene imprinting. We quantify the effects of genetic variations and histone modifications on allelic differences of long-range promoter-enhancer contacts, which likely contribute to the phenotypic differences between the parental pig breeds. We also observe the fine structure of somatically paired homologous chromosomes in the pig genome, which has a functional implication genome-wide. This work illustrates how allele-specific chromatin architecture facilitates concomitant shifts in allele-biased gene expression, as well as the possible consequential phenotypic changes in mammals.
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Affiliation(s)
- Yu Lin
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Jing Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China;
| | - Yiren Gu
- College of Animal and Veterinary Sciences, Southwest Minzu University, Chengdu 610041, China
- Animal Breeding and Genetics Key Laboratory of Sichuan Province, Sichuan Animal Science Academy, Chengdu 610066, China
| | - Long Jin
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Jingyi Bai
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Jiaman Zhang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Yujie Wang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Pengliang Liu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Keren Long
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Mengnan He
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Diyan Li
- School of Pharmacy, Chengdu University, Chengdu 610106, China
| | - Can Liu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Ziyin Han
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Yu Zhang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Xiaokai Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Bo Zeng
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Lu Lu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Fanli Kong
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Ying Sun
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
- Institute of Geriatric Health, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610072, China
| | - Yongliang Fan
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Xun Wang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Tao Wang
- School of Pharmacy, Chengdu University, Chengdu 610106, China
| | - An'an Jiang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Jideng Ma
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Linyuan Shen
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Li Zhu
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Yanzhi Jiang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Guoqing Tang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Xiaolan Fan
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Qingyou Liu
- Animal Molecular Design and Precise Breeding Key Laboratory of Guangdong Province, School of Life Science and Engineering, Foshan University, Foshan 528225, China
| | - Hua Li
- Animal Molecular Design and Precise Breeding Key Laboratory of Guangdong Province, School of Life Science and Engineering, Foshan University, Foshan 528225, China
| | - Jinyong Wang
- Pig Industry Sciences Key Laboratory of Ministry of Agriculture and Rural Affairs, Chongqing Academy of Animal Sciences, Chongqing 402460, China
- National Center of Technology Innovation for Pigs, Chongqing 402460, China
| | - Li Chen
- Pig Industry Sciences Key Laboratory of Ministry of Agriculture and Rural Affairs, Chongqing Academy of Animal Sciences, Chongqing 402460, China
- National Center of Technology Innovation for Pigs, Chongqing 402460, China
| | - Liangpeng Ge
- Pig Industry Sciences Key Laboratory of Ministry of Agriculture and Rural Affairs, Chongqing Academy of Animal Sciences, Chongqing 402460, China
- National Center of Technology Innovation for Pigs, Chongqing 402460, China
| | - Xuewei Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China
| | - Qianzi Tang
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China;
| | - Mingzhou Li
- State Key Laboratory of Swine and Poultry Breeding Industry, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu 611130, China;
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11
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Li H, Playter C, Das P, McCord RP. Chromosome compartmentalization: causes, changes, consequences, and conundrums. Trends Cell Biol 2024:S0962-8924(24)00021-7. [PMID: 38395734 DOI: 10.1016/j.tcb.2024.01.009] [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: 10/31/2023] [Revised: 01/12/2024] [Accepted: 01/22/2024] [Indexed: 02/25/2024]
Abstract
The spatial segregation of the genome into compartments is a major feature of 3D genome organization. New data on mammalian chromosome organization across different conditions reveal important information about how and why these compartments form and change. A combination of epigenetic state, nuclear body tethering, physical forces, gene expression, and replication timing (RT) can all influence the establishment and alteration of chromosome compartments. We review the causes and implications of genomic regions undergoing a 'compartment switch' that changes their physical associations and spatial location in the nucleus. About 20-30% of genomic regions change compartment during cell differentiation or cancer progression, whereas alterations in response to a stimulus within a cell type are usually much more limited. However, even a change in 1-2% of genomic bins may have biologically relevant implications. Finally, we review the effects of compartment changes on gene regulation, DNA damage repair, replication, and the physical state of the cell.
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Affiliation(s)
- Heng Li
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA
| | - Christopher Playter
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA
| | - Priyojit Das
- University of Tennessee-Oak Ridge National Laboratory (UT-ORNL) Graduate School of Genome Science and Technology, University of Tennessee, Knoxville, TN, USA
| | - Rachel Patton McCord
- Department of Biochemistry and Cellular and Molecular Biology, University of Tennessee, Knoxville, TN, USA.
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12
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Kumari A, Vertii A. Perspective: "Current understanding of NADs dynamics and mechanisms of Disease". Gene 2024; 894:147960. [PMID: 37923094 DOI: 10.1016/j.gene.2023.147960] [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: 07/27/2023] [Revised: 10/09/2023] [Accepted: 10/31/2023] [Indexed: 11/07/2023]
Abstract
Chromatin architecture is essential for gene regulation, and multiple levels of the 3D chromatin organization exhibit dynamic changes during organismal development and cell differentiation. Heterochromatin, termed compartment B in Hi-C datasets, is a phase-separating gene-silencing form of chromatin, preferentially located at the two nuclear sites, nuclear (lamina-associate chromatin domains, LADs) and nucleoli (nucleoli-associated chromatin domains, NADs) peripheries. LADs and NADs contain both interchangeable and location-specific chromatin domains. Recent studies suggest striking dynamics in LADs and NADs during the differentiation of embryonic stem cells into neural progenitors and neurons. Here we discuss recent advances in understanding NADs changes during neuronal differentiation and future questions on how NADs integrity can contribute to healthy neurodevelopment and neurodevelopment diseases.
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Affiliation(s)
- Amrita Kumari
- Department of Molecular, Cellular and Cancer Biology, University of Massachusetts Medical School, Worcester, MA 1605, US
| | - Anastassiia Vertii
- Department of Molecular, Cellular and Cancer Biology, University of Massachusetts Medical School, Worcester, MA 1605, US.
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13
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Zhang Y, Boninsegna L, Yang M, Misteli T, Alber F, Ma J. Computational methods for analysing multiscale 3D genome organization. Nat Rev Genet 2024; 25:123-141. [PMID: 37673975 PMCID: PMC11127719 DOI: 10.1038/s41576-023-00638-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/12/2023] [Indexed: 09/08/2023]
Abstract
Recent progress in whole-genome mapping and imaging technologies has enabled the characterization of the spatial organization and folding of the genome in the nucleus. In parallel, advanced computational methods have been developed to leverage these mapping data to reveal multiscale three-dimensional (3D) genome features and to provide a more complete view of genome structure and its connections to genome functions such as transcription. Here, we discuss how recently developed computational tools, including machine-learning-based methods and integrative structure-modelling frameworks, have led to a systematic, multiscale delineation of the connections among different scales of 3D genome organization, genomic and epigenomic features, functional nuclear components and genome function. However, approaches that more comprehensively integrate a wide variety of genomic and imaging datasets are still needed to uncover the functional role of 3D genome structure in defining cellular phenotypes in health and disease.
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Affiliation(s)
- Yang Zhang
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Lorenzo Boninsegna
- Department of Microbiology, Immunology and Molecular Genetics and Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, USA
| | - Muyu Yang
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Tom Misteli
- Center for Cancer Research, National Cancer Institute, Bethesda, MD, USA.
| | - Frank Alber
- Department of Microbiology, Immunology and Molecular Genetics and Institute for Quantitative and Computational Biosciences, University of California Los Angeles, Los Angeles, CA, USA.
| | - Jian Ma
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA.
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14
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Li Y, Li W, Chen J, Qiu S, Liu Y, Xu L, Tian T, Li JP. Deciphering single-cell protein secretion and gene expressions by constructing cell-antibody conjugates. Bioorg Chem 2024; 143:106987. [PMID: 38039927 DOI: 10.1016/j.bioorg.2023.106987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 11/13/2023] [Accepted: 11/19/2023] [Indexed: 12/03/2023]
Abstract
Secreted proteins play critical roles in regulating immune responses, exerting cytotoxic effects on tumor cells, promoting inflammatory processes, and influencing cellular metabolism. Deciphering the intricate relationship between the heterogeneity of secreted proteins and their transcriptional states is pivotal in the study of cellular heterogeneity. Here we proposed a cell-antibody conjugate-based sequencing methodology (Cellab-seq) for joint characterization of secreted proteins and transcriptome. Cellab-seq utilizes a chemoenzymatic strategy to construct cell-antibody conjugates, which enables the capture of secreted proteins and their signal transduction with the incorporation of barcode detection antibodies. We applied Cellab-seq to investigate how gene expression influences the activity of secreted proteins in NK cells. Altogether, this strategy facilitates a nuanced understanding of cellular dynamics under diverse physiological conditions, ultimately contributing to the prevention, diagnosis and treatment of diseases.
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Affiliation(s)
- Yachao Li
- State Key Laboratory of Coordination Chemistry, Chemistry and Biomedicine Innovation Center (ChemBIC), School of Chemistry and Chemical Engineering, Nanjing University, 163 Xianlin Avenue, Nanjing, Jiangsu 210023, China
| | - Wannan Li
- State Key Laboratory of Coordination Chemistry, Chemistry and Biomedicine Innovation Center (ChemBIC), School of Chemistry and Chemical Engineering, Nanjing University, 163 Xianlin Avenue, Nanjing, Jiangsu 210023, China
| | - Jiashang Chen
- State Key Laboratory of Coordination Chemistry, Chemistry and Biomedicine Innovation Center (ChemBIC), School of Chemistry and Chemical Engineering, Nanjing University, 163 Xianlin Avenue, Nanjing, Jiangsu 210023, China
| | - Shuang Qiu
- State Key Laboratory of Coordination Chemistry, Chemistry and Biomedicine Innovation Center (ChemBIC), School of Chemistry and Chemical Engineering, Nanjing University, 163 Xianlin Avenue, Nanjing, Jiangsu 210023, China
| | - Yilong Liu
- State Key Laboratory of Coordination Chemistry, Chemistry and Biomedicine Innovation Center (ChemBIC), School of Chemistry and Chemical Engineering, Nanjing University, 163 Xianlin Avenue, Nanjing, Jiangsu 210023, China
| | - Lingjie Xu
- Vazyme Biotech, Red Maple Hi-tech Industry Park, Kechuang Road, Qixia District, Nanjing, Jiangsu 210023, China
| | - Tian Tian
- State Key Laboratory of Coordination Chemistry, Chemistry and Biomedicine Innovation Center (ChemBIC), School of Chemistry and Chemical Engineering, Nanjing University, 163 Xianlin Avenue, Nanjing, Jiangsu 210023, China.
| | - Jie P Li
- State Key Laboratory of Coordination Chemistry, Chemistry and Biomedicine Innovation Center (ChemBIC), School of Chemistry and Chemical Engineering, Nanjing University, 163 Xianlin Avenue, Nanjing, Jiangsu 210023, China.
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15
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Kocanova S, Raynal F, Goiffon I, Oksuz BA, Baú D, Kamgoué A, Cantaloube S, Zhan Y, Lajoie B, Marti-Renom MA, Dekker J, Bystricky K. Enhancer-driven 3D chromatin domain folding modulates transcription in human mammary tumor cells. Life Sci Alliance 2024; 7:e202302154. [PMID: 37989525 PMCID: PMC10663337 DOI: 10.26508/lsa.202302154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Revised: 11/03/2023] [Accepted: 11/06/2023] [Indexed: 11/23/2023] Open
Abstract
The genome is organized in functional compartments and structural domains at the sub-megabase scale. How within these domains interactions between numerous cis-acting enhancers and promoters regulate transcription remains an open question. Here, we determined chromatin folding and composition over several hundred kb around estrogen-responsive genes in human breast cancer cell lines after hormone stimulation. Modeling of 5C data at 1.8 kb resolution was combined with quantitative 3D analysis of multicolor FISH measurements at 100 nm resolution and integrated with ChIP-seq data on transcription factor binding and histone modifications. We found that rapid estradiol induction of the progesterone gene expression occurs in the context of preexisting, cell type-specific chromosomal architectures encompassing the 90 kb progesterone gene coding region and an enhancer-spiked 5' 300 kb upstream genomic region. In response to estradiol, interactions between estrogen receptor α (ERα) bound regulatory elements are reinforced. Whereas initial enhancer-gene contacts coincide with RNA Pol 2 binding and transcription initiation, sustained hormone stimulation promotes ERα accumulation creating a regulatory hub stimulating transcript synthesis. In addition to implications for estrogen receptor signaling, we uncover that preestablished chromatin architectures efficiently regulate gene expression upon stimulation without the need for de novo extensive rewiring of long-range chromatin interactions.
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Affiliation(s)
- Silvia Kocanova
- Molecular, Cellular and Developmental Biology Unit (MCD), Centre de Biologie Integrative (CBI), University of Toulouse, UPS, CNRS, Toulouse, France
| | - Flavien Raynal
- Molecular, Cellular and Developmental Biology Unit (MCD), Centre de Biologie Integrative (CBI), University of Toulouse, UPS, CNRS, Toulouse, France
| | - Isabelle Goiffon
- Molecular, Cellular and Developmental Biology Unit (MCD), Centre de Biologie Integrative (CBI), University of Toulouse, UPS, CNRS, Toulouse, France
| | - Betul Akgol Oksuz
- https://ror.org/0464eyp60 Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Davide Baú
- Centre Nacional d'Anàlisi Genòmica (CNAG), Barcelona, Spain
| | - Alain Kamgoué
- Molecular, Cellular and Developmental Biology Unit (MCD), Centre de Biologie Integrative (CBI), University of Toulouse, UPS, CNRS, Toulouse, France
| | - Sylvain Cantaloube
- Molecular, Cellular and Developmental Biology Unit (MCD), Centre de Biologie Integrative (CBI), University of Toulouse, UPS, CNRS, Toulouse, France
| | - Ye Zhan
- https://ror.org/0464eyp60 Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Bryan Lajoie
- https://ror.org/0464eyp60 Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Marc A Marti-Renom
- Centre Nacional d'Anàlisi Genòmica (CNAG), Barcelona, Spain
- Genome Biology Program, Centre de Regulació Genòmica (CRG), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
| | - Job Dekker
- https://ror.org/0464eyp60 Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Kerstin Bystricky
- Molecular, Cellular and Developmental Biology Unit (MCD), Centre de Biologie Integrative (CBI), University of Toulouse, UPS, CNRS, Toulouse, France
- Institut Universitaire de France (IUF), Paris, France
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16
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Li Z, Schlick T. Hi-BDiSCO: folding 3D mesoscale genome structures from Hi-C data using brownian dynamics. Nucleic Acids Res 2024; 52:583-599. [PMID: 38015443 PMCID: PMC10810283 DOI: 10.1093/nar/gkad1121] [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: 07/06/2023] [Revised: 10/12/2023] [Accepted: 11/22/2023] [Indexed: 11/29/2023] Open
Abstract
The structure and dynamics of the eukaryotic genome are intimately linked to gene regulation and transcriptional activity. Many chromosome conformation capture experiments like Hi-C have been developed to detect genome-wide contact frequencies and quantify loop/compartment structures for different cellular contexts and time-dependent processes. However, a full understanding of these events requires explicit descriptions of representative chromatin and chromosome configurations. With the exponentially growing amount of data from Hi-C experiments, many methods for deriving 3D structures from contact frequency data have been developed. Yet, most reconstruction methods use polymer models with low resolution to predict overall genome structure. Here we present a Brownian Dynamics (BD) approach termed Hi-BDiSCO for producing 3D genome structures from Hi-C and Micro-C data using our mesoscale-resolution chromatin model based on the Discrete Surface Charge Optimization (DiSCO) model. Our approach integrates reconstruction with chromatin simulations at nucleosome resolution with appropriate biophysical parameters. Following a description of our protocol, we present applications to the NXN, HOXC, HOXA and Fbn2 mouse genes ranging in size from 50 to 100 kb. Such nucleosome-resolution genome structures pave the way for pursuing many biomedical applications related to the epigenomic regulation of chromatin and control of human disease.
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Affiliation(s)
- Zilong Li
- Department of Chemistry, 100 Washington Square East, Silver Building, New York University, New York, NY 10003, USA
- Simons Center for Computational Physical Chemistry, 24 Waverly Place, Silver Building, New York University, New York, NY 10003, USA
| | - Tamar Schlick
- Department of Chemistry, 100 Washington Square East, Silver Building, New York University, New York, NY 10003, USA
- Courant Institute of Mathematical Sciences, New York University, 251 Mercer St., New York, NY 10012, USA
- New York University-East China Normal University Center for Computational Chemistry, New York University Shanghai, Shanghai 200122, China
- Simons Center for Computational Physical Chemistry, 24 Waverly Place, Silver Building, New York University, New York, NY 10003, USA
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17
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Kaplan HS, Logeman BL, Zhang K, Santiago C, Sohail N, Naumenko S, Ho Sui SJ, Ginty DD, Ren B, Dulac C. Sensory Input, Sex, and Function Shape Hypothalamic Cell Type Development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.23.576835. [PMID: 38328205 PMCID: PMC10849564 DOI: 10.1101/2024.01.23.576835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2024]
Abstract
Mammalian behavior and physiology undergo dramatic changes in early life. Young animals rely on conspecifics to meet their homeostatic needs, until weaning and puberty initiate nutritional independence and sex-specific social interactions, respectively. How neuronal populations regulating homeostatic functions and social behaviors develop and mature during these transitions remains unclear. We used paired transcriptomic and chromatin accessibility profiling to examine the developmental trajectories of neuronal populations in the hypothalamic preoptic region, where cell types with key roles in physiological and behavioral control have been identified1-6. These data reveal a remarkable diversity of developmental trajectories shaped by the sex of the animal, and the location and behavioral or physiological function of the corresponding cell types. We identify key stages of preoptic development, including the perinatal emergence of sex differences, postnatal maturation and subsequent refinement of signaling networks, and nonlinear transcriptional changes accelerating at the time of weaning and puberty. We assessed preoptic development in various sensory mutants and find a major role for vomeronasal sensing in the timing of preoptic cell type maturation. These results provide novel insights into the development of neurons controlling homeostatic functions and social behaviors and lay ground for examining the dynamics of these functions in early life.
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Affiliation(s)
- Harris S. Kaplan
- Department of Molecular and Cellular Biology, Howard Hughes Medical Institute, Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Brandon L. Logeman
- Department of Molecular and Cellular Biology, Howard Hughes Medical Institute, Center for Brain Science, Harvard University, Cambridge, MA, USA
| | - Kai Zhang
- Department of Cellular and Molecular Medicine, Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA 92093, USA
- Current address: Westlake Laboratory of Life Sciences and Biomedicine, School of Life Sciences, Westlake University, Hangzhou, China
| | - Celine Santiago
- Department of Neurobiology, Harvard Medical School, Howard Hughes Medical Institute, 220 Longwood Ave, Boston, MA, 02115, USA
| | - Noor Sohail
- Department of Biostatistics, Harvard Chan School of Public Health, Boston, MA, USA
| | - Serhiy Naumenko
- Department of Biostatistics, Harvard Chan School of Public Health, Boston, MA, USA
- Newborn Screening Ontario, Ottawa, ON, Canada
| | - Shannan J. Ho Sui
- Department of Biostatistics, Harvard Chan School of Public Health, Boston, MA, USA
| | - David D. Ginty
- Department of Neurobiology, Harvard Medical School, Howard Hughes Medical Institute, 220 Longwood Ave, Boston, MA, 02115, USA
| | - Bing Ren
- Department of Cellular and Molecular Medicine, Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA 92093, USA
| | - Catherine Dulac
- Department of Molecular and Cellular Biology, Howard Hughes Medical Institute, Center for Brain Science, Harvard University, Cambridge, MA, USA
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18
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Hua D, Gu M, Zhang X, Du Y, Xie H, Qi L, Du X, Bai Z, Zhu X, Tian D. DiffDomain enables identification of structurally reorganized topologically associating domains. Nat Commun 2024; 15:502. [PMID: 38218905 PMCID: PMC10787792 DOI: 10.1038/s41467-024-44782-6] [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: 12/16/2022] [Accepted: 01/02/2024] [Indexed: 01/15/2024] Open
Abstract
Topologically associating domains (TADs) are critical structural units in three-dimensional genome organization of mammalian genome. Dynamic reorganizations of TADs between health and disease states are associated with essential genome functions. However, computational methods for identifying reorganized TADs are still in the early stages of development. Here, we present DiffDomain, an algorithm leveraging high-dimensional random matrix theory to identify structurally reorganized TADs using high-throughput chromosome conformation capture (Hi-C) contact maps. Method comparison using multiple real Hi-C datasets reveals that DiffDomain outperforms alternative methods for false positive rates, true positive rates, and identifying a new subtype of reorganized TADs. Applying DiffDomain to Hi-C data from different cell types and disease states demonstrates its biological relevance. Identified reorganized TADs are associated with structural variations and epigenomic changes such as changes in CTCF binding sites. By applying to a single-cell Hi-C data from mouse neuronal development, DiffDomain can identify reorganized TADs between cell types with reasonable reproducibility using pseudo-bulk Hi-C data from as few as 100 cells per condition. Moreover, DiffDomain reveals differential cell-to-population variability and heterogeneous cell-to-cell variability in TADs. Therefore, DiffDomain is a statistically sound method for better comparative analysis of TADs using both Hi-C and single-cell Hi-C data.
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Affiliation(s)
- Dunming Hua
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 510275, China
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Ming Gu
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 510275, China
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Xiao Zhang
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 510275, China
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Yanyi Du
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 510275, China
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Hangcheng Xie
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 510275, China
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Li Qi
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, 400042, China
| | - Xiangjun Du
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 510275, China
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China
| | - Zhidong Bai
- KLASMOE & School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, 130024, China
| | - Xiaopeng Zhu
- MyCellome LLC., Allison Park, PA, 15101, USA
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, 15213, USA
| | - Dechao Tian
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, 510275, China.
- Department of Biostatistics and Systems Biology, School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, 518107, China.
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19
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Pourmorady AD, Bashkirova EV, Chiariello AM, Belagzhal H, Kodra A, Duffié R, Kahiapo J, Monahan K, Pulupa J, Schieren I, Osterhoudt A, Dekker J, Nicodemi M, Lomvardas S. RNA-mediated symmetry breaking enables singular olfactory receptor choice. Nature 2024; 625:181-188. [PMID: 38123679 PMCID: PMC10765522 DOI: 10.1038/s41586-023-06845-4] [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: 03/20/2023] [Accepted: 11/07/2023] [Indexed: 12/23/2023]
Abstract
Olfactory receptor (OR) choice provides an extreme example of allelic competition for transcriptional dominance, where every olfactory neuron stably transcribes one of approximately 2,000 or more OR alleles1,2. OR gene choice is mediated by a multichromosomal enhancer hub that activates transcription at a single OR3,4, followed by OR-translation-dependent feedback that stabilizes this choice5,6. Here, using single-cell genomics, we show formation of many competing hubs with variable enhancer composition, only one of which retains euchromatic features and transcriptional competence. Furthermore, we provide evidence that OR transcription recruits enhancers and reinforces enhancer hub activity locally, whereas OR RNA inhibits transcription of competing ORs over distance, promoting transition to transcriptional singularity. Whereas OR transcription is sufficient to break the symmetry between equipotent enhancer hubs, OR translation stabilizes transcription at the prevailing hub, indicating that there may be sequential non-coding and coding mechanisms that are implemented by OR alleles for transcriptional prevalence. We propose that coding OR mRNAs possess non-coding functions that influence nuclear architecture, enhance their own transcription and inhibit transcription from their competitors, with generalizable implications for probabilistic cell fate decisions.
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Affiliation(s)
- Ariel D Pourmorady
- Vagelos College of Physicians and Surgeons, Columbia University New York, New York, NY, USA
- Department of Neuroscience, Columbia University, New York, NY, USA
- Mortimer B. Zuckerman Mind, Brain, and Behavior Institute, Columbia University New York, New York, NY, USA
| | - Elizaveta V Bashkirova
- Mortimer B. Zuckerman Mind, Brain, and Behavior Institute, Columbia University New York, New York, NY, USA
- Integrated Program in Cellular, Molecular and Biomedical Studies, Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Andrea M Chiariello
- Department of Physics 'Ettore Pancini', University of Naples, and INFN, Napoli, Italy
| | - Houda Belagzhal
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Albana Kodra
- Integrated Program in Cellular, Molecular and Biomedical Studies, Vagelos College of Physicians and Surgeons, New York, NY, USA
- Department of Genetics and Development, Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Rachel Duffié
- Mortimer B. Zuckerman Mind, Brain, and Behavior Institute, Columbia University New York, New York, NY, USA
| | - Jerome Kahiapo
- Department of Molecular Biology & Biochemistry, Rutgers School of Arts and Sciences, Robert Wood Johnson Medical School, Piscataway, NJ, USA
| | - Kevin Monahan
- Department of Molecular Biology & Biochemistry, Rutgers School of Arts and Sciences, Robert Wood Johnson Medical School, Piscataway, NJ, USA
| | - Joan Pulupa
- Mortimer B. Zuckerman Mind, Brain, and Behavior Institute, Columbia University New York, New York, NY, USA
| | - Ira Schieren
- Mortimer B. Zuckerman Mind, Brain, and Behavior Institute, Columbia University New York, New York, NY, USA
| | - Alexa Osterhoudt
- Mortimer B. Zuckerman Mind, Brain, and Behavior Institute, Columbia University New York, New York, NY, USA
- Integrated Program in Cellular, Molecular and Biomedical Studies, Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - Job Dekker
- Department of Biochemistry and Molecular Pharmacology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Mario Nicodemi
- Department of Physics 'Ettore Pancini', University of Naples, and INFN, Napoli, Italy
| | - Stavros Lomvardas
- Mortimer B. Zuckerman Mind, Brain, and Behavior Institute, Columbia University New York, New York, NY, USA.
- Department of Biochemistry and Molecular Biophysics, Vagelos College of Physicians and Surgeons, New York, NY, USA.
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20
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Muto Y, Humphreys BD. Leveraging multimodal chromatin profiling to identify a new potential driver of diabetic kidney disease. Kidney Int 2024; 105:25-27. [PMID: 38182297 DOI: 10.1016/j.kint.2023.10.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2023] [Accepted: 10/23/2023] [Indexed: 01/07/2024]
Abstract
The 3-dimensional nature of chromatin architecture plays crucial roles in regulating gene expression in development, homeostasis, and disease. Until recently, however, comprehensive chromatin profiling in human kidneys has been lacking. In this issue, Eun and Kim et al. employed a multimodal approach by integrating a single-nucleus assay for transposase-accessible chromatin sequencing, chromatin immunoprecipitation sequencing, and Hi-C (a method to comprehensively detect chromatin interactions) to investigate how the epigenetic landscape is altered in diabetic kidney disease.
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Affiliation(s)
- Yoshiharu Muto
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Benjamin D Humphreys
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA; Department of Developmental Biology, Washington University in St. Louis, St. Louis, Missouri, USA.
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21
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Ding Y, Peng YY, Li S, Tang C, Gao J, Wang HY, Long ZY, Lu XM, Wang YT. Single-Cell Sequencing Technology and Its Application in the Study of Central Nervous System Diseases. Cell Biochem Biophys 2023:10.1007/s12013-023-01207-3. [PMID: 38133792 DOI: 10.1007/s12013-023-01207-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 11/30/2023] [Indexed: 12/23/2023]
Abstract
The mammalian central nervous system consists of a large number of cells, which contain not only different types of neurons, but also a large number of glial cells, such as astrocytes, oligodendrocytes, and microglia. These cells are capable of performing highly refined electrophysiological activities and providing the brain with functions such as nutritional support, information transmission and pathogen defense. The diversity of cell types and individual differences between cells have brought inspiration to the study of the mechanism of central nervous system diseases. In order to explore the role of different cells, a new technology, single-cell sequencing technology has emerged to perform specific analysis of high-throughput cell populations, and has been continuously developed. Single-cell sequencing technology can accurately analyze single-cell expression in mixed-cell populations and collect cells from different spatial locations, time stages and types. By using single-cell sequencing technology to compare gene expression profiles of normal and diseased cells, it is possible to discover cell subsets associated with specific diseases and their associated genes. Therefore, scientists can understand the development process, related functions and disease state of the nervous system from an unprecedented depth. In conclusion, single-cell sequencing technology provides a powerful technology for the discovery of novel therapeutic targets for central nervous system diseases.
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Affiliation(s)
- Yang Ding
- College of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China
- State Key Laboratory of Trauma and Chemical Poisoning, Daping Hospital, Army Medical University, Chongqing, 400042, China
| | - Yu-Yuan Peng
- College of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China
| | - Sen Li
- State Key Laboratory of Trauma and Chemical Poisoning, Daping Hospital, Army Medical University, Chongqing, 400042, China
| | - Can Tang
- College of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China
| | - Jie Gao
- College of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China
| | - Hai-Yan Wang
- State Key Laboratory of Trauma and Chemical Poisoning, Daping Hospital, Army Medical University, Chongqing, 400042, China
| | - Zai-Yun Long
- State Key Laboratory of Trauma and Chemical Poisoning, Daping Hospital, Army Medical University, Chongqing, 400042, China
| | - Xiu-Min Lu
- College of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China.
| | - Yong-Tang Wang
- State Key Laboratory of Trauma and Chemical Poisoning, Daping Hospital, Army Medical University, Chongqing, 400042, China.
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22
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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: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [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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23
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Feng C, Wang J, Chu X. Large-scale data-driven and physics-based models offer insights into the relationships among the structures, dynamics, and functions of chromosomes. J Mol Cell Biol 2023; 15:mjad042. [PMID: 37365687 PMCID: PMC10782906 DOI: 10.1093/jmcb/mjad042] [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: 01/06/2023] [Revised: 03/22/2023] [Accepted: 06/25/2023] [Indexed: 06/28/2023] Open
Abstract
The organized three-dimensional chromosome architecture in the cell nucleus provides scaffolding for precise regulation of gene expression. When the cell changes its identity in the cell-fate decision-making process, extensive rearrangements of chromosome structures occur accompanied by large-scale adaptations of gene expression, underscoring the importance of chromosome dynamics in shaping genome function. Over the last two decades, rapid development of experimental methods has provided unprecedented data to characterize the hierarchical structures and dynamic properties of chromosomes. In parallel, these enormous data offer valuable opportunities for developing quantitative computational models. Here, we review a variety of large-scale polymer models developed to investigate the structures and dynamics of chromosomes. Different from the underlying modeling strategies, these approaches can be classified into data-driven ('top-down') and physics-based ('bottom-up') categories. We discuss their contributions to offering valuable insights into the relationships among the structures, dynamics, and functions of chromosomes and propose the perspective of developing data integration approaches from different experimental technologies and multidisciplinary theoretical/simulation methods combined with different modeling strategies.
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Affiliation(s)
- Cibo Feng
- Advanced Materials Thrust, Function Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China
- Green e Materials Laboratory, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China
- College of Physics, Jilin University, Changchun 130012, China
| | - Jin Wang
- Department of Chemistry and Physics, The State University of New York at Stony Brook, Stony Brook, NY 11794, USA
| | - Xiakun Chu
- Advanced Materials Thrust, Function Hub, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China
- Green e Materials Laboratory, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China
- Division of Life Science, The Hong Kong University of Science and Technology, Hong Kong SAR 999077, China
- Guangzhou Municipal Key Laboratory of Materials Informatics, The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511400, China
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24
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Chen Y, Xu H, Liu Z, Xing D. Simultaneous Profiling of Chromosome Conformation and Gene Expression in Single Cells. Bio Protoc 2023; 13:e4886. [PMID: 38023786 PMCID: PMC10665632 DOI: 10.21769/bioprotoc.4886] [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: 07/31/2023] [Revised: 10/09/2023] [Accepted: 10/16/2023] [Indexed: 12/01/2023] Open
Abstract
Rapid development in single-cell chromosome conformation capture technologies has provided valuable insights into the importance of spatial genome architecture for gene regulation. However, a long-standing technical gap remains in the simultaneous characterization of three-dimensional genomes and transcriptomes in the same cell. We have described an assay named Hi-C and RNA-seq employed simultaneously (HiRES), which integrates in situ reverse transcription and chromosome conformation capture (3C) for the parallel analysis of chromatin organization and gene expression. Here, we provide a detailed implementation of the assay, using mouse embryos and cerebral cortices as examples. The versatility of this method extends beyond these two samples, with the potential to be used in various other cell types. Key features • A multi-omics sequencing approach to profile 3D genome structure and gene expression simultaneously in single cells. • Compatible with animal tissues. • One-tube amplification of both DNA and RNA components. • Requires three days to complete.
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Affiliation(s)
- Yujie Chen
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
| | - Heming Xu
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
| | - Zhiyuan Liu
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Dong Xing
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
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25
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Kuang S, Pollard KS. Exploring the Roles of RNAs in Chromatin Architecture Using Deep Learning. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.22.563498. [PMID: 37961712 PMCID: PMC10634726 DOI: 10.1101/2023.10.22.563498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Recent studies have highlighted the impact of both transcription and transcripts on 3D genome organization, particularly its dynamics. Here, we propose a deep learning framework, called AkitaR, that leverages both genome sequences and genome-wide RNA-DNA interactions to investigate the roles of chromatin-associated RNAs (caRNAs) on genome folding in HFFc6 cells. In order to disentangle the cis- and trans-regulatory roles of caRNAs, we compared models with nascent transcripts, trans-located caRNAs, open chromatin data, or DNA sequence alone. Both nascent transcripts and trans-located caRNAs improved the models' predictions, especially at cell-type-specific genomic regions. Analyses of feature importance scores revealed the contribution of caRNAs at TAD boundaries, chromatin loops and nuclear sub-structures such as nuclear speckles and nucleoli to the models' predictions. Furthermore, we identified non-coding RNAs (ncRNAs) known to regulate chromatin structures, such as MALAT1 and NEAT1, as well as several novel RNAs, RNY5, RPPH1, POLG-DT and THBS1-IT, that might modulate chromatin architecture through trans-interactions in HFFc6. Our modeling also suggests that transcripts from Alus and other repetitive elements may facilitate chromatin interactions through trans R-loop formation. Our findings provide new insights and generate testable hypotheses about the roles of caRNAs in shaping chromatin organization.
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Affiliation(s)
- Shuzhen Kuang
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA
| | - Katherine S. Pollard
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
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26
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Tian W, Zhou J, Bartlett A, Zeng Q, Liu H, Castanon RG, Kenworthy M, Altshul J, Valadon C, Aldridge A, Nery JR, Chen H, Xu J, Johnson ND, Lucero J, Osteen JK, Emerson N, Rink J, Lee J, Li Y, Siletti K, Liem M, Claffey N, O’Connor C, Yanny AM, Nyhus J, Dee N, Casper T, Shapovalova N, Hirschstein D, Ding SL, Hodge R, Levi BP, Keene CD, Linnarsson S, Lein E, Ren B, Behrens MM, Ecker JR. Single-cell DNA methylation and 3D genome architecture in the human brain. Science 2023; 382:eadf5357. [PMID: 37824674 PMCID: PMC10572106 DOI: 10.1126/science.adf5357] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 09/05/2023] [Indexed: 10/14/2023]
Abstract
Delineating the gene-regulatory programs underlying complex cell types is fundamental for understanding brain function in health and disease. Here, we comprehensively examined human brain cell epigenomes by probing DNA methylation and chromatin conformation at single-cell resolution in 517 thousand cells (399 thousand neurons and 118 thousand non-neurons) from 46 regions of three adult male brains. We identified 188 cell types and characterized their molecular signatures. Integrative analyses revealed concordant changes in DNA methylation, chromatin accessibility, chromatin organization, and gene expression across cell types, cortical areas, and basal ganglia structures. We further developed single-cell methylation barcodes that reliably predict brain cell types using the methylation status of select genomic sites. This multimodal epigenomic brain cell atlas provides new insights into the complexity of cell-type-specific gene regulation in adult human brains.
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Affiliation(s)
- Wei Tian
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jingtian Zhou
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Bioinformatics and Systems Biology Program, University of California, San Diego, La Jolla, CA 92037, USA
| | - Anna Bartlett
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Qiurui Zeng
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA 92037, USA
| | - Hanqing Liu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Rosa G. Castanon
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Mia Kenworthy
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jordan Altshul
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Cynthia Valadon
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Andrew Aldridge
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Joseph R. Nery
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Huaming Chen
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jiaying Xu
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Nicholas D. Johnson
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jacinta Lucero
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Julia K. Osteen
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Nora Emerson
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jon Rink
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Jasper Lee
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Yang Li
- Ludwig Institute for Cancer Research, La Jolla, CA 92037, USA
| | - Kimberly Siletti
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet; 171 77 Stockholm, Sweden
| | - Michelle Liem
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Naomi Claffey
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Caz O’Connor
- Flow Cytometry Core Facility, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | | | - Julie Nyhus
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Nick Dee
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Tamara Casper
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | | | | | - Song-Lin Ding
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Rebecca Hodge
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Boaz P. Levi
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - C. Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
| | - Sten Linnarsson
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet; 171 77 Stockholm, Sweden
| | - Ed Lein
- Allen Institute for Brain Science; Seattle, WA 98109, USA
| | - Bing Ren
- Ludwig Institute for Cancer Research, La Jolla, CA 92037, USA
- Center for Epigenomics, University of California, San Diego School of Medicine, La Jolla, CA 92037, USA
- Department of Cellular and Molecular Medicine, University of California, San Diego School of Medicine, La Jolla, CA 92037, USA
- Institute of Genomic Medicine, University of California, San Diego School of Medicine, La Jolla, CA 92037, USA
- Moores Cancer Center, University of California, San Diego School of Medicine, La Jolla, CA 92037, USA
| | - M. Margarita Behrens
- Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Joseph R. Ecker
- Genomic Analysis Laboratory, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
- Howard Hughes Medical Institute, The Salk Institute for Biological Studies, La Jolla, CA 92037, USA
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27
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Shi Q, Chen X, Zhang Z. Decoding Human Biology and Disease Using Single-cell Omics Technologies. GENOMICS, PROTEOMICS & BIOINFORMATICS 2023; 21:926-949. [PMID: 37739168 PMCID: PMC10928380 DOI: 10.1016/j.gpb.2023.06.003] [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: 01/19/2023] [Revised: 05/22/2023] [Accepted: 06/08/2023] [Indexed: 09/24/2023]
Abstract
Over the past decade, advances in single-cell omics (SCO) technologies have enabled the investigation of cellular heterogeneity at an unprecedented resolution and scale, opening a new avenue for understanding human biology and disease. In this review, we summarize the developments of sequencing-based SCO technologies and computational methods, and focus on considerable insights acquired from SCO sequencing studies to understand normal and diseased properties, with a particular emphasis on cancer research. We also discuss the technological improvements of SCO and its possible contribution to fundamental research of the human, as well as its great potential in clinical diagnoses and personalized therapies of human disease.
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Affiliation(s)
- Qiang Shi
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
| | - Xueyan Chen
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China
| | - Zemin Zhang
- Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing 100871, China; Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China; Changping Laboratory, Beijing 102206, China.
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28
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Sherman S, Arnold-Ammer I, Schneider MW, Kawakami K, Baier H. Retina-derived signals control pace of neurogenesis in visual brain areas but not circuit assembly. Nat Commun 2023; 14:6020. [PMID: 37758715 PMCID: PMC10533834 DOI: 10.1038/s41467-023-40749-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Accepted: 08/09/2023] [Indexed: 09/29/2023] Open
Abstract
Brain development is orchestrated by both innate and experience-dependent mechanisms, but their relative contributions are difficult to disentangle. Here we asked if and how central visual areas are altered in a vertebrate brain depleted of any and all signals from retinal ganglion cells throughout development. We transcriptionally profiled neurons in pretectum, thalamus and other retinorecipient areas of larval zebrafish and searched for changes in lakritz mutants that lack all retinal connections. Although individual genes are dysregulated, the complete set of 77 neuronal types develops in apparently normal proportions, at normal locations, and along normal differentiation trajectories. Strikingly, the cell-cycle exits of proliferating progenitors in these areas are delayed, and a greater fraction of early postmitotic precursors remain uncommitted or are diverted to a pre-glial fate. Optogenetic stimulation targeting groups of neurons normally involved in processing visual information evokes behaviors indistinguishable from wildtype. In conclusion, we show that signals emitted by retinal axons influence the pace of neurogenesis in visual brain areas, but do not detectably affect the specification or wiring of downstream neurons.
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Affiliation(s)
- Shachar Sherman
- Max Planck Institute for Biological Intelligence, Department Genes - Circuits - Behavior, Am Klopferspitz 18, 82152, Martinsried, Germany
| | - Irene Arnold-Ammer
- Max Planck Institute for Biological Intelligence, Department Genes - Circuits - Behavior, Am Klopferspitz 18, 82152, Martinsried, Germany
| | - Martin W Schneider
- Max Planck Institute for Biological Intelligence, Department Genes - Circuits - Behavior, Am Klopferspitz 18, 82152, Martinsried, Germany
| | - Koichi Kawakami
- Laboratory of Molecular and Developmental Biology, National Institute of Genetics, and Department of Genetics, SOKENDAI (The Graduate University for Advanced Studies), Mishima, Shizuoka, 411-8540, Japan
| | - Herwig Baier
- Max Planck Institute for Biological Intelligence, Department Genes - Circuits - Behavior, Am Klopferspitz 18, 82152, Martinsried, Germany.
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29
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Lee L, Yu M, Li X, Zhu C, Zhang Y, Yu H, Chen Z, Mishra S, Ren B, Li Y, Hu M. SnapHiC-D: a computational pipeline to identify differential chromatin contacts from single-cell Hi-C data. Brief Bioinform 2023; 24:bbad315. [PMID: 37649383 PMCID: PMC10516352 DOI: 10.1093/bib/bbad315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 08/04/2023] [Accepted: 08/07/2023] [Indexed: 09/01/2023] Open
Abstract
Single-cell high-throughput chromatin conformation capture technologies (scHi-C) has been used to map chromatin spatial organization in complex tissues. However, computational tools to detect differential chromatin contacts (DCCs) from scHi-C datasets in development and through disease pathogenesis are still lacking. Here, we present SnapHiC-D, a computational pipeline to identify DCCs between two scHi-C datasets. Compared to methods designed for bulk Hi-C data, SnapHiC-D detects DCCs with high sensitivity and accuracy. We used SnapHiC-D to identify cell-type-specific chromatin contacts at 10 Kb resolution in mouse hippocampal and human prefrontal cortical tissues, demonstrating that DCCs detected in the hippocampal and cortical cell types are generally associated with cell-type-specific gene expression patterns and epigenomic features. SnapHiC-D is freely available at https://github.com/HuMingLab/SnapHiC-D.
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Affiliation(s)
- Lindsay Lee
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Miao Yu
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Xiaoqi Li
- Carolina Health Informatics Program, University of North Carolina, Chapel Hill, NC, USA
| | - Chenxu Zhu
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
- New York Genome Center, New York, NY, USA
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA
| | - Yanxiao Zhang
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
- Westlake University, Hangzhou, Zhejiang, China
| | - Hongyu Yu
- Department of Statistics, University of Wisconsin Madison, Madison, WI, USA
- Department of Biochemistry, University of Wisconsin Madison, Madison, WI, USA
| | - Ziyin Chen
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Fudan University, Shanghai, China
| | - Shreya Mishra
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
| | - Bing Ren
- Ludwig Institute for Cancer Research, La Jolla, CA, USA
- Center for Epigenomics & Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
- Department of Computer Science, University of North Carolina, Chapel Hill, NC, USA
| | - Ming Hu
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA
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30
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Tan L, Shi J, Moghadami S, Parasar B, Wright CP, Seo Y, Vallejo K, Cobos I, Duncan L, Chen R, Deisseroth K. Lifelong restructuring of 3D genome architecture in cerebellar granule cells. Science 2023; 381:1112-1119. [PMID: 37676945 PMCID: PMC11059189 DOI: 10.1126/science.adh3253] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 08/03/2023] [Indexed: 09/09/2023]
Abstract
The cerebellum contains most of the neurons in the human brain and exhibits distinctive modes of development and aging. In this work, by developing our single-cell three-dimensional (3D) genome assay-diploid chromosome conformation capture, or Dip-C-into population-scale (Pop-C) and virus-enriched (vDip-C) modes, we resolved the first 3D genome structures of single cerebellar cells, created life-spanning 3D genome atlases for both humans and mice, and jointly measured transcriptome and chromatin accessibility during development. We found that although the transcriptome and chromatin accessibility of cerebellar granule neurons mature in early postnatal life, 3D genome architecture gradually remodels throughout life, establishing ultra-long-range intrachromosomal contacts and specific interchromosomal contacts that are rarely seen in neurons. These results reveal unexpected evolutionarily conserved molecular processes that underlie distinctive features of neural development and aging across the mammalian life span.
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Affiliation(s)
- Longzhi Tan
- Department of Neurobiology, Stanford University, Stanford, CA, 94305
- Department of Bioengineering, Stanford University, Stanford, CA, 94305
| | - Jenny Shi
- Department of Neurobiology, Stanford University, Stanford, CA, 94305
- Department of Bioengineering, Stanford University, Stanford, CA, 94305
- Department of Chemistry, Stanford University, Stanford, CA, 94305
| | - Siavash Moghadami
- Department of Neurobiology, Stanford University, Stanford, CA, 94305
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA, 94305
| | - Bibudha Parasar
- Department of Neurobiology, Stanford University, Stanford, CA, 94305
| | - Cydney P. Wright
- Department of Neurobiology, Stanford University, Stanford, CA, 94305
- Department of Biology, Stanford University, Stanford, CA, 94305
| | - Yunji Seo
- Department of Neurobiology, Stanford University, Stanford, CA, 94305
| | - Kristen Vallejo
- Department of Pathology, Stanford University, Stanford, CA, 94305
| | - Inma Cobos
- Department of Pathology, Stanford University, Stanford, CA, 94305
| | - Laramie Duncan
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, 94305
| | - Ritchie Chen
- Department of Bioengineering, Stanford University, Stanford, CA, 94305
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA, 94305
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, 94305
- Howard Hughes Medical Institute, Stanford, CA, 94305
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31
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Qu J, Sun J, Zhao C, Liu X, Zhang X, Jiang S, Wei C, Yu H, Zeng X, Fan L, Ding J. Simultaneous profiling of chromatin architecture and transcription in single cells. Nat Struct Mol Biol 2023; 30:1393-1402. [PMID: 37580628 DOI: 10.1038/s41594-023-01066-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 07/12/2023] [Indexed: 08/16/2023]
Abstract
The three-dimensional structure of chromatin plays a crucial role in development and disease, both of which are associated with transcriptional changes. However, given the heterogeneity in single-cell chromatin architecture and transcription, the regulatory relationship between the three-dimensional chromatin structure and gene expression is difficult to explain based on bulk cell populations. Here we develop a single-cell, multimodal, omics method allowing the simultaneous detection of chromatin architecture and messenger RNA expression by sequencing (single-cell transcriptome sequencing (scCARE-seq)). Applying scCARE-seq to examine chromatin architecture and transcription from 2i to serum single mouse embryonic stem cells, we observe improved separation of cell clusters compared with single-cell chromatin conformation capture. In addition, after defining the cell-cycle phase of each cell through chromatin architecture extracted by scCARE-seq, we find that periodic changes in chromatin architecture occur in parallel with transcription during the cell cycle. These findings highlight the potential of scCARE-seq to facilitate comprehensive analyses that may boost our understanding of chromatin architecture and transcription in the same single cell.
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Affiliation(s)
- Jiale Qu
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Jun Sun
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Cai Zhao
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Xinyi Liu
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Xinyao Zhang
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Shaoshuai Jiang
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Chao Wei
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Haopeng Yu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaoxi Zeng
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
| | - Lili Fan
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China.
| | - Junjun Ding
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
- Department of Histology and Embryology, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China.
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32
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Brovkina MV, Chapman MA, Holding ML, Clowney EJ. Emergence and influence of sequence bias in evolutionarily malleable, mammalian tandem arrays. BMC Biol 2023; 21:179. [PMID: 37612705 PMCID: PMC10463633 DOI: 10.1186/s12915-023-01673-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 08/01/2023] [Indexed: 08/25/2023] Open
Abstract
BACKGROUND The radiation of mammals at the extinction of the dinosaurs produced a plethora of new forms-as diverse as bats, dolphins, and elephants-in only 10-20 million years. Behind the scenes, adaptation to new niches is accompanied by extensive innovation in large families of genes that allow animals to contact the environment, including chemosensors, xenobiotic enzymes, and immune and barrier proteins. Genes in these "outward-looking" families are allelically diverse among humans and exhibit tissue-specific and sometimes stochastic expression. RESULTS Here, we show that these tandem arrays of outward-looking genes occupy AT-biased isochores and comprise the "tissue-specific" gene class that lack CpG islands in their promoters. Models of mammalian genome evolution have not incorporated the sharply different functions and transcriptional patterns of genes in AT- versus GC-biased regions. To examine the relationship between gene family expansion, sequence content, and allelic diversity, we use population genetic data and comparative analysis. First, we find that AT bias can emerge during evolutionary expansion of gene families in cis. Second, human genes in AT-biased isochores or with GC-poor promoters experience relatively low rates of de novo point mutation today but are enriched for non-synonymous variants. Finally, we find that isochores containing gene clusters exhibit low rates of recombination. CONCLUSIONS Our analyses suggest that tolerance of non-synonymous variation and low recombination are two forces that have produced the depletion of GC bases in outward-facing gene arrays. In turn, high AT content exerts a profound effect on their chromatin organization and transcriptional regulation.
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Affiliation(s)
- Margarita V Brovkina
- Graduate Program in Cellular and Molecular Biology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Margaret A Chapman
- Neurosciences Graduate Program, University of Michigan Medical School, Ann Arbor, MI, USA
| | | | - E Josephine Clowney
- Department of Molecular, Cellular, and Developmental Biology, University of Michigan, Ann Arbor, MI, USA.
- Michigan Neuroscience Institute, University of Michigan, Ann Arbor, MI, USA.
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33
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Zhao Z, Parra OP, Musella F, Scrutton-Alvarado N, Fujita SI, Alber F, Yang Y, Yamada T. Mega-Enhancer Bodies Organize Neuronal Long Genes in the Cerebellum. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.19.549737. [PMID: 37503219 PMCID: PMC10370079 DOI: 10.1101/2023.07.19.549737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Dynamic regulation of gene expression plays a key role in establishing the diverse neuronal cell types in the brain. Recent findings in genome biology suggest that three-dimensional (3D) genome organization has important, but mechanistically poorly understood functions in gene transcription. Beyond local genomic interactions between promoters and enhancers, we find that cerebellar granule neurons undergoing differentiation in vivo exhibit striking increases in long-distance genomic interactions between transcriptionally active genomic loci, which are separated by tens of megabases within a chromosome or located on different chromosomes. Among these interactions, we identify a nuclear subcompartment enriched for near-megabase long enhancers and their associated neuronal long genes encoding synaptic or signaling proteins. Neuronal long genes are differentially recruited to this enhancer-dense subcompartment to help shape the transcriptional identities of granule neuron subtypes in the cerebellum. SPRITE analyses of higher-order genomic interactions, together with IGM-based 3D genome modeling and imaging approaches, reveal that the enhancer-dense subcompartment forms prominent nuclear structures, which we term mega-enhancer bodies. These novel nuclear bodies reside in the nuclear periphery, away from other transcriptionally active structures, including nuclear speckles located in the nuclear interior. Together, our findings define additional layers of higher-order 3D genome organization closely linked to neuronal maturation and identity in the brain.
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34
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Zhou T, Zhang R, Jia D, Doty RT, Munday AD, Gao D, Xin L, Abkowitz JL, Duan Z, Ma J. Concurrent profiling of multiscale 3D genome organization and gene expression in single mammalian cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.20.549578. [PMID: 37546900 PMCID: PMC10401946 DOI: 10.1101/2023.07.20.549578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
The organization of mammalian genomes within the nucleus features a complex, multiscale three-dimensional (3D) architecture. The functional significance of these 3D genome features, however, remains largely elusive due to limited single-cell technologies that can concurrently profile genome organization and transcriptional activities. Here, we report GAGE-seq, a highly scalable, robust single-cell co-assay that simultaneously measures 3D genome structure and transcriptome within the same cell. Employing GAGE-seq on mouse brain cortex and human bone marrow CD34+ cells, we comprehensively characterized the intricate relationships between 3D genome and gene expression. We found that these multiscale 3D genome features collectively inform cell type-specific gene expressions, hence contributing to defining cell identity at the single-cell level. Integration of GAGE-seq data with spatial transcriptomic data revealed in situ variations of the 3D genome in mouse cortex. Moreover, our observations of lineage commitment in normal human hematopoiesis unveiled notable discordant changes between 3D genome organization and gene expression, underscoring a complex, temporal interplay at the single-cell level that is more nuanced than previously appreciated. Together, GAGE-seq provides a powerful, cost-effective approach for interrogating genome structure and gene expression relationships at the single-cell level across diverse biological contexts.
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Affiliation(s)
- Tianming Zhou
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Ruochi Zhang
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
- Present address: Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Deyong Jia
- Department of Urology, University of Washington, Seattle, WA 98195, USA
| | - Raymond T. Doty
- Division of Hematology, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Adam D. Munday
- Division of Hematology, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Daniel Gao
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA 98109, USA
- Present address: Department of Chemistry, Pomona College, Claremont, CA 91711, USA
| | - Li Xin
- Department of Urology, University of Washington, Seattle, WA 98195, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA 98109, USA
| | - Janis L. Abkowitz
- Division of Hematology, Department of Medicine, University of Washington, Seattle, WA 98195, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA 98109, USA
| | - Zhijun Duan
- Division of Hematology, Department of Medicine, University of Washington, Seattle, WA 98195, USA
- Institute for Stem Cell and Regenerative Medicine, University of Washington, Seattle, WA 98109, USA
| | - Jian Ma
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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35
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Liu M, Jin S, Agabiti SS, Jensen TB, Yang T, Radda JSD, Ruiz CF, Baldissera G, Muzumdar MD, Wang S. A genome-wide single-cell 3D genome atlas of lung cancer progression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.23.550157. [PMID: 37546882 PMCID: PMC10401964 DOI: 10.1101/2023.07.23.550157] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Alterations in three-dimensional (3D) genome structures are associated with cancer1-5. However, how genome folding evolves and diversifies during subclonal cancer progression in the native tissue environment remains unknown. Here, we leveraged a genome-wide chromatin tracing technology to directly visualize 3D genome folding in situ in a faithful Kras-driven mouse model of lung adenocarcinoma (LUAD)6, generating the first single-cell 3D genome atlas of any cancer. We discovered stereotypical 3D genome alterations during cancer development, including a striking structural bottleneck in preinvasive adenomas prior to progression to LUAD, indicating a stringent selection on the 3D genome early in cancer progression. We further showed that the 3D genome precisely encodes cancer states in single cells, despite considerable cell-to-cell heterogeneity. Finally, evolutionary changes in 3D genome compartmentalization - partially regulated by polycomb group protein Rnf2 through its ubiquitin ligase-independent activity - reveal novel genetic drivers and suppressors of LUAD progression. Our results demonstrate the importance of mapping the single-cell cancer 3D genome and the potential to identify new diagnostic and therapeutic biomarkers from 3D genomic architectures.
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Affiliation(s)
- Miao Liu
- Department of Genetics, Yale School of Medicine, Yale University; New Haven, CT 06510, USA
| | - Shengyan Jin
- Department of Genetics, Yale School of Medicine, Yale University; New Haven, CT 06510, USA
| | - Sherry S. Agabiti
- Department of Genetics, Yale School of Medicine, Yale University; New Haven, CT 06510, USA
- Yale Cancer Biology Institute, Yale University; West Haven, CT 06516, USA
| | - Tyler B. Jensen
- Department of Genetics, Yale School of Medicine, Yale University; New Haven, CT 06510, USA
- M.D.-Ph.D. Program, Yale University; New Haven, CT 06510, USA
| | - Tianqi Yang
- Department of Genetics, Yale School of Medicine, Yale University; New Haven, CT 06510, USA
| | - Jonathan S. D. Radda
- Department of Genetics, Yale School of Medicine, Yale University; New Haven, CT 06510, USA
| | - Christian F. Ruiz
- Department of Genetics, Yale School of Medicine, Yale University; New Haven, CT 06510, USA
- Yale Cancer Biology Institute, Yale University; West Haven, CT 06516, USA
| | - Gabriel Baldissera
- Department of Genetics, Yale School of Medicine, Yale University; New Haven, CT 06510, USA
| | - Mandar Deepak Muzumdar
- Department of Genetics, Yale School of Medicine, Yale University; New Haven, CT 06510, USA
- Yale Cancer Biology Institute, Yale University; West Haven, CT 06516, USA
- M.D.-Ph.D. Program, Yale University; New Haven, CT 06510, USA
- Department of Internal Medicine, Section of Medical Oncology, Yale School of Medicine, Yale University; New Haven, CT 06510, USA
- Yale Cancer Center, Smilow Cancer Hospital, New Haven, CT 06510, USA
- Yale Combined Program in the Biological and Biomedical Sciences, Yale University; New Haven, CT 06510, USA
- Molecular Cell Biology, Genetics and Development Program, Yale University; New Haven, CT 06510, USA
| | - Siyuan Wang
- Department of Genetics, Yale School of Medicine, Yale University; New Haven, CT 06510, USA
- M.D.-Ph.D. Program, Yale University; New Haven, CT 06510, USA
- Yale Combined Program in the Biological and Biomedical Sciences, Yale University; New Haven, CT 06510, USA
- Molecular Cell Biology, Genetics and Development Program, Yale University; New Haven, CT 06510, USA
- Department of Cell Biology, Yale School of Medicine, Yale University; New Haven, CT 06510, USA
- Biochemistry, Quantitative Biology, Biophysics, and Structural Biology Program, Yale University; New Haven, CT 06510, USA
- Yale Center for RNA Science and Medicine, Yale University School of Medicine; New Haven, CT 06510, USA
- Yale Liver Center, Yale University School of Medicine; New Haven, CT 06510, USA
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36
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Jia BB, Jussila A, Kern C, Zhu Q, Ren B. A spatial genome aligner for resolving chromatin architectures from multiplexed DNA FISH. Nat Biotechnol 2023; 41:1004-1017. [PMID: 36593410 PMCID: PMC10344783 DOI: 10.1038/s41587-022-01568-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 10/13/2022] [Indexed: 01/03/2023]
Abstract
Multiplexed fluorescence in situ hybridization (FISH) is a widely used approach for analyzing three-dimensional genome organization, but it is challenging to derive chromosomal conformations from noisy fluorescence signals, and tracing chromatin is not straightforward. Here we report a spatial genome aligner that parses true chromatin signal from noise by aligning signals to a DNA polymer model. Using genomic distances separating imaged loci, our aligner estimates spatial distances expected to separate loci on a polymer in three-dimensional space. Our aligner then evaluates the physical probability observed signals belonging to these loci are connected, thereby tracing chromatin structures. We demonstrate that this spatial genome aligner can efficiently model chromosome architectures from DNA FISH data across multiple scales and be used to predict chromosome ploidies de novo in interphase cells. Reprocessing of previous whole-genome chromosome tracing data with this method indicates the spatial aggregation of sister chromatids in S/G2 phase cells in asynchronous mouse embryonic stem cells and provides evidence for extranumerary chromosomes that remain tightly paired in postmitotic neurons of the adult mouse cortex.
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Affiliation(s)
- Bojing Blair Jia
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA, USA
- Medical Scientist Training Program, University of California San Diego, La Jolla, CA, USA
| | - Adam Jussila
- Bioinformatics and Systems Biology Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Colin Kern
- Department of Cellular and Molecular Medicine, Center for Epigenomics, University of California San Diego, La Jolla, CA, USA
| | - Quan Zhu
- Department of Cellular and Molecular Medicine, Center for Epigenomics, University of California San Diego, La Jolla, CA, 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.
- Institute of Genomic Medicine, Moores Cancer Center, School of Medicine, University of California San Diego, La Jolla, CA, USA.
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37
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Liu Z, Chen Y, Xia Q, Liu M, Xu H, Chi Y, Deng Y, Xing D. Linking genome structures to functions by simultaneous single-cell Hi-C and RNA-seq. Science 2023; 380:1070-1076. [PMID: 37289875 DOI: 10.1126/science.adg3797] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 05/07/2023] [Indexed: 06/10/2023]
Abstract
Much progress has been made recently in single-cell chromosome conformation capture technologies. However, a method that allows simultaneous profiling of chromatin architecture and gene expression has not been reported. Here, we developed an assay named "Hi-C and RNA-seq employed simultaneously" (HiRES) and performed it on thousands of single cells from developing mouse embryos. Single-cell three-dimensional genome structures, despite being heavily determined by the cell cycle and developmental stages, gradually diverged in a cell type-specific manner as development progressed. By comparing the pseudotemporal dynamics of chromatin interactions with gene expression, we found a widespread chromatin rewiring that occurred before transcription activation. Our results demonstrate that the establishment of specific chromatin interactions is tightly related to transcriptional control and cell functions during lineage specification.
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Affiliation(s)
- Zhiyuan Liu
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Yujie Chen
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Qimin Xia
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Menghan Liu
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Heming Xu
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Yi Chi
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Yujing Deng
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
| | - Dong Xing
- Biomedical Pioneering Innovation Center (BIOPIC), School of Life Sciences, Peking University, Beijing, China
- Beijing Advanced Innovation Center for Genomics (ICG), Peking University, Beijing, China
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38
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Fan S, Dang D, Ye Y, Zhang SW, Gao L, Zhang S. scHi-CSim: a flexible simulator that generates high-fidelity single-cell Hi-C data for benchmarking. J Mol Cell Biol 2023; 15:mjad003. [PMID: 36708167 PMCID: PMC10308180 DOI: 10.1093/jmcb/mjad003] [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: 04/01/2022] [Revised: 09/18/2022] [Accepted: 01/25/2023] [Indexed: 01/29/2023] Open
Abstract
Single-cell Hi-C technology provides an unprecedented opportunity to reveal chromatin structure in individual cells. However, high sequencing cost impedes the generation of biological Hi-C data with high sequencing depths and multiple replicates for downstream analysis. Here, we developed a single-cell Hi-C simulator (scHi-CSim) that generates high-fidelity data for benchmarking. scHi-CSim merges neighboring cells to overcome the sparseness of data, samples interactions in distance-stratified chromosomes to maintain the heterogeneity of single cells, and estimates the empirical distribution of restriction fragments to generate simulated data. We demonstrated that scHi-CSim can generate high-fidelity data by comparing the performance of single-cell clustering and detection of chromosomal high-order structures with raw data. Furthermore, scHi-CSim is flexible to change sequencing depth and the number of simulated replicates. We showed that increasing sequencing depth could improve the accuracy of detecting topologically associating domains. We also used scHi-CSim to generate a series of simulated datasets with different sequencing depths to benchmark scHi-C clustering methods.
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Affiliation(s)
- Shichen Fan
- School of Computer Science and Technology, Xidian University, Xi'an 710071, China
| | - Dachang Dang
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Yusen Ye
- School of Computer Science and Technology, Xidian University, Xi'an 710071, China
| | - Shao-Wu Zhang
- School of Automation, Northwestern Polytechnical University, Xi'an 710072, China
| | - Lin Gao
- School of Computer Science and Technology, Xidian University, Xi'an 710071, China
| | - Shihua Zhang
- NCMIS, CEMS, RCSDS, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China
- School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
- Key Laboratory of Systems Health Science of Zhejiang Province, School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024, China
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Chen M, Jiang J, Hou J. Single-cell technologies in multiple myeloma: new insights into disease pathogenesis and translational implications. Biomark Res 2023; 11:55. [PMID: 37259170 DOI: 10.1186/s40364-023-00502-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 05/12/2023] [Indexed: 06/02/2023] Open
Abstract
Multiple myeloma (MM) is a hematological malignancy characterized by clonal proliferation of plasma cells. Although therapeutic advances have been made to improve clinical outcomes and to prolong patients' survival in the past two decades, MM remains largely incurable. Single-cell sequencing (SCS) is a powerful method to dissect the cellular and molecular landscape at single-cell resolution, instead of providing averaged results. The application of single-cell technologies promises to address outstanding questions in myeloma biology and has revolutionized our understanding of the inter- and intra-tumor heterogeneity, tumor microenvironment, and mechanisms of therapeutic resistance in MM. In this review, we summarize the recently developed SCS methodologies and latest MM research progress achieved by single-cell profiling, including information regarding the cancer and immune cell landscapes, tumor heterogeneities, underlying mechanisms and biomarkers associated with therapeutic response and resistance. We also discuss future directions of applying transformative SCS approaches with contribution to clinical translation.
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Affiliation(s)
- Mengping Chen
- Department of Hematology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China
| | - Jinxing Jiang
- Department of Hematology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China
| | - Jian Hou
- Department of Hematology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200127, China.
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40
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Xiong K, Zhang R, Ma J. scGHOST: Identifying single-cell 3D genome subcompartments. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.24.542032. [PMID: 37292994 PMCID: PMC10245874 DOI: 10.1101/2023.05.24.542032] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
New single-cell Hi-C (scHi-C) technologies enable probing of the genome-wide cell-to-cell variability in 3D genome organization from individual cells. Several computational methods have been developed to reveal single-cell 3D genome features based on scHi-C data, including A/B compartments, topologically-associating domains, and chromatin loops. However, no scHi-C analysis method currently exists for annotating single-cell subcompartments, which are crucial for providing a more refined view of large-scale chromosome spatial localization in single cells. Here, we present scGhost, a single-cell subcompartment annotation method based on graph embedding with constrained random walk sampling. Applications of scGhost to scHi-C data and single-cell 3D genome imaging data demonstrate the reliable identification of single-cell subcompartments and offer new insights into cell-to-cell variability of nuclear subcompartments. Using scHi-C data from the human prefrontal cortex, scGhost identifies cell type-specific subcompartments that are strongly connected to cell type-specific gene expression, suggesting the functional implications of single-cell subcompartments. Overall, scGhost is an effective new method for single-cell 3D genome subcompartment annotation based on scHi-C data for a broad range of biological contexts.
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Affiliation(s)
- Kyle Xiong
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Ruochi Zhang
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Jian Ma
- Computational Biology Department, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA
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41
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Takei Y, Yang Y, White J, Yun J, Prasad M, Ombelets LJ, Schindler S, Cai L. High-resolution spatial multi-omics reveals cell-type specific nuclear compartments. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.07.539762. [PMID: 37214923 PMCID: PMC10197539 DOI: 10.1101/2023.05.07.539762] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
The mammalian nucleus is compartmentalized by diverse subnuclear structures. These subnuclear structures, marked by nuclear bodies and histone modifications, are often cell-type specific and affect gene regulation and 3D genome organization1-3. Understanding nuclear organization requires identifying the molecular constituents of subnuclear structures and mapping their associations with specific genomic loci in individual cells, within complex tissues. Here, we introduce two-layer DNA seqFISH+, which allows simultaneous mapping of 100,049 genomic loci, together with nascent transcriptome for 17,856 genes and a diverse set of immunofluorescently labeled subnuclear structures all in single cells in cell lines and adult mouse cerebellum. Using these multi-omics datasets, we showed that repressive chromatin compartments are more variable by cell type than active compartments. We also discovered a single exception to this rule: an RNA polymerase II (RNAPII)-enriched compartment was associated with long, cell-type specific genes (> 200kb), in a manner distinct from nuclear speckles. Further, our analysis revealed that cell-type specific facultative and constitutive heterochromatin compartments marked by H3K27me3 and H4K20me3 are enriched at specific genes and gene clusters, respectively, and shape radial chromosomal positioning and inter-chromosomal interactions in neurons and glial cells. Together, our results provide a single-cell high-resolution multi-omics view of subnuclear compartments, associated genomic loci, and their impacts on gene regulation, directly within complex tissues.
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Affiliation(s)
- Yodai Takei
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Yujing Yang
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Jonathan White
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Jina Yun
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Meera Prasad
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | | | | | - Long Cai
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
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42
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Kaplow IM, Lawler AJ, Schäffer DE, Srinivasan C, Sestili HH, Wirthlin ME, Phan BN, Prasad K, Brown AR, Zhang X, Foley K, Genereux DP, Karlsson EK, Lindblad-Toh K, Meyer WK, Pfenning AR, Andrews G, Armstrong JC, Bianchi M, Birren BW, Bredemeyer KR, Breit AM, Christmas MJ, Clawson H, Damas J, Di Palma F, Diekhans M, Dong MX, Eizirik E, Fan K, Fanter C, Foley NM, Forsberg-Nilsson K, Garcia CJ, Gatesy J, Gazal S, Genereux DP, Goodman L, Grimshaw J, Halsey MK, Harris AJ, Hickey G, Hiller M, Hindle AG, Hubley RM, Hughes GM, Johnson J, Juan D, Kaplow IM, Karlsson EK, Keough KC, Kirilenko B, Koepfli KP, Korstian JM, Kowalczyk A, Kozyrev SV, Lawler AJ, Lawless C, Lehmann T, Levesque DL, Lewin HA, Li X, Lind A, Lindblad-Toh K, Mackay-Smith A, Marinescu VD, Marques-Bonet T, Mason VC, Meadows JRS, Meyer WK, Moore JE, Moreira LR, Moreno-Santillan DD, Morrill KM, Muntané G, Murphy WJ, Navarro A, Nweeia M, Ortmann S, Osmanski A, Paten B, Paulat NS, Pfenning AR, Phan BN, Pollard KS, Pratt HE, Ray DA, Reilly SK, Rosen JR, Ruf I, Ryan L, Ryder OA, Sabeti PC, Schäffer DE, Serres A, Shapiro B, Smit AFA, Springer M, Srinivasan C, Steiner C, Storer JM, Sullivan KAM, Sullivan PF, Sundström E, Supple MA, Swofford R, Talbot JE, Teeling E, Turner-Maier J, Valenzuela A, Wagner F, Wallerman O, Wang C, Wang J, Weng Z, Wilder AP, Wirthlin ME, Xue JR, Zhang X. Relating enhancer genetic variation across mammals to complex phenotypes using machine learning. Science 2023; 380:eabm7993. [PMID: 37104615 DOI: 10.1126/science.abm7993] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
Protein-coding differences between species often fail to explain phenotypic diversity, suggesting the involvement of genomic elements that regulate gene expression such as enhancers. Identifying associations between enhancers and phenotypes is challenging because enhancer activity can be tissue-dependent and functionally conserved despite low sequence conservation. We developed the Tissue-Aware Conservation Inference Toolkit (TACIT) to associate candidate enhancers with species' phenotypes using predictions from machine learning models trained on specific tissues. Applying TACIT to associate motor cortex and parvalbumin-positive interneuron enhancers with neurological phenotypes revealed dozens of enhancer-phenotype associations, including brain size-associated enhancers that interact with genes implicated in microcephaly or macrocephaly. TACIT provides a foundation for identifying enhancers associated with the evolution of any convergently evolved phenotype in any large group of species with aligned genomes.
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Affiliation(s)
- Irene M Kaplow
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Alyssa J Lawler
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Daniel E Schäffer
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Chaitanya Srinivasan
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Heather H Sestili
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Morgan E Wirthlin
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - BaDoi N Phan
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Medical Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Kavya Prasad
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ashley R Brown
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Xiaomeng Zhang
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Kathleen Foley
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Diane P Genereux
- Broad Institute, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Elinor K Karlsson
- Broad Institute, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Kerstin Lindblad-Toh
- Broad Institute, Cambridge, MA, USA
- Science for Life Laboratory, Department of Medical Biochemistry and Microbiology, Uppsala University, Uppsala, Sweden
| | - Wynn K Meyer
- Department of Biological Sciences, Lehigh University, Bethlehem, PA, USA
| | - Andreas R Pfenning
- Department of Computational Biology, Carnegie Mellon University, Pittsburgh, PA, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
- Department of Biology, Carnegie Mellon University, Pittsburgh, PA, USA
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43
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Ouyang W, Zhang X, Guo M, Wang J, Wang X, Gao R, Ma M, Xiang X, Luan S, Xing F, Cao Z, Yan J, Li G, Li X. Haplotype mapping of H3K27me3-associated chromatin interactions defines topological regulation of gene silencing in rice. Cell Rep 2023; 42:112350. [PMID: 37071534 DOI: 10.1016/j.celrep.2023.112350] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Revised: 02/06/2023] [Accepted: 03/20/2023] [Indexed: 04/19/2023] Open
Abstract
Histone modification H3K27me3 is an important chromatin mark that plays vital roles in repressing expression of developmental genes. Here, we construct high-resolution 3D genome maps using long-read chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) and characterize H3K27me3-associated chromatin interactions in an elite rice hybrid, Shanyou 63. We find that many H3K27me3-marked regions may function as silencer-like regulatory elements. The silencer-like elements can come into proximity with distal target genes via forming chromatin loops in 3D space of the nuclei, regulating gene silencing and plant traits. Natural and induced deletion of silencers upregulate expression of distal connected genes. Furthermore, we identify extensive allele-specific chromatin loops. We find that genetic variations alter allelic chromatin topology, thus modulating allelic gene imprinting in rice hybrids. In conclusion, the characterization of silencer-like regulatory elements and haplotype-resolved chromatin interaction maps provide insights into the understanding of molecular mechanisms underlying allelic gene silencing and plant trait controlling.
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Affiliation(s)
- Weizhi Ouyang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiwen Zhang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Minrong Guo
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Jing Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Xiaoting Wang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Runxin Gao
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Meng Ma
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Xu Xiang
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Shiping Luan
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Feng Xing
- College of Life Science, Xinyang Normal University, Xinyang 464000, China
| | - Zhilin Cao
- Department of Resources and Environment, Henan University of Engineering, Zhengzhou 451191, China
| | - Jiapei Yan
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China
| | - Guoliang Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Wuhan, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
| | - Xingwang Li
- National Key Laboratory of Crop Genetic Improvement, Hubei Hongshan Laboratory, Huazhong Agricultural University, Wuhan 430070, China; Shenzhen Institute of Nutrition and Health, Huazhong Agricultural University, Wuhan, China; Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, China.
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44
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Arzate-Mejia RG, Mansuy IM. Remembering through the genome: the role of chromatin states in brain functions and diseases. Transl Psychiatry 2023; 13:122. [PMID: 37041131 PMCID: PMC10090084 DOI: 10.1038/s41398-023-02415-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 03/19/2023] [Accepted: 03/24/2023] [Indexed: 04/13/2023] Open
Abstract
Chromatin is the physical substrate of the genome that carries the DNA sequence and ensures its proper functions and regulation in the cell nucleus. While a lot is known about the dynamics of chromatin during programmed cellular processes such as development, the role of chromatin in experience-dependent functions remains not well defined. Accumulating evidence suggests that in brain cells, environmental stimuli can trigger long-lasting changes in chromatin structure and tri-dimensional (3D) organization that can influence future transcriptional programs. This review describes recent findings suggesting that chromatin plays an important role in cellular memory, particularly in the maintenance of traces of prior activity in the brain. Inspired by findings in immune and epithelial cells, we discuss the underlying mechanisms and the implications for experience-dependent transcriptional regulation in health and disease. We conclude by presenting a holistic view of chromatin as potential molecular substrate for the integration and assimilation of environmental information that may constitute a conceptual basis for future research.
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Affiliation(s)
- Rodrigo G Arzate-Mejia
- Laboratory of Neuroepigenetics, Brain Research Institute, Medical Faculty, University of Zurich, Zurich, Switzerland
- Institute for Neuroscience, Department of Health Science and Technology, Swiss Federal Institute of Technology Zürich (ETHZ), Zurich, Switzerland
- Center for Neuroscience Zürich, University Zürich and ETHZ, Zürich, Switzerland
| | - Isabelle M Mansuy
- Laboratory of Neuroepigenetics, Brain Research Institute, Medical Faculty, University of Zurich, Zurich, Switzerland.
- Institute for Neuroscience, Department of Health Science and Technology, Swiss Federal Institute of Technology Zürich (ETHZ), Zurich, Switzerland.
- Center for Neuroscience Zürich, University Zürich and ETHZ, Zürich, Switzerland.
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45
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Gunsalus LM, McArthur E, Gjoni K, Kuang S, Pittman M, Capra JA, Pollard KS. Comparing chromatin contact maps at scale: methods and insights. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.04.535480. [PMID: 37066196 PMCID: PMC10104037 DOI: 10.1101/2023.04.04.535480] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Comparing chromatin contact maps is an essential step in quantifying how three-dimensional (3D) genome organization shapes development, evolution, and disease. However, no gold standard exists for comparing contact maps, and even simple methods often disagree. In this study, we propose novel comparison methods and evaluate them alongside existing approaches using genome-wide Hi-C data and 22,500 in silico predicted contact maps. We also quantify the robustness of methods to common sources of biological and technical variation, such as boundary size and noise. We find that simple difference-based methods such as mean squared error are suitable for initial screening, but biologically informed methods are necessary to identify why maps diverge and propose specific functional hypotheses. We provide a reference guide, codebase, and benchmark for rapidly comparing chromatin contact maps at scale to enable biological insights into the 3D organization of the genome.
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Affiliation(s)
- Laura M. Gunsalus
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA
| | - Evonne McArthur
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN
| | - Ketrin Gjoni
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA
| | - Shuzhen Kuang
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA
| | - Maureen Pittman
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA
| | - John A. Capra
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA
| | - Katherine S. Pollard
- Gladstone Institute of Data Science and Biotechnology, San Francisco, CA
- Department of Epidemiology & Biostatistics, University of California, San Francisco, CA
- Bakar Computational Health Sciences Institute, University of California, San Francisco, CA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
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46
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Schaeffer M, Nollmann M. Contributions of 3D chromatin structure to cell-type-specific gene regulation. Curr Opin Genet Dev 2023; 79:102032. [PMID: 36893484 DOI: 10.1016/j.gde.2023.102032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Revised: 02/05/2023] [Accepted: 02/06/2023] [Indexed: 03/09/2023]
Abstract
Eukaryotic genomes are organized in 3D in a multiscale manner, and different mechanisms acting at each of these scales can contribute to transcriptional regulation. However, the large single-cell variability in 3D chromatin structures represents a challenge to understand how transcription may be differentially regulated between cell types in a robust and efficient manner. Here, we describe the different mechanisms by which 3D chromatin structure was shown to contribute to cell-type-specific transcriptional regulation. Excitingly, several novel methodologies able to measure 3D chromatin conformation and transcription in single cells in their native tissue context, or to detect the dynamics of cis-regulatory interactions, are starting to allow quantitative dissection of chromatin structure noise and relate it to how transcription may be regulated between different cell types and cell states.
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Affiliation(s)
- Marie Schaeffer
- Centre de Biologie Structurale, Univ Montpellier, CNRS UMR 5048, INSERM U1054, Montpellier, France
| | - Marcelo Nollmann
- Centre de Biologie Structurale, Univ Montpellier, CNRS UMR 5048, INSERM U1054, Montpellier, France.
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47
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Dynamics of RNA m 5C modification during brain development. Genomics 2023; 115:110604. [PMID: 36889368 DOI: 10.1016/j.ygeno.2023.110604] [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: 10/19/2022] [Revised: 02/26/2023] [Accepted: 03/03/2023] [Indexed: 03/08/2023]
Abstract
Post-transcriptional RNA modifications have been recognized as key regulators of neuronal differentiation and synapse development in the mammalian brain. While distinct sets of 5-methylcytosine (m5C) modified mRNAs have been detected in neuronal cells and brain tissues, no study has been performed to characterize methylated mRNA profiles in the developing brain. Here, together with regular RNA-seq, we performed transcriptome-wide bisulfite sequencing to compare RNA cytosine methylation patterns in neural stem cells (NSCs), cortical neuronal cultures, and brain tissues at three postnatal stages. Among 501 m5C sites identified, approximately 6% are consistently methylated across all five conditions. Compared to m5C sites identified in NSCs, 96% of them were hypermethylated in neurons and enriched for genes involved in positive transcriptional regulation and axon extension. In addition, brains at the early postnatal stage demonstrated substantial changes in both RNA cytosine methylation and gene expression of RNA cytosine methylation readers, writers, and erasers. Furthermore, differentially methylated transcripts were significantly enriched for genes regulating synaptic plasticity. Altogether, this study provides a brain epitranscriptomic dataset as a new resource and lays the foundation for further investigations into the role of RNA cytosine methylation during brain development.
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48
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Anholt RRH, Mackay TFC. The genetic architecture of behavioral canalization. Trends Genet 2023:S0168-9525(23)00033-1. [PMID: 36878820 DOI: 10.1016/j.tig.2023.02.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 02/10/2023] [Accepted: 02/14/2023] [Indexed: 03/07/2023]
Abstract
Behaviors are components of fitness and contribute to adaptive evolution. Behaviors represent the interactions of an organism with its environment, yet innate behaviors display robustness in the face of environmental change, which we refer to as 'behavioral canalization'. We hypothesize that positive selection of hub genes of genetic networks stabilizes the genetic architecture for innate behaviors by reducing variation in the expression of interconnected network genes. Robustness of these stabilized networks would be protected from deleterious mutations by purifying selection or suppressing epistasis. We propose that, together with newly emerging favorable mutations, epistatically suppressed mutations can generate a reservoir of cryptic genetic variation that could give rise to decanalization when genetic backgrounds or environmental conditions change to allow behavioral adaptation.
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Affiliation(s)
- Robert R H Anholt
- Department of Genetics and Biochemistry and Center for Human Genetics, Clemson University, 114 Gregor Mendel Circle, Greenwood, SC 29646, USA.
| | - Trudy F C Mackay
- Department of Genetics and Biochemistry and Center for Human Genetics, Clemson University, 114 Gregor Mendel Circle, Greenwood, SC 29646, USA
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49
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Tan L, Shi J, Moghadami S, Wright CP, Parasar B, Seo Y, Vallejo K, Cobos I, Duncan L, Chen R, Deisseroth K. Cerebellar Granule Cells Develop Non-neuronal 3D Genome Architecture over the Lifespan. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.25.530020. [PMID: 36865235 PMCID: PMC9980173 DOI: 10.1101/2023.02.25.530020] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2023]
Abstract
The cerebellum contains most of the neurons in the human brain, and exhibits unique modes of development, malformation, and aging. For example, granule cells-the most abundant neuron type-develop unusually late and exhibit unique nuclear morphology. Here, by developing our high-resolution single-cell 3D genome assay Dip-C into population-scale (Pop-C) and virus-enriched (vDip-C) modes, we were able to resolve the first 3D genome structures of single cerebellar cells, create life-spanning 3D genome atlases for both human and mouse, and jointly measure transcriptome and chromatin accessibility during development. We found that while the transcriptome and chromatin accessibility of human granule cells exhibit a characteristic maturation pattern within the first year of postnatal life, 3D genome architecture gradually remodels throughout life into a non-neuronal state with ultra-long-range intra-chromosomal contacts and specific inter-chromosomal contacts. This 3D genome remodeling is conserved in mice, and robust to heterozygous deletion of chromatin remodeling disease-associated genes (Chd8 or Arid1b). Together these results reveal unexpected and evolutionarily-conserved molecular processes underlying the unique development and aging of the mammalian cerebellum.
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Affiliation(s)
- Longzhi Tan
- Department of Neurobiology, Stanford University, Stanford, CA
- Department of Bioengineering, Stanford University, Stanford, CA
| | - Jenny Shi
- Department of Neurobiology, Stanford University, Stanford, CA
- Department of Bioengineering, Stanford University, Stanford, CA
- Department of Chemistry, Stanford University, Stanford, CA
| | - Siavash Moghadami
- Department of Neurobiology, Stanford University, Stanford, CA
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA
| | - Cydney P. Wright
- Department of Neurobiology, Stanford University, Stanford, CA
- Department of Biology, Stanford University, Stanford, CA
| | - Bibudha Parasar
- Department of Neurobiology, Stanford University, Stanford, CA
| | - Yunji Seo
- Department of Neurobiology, Stanford University, Stanford, CA
| | | | - Inma Cobos
- Department of Pathology, Stanford University, Stanford, CA
| | - Laramie Duncan
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA
| | - Ritchie Chen
- Department of Bioengineering, Stanford University, Stanford, CA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA
- Howard Hughes Medical Institute, Stanford, CA
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50
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Abdennur N, Fudenberg G, Flyamer IM, Galitsyna AA, Goloborodko A, Imakaev M, Venev SV. Pairtools: from sequencing data to chromosome contacts. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.13.528389. [PMID: 36824968 PMCID: PMC9949071 DOI: 10.1101/2023.02.13.528389] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
The field of 3D genome organization produces large amounts of sequencing data from Hi-C and a rapidly-expanding set of other chromosome conformation protocols (3C+). Massive and heterogeneous 3C+ data require high-performance and flexible processing of sequenced reads into contact pairs. To meet these challenges, we present pairtools - a flexible suite of tools for contact extraction from sequencing data. Pairtools provides modular command-line interface (CLI) tools that can be flexibly chained into data processing pipelines. Pairtools provides both crucial core tools as well as auxiliary tools for building feature-rich 3C+ pipelines, including contact pair manipulation, filtration, and quality control. Benchmarking pairtools against popular 3C+ data pipelines shows advantages of pairtools for high-performance and flexible 3C+ analysis. Finally, pairtools provides protocol-specific tools for multi-way contacts, haplotype-resolved contacts, and single-cell Hi-C. The combination of CLI tools and tight integration with Python data analysis libraries makes pairtools a versatile foundation for a broad range of 3C+ pipelines.
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Affiliation(s)
- Open2C
- https://open2c.github.io/
| | - Nezar Abdennur
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, 01605, MA
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, 01605, USA
| | - Geoffrey Fudenberg
- Department of Computational and Quantitative Biology, University of Southern California, Los Angeles, CA, USA
| | - Ilya M. Flyamer
- Friedrich Miescher Institute for Biomedical Research, Maulbeerstrasse 66, CH-4058 Basel, Switzerland
| | - Aleksandra A. Galitsyna
- Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology (MIT), Cambridge, MA, 02139, USA
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria
| | - Anton Goloborodko
- Institute of Molecular Biotechnology of the Austrian Academy of Sciences (IMBA), Vienna BioCenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria
| | - Maxim Imakaev
- Institute for Medical Engineering and Sciences, Massachusetts Institute of Technology (MIT), Cambridge, MA, 02139, USA
| | - Sergey V. Venev
- Department of Systems Biology, University of Massachusetts Chan Medical School, Worcester, MA, 01605, USA
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