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Cheng Y, Hu M, Yang B, Jensen TB, Zhang Y, Yang T, Yu R, Ma Z, Radda JSD, Jin S, Zang C, Wang S. Perturb-tracing enables high-content screening of multi-scale 3D genome regulators. Nat Methods 2025; 22:950-961. [PMID: 40211002 PMCID: PMC12074983 DOI: 10.1038/s41592-025-02652-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2024] [Accepted: 03/07/2025] [Indexed: 04/12/2025]
Abstract
Three-dimensional (3D) genome organization becomes altered during development, aging and disease, but the factors regulating chromatin topology are incompletely understood and currently no technology can efficiently screen for new regulators of multi-scale chromatin organization. Here, we developed an image-based high-content screening platform (Perturb-tracing) that combines pooled CRISPR screens, a cellular barcode readout method (BARC-FISH) and chromatin tracing. We performed a loss-of-function screen in human cells, and visualized alterations to their 3D chromatin folding conformations, alongside perturbation-paired barcode readout in the same single cells. We discovered tens of new regulators of chromatin folding at different length scales, ranging from chromatin domains and compartments to chromosome territory. A subset of the regulators exhibited 3D genome effects associated with loop extrusion and A-B compartmentalization mechanisms, while others were largely unrelated to these known 3D genome mechanisms. Finally, we identified new regulators of nuclear architectures and found a functional link between chromatin compaction and nuclear shape. Altogether, our method enables scalable, high-content identification of chromatin and nuclear topology regulators that will stimulate new insights into the 3D genome.
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Affiliation(s)
- Yubao Cheng
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Mengwei Hu
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Bing Yang
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Tyler B Jensen
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT, USA
- M.D.-Ph.D. Program, Yale University, New Haven, CT, USA
| | - Yuan Zhang
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Tianqi Yang
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Ruihuan Yu
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Zhaoxia Ma
- Department of Genome Sciences, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
| | - Jonathan S D Radda
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Shengyan Jin
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Chongzhi Zang
- Department of Genome Sciences, University of Virginia, Charlottesville, VA, USA
- Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, USA
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA, USA
- UVA Comprehensive Cancer Center, University of Virginia, Charlottesville, VA, USA
| | - Siyuan Wang
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT, USA.
- M.D.-Ph.D. Program, Yale University, New Haven, CT, USA.
- Department of Cell Biology, Yale School of Medicine, Yale University, New Haven, CT, USA.
- Yale Combined Program in the Biological and Biomedical Sciences, Yale University, New Haven, CT, USA.
- Molecular Cell Biology, Genetics and Development Program, Yale University, New Haven, CT, USA.
- Biochemistry, Quantitative Biology, Biophysics, and Structural Biology Program, Yale University, New Haven, CT, USA.
- Yale Center for RNA Science and Medicine, Yale University School of Medicine, New Haven, CT, USA.
- Yale Liver Center, Yale University School of Medicine, New Haven, CT, USA.
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2
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Lee Y, Lee M, Shin Y, Kim K, Kim T. Spatial Omics in Clinical Research: A Comprehensive Review of Technologies and Guidelines for Applications. Int J Mol Sci 2025; 26:3949. [PMID: 40362187 PMCID: PMC12071594 DOI: 10.3390/ijms26093949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2025] [Revised: 04/17/2025] [Accepted: 04/17/2025] [Indexed: 05/15/2025] Open
Abstract
Spatial omics integrates molecular profiling with spatial tissue context, enabling high-resolution analysis of gene expression, protein interactions, and epigenetic modifications. This approach provides critical insights into disease mechanisms and therapeutic responses, with applications in cancer, neurology, and immunology. Spatial omics technologies, including spatial transcriptomics, proteomics, and epigenomics, facilitate the study of cellular heterogeneity, tissue organization, and cell-cell interactions within their native environments. Despite challenges in data complexity and integration, advancements in multi-omics pipelines and computational tools are enhancing data accuracy and biological interpretation. This review provides a comprehensive overview of key spatial omics technologies, their analytical methods, validation strategies, and clinical applications. By integrating spatially resolved molecular data with traditional omics, spatial omics is transforming precision medicine, biomarker discovery, and personalized therapy. Future research should focus on improving standardization, reproducibility, and multimodal data integration to fully realize the potential of spatial omics in clinical and translational research.
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Affiliation(s)
- Yoonji Lee
- College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea; (Y.L.); (M.L.); (Y.S.)
| | - Mingyu Lee
- College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea; (Y.L.); (M.L.); (Y.S.)
| | - Yoojin Shin
- College of Medicine, The Catholic University of Korea, 222 Banpo-daero, Seocho-gu, Seoul 06591, Republic of Korea; (Y.L.); (M.L.); (Y.S.)
| | - Kyuri Kim
- College of Medicine, Ewha Womans University, 25 Magokdong-ro 2-gil, Gangseo-gu, Seoul 07804, Republic of Korea;
| | - Taejung Kim
- Department of Hospital Pathology, Yeouido St. Mary’s Hospital, College of Medicine, The Catholic University of Korea, 10, 63-ro, Yeongdeungpo-gu, Seoul 07345, Republic of Korea
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3
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Cheng Y, Dang S, Zhang Y, Chen Y, Yu R, Liu M, Jin S, Han A, Katz S, Wang S. Sequencing-free whole genome spatial transcriptomics at molecular resolution in intact tissue. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.03.06.641951. [PMID: 40161724 PMCID: PMC11952344 DOI: 10.1101/2025.03.06.641951] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 04/02/2025]
Abstract
Recent breakthroughs in spatial transcriptomics technologies have enhanced our understanding of diverse cellular identities, compositions, interactions, spatial organizations, and functions. Yet existing spatial transcriptomics tools are still limited in either transcriptomic coverage or spatial resolution. Leading spatial-capture or spatial-tagging transcriptomics techniques that rely on in-vitro sequencing offer whole-transcriptome coverage, in principle, but at the cost of lower spatial resolution compared to image-based techniques. In contrast, high-performance image-based spatial transcriptomics techniques, which rely on in situ hybridization or in situ sequencing, achieve single-molecule spatial resolution and retain sub-cellular morphologies, but are limited by probe libraries that target only a subset of the transcriptome, typically covering several hundred to a few thousand transcript species. Together, these limitations hinder unbiased, hypothesis-free transcriptomic analyses at high spatial resolution. Here we develop a new image-based spatial transcriptomics technology termed Reverse-padlock Amplicon Encoding FISH (RAEFISH) with whole-genome level coverage while retaining single-molecule spatial resolution in intact tissues. We demonstrate image-based spatial transcriptomics targeting 23,000 human transcript species or 22,000 mouse transcript species, including nearly the entire protein-coding transcriptome and several thousand long-noncoding RNAs, in single cells in cultures and in tissue sections. Our analyses reveal differential subcellular localizations of diverse transcripts, cell-type-specific and cell-type-invariant tissue zonation dependent transcriptome, and gene expression programs underlying preferential cell-cell interactions. Finally, we further develop our technology for direct spatial readout of gRNAs in an image-based high-content CRISPR screen. Overall, these developments provide the research community with a broadly applicable technology that enables high-coverage, high-resolution spatial profiling of both long and short, native and engineered RNA species in many biomedical contexts.
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Affiliation(s)
- Yubao Cheng
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Shengyuan Dang
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
- These authors contributed equally to this work
| | - Yuan Zhang
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
- These authors contributed equally to this work
| | - Yanbo Chen
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Ruihuan Yu
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
- Present Address: Department of Biological Sciences, Columbia University, New York, NY 10027, USA
| | - Miao Liu
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Shengyan Jin
- Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA
| | - Ailin Han
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Samuel Katz
- Department of Pathology, Yale University School of Medicine, New Haven, CT 06520, USA
| | - Siyuan Wang
- Department of Genetics, Yale University School of Medicine, 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 University School of Medicine, 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
- Lead contact
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4
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Morival J, Hazelwood A, Lammerding J. Feeling the force from within - new tools and insights into nuclear mechanotransduction. J Cell Sci 2025; 138:JCS263615. [PMID: 40059756 PMCID: PMC11959624 DOI: 10.1242/jcs.263615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/03/2025] Open
Abstract
The ability of cells to sense and respond to mechanical signals is essential for many biological processes that form the basis of cell identity, tissue development and maintenance. This process, known as mechanotransduction, involves crucial feedback between mechanical force and biochemical signals, including epigenomic modifications that establish transcriptional programs. These programs, in turn, reinforce the mechanical properties of the cell and its ability to withstand mechanical perturbation. The nucleus has long been hypothesized to play a key role in mechanotransduction due to its direct exposure to forces transmitted through the cytoskeleton, its role in receiving cytoplasmic signals and its central function in gene regulation. However, parsing out the specific contributions of the nucleus from those of the cell surface and cytoplasm in mechanotransduction remains a substantial challenge. In this Review, we examine the latest evidence on how the nucleus regulates mechanotransduction, both via the nuclear envelope (NE) and through epigenetic and transcriptional machinery elements within the nuclear interior. We also explore the role of nuclear mechanotransduction in establishing a mechanical memory, characterized by a mechanical, epigenetic and transcriptomic cell state that persists after mechanical stimuli cease. Finally, we discuss current challenges in the field of nuclear mechanotransduction and present technological advances that are poised to overcome them.
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Affiliation(s)
- Julien Morival
- Weill Institute for Cell and Molecular Biology, Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY 14850, USA
| | - Anna Hazelwood
- Weill Institute for Cell and Molecular Biology, Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY 14850, USA
| | - Jan Lammerding
- Weill Institute for Cell and Molecular Biology, Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY 14850, USA
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5
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Starble RM, Sun EG, Gbyli R, Radda J, Lu J, Jensen TB, Sun N, Khudaverdyan N, Hu B, Melnick MA, Zhao S, Roper N, Wang GG, Song J, Politi K, Wang S, Xiao AZ. Epigenetic priming promotes acquisition of tyrosine kinase inhibitor resistance and oncogene amplification in human lung cancer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.01.26.634826. [PMID: 39974875 PMCID: PMC11838195 DOI: 10.1101/2025.01.26.634826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 02/21/2025]
Abstract
In mammalian cells, gene copy number is tightly controlled to maintain gene expression and genome stability. However, a common molecular feature across cancer types is oncogene amplification, which promotes cancer progression by drastically increasing the copy number and expression of tumor-promoting genes. For example, in tyrosine kinase inhibitor (TKI)-resistant lung adenocarcinoma (LUAD), oncogene amplification occurs in over 40% of patients' tumors. Despite the prevalence of oncogene amplification in TKI-resistant tumors, the mechanisms facilitating oncogene amplification are not fully understood. Here, we find that LUADs exhibit a unique chromatin signature demarcated by strong CTCF and cohesin deposition in drug-naïve tumors, which correlates with the boundaries of oncogene amplicons in TKI-resistant LUAD cells. We identified a global chromatin priming effect during the acquisition of TKI resistance, marked by a dynamic increase of H3K27Ac, cohesin loading, and inter-TAD interactions, which occurs before the onset of oncogene amplification. Furthermore, we have found that the METTL7A protein, which was previously reported to localize to the endoplasmic reticulum and inner nuclear membrane, has a novel chromatin regulatory function by binding to amplified loci and regulating cohesin recruitment and inter-TAD interactions. Surprisingly, we discovered that METTL7A remodels the chromatin landscape prior to large-scale copy number gains. Furthermore, while METTL7A depletion has little effect on the chromatin structure and proliferation of drug-naïve cells, METTL7A depletion prevents the formation and maintenance of TKI resistant-clones, highlighting the specific role of METTL7A as cells are becoming resistant. In summary, we discovered an unexpected mechanism required for the acquisition of TKI resistance regulated by a largely uncharacterized factor, METTL7A. This discovery sheds light into the maintenance of oncogene copy number and paves the way to the development of new therapeutics for preventing TKI resistance in LUAD.
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Affiliation(s)
- Rebecca M Starble
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
- Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
- Department of Pathology, Yale School of Medicine, New Haven, CT 06510, USA
| | - Eric G Sun
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
- Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
- Present address: Tri-Institutional MD-PhD Program, Weill Cornell Medicine, Rockefeller University, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA
| | - Rana Gbyli
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
- Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Jonathan Radda
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
| | - Jiuwei Lu
- Department of Biochemistry, University of California, Riverside, CA 92521, USA
| | - Tyler B Jensen
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
- Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Ning Sun
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
- Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
- Present address: Key Laboratory of Growth Regulation and Transformation Research of Zhejiang Province, School of Life Sciences, Westlake University, Hangzhou 310024, China
| | - Nelli Khudaverdyan
- Department of Biochemistry, University of California, Riverside, CA 92521, USA
| | - Bomiao Hu
- Department of Pathology, Yale School of Medicine, New Haven, CT 06510, USA
| | | | - Shuai Zhao
- Department of Pharmacology and Cancer Biology, Duke University School of Medicine, Durham, NC, USA
- Duke Cancer Institute, Duke University School of Medicine, Durham, NC, USA
| | - Nitin Roper
- Developmental Therapeutics Branch, Center for Cancer Research, NCI, NIH, Bethesda, MD 20892, USA
| | - Gang Greg Wang
- Department of Pharmacology and Cancer Biology, Duke University School of Medicine, Durham, NC, USA
- Duke Cancer Institute, Duke University School of Medicine, Durham, NC, USA
| | - Jikui Song
- Department of Biochemistry, University of California, Riverside, CA 92521, USA
| | - Katerina Politi
- Department of Pathology, Yale School of Medicine, New Haven, CT 06510, USA
- Yale Cancer Center, New Haven, CT 06520, USA
- Department of Medicine (Section of Medical Oncology), Yale School of Medicine, New Haven, CT 06510, USA
| | - Siyuan Wang
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
- Department of Cell Biology, Yale School of Medicine, New Haven, CT 06510, USA
| | - Andrew Z Xiao
- Department of Genetics, Yale School of Medicine, New Haven, CT 06520, USA
- Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
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6
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Harke J, Lee JR, Nguyen SC, Arab A, Rakowiecki SM, Hugelier S, Paliou C, Rauseo A, Yunker R, Xu K, Yao Y, Lakadamyali M, Andrey G, Epstein DJ, Joyce EF. Multiple allelic configurations govern long-range Shh enhancer-promoter communication in the embryonic forebrain. Mol Cell 2024; 84:4698-4710.e6. [PMID: 39579767 DOI: 10.1016/j.molcel.2024.10.042] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Revised: 08/30/2024] [Accepted: 10/30/2024] [Indexed: 11/25/2024]
Abstract
Developmental gene regulation requires input from enhancers spread over large genomic distances. Our understanding of long-range enhancer-promoter (E-P) communication, characterized as loops, remains incomplete without addressing the role of intervening chromatin. Here, we examine the topology of the entire Sonic hedgehog (Shh) regulatory domain in individual alleles from the mouse embryonic forebrain. Through sequential Oligopaint labeling and super-resolution microscopy, we find that the Shh locus maintains a compact structure that adopts several diverse configurations independent of Shh expression. The most frequent configuration contained distal E-P contacts at the expense of those more proximal to Shh, consistent with an interconnected loop. Genetic perturbations demonstrate that this long-range E-P communication operates by Shh-expression-independent and dependent mechanisms, involving CTCF binding sites and active enhancers, respectively. We propose a model whereby gene regulatory elements secure long-range E-P interactions amid an inherent architectural framework to coordinate spatiotemporal patterns of gene expression.
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Affiliation(s)
- Jailynn Harke
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jeewon R Lee
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Son C Nguyen
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arian Arab
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Staci M Rakowiecki
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Siewert Hugelier
- Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Christina Paliou
- Andalusian Center for Developmental Biology (CABD), Spanish National Research Council, Pablo de Olavide University, Andalusian Regional Government, Seville, Spain
| | - Antonella Rauseo
- Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland; Institute of Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland
| | - Rebecca Yunker
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kellen Xu
- Department of Pharmacology, Robert Wood Johnson Medical School, Rutgers, The State University of New Jersey, Piscataway, NJ, USA
| | - Yao Yao
- Department of Animal and Dairy Science, Regenerative Bioscience Center, University of Georgia, Athens, GA, USA
| | - Melike Lakadamyali
- Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Physiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Guillaume Andrey
- Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland; Institute of Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland
| | - Douglas J Epstein
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Eric F Joyce
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Penn Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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7
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Baumgartner M, Ji Y, Noonan JP. Reconstructing human-specific regulatory functions in model systems. Curr Opin Genet Dev 2024; 89:102259. [PMID: 39270593 PMCID: PMC11588545 DOI: 10.1016/j.gde.2024.102259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2024] [Revised: 08/19/2024] [Accepted: 08/20/2024] [Indexed: 09/15/2024]
Abstract
Uniquely human physical traits, such as an expanded cerebral cortex and changes in limb morphology that allow us to use tools and walk upright, are in part due to human-specific genetic changes that altered when, where, and how genes are expressed during development. Over 20 000 putative regulatory elements with potential human-specific functions have been discovered. Understanding how these elements contributed to human evolution requires identifying candidates most likely to have shaped human traits, then studying them in genetically modified animal models. Here, we review the progress and challenges in generating and studying such models and propose a pathway for advancing the field. Finally, we highlight that large-scale collaborations across multiple research domains are essential to decipher what makes us human.
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Affiliation(s)
| | - Yu Ji
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - James P Noonan
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA; Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510 USA; Wu Tsai Institute, Yale University, New Haven, CT 06510, USA.
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8
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Liu M, Jin S, Agabiti SS, Jensen TB, Yang T, Radda JSD, Ruiz CF, Baldissera G, Rajaei M, Townsend JP, Muzumdar MD, Wang S. Tracing the evolution of single-cell cancer 3D genomes: an atlas for cancer gene discovery. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.23.550157. [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
Although three-dimensional (3D) genome structures are altered in cancer cells, little is known about how these changes evolve and diversify during cancer progression. Leveraging genome-wide chromatin tracing to visualize 3D genome folding directly in tissues, we generated 3D genome cancer atlases of murine lung and pancreatic adenocarcinoma. Our data reveal stereotypical, non-monotonic, and stage-specific alterations in 3D genome folding heterogeneity, compaction, and compartmentalization as cancers progress from normal to preinvasive and ultimately to invasive tumors, discovering a potential structural bottleneck in early tumor progression. Remarkably, 3D genome architectures distinguish histologic cancer states in single cells, despite considerable cell-to-cell heterogeneity. Gene-level analyses of evolutionary changes in 3D genome compartmentalization not only showed compartment-associated genes are more homogeneously regulated, but also elucidated prognostic and dependency genes in lung adenocarcinoma and a previously unappreciated role for polycomb-group protein Rnf2 in 3D genome regulation. Our results demonstrate the utility of mapping the single-cell cancer 3D genome in tissues and illuminate its potential to identify new diagnostic, prognostic, and therapeutic biomarkers in cancer.
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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
| | - Moein Rajaei
- Department of Biostatistics, Yale School of Public Health, Yale University; New Haven, CT 06510, USA
| | - Jeffrey P. Townsend
- Department of Biostatistics, Yale School of Public Health, Yale University; New Haven, CT 06510, USA
- Program in Computational Biology and Bioinformatics, Yale University; New Haven, CT 06510, USA
- Program in Genetics, Genomics, and Epigenetics, Yale Cancer Center, 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
- Program in Genetics, Genomics, and Epigenetics, Yale Cancer Center, 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 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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9
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Wang SE, Cheng Y, Lim J, Jang MA, Forrest EN, Kim Y, Donahue M, Qiao SN, Xiong Y, Jin J, Wang S, Jiang YH. Mechanism of EHMT2-mediated genomic imprinting associated with Prader-Willi syndrome. RESEARCH SQUARE 2024:rs.3.rs-4530649. [PMID: 39011107 PMCID: PMC11247926 DOI: 10.21203/rs.3.rs-4530649/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/17/2024]
Abstract
Prader-Willi Syndrome (PWS) is caused by loss of expression of paternally expressed genes in the human 15q11.2-q13 imprinting domain. A set of imprinted genes that are active on the paternal but silenced on the maternal chromosome are intricately regulated by a bipartite imprinting center (PWS-IC) located in the PWS imprinting domain. In past work, we discovered that euchromatic histone lysine N-methyltransferase-2 (EHMT2/G9a) inhibitors were capable of un-silencing PWS-associated genes by restoring their expression from the maternal chromosome. Here, in mice lacking the Ehmt2 gene, we document un-silencing of the imprinted Snrpn/Snhg14 gene on the maternal chromosome in the late embryonic and postnatal brain. Using PWS and Angelman syndrome patient derived cells with either paternal or maternal deletion of 15q11-q13, we have found that chromatin of maternal PWS-IC is closed and has compact 3D folding confirmation. We further show that a new and distinct noncoding RNA preferentially transcribed from upstream of the PWS-IC interacts with EHMT2 and forms a heterochromatin complex to silence gene expression of SNRPN in CIS on maternal chromosome. Taken together, these findings demonstrate that allele-specific recruitment of EHMT2 is required to maintain the maternal imprints. Our findings provide novel mechanistic insights and support a new model for imprinting maintenance of the PWS imprinted domain.
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Affiliation(s)
- Sung Eun Wang
- Department of Genetics, Yale University School of Medicine, 333 Cedar St, New Haven, CT 06520, USA
| | - Yubao Cheng
- Department of Genetics, Yale University School of Medicine, 333 Cedar St, New Haven, CT 06520, USA
| | - Jaechul Lim
- Immunobiology, Yale University School of Medicine, 333 Cedar St, New Haven, CT 06520, USA
- College of Veterinary Medicine and Research Institute for Veterinary Science, Seoul National University, Gwanak-ro 1, Gwanak-gu, Seoul 08826, South Korea
| | - Mi-Ae Jang
- Department of Laboratory Medicine and Genetics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, South Korea
| | - Emily N. Forrest
- Department of Genetics, Yale University School of Medicine, 333 Cedar St, New Haven, CT 06520, USA
| | - Yuna Kim
- St. Jude Children’s Research Hospital, 262 Danny Thomas Place Memphis, TN 38105, USA
| | - Meaghan Donahue
- Department of Genetics, Yale University School of Medicine, 333 Cedar St, New Haven, CT 06520, USA
| | - Sheng-Nan Qiao
- Department of Genetics, Yale University School of Medicine, 333 Cedar St, New Haven, CT 06520, USA
| | - Yan Xiong
- Mount Sinai Center for Therapeutics Discovery, Departments of Pharmacological Sciences, Oncological Sciences and Neuroscience, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jian Jin
- Mount Sinai Center for Therapeutics Discovery, Departments of Pharmacological Sciences, Oncological Sciences and Neuroscience, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Siyuan Wang
- Department of Genetics, Yale University School of Medicine, 333 Cedar St, New Haven, CT 06520, USA
- Cell Biology, Yale University School of Medicine, 333 Cedar St, New Haven, CT 06520, USA
| | - Yong-hui Jiang
- Department of Genetics, Yale University School of Medicine, 333 Cedar St, New Haven, CT 06520, USA
- Neuroscience, Yale University School of Medicine, 333 Cedar St, New Haven, CT 06520, USA
- Pediatrics, Yale University School of Medicine, 333 Cedar St, New Haven, CT 06520, USA
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10
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Murphy SE, Boettiger AN. Polycomb repression of Hox genes involves spatial feedback but not domain compaction or phase transition. Nat Genet 2024; 56:493-504. [PMID: 38361032 DOI: 10.1038/s41588-024-01661-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 01/10/2024] [Indexed: 02/17/2024]
Abstract
Polycomb group proteins have a critical role in silencing transcription during development. It is commonly proposed that Polycomb-dependent changes in genome folding, which compact chromatin, contribute directly to repression by blocking the binding of activating complexes. Recently, it has also been argued that liquid-liquid demixing of Polycomb proteins facilitates this compaction and repression by phase-separating target genes into a membraneless compartment. To test these models, we used Optical Reconstruction of Chromatin Architecture to trace the Hoxa gene cluster, a canonical Polycomb target, in thousands of single cells. Across multiple cell types, we find that Polycomb-bound chromatin frequently explores decompact states and partial mixing with neighboring chromatin, while remaining uniformly repressed, challenging the repression-by-compaction or phase-separation models. Using polymer simulations, we show that these observed flexible ensembles can be explained by 'spatial feedback'-transient contacts that contribute to the propagation of the epigenetic state (epigenetic memory), without inducing a globular organization.
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Affiliation(s)
- Sedona Eve Murphy
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Developmental Biology, Stanford University, Stanford, CA, USA
- Department of Cell Biology, Yale University, New Haven, CT, USA
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11
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Devos X, Fiche JB, Bardou M, Messina O, Houbron C, Gurgo J, Schaeffer M, Götz M, Walter T, Mueller F, Nollmann M. pyHiM: a new open-source, multi-platform software package for spatial genomics based on multiplexed DNA-FISH imaging. Genome Biol 2024; 25:47. [PMID: 38351149 PMCID: PMC10863255 DOI: 10.1186/s13059-024-03178-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 01/29/2024] [Indexed: 02/16/2024] Open
Abstract
Genome-wide ensemble sequencing methods improved our understanding of chromatin organization in eukaryotes but lack the ability to capture single-cell heterogeneity and spatial organization. To overcome these limitations, new imaging-based methods have emerged, giving rise to the field of spatial genomics. Here, we present pyHiM, a user-friendly python toolbox specifically designed for the analysis of multiplexed DNA-FISH data and the reconstruction of chromatin traces in individual cells. pyHiM employs a modular architecture, allowing independent execution of analysis steps and customization according to sample specificity and computing resources. pyHiM aims to facilitate the democratization and standardization of spatial genomics analysis.
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Affiliation(s)
- Xavier Devos
- Centre de Biologie Structurale, Univ Montpellier, CNRS UMR 5048, INSERM U1054, 34090, Montpellier, France
| | - Jean-Bernard Fiche
- Centre de Biologie Structurale, Univ Montpellier, CNRS UMR 5048, INSERM U1054, 34090, Montpellier, France
| | - Marion Bardou
- Centre de Biologie Structurale, Univ Montpellier, CNRS UMR 5048, INSERM U1054, 34090, Montpellier, France
| | - Olivier Messina
- Centre de Biologie Structurale, Univ Montpellier, CNRS UMR 5048, INSERM U1054, 34090, Montpellier, France
| | - Christophe Houbron
- Centre de Biologie Structurale, Univ Montpellier, CNRS UMR 5048, INSERM U1054, 34090, Montpellier, France
| | - Julian Gurgo
- Centre de Biologie Structurale, Univ Montpellier, CNRS UMR 5048, INSERM U1054, 34090, Montpellier, France
| | - Marie Schaeffer
- Centre de Biologie Structurale, Univ Montpellier, CNRS UMR 5048, INSERM U1054, 34090, Montpellier, France
| | - Markus Götz
- Centre de Biologie Structurale, Univ Montpellier, CNRS UMR 5048, INSERM U1054, 34090, Montpellier, France
| | - Thomas Walter
- Centre for Computational Biology (CBIO), Mines Paris, PSL University, 75006, Paris, France
- Institut Curie, 75248, Paris, Cedex, France
- INSERM, U900, 75248, Paris, Cedex, France
| | - Florian Mueller
- Imaging and Modeling Unit, Institut Pasteur, Université Paris Cité, Paris, France
| | - Marcelo Nollmann
- Centre de Biologie Structurale, Univ Montpellier, CNRS UMR 5048, INSERM U1054, 34090, Montpellier, France.
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12
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Tejwani L, Ravindra NG, Lee C, Cheng Y, Nguyen B, Luttik K, Ni L, Zhang S, Morrison LM, Gionco J, Xiang Y, Yoon J, Ro H, Haidery F, Grijalva RM, Bae E, Kim K, Martuscello RT, Orr HT, Zoghbi HY, McLoughlin HS, Ranum LPW, Shakkottai VG, Faust PL, Wang S, van Dijk D, Lim J. Longitudinal single-cell transcriptional dynamics throughout neurodegeneration in SCA1. Neuron 2024; 112:362-383.e15. [PMID: 38016472 PMCID: PMC10922326 DOI: 10.1016/j.neuron.2023.10.039] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Revised: 09/10/2023] [Accepted: 10/27/2023] [Indexed: 11/30/2023]
Abstract
Neurodegeneration is a protracted process involving progressive changes in myriad cell types that ultimately results in the death of vulnerable neuronal populations. To dissect how individual cell types within a heterogeneous tissue contribute to the pathogenesis and progression of a neurodegenerative disorder, we performed longitudinal single-nucleus RNA sequencing of mouse and human spinocerebellar ataxia type 1 (SCA1) cerebellar tissue, establishing continuous dynamic trajectories of each cell population. Importantly, we defined the precise transcriptional changes that precede loss of Purkinje cells and, for the first time, identified robust early transcriptional dysregulation in unipolar brush cells and oligodendroglia. Finally, we applied a deep learning method to predict disease state accurately and identified specific features that enable accurate distinction of wild-type and SCA1 cells. Together, this work reveals new roles for diverse cerebellar cell types in SCA1 and provides a generalizable analysis framework for studying neurodegeneration.
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Affiliation(s)
- Leon Tejwani
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06510, USA; Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA.
| | - Neal G Ravindra
- Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06510, USA; Department of Computer Science, Yale University, New Haven, CT 06510, USA
| | - Changwoo Lee
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06510, USA; Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Yubao Cheng
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Billy Nguyen
- University of California, San Francisco School of Medicine, San Francisco, CA 94143, USA
| | - Kimberly Luttik
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06510, USA; Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Luhan Ni
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Shupei Zhang
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA
| | - Logan M Morrison
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA; Neuroscience Graduate Program, University of Michigan, Ann Arbor, MI 48109, USA
| | - John Gionco
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center and the New York Presbyterian Hospital, New York, NY 10032, USA
| | - Yangfei Xiang
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA; Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06510, USA
| | | | - Hannah Ro
- Yale College, New Haven, CT 06510, USA
| | | | - Rosalie M Grijalva
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06510, USA; Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | | | - Kristen Kim
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06510, USA; Department of Psychiatry, Yale School of Medicine, New Haven, CT 06510, USA
| | - Regina T Martuscello
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center and the New York Presbyterian Hospital, New York, NY 10032, USA
| | - Harry T Orr
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN 55455, USA
| | - Huda Y Zoghbi
- Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital, Houston, TX 77030, USA; Department of Pediatrics, Baylor College of Medicine, Houston, TX 77030, USA; Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA; Howard Hughes Medical Institute, Baylor College of Medicine, Houston, TX 77030, USA
| | - Hayley S McLoughlin
- Department of Neurology, University of Michigan, Ann Arbor, MI 48109-2200, USA
| | - Laura P W Ranum
- Department of Molecular Genetics and Microbiology, Center for Neurogenetics, College of Medicine, Genetics Institute, McKnight Brain Institute, University of Florida, Gainesville, FL 32610, USA
| | - Vikram G Shakkottai
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Phyllis L Faust
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center and the New York Presbyterian Hospital, New York, NY 10032, USA
| | - Siyuan Wang
- Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA; Department of Cell Biology, Yale School of Medicine, New Haven, CT 06510, USA.
| | - David van Dijk
- Cardiovascular Research Center, Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT 06510, USA; Department of Computer Science, Yale University, New Haven, CT 06510, USA.
| | - Janghoo Lim
- Interdepartmental Neuroscience Program, Yale School of Medicine, New Haven, CT 06510, USA; Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA; Department of Genetics, Yale School of Medicine, New Haven, CT 06510, USA; Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06510, USA; Program in Cellular Neuroscience, Neurodegeneration and Repair, Yale School of Medicine, New Haven, CT 06510, USA; Wu Tsai Institute, Yale School of Medicine, New Haven, CT 06510, USA.
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13
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Zhang W, Suo J, Yan Y, Yang R, Lu Y, Jin Y, Gao S, Li S, Gao J, Zhang M, Dai Q. iSMOD: an integrative browser for image-based single-cell multi-omics data. Nucleic Acids Res 2023; 51:8348-8366. [PMID: 37439331 PMCID: PMC10484677 DOI: 10.1093/nar/gkad580] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 06/09/2023] [Accepted: 06/26/2023] [Indexed: 07/14/2023] Open
Abstract
Genomic and transcriptomic image data, represented by DNA and RNA fluorescence in situ hybridization (FISH), respectively, together with proteomic data, particularly that related to nuclear proteins, can help elucidate gene regulation in relation to the spatial positions of chromatins, messenger RNAs, and key proteins. However, methods for image-based multi-omics data collection and analysis are lacking. To this end, we aimed to develop the first integrative browser called iSMOD (image-based Single-cell Multi-omics Database) to collect and browse comprehensive FISH and nucleus proteomics data based on the title, abstract, and related experimental figures, which integrates multi-omics studies focusing on the key players in the cell nucleus from 20 000+ (still growing) published papers. We have also provided several exemplar demonstrations to show iSMOD's wide applications-profiling multi-omics research to reveal the molecular target for diseases; exploring the working mechanism behind biological phenomena using multi-omics interactions, and integrating the 3D multi-omics data in a virtual cell nucleus. iSMOD is a cornerstone for delineating a global view of relevant research to enable the integration of scattered data and thus provides new insights regarding the missing components of molecular pathway mechanisms and facilitates improved and efficient scientific research.
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Affiliation(s)
- Weihang Zhang
- Department of Automation, Tsinghua University, Beijing 100084, China
| | - Jinli Suo
- Department of Automation, Tsinghua University, Beijing 100084, China
- Institute of Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China
- Shanghai Artificial Intelligence Laboratory, Shanghai 200232, China
| | - Yan Yan
- MOE Key Laboratory of Bioinformatics; Bioinformatics Division, BNRist; Center for Synthetic & Systems Biology, Tsinghua University, Beijing 100084, China
- School of Medicine, Tsinghua University, Beijing 100084, China
| | - Runzhao Yang
- Department of Automation, Tsinghua University, Beijing 100084, China
| | - Yiming Lu
- Department of Automation, Tsinghua University, Beijing 100084, China
| | - Yiqi Jin
- Department of Automation, Tsinghua University, Beijing 100084, China
| | - Shuochen Gao
- Department of Automation, Tsinghua University, Beijing 100084, China
| | - Shao Li
- Department of Automation, Tsinghua University, Beijing 100084, China
- MOE Key Laboratory of Bioinformatics; Bioinformatics Division, BNRist; Center for Synthetic & Systems Biology, Tsinghua University, Beijing 100084, China
| | - Juntao Gao
- MOE Key Laboratory of Bioinformatics; Bioinformatics Division, BNRist; Center for Synthetic & Systems Biology, Tsinghua University, Beijing 100084, China
- School of Medicine, Tsinghua University, Beijing 100084, China
| | - Michael Zhang
- MOE Key Laboratory of Bioinformatics; Bioinformatics Division, BNRist; Center for Synthetic & Systems Biology, Tsinghua University, Beijing 100084, China
- School of Medicine, Tsinghua University, Beijing 100084, China
| | - Qionghai Dai
- Department of Automation, Tsinghua University, Beijing 100084, China
- Institute of Brain and Cognitive Sciences, Tsinghua University, Beijing 100084, China
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14
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Patterson B, Yang B, Tanaka Y, Kim KY, Cakir B, Xiang Y, Kim J, Wang S, Park IH. Female naïve human pluripotent stem cells carry X chromosomes with Xa-like and Xi-like folding conformations. SCIENCE ADVANCES 2023; 9:eadf2245. [PMID: 37540754 PMCID: PMC10403202 DOI: 10.1126/sciadv.adf2245] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 07/06/2023] [Indexed: 08/06/2023]
Abstract
Three-dimensional (3D) genomics shows immense promise for studying X chromosome inactivation (XCI) by interrogating changes to the X chromosomes' 3D states. Here, we sought to characterize the 3D state of the X chromosome in naïve and primed human pluripotent stem cells (hPSCs). Using chromatin tracing, we analyzed X chromosome folding conformations in these cells with megabase genomic resolution. X chromosomes in female naïve hPSCs exhibit folding conformations similar to the active X chromosome (Xa) and the inactive X chromosome (Xi) in somatic cells. However, naïve X chromosomes do not exhibit the chromatin compaction typically associated with these somatic X chromosome states. In H7 naïve human embryonic stem cells, XIST accumulation observed on damaged X chromosomes demonstrates the potential for naïve hPSCs to activate XCI-related mechanisms. Overall, our findings provide insight into the X chromosome status of naïve hPSCs with a single-chromosome resolution and are critical in understanding the unique epigenetic regulation in early embryonic cells.
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Affiliation(s)
- Benjamin Patterson
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Bing Yang
- Department of Genetics, and Department of Cell Biology, Yale School of Medicine, New Haven, CT 06520, USA
| | - Yoshiaki Tanaka
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Kun-Yong Kim
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Bilal Cakir
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Yangfei Xiang
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Jonghun Kim
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
| | - Siyuan Wang
- Department of Genetics, and Department of Cell Biology, Yale School of Medicine, New Haven, CT 06520, USA
| | - In-Hyun Park
- Department of Genetics, Yale Stem Cell Center, Yale School of Medicine, New Haven, CT 06520, USA
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15
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Abstract
In animals, the sequences for controlling gene expression do not concentrate just at the transcription start site of genes, but are frequently thousands to millions of base pairs distal to it. The interaction of these sequences with one another and their transcription start sites is regulated by factors that shape the three-dimensional (3D) organization of the genome within the nucleus. Over the past decade, indirect tools exploiting high-throughput DNA sequencing have helped to map this 3D organization, have identified multiple key regulators of its structure and, in the process, have substantially reshaped our view of how 3D genome architecture regulates transcription. Now, new tools for high-throughput super-resolution imaging of chromatin have directly visualized the 3D chromatin organization, settling some debates left unresolved by earlier indirect methods, challenging some earlier models of regulatory specificity and creating hypotheses about the role of chromatin structure in transcriptional regulation.
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16
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Maltz E, Wollman R. Quantifying the phenotypic information in mRNA abundance. Mol Syst Biol 2022; 18:e11001. [PMID: 35965452 PMCID: PMC9376724 DOI: 10.15252/msb.202211001] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 07/12/2022] [Accepted: 07/14/2022] [Indexed: 11/09/2022] Open
Abstract
Quantifying the dependency between mRNA abundance and downstream cellular phenotypes is a fundamental open problem in biology. Advances in multimodal single-cell measurement technologies provide an opportunity to apply new computational frameworks to dissect the contribution of individual genes and gene combinations to a given phenotype. Using an information theory approach, we analyzed multimodal data of the expression of 83 genes in the Ca2+ signaling network and the dynamic Ca2+ response in the same cell. We found that the overall expression levels of these 83 genes explain approximately 60% of Ca2+ signal entropy. The average contribution of each single gene was 17%, revealing a large degree of redundancy between genes. Using different heuristics, we estimated the dependency between the size of a gene set and its information content, revealing that on average, a set of 53 genes contains 54% of the information about Ca2+ signaling. Our results provide the first direct quantification of information content about complex cellular phenotype that exists in mRNA abundance measurements.
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Affiliation(s)
- Evan Maltz
- Department of Chemistry and BiochemistryUCLALos AngelesCAUSA
- Institute of Quantitative and Computational BioscienceUCLALos AngelesCAUSA
| | - Roy Wollman
- Department of Chemistry and BiochemistryUCLALos AngelesCAUSA
- Institute of Quantitative and Computational BioscienceUCLALos AngelesCAUSA
- Department of Integrative Biology and PhysiologyUCLALos AngelesCAUSA
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17
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The era of 3D and spatial genomics. Trends Genet 2022; 38:1062-1075. [PMID: 35680466 DOI: 10.1016/j.tig.2022.05.010] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 05/10/2022] [Accepted: 05/11/2022] [Indexed: 12/28/2022]
Abstract
Over a decade ago the advent of high-throughput chromosome conformation capture (Hi-C) sparked a new era of 3D genomics. Since then the number of methods for mapping the 3D genome has flourished, enabling an ever-increasing understanding of how DNA is packaged in the nucleus and how the spatiotemporal organization of the genome orchestrates its vital functions. More recently, the next generation of spatial genomics technologies has begun to reveal how genome sequence and 3D genome organization vary between cells in their tissue context. We summarize how the toolkit for charting genome topology has evolved over the past decade and discuss how new technological developments are advancing the field of 3D and spatial genomics.
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18
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Cheng Y, Liu M, Hu M, Wang S. TAD-like single-cell domain structures exist on both active and inactive X chromosomes and persist under epigenetic perturbations. Genome Biol 2021; 22:309. [PMID: 34749781 PMCID: PMC8574027 DOI: 10.1186/s13059-021-02523-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 10/22/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Topologically associating domains (TADs) are important building blocks of three-dimensional genome architectures. The formation of TADs has been shown to depend on cohesin in a loop-extrusion mechanism. Recently, advances in an image-based spatial genomics technique known as chromatin tracing lead to the discovery of cohesin-independent TAD-like structures, also known as single-cell domains, which are highly variant self-interacting chromatin domains with boundaries that occasionally overlap with TAD boundaries but tend to differ among single cells and among single chromosome copies. Recent computational modeling studies suggest that epigenetic interactions may underlie the formation of the single-cell domains. RESULTS Here we use chromatin tracing to visualize in female human cells the fine-scale chromatin folding of inactive and active X chromosomes, which are known to have distinct global epigenetic landscapes and distinct population-averaged TAD profiles, with inactive X chromosomes largely devoid of TADs and cohesin. We show that both inactive and active X chromosomes possess highly variant single-cell domains across the same genomic region despite the fact that only active X chromosomes show clear TAD structures at the population level. These X chromosome single-cell domains exist in distinct cell lines. Perturbations of major epigenetic components and transcription mostly do not affect the frequency or strength of the single-cell domains. Increased chromatin compaction of inactive X chromosomes occurs at a length scale above that of the single-cell domains. CONCLUSIONS In sum, this study suggests that single-cell domains are genome architecture building blocks independent of the tested major epigenetic components.
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Affiliation(s)
- Yubao Cheng
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT 06510 USA
| | - Miao Liu
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT 06510 USA
| | - Mengwei Hu
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT 06510 USA
| | - Siyuan Wang
- Department of Genetics, Yale School of Medicine, Yale University, New Haven, CT 06510 USA
- Department of Cell Biology, Yale School of Medicine, 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
- Biochemistry, Quantitative Biology, Biophysics and Structural Biology Program, Yale University, New Haven, CT 06510 USA
- M.D.-Ph.D. 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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