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Pavlu S, Nikumbh S, Kovacik M, An T, Lenhard B, Simkova H, Navratilova P. Core promoterome of barley embryo. Comput Struct Biotechnol J 2024; 23:264-277. [PMID: 38173877 PMCID: PMC10762323 DOI: 10.1016/j.csbj.2023.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 12/01/2023] [Accepted: 12/02/2023] [Indexed: 01/05/2024] Open
Abstract
Precise localization and dissection of gene promoters are key to understanding transcriptional gene regulation and to successful bioengineering applications. The core RNA polymerase II initiation machinery is highly conserved among eukaryotes, leading to a general expectation of equivalent underlying mechanisms. Still, less is known about promoters in the plant kingdom. In this study, we employed cap analysis of gene expression (CAGE) at three embryonic developmental stages in barley to accurately map, annotate, and quantify transcription initiation events. Unsupervised discovery of de novo sequence clusters grouped promoters based on characteristic initiator and position-specific core-promoter motifs. This grouping was complemented by the annotation of transcription factor binding site (TFBS) motifs. Integration with genome-wide epigenomic data sets and gene ontology (GO) enrichment analysis further delineated the chromatin environments and functional roles of genes associated with distinct promoter categories. The TATA-box presence governs all features explored, supporting the general model of two separate genomic regulatory environments. We describe the extent and implications of alternative transcription initiation events, including those that are specific to developmental stages, which can affect the protein sequence or the presence of regions that regulate translation. The generated promoterome dataset provides a valuable genomic resource for enhancing the functional annotation of the barley genome. It also offers insights into the transcriptional regulation of individual genes and presents opportunities for the informed manipulation of promoter architecture, with the aim of enhancing traits of agronomic importance.
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Affiliation(s)
- Simon Pavlu
- Institute of Experimental Botany of the Czech Academy of Sciences, Slechtitelu 31, 77900 Olomouc, Czech Republic
- Department of Cell Biology and Genetics, Faculty of Science, Palacky University, Slechtitelu 27, 78371 Olomouc, Czech Republic
| | - Sarvesh Nikumbh
- Merck Sharp & Dohme (UK) Limited, 120 Moorgate, London EC2M 6UR, UK
| | - Martin Kovacik
- Institute of Experimental Botany of the Czech Academy of Sciences, Slechtitelu 31, 77900 Olomouc, Czech Republic
- Department of Cell Biology and Genetics, Faculty of Science, Palacky University, Slechtitelu 27, 78371 Olomouc, Czech Republic
| | - Tadaichi An
- DNAFORM Precision Gene Technologies, 230–0046 Yokohama, Kanagawa, Japan
| | - Boris Lenhard
- Computational Regulatory Genomics, MRC London Institute of Medical Sciences, London, UK
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, London, UK
| | - Hana Simkova
- Institute of Experimental Botany of the Czech Academy of Sciences, Slechtitelu 31, 77900 Olomouc, Czech Republic
| | - Pavla Navratilova
- Institute of Experimental Botany of the Czech Academy of Sciences, Slechtitelu 31, 77900 Olomouc, Czech Republic
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2
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Bell CC, Balic JJ, Talarmain L, Gillespie A, Scolamiero L, Lam EYN, Ang CS, Faulkner GJ, Gilan O, Dawson MA. Comparative cofactor screens show the influence of transactivation domains and core promoters on the mechanisms of transcription. Nat Genet 2024:10.1038/s41588-024-01749-z. [PMID: 38769457 DOI: 10.1038/s41588-024-01749-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 04/09/2024] [Indexed: 05/22/2024]
Abstract
Eukaryotic transcription factors (TFs) activate gene expression by recruiting cofactors to promoters. However, the relationships between TFs, promoters and their associated cofactors remain poorly understood. Here we combine GAL4-transactivation assays with comparative CRISPR-Cas9 screens to identify the cofactors used by nine different TFs and core promoters in human cells. Using this dataset, we associate TFs with cofactors, classify cofactors as ubiquitous or specific and discover transcriptional co-dependencies. Through a reductionistic, comparative approach, we demonstrate that TFs do not display discrete mechanisms of activation. Instead, each TF depends on a unique combination of cofactors, which influences distinct steps in transcription. By contrast, the influence of core promoters appears relatively discrete. Different promoter classes are constrained by either initiation or pause-release, which influences their dynamic range and compatibility with cofactors. Overall, our comparative cofactor screens characterize the interplay between TFs, cofactors and core promoters, identifying general principles by which they influence transcription.
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Affiliation(s)
- Charles C Bell
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia.
- Mater Research Institute, University of Queensland, TRI Building, Woolloongabba, Queensland, Australia.
| | - Jesse J Balic
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Laure Talarmain
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Andrea Gillespie
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Laura Scolamiero
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia
| | - Enid Y N Lam
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Ching-Seng Ang
- Bio21 Mass Spectrometry and Proteomics Facility, The University of Melbourne, Parkville, Victoria, Australia
| | - Geoffrey J Faulkner
- Mater Research Institute, University of Queensland, TRI Building, Woolloongabba, Queensland, Australia
- Queensland Brain Institute, University of Queensland, Brisbane, Queensland, Australia
| | - Omer Gilan
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
- Australian Centre for Blood Diseases, Monash University, Melbourne, Victoria, Australia
| | - Mark A Dawson
- Cancer Research Division, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
- Sir Peter MacCallum Department of Oncology, University of Melbourne, Melbourne, Victoria, Australia.
- Department of Haematology, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia.
- Centre for Cancer Research, University of Melbourne, Melbourne, Victoria, Australia.
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3
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Wu C, Huang J. Enhancer selectivity across cell types delineates three functionally distinct enhancer-promoter regulation patterns. BMC Genomics 2024; 25:483. [PMID: 38750461 PMCID: PMC11097474 DOI: 10.1186/s12864-024-10408-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2024] [Accepted: 05/13/2024] [Indexed: 05/18/2024] Open
Abstract
BACKGROUND Multiple enhancers co-regulating the same gene is prevalent and plays a crucial role during development and disease. However, how multiple enhancers coordinate the same gene expression across various cell types remains largely unexplored at genome scale. RESULTS We develop a computational approach that enables the quantitative assessment of enhancer specificity and selectivity across diverse cell types, leveraging enhancer-promoter (E-P) interactions data. We observe two well-known gene regulation patterns controlled by enhancer clusters, which regulate the same gene either in a limited number of cell types (Specific pattern, Spe) or in the majority of cell types (Conserved pattern, Con), both of which are enriched for super-enhancers (SEs). We identify a previously overlooked pattern (Variable pattern, Var) that multiple enhancers link to the same gene, but rarely coexist in the same cell type. These three patterns control the genes associating with distinct biological function and exhibit unique epigenetic features. Specifically, we discover a subset of Var patterns contains Shared enhancers with stable enhancer-promoter interactions in the majority of cell types, which might contribute to maintaining gene expression by recruiting abundant CTCF. CONCLUSIONS Together, our findings reveal three distinct E-P regulation patterns across different cell types, providing insights into deciphering the complexity of gene transcriptional regulation.
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Affiliation(s)
- Chengyi Wu
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, 361102, Fujian, China
| | - Jialiang Huang
- State Key Laboratory of Cellular Stress Biology, School of Life Sciences, Faculty of Medicine and Life Sciences, Xiamen University, Xiamen, 361102, Fujian, China.
- National Institute for Data Science in Health and Medicine, Xiamen University, Xiamen, 361102, Fujian, China.
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4
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Ordoñez R, Zhang W, Ellis G, Zhu Y, Ashe HJ, Ribeiro-Dos-Santos AM, Brosh R, Huang E, Hogan MS, Boeke JD, Maurano MT. Genomic context sensitizes regulatory elements to genetic disruption. Mol Cell 2024; 84:1842-1854.e7. [PMID: 38759624 PMCID: PMC11104518 DOI: 10.1016/j.molcel.2024.04.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 03/11/2024] [Accepted: 04/18/2024] [Indexed: 05/19/2024]
Abstract
Genomic context critically modulates regulatory function but is difficult to manipulate systematically. The murine insulin-like growth factor 2 (Igf2)/H19 locus is a paradigmatic model of enhancer selectivity, whereby CTCF occupancy at an imprinting control region directs downstream enhancers to activate either H19 or Igf2. We used synthetic regulatory genomics to repeatedly replace the native locus with 157-kb payloads, and we systematically dissected its architecture. Enhancer deletion and ectopic delivery revealed previously uncharacterized long-range regulatory dependencies at the native locus. Exchanging the H19 enhancer cluster with the Sox2 locus control region (LCR) showed that the H19 enhancers relied on their native surroundings while the Sox2 LCR functioned autonomously. Analysis of regulatory DNA actuation across cell types revealed that these enhancer clusters typify broader classes of context sensitivity genome wide. These results show that unexpected dependencies influence even well-studied loci, and our approach permits large-scale manipulation of complete loci to investigate the relationship between regulatory architecture and function.
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Affiliation(s)
- Raquel Ordoñez
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Weimin Zhang
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Gwen Ellis
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Yinan Zhu
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Hannah J Ashe
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | | | - Ran Brosh
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Emily Huang
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Megan S Hogan
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Jef D Boeke
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA; Department of Biochemistry Molecular Pharmacology, NYU School of Medicine, New York, NY 10016, USA; Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY 11201, USA
| | - Matthew T Maurano
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA; Department of Pathology, NYU School of Medicine, New York, NY 10016, USA.
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5
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Siraj L, Castro RI, Dewey H, Kales S, Nguyen TTL, Kanai M, Berenzy D, Mouri K, Wang QS, McCaw ZR, Gosai SJ, Aguet F, Cui R, Vockley CM, Lareau CA, Okada Y, Gusev A, Jones TR, Lander ES, Sabeti PC, Finucane HK, Reilly SK, Ulirsch JC, Tewhey R. Functional dissection of complex and molecular trait variants at single nucleotide resolution. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.05.592437. [PMID: 38766054 PMCID: PMC11100724 DOI: 10.1101/2024.05.05.592437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Identifying the causal variants and mechanisms that drive complex traits and diseases remains a core problem in human genetics. The majority of these variants have individually weak effects and lie in non-coding gene-regulatory elements where we lack a complete understanding of how single nucleotide alterations modulate transcriptional processes to affect human phenotypes. To address this, we measured the activity of 221,412 trait-associated variants that had been statistically fine-mapped using a Massively Parallel Reporter Assay (MPRA) in 5 diverse cell-types. We show that MPRA is able to discriminate between likely causal variants and controls, identifying 12,025 regulatory variants with high precision. Although the effects of these variants largely agree with orthogonal measures of function, only 69% can plausibly be explained by the disruption of a known transcription factor (TF) binding motif. We dissect the mechanisms of 136 variants using saturation mutagenesis and assign impacted TFs for 91% of variants without a clear canonical mechanism. Finally, we provide evidence that epistasis is prevalent for variants in close proximity and identify multiple functional variants on the same haplotype at a small, but important, subset of trait-associated loci. Overall, our study provides a systematic functional characterization of likely causal common variants underlying complex and molecular human traits, enabling new insights into the regulatory grammar underlying disease risk.
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Affiliation(s)
- Layla Siraj
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Program in Biophysics, Harvard Graduate School of Arts and Sciences, Boston, MA, USA
- Harvard-Massachusetts Institute of Technology MD/PhD Program, Harvard Medical School, Boston, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | | | | | | | | | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA USA
- Center for Computational and Integrative Biology, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Qingbo S. Wang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
| | | | - Sager J. Gosai
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - François Aguet
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA
| | - Ran Cui
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Caleb A. Lareau
- Program in Computational and Systems Biology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Genome Informatics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
| | - Alexander Gusev
- Harvard Medical School and Dana-Farber Cancer Institute, Boston, MA, USA
| | - Thouis R. Jones
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Eric S. Lander
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Biology, MIT, Cambridge, MA, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Pardis C. Sabeti
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Hilary K. Finucane
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA USA
| | - Steven K. Reilly
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
| | - Jacob C. Ulirsch
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA
- Illumina Artificial Intelligence Laboratory, Illumina, San Diego, CA, USA
| | - Ryan Tewhey
- The Jackson Laboratory, Bar Harbor, ME, USA
- Graduate School of Biomedical Sciences and Engineering, University of Maine, Orono, ME, USA
- Graduate School of Biomedical Sciences, Tufts University School of Medicine, Boston, MA, USA
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6
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Park S, Kim M, Lee JW. Optimizing Nucleic Acid Delivery Systems through Barcode Technology. ACS Synth Biol 2024; 13:1006-1018. [PMID: 38526308 DOI: 10.1021/acssynbio.3c00602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/26/2024]
Abstract
Conventional biological experiments often focus on in vitro assays because of the inherent limitations when handling multiple variables in vivo, including labor-intensive and time-consuming procedures. Often only a subset of samples demonstrating significant efficacy in the in vitro assays can be evaluated in vivo. Nonetheless, because of the low correlation between the in vitro and in vivo tests, evaluation of the variables under examination in vivo and not solely in vitro is critical. An emerging approach to achieve high-throughput in vivo tests involves using a barcode system consisting of various nucleotide combinations. Unique barcodes for each variant enable the simultaneous testing of multiple entities, eliminating the need for separate individual tests. Subsequently, to identify crucial parameters, samples were collected and analyzed using barcode sequencing. This review explores the development of barcode design and its applications, including the evaluation of nucleic acid delivery systems and the optimization of gene expression in vivo.
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Affiliation(s)
- Soan Park
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 CheongamRo, Gyeongbuk, 37673 NamGu, Pohang, Republic of Korea
| | - Mibang Kim
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 CheongamRo, Gyeongbuk, 37673 NamGu, Pohang, Republic of Korea
| | - Jeong Wook Lee
- Department of Chemical Engineering, Pohang University of Science and Technology, 77 CheongamRo, Gyeongbuk, 37673 NamGu, Pohang, Republic of Korea
- School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology, 77 CheongamRo, Gyeongbuk, 37673 NamGu, Pohang, Republic of Korea
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7
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Bell CG. Epigenomic insights into common human disease pathology. Cell Mol Life Sci 2024; 81:178. [PMID: 38602535 PMCID: PMC11008083 DOI: 10.1007/s00018-024-05206-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 03/11/2024] [Accepted: 03/13/2024] [Indexed: 04/12/2024]
Abstract
The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.
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Affiliation(s)
- Christopher G Bell
- William Harvey Research Institute, Barts & The London Faculty of Medicine, Queen Mary University of London, Charterhouse Square, London, EC1M 6BQ, UK.
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8
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Chen Z, Snetkova V, Bower G, Jacinto S, Clock B, Dizehchi A, Barozzi I, Mannion BJ, Alcaina-Caro A, Lopez-Rios J, Dickel DE, Visel A, Pennacchio LA, Kvon EZ. Increased enhancer-promoter interactions during developmental enhancer activation in mammals. Nat Genet 2024; 56:675-685. [PMID: 38509385 DOI: 10.1038/s41588-024-01681-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 02/06/2024] [Indexed: 03/22/2024]
Abstract
Remote enhancers are thought to interact with their target promoters via physical proximity, yet the importance of this proximity for enhancer function remains unclear. Here we investigate the three-dimensional (3D) conformation of enhancers during mammalian development by generating high-resolution tissue-resolved contact maps for nearly a thousand enhancers with characterized in vivo activities in ten murine embryonic tissues. Sixty-one percent of developmental enhancers bypass their neighboring genes, which are often marked by promoter CpG methylation. The majority of enhancers display tissue-specific 3D conformations, and both enhancer-promoter and enhancer-enhancer interactions are moderately but consistently increased upon enhancer activation in vivo. Less than 14% of enhancer-promoter interactions form stably across tissues; however, these invariant interactions form in the absence of the enhancer and are likely mediated by adjacent CTCF binding. Our results highlight the general importance of enhancer-promoter physical proximity for developmental gene activation in mammals.
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Affiliation(s)
- Zhuoxin Chen
- Department of Developmental and Cell Biology, School of the Biological Sciences, University of California, Irvine, CA, USA
| | - Valentina Snetkova
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Grace Bower
- Department of Developmental and Cell Biology, School of the Biological Sciences, University of California, Irvine, CA, USA
| | - Sandra Jacinto
- Department of Developmental and Cell Biology, School of the Biological Sciences, University of California, Irvine, CA, USA
| | - Benjamin Clock
- Department of Developmental and Cell Biology, School of the Biological Sciences, University of California, Irvine, CA, USA
| | - Atrin Dizehchi
- Department of Developmental and Cell Biology, School of the Biological Sciences, University of California, Irvine, CA, USA
| | - Iros Barozzi
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Center for Cancer Research, Medical University of Vienna, Vienna, Austria
| | - Brandon J Mannion
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Comparative Biochemistry Program, University of California, Berkeley, CA, USA
| | - Ana Alcaina-Caro
- Centro Andaluz de Biología del Desarrollo, CSIC, Universidad Pablo de Olavide, Junta de Andalucía, Seville, Spain
| | - Javier Lopez-Rios
- Centro Andaluz de Biología del Desarrollo, CSIC, Universidad Pablo de Olavide, Junta de Andalucía, Seville, Spain
- School of Health Sciences, Universidad Loyola Andalucía, Seville, Spain
| | - Diane E Dickel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Octant, Inc, Emeryville, CA, USA
| | - Axel Visel
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- U.S. Department of Energy Joint Genome Institute, Walnut Creek, CA, USA
- School of Natural Sciences, University of California, Merced, CA, USA
| | - Len A Pennacchio
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- Comparative Biochemistry Program, University of California, Berkeley, CA, USA
- U.S. Department of Energy Joint Genome Institute, Walnut Creek, CA, USA
| | - Evgeny Z Kvon
- Department of Developmental and Cell Biology, School of the Biological Sciences, University of California, Irvine, CA, USA.
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9
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Basurto-Cayuela L, Guerrero-Martínez JA, Gómez-Marín E, Sánchez-Escabias E, Escaño-Maestre M, Ceballos-Chávez M, Reyes JC. SWI/SNF-dependent genes are defined by their chromatin landscape. Cell Rep 2024; 43:113855. [PMID: 38427563 DOI: 10.1016/j.celrep.2024.113855] [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: 03/31/2023] [Revised: 11/23/2023] [Accepted: 02/08/2024] [Indexed: 03/03/2024] Open
Abstract
SWI/SNF complexes are evolutionarily conserved, ATP-dependent chromatin remodeling machines. Here, we characterize the features of SWI/SNF-dependent genes using BRM014, an inhibitor of the ATPase activity of the complexes. We find that SWI/SNF activity is required to maintain chromatin accessibility and nucleosome occupancy for most enhancers but not for most promoters. SWI/SNF activity is needed for expression of genes with low to medium levels of expression that have promoters with (1) low chromatin accessibility, (2) low levels of active histone marks, (3) high H3K4me1/H3K4me3 ratio, (4) low nucleosomal phasing, and (5) enrichment in TATA-box motifs. These promoters are mostly occupied by the canonical Brahma-related gene 1/Brahma-associated factor (BAF) complex. These genes are surrounded by SWI/SNF-dependent enhancers and mainly encode signal transduction, developmental, and cell identity genes (with almost no housekeeping genes). Machine-learning models trained with different chromatin characteristics of promoters and their surrounding regulatory regions indicate that the chromatin landscape is a determinant for establishing SWI/SNF dependency.
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Affiliation(s)
- Laura Basurto-Cayuela
- Genome Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa-CABIMER, Consejo Superior de Investigaciones Científicas-Universidad de Sevilla-Universidad Pablo de Olavide (CSIC-USE-UPO), Av. Americo Vespucio, 41092 Seville, Spain
| | - José A Guerrero-Martínez
- Genome Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa-CABIMER, Consejo Superior de Investigaciones Científicas-Universidad de Sevilla-Universidad Pablo de Olavide (CSIC-USE-UPO), Av. Americo Vespucio, 41092 Seville, Spain
| | - Elena Gómez-Marín
- Genome Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa-CABIMER, Consejo Superior de Investigaciones Científicas-Universidad de Sevilla-Universidad Pablo de Olavide (CSIC-USE-UPO), Av. Americo Vespucio, 41092 Seville, Spain
| | - Elena Sánchez-Escabias
- Genome Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa-CABIMER, Consejo Superior de Investigaciones Científicas-Universidad de Sevilla-Universidad Pablo de Olavide (CSIC-USE-UPO), Av. Americo Vespucio, 41092 Seville, Spain
| | - María Escaño-Maestre
- Genome Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa-CABIMER, Consejo Superior de Investigaciones Científicas-Universidad de Sevilla-Universidad Pablo de Olavide (CSIC-USE-UPO), Av. Americo Vespucio, 41092 Seville, Spain
| | - María Ceballos-Chávez
- Genome Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa-CABIMER, Consejo Superior de Investigaciones Científicas-Universidad de Sevilla-Universidad Pablo de Olavide (CSIC-USE-UPO), Av. Americo Vespucio, 41092 Seville, Spain
| | - José C Reyes
- Genome Biology Department, Centro Andaluz de Biología Molecular y Medicina Regenerativa-CABIMER, Consejo Superior de Investigaciones Científicas-Universidad de Sevilla-Universidad Pablo de Olavide (CSIC-USE-UPO), Av. Americo Vespucio, 41092 Seville, Spain.
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10
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Alfonso-Gonzalez C, Hilgers V. (Alternative) transcription start sites as regulators of RNA processing. Trends Cell Biol 2024:S0962-8924(24)00033-3. [PMID: 38531762 DOI: 10.1016/j.tcb.2024.02.010] [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: 12/21/2023] [Revised: 02/20/2024] [Accepted: 02/23/2024] [Indexed: 03/28/2024]
Abstract
Alternative transcription start site usage (ATSS) is a widespread regulatory strategy that enables genes to choose between multiple genomic loci for initiating transcription. This mechanism is tightly controlled during development and is often altered in disease states. In this review, we examine the growing evidence highlighting a role for transcription start sites (TSSs) in the regulation of mRNA isoform selection during and after transcription. We discuss how the choice of transcription initiation sites influences RNA processing and the importance of this crosstalk for cell identity and organism function. We also speculate on possible mechanisms underlying the integration of transcriptional and post-transcriptional processes.
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Affiliation(s)
- Carlos Alfonso-Gonzalez
- Max Planck Institute of Immunobiology and Epigenetics, 79108 Freiburg, Germany; Faculty of Biology, Albert Ludwigs University, 79104 Freiburg, Germany; International Max Planck Research School for Molecular and Cellular Biology (IMPRS- MCB), 79108 Freiburg, Germany
| | - Valérie Hilgers
- Max Planck Institute of Immunobiology and Epigenetics, 79108 Freiburg, Germany.
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11
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Toneyan S, Koo PK. Interpreting Cis-Regulatory Interactions from Large-Scale Deep Neural Networks for Genomics. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.03.547592. [PMID: 37461616 PMCID: PMC10349992 DOI: 10.1101/2023.07.03.547592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/28/2023]
Abstract
The rise of large-scale, sequence-based deep neural networks (DNNs) for predicting gene expression has introduced challenges in their evaluation and interpretation. Current evaluations align DNN predictions with experimental perturbation assays, which provides insights into the generalization capabilities within the studied loci but offers a limited perspective of what drives their predictions. Moreover, existing model explainability tools focus mainly on motif analysis, which becomes complex when interpreting longer sequences. Here we introduce CREME, an in silico perturbation toolkit that interrogates large-scale DNNs to uncover rules of gene regulation that it learns. Using CREME, we investigate Enformer, a prominent DNN in gene expression prediction, revealing cis-regulatory elements (CREs) that directly enhance or silence target genes. We explore the intricate complexity of higher-order CRE interactions, the relationship between CRE distance from transcription start sites on gene expression, as well as the biochemical features of enhancers and silencers learned by Enformer. Moreover, we demonstrate the flexibility of CREME to efficiently uncover a higher-resolution view of functional sequence elements within CREs. This work demonstrates how CREME can be employed to translate the powerful predictions of large-scale DNNs to study open questions in gene regulation.
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12
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Ordoñez R, Zhang W, Ellis G, Zhu Y, Ashe HJ, Ribeiro-dos-Santos AM, Brosh R, Huang E, Hogan MS, Boeke JD, Maurano MT. Genomic context sensitizes regulatory elements to genetic disruption. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.07.02.547201. [PMID: 37781588 PMCID: PMC10541140 DOI: 10.1101/2023.07.02.547201] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/03/2023]
Abstract
Enhancer function is frequently investigated piecemeal using truncated reporter assays or single deletion analysis. Thus it remains unclear to what extent enhancer function at native loci relies on surrounding genomic context. Using the Big-IN technology for targeted integration of large DNAs, we analyzed the regulatory architecture of the murine Igf2/H19 locus, a paradigmatic model of enhancer selectivity. We assembled payloads containing a 157-kb functional Igf2/H19 locus and engineered mutations to genetically direct CTCF occupancy at the imprinting control region (ICR) that switches the target gene of the H19 enhancer cluster. Contrasting activity of payloads delivered at the endogenous Igf2/H19 locus or ectopically at Hprt revealed that the Igf2/H19 locus includes additional, previously unknown long-range regulatory elements. Exchanging components of the Igf2/H19 locus with the well-studied Sox2 locus showed that the H19 enhancer cluster functioned poorly out of context, and required its native surroundings to activate Sox2 expression. Conversely, the Sox2 locus control region (LCR) could activate both Igf2 and H19 outside its native context, but its activity was only partially modulated by CTCF occupancy at the ICR. Analysis of regulatory DNA actuation across different cell types revealed that, while the H19 enhancers are tightly coordinated within their native locus, the Sox2 LCR acts more independently. We show that these enhancer clusters typify broader classes of loci genome-wide. Our results show that unexpected dependencies may influence even the most studied functional elements, and our synthetic regulatory genomics approach permits large-scale manipulation of complete loci to investigate the relationship between locus architecture and function.
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Affiliation(s)
- Raquel Ordoñez
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- These authors contributed equally
| | - Weimin Zhang
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- These authors contributed equally
| | - Gwen Ellis
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- Present address: Department of Biology, University of Vermont, Burlington, VT 05405, USA
| | - Yinan Zhu
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Hannah J. Ashe
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- Present address: School of Medicine, University of Maryland, Baltimore, MD 21201, USA
| | | | - Ran Brosh
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Emily Huang
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- Present address: Highmark Health, Pittsburgh, PA 15222, USA
| | - Megan S. Hogan
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- Present address: Neochromosome Inc., Long Island City, NY 11101, USA
| | - Jef D. Boeke
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- Department of Biochemistry Molecular Pharmacology, NYU School of Medicine, New York, NY 10016, USA
- Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY 11201, USA
| | - Matthew T. Maurano
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
- Department of Pathology, NYU School of Medicine, New York, NY 10016, USA
- Lead contact
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13
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Yang JH, Hansen AS. Enhancer selectivity in space and time: from enhancer-promoter interactions to promoter activation. Nat Rev Mol Cell Biol 2024:10.1038/s41580-024-00710-6. [PMID: 38413840 DOI: 10.1038/s41580-024-00710-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/30/2024] [Indexed: 02/29/2024]
Abstract
The primary regulators of metazoan gene expression are enhancers, originally functionally defined as DNA sequences that can activate transcription at promoters in an orientation-independent and distance-independent manner. Despite being crucial for gene regulation in animals, what mechanisms underlie enhancer selectivity for promoters, and more fundamentally, how enhancers interact with promoters and activate transcription, remain poorly understood. In this Review, we first discuss current models of enhancer-promoter interactions in space and time and how enhancers affect transcription activation. Next, we discuss different mechanisms that mediate enhancer selectivity, including repression, biochemical compatibility and regulation of 3D genome structure. Through 3D polymer simulations, we illustrate how the ability of 3D genome folding mechanisms to mediate enhancer selectivity strongly varies for different enhancer-promoter interaction mechanisms. Finally, we discuss how recent technical advances may provide new insights into mechanisms of enhancer-promoter interactions and how technical biases in methods such as Hi-C and Micro-C and imaging techniques may affect their interpretation.
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Affiliation(s)
- Jin H Yang
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Koch Institute for Integrative Cancer Research, Cambridge, MA, USA
| | - Anders S Hansen
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Koch Institute for Integrative Cancer Research, Cambridge, MA, USA.
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14
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Kawasaki K, Fukaya T. Regulatory landscape of enhancer-mediated transcriptional activation. Trends Cell Biol 2024:S0962-8924(24)00020-5. [PMID: 38355349 DOI: 10.1016/j.tcb.2024.01.008] [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: 12/21/2023] [Accepted: 01/22/2024] [Indexed: 02/16/2024]
Abstract
Enhancers are noncoding regulatory elements that instruct spatial and temporal specificity of gene transcription in response to a variety of intrinsic and extrinsic signals during development. Although it has long been postulated that enhancers physically interact with target promoters through the formation of stable loops, recent studies have changed this static view: sequence-specific transcription factors (TFs) and coactivators are dynamically recruited to enhancers and assemble so-called transcription hubs. Dynamic assembly of transcription hubs appears to serve as a key scaffold to integrate regulatory information encoded by surrounding genome and biophysical properties of transcription machineries. In this review, we outline emerging new models of transcriptional regulation by enhancers and discuss future perspectives.
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Affiliation(s)
- Koji Kawasaki
- Laboratory of Transcription Dynamics, Research Center for Biological Visualization, Institute for Quantitative Biosciences, The University of Tokyo, Bunkyo-ku, Tokyo 113-0032, Japan
| | - Takashi Fukaya
- Laboratory of Transcription Dynamics, Research Center for Biological Visualization, Institute for Quantitative Biosciences, The University of Tokyo, Bunkyo-ku, Tokyo 113-0032, Japan; Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Bunkyo-ku, Tokyo 113-0032, Japan.
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15
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Saha K, Nielsen GI, Nandani R, Kong L, Ye P, An W. YY1 is a transcriptional activator of mouse LINE-1 Tf subfamily. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.03.573552. [PMID: 38260579 PMCID: PMC10802269 DOI: 10.1101/2024.01.03.573552] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Long interspersed element type 1 (LINE-1, L1) is an active autonomous transposable element (TE) in the human genome. The first step of L1 replication is transcription, which is controlled by an internal RNA polymerase II promoter in the 5' untranslated region (UTR) of a full-length L1. It has been shown that transcription factor YY1 binds to a conserved sequence motif at the 5' end of the human L1 5'UTR and dictates where transcription initiates but not the level of transcription. Putative YY1-binding motifs have been predicted in the 5'UTRs of two distinct mouse L1 subfamilies, Tf and Gf. Using site-directed mutagenesis, in vitro binding, and gene knockdown assays, we experimentally tested the role of YY1 in mouse L1 transcription. Our results indicate that Tf, but not Gf subfamily, harbors functional YY1-binding sites in its 5'UTR monomers. In contrast to its role in human L1, YY1 functions as a transcriptional activator for the mouse Tf subfamily. Furthermore, YY1-binding motifs are solely responsible for the synergistic interaction between monomers, consistent with a model wherein distant monomers act as enhancers for mouse L1 transcription. The abundance of YY1-binding sites in Tf elements also raise important implications for gene regulation at the genomic level.
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Affiliation(s)
- Karabi Saha
- Department of Pharmaceutical Sciences, South Dakota State University, Brookings, SD 57007, USA
| | - Grace I. Nielsen
- Department of Pharmaceutical Sciences, South Dakota State University, Brookings, SD 57007, USA
| | - Raj Nandani
- Department of Pharmaceutical Sciences, South Dakota State University, Brookings, SD 57007, USA
| | - Lingqi Kong
- Department of Pharmaceutical Sciences, South Dakota State University, Brookings, SD 57007, USA
| | - Ping Ye
- Department of Pharmaceutical Sciences, South Dakota State University, Brookings, SD 57007, USA
| | - Wenfeng An
- Department of Pharmaceutical Sciences, South Dakota State University, Brookings, SD 57007, USA
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16
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Kondoh H. Enhancer Activation by Transcription Factors and Underlying Mechanisms. Results Probl Cell Differ 2024; 72:167-191. [PMID: 38509258 DOI: 10.1007/978-3-031-39027-2_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/22/2024]
Abstract
Enhancers are classified into two classes based on various criteria. Class I enhancers participate primarily in finely tuned cell-specific regulation, as exemplified by the neural enhancers discussed in Chap. 9 . They are activated by simultaneous binding of transcription factors (TFs) to adjacent sites in the core sequence and are marked by moderate levels of H3K27ac modification. Class II enhancers are activated by the reiterated binding of the same TFs at multiple sites and are marked by high levels of H3K27ac modification. Class II enhancers are exemplified by enhancers in the SCR downstream of the Sox2 gene, as also discussed in Chap. 9 . Both classes of enhancers activate transcription similarly with low selectivity toward the promoters.The genomic loci broadly covered by high-level H3K27ac modification were once dubbed "Super-enhancers," implying that they are densely packed enhancers with superpowers in gene regulation. However, marking with H3K27ac modification does not predict the enhancer activity of a sequence; a "Super enhancer" region includes a few ordinary Class II enhancers. Currently, the most reliable criterion for enhancer prediction is cross-species sequence conservation.The mechanism by which transcription factors find and stay on the target enhancer site remains elusive. Results from two approaches, single-molecule live imaging and kinetic analysis using FRAP, are discussed.
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Affiliation(s)
- Hisato Kondoh
- Osaka University, Suita, Osaka, Japan
- Biohistory Research Hall, Takatsuki, Osaka, Japan
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17
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Murphy D, Salataj E, Di Giammartino DC, Rodriguez-Hernaez J, Kloetgen A, Garg V, Char E, Uyehara CM, Ee LS, Lee U, Stadtfeld M, Hadjantonakis AK, Tsirigos A, Polyzos A, Apostolou E. 3D Enhancer-promoter networks provide predictive features for gene expression and coregulation in early embryonic lineages. Nat Struct Mol Biol 2024; 31:125-140. [PMID: 38053013 PMCID: PMC10897904 DOI: 10.1038/s41594-023-01130-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2022] [Accepted: 09/18/2023] [Indexed: 12/07/2023]
Abstract
Mammalian embryogenesis commences with two pivotal and binary cell fate decisions that give rise to three essential lineages: the trophectoderm, the epiblast and the primitive endoderm. Although key signaling pathways and transcription factors that control these early embryonic decisions have been identified, the non-coding regulatory elements through which transcriptional regulators enact these fates remain understudied. Here, we characterize, at a genome-wide scale, enhancer activity and 3D connectivity in embryo-derived stem cell lines that represent each of the early developmental fates. We observe extensive enhancer remodeling and fine-scale 3D chromatin rewiring among the three lineages, which strongly associate with transcriptional changes, although distinct groups of genes are irresponsive to topological changes. In each lineage, a high degree of connectivity, or 'hubness', positively correlates with levels of gene expression and enriches for cell-type specific and essential genes. Genes within 3D hubs also show a significantly stronger probability of coregulation across lineages compared to genes in linear proximity or within the same contact domains. By incorporating 3D chromatin features, we build a predictive model for transcriptional regulation (3D-HiChAT) that outperforms models using only 1D promoter or proximal variables to predict levels and cell-type specificity of gene expression. Using 3D-HiChAT, we identify, in silico, candidate functional enhancers and hubs in each cell lineage, and with CRISPRi experiments, we validate several enhancers that control gene expression in their respective lineages. Our study identifies 3D regulatory hubs associated with the earliest mammalian lineages and describes their relationship to gene expression and cell identity, providing a framework to comprehensively understand lineage-specific transcriptional behaviors.
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Affiliation(s)
- Dylan Murphy
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- Physiology, Biophysics and Systems Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, NY, USA
| | - Eralda Salataj
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Dafne Campigli Di Giammartino
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- 3D Chromatin Conformation and RNA Genomics Laboratory, Center for Human Technologies (CHT), Istituto Italiano di Tecnologia (IIT), Genova, Italy
| | - Javier Rodriguez-Hernaez
- Department of Pathology, New York University Langone Health, New York, NY, USA
- Department of Medicine, New York University Langone Health, New York, NY, USA
- Applied Bioinformatics Laboratory, New York University Langone Health, New York, NY, USA
| | - Andreas Kloetgen
- Department of Pathology, New York University Langone Health, New York, NY, USA
- Department of Medicine, New York University Langone Health, New York, NY, USA
- Applied Bioinformatics Laboratory, New York University Langone Health, New York, NY, USA
| | - Vidur Garg
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Biochemistry Cell and Molecular Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, NY, USA
| | - Erin Char
- Tri-Institutional Training Program in Computational Biology and Medicine, Weill Cornell Medical College, New York, NY, USA
| | - Christopher M Uyehara
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Ly-Sha Ee
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - UkJin Lee
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
- Biochemistry Cell and Molecular Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, NY, USA
| | - Matthias Stadtfeld
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA
| | - Anna-Katerina Hadjantonakis
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Aristotelis Tsirigos
- Department of Pathology, New York University Langone Health, New York, NY, USA.
- Department of Medicine, New York University Langone Health, New York, NY, USA.
- Applied Bioinformatics Laboratory, New York University Langone Health, New York, NY, USA.
| | - Alexander Polyzos
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
| | - Effie Apostolou
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.
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18
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Martyn GE, Montgomery MT, Jones H, Guo K, Doughty BR, Linder J, Chen Z, Cochran K, Lawrence KA, Munson G, Pampari A, Fulco CP, Kelley DR, Lander ES, Kundaje A, Engreitz JM. Rewriting regulatory DNA to dissect and reprogram gene expression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.20.572268. [PMID: 38187584 PMCID: PMC10769263 DOI: 10.1101/2023.12.20.572268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Regulatory DNA sequences within enhancers and promoters bind transcription factors to encode cell type-specific patterns of gene expression. However, the regulatory effects and programmability of such DNA sequences remain difficult to map or predict because we have lacked scalable methods to precisely edit regulatory DNA and quantify the effects in an endogenous genomic context. Here we present an approach to measure the quantitative effects of hundreds of designed DNA sequence variants on gene expression, by combining pooled CRISPR prime editing with RNA fluorescence in situ hybridization and cell sorting (Variant-FlowFISH). We apply this method to mutagenize and rewrite regulatory DNA sequences in an enhancer and the promoter of PPIF in two immune cell lines. Of 672 variant-cell type pairs, we identify 497 that affect PPIF expression. These variants appear to act through a variety of mechanisms including disruption or optimization of existing transcription factor binding sites, as well as creation of de novo sites. Disrupting a single endogenous transcription factor binding site often led to large changes in expression (up to -40% in the enhancer, and -50% in the promoter). The same variant often had different effects across cell types and states, demonstrating a highly tunable regulatory landscape. We use these data to benchmark performance of sequence-based predictive models of gene regulation, and find that certain types of variants are not accurately predicted by existing models. Finally, we computationally design 185 small sequence variants (≤10 bp) and optimize them for specific effects on expression in silico. 84% of these rationally designed edits showed the intended direction of effect, and some had dramatic effects on expression (-100% to +202%). Variant-FlowFISH thus provides a powerful tool to map the effects of variants and transcription factor binding sites on gene expression, test and improve computational models of gene regulation, and reprogram regulatory DNA.
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Affiliation(s)
- Gabriella E Martyn
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA, USA
| | - Michael T Montgomery
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA, USA
| | - Hank Jones
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA, USA
| | - Katherine Guo
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA, USA
| | - Benjamin R Doughty
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Ziwei Chen
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Kelly Cochran
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Kathryn A Lawrence
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Glen Munson
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Anusri Pampari
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Charles P Fulco
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Present Address: Sanofi, Cambridge, MA, USA
| | | | - Eric S Lander
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biology, MIT, Cambridge, MA, USA
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Jesse M Engreitz
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Science and Engineering Initiative, Stanford Children's Health, Betty Irene Moore Children's Heart Center, Stanford, CA, USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
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19
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Gschwind AR, Mualim KS, Karbalayghareh A, Sheth MU, Dey KK, Jagoda E, Nurtdinov RN, Xi W, Tan AS, Jones H, Ma XR, Yao D, Nasser J, Avsec Ž, James BT, Shamim MS, Durand NC, Rao SSP, Mahajan R, Doughty BR, Andreeva K, Ulirsch JC, Fan K, Perez EM, Nguyen TC, Kelley DR, Finucane HK, Moore JE, Weng Z, Kellis M, Bassik MC, Price AL, Beer MA, Guigó R, Stamatoyannopoulos JA, Lieberman Aiden E, Greenleaf WJ, Leslie CS, Steinmetz LM, Kundaje A, Engreitz JM. An encyclopedia of enhancer-gene regulatory interactions in the human genome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.09.563812. [PMID: 38014075 PMCID: PMC10680627 DOI: 10.1101/2023.11.09.563812] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the impact of human genetic variation on disease1-6. Here we create and evaluate a resource of >13 million enhancer-gene regulatory interactions across 352 cell types and tissues, by integrating predictive models, measurements of chromatin state and 3D contacts, and largescale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,411 elementgene pairs measured in CRISPR perturbation experiments, >30,000 fine-mapped eQTLs, and 569 fine-mapped GWAS variants linked to a likely causal gene. Using this framework, we develop a new predictive model, ENCODE-rE2G, that achieves state-of-the-art performance across multiple prediction tasks, demonstrating a strategy involving iterative perturbations and supervised machine learning to build increasingly accurate predictive models of enhancer regulation. Using the ENCODE-rE2G model, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, which reveals global properties of enhancer networks, identifies differences in the functions of genes that have more or less complex regulatory landscapes, and improves analyses to link noncoding variants to target genes and cell types for common, complex diseases. By interpreting the model, we find evidence that, beyond enhancer activity and 3D enhancer-promoter contacts, additional features guide enhancerpromoter communication including promoter class and enhancer-enhancer synergy. Altogether, these genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models, and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.
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Affiliation(s)
- Andreas R. Gschwind
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Sciences and Engineering Initiative, Betty Irene Moore Children’s Heart Center, Lucile Packard Children’s Hospital, Stanford, CA, USA
| | - Kristy S. Mualim
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Plant Biology, Carnegie Institute of Science, Stanford, CA, USA
| | - Alireza Karbalayghareh
- Computational and Systems Biology Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Maya U. Sheth
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Sciences and Engineering Initiative, Betty Irene Moore Children’s Heart Center, Lucile Packard Children’s Hospital, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Kushal K. Dey
- Computational and Systems Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Evelyn Jagoda
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ramil N. Nurtdinov
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain
| | - Wang Xi
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Anthony S. Tan
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Sciences and Engineering Initiative, Betty Irene Moore Children’s Heart Center, Lucile Packard Children’s Hospital, Stanford, CA, USA
| | - Hank Jones
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Sciences and Engineering Initiative, Betty Irene Moore Children’s Heart Center, Lucile Packard Children’s Hospital, Stanford, CA, USA
| | - X. Rosa Ma
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Sciences and Engineering Initiative, Betty Irene Moore Children’s Heart Center, Lucile Packard Children’s Hospital, Stanford, CA, USA
| | - David Yao
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Joseph Nasser
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Present Address: Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | | | - Benjamin T. James
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Muhammad S. Shamim
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA
- Department of Bioengineering, Rice University, Houston, TX, USA
- Medical Scientist Training Program, Baylor College of Medicine, Houston, Texas, USA
| | - Neva C. Durand
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA
- Department of Computer Science, Rice University, Houston, TX, USA
| | - Suhas S. P. Rao
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
- Department of Structural Biology, Stanford University, Stanford, CA, USA
| | - Ragini Mahajan
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA
- Department of Biosciences, Rice University, Houston, TX, USA
| | - Benjamin R. Doughty
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Kalina Andreeva
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Jacob C. Ulirsch
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Present Address: Artificial Intelligence Laboratory, Illumina, Inc., San Diego, CA, USA
| | - Kaili Fan
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
- Present Address: Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | | | - Tri C. Nguyen
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Sciences and Engineering Initiative, Betty Irene Moore Children’s Heart Center, Lucile Packard Children’s Hospital, Stanford, CA, USA
| | | | - Hilary K. Finucane
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jill E. Moore
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Manolis Kellis
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Michael C. Bassik
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Alkes L. Price
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Michael A. Beer
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- McKusick-Nathans Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Roderic Guigó
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain
| | - John A. Stamatoyannopoulos
- Altius Institute for Biomedical Sciences, Seattle, WA, USA
- Clinical Research Division, Fred Hutch Cancer Center, Seattle, WA, USA
| | - Erez Lieberman Aiden
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA
- Department of Computer Science, Rice University, Houston, TX, USA
| | - William J. Greenleaf
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Applied Physics, Stanford University, Stanford, CA, USA
| | | | - Lars M. Steinmetz
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Genome Technology Center, Palo Alto, CA, USA
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany
| | - Anshul Kundaje
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Jesse M. Engreitz
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
- Basic Sciences and Engineering Initiative, Betty Irene Moore Children’s Heart Center, Lucile Packard Children’s Hospital, Stanford, CA, USA
- The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
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20
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Mulet-Lazaro R, Delwel R. From Genotype to Phenotype: How Enhancers Control Gene Expression and Cell Identity in Hematopoiesis. Hemasphere 2023; 7:e969. [PMID: 37953829 PMCID: PMC10635615 DOI: 10.1097/hs9.0000000000000969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 09/11/2023] [Indexed: 11/14/2023] Open
Abstract
Blood comprises a wide array of specialized cells, all of which share the same genetic information and ultimately derive from the same precursor, the hematopoietic stem cell (HSC). This diversity of phenotypes is underpinned by unique transcriptional programs gradually acquired in the process known as hematopoiesis. Spatiotemporal regulation of gene expression depends on many factors, but critical among them are enhancers-sequences of DNA that bind transcription factors and increase transcription of genes under their control. Thus, hematopoiesis involves the activation of specific enhancer repertoires in HSCs and their progeny, driving the expression of sets of genes that collectively determine morphology and function. Disruption of this tightly regulated process can have catastrophic consequences: in hematopoietic malignancies, dysregulation of transcriptional control by enhancers leads to misexpression of oncogenes that ultimately drive transformation. This review attempts to provide a basic understanding of enhancers and their role in transcriptional regulation, with a focus on normal and malignant hematopoiesis. We present examples of enhancers controlling master regulators of hematopoiesis and discuss the main mechanisms leading to enhancer dysregulation in leukemia and lymphoma.
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Affiliation(s)
- Roger Mulet-Lazaro
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
| | - Ruud Delwel
- Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands
- Oncode Institute, Utrecht, the Netherlands
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21
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Arnold M, Stengel KR. Emerging insights into enhancer biology and function. Transcription 2023; 14:68-87. [PMID: 37312570 PMCID: PMC10353330 DOI: 10.1080/21541264.2023.2222032] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 05/30/2023] [Accepted: 06/01/2023] [Indexed: 06/15/2023] Open
Abstract
Cell type-specific gene expression is coordinated by DNA-encoded enhancers and the transcription factors (TFs) that bind to them in a sequence-specific manner. As such, these enhancers and TFs are critical mediators of normal development and altered enhancer or TF function is associated with the development of diseases such as cancer. While initially defined by their ability to activate gene transcription in reporter assays, putative enhancer elements are now frequently defined by their unique chromatin features including DNase hypersensitivity and transposase accessibility, bidirectional enhancer RNA (eRNA) transcription, CpG hypomethylation, high H3K27ac and H3K4me1, sequence-specific transcription factor binding, and co-factor recruitment. Identification of these chromatin features through sequencing-based assays has revolutionized our ability to identify enhancer elements on a genome-wide scale, and genome-wide functional assays are now capitalizing on this information to greatly expand our understanding of how enhancers function to provide spatiotemporal coordination of gene expression programs. Here, we highlight recent technological advances that are providing new insights into the molecular mechanisms by which these critical cis-regulatory elements function in gene control. We pay particular attention to advances in our understanding of enhancer transcription, enhancer-promoter syntax, 3D organization and biomolecular condensates, transcription factor and co-factor dependencies, and the development of genome-wide functional enhancer screens.
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Affiliation(s)
- Mirjam Arnold
- Department of Cell Biology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Kristy R. Stengel
- Department of Cell Biology, Albert Einstein College of Medicine, Bronx, NY, USA
- Montefiore Einstein Cancer Center, Albert Einstein College of Medicine-Montefiore Health System, Bronx, NY, USA
- Ruth L. and David S. Gottesman Institute for Stem Cell and Regenerative Medicine Research, Albert Einstein College of Medicine, Bronx, NY, USA
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22
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Tovar A, Kyono Y, Nishino K, Bose M, Varshney A, Parker SCJ, Kitzman JO. Using a modular massively parallel reporter assay to discover context-specific regulatory grammars in type 2 diabetes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.08.561391. [PMID: 37873175 PMCID: PMC10592691 DOI: 10.1101/2023.10.08.561391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Recent genome-wide association studies have established that most complex disease-associated loci are found in noncoding regions where defining their function is nontrivial. In this study, we leverage a modular massively parallel reporter assay (MPRA) to uncover sequence features linked to context-specific regulatory activity. We screened enhancer activity across a panel of 198-bp fragments spanning over 10k type 2 diabetes- and metabolic trait-associated variants in the 832/13 rat insulinoma cell line, a relevant model of pancreatic beta cells. We explored these fragments' context sensitivity by comparing their activities when placed up-or downstream of a reporter gene, and in combination with either a synthetic housekeeping promoter (SCP1) or a more biologically relevant promoter corresponding to the human insulin gene ( INS ). We identified clear effects of MPRA construct design on measured fragment enhancer activity. Specifically, a subset of fragments (n = 702/11,656) displayed positional bias, evenly distributed across up- and downstream preference. A separate set of fragments exhibited promoter bias (n = 698/11,656), mostly towards the cell-specific INS promoter (73.4%). To identify sequence features associated with promoter preference, we used Lasso regression with 562 genomic annotations and discovered that fragments with INS promoter-biased activity are enriched for HNF1 motifs. HNF1 family transcription factors are key regulators of glucose metabolism disrupted in maturity onset diabetes of the young (MODY), suggesting genetic convergence between rare coding variants that cause MODY and common T2D-associated regulatory variants. We designed a follow-up MPRA containing HNF1 motif-enriched fragments and observed several instances where deletion or mutation of HNF1 motifs disrupted the INS promoter-biased enhancer activity, specifically in the beta cell model but not in a skeletal muscle cell line, another diabetes-relevant cell type. Together, our study suggests that cell-specific regulatory activity is partially influenced by enhancer-promoter compatibility and indicates that careful attention should be paid when designing MPRA libraries to capture context-specific regulatory processes at disease-associated genetic signals.
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23
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Örd T, Örd D, Adler P, Örd T. Genome-wide census of ATF4 binding sites and functional profiling of trait-associated genetic variants overlapping ATF4 binding motifs. PLoS Genet 2023; 19:e1011014. [PMID: 37906604 PMCID: PMC10637723 DOI: 10.1371/journal.pgen.1011014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 11/10/2023] [Accepted: 10/11/2023] [Indexed: 11/02/2023] Open
Abstract
Activating Transcription Factor 4 (ATF4) is an important regulator of gene expression in stress responses and developmental processes in many cell types. Here, we catalogued ATF4 binding sites in the human genome and identified overlaps with trait-associated genetic variants. We probed these genetic variants for allelic regulatory activity using a massively parallel reporter assay (MPRA) in HepG2 hepatoma cells exposed to tunicamycin to induce endoplasmic reticulum stress and ATF4 upregulation. The results revealed that in the majority of cases, the MPRA allelic activity of these SNPs was in agreement with the nucleotide preference seen in the ATF4 binding motif from ChIP-Seq. Luciferase and electrophoretic mobility shift assays in additional cellular models further confirmed ATF4-dependent regulatory effects for the SNPs rs532446 (GADD45A intronic; linked to hematological parameters), rs7011846 (LPL upstream; myocardial infarction), rs2718215 (diastolic blood pressure), rs281758 (psychiatric disorders) and rs6491544 (educational attainment). CRISPR-Cas9 disruption and/or deletion of the regulatory elements harboring rs532446 and rs7011846 led to the downregulation of GADD45A and LPL, respectively. Thus, these SNPs could represent examples of GWAS genetic variants that affect gene expression by altering ATF4-mediated transcriptional activation.
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Affiliation(s)
- Tiit Örd
- Institute of Genomics, University of Tartu, Tartu, Estonia
- A. I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Daima Örd
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Priit Adler
- Institute of Computer Science, University of Tartu, Tartu, Estonia
| | - Tõnis Örd
- Institute of Genomics, University of Tartu, Tartu, Estonia
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24
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Jores T, Hamm M, Cuperus JT, Queitsch C. Frontiers and techniques in plant gene regulation. CURRENT OPINION IN PLANT BIOLOGY 2023; 75:102403. [PMID: 37331209 DOI: 10.1016/j.pbi.2023.102403] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 05/12/2023] [Accepted: 05/19/2023] [Indexed: 06/20/2023]
Abstract
Understanding plant gene regulation has been a priority for generations of plant scientists. However, due to its complex nature, the regulatory code governing plant gene expression has yet to be deciphered comprehensively. Recently developed methods-often relying on next-generation sequencing technology and state-of-the-art computational approaches-have started to further our understanding of the gene regulatory logic used by plants. In this review, we discuss these methods and the insights into the regulatory code of plants that they can yield.
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Affiliation(s)
- Tobias Jores
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
| | - Morgan Hamm
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Josh T Cuperus
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
| | - Christine Queitsch
- Department of Genome Sciences, University of Washington, Seattle, WA, USA.
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25
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Reece AS, Hulse GK. Perturbation of 3D nuclear architecture, epigenomic dysregulation and aging, and cannabinoid synaptopathy reconfigures conceptualization of cannabinoid pathophysiology: part 1-aging and epigenomics. Front Psychiatry 2023; 14:1182535. [PMID: 37732074 PMCID: PMC10507876 DOI: 10.3389/fpsyt.2023.1182535] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 08/07/2023] [Indexed: 09/22/2023] Open
Abstract
Much recent attention has been directed toward the spatial organization of the cell nucleus and the manner in which three-dimensional topologically associated domains and transcription factories are epigenetically coordinated to precisely bring enhancers into close proximity with promoters to control gene expression. Twenty lines of evidence robustly implicate cannabinoid exposure with accelerated organismal and cellular aging. Aging has recently been shown to be caused by increased DNA breaks. These breaks rearrange and maldistribute the epigenomic machinery to weaken and reverse cellular differentiation, cause genome-wide DNA demethylation, reduce gene transcription, and lead to the inhibition of developmental pathways, which contribute to the progressive loss of function and chronic immune stimulation that characterize cellular aging. Both cell lineage-defining superenhancers and the superanchors that control them are weakened. Cannabis exposure phenocopies the elements of this process and reproduces DNA and chromatin breakages, reduces the DNA, RNA protein and histone synthesis, interferes with the epigenomic machinery controlling both DNA and histone modifications, induces general DNA hypomethylation, and epigenomically disrupts both the critical boundary elements and the cohesin motors that create chromatin loops. This pattern of widespread interference with developmental programs and relative cellular dedifferentiation (which is pro-oncogenic) is reinforced by cannabinoid impairment of intermediate metabolism (which locks in the stem cell-like hyper-replicative state) and cannabinoid immune stimulation (which perpetuates and increases aging and senescence programs, DNA damage, DNA hypomethylation, genomic instability, and oncogenesis), which together account for the diverse pattern of teratologic and carcinogenic outcomes reported in recent large epidemiologic studies in Europe, the USA, and elsewhere. It also accounts for the prominent aging phenotype observed clinically in long-term cannabis use disorder and the 20 characteristics of aging that it manifests. Increasing daily cannabis use, increasing use in pregnancy, and exponential dose-response effects heighten the epidemiologic and clinical urgency of these findings. Together, these findings indicate that cannabinoid genotoxicity and epigenotoxicity are prominent features of cannabis dependence and strongly indicate coordinated multiomics investigations of cannabinoid genome-epigenome-transcriptome-metabolome, chromatin conformation, and 3D nuclear architecture. Considering the well-established exponential dose-response relationships, the diversity of cannabinoids, and the multigenerational nature of the implications, great caution is warranted in community cannabinoid penetration.
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Affiliation(s)
- Albert Stuart Reece
- Division of Psychiatry, University of Western Australia, Crawley, WA, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Gary Kenneth Hulse
- Division of Psychiatry, University of Western Australia, Crawley, WA, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
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26
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Kleinschmidt H, Xu C, Bai L. Using Synthetic DNA Libraries to Investigate Chromatin and Gene Regulation. Chromosoma 2023; 132:167-189. [PMID: 37184694 PMCID: PMC10542970 DOI: 10.1007/s00412-023-00796-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Revised: 04/25/2023] [Accepted: 04/26/2023] [Indexed: 05/16/2023]
Abstract
Despite the recent explosion in genome-wide studies in chromatin and gene regulation, we are still far from extracting a set of genetic rules that can predict the function of the regulatory genome. One major reason for this deficiency is that gene regulation is a multi-layered process that involves an enormous variable space, which cannot be fully explored using native genomes. This problem can be partially solved by introducing synthetic DNA libraries into cells, a method that can test the regulatory roles of thousands to millions of sequences with limited variables. Here, we review recent applications of this method to study transcription factor (TF) binding, nucleosome positioning, and transcriptional activity. We discuss the design principles, experimental procedures, and major findings from these studies and compare the pros and cons of different approaches.
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Affiliation(s)
- Holly Kleinschmidt
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, 16802, USA
- Center for Eukaryotic Gene Regulation, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Cheng Xu
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, 16802, USA
- Center for Eukaryotic Gene Regulation, The Pennsylvania State University, University Park, PA, 16802, USA
| | - Lu Bai
- Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA, 16802, USA.
- Center for Eukaryotic Gene Regulation, The Pennsylvania State University, University Park, PA, 16802, USA.
- Department of Physics, The Pennsylvania State University, University Park, PA, 16802, USA.
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27
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Ober-Reynolds B, Wang C, Ko JM, Rios EJ, Aasi SZ, Davis MM, Oro AE, Greenleaf WJ. Integrated single-cell chromatin and transcriptomic analyses of human scalp identify gene-regulatory programs and critical cell types for hair and skin diseases. Nat Genet 2023; 55:1288-1300. [PMID: 37500727 DOI: 10.1038/s41588-023-01445-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 06/17/2023] [Indexed: 07/29/2023]
Abstract
Genome-wide association studies have identified many loci associated with hair and skin disease, but identification of causal variants requires deciphering of gene-regulatory networks in relevant cell types. We generated matched single-cell chromatin profiles and transcriptomes from scalp tissue from healthy controls and patients with alopecia areata, identifying diverse cell types of the hair follicle niche. By interrogating these datasets at multiple levels of cellular resolution, we infer 50-100% more enhancer-gene links than previous approaches and show that aggregate enhancer accessibility for highly regulated genes predicts expression. We use these gene-regulatory maps to prioritize cell types, genes and causal variants implicated in the pathobiology of androgenetic alopecia (AGA), eczema and other complex traits. AGA genome-wide association studies signals are enriched in dermal papilla regulatory regions, supporting the role of these cells as drivers of AGA pathogenesis. Finally, we train machine learning models to nominate single-nucleotide polymorphisms that affect gene expression through disruption of transcription factor binding, predicting candidate functional single-nucleotide polymorphism for AGA and eczema.
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Affiliation(s)
| | - Chen Wang
- Department of Dermatology, School of Medicine, Stanford University, Stanford, CA, USA
- Division of Dermatology, Department of Medicine, Santa Clara Valley Medical Center, San Jose, CA, USA
- Institute of Immunity, Transplantation and Infection, School of Medicine, Stanford University, Stanford, CA, USA
| | - Justin M Ko
- Department of Dermatology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Eon J Rios
- Department of Dermatology, School of Medicine, Stanford University, Stanford, CA, USA
- Division of Dermatology, Department of Medicine, Santa Clara Valley Medical Center, San Jose, CA, USA
| | - Sumaira Z Aasi
- Department of Dermatology, School of Medicine, Stanford University, Stanford, CA, USA
| | - Mark M Davis
- Institute of Immunity, Transplantation and Infection, School of Medicine, Stanford University, Stanford, CA, USA
- Department of Microbiology and Immunology, School of Medicine, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, School of Medicine, Stanford University, Stanford, CA, USA
| | - Anthony E Oro
- Department of Dermatology, School of Medicine, Stanford University, Stanford, CA, USA
- Program in Epithelial Biology, Stanford University School of Medicine, Stanford, CA, USA
| | - William J Greenleaf
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Applied Physics, Stanford University, Stanford, CA, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, USA.
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28
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The Impact of Genomic Variation on Function (IGVF) Consortium. ARXIV 2023:arXiv:2307.13708v1. [PMID: 37547663 PMCID: PMC10402186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Our genomes influence nearly every aspect of human biology from molecular and cellular functions to phenotypes in health and disease. Human genetics studies have now associated hundreds of thousands of differences in our DNA sequence ("genomic variation") with disease risk and other phenotypes, many of which could reveal novel mechanisms of human biology and uncover the basis of genetic predispositions to diseases, thereby guiding the development of new diagnostics and therapeutics. Yet, understanding how genomic variation alters genome function to influence phenotype has proven challenging. To unlock these insights, we need a systematic and comprehensive catalog of genome function and the molecular and cellular effects of genomic variants. Toward this goal, the Impact of Genomic Variation on Function (IGVF) Consortium will combine approaches in single-cell mapping, genomic perturbations, and predictive modeling to investigate the relationships among genomic variation, genome function, and phenotypes. Through systematic comparisons and benchmarking of experimental and computational methods, we aim to create maps across hundreds of cell types and states describing how coding variants alter protein activity, how noncoding variants change the regulation of gene expression, and how both coding and noncoding variants may connect through gene regulatory and protein interaction networks. These experimental data, computational predictions, and accompanying standards and pipelines will be integrated into an open resource that will catalyze community efforts to explore genome function and the impact of genetic variation on human biology and disease across populations.
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29
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Wang D, Li H, Chandel NS, Dou Y, Yi R. MOF-mediated histone H4 Lysine 16 acetylation governs mitochondrial and ciliary functions by controlling gene promoters. Nat Commun 2023; 14:4404. [PMID: 37479688 PMCID: PMC10362062 DOI: 10.1038/s41467-023-40108-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 07/11/2023] [Indexed: 07/23/2023] Open
Abstract
Histone H4 lysine 16 acetylation (H4K16ac), governed by the histone acetyltransferase MOF, orchestrates gene expression regulation and chromatin interaction. However, the roles of MOF and H4K16ac in controlling cellular function and regulating mammalian tissue development remain unclear. Here we show that conditional deletion of Mof in the skin, but not Kansl1, causes severe defects in the self-renewal of basal epithelial progenitors, epidermal differentiation, and hair follicle growth, resulting in barrier defects and perinatal lethality. MOF-regulated genes are highly enriched for essential functions in the mitochondria and cilia. Genetic deletion of Uqcrq, an essential subunit for the electron transport chain (ETC) Complex III, in the skin, recapitulates the defects in epidermal differentiation and hair follicle growth observed in MOF knockout mouse. Together, this study reveals the requirement of MOF-mediated epigenetic mechanism for regulating mitochondrial and ciliary gene expression and underscores the important function of the MOF/ETC axis for mammalian skin development.
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Affiliation(s)
- Dongmei Wang
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Haimin Li
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Navdeep S Chandel
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Yali Dou
- Department of Medicine, University of Southern California, Los Angeles, CA, 90033, USA
| | - Rui Yi
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA.
- Robert H. Lurie Comprehensive Cancer Center, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA.
- Department of Dermatology, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA.
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30
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Murphy D, Salataj E, Di Giammartino DC, Rodriguez-Hernaez J, Kloetgen A, Garg V, Char E, Uyehara CM, Ee LS, Lee U, Stadtfeld M, Hadjantonakis AK, Tsirigos A, Polyzos A, Apostolou E. Systematic mapping and modeling of 3D enhancer-promoter interactions in early mouse embryonic lineages reveal regulatory principles that determine the levels and cell-type specificity of gene expression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.19.549714. [PMID: 37577543 PMCID: PMC10422694 DOI: 10.1101/2023.07.19.549714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Mammalian embryogenesis commences with two pivotal and binary cell fate decisions that give rise to three essential lineages, the trophectoderm (TE), the epiblast (EPI) and the primitive endoderm (PrE). Although key signaling pathways and transcription factors that control these early embryonic decisions have been identified, the non-coding regulatory elements via which transcriptional regulators enact these fates remain understudied. To address this gap, we have characterized, at a genome-wide scale, enhancer activity and 3D connectivity in embryo-derived stem cell lines that represent each of the early developmental fates. We observed extensive enhancer remodeling and fine-scale 3D chromatin rewiring among the three lineages, which strongly associate with transcriptional changes, although there are distinct groups of genes that are irresponsive to topological changes. In each lineage, a high degree of connectivity or "hubness" positively correlates with levels of gene expression and enriches for cell-type specific and essential genes. Genes within 3D hubs also show a significantly stronger probability of coregulation across lineages, compared to genes in linear proximity or within the same contact domains. By incorporating 3D chromatin features, we build a novel predictive model for transcriptional regulation (3D-HiChAT), which outperformed models that use only 1D promoter or proximal variables in predicting levels and cell-type specificity of gene expression. Using 3D-HiChAT, we performed genome-wide in silico perturbations to nominate candidate functional enhancers and hubs in each cell lineage, and with CRISPRi experiments we validated several novel enhancers that control expression of one or more genes in their respective lineages. Our study comprehensively identifies 3D regulatory hubs associated with the earliest mammalian lineages and describes their relationship to gene expression and cell identity, providing a framework to understand lineage-specific transcriptional behaviors.
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Affiliation(s)
- Dylan Murphy
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
| | - Eralda Salataj
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
| | - Dafne Campigli Di Giammartino
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
- 3D Chromatin Conformation and RNA genomics laboratory, Instituto Italiano di Tecnologia (IIT), Center for Human Technologies (CHT), Genova, Italy (current affiliation)
| | - Javier Rodriguez-Hernaez
- Department of Pathology, New York University Langone Health, New York, NY 10016, USA
- Applied Bioinformatics Laboratory, New York University Langone Health, New York, NY 10016, USA
| | - Andreas Kloetgen
- Department of Pathology, New York University Langone Health, New York, NY 10016, USA
- Applied Bioinformatics Laboratory, New York University Langone Health, New York, NY 10016, USA
| | - Vidur Garg
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Biochemistry Cell and Molecular Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, NY 10065, USA
| | - Erin Char
- Tri-Institutional Training Program in Computational Biology and Medicine, Weill Cornell Medical College, New York, 10065, New York, USA
| | - Christopher M. Uyehara
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
| | - Ly-sha Ee
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
| | - UkJin Lee
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
| | - Matthias Stadtfeld
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
| | - Anna-Katerina Hadjantonakis
- Developmental Biology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY 10065, USA; Biochemistry Cell and Molecular Biology Program, Weill Cornell Graduate School of Medical Sciences, Cornell University, New York, NY 10065, USA
| | - Aristotelis Tsirigos
- Department of Pathology, New York University Langone Health, New York, NY 10016, USA
- Applied Bioinformatics Laboratory, New York University Langone Health, New York, NY 10016, USA
| | - Alexander Polyzos
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
| | - Effie Apostolou
- Sanford I. Weill Department of Medicine, Sandra and Edward Meyer Cancer Center, Weill Cornell Medicine, New York, NY, United States
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Powell SK, Liao W, O’Shea C, Kammourh S, Ghorbani S, Rigat R, Elahi R, Deans PJM, Le DJ, Agarwal P, Seow WQ, Wang KC, Akbarian S, Brennand KJ. Schizophrenia Risk Mapping and Functional Engineering of the 3D Genome in Three Neuronal Subtypes. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.17.549339. [PMID: 37502907 PMCID: PMC10370055 DOI: 10.1101/2023.07.17.549339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Common variants associated with schizophrenia are concentrated in non-coding regulatory sequences, but their precise target genes are context-dependent and impacted by cell-type-specific three-dimensional spatial chromatin organization. Here, we map long-range chromosomal conformations in isogenic human dopaminergic, GABAergic, and glutamatergic neurons to track developmentally programmed shifts in the regulatory activity of schizophrenia risk loci. Massive repressive compartmentalization, concomitant with the emergence of hundreds of neuron-specific multi-valent chromatin architectural stripes, occurs during neuronal differentiation, with genes interconnected to genetic risk loci through these long-range chromatin structures differing in their biological roles from genes more proximal to sequences conferring heritable risk. Chemically induced CRISPR-guided chromosomal loop-engineering for the proximal risk gene SNAP91 and distal risk gene BHLHE22 profoundly alters synaptic development and functional activity. Our findings highlight the large-scale cell-type-specific reorganization of chromosomal conformations at schizophrenia risk loci during neurodevelopment and establish a causal link between risk-associated gene-regulatory loop structures and neuronal function.
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Affiliation(s)
- Samuel K. Powell
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Graduate School of Biomedical Science, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Will Liao
- New York Genome Center, New York, NY, 10029
| | - Callan O’Shea
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Sarah Kammourh
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Sadaf Ghorbani
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Raymond Rigat
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Rahat Elahi
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - PJ Michael Deans
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
| | - Derek J. Le
- Department of Dermatology, Program in Epithelial Biology, Stanford University School of Medicine, Stanford, 94305, California, USA
- Cancer Biology Program, Stanford University School of Medicine, Stanford, California, 94305, USA
| | - Poonam Agarwal
- Department of Dermatology, Program in Epithelial Biology, Stanford University School of Medicine, Stanford, 94305, California, USA
| | - Wei Qiang Seow
- Department of Dermatology, Program in Epithelial Biology, Stanford University School of Medicine, Stanford, 94305, California, USA
| | - Kevin C. Wang
- Department of Dermatology, Program in Epithelial Biology, Stanford University School of Medicine, Stanford, 94305, California, USA
- Cancer Biology Program, Stanford University School of Medicine, Stanford, California, 94305, USA
- Veterans Affairs Palo Alto Healthcare System, Palo Alto, California, 94304, USA
| | - Schahram Akbarian
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
| | - Kristen J. Brennand
- Pamela Sklar Division of Psychiatric Genomics, Department of Genetics and Genomics, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029
- Division of Molecular Psychiatry, Department of Psychiatry, Yale University, New Haven CT, 06511
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32
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Barbosa IAM, Gopalakrishnan R, Mercan S, Mourikis TP, Martin T, Wengert S, Sheng C, Ji F, Lopes R, Knehr J, Altorfer M, Lindeman A, Russ C, Naumann U, Golji J, Sprouffske K, Barys L, Tordella L, Schübeler D, Schmelzle T, Galli GG. Cancer lineage-specific regulation of YAP responsive elements revealed through large-scale functional epigenomic screens. Nat Commun 2023; 14:3907. [PMID: 37400441 DOI: 10.1038/s41467-023-39527-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 06/14/2023] [Indexed: 07/05/2023] Open
Abstract
YAP is a key transcriptional co-activator of TEADs, it regulates cell growth and is frequently activated in cancer. In Malignant Pleural Mesothelioma (MPM), YAP is activated by loss-of-function mutations in upstream components of the Hippo pathway, while, in Uveal Melanoma (UM), YAP is activated in a Hippo-independent manner. To date, it is unclear if and how the different oncogenic lesions activating YAP impact its oncogenic program, which is particularly relevant for designing selective anti-cancer therapies. Here we show that, despite YAP being essential in both MPM and UM, its interaction with TEAD is unexpectedly dispensable in UM, limiting the applicability of TEAD inhibitors in this cancer type. Systematic functional interrogation of YAP regulatory elements in both cancer types reveals convergent regulation of broad oncogenic drivers in both MPM and UM, but also strikingly selective programs. Our work reveals unanticipated lineage-specific features of the YAP regulatory network that provide important insights to guide the design of tailored therapeutic strategies to inhibit YAP signaling across different cancer types.
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Affiliation(s)
- Inês A M Barbosa
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Rajaraman Gopalakrishnan
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Cambridge, MA, USA
- Alltrna Inc., One Kendall Square, Cambridge, MA, USA
| | - Samuele Mercan
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Thanos P Mourikis
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Typhaine Martin
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Simon Wengert
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
- Helmholtz Pioneer Campus, Helmholtz Zentrum München GmbH German Research Center for Environmental Health, Neuherberg, Germany
| | - Caibin Sheng
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Fei Ji
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | - Rui Lopes
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
- Roche Pharmaceutical Research and Early Development, Basel, Switzerland
| | - Judith Knehr
- Chemical Biology and Therapeutics, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Marc Altorfer
- Chemical Biology and Therapeutics, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Alicia Lindeman
- Chemical Biology and Therapeutics, Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | - Carsten Russ
- Chemical Biology and Therapeutics, Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | - Ulrike Naumann
- Chemical Biology and Therapeutics, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Javad Golji
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | - Kathleen Sprouffske
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Louise Barys
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Luca Tordella
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Dirk Schübeler
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
- Faculty of Sciences, University of Basel, Basel, Switzerland
| | - Tobias Schmelzle
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Giorgio G Galli
- Disease Area Oncology, Novartis Institutes for Biomedical Research, Basel, Switzerland.
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33
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Zhou LY, Zhang S, Li LY, Yang GY, Zeng L. Optimization of mammalian expression vector by cis-regulatory element combinations. Mol Genet Genomics 2023:10.1007/s00438-023-02042-0. [PMID: 37318628 DOI: 10.1007/s00438-023-02042-0] [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: 02/09/2023] [Accepted: 05/31/2023] [Indexed: 06/16/2023]
Abstract
The regulation of gene expression in mammalian cells by combining various cis-regulatory features has rarely been discussed. In this study, we constructed expression vectors containing various combinations of regulatory elements to examine the regulation of gene expression by different combinations of cis-regulatory elements. The effects of four promoters (CMV promoter, PGK promoter, Polr2a promoter, and EF-1α core promoter), two enhancers (CMV enhancer and SV40 enhancer), two introns (EF-1α intron A and hybrid intron), two terminators (CYC1 terminator and TEF terminator), and their different combinations on downstream gene expression were compared in various mammalian cells using fluorescence microscopy to observe fluorescence, quantitative real-time PCR (qRT-PCR), and western blot. The receptor binding domain (RBD) sequence from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) spike protein was used to replace the eGFP sequence in the expression vector and the RBD expression was detected by qRT-PCR and western blot. The results showed that protein expression can be regulated by optimizing the combination of cis-acting elements. The vector with the CMV enhancer, EF-1α core promoter, and TEF terminator was found to express approximately threefold higher eGFP than the unmodified vector in different animal cells, as well as 2.63-fold higher recombinant RBD protein than the original vector in HEK-293T cells. Moreover, we suggest that combinations of multiple regulatory elements capable of regulating gene expression do not necessarily exhibit synergistic effects to enhance expression further. Overall, our findings provide insights into biological applications that require the regulation of gene expression and will help to optimize expression vectors for biosynthesis and other fields. Additionally, we provide valuable insights into the production of RBD proteins, which may aid in developing reagents for diagnosis and treatment during the COVID-19 pandemic.
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Affiliation(s)
- Lu-Yu Zhou
- College of Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, People's Republic of China
- Key Laboratory of Animal Biochemistry and Nutrition, Henan Agricultural University, Ministry of Agriculture and Rural Affairs, Zhengzhou, 450046, Henan, People's Republic of China
- Key Laboratory of Animal Growth and Development, The Education Department of Henan Province, Zhengzhou, 450046, Henan, People's Republic of China
| | - Shuang Zhang
- College of Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, People's Republic of China
- Key Laboratory of Animal Biochemistry and Nutrition, Henan Agricultural University, Ministry of Agriculture and Rural Affairs, Zhengzhou, 450046, Henan, People's Republic of China
- Key Laboratory of Animal Growth and Development, The Education Department of Henan Province, Zhengzhou, 450046, Henan, People's Republic of China
| | - Li-Yun Li
- College of Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, People's Republic of China
- Key Laboratory of Animal Biochemistry and Nutrition, Henan Agricultural University, Ministry of Agriculture and Rural Affairs, Zhengzhou, 450046, Henan, People's Republic of China
- Key Laboratory of Animal Growth and Development, The Education Department of Henan Province, Zhengzhou, 450046, Henan, People's Republic of China
| | - Guo-Yu Yang
- Key Laboratory of Animal Biochemistry and Nutrition, Henan Agricultural University, Ministry of Agriculture and Rural Affairs, Zhengzhou, 450046, Henan, People's Republic of China
- Key Laboratory of Animal Growth and Development, The Education Department of Henan Province, Zhengzhou, 450046, Henan, People's Republic of China
| | - Lei Zeng
- College of Veterinary Medicine, Henan Agricultural University, Zhengzhou, 450046, Henan, People's Republic of China.
- Key Laboratory of Animal Biochemistry and Nutrition, Henan Agricultural University, Ministry of Agriculture and Rural Affairs, Zhengzhou, 450046, Henan, People's Republic of China.
- Key Laboratory of Animal Growth and Development, The Education Department of Henan Province, Zhengzhou, 450046, Henan, People's Republic of China.
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34
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Mach P, Giorgetti L. Integrative approaches to study enhancer-promoter communication. Curr Opin Genet Dev 2023; 80:102052. [PMID: 37257410 PMCID: PMC10293802 DOI: 10.1016/j.gde.2023.102052] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 04/21/2023] [Accepted: 04/22/2023] [Indexed: 06/02/2023]
Abstract
The spatiotemporal control of gene expression in complex multicellular organisms relies on noncoding regulatory sequences such as enhancers, which activate transcription of target genes often over large genomic distances. Despite the advances in the identification and characterization of enhancers, the principles and mechanisms by which enhancers select and control their target genes remain largely unknown. Here, we review recent interdisciplinary and quantitative approaches based on emerging techniques that aim to address open questions in the field, notably how regulatory information is encoded in the DNA sequence, how this information is transferred from enhancers to promoters, and how these processes are regulated in time.
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Affiliation(s)
- Pia Mach
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland; University of Basel, Basel, Switzerland. https://twitter.com/@MachPia
| | - Luca Giorgetti
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland.
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35
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Xu H, Lin S, Zhou Z, Li D, Zhang X, Yu M, Zhao R, Wang Y, Qian J, Li X, Li B, Wei C, Chen K, Yoshimura T, Wang JM, Huang J. New genetic and epigenetic insights into the chemokine system: the latest discoveries aiding progression toward precision medicine. Cell Mol Immunol 2023:10.1038/s41423-023-01032-x. [PMID: 37198402 DOI: 10.1038/s41423-023-01032-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 04/14/2023] [Indexed: 05/19/2023] Open
Abstract
Over the past thirty years, the importance of chemokines and their seven-transmembrane G protein-coupled receptors (GPCRs) has been increasingly recognized. Chemokine interactions with receptors trigger signaling pathway activity to form a network fundamental to diverse immune processes, including host homeostasis and responses to disease. Genetic and nongenetic regulation of both the expression and structure of chemokines and receptors conveys chemokine functional heterogeneity. Imbalances and defects in the system contribute to the pathogenesis of a variety of diseases, including cancer, immune and inflammatory diseases, and metabolic and neurological disorders, which render the system a focus of studies aiming to discover therapies and important biomarkers. The integrated view of chemokine biology underpinning divergence and plasticity has provided insights into immune dysfunction in disease states, including, among others, coronavirus disease 2019 (COVID-19). In this review, by reporting the latest advances in chemokine biology and results from analyses of a plethora of sequencing-based datasets, we outline recent advances in the understanding of the genetic variations and nongenetic heterogeneity of chemokines and receptors and provide an updated view of their contribution to the pathophysiological network, focusing on chemokine-mediated inflammation and cancer. Clarification of the molecular basis of dynamic chemokine-receptor interactions will help advance the understanding of chemokine biology to achieve precision medicine application in the clinic.
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Affiliation(s)
- Hanli Xu
- College of Life Sciences and Bioengineering, School of Physical Science and Engineering, Beijing Jiaotong University, 3 ShangyuanCun, Haidian District, 100044, Beijing, P.R. China
| | - Shuye Lin
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Institute, 101149, Beijing, China
| | - Ziyun Zhou
- College of Life Sciences and Bioengineering, School of Physical Science and Engineering, Beijing Jiaotong University, 3 ShangyuanCun, Haidian District, 100044, Beijing, P.R. China
| | - Duoduo Li
- College of Life Sciences and Bioengineering, School of Physical Science and Engineering, Beijing Jiaotong University, 3 ShangyuanCun, Haidian District, 100044, Beijing, P.R. China
| | - Xiting Zhang
- College of Life Sciences and Bioengineering, School of Physical Science and Engineering, Beijing Jiaotong University, 3 ShangyuanCun, Haidian District, 100044, Beijing, P.R. China
| | - Muhan Yu
- College of Life Sciences and Bioengineering, School of Physical Science and Engineering, Beijing Jiaotong University, 3 ShangyuanCun, Haidian District, 100044, Beijing, P.R. China
| | - Ruoyi Zhao
- College of Life Sciences and Bioengineering, School of Physical Science and Engineering, Beijing Jiaotong University, 3 ShangyuanCun, Haidian District, 100044, Beijing, P.R. China
| | - Yiheng Wang
- College of Life Sciences and Bioengineering, School of Physical Science and Engineering, Beijing Jiaotong University, 3 ShangyuanCun, Haidian District, 100044, Beijing, P.R. China
| | - Junru Qian
- College of Life Sciences and Bioengineering, School of Physical Science and Engineering, Beijing Jiaotong University, 3 ShangyuanCun, Haidian District, 100044, Beijing, P.R. China
| | - Xinyi Li
- College of Life Sciences and Bioengineering, School of Physical Science and Engineering, Beijing Jiaotong University, 3 ShangyuanCun, Haidian District, 100044, Beijing, P.R. China
| | - Bohan Li
- College of Life Sciences and Bioengineering, School of Physical Science and Engineering, Beijing Jiaotong University, 3 ShangyuanCun, Haidian District, 100044, Beijing, P.R. China
| | - Chuhan Wei
- College of Life Sciences and Bioengineering, School of Physical Science and Engineering, Beijing Jiaotong University, 3 ShangyuanCun, Haidian District, 100044, Beijing, P.R. China
| | - Keqiang Chen
- Laboratory of Cancer Innovation, Center for Cancer Research, National Cancer Institute at Frederick, Frederick, MD, 21702, USA
| | - Teizo Yoshimura
- Laboratory of Cancer Innovation, Center for Cancer Research, National Cancer Institute at Frederick, Frederick, MD, 21702, USA
| | - Ji Ming Wang
- Laboratory of Cancer Innovation, Center for Cancer Research, National Cancer Institute at Frederick, Frederick, MD, 21702, USA
| | - Jiaqiang Huang
- College of Life Sciences and Bioengineering, School of Physical Science and Engineering, Beijing Jiaotong University, 3 ShangyuanCun, Haidian District, 100044, Beijing, P.R. China.
- Cancer Research Center, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis and Thoracic Tumor Institute, 101149, Beijing, China.
- Laboratory of Cancer Innovation, Center for Cancer Research, National Cancer Institute at Frederick, Frederick, MD, 21702, USA.
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36
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Smith GD, Ching WH, Cornejo-Páramo P, Wong ES. Decoding enhancer complexity with machine learning and high-throughput discovery. Genome Biol 2023; 24:116. [PMID: 37173718 PMCID: PMC10176946 DOI: 10.1186/s13059-023-02955-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 04/28/2023] [Indexed: 05/15/2023] Open
Abstract
Enhancers are genomic DNA elements controlling spatiotemporal gene expression. Their flexible organization and functional redundancies make deciphering their sequence-function relationships challenging. This article provides an overview of the current understanding of enhancer organization and evolution, with an emphasis on factors that influence these relationships. Technological advancements, particularly in machine learning and synthetic biology, are discussed in light of how they provide new ways to understand this complexity. Exciting opportunities lie ahead as we continue to unravel the intricacies of enhancer function.
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Affiliation(s)
- Gabrielle D Smith
- Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW, Australia
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Kensington, NSW, Australia
| | - Wan Hern Ching
- Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW, Australia
| | - Paola Cornejo-Páramo
- Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW, Australia
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Kensington, NSW, Australia
| | - Emily S Wong
- Victor Chang Cardiac Research Institute, 405 Liverpool Street, Darlinghurst, NSW, Australia.
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Kensington, NSW, Australia.
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37
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Gnanapragasam MN, Planutis A, Glassberg JA, Bieker JJ. Identification of a genomic DNA sequence that quantitatively modulates KLF1 transcription factor expression in differentiating human hematopoietic cells. Sci Rep 2023; 13:7589. [PMID: 37165057 PMCID: PMC10172341 DOI: 10.1038/s41598-023-34805-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 05/08/2023] [Indexed: 05/12/2023] Open
Abstract
The onset of erythropoiesis is under strict developmental control, with direct and indirect inputs influencing its derivation from the hematopoietic stem cell. A major regulator of this transition is KLF1/EKLF, a zinc finger transcription factor that plays a global role in all aspects of erythropoiesis. Here, we have identified a short, conserved enhancer element in KLF1 intron 1 that is important for establishing optimal levels of KLF1 in mouse and human cells. Chromatin accessibility of this site exhibits cell-type specificity and is under developmental control during the differentiation of human CD34+ cells towards the erythroid lineage. This site binds GATA1, SMAD1, TAL1, and ETV6. In vivo editing of this region in cell lines and primary cells reduces KLF1 expression quantitatively. However, we find that, similar to observations seen in pedigrees of families with KLF1 mutations, downstream effects are variable, suggesting that the global architecture of the site is buffered towards keeping the KLF1 genetic region in an active state. We propose that modification of intron 1 in both alleles is not equivalent to complete loss of function of one allele.
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Affiliation(s)
- M N Gnanapragasam
- Department of Cell, Developmental, and Regenerative Biology, Mount Sinai School of Medicine, One Gustave L. Levy Place, Box 1020, New York, NY, 10029, USA
- Department of Biological, Geological, and Environmental Sciences, Center for Gene Regulation in Health and Disease, Cleveland State University, Cleveland, OH, USA
| | - A Planutis
- Department of Cell, Developmental, and Regenerative Biology, Mount Sinai School of Medicine, One Gustave L. Levy Place, Box 1020, New York, NY, 10029, USA
| | - J A Glassberg
- Department of Emergency Medicine, Hematology and Medical Oncology, Mount Sinai School of Medicine, New York, NY, USA
| | - J J Bieker
- Department of Cell, Developmental, and Regenerative Biology, Mount Sinai School of Medicine, One Gustave L. Levy Place, Box 1020, New York, NY, 10029, USA.
- Black Family Stem Cell Institute, Mount Sinai School of Medicine, New York, USA.
- Tisch Cancer Institute, Mount Sinai School of Medicine, New York, USA.
- Mindich Child Health and Development Institute, Mount Sinai School of Medicine, New York, NY, USA.
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38
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Schofield JA, Hahn S. Broad compatibility between yeast UAS elements and core promoters and identification of promoter elements that determine cofactor specificity. Cell Rep 2023; 42:112387. [PMID: 37058407 PMCID: PMC10567116 DOI: 10.1016/j.celrep.2023.112387] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/30/2023] [Accepted: 03/28/2023] [Indexed: 04/15/2023] Open
Abstract
Three classes of yeast protein-coding genes are distinguished by their dependence on the transcription cofactors TFIID, SAGA, and Mediator (MED) Tail, but whether this dependence is determined by the core promoter, upstream activating sequences (UASs), or other gene features is unclear. Also unclear is whether UASs can broadly activate transcription from the different promoter classes. Here, we measure transcription and cofactor specificity for thousands of UAS-core promoter combinations and find that most UASs broadly activate promoters regardless of regulatory class, while few display strong promoter specificity. However, matching UASs and promoters from the same gene class is generally important for optimal expression. We find that sensitivity to rapid depletion of MED Tail or SAGA is dependent on the identity of both UAS and core promoter, while dependence on TFIID localizes to only the promoter. Finally, our results suggest the role of TATA and TATA-like promoter sequences in MED Tail function.
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Affiliation(s)
- Jeremy A Schofield
- Basic Sciences Division, Fred Hutchinson Cancer Center, 1100 Fairview Avenue N, Seattle, WA 98105, USA
| | - Steven Hahn
- Basic Sciences Division, Fred Hutchinson Cancer Center, 1100 Fairview Avenue N, Seattle, WA 98105, USA.
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39
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Kravchuk EV, Ashniev GA, Gladkova MG, Orlov AV, Vasileva AV, Boldyreva AV, Burenin AG, Skirda AM, Nikitin PI, Orlova NN. Experimental Validation and Prediction of Super-Enhancers: Advances and Challenges. Cells 2023; 12:cells12081191. [PMID: 37190100 DOI: 10.3390/cells12081191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 04/07/2023] [Accepted: 04/14/2023] [Indexed: 05/17/2023] Open
Abstract
Super-enhancers (SEs) are cis-regulatory elements of the human genome that have been widely discussed since the discovery and origin of the term. Super-enhancers have been shown to be strongly associated with the expression of genes crucial for cell differentiation, cell stability maintenance, and tumorigenesis. Our goal was to systematize research studies dedicated to the investigation of structure and functions of super-enhancers as well as to define further perspectives of the field in various applications, such as drug development and clinical use. We overviewed the fundamental studies which provided experimental data on various pathologies and their associations with particular super-enhancers. The analysis of mainstream approaches for SE search and prediction allowed us to accumulate existing data and propose directions for further algorithmic improvements of SEs' reliability levels and efficiency. Thus, here we provide the description of the most robust algorithms such as ROSE, imPROSE, and DEEPSEN and suggest their further use for various research and development tasks. The most promising research direction, which is based on topic and number of published studies, are cancer-associated super-enhancers and prospective SE-targeted therapy strategies, most of which are discussed in this review.
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Affiliation(s)
- Ekaterina V Kravchuk
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., 119991 Moscow, Russia
- Faculty of Biology, Lomonosov Moscow State University, Leninskiye Gory, MSU, 1-12, 119991 Moscow, Russia
| | - German A Ashniev
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., 119991 Moscow, Russia
- Faculty of Biology, Lomonosov Moscow State University, Leninskiye Gory, MSU, 1-12, 119991 Moscow, Russia
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, GSP-1, Leninskiye Gory, MSU, 1-73, 119234 Moscow, Russia
| | - Marina G Gladkova
- Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, GSP-1, Leninskiye Gory, MSU, 1-73, 119234 Moscow, Russia
| | - Alexey V Orlov
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., 119991 Moscow, Russia
| | - Anastasiia V Vasileva
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., 119991 Moscow, Russia
| | - Anna V Boldyreva
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., 119991 Moscow, Russia
| | - Alexandr G Burenin
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., 119991 Moscow, Russia
| | - Artemiy M Skirda
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., 119991 Moscow, Russia
| | - Petr I Nikitin
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., 119991 Moscow, Russia
| | - Natalia N Orlova
- Prokhorov General Physics Institute of the Russian Academy of Sciences, 38 Vavilov St., 119991 Moscow, Russia
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40
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Kemmler CL, Moran HR, Murray BF, Scoresby A, Klem JR, Eckert RL, Lepovsky E, Bertho S, Nieuwenhuize S, Burger S, D'Agati G, Betz C, Puller AC, Felker A, Ditrychova K, Bötschi S, Affolter M, Rohner N, Lovely CB, Kwan KM, Burger A, Mosimann C. Next-generation plasmids for transgenesis in zebrafish and beyond. Development 2023; 150:dev201531. [PMID: 36975217 PMCID: PMC10263156 DOI: 10.1242/dev.201531] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 03/10/2023] [Indexed: 03/29/2023]
Abstract
Transgenesis is an essential technique for any genetic model. Tol2-based transgenesis paired with Gateway-compatible vector collections has transformed zebrafish transgenesis with an accessible modular system. Here, we establish several next-generation transgenesis tools for zebrafish and other species to expand and enhance transgenic applications. To facilitate gene regulatory element testing, we generated Gateway middle entry vectors harboring the small mouse beta-globin minimal promoter coupled to several fluorophores, CreERT2 and Gal4. To extend the color spectrum for transgenic applications, we established middle entry vectors encoding the bright, blue-fluorescent protein mCerulean and mApple as an alternative red fluorophore. We present a series of p2A peptide-based 3' vectors with different fluorophores and subcellular localizations to co-label cells expressing proteins of interest. Finally, we established Tol2 destination vectors carrying the zebrafish exorh promoter driving different fluorophores as a pineal gland-specific transgenesis marker that is active before hatching and through adulthood. exorh-based reporters and transgenesis markers also drive specific pineal gland expression in the eye-less cavefish (Astyanax). Together, our vectors provide versatile reagents for transgenesis applications in zebrafish, cavefish and other models.
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Affiliation(s)
- Cassie L. Kemmler
- University of Colorado, School of Medicine, Anschutz Medical Campus, Department of Pediatrics, Section of Developmental Biology, 12801 E 17th Avenue, Aurora, CO 80045, USA
| | - Hannah R. Moran
- University of Colorado, School of Medicine, Anschutz Medical Campus, Department of Pediatrics, Section of Developmental Biology, 12801 E 17th Avenue, Aurora, CO 80045, USA
| | - Brooke F. Murray
- Department of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA
| | - Aaron Scoresby
- Department of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA
| | - John R. Klem
- Department of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY 40202, USA
| | - Rachel L. Eckert
- Department of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY 40202, USA
| | - Elizabeth Lepovsky
- Department of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY 40202, USA
| | - Sylvain Bertho
- Stowers Institute for Medical Research, Kansas City, MO 64110, USA
| | - Susan Nieuwenhuize
- University of Colorado, School of Medicine, Anschutz Medical Campus, Department of Pediatrics, Section of Developmental Biology, 12801 E 17th Avenue, Aurora, CO 80045, USA
- Department of Molecular Life Sciences, University of Zurich, 8057 Zürich, Switzerland
| | - Sibylle Burger
- Department of Molecular Life Sciences, University of Zurich, 8057 Zürich, Switzerland
| | - Gianluca D'Agati
- Department of Molecular Life Sciences, University of Zurich, 8057 Zürich, Switzerland
| | - Charles Betz
- Growth & Development, Biozentrum, Spitalstrasse 41, University of Basel, 4056 Basel, Switzerland
| | - Ann-Christin Puller
- Department of Molecular Life Sciences, University of Zurich, 8057 Zürich, Switzerland
| | - Anastasia Felker
- Department of Molecular Life Sciences, University of Zurich, 8057 Zürich, Switzerland
| | - Karolina Ditrychova
- Department of Molecular Life Sciences, University of Zurich, 8057 Zürich, Switzerland
| | - Seraina Bötschi
- Department of Molecular Life Sciences, University of Zurich, 8057 Zürich, Switzerland
| | - Markus Affolter
- Growth & Development, Biozentrum, Spitalstrasse 41, University of Basel, 4056 Basel, Switzerland
| | - Nicolas Rohner
- Stowers Institute for Medical Research, Kansas City, MO 64110, USA
| | - C. Ben Lovely
- Department of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY 40202, USA
| | - Kristen M. Kwan
- Department of Human Genetics, University of Utah, Salt Lake City, UT 84112, USA
| | - Alexa Burger
- University of Colorado, School of Medicine, Anschutz Medical Campus, Department of Pediatrics, Section of Developmental Biology, 12801 E 17th Avenue, Aurora, CO 80045, USA
| | - Christian Mosimann
- University of Colorado, School of Medicine, Anschutz Medical Campus, Department of Pediatrics, Section of Developmental Biology, 12801 E 17th Avenue, Aurora, CO 80045, USA
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41
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Das M, Hossain A, Banerjee D, Praul CA, Girirajan S. Challenges and considerations for reproducibility of STARR-seq assays. Genome Res 2023; 33:479-495. [PMID: 37130797 PMCID: PMC10234304 DOI: 10.1101/gr.277204.122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Accepted: 03/15/2023] [Indexed: 05/04/2023]
Abstract
High-throughput methods such as RNA-seq, ChIP-seq, and ATAC-seq have well-established guidelines, commercial kits, and analysis pipelines that enable consistency and wider adoption for understanding genome function and regulation. STARR-seq, a popular assay for directly quantifying the activities of thousands of enhancer sequences simultaneously, has seen limited standardization across studies. The assay is long, with more than 250 steps, and frequent customization of the protocol and variations in bioinformatics methods raise concerns for reproducibility of STARR-seq studies. Here, we assess each step of the protocol and analysis pipelines from published sources and in-house assays, and identify critical steps and quality control (QC) checkpoints necessary for reproducibility of the assay. We also provide guidelines for experimental design, protocol scaling, customization, and analysis pipelines for better adoption of the assay. These resources will allow better optimization of STARR-seq for specific research needs, enable comparisons and integration across studies, and improve the reproducibility of results.
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Affiliation(s)
- Maitreya Das
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, Pennsylvania 16802, USA;
- Molecular and Cellular Integrative Biosciences Graduate Program, Pennsylvania State University, University Park, Pennsylvania 16802, USA
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Ayaan Hossain
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA
- Bioinformatics and Genomics Graduate Program, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Deepro Banerjee
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA
- Bioinformatics and Genomics Graduate Program, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Craig Alan Praul
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA
| | - Santhosh Girirajan
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, Pennsylvania 16802, USA;
- Molecular and Cellular Integrative Biosciences Graduate Program, Pennsylvania State University, University Park, Pennsylvania 16802, USA
- Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, Pennsylvania 16802, USA
- Bioinformatics and Genomics Graduate Program, Pennsylvania State University, University Park, Pennsylvania 16802, USA
- Department of Anthropology, Pennsylvania State University, University Park, Pennsylvania 16802, USA
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42
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Karollus A, Mauermeier T, Gagneur J. Current sequence-based models capture gene expression determinants in promoters but mostly ignore distal enhancers. Genome Biol 2023; 24:56. [PMID: 36973806 PMCID: PMC10045630 DOI: 10.1186/s13059-023-02899-9] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 03/16/2023] [Indexed: 03/29/2023] Open
Abstract
BACKGROUND The largest sequence-based models of transcription control to date are obtained by predicting genome-wide gene regulatory assays across the human genome. This setting is fundamentally correlative, as those models are exposed during training solely to the sequence variation between human genes that arose through evolution, questioning the extent to which those models capture genuine causal signals. RESULTS Here we confront predictions of state-of-the-art models of transcription regulation against data from two large-scale observational studies and five deep perturbation assays. The most advanced of these sequence-based models, Enformer, by and large, captures causal determinants of human promoters. However, models fail to capture the causal effects of enhancers on expression, notably in medium to long distances and particularly for highly expressed promoters. More generally, the predicted impact of distal elements on gene expression predictions is small and the ability to correctly integrate long-range information is significantly more limited than the receptive fields of the models suggest. This is likely caused by the escalating class imbalance between actual and candidate regulatory elements as distance increases. CONCLUSIONS Our results suggest that sequence-based models have advanced to the point that in silico study of promoter regions and promoter variants can provide meaningful insights and we provide practical guidance on how to use them. Moreover, we foresee that it will require significantly more and particularly new kinds of data to train models accurately accounting for distal elements.
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Affiliation(s)
- Alexander Karollus
- School of Computation, Information and Technology, Technical University of Munich, Garching, Germany.
| | - Thomas Mauermeier
- School of Computation, Information and Technology, Technical University of Munich, Garching, Germany
| | - Julien Gagneur
- School of Computation, Information and Technology, Technical University of Munich, Garching, Germany.
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany.
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.
- Munich Data Science Institute, Technical University of Munich, Garching, Germany.
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43
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Kabirova E, Nurislamov A, Shadskiy A, Smirnov A, Popov A, Salnikov P, Battulin N, Fishman V. Function and Evolution of the Loop Extrusion Machinery in Animals. Int J Mol Sci 2023; 24:ijms24055017. [PMID: 36902449 PMCID: PMC10003631 DOI: 10.3390/ijms24055017] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 02/25/2023] [Accepted: 03/02/2023] [Indexed: 03/08/2023] Open
Abstract
Structural maintenance of chromosomes (SMC) complexes are essential proteins found in genomes of all cellular organisms. Essential functions of these proteins, such as mitotic chromosome formation and sister chromatid cohesion, were discovered a long time ago. Recent advances in chromatin biology showed that SMC proteins are involved in many other genomic processes, acting as active motors extruding DNA, which leads to the formation of chromatin loops. Some loops formed by SMC proteins are highly cell type and developmental stage specific, such as SMC-mediated DNA loops required for VDJ recombination in B-cell progenitors, or dosage compensation in Caenorhabditis elegans and X-chromosome inactivation in mice. In this review, we focus on the extrusion-based mechanisms that are common for multiple cell types and species. We will first describe an anatomy of SMC complexes and their accessory proteins. Next, we provide biochemical details of the extrusion process. We follow this by the sections describing the role of SMC complexes in gene regulation, DNA repair, and chromatin topology.
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Affiliation(s)
- Evelyn Kabirova
- Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
- Department of Natural Sciences, Novosibirsk State University, 630090 Novosibirsk, Russia
| | - Artem Nurislamov
- Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
- Department of Natural Sciences, Novosibirsk State University, 630090 Novosibirsk, Russia
| | - Artem Shadskiy
- Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
- Department of Natural Sciences, Novosibirsk State University, 630090 Novosibirsk, Russia
| | - Alexander Smirnov
- Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
- Department of Natural Sciences, Novosibirsk State University, 630090 Novosibirsk, Russia
| | - Andrey Popov
- Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
- Department of Natural Sciences, Novosibirsk State University, 630090 Novosibirsk, Russia
| | - Pavel Salnikov
- Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
- Department of Natural Sciences, Novosibirsk State University, 630090 Novosibirsk, Russia
| | - Nariman Battulin
- Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
- Department of Natural Sciences, Novosibirsk State University, 630090 Novosibirsk, Russia
| | - Veniamin Fishman
- Institute of Cytology and Genetics SB RAS, 630090 Novosibirsk, Russia
- Department of Natural Sciences, Novosibirsk State University, 630090 Novosibirsk, Russia
- Artificial Intelligence Research Institute (AIRI), 121108 Moscow, Russia
- Correspondence:
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44
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Stankey CT, Lee JC. Translating non-coding genetic associations into a better understanding of immune-mediated disease. Dis Model Mech 2023; 16:297044. [PMID: 36897113 PMCID: PMC10040244 DOI: 10.1242/dmm.049790] [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: 03/11/2023] Open
Abstract
Genome-wide association studies have identified hundreds of genetic loci that are associated with immune-mediated diseases. Most disease-associated variants are non-coding, and a large proportion of these variants lie within enhancers. As a result, there is a pressing need to understand how common genetic variation might affect enhancer function and thereby contribute to immune-mediated (and other) diseases. In this Review, we first describe statistical and experimental methods to identify causal genetic variants that modulate gene expression, including statistical fine-mapping and massively parallel reporter assays. We then discuss approaches to characterise the mechanisms by which these variants modulate immune function, such as clustered regularly interspaced short palindromic repeats (CRISPR)-based screens. We highlight examples of studies that, by elucidating the effects of disease variants within enhancers, have provided important insights into immune function and uncovered key pathways of disease.
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Affiliation(s)
- Christina T Stankey
- Genetic Mechanisms of Disease Laboratory, The Francis Crick Institute, London NW1 1AT, UK
- Department of Immunology and Inflammation, Imperial College London, London W12 0NN, UK
| | - James C Lee
- Genetic Mechanisms of Disease Laboratory, The Francis Crick Institute, London NW1 1AT, UK
- Institute of Liver and Digestive Health, Royal Free Hospital, University College London, London NW3 2PF, UK
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45
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Mechanisms of Interaction between Enhancers and Promoters in Three Drosophila Model Systems. Int J Mol Sci 2023; 24:ijms24032855. [PMID: 36769179 PMCID: PMC9917889 DOI: 10.3390/ijms24032855] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Revised: 01/26/2023] [Accepted: 01/30/2023] [Indexed: 02/05/2023] Open
Abstract
In higher eukaryotes, the regulation of developmental gene expression is determined by enhancers, which are often located at a large distance from the promoters they regulate. Therefore, the architecture of chromosomes and the mechanisms that determine the functional interaction between enhancers and promoters are of decisive importance in the development of organisms. Mammals and the model animal Drosophila have homologous key architectural proteins and similar mechanisms in the organization of chromosome architecture. This review describes the current progress in understanding the mechanisms of the formation and regulation of long-range interactions between enhancers and promoters at three well-studied key regulatory loci in Drosophila.
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46
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Kim S, Wysocka J. Deciphering the multi-scale, quantitative cis-regulatory code. Mol Cell 2023; 83:373-392. [PMID: 36693380 PMCID: PMC9898153 DOI: 10.1016/j.molcel.2022.12.032] [Citation(s) in RCA: 45] [Impact Index Per Article: 45.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 12/29/2022] [Accepted: 12/30/2022] [Indexed: 01/24/2023]
Abstract
Uncovering the cis-regulatory code that governs when and how much each gene is transcribed in a given genome and cellular state remains a central goal of biology. Here, we discuss major layers of regulation that influence how transcriptional outputs are encoded by DNA sequence and cellular context. We first discuss how transcription factors bind specific DNA sequences in a dosage-dependent and cooperative manner and then proceed to the cofactors that facilitate transcription factor function and mediate the activity of modular cis-regulatory elements such as enhancers, silencers, and promoters. We then consider the complex and poorly understood interplay of these diverse elements within regulatory landscapes and its relationships with chromatin states and nuclear organization. We propose that a mechanistically informed, quantitative model of transcriptional regulation that integrates these multiple regulatory layers will be the key to ultimately cracking the cis-regulatory code.
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Affiliation(s)
- Seungsoo Kim
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Joanna Wysocka
- Howard Hughes Medical Institute, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Chemical and Systems Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Department of Developmental Biology, Stanford University School of Medicine, Stanford, CA 94305, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA.
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47
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Mouri K, Dewey HB, Castro R, Berenzy D, Kales S, Tewhey R. Whole-genome functional characterization of RE1 silencers using a modified massively parallel reporter assay. CELL GENOMICS 2023; 3:100234. [PMID: 36777181 PMCID: PMC9903721 DOI: 10.1016/j.xgen.2022.100234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 09/12/2022] [Accepted: 11/23/2022] [Indexed: 12/23/2022]
Abstract
Both upregulation and downregulation by cis-regulatory elements help modulate precise gene expression. However, our understanding of repressive elements is far more limited than activating elements. To address this gap, we characterized RE1, a group of transcriptional silencers bound by REST, at genome-wide scale using a modified massively parallel reporter assay (MPRAduo). MPRAduo empirically defined a minimal binding strength of REST (REST motif-intrinsic value [m-value]), above which cofactors colocalize and silence transcription. We identified 1,500 human variants that alter RE1 silencing and found that their effect sizes are predictable when they overlap with REST-binding sites above the m-value. Additionally, we demonstrate that non-canonical REST-binding motifs exhibit silencer function only if they precisely align half sites with specific spacer lengths. Our results show mechanistic insights into RE1, which allow us to predict its activity and effect of variants on RE1, providing a paradigm for performing genome-wide functional characterization of transcription-factor-binding sites.
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Affiliation(s)
| | | | | | | | - Susan Kales
- The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | - Ryan Tewhey
- The Jackson Laboratory, Bar Harbor, ME 04609, USA
- Graduate School of Biomedical Sciences and Engineering, University of Maine, Orono, ME, USA
- Graduate School of Biomedical Sciences, Tufts University School of Medicine, Boston, MA, USA
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48
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Galupa R, Alvarez-Canales G, Borst NO, Fuqua T, Gandara L, Misunou N, Richter K, Alves MRP, Karumbi E, Perkins ML, Kocijan T, Rushlow CA, Crocker J. Enhancer architecture and chromatin accessibility constrain phenotypic space during Drosophila development. Dev Cell 2023; 58:51-62.e4. [PMID: 36626871 PMCID: PMC9860173 DOI: 10.1016/j.devcel.2022.12.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 10/18/2022] [Accepted: 12/07/2022] [Indexed: 01/11/2023]
Abstract
Developmental enhancers bind transcription factors and dictate patterns of gene expression during development. Their molecular evolution can underlie phenotypical evolution, but the contributions of the evolutionary pathways involved remain little understood. Here, using mutation libraries in Drosophila melanogaster embryos, we observed that most point mutations in developmental enhancers led to changes in gene expression levels but rarely resulted in novel expression outside of the native pattern. In contrast, random sequences, often acting as developmental enhancers, drove expression across a range of cell types; random sequences including motifs for transcription factors with pioneer activity acted as enhancers even more frequently. Our findings suggest that the phenotypic landscapes of developmental enhancers are constrained by enhancer architecture and chromatin accessibility. We propose that the evolution of existing enhancers is limited in its capacity to generate novel phenotypes, whereas the activity of de novo elements is a primary source of phenotypic novelty.
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Affiliation(s)
- Rafael Galupa
- European Molecular Biology Laboratory, 69117 Heidelberg, Germany.
| | | | | | - Timothy Fuqua
- European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Lautaro Gandara
- European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Natalia Misunou
- European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | - Kerstin Richter
- European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | | | - Esther Karumbi
- European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | | | - Tin Kocijan
- European Molecular Biology Laboratory, 69117 Heidelberg, Germany
| | | | - Justin Crocker
- European Molecular Biology Laboratory, 69117 Heidelberg, Germany.
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49
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Аpplication of massive parallel reporter analysis in biotechnology and medicine. КЛИНИЧЕСКАЯ ПРАКТИКА 2023. [DOI: 10.17816/clinpract115063] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
The development and functioning of an organism relies on tissue-specific gene programs. Genome regulatory elements play a key role in the regulation of such programs, and disruptions in their function can lead to the development of various pathologies, including cancers, malformations and autoimmune diseases. The emergence of high-throughput genomic studies has led to massively parallel reporter analysis (MPRA) methods, which allow the functional verification and identification of regulatory elements on a genome-wide scale. Initially MPRA was used as a tool to investigate fundamental aspects of epigenetics, but the approach also has great potential for clinical and practical biotechnology. Currently, MPRA is used for validation of clinically significant mutations, identification of tissue-specific regulatory elements, search for the most promising loci for transgene integration, and is an indispensable tool for creating highly efficient expression systems, the range of application of which extends from approaches for protein development and design of next-generation therapeutic antibody superproducers to gene therapy. In this review, the main principles and areas of practical application of high-throughput reporter assays will be discussed.
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Promoter-Adjacent DNA Hypermethylation Can Downmodulate Gene Expression: TBX15 in the Muscle Lineage. EPIGENOMES 2022; 6:epigenomes6040043. [PMID: 36547252 PMCID: PMC9778270 DOI: 10.3390/epigenomes6040043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 12/01/2022] [Accepted: 12/06/2022] [Indexed: 12/13/2022] Open
Abstract
TBX15, which encodes a differentiation-related transcription factor, displays promoter-adjacent DNA hypermethylation in myoblasts and skeletal muscle (psoas) that is absent from non-expressing cells in other lineages. By whole-genome bisulfite sequencing (WGBS) and enzymatic methyl-seq (EM-seq), these hypermethylated regions were found to border both sides of a constitutively unmethylated promoter. To understand the functionality of this DNA hypermethylation, we cloned the differentially methylated sequences (DMRs) in CpG-free reporter vectors and tested them for promoter or enhancer activity upon transient transfection. These cloned regions exhibited strong promoter activity and, when placed upstream of a weak promoter, strong enhancer activity specifically in myoblast host cells. In vitro CpG methylation targeted to the DMR sequences in the plasmids resulted in 86−100% loss of promoter or enhancer activity, depending on the insert sequence. These results as well as chromatin epigenetic and transcription profiles for this gene in various cell types support the hypothesis that DNA hypermethylation immediately upstream and downstream of the unmethylated promoter region suppresses enhancer/extended promoter activity, thereby downmodulating, but not silencing, expression in myoblasts and certain kinds of skeletal muscle. This promoter-border hypermethylation was not found in cell types with a silent TBX15 gene, and these cells, instead, exhibit repressive chromatin in and around the promoter. TBX18, TBX2, TBX3 and TBX1 display TBX15-like hypermethylated DMRs at their promoter borders and preferential expression in myoblasts. Therefore, promoter-adjacent DNA hypermethylation for downmodulating transcription to prevent overexpression may be used more frequently for transcription regulation than currently appreciated.
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