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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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2
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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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3
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Pinglay S, Lalanne JB, Daza RM, Koeppel J, Li X, Lee DS, Shendure J. Multiplex generation and single cell analysis of structural variants in a mammalian genome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.01.22.576756. [PMID: 38405830 PMCID: PMC10888807 DOI: 10.1101/2024.01.22.576756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
The functional consequences of structural variants (SVs) in mammalian genomes are challenging to study. This is due to several factors, including: 1) their numerical paucity relative to other forms of standing genetic variation such as single nucleotide variants (SNVs) and short insertions or deletions (indels); 2) the fact that a single SV can involve and potentially impact the function of more than one gene and/or cis regulatory element; and 3) the relative immaturity of methods to generate and map SVs, either randomly or in targeted fashion, in in vitro or in vivo model systems. Towards addressing these challenges, we developed Genome-Shuffle-seq, a straightforward method that enables the multiplex generation and mapping of several major forms of SVs (deletions, inversions, translocations) throughout a mammalian genome. Genome-Shuffle-seq is based on the integration of "shuffle cassettes" to the genome, wherein each shuffle cassette contains components that facilitate its site-specific recombination (SSR) with other integrated shuffle cassettes (via Cre-loxP), its mapping to a specific genomic location (via T7-mediated in vitro transcription or IVT), and its identification in single-cell RNA-seq (scRNA-seq) data (via T7-mediated in situ transcription or IST). In this proof-of-concept, we apply Genome-Shuffle-seq to induce and map thousands of genomic SVs in mouse embryonic stem cells (mESCs) in a single experiment. Induced SVs are rapidly depleted from the cellular population over time, possibly due to Cre-mediated toxicity and/or negative selection on the rearrangements themselves. Leveraging T7 IST of barcodes whose positions are already mapped, we further demonstrate that we can efficiently genotype which SVs are present in association with each of many single cell transcriptomes in scRNA-seq data. Finally, preliminary evidence suggests our method may be a powerful means of generating extrachromosomal circular DNAs (ecDNAs). Looking forward, we anticipate that Genome-Shuffle-seq may be broadly useful for the systematic exploration of the functional consequences of SVs on gene expression, the chromatin landscape, and 3D nuclear architecture. We further anticipate potential uses for in vitro modeling of ecDNAs, as well as in paving the path to a minimal mammalian genome.
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Affiliation(s)
- Sudarshan Pinglay
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | | | - Riza M Daza
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
| | | | - Xiaoyi Li
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - David S Lee
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Institute for Protein Design, University of Washington, Seattle, WA, USA
| | - Jay Shendure
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
- Brotman Baty Institute for Precision Medicine, Seattle, WA, USA
- Seattle Hub for Synthetic Biology, Seattle, WA, USA
- Allen Discovery Center for Cell Lineage Tracing, Seattle, WA, USA
- Howard Hughes Medical Institute, Seattle, WA, USA
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4
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Hollingsworth EW, Liu TA, Jacinto SH, Chen CX, Alcantara JA, Kvon EZ. Rapid and Quantitative Functional Interrogation of Human Enhancer Variant Activity in Live Mice. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.10.570890. [PMID: 38105996 PMCID: PMC10723448 DOI: 10.1101/2023.12.10.570890] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Functional analysis of non-coding variants associated with human congenital disorders remains challenging due to the lack of efficient in vivo models. Here we introduce dual-enSERT, a robust Cas9-based two-color fluorescent reporter system which enables rapid, quantitative comparison of enhancer allele activities in live mice of any genetic background. We use this new technology to examine and measure the gain- and loss-of-function effects of enhancer variants linked to limb polydactyly, autism, and craniofacial malformation. By combining dual-enSERT with single-cell transcriptomics, we characterize variant enhancer alleles at cellular resolution, thereby implicating candidate molecular pathways in pathogenic enhancer misregulation. We further show that independent, polydactyly-linked enhancer variants lead to ectopic expression in the same cell populations, indicating shared genetic mechanisms underlying non-coding variant pathogenesis. Finally, we streamline dual-enSERT for analysis in F0 animals by placing both reporters on the same transgene separated by a synthetic insulator. Dual-enSERT allows researchers to go from identifying candidate enhancer variants to analysis of comparative enhancer activity in live embryos in under two weeks.
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Affiliation(s)
- Ethan W. Hollingsworth
- Department of Developmental and Cell Biology, University of California, Irvine, CA 92697, USA
- Medical Scientist Training Program, University of California, Irvine School of Medicine, Irvine, CA 92697, USA
| | - Taryn A. Liu
- Department of Developmental and Cell Biology, University of California, Irvine, CA 92697, USA
| | - Sandra H. Jacinto
- Department of Developmental and Cell Biology, University of California, Irvine, CA 92697, USA
| | - Cindy X. Chen
- Department of Developmental and Cell Biology, University of California, Irvine, CA 92697, USA
| | - Joshua A. Alcantara
- Department of Developmental and Cell Biology, University of California, Irvine, CA 92697, USA
| | - Evgeny Z. Kvon
- Department of Developmental and Cell Biology, University of California, Irvine, CA 92697, USA
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5
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Zhang W, Golynker I, Brosh R, Fajardo A, Zhu Y, Wudzinska AM, Ordoñez R, Ribeiro-Dos-Santos AM, Carrau L, Damani-Yokota P, Yeung ST, Khairallah C, Vela Gartner A, Chalhoub N, Huang E, Ashe HJ, Khanna KM, Maurano MT, Kim SY, tenOever BR, Boeke JD. Mouse genome rewriting and tailoring of three important disease loci. Nature 2023; 623:423-431. [PMID: 37914927 PMCID: PMC10632133 DOI: 10.1038/s41586-023-06675-4] [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: 06/28/2022] [Accepted: 09/25/2023] [Indexed: 11/03/2023]
Abstract
Genetically engineered mouse models (GEMMs) help us to understand human pathologies and develop new therapies, yet faithfully recapitulating human diseases in mice is challenging. Advances in genomics have highlighted the importance of non-coding regulatory genome sequences, which control spatiotemporal gene expression patterns and splicing in many human diseases1,2. Including regulatory extensive genomic regions, which requires large-scale genome engineering, should enhance the quality of disease modelling. Existing methods set limits on the size and efficiency of DNA delivery, hampering the routine creation of highly informative models that we call genomically rewritten and tailored GEMMs (GREAT-GEMMs). Here we describe 'mammalian switching antibiotic resistance markers progressively for integration' (mSwAP-In), a method for efficient genome rewriting in mouse embryonic stem cells. We demonstrate the use of mSwAP-In for iterative genome rewriting of up to 115 kb of a tailored Trp53 locus, as well as for humanization of mice using 116 kb and 180 kb human ACE2 loci. The ACE2 model recapitulated human ACE2 expression patterns and splicing, and notably, presented milder symptoms when challenged with SARS-CoV-2 compared with the existing K18-hACE2 model, thus representing a more human-like model of infection. Finally, we demonstrated serial genome writing by humanizing mouse Tmprss2 biallelically in the ACE2 GREAT-GEMM, highlighting the versatility of mSwAP-In in genome writing.
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Affiliation(s)
- Weimin Zhang
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Ilona Golynker
- Department of Microbiology, NYU Langone Health, New York, NY, USA
| | - Ran Brosh
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Alvaro Fajardo
- Department of Microbiology, NYU Langone Health, New York, NY, USA
| | - Yinan Zhu
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Aleksandra M Wudzinska
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Raquel Ordoñez
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - André M Ribeiro-Dos-Santos
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Lucia Carrau
- Department of Microbiology, NYU Langone Health, New York, NY, USA
| | | | - Stephen T Yeung
- Department of Microbiology, NYU Langone Health, New York, NY, USA
| | | | - Antonio Vela Gartner
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Noor Chalhoub
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Emily Huang
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Hannah J Ashe
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
| | - Kamal M Khanna
- Department of Microbiology, NYU Langone Health, New York, NY, USA
- Perlmutter Cancer Center, NYU Langone Health, New York, NY, USA
| | - Matthew T Maurano
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA
- Department of Pathology, NYU Langone Health, New York, NY, USA
| | - Sang Yong Kim
- Department of Pathology, NYU Langone Health, New York, NY, USA
| | - Benjamin R tenOever
- Department of Microbiology, NYU Langone Health, New York, NY, USA
- Department of Medicine, NYU Langone Health, New York, NY, USA
| | - Jef D Boeke
- Institute for Systems Genetics and Department of Biochemistry and Molecular Pharmacology, NYU Langone Health, New York, NY, USA.
- Department of Biomedical Engineering, NYU Tandon School of Engineering, Brooklyn, NY, USA.
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6
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Xu H, Yi X, Fan X, Wu C, Wang W, Chu X, Zhang S, Dong X, Wang Z, Wang J, Zhou Y, Zhao K, Yao H, Zheng N, Wang J, Chen Y, Plewczynski D, Sham PC, Chen K, Huang D, Li MJ. Inferring CTCF-binding patterns and anchored loops across human tissues and cell types. PATTERNS (NEW YORK, N.Y.) 2023; 4:100798. [PMID: 37602215 PMCID: PMC10436006 DOI: 10.1016/j.patter.2023.100798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 01/25/2023] [Accepted: 06/20/2023] [Indexed: 08/22/2023]
Abstract
CCCTC-binding factor (CTCF) is a transcription regulator with a complex role in gene regulation. The recognition and effects of CTCF on DNA sequences, chromosome barriers, and enhancer blocking are not well understood. Existing computational tools struggle to assess the regulatory potential of CTCF-binding sites and their impact on chromatin loop formation. Here we have developed a deep-learning model, DeepAnchor, to accurately characterize CTCF binding using high-resolution genomic/epigenomic features. This has revealed distinct chromatin and sequence patterns for CTCF-mediated insulation and looping. An optimized implementation of a previous loop model based on DeepAnchor score excels in predicting CTCF-anchored loops. We have established a compendium of CTCF-anchored loops across 52 human tissue/cell types, and this suggests that genomic disruption of these loops could be a general mechanism of disease pathogenesis. These computational models and resources can help investigate how CTCF-mediated cis-regulatory elements shape context-specific gene regulation in cell development and disease progression.
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Affiliation(s)
- Hang Xu
- Department of Epidemiology and Biostatistics, Key Laboratory of Prevention and Control of Human Major Diseases (Ministry of Education), National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A∗STAR), Singapore 138648, Singapore
| | - Xianfu Yi
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xutong Fan
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Chengyue Wu
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Wei Wang
- Department of Epidemiology and Biostatistics, Key Laboratory of Prevention and Control of Human Major Diseases (Ministry of Education), National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Xinlei Chu
- Department of Epidemiology and Biostatistics, Key Laboratory of Prevention and Control of Human Major Diseases (Ministry of Education), National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Shijie Zhang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Xiaobao Dong
- Department of Genetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Zhao Wang
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Jianhua Wang
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Yao Zhou
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Ke Zhao
- Department of Pharmacology, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Hongcheng Yao
- Centre for PanorOmic Sciences-Genomics and Bioinformatics Cores, The University of Hong Kong, Hong Kong 999077, China
| | - Nan Zheng
- Department of Network Security and Informatization, Tianjin Medical University, Tianjin 300070, China
| | - Junwen Wang
- Department of Health Sciences Research and Center for Individualized Medicine, Mayo Clinic, Scottsdale, AZ 85259, USA
| | - Yupeng Chen
- Department of Biochemistry and Molecular Biology, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
| | - Dariusz Plewczynski
- Faculty of Mathematics and Information Science, Warsaw University of Technology, Warsaw, Poland
| | - Pak Chung Sham
- Centre for PanorOmic Sciences-Genomics and Bioinformatics Cores, The University of Hong Kong, Hong Kong 999077, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, Key Laboratory of Prevention and Control of Human Major Diseases (Ministry of Education), National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
| | - Dandan Huang
- Wuxi School of Medicine, Jiangnan University, Wuxi 214122, China
| | - Mulin Jun Li
- Department of Epidemiology and Biostatistics, Key Laboratory of Prevention and Control of Human Major Diseases (Ministry of Education), National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300070, China
- Department of Bioinformatics, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin 300070, China
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7
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Brosh R, Coelho C, Ribeiro-Dos-Santos AM, Ellis G, Hogan MS, Ashe HJ, Somogyi N, Ordoñez R, Luther RD, Huang E, Boeke JD, Maurano MT. Synthetic regulatory genomics uncovers enhancer context dependence at the Sox2 locus. Mol Cell 2023; 83:1140-1152.e7. [PMID: 36931273 PMCID: PMC10081970 DOI: 10.1016/j.molcel.2023.02.027] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 01/20/2023] [Accepted: 02/23/2023] [Indexed: 03/18/2023]
Abstract
Sox2 expression in mouse embryonic stem cells (mESCs) depends on a distal cluster of DNase I hypersensitive sites (DHSs), but their individual contributions and degree of interdependence remain a mystery. We analyzed the endogenous Sox2 locus using Big-IN to scarlessly integrate large DNA payloads incorporating deletions, rearrangements, and inversions affecting single or multiple DHSs, as well as surgical alterations to transcription factor (TF) recognition sequences. Multiple mESC clones were derived for each payload, sequence-verified, and analyzed for Sox2 expression. We found that two DHSs comprising a handful of key TF recognition sequences were each sufficient for long-range activation of Sox2 expression. By contrast, three nearby DHSs were entirely context dependent, showing no activity alone but dramatically augmenting the activity of the autonomous DHSs. Our results highlight the role of context in modulating genomic regulatory element function, and our synthetic regulatory genomics approach provides a roadmap for the dissection of other genomic loci.
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Affiliation(s)
- Ran Brosh
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Camila Coelho
- 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
| | - Megan S Hogan
- 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
| | - Nicolette Somogyi
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Raquel Ordoñez
- Institute for Systems Genetics, NYU School of Medicine, New York, NY 10016, USA
| | - Raven D Luther
- 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
| | - 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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8
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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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9
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Dehingia B, Milewska M, Janowski M, Pękowska A. CTCF
shapes chromatin structure and gene expression in health and disease. EMBO Rep 2022; 23:e55146. [PMID: 35993175 PMCID: PMC9442299 DOI: 10.15252/embr.202255146] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 05/31/2022] [Accepted: 07/14/2022] [Indexed: 11/09/2022] Open
Affiliation(s)
- Bondita Dehingia
- Dioscuri Centre for Chromatin Biology and Epigenomics, Nencki Institute of Experimental Biology Polish Academy of Sciences Warsaw Poland
| | - Małgorzata Milewska
- Dioscuri Centre for Chromatin Biology and Epigenomics, Nencki Institute of Experimental Biology Polish Academy of Sciences Warsaw Poland
| | - Marcin Janowski
- Dioscuri Centre for Chromatin Biology and Epigenomics, Nencki Institute of Experimental Biology Polish Academy of Sciences Warsaw Poland
| | - Aleksandra Pękowska
- Dioscuri Centre for Chromatin Biology and Epigenomics, Nencki Institute of Experimental Biology Polish Academy of Sciences Warsaw Poland
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