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Latif‐Hernandez A, Yang T, Butler RR, Losada PM, Minhas PS, White H, Tran KC, Liu H, Simmons DA, Langness V, Andreasson KI, Wyss‐Coray T, Longo FM. A TrkB and TrkC partial agonist restores deficits in synaptic function and promotes activity-dependent synaptic and microglial transcriptomic changes in a late-stage Alzheimer's mouse model. Alzheimers Dement 2024; 20:4434-4460. [PMID: 38779814 PMCID: PMC11247716 DOI: 10.1002/alz.13857] [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: 10/09/2023] [Revised: 03/12/2024] [Accepted: 04/02/2024] [Indexed: 05/25/2024]
Abstract
INTRODUCTION Tropomyosin related kinase B (TrkB) and C (TrkC) receptor signaling promotes synaptic plasticity and interacts with pathways affected by amyloid beta (Aβ) toxicity. Upregulating TrkB/C signaling could reduce Alzheimer's disease (AD)-related degenerative signaling, memory loss, and synaptic dysfunction. METHODS PTX-BD10-2 (BD10-2), a small molecule TrkB/C receptor partial agonist, was orally administered to aged London/Swedish-APP mutant mice (APPL/S) and wild-type controls. Effects on memory and hippocampal long-term potentiation (LTP) were assessed using electrophysiology, behavioral studies, immunoblotting, immunofluorescence staining, and RNA sequencing. RESULTS In APPL/S mice, BD10-2 treatment improved memory and LTP deficits. This was accompanied by normalized phosphorylation of protein kinase B (Akt), calcium-calmodulin-dependent kinase II (CaMKII), and AMPA-type glutamate receptors containing the subunit GluA1; enhanced activity-dependent recruitment of synaptic proteins; and increased excitatory synapse number. BD10-2 also had potentially favorable effects on LTP-dependent complement pathway and synaptic gene transcription. DISCUSSION BD10-2 prevented APPL/S/Aβ-associated memory and LTP deficits, reduced abnormalities in synapse-related signaling and activity-dependent transcription of synaptic genes, and bolstered transcriptional changes associated with microglial immune response. HIGHLIGHTS Small molecule modulation of tropomyosin related kinase B (TrkB) and C (TrkC) restores long-term potentiation (LTP) and behavior in an Alzheimer's disease (AD) model. Modulation of TrkB and TrkC regulates synaptic activity-dependent transcription. TrkB and TrkC receptors are candidate targets for translational therapeutics. Electrophysiology combined with transcriptomics elucidates synaptic restoration. LTP identifies neuron and microglia AD-relevant human-mouse co-expression modules.
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Affiliation(s)
- Amira Latif‐Hernandez
- Department of Neurology & Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Tao Yang
- Department of Neurology & Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Robert R. Butler
- Department of Neurology & Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Patricia Moran Losada
- Department of Neurology & Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
- Wu Tsai Neurosciences Institute, Stanford UniversityStanfordCaliforniaUSA
| | - Paras S. Minhas
- Department of Neurology & Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Halle White
- Department of Neurology & Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Kevin C. Tran
- Department of Neurology & Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Harry Liu
- Department of Neurology & Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Danielle A. Simmons
- Department of Neurology & Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Vanessa Langness
- Department of Neurology & Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Katrin I. Andreasson
- Department of Neurology & Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
- Wu Tsai Neurosciences Institute, Stanford UniversityStanfordCaliforniaUSA
- Chan Zuckerberg BiohubSan FranciscoCaliforniaUSA
| | - Tony Wyss‐Coray
- Department of Neurology & Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
- Wu Tsai Neurosciences Institute, Stanford UniversityStanfordCaliforniaUSA
- The Phil and Penny Knight Initiative for Brain ResilienceStanford UniversityStanfordCaliforniaUSA
| | - Frank M. Longo
- Department of Neurology & Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
- Wu Tsai Neurosciences Institute, Stanford UniversityStanfordCaliforniaUSA
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Wakim JG, Spakowitz AJ. Physical modeling of nucleosome clustering in euchromatin resulting from interactions between epigenetic reader proteins. Proc Natl Acad Sci U S A 2024; 121:e2317911121. [PMID: 38900792 PMCID: PMC11214050 DOI: 10.1073/pnas.2317911121] [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: 10/14/2023] [Accepted: 04/15/2024] [Indexed: 06/22/2024] Open
Abstract
Euchromatin is an accessible phase of genetic material containing genes that encode proteins with increased expression levels. The structure of euchromatin in vitro has been described as a 30-nm fiber formed from ordered nucleosome arrays. However, recent advances in microscopy have revealed an in vivo euchromatin architecture that is much more disordered, characterized by variable-length linker DNA and sporadic nucleosome clusters. In this work, we develop a theoretical model to elucidate factors contributing to the disordered in vivo architecture of euchromatin. We begin by developing a 1D model of nucleosome positioning that captures the interactions between bound epigenetic reader proteins to predict the distribution of DNA linker lengths between adjacent nucleosomes. We then use the predicted linker lengths to construct 3D chromatin configurations consistent with the physical properties of DNA within the nucleosome array, and we evaluate the distribution of nucleosome cluster sizes in those configurations. Our model reproduces experimental cluster-size distributions, which are dramatically influenced by the local pattern of epigenetic marks and the concentration of reader proteins. Based on our model, we attribute the disordered arrangement of euchromatin to the heterogeneous binding of reader proteins and subsequent short-range interactions between bound reader proteins on adjacent nucleosomes. By replicating experimental results with our physics-based model, we propose a mechanism for euchromatin organization in the nucleus that impacts gene regulation and the maintenance of epigenetic marks.
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Affiliation(s)
- Joseph G. Wakim
- Department of Chemical Engineering, Stanford University, Stanford, CA94305
| | - Andrew J. Spakowitz
- Department of Chemical Engineering, Stanford University, Stanford, CA94305
- Department of Materials Science and Engineering, Stanford University, Stanford, CA94305
- Biophysics Program, Stanford University, Stanford, CA94305
- Department of Applied Physics, Stanford University, Stanford, CA94305
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3
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Very N, Boulet C, Gheeraert C, Berthier A, Johanns M, Bou Saleh M, Guille L, Bray F, Strub JM, Bobowski-Gerard M, Zummo FP, Vallez E, Molendi-Coste O, Woitrain E, Cianférani S, Montaigne D, Ntandja-Wandji LC, Dubuquoy L, Dubois-Chevalier J, Staels B, Lefebvre P, Eeckhoute J. O-GlcNAcylation controls pro-fibrotic transcriptional regulatory signaling in myofibroblasts. Cell Death Dis 2024; 15:391. [PMID: 38830870 PMCID: PMC11148087 DOI: 10.1038/s41419-024-06773-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 05/21/2024] [Accepted: 05/23/2024] [Indexed: 06/05/2024]
Abstract
Tissue injury causes activation of mesenchymal lineage cells into wound-repairing myofibroblasts (MFs), whose uncontrolled activity ultimately leads to fibrosis. Although this process is triggered by deep metabolic and transcriptional reprogramming, functional links between these two key events are not yet understood. Here, we report that the metabolic sensor post-translational modification O-linked β-D-N-acetylglucosaminylation (O-GlcNAcylation) is increased and required for myofibroblastic activation. Inhibition of protein O-GlcNAcylation impairs archetypal myofibloblast cellular activities including extracellular matrix gene expression and collagen secretion/deposition as defined in vitro and using ex vivo and in vivo murine liver injury models. Mechanistically, a multi-omics approach combining proteomic, epigenomic, and transcriptomic data mining revealed that O-GlcNAcylation controls the MF transcriptional program by targeting the transcription factors Basonuclin 2 (BNC2) and TEA domain transcription factor 4 (TEAD4) together with the Yes-associated protein 1 (YAP1) co-activator. Indeed, inhibition of protein O-GlcNAcylation impedes their stability leading to decreased functionality of the BNC2/TEAD4/YAP1 complex towards promoting activation of the MF transcriptional regulatory landscape. We found that this involves O-GlcNAcylation of BNC2 at Thr455 and Ser490 and of TEAD4 at Ser69 and Ser99. Altogether, this study unravels protein O-GlcNAcylation as a key determinant of myofibroblastic activation and identifies its inhibition as an avenue to intervene with fibrogenic processes.
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Affiliation(s)
- Ninon Very
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France
| | - Clémence Boulet
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France
| | - Céline Gheeraert
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France
| | - Alexandre Berthier
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France
| | - Manuel Johanns
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France
| | - Mohamed Bou Saleh
- Univ. Lille, Inserm, CHU Lille, U1286 - INFINITE - Institute for Translational Research in Inflammation, Lille, France
| | - Loïc Guille
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France
| | - Fabrice Bray
- Miniaturization for Synthesis, Analysis & Proteomics, UAR 3290, CNRS, University of Lille, Villeneuve d'Ascq Cedex, France
| | - Jean-Marc Strub
- Laboratoire de Spectrométrie de Masse BioOrganique, CNRS UMR7178, Univ. Strasbourg, IPHC, Infrastructure Nationale de Protéomique ProFI - FR2048, Strasbourg, France
| | - Marie Bobowski-Gerard
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France
| | - Francesco P Zummo
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France
| | - Emmanuelle Vallez
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France
| | - Olivier Molendi-Coste
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France
| | - Eloise Woitrain
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France
| | - Sarah Cianférani
- Laboratoire de Spectrométrie de Masse BioOrganique, CNRS UMR7178, Univ. Strasbourg, IPHC, Infrastructure Nationale de Protéomique ProFI - FR2048, Strasbourg, France
| | - David Montaigne
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France
| | - Line Carolle Ntandja-Wandji
- Univ. Lille, Inserm, CHU Lille, U1286 - INFINITE - Institute for Translational Research in Inflammation, Lille, France
| | - Laurent Dubuquoy
- Univ. Lille, Inserm, CHU Lille, U1286 - INFINITE - Institute for Translational Research in Inflammation, Lille, France
| | | | - Bart Staels
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France
| | - Philippe Lefebvre
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France
| | - Jérôme Eeckhoute
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1011-EGID, Lille, France.
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Conery M, Pippin JA, Wagley Y, Trang K, Pahl MC, Villani DA, Favazzo LJ, Ackert-Bicknell CL, Zuscik MJ, Katsevich E, Wells AD, Zemel BS, Voight BF, Hankenson KD, Chesi A, Grant SF. GWAS-informed data integration and non-coding CRISPRi screen illuminate genetic etiology of bone mineral density. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.19.585778. [PMID: 38562830 PMCID: PMC10983984 DOI: 10.1101/2024.03.19.585778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Over 1,100 independent signals have been identified with genome-wide association studies (GWAS) for bone mineral density (BMD), a key risk factor for mortality-increasing fragility fractures; however, the effector gene(s) for most remain unknown. Informed by a variant-to-gene mapping strategy implicating 89 non-coding elements predicted to regulate osteoblast gene expression at BMD GWAS loci, we executed a single-cell CRISPRi screen in human fetal osteoblast 1.19 cells (hFOBs). The BMD relevance of hFOBs was supported by heritability enrichment from cross-cell type stratified LD-score regression involving 98 cell types grouped into 15 tissues. 24 genes showed perturbation in the screen, with four (ARID5B, CC2D1B, EIF4G2, and NCOA3) exhibiting consistent effects upon siRNA knockdown on three measures of osteoblast maturation and mineralization. Lastly, additional heritability enrichments, genetic correlations, and multi-trait fine-mapping revealed that many BMD GWAS signals are pleiotropic and likely mediate their effects via non-bone tissues that warrant attention in future screens.
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Affiliation(s)
- Mitchell Conery
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Graduate Group in Genomics and Computational Biology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - James A. Pippin
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Yadav Wagley
- Department of Orthopaedic Surgery, University of Michigan Medical School, Ann Arbor, MI 48109
| | - Khanh Trang
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Matthew C. Pahl
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - David A. Villani
- Colorado Program for Musculoskeletal Research, University of Colorado Anschutz Medical Campus, Aurora, CO
- Cell Biology, Stems Cells and Development Ph.D. Program, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Lacey J. Favazzo
- Colorado Program for Musculoskeletal Research, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Orthopedics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- University of Colorado Interdisciplinary Joint Biology Program, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Cheryl L. Ackert-Bicknell
- Colorado Program for Musculoskeletal Research, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Orthopedics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- University of Colorado Interdisciplinary Joint Biology Program, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Michael J. Zuscik
- Colorado Program for Musculoskeletal Research, University of Colorado Anschutz Medical Campus, Aurora, CO
- Department of Orthopedics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, United States
- University of Colorado Interdisciplinary Joint Biology Program, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Eugene Katsevich
- Department of Statistics and Data Science, The Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Andrew D. Wells
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Babette S. Zemel
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Division of Gastroenterology, Hepatology and Nutrition, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
| | - Benjamin F. Voight
- Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute for Translational Medicine and Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kurt D. Hankenson
- Department of Orthopaedic Surgery, University of Michigan Medical School, Ann Arbor, MI 48109
| | - Alessandra Chesi
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Struan F.A. Grant
- Center for Spatial and Functional Genomics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Division of Human Genetics, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Institute of Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Division of Endocrinology and Diabetes, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
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Tullius TW, Isaac RS, Ranchalis J, Dubocanin D, Churchman LS, Stergachis AB. RNA polymerases reshape chromatin and coordinate transcription on individual fibers. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.22.573133. [PMID: 38187631 PMCID: PMC10769320 DOI: 10.1101/2023.12.22.573133] [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
During eukaryotic transcription, RNA polymerases must initiate and pause within a crowded, complex environment, surrounded by nucleosomes and other transcriptional activity. This environment creates a spatial arrangement along individual chromatin fibers ripe for both competition and coordination, yet these relationships remain largely unknown owing to the inherent limitations of traditional structural and sequencing methodologies. To address these limitations, we employed long-read chromatin fiber sequencing (Fiber-seq) to visualize RNA polymerases within their native chromatin context at single-molecule and near single-nucleotide resolution along up to 30 kb fibers. We demonstrate that Fiber-seq enables the identification of single-molecule RNA Polymerase (Pol) II and III transcription associated footprints, which, in aggregate, mirror bulk short-read sequencing-based measurements of transcription. We show that Pol II pausing destabilizes downstream nucleosomes, with frequently paused genes maintaining a short-term memory of these destabilized nucleosomes. Furthermore, we demonstrate pervasive direct coordination and anti-coordination between nearby Pol II genes, Pol III genes, transcribed enhancers, and insulator elements. This coordination is largely limited to spatially organized elements within 5 kb of each other, implicating short-range chromatin environments as a predominant determinant of coordinated polymerase initiation. Overall, transcription initiation reshapes surrounding nucleosome architecture and coordinates nearby transcriptional machinery along individual chromatin fibers.
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Affiliation(s)
- Thomas W Tullius
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - R Stefan Isaac
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Jane Ranchalis
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA
| | - Danilo Dubocanin
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA
| | - L Stirling Churchman
- Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA 02115, USA
| | - Andrew B Stergachis
- Division of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA
- Department of Genome Sciences, University of Washington, Seattle, WA
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6
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Park SG, Kim WJ, Moon JI, Kim KT, Ryoo HM. MESIA: multi-epigenome sample integration approach for precise peak calling. Sci Rep 2023; 13:20859. [PMID: 38012291 PMCID: PMC10681995 DOI: 10.1038/s41598-023-47948-2] [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: 09/18/2023] [Accepted: 11/20/2023] [Indexed: 11/29/2023] Open
Abstract
The assay for transposase-accessible chromatin with sequencing (ATAC-seq) is the most widely used method for measuring chromatin accessibility. Researchers have included multi-sample replication in ATAC-seq experimental designs. In epigenomic analysis, researchers should measure subtle changes in the peak by considering the read depth of individual samples. It is important to determine whether the peaks of each replication have an integrative meaning for the region of interest observed during multi-sample integration. We developed multi-epigenome sample integration approach for precise peak calling (MESIA), which integrates replication with high representativeness and reproducibility in multi-sample replication and determines the optimal peak. After identifying the reproducibility between all replications, our method integrated multiple samples determined as representative replicates. MESIA detected 6.06 times more peaks, and the value of the peaks was 1.32 times higher than the previously used method. MESIA is a shell-script-based open-source code that provides researchers involved in the epigenome with comprehensive insights.
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Grants
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 Korean government (MSIT)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 Korean government (MSIT)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 Korean government (MSIT)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 Korean government (MSIT)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 Korean government (MSIT)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 National Research Foundation of Korea (NRF)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 National Research Foundation of Korea (NRF)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 National Research Foundation of Korea (NRF)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 National Research Foundation of Korea (NRF)
- RS-2023-00207971, 2020R1A4A1019423, 2022R1I1A1A01062894 and 2021R1C1C2095130 National Research Foundation of Korea (NRF)
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Affiliation(s)
- Seung Gwa Park
- Department of Molecular Genetics & Dental Pharmacology, School of Dentistry and Dental Multiomics Center, Dental Research Institute, Seoul National University, Seoul, South Korea
- Epigenetic Regulation of Aged Skeleto-Muscular System Laboratory, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, South Korea
| | - Woo-Jin Kim
- Department of Molecular Genetics & Dental Pharmacology, School of Dentistry and Dental Multiomics Center, Dental Research Institute, Seoul National University, Seoul, South Korea
- Epigenetic Regulation of Aged Skeleto-Muscular System Laboratory, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, South Korea
| | - Jae-I Moon
- Department of Molecular Genetics & Dental Pharmacology, School of Dentistry and Dental Multiomics Center, Dental Research Institute, Seoul National University, Seoul, South Korea
- Epigenetic Regulation of Aged Skeleto-Muscular System Laboratory, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, South Korea
| | - Ki-Tae Kim
- Department of Molecular Genetics & Dental Pharmacology, School of Dentistry and Dental Multiomics Center, Dental Research Institute, Seoul National University, Seoul, South Korea.
- Epigenetic Regulation of Aged Skeleto-Muscular System Laboratory, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, South Korea.
| | - Hyun-Mo Ryoo
- Department of Molecular Genetics & Dental Pharmacology, School of Dentistry and Dental Multiomics Center, Dental Research Institute, Seoul National University, Seoul, South Korea.
- Epigenetic Regulation of Aged Skeleto-Muscular System Laboratory, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, South Korea.
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7
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van der Sande M, Frölich S, Schäfers T, Smits JG, Snabel RR, Rinzema S, van Heeringen SJ. Seq2science: an end-to-end workflow for functional genomics analysis. PeerJ 2023; 11:e16380. [PMID: 38025697 PMCID: PMC10656911 DOI: 10.7717/peerj.16380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2023] [Accepted: 10/09/2023] [Indexed: 12/01/2023] Open
Abstract
Sequencing databases contain enormous amounts of functional genomics data, making them an extensive resource for genome-scale analysis. Reanalyzing publicly available data, and integrating it with new, project-specific data sets, can be invaluable. With current technologies, genomic experiments have become feasible for virtually any species of interest. However, using and integrating this data comes with its challenges, such as standardized and reproducible analysis. Seq2science is a multi-purpose workflow that covers preprocessing, quality control, visualization, and analysis of functional genomics sequencing data. It facilitates the downloading of sequencing data from all major databases, including NCBI SRA, EBI ENA, DDBJ, GSA, and ENCODE. Furthermore, it automates the retrieval of any genome assembly available from Ensembl, NCBI, and UCSC. It has been tested on a variety of species, and includes diverse workflows such as ATAC-, RNA-, and ChIP-seq. It consists of both generic as well as advanced steps, such as differential gene expression or peak accessibility analysis and differential motif analysis. Seq2science is built on the Snakemake workflow language and thus can be run on a range of computing infrastructures. It is available at https://github.com/vanheeringen-lab/seq2science.
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Affiliation(s)
- Maarten van der Sande
- Molecular Developmental Biology, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Siebren Frölich
- Molecular Developmental Biology, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Tilman Schäfers
- Molecular Developmental Biology, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Jos G.A. Smits
- Molecular Developmental Biology, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Rebecca R. Snabel
- Molecular Developmental Biology, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Sybren Rinzema
- Molecular Developmental Biology, Radboud University Nijmegen, Nijmegen, the Netherlands
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8
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Wang M, Sreenivas P, Sunkel BD, Wang L, Ignatius M, Stanton B. The 3D chromatin landscape of rhabdomyosarcoma. NAR Cancer 2023; 5:zcad028. [PMID: 37325549 PMCID: PMC10261698 DOI: 10.1093/narcan/zcad028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 04/27/2023] [Accepted: 05/24/2023] [Indexed: 06/17/2023] Open
Abstract
Rhabdomyosarcoma (RMS) is a pediatric soft tissue cancer with a lack of precision therapy options for patients. We hypothesized that with a general paucity of known mutations in RMS, chromatin structural driving mechanisms are essential for tumor proliferation. Thus, we carried out high-depth in situ Hi-C in representative cell lines and patient-derived xenografts (PDXs) to define chromatin architecture in each major RMS subtype. We report a comprehensive 3D chromatin structural analysis and characterization of fusion-positive (FP-RMS) and fusion-negative RMS (FN-RMS). We have generated spike-in in situ Hi-C chromatin interaction maps for the most common FP-RMS and FN-RMS cell lines and compared our data with PDX models. In our studies, we uncover common and distinct structural elements in large Mb-scale chromatin compartments, tumor-essential genes within variable topologically associating domains and unique patterns of structural variation. Our high-depth chromatin interactivity maps and comprehensive analyses provide context for gene regulatory events and reveal functional chromatin domains in RMS.
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Affiliation(s)
- Meng Wang
- Nationwide Children’s Hospital, Center for Childhood Cancer, Columbus, OH 43205, USA
| | - Prethish Sreenivas
- Greehey Children’s Cancer Research Institute, Department of Molecular Medicine, University of Texas Health Science Center, San Antonio, TX 78229, USA
| | - Benjamin D Sunkel
- Nationwide Children’s Hospital, Center for Childhood Cancer, Columbus, OH 43205, USA
| | - Long Wang
- Greehey Children’s Cancer Research Institute, Department of Molecular Medicine, University of Texas Health Science Center, San Antonio, TX 78229, USA
| | - Myron Ignatius
- Greehey Children’s Cancer Research Institute, Department of Molecular Medicine, University of Texas Health Science Center, San Antonio, TX 78229, USA
| | - Benjamin Z Stanton
- Nationwide Children’s Hospital, Center for Childhood Cancer, Columbus, OH 43205, USA
- Department of Pediatrics, The Ohio State University College of Medicine, Columbus, OH 43205, USA
- Department of Biological Chemistry and Pharmacology, The Ohio State University College of Medicine, Columbus, OH 43210, USA
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9
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Gosai SJ, Castro RI, Fuentes N, Butts JC, Kales S, Noche RR, Mouri K, Sabeti PC, Reilly SK, Tewhey R. Machine-guided design of synthetic cell type-specific cis-regulatory elements. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.08.552077. [PMID: 37609287 PMCID: PMC10441439 DOI: 10.1101/2023.08.08.552077] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
Cis-regulatory elements (CREs) control gene expression, orchestrating tissue identity, developmental timing, and stimulus responses, which collectively define the thousands of unique cell types in the body. While there is great potential for strategically incorporating CREs in therapeutic or biotechnology applications that require tissue specificity, there is no guarantee that an optimal CRE for an intended purpose has arisen naturally through evolution. Here, we present a platform to engineer and validate synthetic CREs capable of driving gene expression with programmed cell type specificity. We leverage innovations in deep neural network modeling of CRE activity across three cell types, efficient in silico optimization, and massively parallel reporter assays (MPRAs) to design and empirically test thousands of CREs. Through in vitro and in vivo validation, we show that synthetic sequences outperform natural sequences from the human genome in driving cell type-specific expression. Synthetic sequences leverage unique sequence syntax to promote activity in the on-target cell type and simultaneously reduce activity in off-target cells. Together, we provide a generalizable framework to prospectively engineer CREs and demonstrate the required literacy to write regulatory code that is fit-for-purpose in vivo across vertebrates.
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Affiliation(s)
- SJ Gosai
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Graduate Program in Biological and Biomedical Science, Boston MA
- Department Of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - RI Castro
- The Jackson Laboratory, Bar Harbor, ME, USA
| | - N Fuentes
- The Jackson Laboratory, Bar Harbor, ME, USA
- Harvard College, Harvard University, Cambridge, MA, USA
| | - JC Butts
- The Jackson Laboratory, Bar Harbor, ME, USA
- Graduate School of Biomedical Sciences and Engineering, University of Maine, Orono, ME, USA
| | - S Kales
- The Jackson Laboratory, Bar Harbor, ME, USA
| | - RR Noche
- Department of Comparative Medicine, Yale School of Medicine, New Haven, CT, USA
- Yale Zebrafish Research Core, Yale School of Medicine, New Haven, CT, USA
| | - K Mouri
- The Jackson Laboratory, Bar Harbor, ME, USA
| | - PC Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department Of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - SK Reilly
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
| | - R 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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10
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Bao Y, Wei Y, Liu Y, Gao J, Cheng S, Liu G, You Q, Liu P, Lu Q, Li P, Zhang S, Hu N, Han Y, Liu S, Wu Y, Yang Q, Li Z, Ao G, Liu F, Wang K, Jiang J, Zhang T, Zhang W, Peng R. Genome-wide chromatin accessibility landscape and dynamics of transcription factor networks during ovule and fiber development in cotton. BMC Biol 2023; 21:165. [PMID: 37525156 PMCID: PMC10391996 DOI: 10.1186/s12915-023-01665-4] [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: 11/24/2022] [Accepted: 07/18/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND The development of cotton fiber is regulated by the orchestrated binding of regulatory proteins to cis-regulatory elements associated with developmental genes. The cis-trans regulatory dynamics occurred throughout the course of cotton fiber development are elusive. Here we generated genome-wide high-resolution DNase I hypersensitive sites (DHSs) maps to understand the regulatory mechanisms of cotton ovule and fiber development. RESULTS We generated DNase I hypersensitive site (DHS) profiles from cotton ovules at 0 and 3 days post anthesis (DPA) and fibers at 8, 12, 15, and 18 DPA. We obtained a total of 1185 million reads and identified a total of 199,351 DHSs through ~ 30% unique mapping reads. It should be noted that more than half of DNase-seq reads mapped multiple genome locations and were not analyzed in order to achieve a high specificity of peak profile and to avoid bias from repetitive genomic regions. Distinct chromatin accessibilities were observed in the ovules (0 and 3 DPA) compared to the fiber elongation stages (8, 12, 15, and 18 DPA). Besides, the chromatin accessibility during ovules was particularly elevated in genomic regions enriched with transposable elements (TEs) and genes in TE-enriched regions were involved in ovule cell division. We analyzed cis-regulatory modules and revealed the influence of hormones on fiber development from the regulatory divergence of transcription factor (TF) motifs. Finally, we constructed a reliable regulatory network of TFs related to ovule and fiber development based on chromatin accessibility and gene co-expression network. From this network, we discovered a novel TF, WRKY46, which may shape fiber development by regulating the lignin content. CONCLUSIONS Our results not only reveal the contribution of TEs in fiber development, but also predict and validate the TFs related to fiber development, which will benefit the research of cotton fiber molecular breeding.
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Affiliation(s)
- Yu Bao
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Agricultural College of Yangzhou University, Yangzhou, 225009, China
- Anyang Institute of Technology, Anyang, Henan, 455000, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education/Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, 225009, China
| | - Yangyang Wei
- Anyang Institute of Technology, Anyang, Henan, 455000, China
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Anyang, Henan, 455000, China
| | - Yuling Liu
- Anyang Institute of Technology, Anyang, Henan, 455000, China
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Anyang, Henan, 455000, China
| | - Jingjing Gao
- National Key Laboratory for Crop Genetics and Germplasm Enhancement and Utilization, Collaborative Innovation Center for Modern Crop Production Co-Sponsored By Province and Ministry (CIC-MCP), Nanjing Agricultural University, No.1 Weigang, Nanjing, 210095, Jiangsu, China
| | - Shuang Cheng
- Anyang Institute of Technology, Anyang, Henan, 455000, China
- Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Guanqing Liu
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Agricultural College of Yangzhou University, Yangzhou, 225009, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education/Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, 225009, China
| | - Qi You
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Agricultural College of Yangzhou University, Yangzhou, 225009, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education/Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, 225009, China
| | - Peng Liu
- Institutes of Agricultural Science and Technology Development, Joint International Research Laboratory of Agriculture and Agri-Product Safety, Yangzhou University, Yangzhou, 225009, China
| | - Quanwei Lu
- Anyang Institute of Technology, Anyang, Henan, 455000, China
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Anyang, Henan, 455000, China
| | - Pengtao Li
- Anyang Institute of Technology, Anyang, Henan, 455000, China
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Anyang, Henan, 455000, China
| | - Shulin Zhang
- Anyang Institute of Technology, Anyang, Henan, 455000, China
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Anyang, Henan, 455000, China
| | - Nan Hu
- Anyang Institute of Technology, Anyang, Henan, 455000, China
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Anyang, Henan, 455000, China
| | - Yangshuo Han
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Agricultural College of Yangzhou University, Yangzhou, 225009, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education/Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, 225009, China
| | - Shuo Liu
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Agricultural College of Yangzhou University, Yangzhou, 225009, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education/Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, 225009, China
| | - Yuechao Wu
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Agricultural College of Yangzhou University, Yangzhou, 225009, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education/Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, 225009, China
| | - Qingqing Yang
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Agricultural College of Yangzhou University, Yangzhou, 225009, China
- Key Laboratory of Plant Functional Genomics of the Ministry of Education/Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, 225009, China
| | - Zhaoguo Li
- Anyang Institute of Technology, Anyang, Henan, 455000, China
- Zhengzhou University, Zhengzhou, Henan, 450001, China
| | - Guowei Ao
- Anyang Institute of Technology, Anyang, Henan, 455000, China
| | - Fang Liu
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Anyang, Henan, 455000, China
| | - Kunbo Wang
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Anyang, Henan, 455000, China
| | - Jiming Jiang
- Department of Plant Biology, Michigan State University, East Lansing, MI, USA
- Department of Horticulture, Michigan State University, East Lansing, MI, USA
- Michigan State University AgBioResearch, East Lansing, MI, USA
| | - Tao Zhang
- Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding/Jiangsu Key Laboratory of Crop Genetics and Physiology/Jiangsu Co-Innovation Center for Modern Production Technology of Grain Crops, Agricultural College of Yangzhou University, Yangzhou, 225009, China.
- Key Laboratory of Plant Functional Genomics of the Ministry of Education/Joint International Research Laboratory of Agriculture and Agri-Product Safety of Ministry of Education of China, Yangzhou University, Yangzhou, 225009, China.
| | - Wenli Zhang
- National Key Laboratory for Crop Genetics and Germplasm Enhancement and Utilization, Collaborative Innovation Center for Modern Crop Production Co-Sponsored By Province and Ministry (CIC-MCP), Nanjing Agricultural University, No.1 Weigang, Nanjing, 210095, Jiangsu, China.
| | - Renhai Peng
- Anyang Institute of Technology, Anyang, Henan, 455000, China.
- Research Base, Anyang Institute of Technology, State Key Laboratory of Cotton Biology, Anyang, Henan, 455000, China.
- Zhengzhou University, Zhengzhou, Henan, 450001, China.
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11
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Zeng J, Nguyen MA, Liu P, Ferreira da Silva L, Lin LY, Justus DG, Petri K, Clement K, Porter SN, Verma A, Neri NR, Rosanwo T, Ciuculescu MF, Abriss D, Mintzer E, Maitland SA, Demirci S, Tisdale JF, Williams DA, Zhu LJ, Pruett-Miller SM, Pinello L, Joung JK, Pattanayak V, Manis JP, Armant M, Pellin D, Brendel C, Wolfe SA, Bauer DE. Gene editing without ex vivo culture evades genotoxicity in human hematopoietic stem cells. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.27.542323. [PMID: 37292647 PMCID: PMC10245949 DOI: 10.1101/2023.05.27.542323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Gene editing the BCL11A erythroid enhancer is a validated approach to fetal hemoglobin (HbF) induction for β-hemoglobinopathy therapy, though heterogeneity in edit allele distribution and HbF response may impact its safety and efficacy. Here we compared combined CRISPR-Cas9 endonuclease editing of the BCL11A +58 and +55 enhancers with leading gene modification approaches under clinical investigation. We found that combined targeting of the BCL11A +58 and +55 enhancers with 3xNLS-SpCas9 and two sgRNAs resulted in superior HbF induction, including in engrafting erythroid cells from sickle cell disease (SCD) patient xenografts, attributable to simultaneous disruption of core half E-box/GATA motifs at both enhancers. We corroborated prior observations that double strand breaks (DSBs) could produce unintended on- target outcomes in hematopoietic stem and progenitor cells (HSPCs) such as long deletions and centromere-distal chromosome fragment loss. We show these unintended outcomes are a byproduct of cellular proliferation stimulated by ex vivo culture. Editing HSPCs without cytokine culture bypassed long deletion and micronuclei formation while preserving efficient on-target editing and engraftment function. These results indicate that nuclease editing of quiescent hematopoietic stem cells (HSCs) limits DSB genotoxicity while maintaining therapeutic potency and encourages efforts for in vivo delivery of nucleases to HSCs.
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