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Yen A, Chen X, Skinner DD, Leti F, Crosby M, Hoisington-Lopez J, Wu Y, Chen J, Mitra RD, Dougherty JD. MYT1L deficiency impairs excitatory neuron trajectory during cortical development. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.06.583632. [PMID: 38496654 PMCID: PMC10942489 DOI: 10.1101/2024.03.06.583632] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Mutations that reduce the function of MYT1L, a neuron-specific transcription factor, are associated with a syndromic neurodevelopmental disorder. Furthermore, MYT1L is routinely used as a proneural factor in fibroblast-to-neuron transdifferentiation. MYT1L has been hypothesized to play a role in the trajectory of neuronal specification and subtype specific maturation, but this hypothesis has not been directly tested, nor is it clear which neuron types are most impacted by MYT1L loss. In this study, we profiled 313,335 nuclei from the forebrains of wild-type and MYT1L-deficient mice at two developmental stages: E14 at the peak of neurogenesis and P21, when neurogenesis is complete, to examine the role of MYT1L levels in the trajectory of neuronal development. We found that MYT1L deficiency significantly disrupted the relative proportion of cortical excitatory neurons at E14 and P21. Significant changes in gene expression were largely concentrated in excitatory neurons, suggesting that transcriptional effects of MYT1L deficiency are largely due to disruption of neuronal maturation programs. Most effects on gene expression were cell autonomous and persistent through development. In addition, while MYT1L can both activate and repress gene expression, the repressive effects were most sensitive to haploinsufficiency, and thus more likely mediate MYT1L syndrome. These findings illuminate the intricate role of MYT1L in orchestrating gene expression dynamics during neuronal development, providing insights into the molecular underpinnings of MYT1L syndrome.
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Affiliation(s)
- Allen Yen
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Xuhua Chen
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO, USA
| | | | | | - MariaLynn Crosby
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO, USA
- DNA Sequencing and Innovation Lab, Washington University School of Medicine, Saint Louis, MO
| | - Jessica Hoisington-Lopez
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO, USA
- DNA Sequencing and Innovation Lab, Washington University School of Medicine, Saint Louis, MO
| | - Yizhe Wu
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Jiayang Chen
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
| | - Robi D. Mitra
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Joseph D. Dougherty
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, USA
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, Saint Louis, MO, USA
- Lead contact
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2
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Guo J, Zhang W, Chen X, Yen A, Chen L, Shively CA, Li D, Wang T, Dougherty JD, Mitra RD. Pycallingcards: an integrated environment for visualizing, analyzing, and interpreting Calling Cards data. Bioinformatics 2024; 40:btae070. [PMID: 38323623 PMCID: PMC10881108 DOI: 10.1093/bioinformatics/btae070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Revised: 12/25/2023] [Accepted: 02/05/2024] [Indexed: 02/08/2024] Open
Abstract
MOTIVATION Unraveling the transcriptional programs that control how cells divide, differentiate, and respond to their environments requires a precise understanding of transcription factors' (TFs) DNA-binding activities. Calling cards (CC) technology uses transposons to capture transient TF binding events at one instant in time and then read them out at a later time. This methodology can also be used to simultaneously measure TF binding and mRNA expression from single-cell CC and to record and integrate TF binding events across time in any cell type of interest without the need for purification. Despite these advantages, there has been a lack of dedicated bioinformatics tools for the detailed analysis of CC data. RESULTS We introduce Pycallingcards, a comprehensive Python module specifically designed for the analysis of single-cell and bulk CC data across multiple species. Pycallingcards introduces two innovative peak callers, CCcaller and MACCs, enhancing the accuracy and speed of pinpointing TF binding sites from CC data. Pycallingcards offers a fully integrated environment for data visualization, motif finding, and comparative analysis with RNA-seq and ChIP-seq datasets. To illustrate its practical application, we have reanalyzed previously published mouse cortex and glioblastoma datasets. This analysis revealed novel cell-type-specific binding sites and potential sex-linked TF regulators, furthering our understanding of TF binding and gene expression relationships. Thus, Pycallingcards, with its user-friendly design and seamless interface with the Python data science ecosystem, stands as a critical tool for advancing the analysis of TF functions via CC data. AVAILABILITY AND IMPLEMENTATION Pycallingcards can be accessed on the GitHub repository: https://github.com/The-Mitra-Lab/pycallingcards.
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Affiliation(s)
- Juanru Guo
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
| | - Wenjin Zhang
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
| | - Xuhua Chen
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
| | - Allen Yen
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Department of Psychiatry, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
| | - Lucy Chen
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
| | - Christian A Shively
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
| | - Daofeng Li
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
| | - Ting Wang
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- McDonnell Genome Institute, , Washington University in St. Louis School of Medicine, Saint Louis, MO, 63110, United States
| | - Joseph D Dougherty
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Department of Psychiatry, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, Saint Louis, MO 63108, United States
| | - Robi D Mitra
- Department of Genetics, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- Edison Family Center for Genome Sciences and Systems Biology, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, United States
- McDonnell Genome Institute, , Washington University in St. Louis School of Medicine, Saint Louis, MO, 63110, United States
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, Saint Louis, MO 63108, United States
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3
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Lagunas T, Plassmeyer SP, Fischer AD, Friedman RZ, Rieger MA, Selmanovic D, Sarafinovska S, Sol YK, Kasper MJ, Fass SB, Aguilar Lucero AF, An JY, Sanders SJ, Cohen BA, Dougherty JD. A Cre-dependent massively parallel reporter assay allows for cell-type specific assessment of the functional effects of non-coding elements in vivo. Commun Biol 2023; 6:1151. [PMID: 37953348 PMCID: PMC10641075 DOI: 10.1038/s42003-023-05483-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: 02/15/2023] [Accepted: 10/18/2023] [Indexed: 11/14/2023] Open
Abstract
The function of regulatory elements is highly dependent on the cellular context, and thus for understanding the function of elements associated with psychiatric diseases these would ideally be studied in neurons in a living brain. Massively Parallel Reporter Assays (MPRAs) are molecular genetic tools that enable functional screening of hundreds of predefined sequences in a single experiment. These assays have not yet been adapted to query specific cell types in vivo in a complex tissue like the mouse brain. Here, using a test-case 3'UTR MPRA library with genomic elements containing variants from autism patients, we developed a method to achieve reproducible measurements of element effects in vivo in a cell type-specific manner, using excitatory cortical neurons and striatal medium spiny neurons as test cases. This targeted technique should enable robust, functional annotation of genetic elements in the cellular contexts most relevant to psychiatric disease.
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Affiliation(s)
- Tomas Lagunas
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Stephen P Plassmeyer
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Anthony D Fischer
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Ryan Z Friedman
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Michael A Rieger
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Din Selmanovic
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Simona Sarafinovska
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Yvette K Sol
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Michael J Kasper
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Stuart B Fass
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Alessandra F Aguilar Lucero
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neuroscience, University of California San Francisco, San Francisco, CA, 94518, USA
| | - Joon-Yong An
- Department of Integrated Biomedical and Life Science, Korea University, Seoul, 02841, Republic of Korea
- School of Biosystem and Biomedical Science, College of Health Science, Korea University, Seoul, 02841, Republic of Korea
| | - Stephan J Sanders
- Department of Psychiatry and Behavioral Sciences, UCSF Weill Institute for Neuroscience, University of California San Francisco, San Francisco, CA, 94518, USA
| | - Barak A Cohen
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA
| | - Joseph D Dougherty
- Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO, 63108, USA.
- Department of Psychiatry, Washington University School of Medicine., 660 S. Euclid Ave, Saint Louis, MO, 63108, USA.
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4
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Longet S, Paul S. Pivotal role of tissue-resident memory lymphocytes in the control of mucosal infections: can mucosal vaccination induce protective tissue-resident memory T and B cells? Front Immunol 2023; 14:1216402. [PMID: 37753095 PMCID: PMC10518612 DOI: 10.3389/fimmu.2023.1216402] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 08/28/2023] [Indexed: 09/28/2023] Open
Affiliation(s)
- Stephanie Longet
- Centre International de Recherche en Infectiologie, Team Groupe sur l'immunité des muqueuses et agents pathogènes (GIMAP), Université Jean Monnet, Université Claude Bernard Lyon, Inserm, Saint-Etienne, France
| | - Stephane Paul
- Centre International de Recherche en Infectiologie, Team Groupe sur l'immunité des muqueuses et agents pathogènes (GIMAP), Université Jean Monnet, Université Claude Bernard Lyon, Inserm, Saint-Etienne, France
- Centre d'investigation clinique (CIC) 1408 Inserm Vaccinology, University Hospital of Saint-Etienne, Saint-Etienne, France
- Immunology Department, iBiothera Reference Center, University Hospital of Saint-Etienne, Saint-Etienne, France
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5
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Yen A, Mateusiak C, Sarafinovska S, Gachechiladze MA, Guo J, Chen X, Moudgil A, Cammack AJ, Hoisington-Lopez J, Crosby M, Brent MR, Mitra RD, Dougherty JD. Calling Cards: A Customizable Platform to Longitudinally Record Protein-DNA Interactions Over Time in Cells and Tissues. Curr Protoc 2023; 3:e883. [PMID: 37755132 PMCID: PMC10627244 DOI: 10.1002/cpz1.883] [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: 09/28/2023]
Abstract
Calling Cards is a platform technology to record a cumulative history of transient protein-DNA interactions in the genome of genetically targeted cell types. The record of these interactions is recovered by next-generation sequencing. Compared with other genomic assays, readouts of which provide a snapshot at the time of harvest, Calling Cards enables correlation of historical molecular states to eventual outcomes or phenotypes. To achieve this, Calling Cards uses the piggyBac transposase to insert self-reporting transposon "Calling Cards" into the genome, leaving permanent marks at interaction sites. Calling Cards can be deployed in a variety of in vitro and in vivo biological systems to study gene regulatory networks involved in development, aging, and disease. Out of the box, it assesses enhancer usage but can be adapted to profile-specific transcription factor (TF) binding with custom TF-piggyBac fusion proteins. The Calling Cards workflow has five main stages: delivery of Calling Cards reagents, sample preparation, library preparation, sequencing, and data analysis. Here, we first present a comprehensive guide for experimental design, reagent selection, and optional customization of the platform to study additional TFs. Then, we provide an updated protocol for the five steps, using reagents that improve throughput and decrease costs, including an overview of a newly deployed computational pipeline. This protocol is designed for users with basic molecular biology experience to process samples into sequencing libraries in 2 days. Familiarity with bioinformatic analysis and command line tools is required to set up the pipeline in a high-performance computing environment and to conduct downstream analyses. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Preparation and delivery of Calling Cards reagents Support Protocol 1: Next-generation sequencing quantification of barcode distribution within self-reporting transposon plasmid pool and adeno-associated virus genome Basic Protocol 2: Sample collection and RNA purification Support Protocol 2: Library density quantitative PCR Basic Protocol 3: Sequencing library preparation Basic Protocol 4: Library pooling and sequencing Basic Protocol 5: Data analysis.
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Affiliation(s)
- Allen Yen
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Chase Mateusiak
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Simona Sarafinovska
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Mariam A. Gachechiladze
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Juanru Guo
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Xuhua Chen
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Arnav Moudgil
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Alexander J. Cammack
- Department of Neurology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Jessica Hoisington-Lopez
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - MariaLynn Crosby
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Michael R. Brent
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Computer Science and Engineering, Washington University, Saint Louis, MO 63130
| | - Robi D. Mitra
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Joseph D. Dougherty
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, Saint Louis, MO 63110
- Lead contact
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6
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Yen A, Mateusiak C, Sarafinovska S, Gachechiladze MA, Guo J, Chen X, Moudgil A, Cammack AJ, Hoisington-Lopez J, Crosby M, Brent MR, Mitra RD, Dougherty JD. Calling Cards: a customizable platform to longitudinally record protein-DNA interactions over time in cells and tissues. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.07.544098. [PMID: 37333130 PMCID: PMC10274760 DOI: 10.1101/2023.06.07.544098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Calling Cards is a platform technology to record a cumulative history of transient protein-DNA interactions in the genome of genetically targeted cell types. The record of these interactions is recovered by next generation sequencing. Compared to other genomic assays, whose readout provides a snapshot at the time of harvest, Calling Cards enables correlation of historical molecular states to eventual outcomes or phenotypes. To achieve this, Calling Cards uses the piggyBac transposase to insert self-reporting transposon (SRT) "Calling Cards" into the genome, leaving permanent marks at interaction sites. Calling Cards can be deployed in a variety of in vitro and in vivo biological systems to study gene regulatory networks involved in development, aging, and disease. Out of the box, it assesses enhancer usage but can be adapted to profile specific transcription factor binding with custom transcription factor (TF)-piggyBac fusion proteins. The Calling Cards workflow has five main stages: delivery of Calling Card reagents, sample preparation, library preparation, sequencing, and data analysis. Here, we first present a comprehensive guide for experimental design, reagent selection, and optional customization of the platform to study additional TFs. Then, we provide an updated protocol for the five steps, using reagents that improve throughput and decrease costs, including an overview of a newly deployed computational pipeline. This protocol is designed for users with basic molecular biology experience to process samples into sequencing libraries in 1-2 days. Familiarity with bioinformatic analysis and command line tools is required to set up the pipeline in a high-performance computing environment and to conduct downstream analyses. Basic Protocol 1: Preparation and delivery of Calling Cards reagentsBasic Protocol 2: Sample preparationBasic Protocol 3: Sequencing library preparationBasic Protocol 4: Library pooling and sequencingBasic Protocol 5: Data analysis.
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Affiliation(s)
- Allen Yen
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Chase Mateusiak
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Simona Sarafinovska
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Mariam A Gachechiladze
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
| | - Juanru Guo
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Xuhua Chen
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Arnav Moudgil
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Alexander J Cammack
- Department of Neurology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Jessica Hoisington-Lopez
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - MariaLynn Crosby
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Michael R Brent
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Computer Science and Engineering, Washington University, Saint Louis, MO 63130
| | - Robi D Mitra
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine, Saint Louis, MO 63110
| | - Joseph D Dougherty
- Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63110
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO 63110
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, Saint Louis, MO 63110
- Lead contact
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7
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Chen J, Fuhler NA, Noguchi KK, Dougherty JD. MYT1L is required for suppressing earlier neuronal development programs in the adult mouse brain. Genome Res 2023; 33:541-556. [PMID: 37100461 PMCID: PMC10234307 DOI: 10.1101/gr.277413.122] [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: 10/18/2022] [Accepted: 03/09/2023] [Indexed: 04/28/2023]
Abstract
In vitro studies indicate the neurodevelopmental disorder gene myelin transcription factor 1-like (MYT1L) suppresses non-neuronal lineage genes during fibroblast-to-neuron direct differentiation. However, MYT1L's molecular and cellular functions in the adult mammalian brain have not been fully characterized. Here, we found that MYT1L loss leads to up-regulated deep layer (DL) gene expression, corresponding to an increased ratio of DL/UL neurons in the adult mouse cortex. To define potential mechanisms, we conducted Cleavage Under Targets & Release Using Nuclease (CUT&RUN) to map MYT1L binding targets and epigenetic changes following MYT1L loss in mouse developing cortex and adult prefrontal cortex (PFC). We found MYT1L mainly binds to open chromatin, but with different transcription factor co-occupancies between promoters and enhancers. Likewise, multiomic data set integration revealed that, at promoters, MYT1L loss does not change chromatin accessibility but increases H3K4me3 and H3K27ac, activating both a subset of earlier neuronal development genes as well as Bcl11b, a key regulator for DL neuron development. Meanwhile, we discovered that MYT1L normally represses the activity of neurogenic enhancers associated with neuronal migration and neuronal projection development by closing chromatin structures and promoting removal of active histone marks. Further, we showed that MYT1L interacts with HDAC2 and transcriptional repressor SIN3B in vivo, providing potential mechanisms underlying repressive effects on histone acetylation and gene expression. Overall, our findings provide a comprehensive map of MYT1L binding in vivo and mechanistic insights into how MYT1L loss leads to aberrant activation of earlier neuronal development programs in the adult mouse brain.
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Affiliation(s)
- Jiayang Chen
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Nicole A Fuhler
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Kevin K Noguchi
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Joseph D Dougherty
- Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63110, USA;
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, Missouri 63108, USA
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8
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Lalli M, Yen A, Thopte U, Dong F, Moudgil A, Chen X, Milbrandt J, Dougherty JD, Mitra RD. Measuring transcription factor binding and gene expression using barcoded self-reporting transposon calling cards and transcriptomes. NAR Genom Bioinform 2022; 4:lqac061. [PMID: 36062164 PMCID: PMC9428926 DOI: 10.1093/nargab/lqac061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 07/04/2022] [Accepted: 08/24/2022] [Indexed: 11/29/2022] Open
Abstract
Calling cards technology using self-reporting transposons enables the identification of DNA-protein interactions through RNA sequencing. Although immensely powerful, current implementations of calling cards in bulk experiments on populations of cells are technically cumbersome and require many replicates to identify independent insertions into the same genomic locus. Here, we have drastically reduced the cost and labor requirements of calling card experiments in bulk populations of cells by introducing a DNA barcode into the calling card itself. An additional barcode incorporated during reverse transcription enables simultaneous transcriptome measurement in a facile and affordable protocol. We demonstrate that barcoded self-reporting transposons recover in vitro binding sites for four basic helix-loop-helix transcription factors with important roles in cell fate specification: ASCL1, MYOD1, NEUROD2 and NGN1. Further, simultaneous calling cards and transcriptional profiling during transcription factor overexpression identified both binding sites and gene expression changes for two of these factors. Lastly, we demonstrated barcoded calling cards can record binding in vivo in the mouse brain. In sum, RNA-based identification of transcription factor binding sites and gene expression through barcoded self-reporting transposon calling cards and transcriptomes is an efficient and powerful method to infer gene regulatory networks in a population of cells.
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Affiliation(s)
- Matthew Lalli
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Allen Yen
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Urvashi Thopte
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Fengping Dong
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA
| | - Arnav Moudgil
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA
| | - Xuhua Chen
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA
| | - Jeffrey Milbrandt
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA
| | - Joseph D Dougherty
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Robi D Mitra
- Department of Genetics, School of Medicine, Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology Washington University in St. Louis School of Medicine, Saint Louis, MO 63110, USA
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9
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Chen J, Yen A, Florian CP, Dougherty JD. MYT1L in the making: emerging insights on functions of a neurodevelopmental disorder gene. Transl Psychiatry 2022; 12:292. [PMID: 35869058 PMCID: PMC9307810 DOI: 10.1038/s41398-022-02058-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 06/27/2022] [Accepted: 07/01/2022] [Indexed: 12/03/2022] Open
Abstract
Large scale human genetic studies have shown that loss of function (LoF) mutations in MYT1L are implicated in neurodevelopmental disorders (NDDs). Here, we provide an overview of the growing number of published MYT1L patient cases, and summarize prior studies in cells, zebrafish, and mice, both to understand MYT1L's molecular and cellular role during brain development and consider how its dysfunction can lead to NDDs. We integrate the conclusions from these studies and highlight conflicting findings to reassess the current model of the role of MYT1L as a transcriptional activator and/or repressor based on the biological context. Finally, we highlight additional functional studies that are needed to understand the molecular mechanisms underlying pathophysiology and propose key questions to guide future preclinical studies.
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Affiliation(s)
- Jiayang Chen
- grid.4367.60000 0001 2355 7002Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO 63108 USA ,grid.4367.60000 0001 2355 7002Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO 63108 USA
| | - Allen Yen
- grid.4367.60000 0001 2355 7002Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO 63108 USA ,grid.4367.60000 0001 2355 7002Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO 63108 USA
| | - Colin P. Florian
- grid.4367.60000 0001 2355 7002Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO 63108 USA ,grid.4367.60000 0001 2355 7002Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO 63108 USA
| | - Joseph D. Dougherty
- grid.4367.60000 0001 2355 7002Department of Genetics, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO 63108 USA ,grid.4367.60000 0001 2355 7002Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO 63108 USA ,grid.4367.60000 0001 2355 7002Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, 660 S. Euclid Ave, Saint Louis, MO 63108 USA
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10
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Kok L, Masopust D, Schumacher TN. The precursors of CD8 + tissue resident memory T cells: from lymphoid organs to infected tissues. Nat Rev Immunol 2022; 22:283-293. [PMID: 34480118 PMCID: PMC8415193 DOI: 10.1038/s41577-021-00590-3] [Citation(s) in RCA: 78] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/05/2021] [Indexed: 02/08/2023]
Abstract
CD8+ tissue resident memory T cells (TRM cells) are essential for immune defence against pathogens and malignancies, and the molecular processes that lead to TRM cell formation are therefore of substantial biomedical interest. Prior work has demonstrated that signals present in the inflamed tissue micro-environment can promote the differentiation of memory precursor cells into mature TRM cells, and it was therefore long assumed that TRM cell formation adheres to a 'local divergence' model, in which TRM cell lineage decisions are exclusively made within the tissue. However, a growing body of work provides evidence for a 'systemic divergence' model, in which circulating T cells already become preconditioned to preferentially give rise to the TRM cell lineage, resulting in the generation of a pool of TRM cell-poised T cells within the lymphoid compartment. Here, we review the emerging evidence that supports the existence of such a population of circulating TRM cell progenitors, discuss current insights into their formation and highlight open questions in the field.
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Affiliation(s)
- Lianne Kok
- grid.430814.a0000 0001 0674 1393Division of Molecular Oncology & Immunology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands
| | - David Masopust
- grid.17635.360000000419368657Department of Microbiology and Immunology, Center for Immunology, University of Minnesota Medical School, Minneapolis, MN USA
| | - Ton N. Schumacher
- grid.430814.a0000 0001 0674 1393Division of Molecular Oncology & Immunology, Oncode Institute, The Netherlands Cancer Institute, Amsterdam, The Netherlands
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11
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Moudgil A, Li D, Hsu S, Purushotham D, Wang T, Mitra RD. The qBED track: a novel genome browser visualization for point processes. Bioinformatics 2021; 37:1168-1170. [PMID: 32941613 DOI: 10.1093/bioinformatics/btaa771] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 08/10/2020] [Accepted: 09/15/2020] [Indexed: 01/25/2023] Open
Abstract
SUMMARY Transposon calling cards is a genomic assay for identifying transcription factor binding sites in both bulk and single cell experiments. Here, we describe the qBED format, an open, text-based standard for encoding and analyzing calling card data. In parallel, we introduce the qBED track on the WashU Epigenome Browser, a novel visualization that enables researchers to inspect calling card data in their genomic context. Finally, through examples, we demonstrate that qBED files can be used to visualize non-calling card datasets, such as Combined Annotation-Dependent Depletion scores and GWAS/eQTL hits, and thus may have broad utility to the genomics community. AVAILABILITY AND IMPLEMENTATION The qBED track is available on the WashU Epigenome Browser (http://epigenomegateway.wustl.edu/browser), beginning with version 46. Source code for the WashU Epigenome Browser with qBED support is available on GitHub (http://github.com/arnavm/eg-react and http://github.com/lidaof/eg-react). A complete definition of the qBED format is available as part of the WashU Epigenome Browser documentation (https://eg.readthedocs.io/en/latest/tracks.html#qbed-track). We have also released a tutorial on how to upload qBED data to the browser (http://dx.doi.org/10.17504/protocols.io.bca8ishw).
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Affiliation(s)
- Arnav Moudgil
- Department of Genetics, St. Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology, St. Louis, MO 63110, USA.,Medical Scientist Training Program, Washington University in St. Louis School of Medicine, St. Louis, MO 63110, USA
| | - Daofeng Li
- Department of Genetics, St. Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology, St. Louis, MO 63110, USA
| | - Silas Hsu
- Department of Genetics, St. Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology, St. Louis, MO 63110, USA
| | - Deepak Purushotham
- Department of Genetics, St. Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology, St. Louis, MO 63110, USA
| | - Ting Wang
- Department of Genetics, St. Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology, St. Louis, MO 63110, USA
| | - Robi D Mitra
- Department of Genetics, St. Louis, MO 63110, USA.,Edison Family Center for Genome Sciences and Systems Biology, St. Louis, MO 63110, USA
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12
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Sharif N, Calzolari F, Berninger B. Direct In Vitro Reprogramming of Astrocytes into Induced Neurons. Methods Mol Biol 2021; 2352:13-29. [PMID: 34324177 DOI: 10.1007/978-1-0716-1601-7_2] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Spontaneous neuronal replacement is almost absent in the postnatal mammalian nervous system. However, several studies have shown that both early postnatal and adult astroglia can be reprogrammed in vitro or in vivo by forced expression of proneural transcription factors, such as Neurogenin-2 or Achaete-scute homolog 1 (Ascl1), to acquire a neuronal fate. The reprogramming process stably induces properties such as distinctly neuronal morphology, expression of neuron-specific proteins, and the gain of mature neuronal functional features. Direct conversion of astroglia into neurons thus possesses potential as a basis for cell-based strategies against neurological diseases. In this chapter, we describe a well-established protocol used for direct reprogramming of postnatal cortical astrocytes into functional neurons in vitro and discuss available tools and approaches to dissect molecular and cell biological mechanisms underlying the reprogramming process.
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Affiliation(s)
- Nesrin Sharif
- Institute of Physiological Chemistry, University Medical Center Johannes Gutenberg University Mainz, Mainz, Germany
- International PhD Programme on Gene Regulation, Epigenetics and Genome Stability, Mainz, Germany
| | - Filippo Calzolari
- Institute of Physiological Chemistry, University Medical Center Johannes Gutenberg University Mainz, Mainz, Germany
| | - Benedikt Berninger
- Institute of Physiological Chemistry, University Medical Center Johannes Gutenberg University Mainz, Mainz, Germany.
- Institute of Psychiatry, Psychology, and Neuroscience, Centre for Developmental Neurobiology, King's College London, London, UK.
- MRC Centre for Neurodevelopmental Disorders, King's College London, London, UK.
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13
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Moudgil A, Wilkinson MN, Chen X, He J, Cammack AJ, Vasek MJ, Lagunas T, Qi Z, Lalli MA, Guo C, Morris SA, Dougherty JD, Mitra RD. Self-Reporting Transposons Enable Simultaneous Readout of Gene Expression and Transcription Factor Binding in Single Cells. Cell 2020; 182:992-1008.e21. [PMID: 32710817 PMCID: PMC7510185 DOI: 10.1016/j.cell.2020.06.037] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2019] [Revised: 04/14/2020] [Accepted: 06/23/2020] [Indexed: 12/13/2022]
Abstract
Cellular heterogeneity confounds in situ assays of transcription factor (TF) binding. Single-cell RNA sequencing (scRNA-seq) deconvolves cell types from gene expression, but no technology links cell identity to TF binding sites (TFBS) in those cell types. We present self-reporting transposons (SRTs) and use them in single-cell calling cards (scCC), a novel assay for simultaneously measuring gene expression and mapping TFBS in single cells. The genomic locations of SRTs are recovered from mRNA, and SRTs deposited by exogenous, TF-transposase fusions can be used to map TFBS. We then present scCC, which map SRTs from scRNA-seq libraries, simultaneously identifying cell types and TFBS in those same cells. We benchmark multiple TFs with this technique. Next, we use scCC to discover BRD4-mediated cell-state transitions in K562 cells. Finally, we map BRD4 binding sites in the mouse cortex at single-cell resolution, establishing a new method for studying TF biology in situ.
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Affiliation(s)
- Arnav Moudgil
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; Medical Scientist Training Program, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
| | - Michael N Wilkinson
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
| | - Xuhua Chen
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
| | - June He
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
| | - Alexander J Cammack
- Department of Neurology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
| | - Michael J Vasek
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
| | - Tomás Lagunas
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
| | - Zongtai Qi
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
| | - Matthew A Lalli
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
| | - Chuner Guo
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; Medical Scientist Training Program, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; Department of Developmental Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
| | - Samantha A Morris
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; Department of Developmental Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; Center of Regenerative Medicine, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
| | - Joseph D Dougherty
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA
| | - Robi D Mitra
- Department of Genetics, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA; Edison Family Center for Genome Sciences and Systems Biology, Washington University School of Medicine in St. Louis, St. Louis, MO 63110, USA.
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14
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A viral toolkit for recording transcription factor-DNA interactions in live mouse tissues. Proc Natl Acad Sci U S A 2020; 117:10003-10014. [PMID: 32300008 DOI: 10.1073/pnas.1918241117] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
Transcription factors (TFs) enact precise regulation of gene expression through site-specific, genome-wide binding. Common methods for TF-occupancy profiling, such as chromatin immunoprecipitation, are limited by requirement of TF-specific antibodies and provide only end-point snapshots of TF binding. Alternatively, TF-tagging techniques, in which a TF is fused to a DNA-modifying enzyme that marks TF-binding events across the genome as they occur, do not require TF-specific antibodies and offer the potential for unique applications, such as recording of TF occupancy over time and cell type specificity through conditional expression of the TF-enzyme fusion. Here, we create a viral toolkit for one such method, calling cards, and demonstrate that these reagents can be delivered to the live mouse brain and used to report TF occupancy. Further, we establish a Cre-dependent calling cards system and, in proof-of-principle experiments, show utility in defining cell type-specific TF profiles and recording and integrating TF-binding events across time. This versatile approach will enable unique studies of TF-mediated gene regulation in live animal models.
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