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Wu E, Wu Z, Mayer AT, Trevino AE, Zou J. PEPSI: Polarity measurements from spatial proteomics imaging suggest immune cell engagement. Pac Symp Biocomput 2024; 29:492-505. [PMID: 38160302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/03/2024]
Abstract
Subcellular protein localization is important for understanding functional states of cells, but measuring and quantifying this information can be difficult and typically requires high-resolution microscopy. In this work, we develop a metric to define surface protein polarity from immunofluorescence (IF) imaging data and use it to identify distinct immune cell states within tumor microenvironments. We apply this metric to characterize over two million cells across 600 patient samples and find that cells identified as having polar expression exhibit characteristics relating to tumor-immune cell engagement. Additionally, we show that incorporating these polarity-defined cell subtypes improves the performance of deep learning models trained to predict patient survival outcomes. This method provides a first look at using subcellular protein expression patterns to phenotype immune cell functional states with applications to precision medicine.
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Affiliation(s)
- Eric Wu
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA2Enable Medicine, Inc., Menlo Park, CA, USA,
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2
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Wu E, Trevino AE, Wu Z, Swanson K, Kim HJ, D’Angio HB, Preska R, Chiou AE, Charville GW, Dalerba P, Duvvuri U, Colevas AD, Levi J, Bedi N, Chang S, Sunwoo J, Egloff AM, Uppaluri R, Mayer AT, Zou J. 7-UP: Generating in silico CODEX from a small set of immunofluorescence markers. PNAS Nexus 2023; 2:pgad171. [PMID: 37275261 PMCID: PMC10236358 DOI: 10.1093/pnasnexus/pgad171] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 05/15/2023] [Indexed: 06/07/2023]
Abstract
Multiplex immunofluorescence (mIF) assays multiple protein biomarkers on a single tissue section. Recently, high-plex CODEX (co-detection by indexing) systems enable simultaneous imaging of 40+ protein biomarkers, unlocking more detailed molecular phenotyping, leading to richer insights into cellular interactions and disease. However, high-plex data can be slower and more costly to collect, limiting its applications, especially in clinical settings. We propose a machine learning framework, 7-UP, that can computationally generate in silico 40-plex CODEX at single-cell resolution from a standard 7-plex mIF panel by leveraging cellular morphology. We demonstrate the usefulness of the imputed biomarkers in accurately classifying cell types and predicting patient survival outcomes. Furthermore, 7-UP's imputations generalize well across samples from different clinical sites and cancer types. 7-UP opens the possibility of in silico CODEX, making insights from high-plex mIF more widely available.
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Affiliation(s)
| | | | - Zhenqin Wu
- Enable Medicine, Menlo Park, CA 94025, USA
- Department of Chemistry, Stanford University, Stanford, CA 94305, USA
| | - Kyle Swanson
- Department of Computer Science, Stanford University, Stanford, CA 94305, USA
| | | | | | | | | | | | - Piero Dalerba
- Department of Pathology and Cell Biology, Columbia University, New York, NY 10027, USA
| | - Umamaheswar Duvvuri
- Department of Otolaryngology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | | | - Jelena Levi
- CellSight Technologies, San Francisco, CA 94107, USA
| | - Nikita Bedi
- Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA 94305, USA
| | - Serena Chang
- Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA 94305, USA
| | - John Sunwoo
- Department of Otolaryngology-Head and Neck Surgery, Stanford University, Stanford, CA 94305, USA
| | - Ann Marie Egloff
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Ravindra Uppaluri
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA
| | - Aaron T Mayer
- To whom correspondence should be addressed: (A.E.T.); (A.T.M.); (J.Z.)
| | - James Zou
- To whom correspondence should be addressed: (A.E.T.); (A.T.M.); (J.Z.)
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3
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Marinov GK, Kim SH, Bagdatli ST, Higashino SI, Trevino AE, Tycko J, Wu T, Bintu L, Bassik MC, He C, Kundaje A, Greenleaf WJ. CasKAS: direct profiling of genome-wide dCas9 and Cas9 specificity using ssDNA mapping. Genome Biol 2023; 24:85. [PMID: 37085898 PMCID: PMC10120127 DOI: 10.1186/s13059-023-02930-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 04/07/2023] [Indexed: 04/23/2023] Open
Abstract
Detecting and mitigating off-target activity is critical to the practical application of CRISPR-mediated genome and epigenome editing. While numerous methods have been developed to map Cas9 binding specificity genome-wide, they are generally time-consuming and/or expensive, and not applicable to catalytically dead CRISPR enzymes. We have developed CasKAS, a rapid, inexpensive, and facile assay for identifying off-target CRISPR enzyme binding and cleavage by chemically mapping the unwound single-stranded DNA structures formed upon binding of a sgRNA-loaded Cas9 protein. We demonstrate this method in both in vitro and in vivo contexts.
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Affiliation(s)
- Georgi K Marinov
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, 94305, USA.
| | - Samuel H Kim
- Cancer Biology Program, School of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - S Tansu Bagdatli
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - Soon Il Higashino
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - Alexandro E Trevino
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, 94305, USA
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
| | - Josh Tycko
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - Tong Wu
- Department of Chemistry, The University of Chicago, Chicago, IL, 60637, USA
| | - Lacramioara Bintu
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
| | - Michael C Bassik
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, 94305, USA
- Chemistry, Engineering, and Medicine for Human Health (ChEM-H), Stanford University, Stanford, CA, 94305, USA
| | - Chuan He
- Department of Chemistry, The University of Chicago, Chicago, IL, 60637, USA
- Department of Biochemistry and Molecular Biology and Institute for Biophysical Dynamics, The University of Chicago, Chicago, IL, 60637, USA
- Howard Hughes Medical Institute, The University of Chicago, Chicago, IL, 60637, USA
| | - Anshul Kundaje
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, 94305, USA
- Department of Computer Science, Stanford University, Stanford, CA, 94305, USA
| | - William J Greenleaf
- Department of Genetics, School of Medicine, Stanford University, Stanford, CA, 94305, USA.
- Department of Applied Physics, Stanford University, Stanford, CA, 94305, USA.
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, 94305, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, USA.
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4
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Zamani M, Cheng YH, Charbonier F, Gupta VK, Mayer AT, Trevino AE, Quertermous T, Chaudhuri O, Cahan P, Huang NF. Single-Cell Transcriptomic Census of Endothelial Changes Induced by Matrix Stiffness and the Association with Atherosclerosis. Adv Funct Mater 2022; 32:2203069. [PMID: 36816792 PMCID: PMC9937733 DOI: 10.1002/adfm.202203069] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Indexed: 05/28/2023]
Abstract
Vascular endothelial cell (EC) plasticity plays a critical role in the progression of atherosclerosis by giving rise to mesenchymal phenotypes in the plaque lesion. Despite the evidence for arterial stiffening as a major contributor to atherosclerosis, the complex interplay among atherogenic stimuli in vivo has hindered attempts to determine the effects of extracellular matrix (ECM) stiffness on endothelial-mesenchymal transition (EndMT). To study the regulatory effects of ECM stiffness on EndMT, an in vitro model is developed in which human coronary artery ECs are cultured on physiological or pathological stiffness substrates. Leveraging single-cell RNA sequencing, cell clusters with mesenchymal transcriptional features are identified to be more prevalent on pathological substrates than physiological substrates. Trajectory inference analyses reveal a novel mesenchymal-to-endothelial reverse transition, which is blocked by pathological stiffness substrates, in addition to the expected EndMT trajectory. ECs pushed to a mesenchymal character by pathological stiffness substrates are enriched in transcriptional signatures of atherosclerotic ECs from human and murine plaques. This study characterizes at single-cell resolution the transcriptional programs that underpin EC plasticity in both physiological or pathological milieus, and thus serves as a valuable resource for more precisely defining EndMT and the transcriptional programs contributing to atherosclerosis.
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Affiliation(s)
- Maedeh Zamani
- Department of Cardiothoracic Surgery, Stanford University, Stanford, CA 94305, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA 94305, USA
| | - Yu-Hao Cheng
- Department of Molecular Biology and Genetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Frank Charbonier
- Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Vivek Kumar Gupta
- Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA
| | | | | | - Thomas Quertermous
- Division of Cardiovascular Medicine, Stanford School of Medicine, Stanford, CA 94305, USA
| | - Ovijit Chaudhuri
- Department of Mechanical Engineering, Stanford University, Stanford, CA 94305, USA
| | - Patrick Cahan
- Department of Molecular Biology and Genetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Ngan F Huang
- Department of Cardiothoracic Surgery, Stanford University, Stanford, CA 94305, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA 94305, USA
- Department of Chemical Engineering, Stanford University, Stanford, CA 94305, USA
- Veterans Affairs Palo Alto Health Care System, Palo Alto, CA 94304, USA
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5
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Balood M, Ahmadi M, Eichwald T, Ahmadi A, Majdoubi A, Roversi K, Roversi K, Lucido CT, Restaino AC, Huang S, Ji L, Huang KC, Semerena E, Thomas SC, Trevino AE, Merrison H, Parrin A, Doyle B, Vermeer DW, Spanos WC, Williamson CS, Seehus CR, Foster SL, Dai H, Shu CJ, Rangachari M, Thibodeau J, V Del Rincon S, Drapkin R, Rafei M, Ghasemlou N, Vermeer PD, Woolf CJ, Talbot S. Nociceptor neurons affect cancer immunosurveillance. Nature 2022; 611:405-412. [PMID: 36323780 PMCID: PMC9646485 DOI: 10.1038/s41586-022-05374-w] [Citation(s) in RCA: 47] [Impact Index Per Article: 23.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2021] [Accepted: 09/21/2022] [Indexed: 11/07/2022]
Abstract
Solid tumours are innervated by nerve fibres that arise from the autonomic and sensory peripheral nervous systems1-5. Whether the neo-innervation of tumours by pain-initiating sensory neurons affects cancer immunosurveillance remains unclear. Here we show that melanoma cells interact with nociceptor neurons, leading to increases in their neurite outgrowth, responsiveness to noxious ligands and neuropeptide release. Calcitonin gene-related peptide (CGRP)-one such nociceptor-produced neuropeptide-directly increases the exhaustion of cytotoxic CD8+ T cells, which limits their capacity to eliminate melanoma. Genetic ablation of the TRPV1 lineage, local pharmacological silencing of nociceptors and antagonism of the CGRP receptor RAMP1 all reduced the exhaustion of tumour-infiltrating leukocytes and decreased the growth of tumours, nearly tripling the survival rate of mice that were inoculated with B16F10 melanoma cells. Conversely, CD8+ T cell exhaustion was rescued in sensory-neuron-depleted mice that were treated with local recombinant CGRP. As compared with wild-type CD8+ T cells, Ramp1-/- CD8+ T cells were protected against exhaustion when co-transplanted into tumour-bearing Rag1-deficient mice. Single-cell RNA sequencing of biopsies from patients with melanoma revealed that intratumoral RAMP1-expressing CD8+ T cells were more exhausted than their RAMP1-negative counterparts, whereas overexpression of RAMP1 correlated with a poorer clinical prognosis. Overall, our results suggest that reducing the release of CGRP from tumour-innervating nociceptors could be a strategy to improve anti-tumour immunity by eliminating the immunomodulatory effects of CGRP on cytotoxic CD8+ T cells.
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Affiliation(s)
- Mohammad Balood
- Département de Pharmacologie et Physiologie, Université de Montréal, Montréal, Quebec, Canada
- Département de Médecine Moléculaire, Faculté de Médecine, Université Laval, Québec, Quebec, Canada
| | - Maryam Ahmadi
- Département de Pharmacologie et Physiologie, Université de Montréal, Montréal, Quebec, Canada
| | - Tuany Eichwald
- Département de Pharmacologie et Physiologie, Université de Montréal, Montréal, Quebec, Canada
- Departamento de Bioquímica, Universidade Federal de Santa Catarina, Florianópolis, Brazil
| | - Ali Ahmadi
- Département de Pharmacologie et Physiologie, Université de Montréal, Montréal, Quebec, Canada
| | - Abdelilah Majdoubi
- Département de Microbiologie, Infectiologie et Immunologie, Université de Montréal, Montréal, Quebec, Canada
| | - Karine Roversi
- Département de Pharmacologie et Physiologie, Université de Montréal, Montréal, Quebec, Canada
| | - Katiane Roversi
- Département de Pharmacologie et Physiologie, Université de Montréal, Montréal, Quebec, Canada
| | | | - Anthony C Restaino
- Cancer Biology and Immunotherapies, Sanford Research, Sioux Falls, SD, USA
| | | | | | | | - Elise Semerena
- Département de Pharmacologie et Physiologie, Université de Montréal, Montréal, Quebec, Canada
| | - Sini C Thomas
- Département de Pharmacologie et Physiologie, Université de Montréal, Montréal, Quebec, Canada
| | - Alexandro E Trevino
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Hannah Merrison
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Alexandre Parrin
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Benjamin Doyle
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Daniel W Vermeer
- Cancer Biology and Immunotherapies, Sanford Research, Sioux Falls, SD, USA
| | - William C Spanos
- Cancer Biology and Immunotherapies, Sanford Research, Sioux Falls, SD, USA
| | | | - Corey R Seehus
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Simmie L Foster
- Depression Clinical Research Program, Massachusetts General Hospital, Boston, MA, USA
| | | | | | - Manu Rangachari
- Département de Médecine Moléculaire, Faculté de Médecine, Université Laval, Québec, Quebec, Canada
| | - Jacques Thibodeau
- Département de Microbiologie, Infectiologie et Immunologie, Université de Montréal, Montréal, Quebec, Canada
| | | | - Ronny Drapkin
- Penn Ovarian Cancer Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Moutih Rafei
- Département de Pharmacologie et Physiologie, Université de Montréal, Montréal, Quebec, Canada
| | - Nader Ghasemlou
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, Ontario, Canada
| | - Paola D Vermeer
- Cancer Biology and Immunotherapies, Sanford Research, Sioux Falls, SD, USA
| | - Clifford J Woolf
- F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA, USA
- Department of Neurobiology, Harvard Medical School, Boston, MA, USA
| | - Sebastien Talbot
- Département de Pharmacologie et Physiologie, Université de Montréal, Montréal, Quebec, Canada.
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, Ontario, Canada.
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6
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Trevino AE, Müller F, Andersen J, Sundaram L, Kathiria A, Shcherbina A, Farh K, Chang HY, Pașca AM, Kundaje A, Pașca SP, Greenleaf WJ. Chromatin and gene-regulatory dynamics of the developing human cerebral cortex at single-cell resolution. Cell 2021; 184:5053-5069.e23. [PMID: 34390642 DOI: 10.1016/j.cell.2021.07.039] [Citation(s) in RCA: 138] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 05/18/2021] [Accepted: 07/28/2021] [Indexed: 12/20/2022]
Abstract
Genetic perturbations of cortical development can lead to neurodevelopmental disease, including autism spectrum disorder (ASD). To identify genomic regions crucial to corticogenesis, we mapped the activity of gene-regulatory elements generating a single-cell atlas of gene expression and chromatin accessibility both independently and jointly. This revealed waves of gene regulation by key transcription factors (TFs) across a nearly continuous differentiation trajectory, distinguished the expression programs of glial lineages, and identified lineage-determining TFs that exhibited strong correlation between linked gene-regulatory elements and expression levels. These highly connected genes adopted an active chromatin state in early differentiating cells, consistent with lineage commitment. Base-pair-resolution neural network models identified strong cell-type-specific enrichment of noncoding mutations predicted to be disruptive in a cohort of ASD individuals and identified frequently disrupted TF binding sites. This approach illustrates how cell-type-specific mapping can provide insights into the programs governing human development and disease.
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Affiliation(s)
| | - Fabian Müller
- Department of Genetics, Stanford University, Stanford, CA, USA; Center for Bioinformatics, Saarland University, Saarbrücken, Germany
| | - Jimena Andersen
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute Stanford University, Stanford, CA, USA
| | | | - Arwa Kathiria
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Anna Shcherbina
- Biomedical Data Science Program, Stanford University, Stanford CA, USA
| | - Kyle Farh
- Illumina Artificial Intelligence Laboratory, Illumina Inc, San Diego, CA, USA
| | - Howard Y Chang
- Department of Genetics, Stanford University, Stanford, CA, USA; Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA
| | - Anca M Pașca
- Department of Pediatrics, Division of Neonatology, Stanford University, Stanford, CA, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University, Stanford, CA, USA; Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Sergiu P Pașca
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA; Stanford Brain Organogenesis Program, Wu Tsai Neuroscience Institute Stanford University, Stanford, CA, USA.
| | - William J Greenleaf
- Department of Genetics, Stanford University, Stanford, CA, USA; Department of Applied Physics, Stanford University, Stanford, CA, USA; Chan-Zuckerberg Biohub, San Francisco, CA, USA.
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7
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Marinov GK, Trevino AE, Xiang T, Kundaje A, Grossman AR, Greenleaf WJ. Transcription-dependent domain-scale three-dimensional genome organization in the dinoflagellate Breviolum minutum. Nat Genet 2021; 53:613-617. [PMID: 33927397 PMCID: PMC8110477 DOI: 10.1038/s41588-021-00848-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 03/17/2021] [Indexed: 11/09/2022]
Abstract
Dinoflagellate chromosomes represent a unique evolutionary experiment, as they exist in a permanently condensed, liquid crystalline state; are not packaged by histones; and contain genes organized into tandem gene arrays, with minimal transcriptional regulation. We analyze the three-dimensional genome of Breviolum minutum, and find large topological domains (dinoflagellate topologically associating domains, which we term 'dinoTADs') without chromatin loops, which are demarcated by convergent gene array boundaries. Transcriptional inhibition disrupts dinoTADs, implicating transcription-induced supercoiling as the primary topological force in dinoflagellates.
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Affiliation(s)
| | - Alexandro E Trevino
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA.,Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Tingting Xiang
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA, USA.,Department of Biological Sciences, University of North Carolina at Charlotte, Charlotte, NC, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University, Stanford, CA, USA.,Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Arthur R Grossman
- Department of Plant Biology, Carnegie Institution for Science, Stanford, CA, USA
| | - William J Greenleaf
- Department of Genetics, Stanford University, Stanford, CA, USA. .,Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA. .,Department of Applied Physics, Stanford University, Stanford, CA, USA. .,Chan Zuckerberg Biohub, San Francisco, CA, USA.
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8
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Ang CE, Trevino AE, Chang HY. Diverse lncRNA mechanisms in brain development and disease. Curr Opin Genet Dev 2020; 65:42-46. [PMID: 32554106 DOI: 10.1016/j.gde.2020.05.006] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2020] [Accepted: 05/01/2020] [Indexed: 01/20/2023]
Abstract
Long noncoding RNAs (lncRNAs) are a diverse and pervasive class of genes. Recent studies in the mammalian brain have uncovered several novel mechanisms. LncRNA loci are often located in proximity to developmental transcriptional factors. The lncRNA product may act like a transcription factor to control distantly located genes, or in other instances, the lncRNA loci contain DNA regulatory elements that act locally on neighboring genes. Circular RNAs are covalently closed single-stranded RNAs that can control neuronal function by acting as microRNA sponges and additional mechanisms. LncRNAs can also engage in target-directed microRNA degradation to shape the pool of microRNAs and translation. Thus, diverse mechanisms allow lncRNAs to act in the nucleus and cytoplasm to control neuronal fate and function.
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Affiliation(s)
- Cheen Euong Ang
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Alexandro E Trevino
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA; Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA; Howard Hughes Medical Institute, Stanford, CA 94305, USA.
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9
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Trevino AE, Sinnott-Armstrong N, Andersen J, Yoon SJ, Huber N, Pritchard JK, Chang HY, Greenleaf WJ, Pașca SP. Chromatin accessibility dynamics in a model of human forebrain development. Science 2020; 367:eaay1645. [PMID: 31974223 PMCID: PMC7313757 DOI: 10.1126/science.aay1645] [Citation(s) in RCA: 123] [Impact Index Per Article: 30.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Accepted: 12/16/2019] [Indexed: 12/12/2022]
Abstract
Forebrain development is characterized by highly synchronized cellular processes, which, if perturbed, can cause disease. To chart the regulatory activity underlying these events, we generated a map of accessible chromatin in human three-dimensional forebrain organoids. To capture corticogenesis, we sampled glial and neuronal lineages from dorsal or ventral forebrain organoids over 20 months in vitro. Active chromatin regions identified in human primary brain tissue were observed in organoids at different developmental stages. We used this resource to map genetic risk for disease and to explore evolutionary conservation. Moreover, we integrated chromatin accessibility with transcriptomics to identify putative enhancer-gene linkages and transcription factors that regulate human corticogenesis. Overall, this platform brings insights into gene-regulatory dynamics at previously inaccessible stages of human forebrain development, including signatures of neuropsychiatric disorders.
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Affiliation(s)
- Alexandro E Trevino
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Stanford Human Brain Organogenesis Program, Stanford, CA, USA
| | | | - Jimena Andersen
- Stanford Human Brain Organogenesis Program, Stanford, CA, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Se-Jin Yoon
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Nina Huber
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Jonathan K Pritchard
- Department of Genetics, Stanford University, Stanford, CA, USA
- Department of Biology, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Howard Y Chang
- Department of Genetics, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
- Department of Dermatology, Stanford University, Stanford, CA, USA
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, USA
| | - William J Greenleaf
- Department of Genetics, Stanford University, Stanford, CA, USA.
- Department of Applied Physics, Stanford University, Stanford, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Sergiu P Pașca
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
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10
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Tycko J, Wainberg M, Marinov GK, Ursu O, Hess GT, Ego BK, Aradhana, Li A, Truong A, Trevino AE, Spees K, Yao D, Kaplow IM, Greenside PG, Morgens DW, Phanstiel DH, Snyder MP, Bintu L, Greenleaf WJ, Kundaje A, Bassik MC. Mitigation of off-target toxicity in CRISPR-Cas9 screens for essential non-coding elements. Nat Commun 2019; 10:4063. [PMID: 31492858 PMCID: PMC6731277 DOI: 10.1038/s41467-019-11955-7] [Citation(s) in RCA: 75] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2019] [Accepted: 08/07/2019] [Indexed: 12/26/2022] Open
Abstract
Pooled CRISPR-Cas9 screens are a powerful method for functionally characterizing regulatory elements in the non-coding genome, but off-target effects in these experiments have not been systematically evaluated. Here, we investigate Cas9, dCas9, and CRISPRi/a off-target activity in screens for essential regulatory elements. The sgRNAs with the largest effects in genome-scale screens for essential CTCF loop anchors in K562 cells were not single guide RNAs (sgRNAs) that disrupted gene expression near the on-target CTCF anchor. Rather, these sgRNAs had high off-target activity that, while only weakly correlated with absolute off-target site number, could be predicted by the recently developed GuideScan specificity score. Screens conducted in parallel with CRISPRi/a, which do not induce double-stranded DNA breaks, revealed that a distinct set of off-targets also cause strong confounding fitness effects with these epigenome-editing tools. Promisingly, filtering of CRISPRi libraries using GuideScan specificity scores removed these confounded sgRNAs and enabled identification of essential regulatory elements.
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Affiliation(s)
- Josh Tycko
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Michael Wainberg
- Department of Computer Science, Stanford University, Stanford, CA, 94305, USA
| | - Georgi K Marinov
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Oana Ursu
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Gaelen T Hess
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Braeden K Ego
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Aradhana
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Amy Li
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Alisa Truong
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Alexandro E Trevino
- Center for Personal Dynamic Regulomes, Stanford University, Stanford, CA, 94305, USA
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
| | - Kaitlyn Spees
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - David Yao
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Irene M Kaplow
- Department of Computer Science, Stanford University, Stanford, CA, 94305, USA
- Department of Biology, Stanford University, Stanford, CA, 94305, USA
| | - Peyton G Greenside
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
- Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - David W Morgens
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Douglas H Phanstiel
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
- Department of Cell Biology and Physiology, University of North Carolina, Chapel Hill, NC, 27599, USA
- Thurston Arthritis Research Center, University of North Carolina, Chapel Hill, NC, 27599, USA
| | - Michael P Snyder
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Lacramioara Bintu
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
| | - William J Greenleaf
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA.
- Department of Applied Physics, Stanford University, Stanford, CA, 94305, USA.
- Chan Zuckerberg Biohub, San Francisco, CA, 94158, USA.
| | - Anshul Kundaje
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA.
- Department of Computer Science, Stanford University, Stanford, CA, 94305, USA.
| | - Michael C Bassik
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA.
- Chemistry, Engineering, and Medicine for Human Health (ChEM-H), Stanford University, Stanford, CA, 94305, USA.
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11
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Corces MR, Trevino AE, Hamilton EG, Greenside PG, Sinnott-Armstrong NA, Vesuna S, Satpathy AT, Rubin AJ, Montine KS, Wu B, Kathiria A, Cho SW, Mumbach MR, Carter AC, Kasowski M, Orloff LA, Risca VI, Kundaje A, Khavari PA, Montine TJ, Greenleaf WJ, Chang HY. An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues. Nat Methods 2017; 14:959-962. [PMID: 28846090 PMCID: PMC5623106 DOI: 10.1038/nmeth.4396] [Citation(s) in RCA: 1203] [Impact Index Per Article: 171.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 07/11/2017] [Indexed: 12/16/2022]
Abstract
We present Omni-ATAC, an improved ATAC-seq protocol for chromatin accessibility profiling that works across multiple applications with substantial improvement of signal-to-background ratio and information content. The Omni-ATAC protocol generates chromatin accessibility profiles from archival frozen tissue samples and 50-μm sections, revealing the activities of disease-associated DNA elements in distinct human brain structures. The Omni-ATAC protocol enables the interrogation of personal regulomes in tissue context and translational studies.
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Affiliation(s)
- M Ryan Corces
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
- Department of Dermatology, Stanford University School of Medicine, Stanford, California, USA
| | - Alexandro E Trevino
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
- Department of Bioengineering, Stanford University School of Medicine and School of Engineering, Stanford, California, USA
| | - Emily G Hamilton
- Program in Cancer Biology, Stanford University School of Medicine, Stanford, California, USA
| | - Peyton G Greenside
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
- Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, California, USA
| | | | - Sam Vesuna
- Department of Bioengineering, Stanford University School of Medicine and School of Engineering, Stanford, California, USA
| | - Ansuman T Satpathy
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, California, USA
| | - Adam J Rubin
- Department of Dermatology, Stanford University School of Medicine, Stanford, California, USA
| | - Kathleen S Montine
- Department of Pathology, Stanford University School of Medicine, Stanford, California, USA
| | - Beijing Wu
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Arwa Kathiria
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Seung Woo Cho
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
- Department of Dermatology, Stanford University School of Medicine, Stanford, California, USA
| | - Maxwell R Mumbach
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Ava C Carter
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
- Department of Dermatology, Stanford University School of Medicine, Stanford, California, USA
| | - Maya Kasowski
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
- Department of Pathology, Stanford University School of Medicine, Stanford, California, USA
| | - Lisa A Orloff
- Department of Otolaryngology Head and Neck Surgery, Stanford University School of Medicine, Stanford, California, USA
| | - Viviana I Risca
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Anshul Kundaje
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
- Department of Computer Science, Stanford University, Stanford, California, USA
| | - Paul A Khavari
- Department of Dermatology, Stanford University School of Medicine, Stanford, California, USA
| | - Thomas J Montine
- Department of Pathology, Stanford University School of Medicine, Stanford, California, USA
| | - William J Greenleaf
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Howard Y Chang
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, California, USA
- Department of Dermatology, Stanford University School of Medicine, Stanford, California, USA
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12
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Konermann S, Brigham MD, Trevino AE, Joung J, Abudayyeh OO, Barcena C, Hsu PD, Habib N, Gootenberg JS, Nishimasu H, Nureki O, Zhang F. Genome-scale transcriptional activation by an engineered CRISPR-Cas9 complex. Nature 2015. [PMID: 25494202 DOI: 10.1038/nature14136.genome-scale] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/17/2023]
Abstract
Systematic interrogation of gene function requires the ability to perturb gene expression in a robust and generalizable manner. Here we describe structure-guided engineering of a CRISPR-Cas9 complex to mediate efficient transcriptional activation at endogenous genomic loci. We used these engineered Cas9 activation complexes to investigate single-guide RNA (sgRNA) targeting rules for effective transcriptional activation, to demonstrate multiplexed activation of ten genes simultaneously, and to upregulate long intergenic non-coding RNA (lincRNA) transcripts. We also synthesized a library consisting of 70,290 guides targeting all human RefSeq coding isoforms to screen for genes that, upon activation, confer resistance to a BRAF inhibitor. The top hits included genes previously shown to be able to confer resistance, and novel candidates were validated using individual sgRNA and complementary DNA overexpression. A gene expression signature based on the top screening hits correlated with markers of BRAF inhibitor resistance in cell lines and patient-derived samples. These results collectively demonstrate the potential of Cas9-based activators as a powerful genetic perturbation technology.
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MESH Headings
- CRISPR-Associated Proteins/genetics
- CRISPR-Associated Proteins/metabolism
- CRISPR-Cas Systems/genetics
- Cell Line, Tumor
- Clustered Regularly Interspaced Short Palindromic Repeats/genetics
- DNA, Complementary/biosynthesis
- DNA, Complementary/genetics
- Drug Resistance, Neoplasm/drug effects
- Drug Resistance, Neoplasm/genetics
- Gene Expression Regulation, Neoplastic/genetics
- Gene Library
- Genetic Engineering/methods
- Genetic Loci/genetics
- Genetic Testing
- Genome, Human/genetics
- Humans
- Indoles/pharmacology
- Melanoma/drug therapy
- Melanoma/genetics
- Proto-Oncogene Proteins B-raf/antagonists & inhibitors
- RNA, Untranslated/biosynthesis
- RNA, Untranslated/genetics
- RNA, Untranslated/metabolism
- Reproducibility of Results
- Sulfonamides/pharmacology
- Transcriptional Activation/genetics
- Up-Regulation/genetics
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Affiliation(s)
- Silvana Konermann
- 1] Broad Institute of MIT and Harvard, 75 Ames Street, Cambridge, Massachusetts 02142, USA [2] McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [3] Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [4] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Mark D Brigham
- 1] Broad Institute of MIT and Harvard, 75 Ames Street, Cambridge, Massachusetts 02142, USA [2] McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [3] Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [4] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Alexandro E Trevino
- 1] Broad Institute of MIT and Harvard, 75 Ames Street, Cambridge, Massachusetts 02142, USA [2] McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [3] Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [4] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Julia Joung
- 1] Broad Institute of MIT and Harvard, 75 Ames Street, Cambridge, Massachusetts 02142, USA [2] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Omar O Abudayyeh
- 1] Broad Institute of MIT and Harvard, 75 Ames Street, Cambridge, Massachusetts 02142, USA [2] McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [3] Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [4] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Clea Barcena
- 1] Broad Institute of MIT and Harvard, 75 Ames Street, Cambridge, Massachusetts 02142, USA [2] McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [3] Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [4] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Patrick D Hsu
- 1] Broad Institute of MIT and Harvard, 75 Ames Street, Cambridge, Massachusetts 02142, USA [2] McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [3] Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [4] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Naomi Habib
- Broad Institute of MIT and Harvard, 75 Ames Street, Cambridge, Massachusetts 02142, USA
| | - Jonathan S Gootenberg
- 1] Broad Institute of MIT and Harvard, 75 Ames Street, Cambridge, Massachusetts 02142, USA [2] McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [3] Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [4] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [5] Department of Systems Biology, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Hiroshi Nishimasu
- 1] Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 2-11-16 Yayoi Bunkyo, Tokyo 113-0032, Japan [2] JST, PRESTO 2-11-16 Yayoi Bunkyo, Tokyo 113-0032, Japan
| | - Osamu Nureki
- Department of Biological Sciences, Graduate School of Science, The University of Tokyo, 2-11-16 Yayoi Bunkyo, Tokyo 113-0032, Japan
| | - Feng Zhang
- 1] Broad Institute of MIT and Harvard, 75 Ames Street, Cambridge, Massachusetts 02142, USA [2] McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [3] Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA [4] Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
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13
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Wu X, Scott DA, Kriz AJ, Chiu AC, Hsu PD, Dadon DB, Cheng AW, Trevino AE, Konermann S, Chen S, Jaenisch R, Zhang F, Sharp PA. Genome-wide binding of the CRISPR endonuclease Cas9 in mammalian cells. Nat Biotechnol 2014; 32:670-6. [PMID: 24752079 DOI: 10.1038/nbt.2889] [Citation(s) in RCA: 692] [Impact Index Per Article: 69.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2014] [Accepted: 03/27/2014] [Indexed: 12/26/2022]
Abstract
Bacterial type II CRISPR-Cas9 systems have been widely adapted for RNA-guided genome editing and transcription regulation in eukaryotic cells, yet their in vivo target specificity is poorly understood. Here we mapped genome-wide binding sites of a catalytically inactive Cas9 (dCas9) from Streptococcus pyogenes loaded with single guide RNAs (sgRNAs) in mouse embryonic stem cells (mESCs). Each of the four sgRNAs we tested targets dCas9 to between tens and thousands of genomic sites, frequently characterized by a 5-nucleotide seed region in the sgRNA and an NGG protospacer adjacent motif (PAM). Chromatin inaccessibility decreases dCas9 binding to other sites with matching seed sequences; thus 70% of off-target sites are associated with genes. Targeted sequencing of 295 dCas9 binding sites in mESCs transfected with catalytically active Cas9 identified only one site mutated above background levels. We propose a two-state model for Cas9 binding and cleavage, in which a seed match triggers binding but extensive pairing with target DNA is required for cleavage.
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Affiliation(s)
- Xuebing Wu
- 1] David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] Computational and Systems Biology Graduate Program, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - David A Scott
- 1] Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3]
| | - Andrea J Kriz
- 1] Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2]
| | - Anthony C Chiu
- 1] David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Patrick D Hsu
- 1] Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [3] Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA
| | - Daniel B Dadon
- 1] Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Albert W Cheng
- 1] Computational and Systems Biology Graduate Program, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Alexandro E Trevino
- 1] Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Silvana Konermann
- 1] Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Sidi Chen
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Rudolf Jaenisch
- Whitehead Institute for Biomedical Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Feng Zhang
- 1] Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA. [2] McGovern Institute for Brain Research, Department of Brain and Cognitive Sciences, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Phillip A Sharp
- 1] David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA. [2] Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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14
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Abstract
The RNA-guided, sequence-specific endonuclease Cas9 has been widely adopted as genome engineering tool due to its efficiency and ease of use. Derived from the microbial CRISPR (clustered regularly interspaced short palindromic repeat) type II adaptive immune system, Cas9 has now been successfully engineered for genome editing applications in a variety of animal and plant species. To reduce potential off-target mutagenesis by wild-type Cas9, homology- and structure-guided mutagenesis of Streptococcus pyogenes Cas9 catalytic domains has produced "nicking" enzymes (Cas9n) capable of inducing single-strand nicks rather than double-strand breaks. Since nicks are generally repaired with high fidelity in eukaryotic cells, Cas9n can be leveraged to mediate highly specific genome editing, either via nonhomologous end-joining or homology-directed repair. Here we describe the preparation, testing, and application of Cas9n reagents for precision mammalian genome engineering.
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Affiliation(s)
- Alexandro E Trevino
- Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, Massachusetts, USA; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Feng Zhang
- Broad Institute of MIT and Harvard, 7 Cambridge Center, Cambridge, Massachusetts, USA; McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
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