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Swaminath S, Russell AB. The use of single-cell RNA-seq to study heterogeneity at varying levels of virus-host interactions. PLoS Pathog 2024; 20:e1011898. [PMID: 38236826 PMCID: PMC10796064 DOI: 10.1371/journal.ppat.1011898] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2024] Open
Abstract
The outcome of viral infection depends on the diversity of the infecting viral population and the heterogeneity of the cell population that is infected. Until almost a decade ago, the study of these dynamic processes during viral infection was challenging and limited to certain targeted measurements. Presently, with the use of single-cell sequencing technology, the complex interface defined by the interactions of cells with infecting virus can now be studied across the breadth of the transcriptome in thousands of individual cells simultaneously. In this review, we will describe the use of single-cell RNA sequencing (scRNA-seq) to study the heterogeneity of viral infections, ranging from individual virions to the immune response between infected individuals. In addition, we highlight certain key experimental limitations and methodological decisions that are critical to analyzing scRNA-seq data at each scale.
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Affiliation(s)
- Sharmada Swaminath
- School of Biological Sciences, University of California, San Diego, La Jolla, California, United States of America
| | - Alistair B. Russell
- School of Biological Sciences, University of California, San Diego, La Jolla, California, United States of America
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52
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Wang JH, Wu C, Lian YN, Cao XW, Wang ZY, Dong JJ, Wu Q, Liu L, Sun L, Chen W, Chen WJ, Zhang Z, Zhuo M, Li XY. Single-cell RNA sequencing uncovers the cell type-dependent transcriptomic changes in the retrosplenial cortex after peripheral nerve injury. Cell Rep 2023; 42:113551. [PMID: 38048224 DOI: 10.1016/j.celrep.2023.113551] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 05/14/2023] [Accepted: 11/20/2023] [Indexed: 12/06/2023] Open
Abstract
The retrosplenial cortex (RSC) is a vital area for storing remote memory and has recently been found to undergo broad changes after peripheral nerve injury. However, little is known about the role of RSC in pain regulation. Here, we examine the involvement of RSC in the pain of mice with nerve injury. Notably, reducing the activities of calcium-/calmodulin-dependent protein kinase type II-positive splenial neurons chemogenetically increases paw withdrawal threshold and extends thermal withdrawal latency in mice with nerve injury. The single-cell or single-nucleus RNA-sequencing results predict enhanced excitatory synaptic transmissions in RSC induced by nerve injury. Local infusion of 1-naphthyl acetyl spermine into RSC to decrease the excitatory synaptic transmissions relieves pain and induces conditioned place preference. Our data indicate that RSC is critical for regulating physiological and neuropathic pain. The cell type-dependent transcriptomic information would help understand the molecular basis of neuropathic pain.
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Affiliation(s)
- Jing-Hua Wang
- Department of Psychiatry of the Fourth Affiliated Hospital, International Institutes of Medicine, Zhejiang University School of Medicine, Yiwu, Zhejiang 322000, China; NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain, Research and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Cheng Wu
- Department of Psychiatry of the Fourth Affiliated Hospital, International Institutes of Medicine, Zhejiang University School of Medicine, Yiwu, Zhejiang 322000, China; NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain, Research and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China; Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Zhejiang University, Haining, Zhejiang 314400, China; Biomedical Sciences, College of Medicine and Veterinary Medicine, The University of Edinburgh, Edinburgh EH8 9JU, UK
| | - Yan-Na Lian
- Department of Psychiatry of the Fourth Affiliated Hospital, International Institutes of Medicine, Zhejiang University School of Medicine, Yiwu, Zhejiang 322000, China; NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain, Research and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Xiao-Wen Cao
- Department of Psychiatry of the Fourth Affiliated Hospital, International Institutes of Medicine, Zhejiang University School of Medicine, Yiwu, Zhejiang 322000, China; NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain, Research and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Zi-Yue Wang
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain, Research and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Jia-Jun Dong
- Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Zhejiang University, Haining, Zhejiang 314400, China
| | - Qin Wu
- Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Zhejiang University, Haining, Zhejiang 314400, China
| | - Li Liu
- Core Facilities of the School of Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Li Sun
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain, Research and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China
| | - Wei Chen
- Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310016, China
| | - Wen-Juan Chen
- Department of Psychiatry, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang 310016, China
| | - Zhi Zhang
- Key Laboratory of Brain Functions and Diseases, School of Life Science, University of Science and Technology of China, Hefei, Anhui 230027, China
| | - Min Zhuo
- Department of Physiology, Faculty of Medicine, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Xiang-Yao Li
- Department of Psychiatry of the Fourth Affiliated Hospital, International Institutes of Medicine, Zhejiang University School of Medicine, Yiwu, Zhejiang 322000, China; NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain, Research and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, Zhejiang 310058, China; Zhejiang University-University of Edinburgh Institute, Zhejiang University School of Medicine, Zhejiang University, Haining, Zhejiang 314400, China; Biomedical Sciences, College of Medicine and Veterinary Medicine, The University of Edinburgh, Edinburgh EH8 9JU, UK.
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53
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Maden SK, Kwon SH, Huuki-Myers LA, Collado-Torres L, Hicks SC, Maynard KR. Challenges and opportunities to computationally deconvolve heterogeneous tissue with varying cell sizes using single-cell RNA-sequencing datasets. Genome Biol 2023; 24:288. [PMID: 38098055 PMCID: PMC10722720 DOI: 10.1186/s13059-023-03123-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Accepted: 11/24/2023] [Indexed: 12/17/2023] Open
Abstract
Deconvolution of cell mixtures in "bulk" transcriptomic samples from homogenate human tissue is important for understanding disease pathologies. However, several experimental and computational challenges impede transcriptomics-based deconvolution approaches using single-cell/nucleus RNA-seq reference atlases. Cells from the brain and blood have substantially different sizes, total mRNA, and transcriptional activities, and existing approaches may quantify total mRNA instead of cell type proportions. Further, standards are lacking for the use of cell reference atlases and integrative analyses of single-cell and spatial transcriptomics data. We discuss how to approach these key challenges with orthogonal "gold standard" datasets for evaluating deconvolution methods.
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Affiliation(s)
- Sean K Maden
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Sang Ho Kwon
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Louise A Huuki-Myers
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Leonardo Collado-Torres
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA
| | - Stephanie C Hicks
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
- Center for Computational Biology, Johns Hopkins University, Baltimore, MD, USA.
- Malone Center for Engineering in Healthcare, Johns Hopkins University, Baltimore, MD, USA.
| | - Kristen R Maynard
- Lieber Institute for Brain Development, Johns Hopkins Medical Campus, Baltimore, MD, USA.
- The Solomon H. Snyder Department of Neuroscience, Johns Hopkins School of Medicine, Baltimore, MD, USA.
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD, USA.
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54
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Zhu Q, Zhao X, Zhang Y, Li Y, Liu S, Han J, Sun Z, Wang C, Deng D, Wang S, Tang Y, Huang Y, Jiang S, Tian C, Chen X, Yuan Y, Li Z, Yang T, Lai T, Liu Y, Yang W, Zou X, Zhang M, Cui H, Liu C, Jin X, Hu Y, Chen A, Xu X, Li G, Hou Y, Liu L, Liu S, Fang L, Chen W, Wu L. Single cell multi-omics reveal intra-cell-line heterogeneity across human cancer cell lines. Nat Commun 2023; 14:8170. [PMID: 38071219 PMCID: PMC10710513 DOI: 10.1038/s41467-023-43991-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 11/27/2023] [Indexed: 12/18/2023] Open
Abstract
Human cancer cell lines have long served as tools for cancer research and drug discovery, but the presence and the source of intra-cell-line heterogeneity remain elusive. Here, we perform single-cell RNA-sequencing and ATAC-sequencing on 42 and 39 human cell lines, respectively, to illustrate both transcriptomic and epigenetic heterogeneity within individual cell lines. Our data reveal that transcriptomic heterogeneity is frequently observed in cancer cell lines of different tissue origins, often driven by multiple common transcriptional programs. Copy number variation, as well as epigenetic variation and extrachromosomal DNA distribution all contribute to the detected intra-cell-line heterogeneity. Using hypoxia treatment as an example, we demonstrate that transcriptomic heterogeneity could be reshaped by environmental stress. Overall, our study performs single-cell multi-omics of commonly used human cancer cell lines and offers mechanistic insights into the intra-cell-line heterogeneity and its dynamics, which would serve as an important resource for future cancer cell line-based studies.
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Affiliation(s)
- Qionghua Zhu
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China.
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China.
| | - Xin Zhao
- BGI Research, 518083, Shenzhen, China
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Yuanhang Zhang
- BGI Research, 518083, Shenzhen, China
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Yanping Li
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China
| | - Shang Liu
- BGI Research, 518083, Shenzhen, China
| | - Jingxuan Han
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China
| | - Zhiyuan Sun
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China
| | - Chunqing Wang
- BGI Research, 518083, Shenzhen, China
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Daqi Deng
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China
| | | | - Yisen Tang
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China
| | | | - Siyuan Jiang
- BGI Research, 518083, Shenzhen, China
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Chi Tian
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China
| | - Xi Chen
- BGI Research, 518083, Shenzhen, China
| | - Yue Yuan
- BGI Research, 518083, Shenzhen, China
| | - Zeyu Li
- BGI Research, 518083, Shenzhen, China
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | - Tao Yang
- China National GeneBank, 518120, Shenzhen, China
| | - Tingting Lai
- China National GeneBank, 518120, Shenzhen, China
| | - Yiqun Liu
- China National GeneBank, 518120, Shenzhen, China
| | - Wenzhen Yang
- China National GeneBank, 518120, Shenzhen, China
| | - Xuanxuan Zou
- BGI Research, 518083, Shenzhen, China
- College of Life Sciences, University of Chinese Academy of Sciences, 100049, Beijing, China
| | | | - Huanhuan Cui
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China
- Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, 518055, Shenzhen, China
| | | | - Xin Jin
- BGI Research, 518083, Shenzhen, China
| | - Yuhui Hu
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China
- Department of Pharmacology, School of Medicine, Southern University of Science and Technology, 518055, Shenzhen, China
| | - Ao Chen
- BGI Research, 518083, Shenzhen, China
- JFL-BGI STOmics Center, Jinfeng Laboratory, 401329, Chongqing, China
- The Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong, China
| | - Xun Xu
- BGI Research, 518083, Shenzhen, China
| | - Guipeng Li
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China
- Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, 518055, Shenzhen, China
| | - Yong Hou
- BGI Research, 518083, Shenzhen, China
- Shenzhen Key Laboratory of Single-Cell Omics, BGI-Shenzhen, 518100, Shenzhen, China
| | - Longqi Liu
- BGI Research, 518083, Shenzhen, China.
- BGI Research, 310012, Hangzhou, China.
- Shenzhen Bay Laboratory, 518000, Shenzhen, China.
| | - Shiping Liu
- BGI Research, 518083, Shenzhen, China.
- The Guangdong-Hong Kong Joint Laboratory on Immunological and Genetic Kidney Diseases, Guangdong, China.
- Shenzhen Key Laboratory of Single-Cell Omics, BGI-Shenzhen, 518100, Shenzhen, China.
- BGI Research, 310012, Hangzhou, China.
- Shenzhen Bay Laboratory, 518000, Shenzhen, China.
| | - Liang Fang
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China.
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China.
- Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, 518055, Shenzhen, China.
| | - Wei Chen
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China.
- Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, 518055, Shenzhen, China.
| | - Liang Wu
- BGI Research, 518083, Shenzhen, China.
- JFL-BGI STOmics Center, Jinfeng Laboratory, 401329, Chongqing, China.
- BGI Research, 401329, Chongqing, China.
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Muraleedharan Saraswathy V, Zhou L, Mokalled MH. Single-cell analysis of innate spinal cord regeneration identifies intersecting modes of neuronal repair. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.19.541505. [PMID: 37292638 PMCID: PMC10245778 DOI: 10.1101/2023.05.19.541505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Adult zebrafish have an innate ability to recover from severe spinal cord injury. Here, we report a comprehensive single nuclear RNA sequencing atlas that spans 6 weeks of regeneration. We identify cooperative roles for adult neurogenesis and neuronal plasticity during spinal cord repair. Neurogenesis of glutamatergic and GABAergic neurons restores the excitatory/inhibitory balance after injury. In addition, transient populations of injury-responsive neurons (iNeurons) show elevated plasticity between 1 and 3 weeks post-injury. Using cross-species transcriptomics and CRISPR/Cas9 mutagenesis, we found iNeurons are injury-surviving neurons that share transcriptional similarities with a rare population of spontaneously plastic mouse neurons. iNeurons are required for functional recovery and employ vesicular trafficking as an essential mechanism that underlies neuronal plasticity. This study provides a comprehensive resource of the cells and mechanisms that direct spinal cord regeneration and establishes zebrafish as a model of plasticity-driven neural repair.
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56
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Santiago CP, Gimmen MY, Lu Y, McNally MM, Duncan LH, Creamer TJ, Orzolek LD, Blackshaw S, Singh MS. Comparative Analysis of Single-cell and Single-nucleus RNA-sequencing in a Rabbit Model of Retinal Detachment-related Proliferative Vitreoretinopathy. OPHTHALMOLOGY SCIENCE 2023; 3:100335. [PMID: 37496518 PMCID: PMC10365955 DOI: 10.1016/j.xops.2023.100335] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 05/16/2023] [Accepted: 05/17/2023] [Indexed: 07/28/2023]
Abstract
Purpose Proliferative vitreoretinopathy (PVR) is the most common cause of failure of retinal reattachment surgery, and the molecular changes leading to this aberrant wound healing process are currently unknown. Our ultimate goal is to study PVR pathogenesis by employing single-cell transcriptomics to dissect cellular heterogeneity. Design Here we aimed to compare single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA-sequencing (snRNA-seq) of retinal PVR samples in the rabbit model. Participants Unilateral induction of PVR lesions in rabbit eyes with contralateral eyes serving as controls. Methods Proliferative vitreoretinopathy was induced unilaterally in Dutch Belted rabbits. At different timepoints after PVR induction, retinas were dissociated into either cells or nuclei suspension and processed for scRNA-seq or snRNA-seq. Main Outcome Measures Single cell and nuclei transcriptomic profiles of retinas after PVR induction. Results Single-cell RNA sequencing and snRNA-seq were conducted on retinas at 4 hours and 14 days after disease induction. Although the capture rate of unique molecular identifiers and genes were greater in scRNA-seq samples, overall gene expression profiles of individual cell types were highly correlated between scRNA-seq and snRNA-seq. A major disparity between the 2 sequencing modalities was the cell type capture rate, however, with glial cell types overrepresented in scRNA-seq, and inner retinal neurons were enriched by snRNA-seq. Furthermore, fibrotic Müller glia were overrepresented in snRNA-seq samples, whereas reactive Müller glia were overrepresented in scRNA-seq samples. Trajectory analyses were similar between the 2 methods, allowing for the combined analysis of the scRNA-seq and snRNA-seq data sets. Conclusions These findings highlight limitations of both scRNA-seq and snRNA-seq analysis and imply that use of both techniques together can more accurately identify transcriptional networks critical for aberrant fibrogenesis in PVR than using either in isolation. Financial Disclosures Proprietary or commercial disclosure may be found after the references.
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Affiliation(s)
- Clayton P. Santiago
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, Maryland
| | - Megan Y. Gimmen
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, Maryland
| | - Yuchen Lu
- Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Minda M. McNally
- Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Leighton H. Duncan
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, Maryland
| | - Tyler J. Creamer
- Institute for Basic Biomedical Sciences, Johns Hopkins University, Baltimore, Maryland
| | - Linda D. Orzolek
- Institute for Basic Biomedical Sciences, Johns Hopkins University, Baltimore, Maryland
| | - Seth Blackshaw
- Solomon H. Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, Maryland
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Institute for Cell Engineering, Johns Hopkins University, Baltimore, Maryland
- Kavli Neuroscience Discovery Institute, Johns Hopkins University, Baltimore, Maryland
| | - Mandeep S. Singh
- Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
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57
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Boussaty EC, Tedeschi N, Novotny M, Ninoyu Y, Du E, Draf C, Zhang Y, Manor U, Scheuermann RH, Friedman R. Cochlear transcriptome analysis of an outbred mouse population (CFW). Front Cell Neurosci 2023; 17:1256619. [PMID: 38094513 PMCID: PMC10716316 DOI: 10.3389/fncel.2023.1256619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 10/11/2023] [Indexed: 12/20/2023] Open
Abstract
Age-related hearing loss (ARHL) is the most common cause of hearing loss and one of the most prevalent conditions affecting the elderly worldwide. Despite evidence from our lab and others about its polygenic nature, little is known about the specific genes, cell types, and pathways involved in ARHL, impeding the development of therapeutic interventions. In this manuscript, we describe, for the first time, the complete cell-type specific transcriptome of the aging mouse cochlea using snRNA-seq in an outbred mouse model in relation to auditory threshold variation. Cochlear cell types were identified using unsupervised clustering and annotated via a three-tiered approach-first by linking to expression of known marker genes, then using the NSForest algorithm to select minimum cluster-specific marker genes and reduce dimensional feature space for statistical comparison of our clusters with existing publicly-available data sets on the gEAR website, and finally, by validating and refining the annotations using Multiplexed Error Robust Fluorescence In Situ Hybridization (MERFISH) and the cluster-specific marker genes as probes. We report on 60 unique cell-types expanding the number of defined cochlear cell types by more than two times. Importantly, we show significant specific cell type increases and decreases associated with loss of hearing acuity implicating specific subsets of hair cell subtypes, ganglion cell subtypes, and cell subtypes within the stria vascularis in this model of ARHL. These results provide a view into the cellular and molecular mechanisms responsible for age-related hearing loss and pathways for therapeutic targeting.
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Affiliation(s)
- Ely Cheikh Boussaty
- Department of Otolaryngology, University of California, San Diego, La Jolla, CA, United States
| | - Neil Tedeschi
- J. Craig Venter Institute, La Jolla, CA, United States
| | - Mark Novotny
- J. Craig Venter Institute, La Jolla, CA, United States
| | - Yuzuru Ninoyu
- Department of Otolaryngology, University of California, San Diego, La Jolla, CA, United States
| | - Eric Du
- Department of Otolaryngology, University of California, San Diego, La Jolla, CA, United States
| | - Clara Draf
- Department of Otolaryngology, University of California, San Diego, La Jolla, CA, United States
| | - Yun Zhang
- J. Craig Venter Institute, La Jolla, CA, United States
| | - Uri Manor
- Department of Cell and Developmental Biology, University of California San Diego, Salk Institute for Biological Studies, Waitt Advanced Biophotonics Center, La Jolla, CA, United States
| | - Richard H. Scheuermann
- J. Craig Venter Institute, La Jolla, CA, United States
- Department of Pathology, University of California, San Diego, La Jolla, CA, United States
| | - Rick Friedman
- Department of Otolaryngology, University of California, San Diego, La Jolla, CA, United States
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58
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Golan N, Ehrlich D, Bonanno J, O'Brien RF, Murillo M, Kauer SD, Ravindra N, Van Dijk D, Cafferty WB. Anatomical Diversity of the Adult Corticospinal Tract Revealed by Single-Cell Transcriptional Profiling. J Neurosci 2023; 43:7929-7945. [PMID: 37748862 PMCID: PMC10669816 DOI: 10.1523/jneurosci.0811-22.2023] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 07/28/2023] [Accepted: 08/01/2023] [Indexed: 09/27/2023] Open
Abstract
The corticospinal tract (CST) forms a central part of the voluntary motor apparatus in all mammals. Thus, injury, disease, and subsequent degeneration within this pathway result in chronic irreversible functional deficits. Current strategies to repair the damaged CST are suboptimal in part because of underexplored molecular heterogeneity within the adult tract. Here, we combine spinal retrograde CST tracing with single-cell RNA sequencing (scRNAseq) in adult male and female mice to index corticospinal neuron (CSN) subtypes that differentially innervate the forelimb and hindlimb. We exploit publicly available datasets to confer anatomic specialization among CSNs and show that CSNs segregate not only along the forelimb and hindlimb axis but also by supraspinal axon collateralization. These anatomically defined transcriptional data allow us to use machine learning tools to build classifiers that discriminate between CSNs and cortical layer 2/3 and nonspinally terminating layer 5 neurons in M1 and separately identify limb-specific CSNs. Using these tools, CSN subtypes can be differentially identified to study postnatal patterning of the CST in vivo, leveraged to screen for novel limb-specific axon growth survival and growth activators in vitro, and ultimately exploited to repair the damaged CST after injury and disease.SIGNIFICANCE STATEMENT Therapeutic interventions designed to repair the damaged CST after spinal cord injury have remained functionally suboptimal in part because of an incomplete understanding of the molecular heterogeneity among subclasses of CSNs. Here, we combine spinal retrograde labeling with scRNAseq and annotate a CSN index by the termination pattern of their primary axon in the cervical or lumbar spinal cord and supraspinal collateral terminal fields. Using machine learning we have confirmed the veracity of our CSN gene lists to train classifiers to identify CSNs among all classes of neurons in primary motor cortex to study the development, patterning, homeostasis, and response to injury and disease, and ultimately target streamlined repair strategies to this critical motor pathway.
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Affiliation(s)
- Noa Golan
- Interdepartmental Neuroscience Program, Yale University School, New Haven, Connecticut 06511
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Daniel Ehrlich
- Interdepartmental Neuroscience Program, Yale University School, New Haven, Connecticut 06511
- Department of Psychiatry, Yale University School, New Haven, Connecticut 06511
| | - James Bonanno
- Interdepartmental Neuroscience Program, Yale University School, New Haven, Connecticut 06511
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Rory F O'Brien
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Matias Murillo
- Interdepartmental Neuroscience Program, Yale University School, New Haven, Connecticut 06511
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Sierra D Kauer
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
| | - Neal Ravindra
- Department of Internal Medicine, Yale University School, New Haven, Connecticut 06511
- Department of Computer Science, Yale University School, New Haven, Connecticut 06511
| | - David Van Dijk
- Department of Internal Medicine, Yale University School, New Haven, Connecticut 06511
- Department of Computer Science, Yale University School, New Haven, Connecticut 06511
| | - William B Cafferty
- Department of Neurology, Yale University School, New Haven, Connecticut 06511
- Department of Neuroscience, Yale University School, New Haven, Connecticut 06511
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Gaunt JR, Zainolabidin N, Yip AKK, Tan JM, Low AYT, Chen AI, Ch'ng TH. Cytokine enrichment in deep cerebellar nuclei is contributed by multiple glial populations and linked to reduced amyloid plaque pathology. J Neuroinflammation 2023; 20:269. [PMID: 37978387 PMCID: PMC10656954 DOI: 10.1186/s12974-023-02913-8] [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: 04/24/2023] [Accepted: 09/28/2023] [Indexed: 11/19/2023] Open
Abstract
Alzheimer's disease (AD) pathology and amyloid-beta (Aβ) plaque deposition progress slowly in the cerebellum compared to other brain regions, while the entorhinal cortex (EC) is one of the most vulnerable regions. Using a knock-in AD mouse model (App KI), we show that within the cerebellum, the deep cerebellar nuclei (DCN) has particularly low accumulation of Aβ plaques. To identify factors that might underlie differences in the progression of AD-associated neuropathology across regions, we profiled gene expression in single nuclei (snRNAseq) across all cell types in the DCN and EC of wild-type (WT) and App KI male mice at age 7 months. We found differences in expression of genes associated with inflammatory activation, PI3K-AKT signalling, and neuron support functions between both regions and genotypes. In WT mice, the expression of interferon-response genes in microglia is higher in the DCN than the EC and this enrichment is confirmed by RNA in situ hybridisation, and measurement of inflammatory cytokines by protein array. Our analyses also revealed that multiple glial populations are responsible for establishing this cytokine-enriched niche. Furthermore, homogenates derived from the DCN induced inflammatory gene expression in BV2 microglia. We also assessed the relationship between the DCN microenvironment and Aβ pathology by depleting microglia using a CSF1R inhibitor PLX5622 and saw that, surprisingly, the expression of a subset of inflammatory cytokines was increased while plaque abundance in the DCN was further reduced. Overall, our study revealed the presence of a cytokine-enriched microenvironment unique to the DCN that when modulated, can alter plaque deposition.
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Affiliation(s)
- Jessica R Gaunt
- Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Science Building, 11 Mandalay Road, Singapore, 308232, Singapore
| | - Norliyana Zainolabidin
- Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Science Building, 11 Mandalay Road, Singapore, 308232, Singapore
| | - Alaric K K Yip
- Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Science Building, 11 Mandalay Road, Singapore, 308232, Singapore
| | - Jia Min Tan
- Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Science Building, 11 Mandalay Road, Singapore, 308232, Singapore
| | - Aloysius Y T Low
- Department of Biology, University of Pennsylvania, Philadelphia, PA, USA
| | - Albert I Chen
- Center for Aging Research, Scintillon Institute, 6868 Nancy Ridge Drive, San Diego, CA, 92121, USA.
- Molecular Neurobiology Laboratory, Salk Institute, La Jolla, CA, 92037, USA.
| | - Toh Hean Ch'ng
- Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Science Building, 11 Mandalay Road, Singapore, 308232, Singapore.
- School of Biological Science, Nanyang Technological University, Singapore, 63755, Singapore.
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60
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Nance RL, Wang X, Sandey M, Matz BM, Thomas A, Smith BF. Single-Nuclei Multiome (ATAC + Gene Expression) Sequencing of a Primary Canine Osteosarcoma Elucidates Intra-Tumoral Heterogeneity and Characterizes the Tumor Microenvironment. Int J Mol Sci 2023; 24:16365. [PMID: 38003552 PMCID: PMC10671194 DOI: 10.3390/ijms242216365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Revised: 11/09/2023] [Accepted: 11/11/2023] [Indexed: 11/26/2023] Open
Abstract
Osteosarcoma (OSA) is a highly aggressive bone tumor primarily affecting pediatric or adolescent humans and large-breed dogs. Canine OSA shares striking similarities with its human counterpart, making it an invaluable translational model for uncovering the disease's complexities and developing novel therapeutic strategies. Tumor heterogeneity, a hallmark of OSA, poses significant challenges to effective treatment due to the evolution of diverse cell populations that influence tumor growth, metastasis, and resistance to therapies. In this study, we apply single-nuclei multiome sequencing, encompassing ATAC (Assay for Transposase-Accessible Chromatin) and GEX (Gene Expression, or RNA) sequencing, to a treatment-naïve primary canine osteosarcoma. This comprehensive approach reveals the complexity of the tumor microenvironment by simultaneously capturing the transcriptomic and epigenomic profiles within the same nucleus. Furthermore, these results are analyzed in conjunction with bulk RNA sequencing and differential analysis of the same tumor and patient-matched normal bone. By delving into the intricacies of OSA at this unprecedented level of detail, we aim to unravel the underlying mechanisms driving intra-tumoral heterogeneity, opening new avenues for therapeutic interventions in both human and canine patients. This study pioneers an approach that is broadly applicable, while demonstrating significant heterogeneity in the context of a single individual's tumor.
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Affiliation(s)
- Rebecca L. Nance
- Scott-Ritchey Research Center, Auburn University College of Veterinary Medicine, Auburn, AL 36849, USA; (R.L.N.); (X.W.)
- Department of Pathobiology, Auburn University College of Veterinary Medicine, Auburn, AL 36849, USA;
| | - Xu Wang
- Scott-Ritchey Research Center, Auburn University College of Veterinary Medicine, Auburn, AL 36849, USA; (R.L.N.); (X.W.)
- Department of Pathobiology, Auburn University College of Veterinary Medicine, Auburn, AL 36849, USA;
| | - Maninder Sandey
- Department of Pathobiology, Auburn University College of Veterinary Medicine, Auburn, AL 36849, USA;
| | - Brad M. Matz
- Department of Clinical Sciences, Auburn University College of Veterinary Medicine, Auburn, AL 36849, USA;
| | - AriAnna Thomas
- Department of Nursing, Tuskegee University, Tuskegee, AL 36088, USA;
| | - Bruce F. Smith
- Scott-Ritchey Research Center, Auburn University College of Veterinary Medicine, Auburn, AL 36849, USA; (R.L.N.); (X.W.)
- Department of Pathobiology, Auburn University College of Veterinary Medicine, Auburn, AL 36849, USA;
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61
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Magrath JW, Goldberg IN, Truong DD, Hartono AB, Sampath SS, Jackson CE, Ghosh A, Cardin DL, Zhang H, Ludwig JA, Lee SB. Enzalutamide Induces Cytotoxicity in Desmoplastic Small Round Cell Tumor Independent of the Androgen Receptor. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.06.565842. [PMID: 37986851 PMCID: PMC10659336 DOI: 10.1101/2023.11.06.565842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Desmoplastic Small Round Cell Tumor (DSRCT) is a rare, pediatric cancer caused by the EWSR1::WT1 fusion protein. DSRCT predominantly occurs in males, which comprise 80-90% of the patient population. While the reason for this male predominance remains unknown, one hypothesis is that the androgen receptor (AR) plays a critical role in DSRCT and elevated testosterone levels in males help drive tumor growth. Here, we demonstrate that AR is highly expressed in DSRCT relative to other fusion-driven sarcomas and that the AR antagonists enzalutamide and flutamide reduce DSRCT growth. However, despite these findings, which suggest an important role for AR in DSRCT, we show that DSRCT cell lines form xenografts in female mice at the same rate as male mice and AR depletion does not significantly alter DSRCT growth in vitro. Further, we find that AR antagonists reduce DSRCT growth in cells depleted of AR, establishing an AR-independent mechanism of action. These findings suggest that AR dependence is not the reason for male predominance in DSRCT and that AR-targeted therapies may provide therapeutic benefit primarily through an AR-independent mechanism that requires further elucidation.
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Affiliation(s)
- Justin W Magrath
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave. New Orleans, LA, USA
| | - Ilon N Goldberg
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave. New Orleans, LA, USA
| | - Danh D Truong
- Sarcoma Medical Oncology Department, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Alifiani B Hartono
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave. New Orleans, LA, USA
| | - Shruthi Sanjitha Sampath
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave. New Orleans, LA, USA
| | - Chandler E Jackson
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave. New Orleans, LA, USA
| | - Anushka Ghosh
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave. New Orleans, LA, USA
| | - Derrick L Cardin
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave. New Orleans, LA, USA
| | - Haitao Zhang
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave. New Orleans, LA, USA
| | - Joseph A Ludwig
- Sarcoma Medical Oncology Department, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Sean B Lee
- Department of Pathology and Laboratory Medicine, Tulane University School of Medicine, 1430 Tulane Ave. New Orleans, LA, USA
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62
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Konopka G, Bhaduri A. Functional genomics and systems biology in human neuroscience. Nature 2023; 623:274-282. [PMID: 37938705 DOI: 10.1038/s41586-023-06686-1] [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: 02/23/2023] [Accepted: 09/27/2023] [Indexed: 11/09/2023]
Abstract
Neuroscience research has entered a phase of key discoveries in the realm of neurogenomics owing to strong financial and intellectual support for resource building and tool development. The previous challenge of tissue heterogeneity has been met with the application of techniques that can profile individual cells at scale. Moreover, the ability to perturb genes, gene regulatory elements and neuronal activity in a cell-type-specific manner has been integrated with gene expression studies to uncover the functional underpinnings of the genome at a systems level. Although these insights have necessarily been grounded in model systems, we now have the opportunity to apply these approaches in humans and in human tissue, thanks to advances in human genetics, brain imaging and tissue collection. We acknowledge that there will probably always be limits to the extent to which we can apply the genomic tools developed in model systems to human neuroscience; however, as we describe in this Perspective, the neuroscience field is now primed with an optimal foundation for tackling this ambitious challenge. The application of systems-level network analyses to these datasets will facilitate a deeper appreciation of human neurogenomics that cannot otherwise be achieved from directly observable phenomena.
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Affiliation(s)
- Genevieve Konopka
- Department of Neuroscience, UT Southwestern Medical Center, Dallas, TX, USA.
- Peter O'Donnell Jr Brain Institute, UT Southwestern Medical Center, Dallas, TX, USA.
| | - Aparna Bhaduri
- Department of Biological Chemistry, University of California, Los Angeles, CA, USA.
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63
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Waag R, Bohacek J. Single-Nucleus RNA-Sequencing in Brain Tissue. Curr Protoc 2023; 3:e919. [PMID: 37987152 DOI: 10.1002/cpz1.919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Neuroscience research greatly benefits from single-cell sequencing technologies, which can reveal transcriptional alterations on a cellular level. However, preparing single-cell suspensions is technically challenging, requires experience, and has several limitations that can influence the transcriptional readout. Performing sequencing of single nuclei instead of single cells alleviates several of the challenges of sample preparation and highlights acute nuclear transcription. Here, we provide a protocol to prepare a nuclei suspension for single-nucleus RNA-sequencing for cell type-specific transcriptional profiling of brain tissue using the 10x Genomics single-cell gene expression assay. Furthermore, we highlight important aspects to consider during experimental design and data analysis. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Preparation of single-nucleus suspension Basic Protocol 2: Preparation and sequencing of single-nucleus libraries for RNA-seq.
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Affiliation(s)
- Rebecca Waag
- Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, ETH Zurich and University of Zurich, Zurich, Switzerland
| | - Johannes Bohacek
- Laboratory of Molecular and Behavioral Neuroscience, Institute for Neuroscience, Department of Health Sciences and Technology, ETH Zurich, Zurich, Switzerland
- Neuroscience Center Zurich, ETH Zurich and University of Zurich, Zurich, Switzerland
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64
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Yang S, Lan T, Wei R, Zhang L, Lin L, Du H, Huang Y, Zhang G, Huang S, Shi M, Wang C, Wang Q, Li R, Han L, Tang D, Li H, Zhang H, Cui J, Lu H, Huang J, Luo Y, Li D, Wan QH, Liu H, Fang SG. Single-nucleus transcriptome inventory of giant panda reveals cellular basis for fitness optimization under low metabolism. BMC Biol 2023; 21:222. [PMID: 37858133 PMCID: PMC10588165 DOI: 10.1186/s12915-023-01691-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 08/25/2023] [Indexed: 10/21/2023] Open
Abstract
BACKGROUND Energy homeostasis is essential for the adaptation of animals to their environment and some wild animals keep low metabolism adaptive to their low-nutrient dietary supply. Giant panda is such a typical low-metabolic mammal exhibiting species specialization of extremely low daily energy expenditure. It has low levels of basal metabolic rate, thyroid hormone, and physical activities, whereas the cellular bases of its low metabolic adaptation remain rarely explored. RESULTS In this study, we generate a single-nucleus transcriptome atlas of 21 organs/tissues from a female giant panda. We focused on the central metabolic organ (liver) and dissected cellular metabolic status by cross-species comparison. Adaptive expression mode (i.e., AMPK related) was prominently displayed in the hepatocyte of giant panda. In the highest energy-consuming organ, the heart, we found a possibly optimized utilization of fatty acid. Detailed cell subtype annotation of endothelial cells showed the uterine-specific deficiency of blood vascular subclasses, indicating a potential adaptation for a low reproductive energy expenditure. CONCLUSIONS Our findings shed light on the possible cellular basis and transcriptomic regulatory clues for the low metabolism in giant pandas and helped to understand physiological adaptation response to nutrient stress.
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Affiliation(s)
- Shangchen Yang
- MOE Key Laboratory of Biosystems Homeostasis & Protection, State Conservation Centre for Gene Resources of Endangered Wildlife, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Tianming Lan
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China
- BGI Life Science Joint Research Center, Northeast Forestry University, Harbin, 150040, China
| | - Rongping Wei
- Key Laboratory of State Forestry and Grassland Administration (State Park Administration) on Conservation Biology of Rare Animals in the Giant Panda National Park, China Conservation and Research Center for the Giant Panda, Dujiangyan, 611830, China
| | - Ling Zhang
- China Wildlife Conservation Association, Beijing, 100714, China
| | - Lin Lin
- Department of Biomedicine, Aarhus University, 8000, Aarhus, Denmark
- Lars Bolund Institute of Regenerative Medicine, Qingdao-Europe Advanced Institute for Life Sciences, BGI-Qingdao, Qingdao, 266555, China
- Steno Diabetes Center Aarhus, Aarhus University Hospital, 8000, Aarhus, Denmark
| | - Hanyu Du
- MOE Key Laboratory of Biosystems Homeostasis & Protection, State Conservation Centre for Gene Resources of Endangered Wildlife, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China
| | - Yunting Huang
- China National GeneBank, BGI-Shenzhen, Shenzhen, 518120, China
| | - Guiquan Zhang
- Key Laboratory of State Forestry and Grassland Administration (State Park Administration) on Conservation Biology of Rare Animals in the Giant Panda National Park, China Conservation and Research Center for the Giant Panda, Dujiangyan, 611830, China
| | - Shan Huang
- Key Laboratory of State Forestry and Grassland Administration (State Park Administration) on Conservation Biology of Rare Animals in the Giant Panda National Park, China Conservation and Research Center for the Giant Panda, Dujiangyan, 611830, China
| | - Minhui Shi
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Chengdong Wang
- Key Laboratory of State Forestry and Grassland Administration (State Park Administration) on Conservation Biology of Rare Animals in the Giant Panda National Park, China Conservation and Research Center for the Giant Panda, Dujiangyan, 611830, China
| | - Qing Wang
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Rengui Li
- Key Laboratory of State Forestry and Grassland Administration (State Park Administration) on Conservation Biology of Rare Animals in the Giant Panda National Park, China Conservation and Research Center for the Giant Panda, Dujiangyan, 611830, China
| | - Lei Han
- College of Wildlife Resources, Northeast Forestry University, Harbin, 150040, China
| | - Dan Tang
- Key Laboratory of State Forestry and Grassland Administration (State Park Administration) on Conservation Biology of Rare Animals in the Giant Panda National Park, China Conservation and Research Center for the Giant Panda, Dujiangyan, 611830, China
| | - Haimeng Li
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Hemin Zhang
- Key Laboratory of State Forestry and Grassland Administration (State Park Administration) on Conservation Biology of Rare Animals in the Giant Panda National Park, China Conservation and Research Center for the Giant Panda, Dujiangyan, 611830, China
| | - Jie Cui
- The Genome Synthesis and Editing Platform, BGI-Shenzhen, Shenzhen, 518120, China
| | - Haorong Lu
- China National GeneBank, BGI-Shenzhen, Shenzhen, 518120, China
- Guangdong Provincial Key Laboratory of Genome Read and Write, BGI-Shenzhen, Shenzhen, 518120, China
| | - Jinrong Huang
- Lars Bolund Institute of Regenerative Medicine, Qingdao-Europe Advanced Institute for Life Sciences, BGI-Qingdao, Qingdao, 266555, China
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Yonglun Luo
- Department of Biomedicine, Aarhus University, 8000, Aarhus, Denmark
- Lars Bolund Institute of Regenerative Medicine, Qingdao-Europe Advanced Institute for Life Sciences, BGI-Qingdao, Qingdao, 266555, China
- Steno Diabetes Center Aarhus, Aarhus University Hospital, 8000, Aarhus, Denmark
| | - Desheng Li
- Key Laboratory of State Forestry and Grassland Administration (State Park Administration) on Conservation Biology of Rare Animals in the Giant Panda National Park, China Conservation and Research Center for the Giant Panda, Dujiangyan, 611830, China.
| | - Qiu-Hong Wan
- MOE Key Laboratory of Biosystems Homeostasis & Protection, State Conservation Centre for Gene Resources of Endangered Wildlife, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
| | - Huan Liu
- State Key Laboratory of Agricultural Genomics, BGI-Shenzhen, Shenzhen, 518083, China.
- BGI Life Science Joint Research Center, Northeast Forestry University, Harbin, 150040, China.
| | - Sheng-Guo Fang
- MOE Key Laboratory of Biosystems Homeostasis & Protection, State Conservation Centre for Gene Resources of Endangered Wildlife, College of Life Sciences, Zhejiang University, Hangzhou, 310058, China.
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65
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Wang W, Li T, Wang Z, Yin Y, Zhang S, Wang C, Hu X, Lu S. Bibliometric analysis of research on neurodegenerative diseases and single-cell RNA sequencing: Opportunities and challenges. iScience 2023; 26:107833. [PMID: 37736042 PMCID: PMC10509354 DOI: 10.1016/j.isci.2023.107833] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 07/18/2023] [Accepted: 09/01/2023] [Indexed: 09/23/2023] Open
Abstract
Neurodegeneration, characterized by the progressive deterioration in neuronal structure or function, presents an elusive mechanism. The use of single-cell RNA sequencing (scRNA-seq) technology in the clinic is becoming increasingly prevalent in recent decades. This technology offers unparalleled cell-level insights into neurodegenerative diseases, establishing itself as a potent tool for elucidating these diseases underlying mechanisms. Here, we made a deep investigation for scRNA-seq research in neurodegenerative diseases using bibliometric analysis from 2009 to 2022. We observed a robust upward trajectory in the number of publications on this subject. The United States stood out as the principal contributor to this expanding field. Specifically, the University of California System exhibited notable research prowess in this field. Alzheimer disease and Parkinson disease were the diseases most frequently investigated. Key research hotspots include the creation of a molecular brain atlas and identification of vulnerable neuronal subpopulations and potential therapeutic targets at the transcriptomic level.
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Affiliation(s)
- Wei Wang
- Department of Orthopedics, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Tianhua Li
- Department of Neurosurgery, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Zheng Wang
- Department of Orthopedics, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Yaxin Yin
- Department of Orthopedics, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Sitao Zhang
- Department of Orthopedics, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Chaodong Wang
- Department of Neurology, National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital of Capital Medical University, Beijing, China
| | - Xinli Hu
- Department of Orthopedics, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Shibao Lu
- Department of Orthopedics, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
- National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
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66
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Johansen N, Somasundaram S, Travaglini KJ, Yanny AM, Shumyatcher M, Casper T, Cobbs C, Dee N, Ellenbogen R, Ferreira M, Goldy J, Guzman J, Gwinn R, Hirschstein D, Jorstad NL, Keene CD, Ko A, Levi BP, Ojemann JG, Pham T, Shapovalova N, Silbergeld D, Sulc J, Torkelson A, Tung H, Smith K, Lein ES, Bakken TE, Hodge RD, Miller JA. Interindividual variation in human cortical cell type abundance and expression. Science 2023; 382:eadf2359. [PMID: 37824649 DOI: 10.1126/science.adf2359] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 07/30/2023] [Indexed: 10/14/2023]
Abstract
Single-cell transcriptomic studies have identified a conserved set of neocortical cell types from small postmortem cohorts. We extended these efforts by assessing cell type variation across 75 adult individuals undergoing epilepsy and tumor surgeries. Nearly all nuclei map to one of 125 robust cell types identified in the middle temporal gyrus. However, we found interindividual variance in abundances and gene expression signatures, particularly in deep-layer glutamatergic neurons and microglia. A minority of donor variance is explainable by age, sex, ancestry, disease state, and cell state. Genomic variation was associated with expression of 150 to 250 genes for most cell types. This characterization of cellular variation provides a baseline for cell typing in health and disease.
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Affiliation(s)
| | | | | | | | | | - Tamara Casper
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Charles Cobbs
- Swedish Neuroscience Institute, Seattle,WA 98122, USA
| | - Nick Dee
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Richard Ellenbogen
- Department of Neurological Surgery, University of Washington, Seattle, WA 98104, USA
| | - Manuel Ferreira
- Department of Neurological Surgery, University of Washington, Seattle, WA 98104, USA
| | - Jeff Goldy
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Junitta Guzman
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Ryder Gwinn
- Swedish Neuroscience Institute, Seattle,WA 98122, USA
| | | | | | - C Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104, USA
| | - Andrew Ko
- Department of Neurological Surgery, University of Washington, Seattle, WA 98104, USA
| | - Boaz P Levi
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Jeffrey G Ojemann
- Department of Neurological Surgery, University of Washington, Seattle, WA 98104, USA
| | - Thanh Pham
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | | | - Daniel Silbergeld
- Department of Neurological Surgery, University of Washington, Seattle, WA 98104, USA
| | - Josef Sulc
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Amy Torkelson
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Herman Tung
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Kimberly Smith
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Ed S Lein
- Allen Institute for Brain Science, Seattle, WA 98109, USA
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67
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Dugger SA, Dhindsa RS, Sampaio GDA, Ressler AK, Rafikian EE, Petri S, Letts VA, Teoh J, Ye J, Colombo S, Peng Y, Yang M, Boland MJ, Frankel WN, Goldstein DB. Neurodevelopmental deficits and cell-type-specific transcriptomic perturbations in a mouse model of HNRNPU haploinsufficiency. PLoS Genet 2023; 19:e1010952. [PMID: 37782669 PMCID: PMC10569524 DOI: 10.1371/journal.pgen.1010952] [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: 03/29/2023] [Revised: 10/12/2023] [Accepted: 09/01/2023] [Indexed: 10/04/2023] Open
Abstract
Heterozygous de novo loss-of-function mutations in the gene expression regulator HNRNPU cause an early-onset developmental and epileptic encephalopathy. To gain insight into pathological mechanisms and lay the potential groundwork for developing targeted therapies, we characterized the neurophysiologic and cell-type-specific transcriptomic consequences of a mouse model of HNRNPU haploinsufficiency. Heterozygous mutants demonstrated global developmental delay, impaired ultrasonic vocalizations, cognitive dysfunction and increased seizure susceptibility, thus modeling aspects of the human disease. Single-cell RNA-sequencing of hippocampal and neocortical cells revealed widespread, yet modest, dysregulation of gene expression across mutant neuronal subtypes. We observed an increased burden of differentially-expressed genes in mutant excitatory neurons of the subiculum-a region of the hippocampus implicated in temporal lobe epilepsy. Evaluation of transcriptomic signature reversal as a therapeutic strategy highlights the potential importance of generating cell-type-specific signatures. Overall, this work provides insight into HNRNPU-mediated disease mechanisms and provides a framework for using single-cell RNA-sequencing to study transcriptional regulators implicated in disease.
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Affiliation(s)
- Sarah A. Dugger
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Ryan S. Dhindsa
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
- Department of Pathology & Immunology, Baylor College of Medicine, Houston, Texas, United States of America
- Jan and Dan Duncan Neurological Research Institute of Texas Children’s Hospital, Houston, Texas, United States of America
| | - Gabriela De Almeida Sampaio
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Andrew K. Ressler
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Elizabeth E. Rafikian
- Mouse Neurobehavioral Core Facility, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Sabrina Petri
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Verity A. Letts
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - JiaJie Teoh
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Junqiang Ye
- Department of Biochemistry and Molecular Biophysics, Columbia University Irving Medical Center, New York, New York, United States of America
- Zuckerman Mind Brain and Behavior Institute, Columbia University, New York, New York, United States of America
| | - Sophie Colombo
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Yueqing Peng
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
- Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Mu Yang
- Mouse Neurobehavioral Core Facility, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Michael J. Boland
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
- Department of Neurology, Columbia University Irving Medical Center, New York, New York, United States of America
| | - Wayne N. Frankel
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, New York, United States of America
| | - David B. Goldstein
- Institute for Genomic Medicine, Columbia University Irving Medical Center, New York, New York, United States of America
- Department of Genetics and Development, Columbia University Irving Medical Center, New York, New York, United States of America
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68
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Bageritz J, Krausse N, Yousefian S, Leible S, Valentini E, Boutros M. Glyoxal as an alternative fixative for single-cell RNA sequencing. G3 (BETHESDA, MD.) 2023; 13:jkad160. [PMID: 37494060 PMCID: PMC10542564 DOI: 10.1093/g3journal/jkad160] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Revised: 07/10/2023] [Accepted: 07/11/2023] [Indexed: 07/27/2023]
Abstract
Single-cell RNA sequencing has become an important method to identify cell types, delineate the trajectories of cell differentiation in whole organisms, and understand the heterogeneity in cellular responses. Nevertheless, sample collection and processing remain a severe bottleneck for single-cell RNA sequencing experiments. Cell isolation protocols often lead to significant changes in the transcriptomes of cells, requiring novel methods to preserve cell states. Here, we developed and benchmarked protocols using glyoxal as a fixative for single-cell RNA sequencing applications. Using Drop-seq methodology, we detected a large number of transcripts and genes from glyoxal-fixed Drosophila cells after single-cell RNA sequencing. The effective glyoxal fixation of transcriptomes in Drosophila and human cells was further supported by a high correlation of gene expression data between glyoxal-fixed and unfixed samples. Accordingly, we also found highly expressed genes overlapping to a large extent between experimental conditions. These results indicated that our fixation protocol did not induce considerable changes in gene expression and conserved the transcriptome for subsequent single-cell isolation procedures. In conclusion, we present glyoxal as a suitable fixative for Drosophila cells and potentially cells of other species that allow high-quality single-cell RNA sequencing applications.
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Affiliation(s)
- Josephine Bageritz
- Division Signaling and Functional Genomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Niklas Krausse
- Division Signaling and Functional Genomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Schayan Yousefian
- Division Signaling and Functional Genomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Svenja Leible
- Division Signaling and Functional Genomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Erica Valentini
- Division Signaling and Functional Genomics, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
| | - Michael Boutros
- Division Signaling and Functional Genomics, BioQuant and Medical Faculty Mannheim, German Cancer Research Center (DKFZ), Heidelberg University, D-69120 Heidelberg, Germany
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69
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Salamon I, Park Y, Miškić T, Kopić J, Matteson P, Page NF, Roque A, McAuliffe GW, Favate J, Garcia-Forn M, Shah P, Judaš M, Millonig JH, Kostović I, De Rubeis S, Hart RP, Krsnik Ž, Rasin MR. Celf4 controls mRNA translation underlying synaptic development in the prenatal mammalian neocortex. Nat Commun 2023; 14:6025. [PMID: 37758766 PMCID: PMC10533865 DOI: 10.1038/s41467-023-41730-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 09/18/2023] [Indexed: 09/29/2023] Open
Abstract
Abnormalities in neocortical and synaptic development are linked to neurodevelopmental disorders. However, the molecular and cellular mechanisms governing initial synapse formation in the prenatal neocortex remain poorly understood. Using polysome profiling coupled with snRNAseq on human cortical samples at various fetal phases, we identify human mRNAs, including those encoding synaptic proteins, with finely controlled translation in distinct cell populations of developing frontal neocortices. Examination of murine and human neocortex reveals that the RNA binding protein and translational regulator, CELF4, is expressed in compartments enriched in initial synaptogenesis: the marginal zone and the subplate. We also find that Celf4/CELF4-target mRNAs are encoded by risk genes for adverse neurodevelopmental outcomes translating into synaptic proteins. Surprisingly, deleting Celf4 in the forebrain disrupts the balance of subplate synapses in a sex-specific fashion. This highlights the significance of RNA binding proteins and mRNA translation in evolutionarily advanced synaptic development, potentially contributing to sex differences.
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Affiliation(s)
- Iva Salamon
- Department of Neuroscience and Cell Biology, Rutgers University, Robert Wood Johnson Medical School, Piscataway, NJ, 08854, USA
- Rutgers University, School of Graduate Studies, New Brunswick, NJ, 08854, USA
| | - Yongkyu Park
- Department of Neuroscience and Cell Biology, Rutgers University, Robert Wood Johnson Medical School, Piscataway, NJ, 08854, USA
| | - Terezija Miškić
- Croatian Institute for Brain Research, Center of Research Excellence for Basic, Clinical and Translational Neuroscience, University of Zagreb, School of Medicine, Zagreb, 10000, Croatia
| | - Janja Kopić
- Croatian Institute for Brain Research, Center of Research Excellence for Basic, Clinical and Translational Neuroscience, University of Zagreb, School of Medicine, Zagreb, 10000, Croatia
| | - Paul Matteson
- Center for Advanced Biotechnology and Medicine, Department of Neuroscience and Cell Biology, Rutgers Robert Wood Johnson Medical School, Piscataway, NJ, USA
| | - Nicholas F Page
- Department of Neuroscience and Cell Biology, Rutgers University, Robert Wood Johnson Medical School, Piscataway, NJ, 08854, USA
| | - Alfonso Roque
- Department of Neuroscience and Cell Biology, Rutgers University, Robert Wood Johnson Medical School, Piscataway, NJ, 08854, USA
| | - Geoffrey W McAuliffe
- Department of Neuroscience and Cell Biology, Rutgers University, Robert Wood Johnson Medical School, Piscataway, NJ, 08854, USA
| | - John Favate
- Department of Genetics, Rutgers University, Piscataway, NJ, 08854, USA
| | - Marta Garcia-Forn
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- The Alper Center for Neural Development and Regeneration, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Premal Shah
- Department of Genetics, Rutgers University, Piscataway, NJ, 08854, USA
| | - Miloš Judaš
- Croatian Institute for Brain Research, Center of Research Excellence for Basic, Clinical and Translational Neuroscience, University of Zagreb, School of Medicine, Zagreb, 10000, Croatia
| | - James H Millonig
- Center for Advanced Biotechnology and Medicine, Department of Neuroscience and Cell Biology, Rutgers Robert Wood Johnson Medical School, Piscataway, NJ, USA
| | - Ivica Kostović
- Croatian Institute for Brain Research, Center of Research Excellence for Basic, Clinical and Translational Neuroscience, University of Zagreb, School of Medicine, Zagreb, 10000, Croatia
| | - Silvia De Rubeis
- Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- The Alper Center for Neural Development and Regeneration, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Ronald P Hart
- Department of Cell Biology and Neuroscience, Rutgers, The State University of New Jersey, Piscataway, NJ, 08854, USA
| | - Željka Krsnik
- Croatian Institute for Brain Research, Center of Research Excellence for Basic, Clinical and Translational Neuroscience, University of Zagreb, School of Medicine, Zagreb, 10000, Croatia.
| | - Mladen-Roko Rasin
- Department of Neuroscience and Cell Biology, Rutgers University, Robert Wood Johnson Medical School, Piscataway, NJ, 08854, USA.
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70
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Choi JS, Ayupe AC, Beckedorff F, Catanuto P, McCartan R, Levay K, Park KK. Single-nucleus RNA sequencing of developing superior colliculus identifies neuronal diversity and candidate mediators of circuit assembly. Cell Rep 2023; 42:113037. [PMID: 37624694 PMCID: PMC10592058 DOI: 10.1016/j.celrep.2023.113037] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Revised: 06/26/2023] [Accepted: 08/11/2023] [Indexed: 08/27/2023] Open
Abstract
The superior colliculus (SC) is a sensorimotor structure in the midbrain that integrates input from multiple sensory modalities to initiate motor commands. It undergoes well-characterized steps of circuit assembly during development, rendering the mouse SC a popular model to study establishment of neural connectivity. Here we perform single-nucleus RNA-sequencing analysis of the mouse SC isolated at various developmental time points. Our study provides a transcriptomic landscape of the cell types that comprise the SC across murine development with particular emphasis on neuronal heterogeneity. We report a repertoire of genes differentially expressed across the different postnatal ages, many of which are known to regulate axon guidance and synapse formation. Using these data, we find that Pax7 expression is restricted to a subset of GABAergic neurons. Our data provide a valuable resource for interrogating the mechanisms of circuit development and identifying markers for manipulating specific SC neuronal populations and circuits.
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Affiliation(s)
- James S Choi
- Department of Neurological Surgery, The Miami Project to Cure Paralysis, University of Miami Miller School of Medicine, 1095 NW 14th Ter., Miami, FL 33136, USA
| | - Ana C Ayupe
- Department of Neurological Surgery, The Miami Project to Cure Paralysis, University of Miami Miller School of Medicine, 1095 NW 14th Ter., Miami, FL 33136, USA
| | - Felipe Beckedorff
- Department of Human Genetics, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, 1501 NW 10th Avenue, Miami, FL 33136, USA
| | - Paola Catanuto
- Department of Neurological Surgery, The Miami Project to Cure Paralysis, University of Miami Miller School of Medicine, 1095 NW 14th Ter., Miami, FL 33136, USA
| | - Robyn McCartan
- Department of Neurological Surgery, The Miami Project to Cure Paralysis, University of Miami Miller School of Medicine, 1095 NW 14th Ter., Miami, FL 33136, USA
| | - Konstantin Levay
- Department of Neurological Surgery, The Miami Project to Cure Paralysis, University of Miami Miller School of Medicine, 1095 NW 14th Ter., Miami, FL 33136, USA
| | - Kevin K Park
- Department of Neurological Surgery, The Miami Project to Cure Paralysis, University of Miami Miller School of Medicine, 1095 NW 14th Ter., Miami, FL 33136, USA.
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71
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Zhang J, Ahmad M, Gao H. Application of single-cell multi-omics approaches in horticulture research. MOLECULAR HORTICULTURE 2023; 3:18. [PMID: 37789394 PMCID: PMC10521458 DOI: 10.1186/s43897-023-00067-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Accepted: 09/15/2023] [Indexed: 10/05/2023]
Abstract
Cell heterogeneity shapes the morphology and function of various tissues and organs in multicellular organisms. Elucidation of the differences among cells and the mechanism of intercellular regulation is essential for an in-depth understanding of the developmental process. In recent years, the rapid development of high-throughput single-cell transcriptome sequencing technologies has influenced the study of plant developmental biology. Additionally, the accuracy and sensitivity of tools used to study the epigenome and metabolome have significantly increased, thus enabling multi-omics analysis at single-cell resolution. Here, we summarize the currently available single-cell multi-omics approaches and their recent applications in plant research, review the single-cell based studies in fruit, vegetable, and ornamental crops, and discuss the potential of such approaches in future horticulture research.
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Affiliation(s)
- Jun Zhang
- Joint Center for Single Cell Biology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Mayra Ahmad
- Joint Center for Single Cell Biology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Hongbo Gao
- Joint Center for Single Cell Biology, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, 200240, China.
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72
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Feng W, Liu S, Deng Q, Fu S, Yang Y, Dai X, Wang S, Wang Y, Liu Y, Lin X, Pan X, Hao S, Yuan Y, Gu Y, Zhang X, Li H, Liu L, Liu C, Fei JF, Wei X. A scATAC-seq atlas of chromatin accessibility in axolotl brain regions. Sci Data 2023; 10:627. [PMID: 37709774 PMCID: PMC10502032 DOI: 10.1038/s41597-023-02533-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 09/01/2023] [Indexed: 09/16/2023] Open
Abstract
Axolotl (Ambystoma mexicanum) is an excellent model for investigating regeneration, the interaction between regenerative and developmental processes, comparative genomics, and evolution. The brain, which serves as the material basis of consciousness, learning, memory, and behavior, is the most complex and advanced organ in axolotl. The modulation of transcription factors is a crucial aspect in determining the function of diverse regions within the brain. There is, however, no comprehensive understanding of the gene regulatory network of axolotl brain regions. Here, we utilized single-cell ATAC sequencing to generate the chromatin accessibility landscapes of 81,199 cells from the olfactory bulb, telencephalon, diencephalon and mesencephalon, hypothalamus and pituitary, and the rhombencephalon. Based on these data, we identified key transcription factors specific to distinct cell types and compared cell type functions across brain regions. Our results provide a foundation for comprehensive analysis of gene regulatory programs, which are valuable for future studies of axolotl brain development, regeneration, and evolution, as well as on the mechanisms underlying cell-type diversity in vertebrate brains.
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Affiliation(s)
- Weimin Feng
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Shuai Liu
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
- BGI College & Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450000, China
| | - Qiuting Deng
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Sulei Fu
- Department of Pathology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510080, China
- Key Laboratory of Brain, Cognition and Education Sciences, Ministry of Education; Institute for Brain Research and Rehabilitation, South China Normal University, Guangzhou, 510631, China
| | - Yunzhi Yang
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
- BGI College & Henan Institute of Medical and Pharmaceutical Sciences, Zhengzhou University, Zhengzhou, 450000, China
| | - Xi Dai
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Shuai Wang
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Yijin Wang
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
- College of Life Sciences, Nankai University, Tianjin, 300071, China
| | - Yang Liu
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Xiumei Lin
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Xiangyu Pan
- Medical Research Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, 510080, China
- Guangdong Cardiovsacular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Shijie Hao
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Yue Yuan
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | - Ying Gu
- BGI-Shenzhen, Shenzhen, 518103, China
| | | | - Hanbo Li
- BGI-Shenzhen, Shenzhen, 518103, China
- BGI-Qingdao, Qingdao, 266555, China
- Lars Bolund Institute of Regenerative Medicine, Qingdao-Europe Advanced Institute for Life Sciences, BGI-Qingdao, Qingdao, 266555, China
| | - Longqi Liu
- BGI-Hangzhou, Hangzhou, 310012, China
- BGI-Shenzhen, Shenzhen, 518103, China
| | | | - Ji-Feng Fei
- Department of Pathology, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, Guangdong, 510080, China.
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, 510006, China.
- School of Basic Medical Sciences, Southern Medical University, Guangzhou, Guangdong, 510515, China.
| | - Xiaoyu Wei
- BGI-Hangzhou, Hangzhou, 310012, China.
- BGI-Shenzhen, Shenzhen, 518103, China.
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73
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Guo Y, Wang W, Ye K, He L, Ge Q, Huang Y, Zhao X. Single-Nucleus RNA-Seq: Open the Era of Great Navigation for FFPE Tissue. Int J Mol Sci 2023; 24:13744. [PMID: 37762049 PMCID: PMC10530744 DOI: 10.3390/ijms241813744] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 08/28/2023] [Accepted: 09/04/2023] [Indexed: 09/29/2023] Open
Abstract
Single-cell sequencing (scRNA-seq) has revolutionized our ability to explore heterogeneity and genetic variations at the single-cell level, opening up new avenues for understanding disease mechanisms and cell-cell interactions. Single-nucleus RNA-sequencing (snRNA-seq) is emerging as a promising solution to scRNA-seq due to its reduced ionized transcription bias and compatibility with richer samples. This approach will provide an exciting opportunity for in-depth exploration of billions of formalin-fixed paraffin-embedded (FFPE) tissues. Recent advancements in single-cell/nucleus gene expression workflows tailored for FFPE tissues have demonstrated their feasibility and provided crucial guidance for future studies utilizing FFPE specimens. In this review, we provide a broad overview of the nuclear preparation strategies, the latest technologies of snRNA-seq applicable to FFPE samples. Finally, the limitations and potential technical developments of snRNA-seq in FFPE samples are summarized. The development of snRNA-seq technologies for FFPE samples will lay a foundation for transcriptomic studies of valuable samples in clinical medicine and human sample banks.
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Affiliation(s)
| | | | | | | | | | | | - Xiangwei Zhao
- State Key Laboratory of Digital Medical Engineering, School of Biological Science & Medical Engineering, Southeast University, Nanjing 210096, China; (Y.G.); (W.W.); (K.Y.); (L.H.); (Q.G.); (Y.H.)
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74
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Wu SJ, Sevier E, Dwivedi D, Saldi GA, Hairston A, Yu S, Abbott L, Choi DH, Sherer M, Qiu Y, Shinde A, Lenahan M, Rizzo D, Xu Q, Barrera I, Kumar V, Marrero G, Prönneke A, Huang S, Kullander K, Stafford DA, Macosko E, Chen F, Rudy B, Fishell G. Cortical somatostatin interneuron subtypes form cell-type-specific circuits. Neuron 2023; 111:2675-2692.e9. [PMID: 37390821 DOI: 10.1016/j.neuron.2023.05.032] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 03/16/2023] [Accepted: 05/31/2023] [Indexed: 07/02/2023]
Abstract
The cardinal classes are a useful simplification of cortical interneuron diversity, but such broad subgroupings gloss over the molecular, morphological, and circuit specificity of interneuron subtypes, most notably among the somatostatin interneuron class. Although there is evidence that this diversity is functionally relevant, the circuit implications of this diversity are unknown. To address this knowledge gap, we designed a series of genetic strategies to target the breadth of somatostatin interneuron subtypes and found that each subtype possesses a unique laminar organization and stereotyped axonal projection pattern. Using these strategies, we examined the afferent and efferent connectivity of three subtypes (two Martinotti and one non-Martinotti) and demonstrated that they possess selective connectivity with intratelecephalic or pyramidal tract neurons. Even when two subtypes targeted the same pyramidal cell type, their synaptic targeting proved selective for particular dendritic compartments. We thus provide evidence that subtypes of somatostatin interneurons form cell-type-specific cortical circuits.
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Affiliation(s)
- Sherry Jingjing Wu
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Elaine Sevier
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Deepanjali Dwivedi
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Giuseppe-Antonio Saldi
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ariel Hairston
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Sabrina Yu
- Department of Health Sciences, Bouvé College of Health Sciences, Northeastern University, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Lydia Abbott
- Department of Biology, College of Science, Northeastern University, Boston, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Da Hae Choi
- Department of Behavioral Neuroscience, College of Science, Northeastern University, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Mia Sherer
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Yanjie Qiu
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Ashwini Shinde
- Department of Behavioral Neuroscience, College of Science, Northeastern University, Boston, MA 02115, USA; Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA
| | - Mackenzie Lenahan
- Department of Biology, College of Science, Northeastern University, Boston, MA, USA; Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA
| | - Daniella Rizzo
- Department of Biology, Brandeis University, Waltham, MA, USA; Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA
| | - Qing Xu
- Center for Genomics & Systems Biology, New York University Abu Dhabi, Abu Dhabi, UAE
| | - Irving Barrera
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Vipin Kumar
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Giovanni Marrero
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Alvar Prönneke
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
| | - Shuhan Huang
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Klas Kullander
- Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - David A Stafford
- Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94708, USA
| | - Evan Macosko
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Fei Chen
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Bernardo Rudy
- Neuroscience Institute, New York University School of Medicine, New York, NY, USA
| | - Gord Fishell
- Harvard Medical School, Blavatnik Institute, Department of Neurobiology, Boston, MA 02115, USA; Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
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75
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Byeon S, du Toit‐Thompson T, Gillson J, Gill AJ, Samra JS, Mittal A, Sahni S. Heterogeneous tumor microenvironment in pancreatic ductal adenocarcinoma: An emerging role of single-cell analysis. Cancer Med 2023; 12:18020-18031. [PMID: 37537839 PMCID: PMC10523961 DOI: 10.1002/cam4.6407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 06/21/2023] [Accepted: 07/25/2023] [Indexed: 08/05/2023] Open
Abstract
BACKGROUND Pancreatic ductal adenocarcinoma (PDAC) is one of the deadliest malignancies in the world, for which the mortality is almost as high as the disease incidence and is predicted to be the second-highest cause of cancer-related deaths by 2030. These cancerous tumors consist of diversified gene expressions within the different cellular subpopulations that include neoplastic ductal cells, cancer-associated fibroblasts, and immune cells, all of which collectively facilitate cellular heterogeneity in the PDAC tumor microenvironment (TME). Active intratumoral interaction within the cell populations in TME induces the proliferation of cancerous cells, accounting for tumorigenesis and rapid metastasis. METHODS This review will focus on novel findings uncovering PDAC heterogeneity in different cellular subpopulations using single-cell RNA-sequencing (scRNA-seq) and other single-cell analysis technologies. It will further explore the emerging role of single-cell technologies in assessing the role of different subpopulations of neoplastic ductal cells, cancer-associated fibroblasts, and immune cells in PDAC progression. RESULTS AND CONCLUSION The application of scRNA-seq in PDAC has started to unveil associations between disease progression and heterogeneity in pancreatic TME and could influence future PDAC treatment. Recent advances in scRNA-seq have uncovered comprehensive analyses of heterogeneous ecosystems present within the TME. These emerging findings underpins further need for a more in-depth understanding of intratumoral heterogeneity in the PDAC microenvironment.
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Affiliation(s)
- Sooin Byeon
- Northern Clinical School, Faculty of Medicine and HealthUniversity of SydneySydneyNew South WalesAustralia
- Kolling Institute of Medical Research, University of SydneySydneyNew South WalesAustralia
| | - Taymin du Toit‐Thompson
- Northern Clinical School, Faculty of Medicine and HealthUniversity of SydneySydneyNew South WalesAustralia
- Kolling Institute of Medical Research, University of SydneySydneyNew South WalesAustralia
| | - Josef Gillson
- Northern Clinical School, Faculty of Medicine and HealthUniversity of SydneySydneyNew South WalesAustralia
- Kolling Institute of Medical Research, University of SydneySydneyNew South WalesAustralia
| | - Anthony J. Gill
- Northern Clinical School, Faculty of Medicine and HealthUniversity of SydneySydneyNew South WalesAustralia
- Kolling Institute of Medical Research, University of SydneySydneyNew South WalesAustralia
- Australian Pancreatic CentreSydneyNew South WalesAustralia
- Cancer Diagnosis and Pathology GroupKolling Institute of Medical ResearchSt LeonardsNew South WalesAustralia
- NSW Health Pathology, Department of Anatomical PathologyRoyal North Shore HospitalSt LeonardsNew South WalesAustralia
| | - Jaswinder S. Samra
- Northern Clinical School, Faculty of Medicine and HealthUniversity of SydneySydneyNew South WalesAustralia
- Australian Pancreatic CentreSydneyNew South WalesAustralia
- Upper GI Surgical UnitRoyal North Shore Hospital and North Shore Private HospitalSt LeonardsNew South WalesAustralia
| | - Anubhav Mittal
- Northern Clinical School, Faculty of Medicine and HealthUniversity of SydneySydneyNew South WalesAustralia
- Australian Pancreatic CentreSydneyNew South WalesAustralia
- Upper GI Surgical UnitRoyal North Shore Hospital and North Shore Private HospitalSt LeonardsNew South WalesAustralia
- The University of Notre Dame AustraliaSydneyNew South WalesAustralia
| | - Sumit Sahni
- Northern Clinical School, Faculty of Medicine and HealthUniversity of SydneySydneyNew South WalesAustralia
- Kolling Institute of Medical Research, University of SydneySydneyNew South WalesAustralia
- Australian Pancreatic CentreSydneyNew South WalesAustralia
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76
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Qu J, Sun J, Zhao C, Liu X, Zhang X, Jiang S, Wei C, Yu H, Zeng X, Fan L, Ding J. Simultaneous profiling of chromatin architecture and transcription in single cells. Nat Struct Mol Biol 2023; 30:1393-1402. [PMID: 37580628 DOI: 10.1038/s41594-023-01066-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Accepted: 07/12/2023] [Indexed: 08/16/2023]
Abstract
The three-dimensional structure of chromatin plays a crucial role in development and disease, both of which are associated with transcriptional changes. However, given the heterogeneity in single-cell chromatin architecture and transcription, the regulatory relationship between the three-dimensional chromatin structure and gene expression is difficult to explain based on bulk cell populations. Here we develop a single-cell, multimodal, omics method allowing the simultaneous detection of chromatin architecture and messenger RNA expression by sequencing (single-cell transcriptome sequencing (scCARE-seq)). Applying scCARE-seq to examine chromatin architecture and transcription from 2i to serum single mouse embryonic stem cells, we observe improved separation of cell clusters compared with single-cell chromatin conformation capture. In addition, after defining the cell-cycle phase of each cell through chromatin architecture extracted by scCARE-seq, we find that periodic changes in chromatin architecture occur in parallel with transcription during the cell cycle. These findings highlight the potential of scCARE-seq to facilitate comprehensive analyses that may boost our understanding of chromatin architecture and transcription in the same single cell.
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Affiliation(s)
- Jiale Qu
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Jun Sun
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Cai Zhao
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Xinyi Liu
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Xinyao Zhang
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Shaoshuai Jiang
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Chao Wei
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Haopeng Yu
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaoxi Zeng
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
| | - Lili Fan
- Guangzhou Key Laboratory of Formula-Pattern of Traditional Chinese Medicine, School of Traditional Chinese Medicine, Jinan University, Guangzhou, China.
| | - Junjun Ding
- RNA Biomedical Institute, Sun Yat-sen Memorial Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
- Advanced Medical Technology Center, The First Affiliated Hospital, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
- Center for Stem Cell Biology and Tissue Engineering, Key Laboratory for Stem Cells and Tissue Engineering, Ministry of Education, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China.
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
- Department of Histology and Embryology, School of Basic Medical Sciences, Guangzhou Medical University, Guangzhou, China.
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77
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Daniels RR, Taylor RS, Robledo D, Macqueen DJ. Single cell genomics as a transformative approach for aquaculture research and innovation. REVIEWS IN AQUACULTURE 2023; 15:1618-1637. [PMID: 38505116 PMCID: PMC10946576 DOI: 10.1111/raq.12806] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 02/16/2023] [Accepted: 02/16/2023] [Indexed: 03/21/2024]
Abstract
Single cell genomics encompasses a suite of rapidly maturing technologies that measure the molecular profiles of individual cells within target samples. These approaches provide a large up-step in biological information compared to long-established 'bulk' methods that profile the average molecular profiles of all cells in a sample, and have led to transformative advances in understanding of cellular biology, particularly in humans and model organisms. The application of single cell genomics is fast expanding to non-model taxa, including aquaculture species, where numerous research applications are underway with many more envisaged. In this review, we highlight the potential transformative applications of single cell genomics in aquaculture research, considering barriers and potential solutions to the broad uptake of these technologies. Focusing on single cell transcriptomics, we outline considerations for experimental design, including the essential requirement to obtain high quality cells/nuclei for sequencing in ectothermic aquatic species. We further outline data analysis and bioinformatics considerations, tailored to studies with the under-characterized genomes of aquaculture species, where our knowledge of cellular heterogeneity and cell marker genes is immature. Overall, this review offers a useful source of knowledge for researchers aiming to apply single cell genomics to address biological challenges faced by the global aquaculture sector though an improved understanding of cell biology.
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Affiliation(s)
- Rose Ruiz Daniels
- The Roslin Institute and Royal (Dick) School of Veterinary StudiesThe University of EdinburghMidlothianUK
| | - Richard S. Taylor
- The Roslin Institute and Royal (Dick) School of Veterinary StudiesThe University of EdinburghMidlothianUK
| | - Diego Robledo
- The Roslin Institute and Royal (Dick) School of Veterinary StudiesThe University of EdinburghMidlothianUK
| | - Daniel J. Macqueen
- The Roslin Institute and Royal (Dick) School of Veterinary StudiesThe University of EdinburghMidlothianUK
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78
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Forrest SL, Lee S, Nassir N, Martinez-Valbuena I, Sackmann V, Li J, Ahmed A, Tartaglia MC, Ittner LM, Lang AE, Uddin M, Kovacs GG. Cell-specific MAPT gene expression is preserved in neuronal and glial tau cytopathologies in progressive supranuclear palsy. Acta Neuropathol 2023; 146:395-414. [PMID: 37354322 PMCID: PMC10412651 DOI: 10.1007/s00401-023-02604-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Revised: 06/11/2023] [Accepted: 06/16/2023] [Indexed: 06/26/2023]
Abstract
Microtubule-associated protein tau (MAPT) aggregates in neurons, astrocytes and oligodendrocytes in a number of neurodegenerative diseases, including progressive supranuclear palsy (PSP). Tau is a target of therapy and the strategy includes either the elimination of pathological tau aggregates or reducing MAPT expression, and thus the amount of tau protein made to prevent its aggregation. Disease-associated tau affects brain regions in a sequential manner that includes cell-to-cell spreading. Involvement of glial cells that show tau aggregates is interpreted as glial cells taking up misfolded tau assuming that glial cells do not express enough MAPT. Although studies have evaluated MAPT expression in human brain tissue homogenates, it is not clear whether MAPT expression is compromised in cells accumulating pathological tau. To address these perplexing aspects of disease pathogenesis, this study used RNAscope combined with immunofluorescence (AT8), and single-nuclear(sn) RNAseq to systematically map and quantify MAPT expression dynamics across different cell types and brain regions in controls (n = 3) and evaluated whether tau cytopathology affects MAPT expression in PSP (n = 3). MAPT transcripts were detected in neurons, astrocytes and oligodendrocytes, and varied between brain regions and within each cell type, and were preserved in all cell types with tau aggregates in PSP. These results propose a complex scenario in all cell types, where, in addition to the ingested misfolded tau, the preserved cellular MAPT expression provides a pool for local protein production that can (1) be phosphorylated and aggregated, or (2) feed the seeding of ingested misfolded tau by providing physiological tau, both accentuating the pathological process. Since tau cytopathology does not compromise MAPT gene expression in PSP, a complete loss of tau protein expression as an early pathogenic component is less likely. These observations provide rationale for a dual approach to therapy by decreasing cellular MAPT expression and targeting removal of misfolded tau.
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Affiliation(s)
- Shelley L Forrest
- Tanz Centre for Research in Neurodegenerative Disease (CRND), University of Toronto, Krembil Discovery Tower, 60 Leonard Ave, Toronto, ON, M5T 0S8, Canada
- Dementia Research Centre, Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia
- Laboratory Medicine Program and Krembil Brain Institute, University Health Network, Toronto, ON, Canada
| | - Seojin Lee
- Tanz Centre for Research in Neurodegenerative Disease (CRND), University of Toronto, Krembil Discovery Tower, 60 Leonard Ave, Toronto, ON, M5T 0S8, Canada
| | - Nasna Nassir
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE
| | - Ivan Martinez-Valbuena
- Tanz Centre for Research in Neurodegenerative Disease (CRND), University of Toronto, Krembil Discovery Tower, 60 Leonard Ave, Toronto, ON, M5T 0S8, Canada
| | - Valerie Sackmann
- Tanz Centre for Research in Neurodegenerative Disease (CRND), University of Toronto, Krembil Discovery Tower, 60 Leonard Ave, Toronto, ON, M5T 0S8, Canada
| | - Jun Li
- Tanz Centre for Research in Neurodegenerative Disease (CRND), University of Toronto, Krembil Discovery Tower, 60 Leonard Ave, Toronto, ON, M5T 0S8, Canada
| | - Awab Ahmed
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE
| | - Maria Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Disease (CRND), University of Toronto, Krembil Discovery Tower, 60 Leonard Ave, Toronto, ON, M5T 0S8, Canada
- University Health Network Memory Clinic, Krembil Brain Institute, Toronto, ON, Canada
| | - Lars M Ittner
- Dementia Research Centre, Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia
| | - Anthony E Lang
- Edmond J. Safra Program in Parkinson's Disease, Rossy PSP Centre and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, Toronto, ON, Canada
| | - Mohammed Uddin
- College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE
- Cellular Intelligence (Ci) Lab, GenomeArc Inc., Toronto, ON, Canada
| | - Gabor G Kovacs
- Tanz Centre for Research in Neurodegenerative Disease (CRND), University of Toronto, Krembil Discovery Tower, 60 Leonard Ave, Toronto, ON, M5T 0S8, Canada.
- Dementia Research Centre, Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, Australia.
- Laboratory Medicine Program and Krembil Brain Institute, University Health Network, Toronto, ON, Canada.
- Edmond J. Safra Program in Parkinson's Disease, Rossy PSP Centre and the Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, Toronto, ON, Canada.
- Department of Laboratory Medicine and Pathobiology and Department of Medicine, University of Toronto, Toronto, ON, Canada.
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79
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Kang JB, Raveane A, Nathan A, Soranzo N, Raychaudhuri S. Methods and Insights from Single-Cell Expression Quantitative Trait Loci. Annu Rev Genomics Hum Genet 2023; 24:277-303. [PMID: 37196361 PMCID: PMC10784788 DOI: 10.1146/annurev-genom-101422-100437] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/19/2023]
Abstract
Recent advancements in single-cell technologies have enabled expression quantitative trait locus (eQTL) analysis across many individuals at single-cell resolution. Compared with bulk RNA sequencing, which averages gene expression across cell types and cell states, single-cell assays capture the transcriptional states of individual cells, including fine-grained, transient, and difficult-to-isolate populations at unprecedented scale and resolution. Single-cell eQTL (sc-eQTL) mapping can identify context-dependent eQTLs that vary with cell states, including some that colocalize with disease variants identified in genome-wide association studies. By uncovering the precise contexts in which these eQTLs act, single-cell approaches can unveil previously hidden regulatory effects and pinpoint important cell states underlying molecular mechanisms of disease. Here, we present an overview of recently deployed experimental designs in sc-eQTL studies. In the process, we consider the influence of study design choices such as cohort, cell states, and ex vivo perturbations. We then discuss current methodologies, modeling approaches, and technical challenges as well as future opportunities and applications.
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Affiliation(s)
- Joyce B Kang
- Center for Data Sciences and Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA; ,
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA;
| | | | - Aparna Nathan
- Center for Data Sciences and Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA; ,
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA;
| | - Nicole Soranzo
- Human Technopole, Milan, Italy; ,
- Department of Human Genetics, Wellcome Sanger Institute, Hinxton, United Kingdom
- British Heart Foundation Centre of Research Excellence and Department of Haematology, University of Cambridge, Cambridge, United Kingdom
| | - Soumya Raychaudhuri
- Center for Data Sciences and Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA; ,
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA;
- Centre for Genetics and Genomics Versus Arthritis, University of Manchester, Manchester, United Kingdom
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80
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Chen A, Sun Y, Lei Y, Li C, Liao S, Meng J, Bai Y, Liu Z, Liang Z, Zhu Z, Yuan N, Yang H, Wu Z, Lin F, Wang K, Li M, Zhang S, Yang M, Fei T, Zhuang Z, Huang Y, Zhang Y, Xu Y, Cui L, Zhang R, Han L, Sun X, Chen B, Li W, Huangfu B, Ma K, Ma J, Li Z, Lin Y, Wang H, Zhong Y, Zhang H, Yu Q, Wang Y, Liu X, Peng J, Liu C, Chen W, Pan W, An Y, Xia S, Lu Y, Wang M, Song X, Liu S, Wang Z, Gong C, Huang X, Yuan Y, Zhao Y, Chai Q, Tan X, Liu J, Zheng M, Li S, Huang Y, Hong Y, Huang Z, Li M, Jin M, Li Y, Zhang H, Sun S, Gao L, Bai Y, Cheng M, Hu G, Liu S, Wang B, Xiang B, Li S, Li H, Chen M, Wang S, Li M, Liu W, Liu X, Zhao Q, Lisby M, Wang J, Fang J, Lin Y, Xie Q, Liu Z, He J, Xu H, Huang W, Mulder J, Yang H, Sun Y, Uhlen M, Poo M, Wang J, Yao J, Wei W, Li Y, Shen Z, Liu L, Liu Z, Xu X, Li C. Single-cell spatial transcriptome reveals cell-type organization in the macaque cortex. Cell 2023; 186:3726-3743.e24. [PMID: 37442136 DOI: 10.1016/j.cell.2023.06.009] [Citation(s) in RCA: 42] [Impact Index Per Article: 42.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 02/24/2023] [Accepted: 06/14/2023] [Indexed: 07/15/2023]
Abstract
Elucidating the cellular organization of the cerebral cortex is critical for understanding brain structure and function. Using large-scale single-nucleus RNA sequencing and spatial transcriptomic analysis of 143 macaque cortical regions, we obtained a comprehensive atlas of 264 transcriptome-defined cortical cell types and mapped their spatial distribution across the entire cortex. We characterized the cortical layer and region preferences of glutamatergic, GABAergic, and non-neuronal cell types, as well as regional differences in cell-type composition and neighborhood complexity. Notably, we discovered a relationship between the regional distribution of various cell types and the region's hierarchical level in the visual and somatosensory systems. Cross-species comparison of transcriptomic data from human, macaque, and mouse cortices further revealed primate-specific cell types that are enriched in layer 4, with their marker genes expressed in a region-dependent manner. Our data provide a cellular and molecular basis for understanding the evolution, development, aging, and pathogenesis of the primate brain.
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Affiliation(s)
- Ao Chen
- BGI-Shenzhen, Shenzhen 518103, China; Department of Biology, University of Copenhagen, Copenhagen 2200, Denmark; BGI Research-Southwest, BGI, Chongqing 401329, China; JFL-BGI STOmics Center, Jinfeng Laboratory, Chongqing 401329, China
| | - Yidi Sun
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
| | - Ying Lei
- BGI-Shenzhen, Shenzhen 518103, China; BGI-Hangzhou, Hangzhou 310012, China
| | - Chao Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Sha Liao
- BGI-Shenzhen, Shenzhen 518103, China; BGI Research-Southwest, BGI, Chongqing 401329, China; JFL-BGI STOmics Center, Jinfeng Laboratory, Chongqing 401329, China
| | - Juan Meng
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yiqin Bai
- Lingang Laboratory, Shanghai 200031, China
| | - Zhen Liu
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zhifeng Liang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | - Nini Yuan
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Hao Yang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zihan Wu
- Tencent AI Lab, Shenzhen 518057, China
| | - Feng Lin
- BGI-Shenzhen, Shenzhen 518103, China
| | - Kexin Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Mei Li
- BGI-Shenzhen, Shenzhen 518103, China
| | - Shuzhen Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | - Tianyi Fei
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zhenkun Zhuang
- BGI-Shenzhen, Shenzhen 518103, China; School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | - Yiming Huang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yong Zhang
- BGI-Shenzhen, Shenzhen 518103, China; School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | - Yuanfang Xu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Luman Cui
- BGI-Shenzhen, Shenzhen 518103, China
| | - Ruiyi Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Lei Han
- BGI-Shenzhen, Shenzhen 518103, China
| | - Xing Sun
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | | | - Baoqian Huangfu
- BGI-Shenzhen, Shenzhen 518103, China; School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | | | - Jianyun Ma
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zhao Li
- BGI-Shenzhen, Shenzhen 518103, China
| | - Yikun Lin
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - He Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yanqing Zhong
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Huifang Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Qian Yu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yaqian Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xing Liu
- BGI-Shenzhen, Shenzhen 518103, China
| | - Jian Peng
- BGI-Shenzhen, Shenzhen 518103, China
| | | | - Wei Chen
- BGI-Shenzhen, Shenzhen 518103, China
| | | | - Yingjie An
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shihui Xia
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yanbing Lu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Mingli Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xinxiang Song
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shuai Liu
- BGI-Shenzhen, Shenzhen 518103, China
| | | | - Chun Gong
- BGI-Shenzhen, Shenzhen 518103, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Xin Huang
- BGI-Shenzhen, Shenzhen 518103, China
| | - Yue Yuan
- BGI-Shenzhen, Shenzhen 518103, China
| | - Yun Zhao
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Qinwen Chai
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xing Tan
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Jianfeng Liu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Mingyuan Zheng
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shengkang Li
- BGI-Shenzhen, Shenzhen 518103, China; Guangdong Bigdata Engineering Technology Research Center for Life Sciences, Shenzhen 518083, China
| | | | - Yan Hong
- BGI-Shenzhen, Shenzhen 518103, China
| | | | - Min Li
- BGI-Shenzhen, Shenzhen 518103, China
| | - Mengmeng Jin
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yan Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Hui Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Suhong Sun
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Li Gao
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yinqi Bai
- BGI-Shenzhen, Shenzhen 518103, China
| | | | - Guohai Hu
- China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Shiping Liu
- BGI-Shenzhen, Shenzhen 518103, China; BGI-Hangzhou, Hangzhou 310012, China
| | - Bo Wang
- China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | - Bin Xiang
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shuting Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Huanhuan Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Mengni Chen
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shiwen Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Minglong Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | - Xin Liu
- BGI-Shenzhen, Shenzhen 518103, China
| | - Qian Zhao
- BGI-Shenzhen, Shenzhen 518103, China
| | - Michael Lisby
- Department of Biology, University of Copenhagen, Copenhagen 2200, Denmark
| | - Jing Wang
- BGI-Shenzhen, Shenzhen 518103, China
| | - Jiao Fang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yun Lin
- BGI-Shenzhen, Shenzhen 518103, China
| | - Qing Xie
- BGI-Shenzhen, Shenzhen 518103, China
| | - Zhen Liu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China
| | - Jie He
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Huatai Xu
- Lingang Laboratory, Shanghai 200031, China
| | - Wei Huang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Jan Mulder
- Department of Protein Science, Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm 17121, Sweden; Department of Neuroscience, Karolinska Institute, Stockholm 17177, Sweden
| | | | - Yangang Sun
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Mathias Uhlen
- Department of Protein Science, Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm 17121, Sweden; Department of Neuroscience, Karolinska Institute, Stockholm 17177, Sweden
| | - Muming Poo
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China
| | - Jian Wang
- BGI-Shenzhen, Shenzhen 518103, China; China National GeneBank, BGI-Shenzhen, Shenzhen 518120, China
| | | | - Wu Wei
- Lingang Laboratory, Shanghai 200031, China; CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
| | - Yuxiang Li
- BGI-Shenzhen, Shenzhen 518103, China; BGI Research-Wuhan, BGI, Wuhan 430074, China.
| | - Zhiming Shen
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China.
| | - Longqi Liu
- BGI-Shenzhen, Shenzhen 518103, China; BGI-Hangzhou, Hangzhou 310012, China.
| | - Zhiyong Liu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China.
| | - Xun Xu
- BGI-Shenzhen, Shenzhen 518103, China; Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen 518120, China.
| | - Chengyu Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China; School of Future Technology, University of Chinese Academy of Sciences, Beijing 100049, China.
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81
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Lassé M, El Saghir J, Berthier CC, Eddy S, Fischer M, Laufer SD, Kylies D, Hutzfeldt A, Bonin LL, Dumoulin B, Menon R, Vega-Warner V, Eichinger F, Alakwaa F, Fermin D, Billing AM, Minakawa A, McCown PJ, Rose MP, Godfrey B, Meister E, Wiech T, Noriega M, Chrysopoulou M, Brandts P, Ju W, Reinhard L, Hoxha E, Grahammer F, Lindenmeyer MT, Huber TB, Schlüter H, Thiel S, Mariani LH, Puelles VG, Braun F, Kretzler M, Demir F, Harder JL, Rinschen MM. An integrated organoid omics map extends modeling potential of kidney disease. Nat Commun 2023; 14:4903. [PMID: 37580326 PMCID: PMC10425428 DOI: 10.1038/s41467-023-39740-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Accepted: 06/27/2023] [Indexed: 08/16/2023] Open
Abstract
Kidney organoids are a promising model to study kidney disease, but their use is constrained by limited knowledge of their functional protein expression profile. Here, we define the organoid proteome and transcriptome trajectories over culture duration and upon exposure to TNFα, a cytokine stressor. Older organoids increase deposition of extracellular matrix but decrease expression of glomerular proteins. Single cell transcriptome integration reveals that most proteome changes localize to podocytes, tubular and stromal cells. TNFα treatment of organoids results in 322 differentially expressed proteins, including cytokines and complement components. Transcript expression of these 322 proteins is significantly higher in individuals with poorer clinical outcomes in proteinuric kidney disease. Key TNFα-associated protein (C3 and VCAM1) expression is increased in both human tubular and organoid kidney cell populations, highlighting the potential for organoids to advance biomarker development. By integrating kidney organoid omic layers, incorporating a disease-relevant cytokine stressor and comparing with human data, we provide crucial evidence for the functional relevance of the kidney organoid model to human kidney disease.
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Affiliation(s)
- Moritz Lassé
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jamal El Saghir
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
| | - Celine C Berthier
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
| | - Sean Eddy
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
| | - Matthew Fischer
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
| | - Sandra D Laufer
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Dominik Kylies
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Arvid Hutzfeldt
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | | | - Bernhard Dumoulin
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Rajasree Menon
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Virginia Vega-Warner
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
| | - Felix Eichinger
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
| | - Fadhl Alakwaa
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
| | - Damian Fermin
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
| | - Anja M Billing
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Akihiro Minakawa
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
| | - Phillip J McCown
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
| | - Michael P Rose
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
| | - Bradley Godfrey
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
| | - Elisabeth Meister
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Thorsten Wiech
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Pathology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Mercedes Noriega
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Pathology, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | | | - Paul Brandts
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Wenjun Ju
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
| | - Linda Reinhard
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Elion Hoxha
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Florian Grahammer
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Maja T Lindenmeyer
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Tobias B Huber
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Hartmut Schlüter
- Section Mass Spectrometric Proteomics, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Steffen Thiel
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Laura H Mariani
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
| | - Victor G Puelles
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Department of Pathology, Aarhus University Hospital, Aarhus, Denmark
| | - Fabian Braun
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Matthias Kretzler
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Fatih Demir
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Jennifer L Harder
- Department of Internal Medicine, Division of Nephrology, University of Michigan Medical School, Ann Arbor, USA.
| | - Markus M Rinschen
- III. Department of Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany.
- Hamburg Center for Kidney Health (HCKH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
- Department of Biomedicine, Aarhus University, Aarhus, Denmark.
- Aarhus Institute of Advanced Studies (AIAS), Aarhus, Denmark.
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82
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Chen C, Ge Y, Lu L. Opportunities and challenges in the application of single-cell and spatial transcriptomics in plants. FRONTIERS IN PLANT SCIENCE 2023; 14:1185377. [PMID: 37636094 PMCID: PMC10453814 DOI: 10.3389/fpls.2023.1185377] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 07/26/2023] [Indexed: 08/29/2023]
Abstract
Single-cell and spatial transcriptomics have diverted researchers' attention from the multicellular level to the single-cell level and spatial information. Single-cell transcriptomes provide insights into the transcriptome at the single-cell level, whereas spatial transcriptomes help preserve spatial information. Although these two omics technologies are helpful and mature, further research is needed to ensure their widespread applicability in plant studies. Reviewing recent research on plant single-cell or spatial transcriptomics, we compared the different experimental methods used in various plants. The limitations and challenges are clear for both single-cell and spatial transcriptomic analyses, such as the lack of applicability, spatial information, or high resolution. Subsequently, we put forth further applications, such as cross-species analysis of roots at the single-cell level and the idea that single-cell transcriptome analysis needs to be combined with other omics analyses to achieve superiority over individual omics analyses. Overall, the results of this review suggest that combining single-cell transcriptomics, spatial transcriptomics, and spatial element distribution can provide a promising research direction, particularly for plant research.
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Affiliation(s)
- Ce Chen
- Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China
| | - Yining Ge
- Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China
| | - Lingli Lu
- Ministry of Education Key Laboratory of Environment Remediation and Ecological Health, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China
- Key Laboratory of Agricultural Resource and Environment of Zhejiang Province, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China
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83
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Dai DL, Li M, Lee EB. Human Alzheimer's disease reactive astrocytes exhibit a loss of homeostastic gene expression. Acta Neuropathol Commun 2023; 11:127. [PMID: 37533101 PMCID: PMC10398957 DOI: 10.1186/s40478-023-01624-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 07/14/2023] [Indexed: 08/04/2023] Open
Abstract
Astrocytes are one of the brain's major cell types and are responsible for maintaining neuronal homeostasis via regulating the extracellular environment, providing metabolic support, and modulating synaptic activity. In neurodegenerative diseases, such as Alzheimer's disease, astrocytes can take on a hypertrophic appearance. These reactive astrocytes are canonically associated with increases in cytoskeletal proteins, such as glial fibrillary acidic protein and vimentin. However, the molecular alterations that characterize astrocytes in human disease tissues have not been extensively studied with single cell resolution. Using single nucleus RNA sequencing data from normal, pathologic aging, and Alzheimer's disease brains, we identified the transcriptomic changes associated with reactive astrocytes. Deep learning-based clustering algorithms denoised expression data for 17,012 genes and clustered 15,529 astrocyte nuclei, identifying protoplasmic, gray matter and fibrous, white matter astrocyte clusters. RNA trajectory analyses revealed a spectrum of reactivity within protoplasmic astrocytes characterized by a modest increase of reactive genes and a marked decrease in homeostatic genes. Amyloid but not tau pathology correlated with astrocyte reactivity. To identify reactivity-associated genes, linear regressions of gene expression versus reactivity were used to identify the top 52 upregulated and 144 downregulated genes. Gene Ontology analysis revealed that upregulated genes were associated with cellular growth, responses to metal ions, inflammation, and proteostasis. Downregulated genes were involved in cellular interactions, neuronal development, ERBB signaling, and synapse regulation. Transcription factors were significantly enriched among the downregulated genes. Using co-immunofluorescence staining of Alzheimer's disease brain tissues, we confirmed pathologic downregulation of ERBB4 and transcription factor NFIA in reactive astrocytes. Our findings reveal that protoplasmic, gray matter astrocytes in Alzheimer's disease exist within a spectrum of reactivity that is marked by a strong loss of normal function.
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Affiliation(s)
- David L Dai
- Translational Neuropathology Research Laboratory, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 19104, USA
| | - Mingyao Li
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 19104, USA
| | - Edward B Lee
- Translational Neuropathology Research Laboratory, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 19104, USA.
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84
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Gallegos DA, Minto M, Liu F, Hazlett MF, Aryana Yousefzadeh S, Bartelt LC, West AE. Cell-type specific transcriptional adaptations of nucleus accumbens interneurons to amphetamine. Mol Psychiatry 2023; 28:3414-3428. [PMID: 35173267 PMCID: PMC9378812 DOI: 10.1038/s41380-022-01466-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/26/2021] [Revised: 01/13/2022] [Accepted: 01/26/2022] [Indexed: 11/09/2022]
Abstract
Parvalbumin-expressing (PV+) interneurons of the nucleus accumbens (NAc) play an essential role in the addictive-like behaviors induced by psychostimulant exposure. To identify molecular mechanisms of PV+ neuron plasticity, we isolated interneuron nuclei from the NAc of male and female mice following acute or repeated exposure to amphetamine (AMPH) and sequenced for cell type-specific RNA expression and chromatin accessibility. AMPH regulated the transcription of hundreds of genes in PV+ interneurons, and this program was largely distinct from that regulated in other NAc GABAergic neurons. Chromatin accessibility at enhancers predicted cell-type specific gene regulation, identifying transcriptional mechanisms of differential AMPH responses. Finally, we assessed expression of PV-enriched, AMPH-regulated genes in an Mecp2 mutant mouse strain that shows heightened behavioral sensitivity to psychostimulants to explore the functional importance of this transcriptional program. Together these data provide novel insight into the cell-type specific programs of transcriptional plasticity in NAc neurons that underlie addictive-like behaviors.
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Affiliation(s)
- David A Gallegos
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
| | - Melyssa Minto
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
| | - Fang Liu
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
| | - Mariah F Hazlett
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
| | | | - Luke C Bartelt
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA
| | - Anne E West
- Department of Neurobiology, Duke University Medical Center, Durham, NC, USA.
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85
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He YT, Zou JX, He Y, Wang CY, Pan BX, Pan HQ. Isolation of Projection-Specific and Behavior-Relevant Amygdala Circuit for RNA Sequencing. Curr Protoc 2023; 3:e858. [PMID: 37561726 DOI: 10.1002/cpz1.858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/12/2023]
Abstract
One of the most sought-after topics in neuroscience is to understand how the environment regulates the activity and function of neural circuitry and subsequently influences relevant behaviors. In response to alterations in the environment, the neural circuits undergo adaptive changes ranging from gene expression changes to altered cellular function. Performing sequencing of the transcriptome involved in these behavior-related circuits will provide clues to accurately dissect the detailed mechanisms of related behavior. Here, we describe methods for marking and collecting the ventral hippocampus-projecting basolateral amygdala neurons, which have been repeatedly implicated in regulation of anxiety-like behavior, and subsequently constructing a library ready for sequencing. Specifically, the reported approaches include adeno-associated virus injection, acute brain slice isolation, cell suspension preparation, cell extraction, and cDNA library construction. By utilizing the techniques described here, researchers can comprehensively investigate the transcriptional levels of neural clusters embedded in particular circuits and discover potential pathogenic and therapeutic targets for behavior-relevant disorders. © 2023 Wiley Periodicals LLC. Basic Protocol 1: Tagging of behavior-related neural circuits Basic Protocol 2: Isolation and capture of fluorescent-positive cells Basic Protocol 3: Foundation of sequencing library.
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Affiliation(s)
- Yu-Ting He
- Queen Mary School, Nanchang University, Nanchang, China
- Laboratory of Fear and Anxiety Disorders, Institutes of Life Science, Nanchang University, Nanchang, China
| | - Jia-Xin Zou
- Laboratory of Fear and Anxiety Disorders, Institutes of Life Science, Nanchang University, Nanchang, China
- Department of Biological Science, School of Life Science, Nanchang University, Nanchang, China
| | - Ye He
- Center for Medical Experiments, Nanchang University, Nanchang, China
| | - Chun-Yan Wang
- Laboratory of Fear and Anxiety Disorders, Institutes of Life Science, Nanchang University, Nanchang, China
| | - Bing-Xing Pan
- Laboratory of Fear and Anxiety Disorders, Institutes of Life Science, Nanchang University, Nanchang, China
| | - Han-Qing Pan
- Laboratory of Fear and Anxiety Disorders, Institutes of Life Science, Nanchang University, Nanchang, China
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86
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Bhuiyan SA, Xu M, Yang L, Semizoglou E, Bhatia P, Pantaleo KI, Tochitsky I, Jain A, Erdogan B, Blair S, Cat V, Mwirigi JM, Sankaranarayanan I, Tavares-Ferreira D, Green U, McIlvried LA, Copits BA, Bertels Z, Del Rosario JS, Widman AJ, Slivicki RA, Yi J, Woolf CJ, Lennerz JK, Whited JL, Price TJ, Gereau RW, Renthal W. Harmonized cross-species cell atlases of trigeminal and dorsal root ganglia. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.04.547740. [PMID: 37461736 PMCID: PMC10350076 DOI: 10.1101/2023.07.04.547740] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/30/2023]
Abstract
Peripheral sensory neurons in the dorsal root ganglion (DRG) and trigeminal ganglion (TG) are specialized to detect and transduce diverse environmental stimuli including touch, temperature, and pain to the central nervous system. Recent advances in single-cell RNA-sequencing (scRNA-seq) have provided new insights into the diversity of sensory ganglia cell types in rodents, non-human primates, and humans, but it remains difficult to compare transcriptomically defined cell types across studies and species. Here, we built cross-species harmonized atlases of DRG and TG cell types that describe 18 neuronal and 11 non-neuronal cell types across 6 species and 19 studies. We then demonstrate the utility of this harmonized reference atlas by using it to annotate newly profiled DRG nuclei/cells from both human and the highly regenerative axolotl. We observe that the transcriptomic profiles of sensory neuron subtypes are broadly similar across vertebrates, but the expression of functionally important neuropeptides and channels can vary notably. The new resources and data presented here can guide future studies in comparative transcriptomics, simplify cell type nomenclature differences across studies, and help prioritize targets for future pain therapy development.
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Affiliation(s)
- Shamsuddin A Bhuiyan
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Mengyi Xu
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
- Alan Edwards Center for Research on Pain and Department of Physiology, McGill University, Montreal, QC, H3G 1Y6, Canada
| | - Lite Yang
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
- Program in Neurosciences, Division of Biology and Biomedical Sciences, Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, Missouri 63110, USA
| | - Evangelia Semizoglou
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Parth Bhatia
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Katerina I Pantaleo
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
| | - Ivan Tochitsky
- F.M. Kirby Neurobiology Center and Department of Neurobiology, Boston Children's Hospital and Harvard Medical School, 3 Blackfan Cir. Boston, MA 02115
| | - Aakanksha Jain
- F.M. Kirby Neurobiology Center and Department of Neurobiology, Boston Children's Hospital and Harvard Medical School, 3 Blackfan Cir. Boston, MA 02115
| | - Burcu Erdogan
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, 02138
| | - Steven Blair
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, 02138
| | - Victor Cat
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, 02138
| | - Juliet M Mwirigi
- Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, 800 W Campbell Rd, Richardson, TX, 75080
| | - Ishwarya Sankaranarayanan
- Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, 800 W Campbell Rd, Richardson, TX, 75080
| | - Diana Tavares-Ferreira
- Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, 800 W Campbell Rd, Richardson, TX, 75080
| | - Ursula Green
- Department of Pathology, Center for Integrated Diagnostics, Massachussetts General Hospital and Havard Medical School, Boston, MA 02114
| | - Lisa A McIlvried
- Program in Neurosciences, Division of Biology and Biomedical Sciences, Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, Missouri 63110, USA
| | - Bryan A Copits
- Program in Neurosciences, Division of Biology and Biomedical Sciences, Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, Missouri 63110, USA
| | - Zachariah Bertels
- Program in Neurosciences, Division of Biology and Biomedical Sciences, Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, Missouri 63110, USA
| | - John S Del Rosario
- Program in Neurosciences, Division of Biology and Biomedical Sciences, Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, Missouri 63110, USA
| | - Allie J Widman
- Program in Neurosciences, Division of Biology and Biomedical Sciences, Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, Missouri 63110, USA
| | - Richard A Slivicki
- Program in Neurosciences, Division of Biology and Biomedical Sciences, Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, Missouri 63110, USA
| | - Jiwon Yi
- Program in Neurosciences, Division of Biology and Biomedical Sciences, Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, Missouri 63110, USA
| | - Clifford J Woolf
- F.M. Kirby Neurobiology Center and Department of Neurobiology, Boston Children's Hospital and Harvard Medical School, 3 Blackfan Cir. Boston, MA 02115
| | - Jochen K Lennerz
- Department of Pathology, Center for Integrated Diagnostics, Massachussetts General Hospital and Havard Medical School, Boston, MA 02114
| | - Jessica L Whited
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, Massachusetts, 02138
| | - Theodore J Price
- Department of Neuroscience and Center for Advanced Pain Studies, University of Texas at Dallas, 800 W Campbell Rd, Richardson, TX, 75080
| | - Robert W Gereau
- Program in Neurosciences, Division of Biology and Biomedical Sciences, Washington University Pain Center and Department of Anesthesiology, Washington University School of Medicine, St Louis, Missouri 63110, USA
| | - William Renthal
- Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA
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Sakaguchi S, Mizuno S, Okochi Y, Tanegashima C, Nishimura O, Uemura T, Kadota M, Naoki H, Kondo T. Single-cell transcriptome atlas of Drosophila gastrula 2.0. Cell Rep 2023:112707. [PMID: 37433294 DOI: 10.1016/j.celrep.2023.112707] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 03/27/2023] [Accepted: 06/13/2023] [Indexed: 07/13/2023] Open
Abstract
During development, positional information directs cells to specific fates, leading them to differentiate with their own transcriptomes and express specific behaviors and functions. However, the mechanisms underlying these processes in a genome-wide view remain ambiguous, partly because the single-cell transcriptomic data of early developing embryos containing accurate spatial and lineage information are still lacking. Here, we report a single-cell transcriptome atlas of Drosophila gastrulae, divided into 77 transcriptomically distinct clusters. We find that the expression profiles of plasma-membrane-related genes, but not those of transcription-factor genes, represent each germ layer, supporting the nonequivalent contribution of each transcription-factor mRNA level to effector gene expression profiles at the transcriptome level. We also reconstruct the spatial expression patterns of all genes at the single-cell stripe level as the smallest unit. This atlas is an important resource for the genome-wide understanding of the mechanisms by which genes cooperatively orchestrate Drosophila gastrulation.
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Affiliation(s)
- Shunta Sakaguchi
- Laboratory of Cell Recognition and Pattern Formation, Graduate School of Biostudies, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Sonoko Mizuno
- Laboratory of Cell Recognition and Pattern Formation, Graduate School of Biostudies, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Yasushi Okochi
- Laboratory of Theoretical Biology, Graduate School of Biostudies, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan; Faculty of Medicine, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Chiharu Tanegashima
- Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Osamu Nishimura
- Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Tadashi Uemura
- Laboratory of Cell Recognition and Pattern Formation, Graduate School of Biostudies, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan; Center for Living Systems Information Science, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan
| | - Mitsutaka Kadota
- Laboratory for Phyloinformatics, RIKEN Center for Biosystems Dynamics Research, Chuo-ku, Kobe, Hyogo 650-0047, Japan
| | - Honda Naoki
- Laboratory of Theoretical Biology, Graduate School of Biostudies, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan; Laboratory of Data-driven Biology, Graduate School of Integrated Sciences for Life, Hiroshima University, Higashihiroshima, Hiroshima 739-8511, Japan; Theoretical Biology Research Group, Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Okazaki, Aichi 444-8585, Japan
| | - Takefumi Kondo
- Graduate School of Biostudies, Kyoto University, Sakyo-ku, Kyoto 606-8501, Japan; The Keihanshin Consortium for Fostering the Next Generation of Global Leaders in Research (K-CONNEX), Sakyo-ku, Kyoto 606-8501, Japan.
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88
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Britton C, Laing R, McNeilly TN, Perez MG, Otto TD, Hildersley KA, Maizels RM, Devaney E, Gillan V. New technologies to study helminth development and host-parasite interactions. Int J Parasitol 2023; 53:393-403. [PMID: 36931423 DOI: 10.1016/j.ijpara.2022.11.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 11/24/2022] [Accepted: 11/26/2022] [Indexed: 03/17/2023]
Abstract
How parasites develop and survive, and how they stimulate or modulate host immune responses are important in understanding disease pathology and for the design of new control strategies. Microarray analysis and bulk RNA sequencing have provided a wealth of data on gene expression as parasites develop through different life-cycle stages and on host cell responses to infection. These techniques have enabled gene expression in the whole organism or host tissue to be detailed, but do not take account of the heterogeneity between cells of different types or developmental stages, nor the spatial organisation of these cells. Single-cell RNA-seq (scRNA-seq) adds a new dimension to studying parasite biology and host immunity by enabling gene profiling at the individual cell level. Here we review the application of scRNA-seq to establish gene expression cell atlases for multicellular helminths and to explore the expansion and molecular profile of individual host cell types involved in parasite immunity and tissue repair. Studying host-parasite interactions in vivo is challenging and we conclude this review by briefly discussing the applications of organoids (stem-cell derived mini-tissues) to examine host-parasite interactions at the local level, and as a potential system to study parasite development in vitro. Organoid technology and its applications have developed rapidly, and the elegant studies performed to date support the use of organoids as an alternative in vitro system for research on helminth parasites.
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Affiliation(s)
- Collette Britton
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, United Kingdom.
| | - Roz Laing
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, United Kingdom
| | - Tom N McNeilly
- Disease Control Department, Moredun Research Institute, Penicuik, United Kingdom
| | - Matias G Perez
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, United Kingdom
| | - Thomas D Otto
- Wellcome Centre for Integrative Parasitology, School of Infection and Immunity, University of Glasgow, Glasgow, United Kingdom
| | - Katie A Hildersley
- Disease Control Department, Moredun Research Institute, Penicuik, United Kingdom
| | - Rick M Maizels
- Wellcome Centre for Integrative Parasitology, School of Infection and Immunity, University of Glasgow, Glasgow, United Kingdom
| | - Eileen Devaney
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, United Kingdom
| | - Victoria Gillan
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, United Kingdom
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89
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Cain A, Taga M, McCabe C, Green GS, Hekselman I, White CC, Lee DI, Gaur P, Rozenblatt-Rosen O, Zhang F, Yeger-Lotem E, Bennett DA, Yang HS, Regev A, Menon V, Habib N, De Jager PL. Multicellular communities are perturbed in the aging human brain and Alzheimer's disease. Nat Neurosci 2023; 26:1267-1280. [PMID: 37336975 PMCID: PMC10789499 DOI: 10.1038/s41593-023-01356-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2020] [Accepted: 05/10/2023] [Indexed: 06/21/2023]
Abstract
The role of different cell types and their interactions in Alzheimer's disease (AD) is a complex and open question. Here, we pursued this question by assembling a high-resolution cellular map of the aging frontal cortex using single-nucleus RNA sequencing of 24 individuals with a range of clinicopathologic characteristics. We used this map to infer the neocortical cellular architecture of 638 individuals profiled by bulk RNA sequencing, providing the sample size necessary for identifying statistically robust associations. We uncovered diverse cell populations associated with AD, including a somatostatin inhibitory neuronal subtype and oligodendroglial states. We further identified a network of multicellular communities, each composed of coordinated subpopulations of neuronal, glial and endothelial cells, and we found that two of these communities are altered in AD. Finally, we used mediation analyses to prioritize cellular changes that might contribute to cognitive decline. Thus, our deconstruction of the aging neocortex provides a roadmap for evaluating the cellular microenvironments underlying AD and dementia.
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Affiliation(s)
- Anael Cain
- Edmond & Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Mariko Taga
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Cristin McCabe
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Gilad S Green
- Edmond & Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Idan Hekselman
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | | | - Dylan I Lee
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Pallavi Gaur
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - Orit Rozenblatt-Rosen
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Genentech, South San Francisco, CA, USA
| | - Feng Zhang
- Broad Institute, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Esti Yeger-Lotem
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Hyun-Sik Yang
- Broad Institute, Cambridge, MA, USA
- Harvard Medical School, Boston, MA, USA
- Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
| | - Aviv Regev
- Klarman Cell Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Biology, Koch Institute of Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA
- Genentech, South San Francisco, CA, USA
| | - Vilas Menon
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA.
| | - Naomi Habib
- Edmond & Lily Safra Center for Brain Sciences, The Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Philip L De Jager
- Center for Translational & Computational Immunology, Department of Neurology and Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA.
- Broad Institute, Cambridge, MA, USA.
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90
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van der Valk WH, van Beelen ESA, Steinhart MR, Nist-Lund C, Osorio D, de Groot JCMJ, Sun L, van Benthem PPG, Koehler KR, Locher H. A single-cell level comparison of human inner ear organoids with the human cochlea and vestibular organs. Cell Rep 2023; 42:112623. [PMID: 37289589 PMCID: PMC10592453 DOI: 10.1016/j.celrep.2023.112623] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 02/21/2023] [Accepted: 05/23/2023] [Indexed: 06/10/2023] Open
Abstract
Inner ear disorders are among the most common congenital abnormalities; however, current tissue culture models lack the cell type diversity to study these disorders and normal otic development. Here, we demonstrate the robustness of human pluripotent stem cell-derived inner ear organoids (IEOs) and evaluate cell type heterogeneity by single-cell transcriptomics. To validate our findings, we construct a single-cell atlas of human fetal and adult inner ear tissue. Our study identifies various cell types in the IEOs including periotic mesenchyme, type I and type II vestibular hair cells, and developing vestibular and cochlear epithelium. Many genes linked to congenital inner ear dysfunction are confirmed to be expressed in these cell types. Additional cell-cell communication analysis within IEOs and fetal tissue highlights the role of endothelial cells on the developing sensory epithelium. These findings provide insights into this organoid model and its potential applications in studying inner ear development and disorders.
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Affiliation(s)
- Wouter H van der Valk
- OtoBiology Leiden, Department of Otorhinolaryngology and Head & Neck Surgery, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands; The Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), Leiden University Medical Center, 2333 ZA Leiden, the Netherlands; Department of Otolaryngology, Boston Children's Hospital, Boston, MA 02115, USA; F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA 02115, USA; Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston, MA 02115, USA.
| | - Edward S A van Beelen
- OtoBiology Leiden, Department of Otorhinolaryngology and Head & Neck Surgery, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Matthew R Steinhart
- Department of Otolaryngology, Boston Children's Hospital, Boston, MA 02115, USA; F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA 02115, USA; Department of Otolaryngology-Head and Neck Surgery, Indiana University School of Medicine, Indianapolis, IN 46202, USA; Medical Neuroscience Graduate Program, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Carl Nist-Lund
- Department of Otolaryngology, Boston Children's Hospital, Boston, MA 02115, USA; F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA 02115, USA; Program in Neuroscience, Harvard Medical School, Boston, MA 02115, USA
| | - Daniel Osorio
- Research Computing, Department of Information Technology, Boston Children's Hospital, Boston, MA 02115, USA
| | - John C M J de Groot
- OtoBiology Leiden, Department of Otorhinolaryngology and Head & Neck Surgery, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Liang Sun
- Research Computing, Department of Information Technology, Boston Children's Hospital, Boston, MA 02115, USA
| | - Peter Paul G van Benthem
- OtoBiology Leiden, Department of Otorhinolaryngology and Head & Neck Surgery, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands
| | - Karl R Koehler
- Department of Otolaryngology, Boston Children's Hospital, Boston, MA 02115, USA; F.M. Kirby Neurobiology Center, Boston Children's Hospital, Boston, MA 02115, USA; Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston, MA 02115, USA; Department of Plastic and Oral Surgery, Boston Children's Hospital, Boston, MA 02115, USA.
| | - Heiko Locher
- OtoBiology Leiden, Department of Otorhinolaryngology and Head & Neck Surgery, Leiden University Medical Center, 2333 ZA Leiden, the Netherlands; The Novo Nordisk Foundation Center for Stem Cell Medicine (reNEW), Leiden University Medical Center, 2333 ZA Leiden, the Netherlands.
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91
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Zhang Y, Tan J, Yang K, Fan W, Yu B, Shi W. Ambient RNAs removal of cortex-specific snRNA-seq reveals Apoe + microglia/macrophage after deeper cerebral hypoperfusion in mice. J Neuroinflammation 2023; 20:152. [PMID: 37365617 DOI: 10.1186/s12974-023-02831-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 06/12/2023] [Indexed: 06/28/2023] Open
Abstract
BACKGROUND Ambient RNAs contamination in single-nuclei RNA sequencing (snRNA-seq) is a challenging problem, but the consequences of ambient RNAs contamination of damaged and/or diseased tissues are poorly understood. Cognitive impairments and white/gray matter injuries are characteristic of deeper cerebral hypoperfusion mouse models induced by bilateral carotid artery stenosis (BCAS), but the molecular mechanisms still need to be further explored. More importantly, the BCAS mice can also offer an excellent model to examine the signatures of ambient RNAs contamination in damaged tissues when performing snRNA-seq. METHODS After the sham and BCAS mice were established, cortex-specific single-nuclei libraries were constructed. Single-nuclei transcriptomes were described informatically by the R package Seurat, and ambient RNA markers of were identified in each library. Then, after removing ambient RNAs in each sample using the in silico approaches, the combination of CellBender and subcluster cleaning, single-nuclei transcriptomes were reconstructed. Next, the comparison of ambient RNA contamination was performed using irGSEA analysis before and after the in silico approaches. Finally, further bioinformatic analyses were performed. RESULTS The ambient RNAs are more predominant in the BCAS group than the sham group. The contamination mainly originated from damaged neuronal nuclei, but could be reduced largely using the in silico approaches. The integrative analysis of cortex-specific snRNA-seq data and the published bulk transcriptome revealed that microglia and other immune cells were the primary effectors. In the sequential microglia/immune subgroups analysis, the subgroup of Apoe+ MG/Mac (microglia/macrophages) was identified. Interestingly, this subgroup mainly participated in the pathways of lipid metabolism, associated with the phagocytosis of cell debris. CONCLUSIONS Taken together, our current study unravels the features of ambient RNAs in snRNA-seq datasets under diseased conditions, and the in silico approaches can effectively eliminate the incorrected cell annotation and following misleading analysis. In the future, snRNA-seq data analysis should be carefully revisited, and ambient RNAs removal needs to be taken into consideration, especially for those diseased tissues. To our best knowledge, our study also offers the first cortex-specific snRNA-seq data of deeper cerebral hypoperfusion, which provides with novel therapeutic targets.
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Affiliation(s)
- Yuan Zhang
- Department of Vascular Surgery, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, People's Republic of China
- Fudan Zhangjiang Institute, Shanghai, 201203, China
| | - Jinyun Tan
- Department of Vascular Surgery, Huashan Hospital of Fudan University, Shanghai, People's Republic of China
| | - Kai Yang
- Department of Vascular Surgery, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, People's Republic of China
| | - Weijian Fan
- Department of Vascular Surgery, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, People's Republic of China
| | - Bo Yu
- Department of Vascular Surgery, Shanghai Pudong Hospital, Fudan University Pudong Medical Center, Shanghai, People's Republic of China.
- Fudan Zhangjiang Institute, Shanghai, 201203, China.
| | - Weihao Shi
- Department of Vascular Surgery, Huashan Hospital of Fudan University, Shanghai, People's Republic of China.
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92
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Liu Y, Savier EL, DePiero VJ, Chen C, Schwalbe DC, Abraham-Fan RJ, Chen H, Campbell JN, Cang J. Mapping visual functions onto molecular cell types in the mouse superior colliculus. Neuron 2023; 111:1876-1886.e5. [PMID: 37086721 PMCID: PMC10330256 DOI: 10.1016/j.neuron.2023.03.036] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Revised: 03/17/2023] [Accepted: 03/28/2023] [Indexed: 04/24/2023]
Abstract
The superficial superior colliculus (sSC) carries out diverse roles in visual processing and behaviors, but how these functions are delegated among collicular neurons remains unclear. Here, using single-cell transcriptomics, we identified 28 neuron subtypes and subtype-enriched marker genes from tens of thousands of adult mouse sSC neurons. We then asked whether the sSC's molecular subtypes are tuned to different visual stimuli. Specifically, we imaged calcium dynamics in single sSC neurons in vivo during visual stimulation and then mapped marker gene transcripts onto the same neurons ex vivo. Our results identify a molecular subtype of inhibitory neuron accounting for ∼50% of the sSC's direction-selective cells, suggesting a genetic logic for the functional organization of the sSC. In addition, our studies provide a comprehensive molecular atlas of sSC neuron subtypes and a multimodal mapping method that will facilitate investigation of their respective functions, connectivity, and development.
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Affiliation(s)
- Yuanming Liu
- Department of Biology, University of Virginia, Charlottesville, VA 22904, USA
| | - Elise L Savier
- Department of Biology, University of Virginia, Charlottesville, VA 22904, USA
| | - Victor J DePiero
- Department of Biology, University of Virginia, Charlottesville, VA 22904, USA
| | - Chen Chen
- Department of Psychology, University of Virginia, Charlottesville, VA 22904, USA
| | - Dana C Schwalbe
- Department of Biology, University of Virginia, Charlottesville, VA 22904, USA
| | | | - Hui Chen
- Department of Biology, University of Virginia, Charlottesville, VA 22904, USA
| | - John N Campbell
- Department of Biology, University of Virginia, Charlottesville, VA 22904, USA.
| | - Jianhua Cang
- Department of Biology, University of Virginia, Charlottesville, VA 22904, USA; Department of Psychology, University of Virginia, Charlottesville, VA 22904, USA.
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93
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Boussaty EC, Tedeschi N, Novotny M, Ninoyu Y, Du E, Draf C, Zhang Y, Manor U, Scheuermann RH, Friedman R. Cochlear transcriptome analysis of an outbred mouse population (CFW). BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.15.528661. [PMID: 36824745 PMCID: PMC9948975 DOI: 10.1101/2023.02.15.528661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
Age-related hearing loss (ARHL) is the most common cause of hearing loss and one of the most prevalent conditions affecting the elderly worldwide. Despite evidence from our lab and others about its polygenic nature, little is known about the specific genes, cell types and pathways involved in ARHL, impeding the development of therapeutic interventions. In this manuscript, we describe, for the first time, the complete cell-type specific transcriptome of the aging mouse cochlea using snRNA-seq in an outbred mouse model in relation to auditory threshold variation. Cochlear cell types were identified using unsupervised clustering and annotated via a three-tiered approach - first by linking to expression of known marker genes, then using the NS-Forest algorithm to select minimum cluster-specific marker genes and reduce dimensional feature space for statistical comparison of our clusters with existing publicly-available data sets on the gEAR website (https://umgear.org/), and finally, by validating and refining the annotations using Multiplexed Error Robust Fluorescence In Situ Hybridization (MERFISH) and the cluster-specific marker genes as probes. We report on 60 unique cell-types expanding the number of defined cochlear cell types by more than two times. Importantly, we show significant specific cell type increases and decreases associated with loss of hearing acuity implicating specific subsets of hair cell subtypes, ganglion cell subtypes, and cell subtypes withing the stria vascularis in this model of ARHL. These results provide a view into the cellular and molecular mechanisms responsible for age-related hearing loss and pathways for therapeutic targeting.
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Affiliation(s)
| | | | | | - Yuzuru Ninoyu
- Department of Otolaryngology, University of California, San Diego, CA
| | - Eric Du
- Department of Otolaryngology, University of California, San Diego, CA
| | - Clara Draf
- Department of Otolaryngology, University of California, San Diego, CA
| | - Yun Zhang
- J. Craig Venter Institute, La Jolla, CA
| | - Uri Manor
- Salk Institute for Biological Studies, Waitt Advanced Biophotonics Center, La Jolla, CA, United States
| | - Richard H. Scheuermann
- J. Craig Venter Institute, La Jolla, CA
- Department of Pathology, University of California, San Diego, CA
| | - Rick Friedman
- Department of Otolaryngology, University of California, San Diego, CA
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94
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Tosoni G, Ayyildiz D, Bryois J, Macnair W, Fitzsimons CP, Lucassen PJ, Salta E. Mapping human adult hippocampal neurogenesis with single-cell transcriptomics: Reconciling controversy or fueling the debate? Neuron 2023; 111:1714-1731.e3. [PMID: 37015226 DOI: 10.1016/j.neuron.2023.03.010] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 02/06/2023] [Accepted: 03/08/2023] [Indexed: 04/05/2023]
Abstract
The notion of exploiting the regenerative potential of the human brain in physiological aging or neurological diseases represents a particularly attractive alternative to conventional strategies for enhancing or restoring brain function. However, a major first question to address is whether the human brain does possess the ability to regenerate. The existence of human adult hippocampal neurogenesis (AHN) has been at the center of a fierce scientific debate for many years. The advent of single-cell transcriptomic technologies was initially viewed as a panacea to resolving this controversy. However, recent single-cell RNA sequencing studies in the human hippocampus yielded conflicting results. Here, we critically discuss and re-analyze previously published AHN-related single-cell transcriptomic datasets. We argue that, although promising, the single-cell transcriptomic profiling of AHN in the human brain can be confounded by methodological, conceptual, and biological factors that need to be consistently addressed across studies and openly discussed within the scientific community.
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Affiliation(s)
- Giorgia Tosoni
- Laboratory of Neurogenesis and Neurodegeneration, Netherlands Institute for Neuroscience, 1105 BA, Amsterdam, the Netherlands
| | - Dilara Ayyildiz
- Laboratory of Neurogenesis and Neurodegeneration, Netherlands Institute for Neuroscience, 1105 BA, Amsterdam, the Netherlands
| | - Julien Bryois
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center, CH-4070, Basel, Switzerland
| | - Will Macnair
- Roche Pharma Research and Early Development, Neuroscience and Rare Diseases, Roche Innovation Center, CH-4070, Basel, Switzerland
| | - Carlos P Fitzsimons
- Brain Plasticity group, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, 1098 XH, Amsterdam, the Netherlands
| | - Paul J Lucassen
- Brain Plasticity group, Swammerdam Institute for Life Sciences, Faculty of Science, University of Amsterdam, 1098 XH, Amsterdam, the Netherlands; Center for Urban Mental Health, University of Amsterdam, 1098 SM, Amsterdam, the Netherlands
| | - Evgenia Salta
- Laboratory of Neurogenesis and Neurodegeneration, Netherlands Institute for Neuroscience, 1105 BA, Amsterdam, the Netherlands.
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95
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Ayupe AC, Choi JS, Beckedorff F, Catanuto P, Mccartan R, Levay K, Park KK. Single-Nucleus RNA Sequencing of Developing and Mature Superior Colliculus Identifies Neuronal Diversity and Candidate Mediators of Circuit Assembly. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.01.526254. [PMID: 36778361 PMCID: PMC9915630 DOI: 10.1101/2023.02.01.526254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The superior colliculus (SC) is a sensorimotor structure in the midbrain that integrates input from multiple sensory modalities to initiate motor commands. It undergoes well-characterized steps of circuit assembly during development, rendering the mouse SC a popular model to study establishment and refinement of neural connectivity. Here we performed single nucleus RNA-sequencing analysis of the mouse SC isolated at various developmental time points. Our study provides a transcriptomic landscape of the cell types that comprise the SC across murine development with particular emphasis on neuronal heterogeneity. We used these data to identify Pax7 as a marker for an anatomically homogeneous population of GABAergic neurons. Lastly, we report a repertoire of genes differentially expressed across the different postnatal ages, many of which are known to regulate axon guidance and synapse formation. Our data provide a valuable resource for interrogating the mechanisms of circuit development, and identifying markers for manipulating specific SC neuronal populations and circuits.
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96
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Piwecka M, Rajewsky N, Rybak-Wolf A. Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease. Nat Rev Neurol 2023; 19:346-362. [PMID: 37198436 PMCID: PMC10191412 DOI: 10.1038/s41582-023-00809-y] [Citation(s) in RCA: 51] [Impact Index Per Article: 51.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/31/2023] [Indexed: 05/19/2023]
Abstract
In the past decade, single-cell technologies have proliferated and improved from their technically challenging beginnings to become common laboratory methods capable of determining the expression of thousands of genes in thousands of cells simultaneously. The field has progressed by taking the CNS as a primary research subject - the cellular complexity and multiplicity of neuronal cell types provide fertile ground for the increasing power of single-cell methods. Current single-cell RNA sequencing methods can quantify gene expression with sufficient accuracy to finely resolve even subtle differences between cell types and states, thus providing a great tool for studying the molecular and cellular repertoire of the CNS and its disorders. However, single-cell RNA sequencing requires the dissociation of tissue samples, which means that the interrelationships between cells are lost. Spatial transcriptomic methods bypass tissue dissociation and retain this spatial information, thereby allowing gene expression to be assessed across thousands of cells within the context of tissue structural organization. Here, we discuss how single-cell and spatially resolved transcriptomics have been contributing to unravelling the pathomechanisms underlying brain disorders. We focus on three areas where we feel these new technologies have provided particularly useful insights: selective neuronal vulnerability, neuroimmune dysfunction and cell-type-specific treatment response. We also discuss the limitations and future directions of single-cell and spatial RNA sequencing technologies.
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Affiliation(s)
- Monika Piwecka
- Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, Poland
| | - Nikolaus Rajewsky
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrueck Center for Molecular Medicine, Berlin, Germany
| | - Agnieszka Rybak-Wolf
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrueck Center for Molecular Medicine, Berlin, Germany.
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97
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Fernández-Moya SM, Ganesh AJ, Plass M. Neural cell diversity in the light of single-cell transcriptomics. Transcription 2023; 14:158-176. [PMID: 38229529 PMCID: PMC10807474 DOI: 10.1080/21541264.2023.2295044] [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: 06/27/2023] [Accepted: 11/10/2023] [Indexed: 01/18/2024] Open
Abstract
The development of highly parallel and affordable high-throughput single-cell transcriptomics technologies has revolutionized our understanding of brain complexity. These methods have been used to build cellular maps of the brain, its different regions, and catalog the diversity of cells in each of them during development, aging and even in disease. Now we know that cellular diversity is way beyond what was previously thought. Single-cell transcriptomics analyses have revealed that cell types previously considered homogeneous based on imaging techniques differ depending on several factors including sex, age and location within the brain. The expression profiles of these cells have also been exploited to understand which are the regulatory programs behind cellular diversity and decipher the transcriptional pathways driving them. In this review, we summarize how single-cell transcriptomics have changed our view on the cellular diversity in the human brain, and how it could impact the way we study neurodegenerative diseases. Moreover, we describe the new computational approaches that can be used to study cellular differentiation and gain insight into the functions of individual cell populations under different conditions and their alterations in disease.
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Affiliation(s)
- Sandra María Fernández-Moya
- Gene Regulation of Cell Identity, Regenerative Medicine Program, Bellvitge Institute for Biomedical Research (IDIBELL), Barcelona, L’Hospitalet del Llobregat, Spain
- Program for Advancing Clinical Translation of Regenerative Medicine of Catalonia, P- CMR[C], Barcelona, L’Hospitalet del Llobregat, Spain
| | - Akshay Jaya Ganesh
- Gene Regulation of Cell Identity, Regenerative Medicine Program, Bellvitge Institute for Biomedical Research (IDIBELL), Barcelona, L’Hospitalet del Llobregat, Spain
- Program for Advancing Clinical Translation of Regenerative Medicine of Catalonia, P- CMR[C], Barcelona, L’Hospitalet del Llobregat, Spain
| | - Mireya Plass
- Gene Regulation of Cell Identity, Regenerative Medicine Program, Bellvitge Institute for Biomedical Research (IDIBELL), Barcelona, L’Hospitalet del Llobregat, Spain
- Program for Advancing Clinical Translation of Regenerative Medicine of Catalonia, P- CMR[C], Barcelona, L’Hospitalet del Llobregat, Spain
- Center for Networked Biomedical Research on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid, Spain
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98
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Sant P, Rippe K, Mallm JP. Approaches for single-cell RNA sequencing across tissues and cell types. Transcription 2023; 14:127-145. [PMID: 37062951 PMCID: PMC10807473 DOI: 10.1080/21541264.2023.2200721] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Accepted: 03/30/2023] [Indexed: 04/18/2023] Open
Abstract
Single-cell sequencing of RNA (scRNA-seq) has advanced our understanding of cellular heterogeneity and signaling in developmental biology and disease. A large number of complementary assays have been developed to profile transcriptomes of individual cells, also in combination with other readouts, such as chromatin accessibility or antibody-based analysis of protein surface markers. As scRNA-seq technologies are advancing fast, it is challenging to establish robust workflows and up-to-date protocols that are best suited to address the large range of research questions. Here, we review scRNA-seq techniques from mRNA end-counting to total RNA in relation to their specific features and outline the necessary sample preparation steps and quality control measures. Based on our experience in dealing with the continuously growing portfolio from the perspective of a central single-cell facility, we aim to provide guidance on how workflows can be best automatized and share our experience in coping with the continuous expansion of scRNA-seq techniques.
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Affiliation(s)
- Pooja Sant
- Single-cell Open Lab, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Karsten Rippe
- Division Chromatin Networks, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
| | - Jan-Philipp Mallm
- Single-cell Open Lab, German Cancer Research Center (DKFZ) and Bioquant, Heidelberg, Germany
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99
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Truong DD, Lamhamedi-Cherradi SE, Porter RW, Krishnan S, Swaminathan J, Gibson A, Lazar AJ, Livingston JA, Gopalakrishnan V, Gordon N, Daw NC, Navin NE, Gorlick R, Ludwig JA. Dissociation protocols used for sarcoma tissues bias the transcriptome observed in single-cell and single-nucleus RNA sequencing. BMC Cancer 2023; 23:488. [PMID: 37254069 PMCID: PMC10230784 DOI: 10.1186/s12885-023-10977-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 05/17/2023] [Indexed: 06/01/2023] Open
Abstract
BACKGROUND Single-cell RNA-seq has emerged as an innovative technology used to study complex tissues and characterize cell types, states, and lineages at a single-cell level. Classification of bulk tumors by their individual cellular constituents has also created new opportunities to generate single-cell atlases for many organs, cancers, and developmental models. Despite the tremendous promise of this technology, recent evidence studying epithelial tissues and diverse carcinomas suggests the methods used for tissue processing, cell disaggregation, and preservation can significantly bias gene expression and alter the observed cell types. To determine whether sarcomas - tumors of mesenchymal origin - are subject to the same technical artifacts, we profiled patient-derived tumor explants (PDXs) propagated from three aggressive subtypes: osteosarcoma (OS), Ewing sarcoma (ES), desmoplastic small round cell tumor (DSRCT). Given the rarity of these sarcoma subtypes, we explored whether single-nuclei RNA-seq from more widely available archival frozen specimens could accurately be identified by gene expression signatures linked to tissue phenotype or pathognomonic fusion proteins. RESULTS We systematically assessed dissociation methods across different sarcoma subtypes. We compared gene expression from single-cell and single-nucleus RNA-sequencing of 125,831 whole-cells and nuclei from ES, DSRCT, and OS PDXs. We detected warm dissociation artifacts in single-cell samples and gene length bias in single-nucleus samples. Classic sarcoma gene signatures were observed regardless of the dissociation method. In addition, we showed that dissociation method biases could be computationally corrected. CONCLUSIONS We highlighted transcriptional biases, including warm dissociation and gene-length biases, introduced by the dissociation method for various sarcoma subtypes. This work is the first to characterize how the dissociation methods used for sc/snRNA-seq may affect the interpretation of the molecular features in sarcoma PDXs.
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Affiliation(s)
- Danh D Truong
- Sarcoma Medical Oncology Department, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | | | - Robert W Porter
- Sarcoma Medical Oncology Department, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Sandhya Krishnan
- Sarcoma Medical Oncology Department, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | | | - Amber Gibson
- Division of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Alexander J Lazar
- Division of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - J Andrew Livingston
- Sarcoma Medical Oncology Department, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Vidya Gopalakrishnan
- Division of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Nancy Gordon
- Division of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Najat C Daw
- Division of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Nicholas E Navin
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Richard Gorlick
- Division of Pediatrics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Joseph A Ludwig
- Sarcoma Medical Oncology Department, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA.
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100
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Gabitto MI, Travaglini KJ, Rachleff VM, Kaplan ES, Long B, Ariza J, Ding Y, Mahoney JT, Dee N, Goldy J, Melief EJ, Brouner K, Campos J, Carr AJ, Casper T, Chakrabarty R, Clark M, Compos J, Cool J, Valera Cuevas NJ, Dalley R, Darvas M, Ding SL, Dolbeare T, Mac Donald CL, Egdorf T, Esposito L, Ferrer R, Gala R, Gary A, Gloe J, Guilford N, Guzman J, Ho W, Jarksy T, Johansen N, Kalmbach BE, Keene LM, Khawand S, Kilgore M, Kirkland A, Kunst M, Lee BR, Malone J, Maltzer Z, Martin N, McCue R, McMillen D, Meyerdierks E, Meyers KP, Mollenkopf T, Montine M, Nolan AL, Nyhus J, Olsen PA, Pacleb M, Pham T, Pom CA, Postupna N, Ruiz A, Schantz AM, Sorensen SA, Staats B, Sullivan M, Sunkin SM, Thompson C, Tieu M, Ting J, Torkelson A, Tran T, Wang MQ, Waters J, Wilson AM, Haynor D, Gatto N, Jayadev S, Mufti S, Ng L, Mukherjee S, Crane PK, Latimer CS, Levi BP, Smith K, Close JL, Miller JA, Hodge RD, Larson EB, Grabowski TJ, Hawrylycz M, Keene CD, Lein ES. Integrated multimodal cell atlas of Alzheimer's disease. RESEARCH SQUARE 2023:rs.3.rs-2921860. [PMID: 37292694 PMCID: PMC10246227 DOI: 10.21203/rs.3.rs-2921860/v1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Alzheimer's disease (AD) is the most common cause of dementia in older adults. Neuropathological and imaging studies have demonstrated a progressive and stereotyped accumulation of protein aggregates, but the underlying molecular and cellular mechanisms driving AD progression and vulnerable cell populations affected by disease remain coarsely understood. The current study harnesses single cell and spatial genomics tools and knowledge from the BRAIN Initiative Cell Census Network to understand the impact of disease progression on middle temporal gyrus cell types. We used image-based quantitative neuropathology to place 84 donors spanning the spectrum of AD pathology along a continuous disease pseudoprogression score and multiomic technologies to profile single nuclei from each donor, mapping their transcriptomes, epigenomes, and spatial coordinates to a common cell type reference with unprecedented resolution. Temporal analysis of cell-type proportions indicated an early reduction of Somatostatin-expressing neuronal subtypes and a late decrease of supragranular intratelencephalic-projecting excitatory and Parvalbumin-expressing neurons, with increases in disease-associated microglial and astrocytic states. We found complex gene expression differences, ranging from global to cell type-specific effects. These effects showed different temporal patterns indicating diverse cellular perturbations as a function of disease progression. A subset of donors showed a particularly severe cellular and molecular phenotype, which correlated with steeper cognitive decline. We have created a freely available public resource to explore these data and to accelerate progress in AD research at SEA-AD.org.
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Affiliation(s)
| | | | - Victoria M. Rachleff
- Allen Institute for Brain Science, Seattle, WA, 98109
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | | | - Brian Long
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Jeanelle Ariza
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | - Yi Ding
- Allen Institute for Brain Science, Seattle, WA, 98109
| | | | - Nick Dee
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Jeff Goldy
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Erica J. Melief
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | | | - John Campos
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | | | - Tamara Casper
- Allen Institute for Brain Science, Seattle, WA, 98109
| | | | - Michael Clark
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Jazmin Compos
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Jonah Cool
- Chan Zuckerberg Initiative, Redwood City, CA 94063
| | | | - Rachel Dalley
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Martin Darvas
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | - Song-Lin Ding
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Tim Dolbeare
- Allen Institute for Brain Science, Seattle, WA, 98109
| | | | - Tom Egdorf
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Luke Esposito
- Allen Institute for Brain Science, Seattle, WA, 98109
| | | | - Rohan Gala
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Amanda Gary
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Jessica Gloe
- Allen Institute for Brain Science, Seattle, WA, 98109
| | | | | | - Windy Ho
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Tim Jarksy
- Allen Institute for Brain Science, Seattle, WA, 98109
| | | | | | - Lisa M. Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | - Sarah Khawand
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | - Mitch Kilgore
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | - Amanda Kirkland
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | - Michael Kunst
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Brian R. Lee
- Allen Institute for Brain Science, Seattle, WA, 98109
| | | | - Zoe Maltzer
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Naomi Martin
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Rachel McCue
- Allen Institute for Brain Science, Seattle, WA, 98109
| | | | | | - Kelly P. Meyers
- Kaiser Permanente Washington Research Institute, Seattle, WA, 98101
| | | | - Mark Montine
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | - Amber L. Nolan
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | - Julie Nyhus
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Paul A. Olsen
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Maiya Pacleb
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | - Thanh Pham
- Allen Institute for Brain Science, Seattle, WA, 98109
| | | | - Nadia Postupna
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | - Augustin Ruiz
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Aimee M. Schantz
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | | | - Brian Staats
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Matt Sullivan
- Allen Institute for Brain Science, Seattle, WA, 98109
| | | | | | - Michael Tieu
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Jonathan Ting
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Amy Torkelson
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Tracy Tran
- Allen Institute for Brain Science, Seattle, WA, 98109
| | | | - Jack Waters
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Angela M. Wilson
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | - David Haynor
- Department of Radiology, University of Washington, Seattle, WA 98014
| | - Nicole Gatto
- Kaiser Permanente Washington Research Institute, Seattle, WA, 98101
| | - Suman Jayadev
- Department of Neurology, University of Washington, Seattle, WA 98104
| | - Shoaib Mufti
- Allen Institute for Brain Science, Seattle, WA, 98109
| | - Lydia Ng
- Allen Institute for Brain Science, Seattle, WA, 98109
| | | | - Paul K. Crane
- Department of Medicine, University of Washington, Seattle, WA 98104
| | - Caitlin S. Latimer
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | - Boaz P. Levi
- Allen Institute for Brain Science, Seattle, WA, 98109
| | | | | | | | | | - Eric B. Larson
- Department of Medicine, University of Washington, Seattle, WA 98104
| | | | | | - C. Dirk Keene
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98104
| | - Ed S. Lein
- Allen Institute for Brain Science, Seattle, WA, 98109
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