Single-Cell RNA Sequencing of Oligodendrocyte Lineage Cells from the Mouse Central Nervous System

Background Genome-wide association studies have implicated dozens of genes with migraine susceptibility, but it remains unclear in which nervous system cell types these genes are expressed. Methods Using single-cell RNA sequencing data from the central and peripheral nervous system, including the trigeminal ganglion, the expression of putative migraine-associated genes was compared across neuronal, glial and neurovascular cell types within these tissues. Results Fifty-four putative migraine-associated genes were expressed in the central nervous system, peripheral nervous system or neurovascular cell types analyzed. Six genes (11.1%) were selectively enriched in central nervous system cell types, three (5.5%) in neurovascular cell types, and two (3.7%) in peripheral nervous system cell types. The remaining genes were expressed in multiple cell types. Conclusions Single-cell RNA sequencing of the brain and peripheral nervous system localizes each migraine-associated gene to its respective nervous system tissue and the cell types in which it is expressed. While the majority of migraine-associated genes are broadly expressed, we identified several cell-type-specific migraine-associated genes in the central nervous system, peripheral nervous system, and neurovasculature. Trial registration: not applicable.

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Excel Template for Identifying Mouse Myeloid Cell-Types in the Central Nervous System Based on Single-Cell RNA Sequencing Data

10.21203/rs.3.rs-1071141/v1 ◽

2021 ◽

Author(s):

He-zuo Lü ◽

Xin-Yi Lyu ◽

Jing-Lu Li ◽

Shu-Qin Ding ◽

Jian-Guo Hu

Keyword(s):

Central Nervous System ◽

Nervous System ◽

Single Cell ◽

Rna Sequencing ◽

Myeloid Cells ◽

Myeloid Cell ◽

Gene Markers ◽

Cell Clusters ◽

Significant Difference ◽

Single Cell Rna Sequencing

Abstract Background The myeloid cells play a vital role in health and disease of central nervous system (CNS). However, how to clearly distinguish them is still a knotty problem. At present, single-cell RNA Sequencing (scRNA-Seq) technology can sequence thousands of cells at the single-cell level, and then divide the cells into different clusters according to the similarity of gene expression, but it is still difficult to further identity these cell clusters. Generally, there are some specific marker genes for cell-type identities. However, it is difficult to distinguish a variety of myeloid cells in the CNS, because these cells often have the same or cross gene markers, and some markers will change significantly in different pathological states. Therefore, establishing a simple and practical method to distinguish these cell populations is of great significance for the analysis of scRNA-Seq data. Methods Referring to CellMarker (http://biocc.hrbmu.edu.cn/CellMarker/), PanglaoDB (https://panglaodb.se/) and Mouse Cell Atlas (http://bis.zju.edu.cn/MCA/gallery.html), combining with the recent literatures, a simple Excel template was designed, in which a panel of gene makers corresponding to the myeloid cells were included. The 83 cell clusters from several recently reported single-cell data were used to verify the accuracy of this template. Results This template could easily distinguish myeloid cell-subtypes and non-myeloid cells. Comparing with literatures, the overall consistency rate was 93.98%. There was no statistically significant difference between the two groups (Bowker’s test, P >0.05). Kappa symmetric measures showed that the Kappa value = 0.642 (P < 0.01). Conclusions The cell identities of scRNA-Seq cluster data could be performed using our simple Excel formulae, a panel of gene markers and ideal cell clustering data are the basis for accurate identification of CNS myeloid cell-subtypes.

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Single-Cell RNA Sequencing Reveals the Diversity of the Immunological Landscape following Central Nervous System Infection by a Murine Coronavirus

Journal of Virology ◽

10.1128/jvi.01295-20 ◽

2020 ◽

Vol 94 (24) ◽

Author(s):

Amber R. Syage ◽

H. Atakan Ekiz ◽

Dominic D. Skinner ◽

Colleen Stone ◽

Ryan M. O’Connell ◽

...

Keyword(s):

Central Nervous System ◽

Nervous System ◽

Immune Responses ◽

Viral Infection ◽

Single Cell ◽

Rna Sequencing ◽

Host Defense ◽

Molecular Signatures ◽

Single Cell Rna Sequencing ◽

Murine Coronavirus

ABSTRACT Intracranial (i.c.) infection of susceptible C57BL/6 mice with the neurotropic JHM strain of mouse hepatitis virus (JHMV) (a member of the Coronaviridae family) results in acute encephalomyelitis and viral persistence associated with an immune-mediated demyelinating disease. The present study was undertaken to better understand the molecular pathways evoked during innate and adaptive immune responses as well as the chronic demyelinating stage of disease in response to JHMV infection of the central nervous system (CNS). Using single-cell RNA sequencing analysis (scRNAseq) on flow-sorted CD45-positive (CD45+) cells enriched from brains and spinal cords of experimental mice, we demonstrate the heterogeneity of the immune response as determined by the presence of unique molecular signatures and pathways involved in effective antiviral host defense. Furthermore, we identify potential genes involved in contributing to demyelination as well as remyelination being expressed by both microglia and macrophages. Collectively, these findings emphasize the diversity of the immune responses and molecular networks at defined stages following viral infection of the CNS. IMPORTANCE Understanding the immunological mechanisms contributing to both host defense and disease following viral infection of the CNS is of critical importance given the increasing number of viruses that are capable of infecting and replicating within the nervous system. With this in mind, the present study was undertaken to evaluate the molecular signatures of immune cells within the CNS at defined times following infection with a neuroadapted murine coronavirus using scRNAseq. This approach has revealed that the immunological landscape is diverse, with numerous immune cell subsets expressing distinct mRNA expression profiles that are, in part, dictated by the stage of infection. In addition, these findings reveal new insight into cellular pathways contributing to control of viral replication as well as to neurologic disease.

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Microglia response following acute demyelination is heterogeneous and limits infiltrating macrophage dispersion

Science Advances ◽

10.1126/sciadv.aay6324 ◽

2020 ◽

Vol 6 (3) ◽

pp. eaay6324 ◽

Cited By ~ 15

Author(s):

Jason R. Plemel ◽

Jo Anne Stratton ◽

Nathan J. Michaels ◽

Khalil S. Rawji ◽

Eric Zhang ◽

...

Keyword(s):

Spinal Cord ◽

Central Nervous System ◽

Nervous System ◽

Sciatic Nerve ◽

Single Cell ◽

Peripheral Inflammation ◽

Macrophage Response ◽

Single Cell Rna Sequencing ◽

Privileged Status ◽

The Central Nervous System

Microglia and infiltrating macrophages are thought to orchestrate the central nervous system (CNS) response to injury; however, the similarities between these cells make it challenging to distinguish their relative contributions. We genetically labeled microglia and CNS-associated macrophages to distinguish them from infiltrating macrophages. Using single-cell RNA sequencing, we describe multiple microglia activation states, one of which was enriched for interferon associated signaling. Although blood-derived macrophages acutely infiltrated the demyelinated lesion, microglia progressively monopolized the lesion environment where they surrounded infiltrating macrophages. In the microglia-devoid sciatic nerve, the infiltrating macrophage response was sustained. In the CNS, the preferential proliferation of microglia and sparse microglia death contributed to microglia dominating the lesion. Microglia ablation reversed the spatial restriction of macrophages with the demyelinated spinal cord, highlighting an unrealized macrophages-microglia interaction. The restriction of peripheral inflammation by microglia may be a previously unidentified mechanism by which the CNS maintains its “immune privileged” status.

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Decoding nervous system by single-cell RNA sequencing

Quantitative Biology ◽

10.1007/s40484-017-0116-3 ◽

2017 ◽

Vol 5 (3) ◽

pp. 210-214 ◽

Cited By ~ 1

Author(s):

Ganlu Hu ◽

Guang-Zhong Wang

Keyword(s):

Nervous System ◽

Single Cell ◽

Rna Sequencing ◽

Single Cell Rna Sequencing

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Diversity of developing peripheral glia revealed by single cell RNA sequencing

10.1101/2020.12.04.411975 ◽

2020 ◽

Author(s):

OE Tasdemir-Yilmaz ◽

NR Druckenbrod ◽

OO Olukoya ◽

AR Yung ◽

I Bastille ◽

...

Keyword(s):

Nervous System ◽

Single Cell ◽

Rna Sequencing ◽

Neuronal Cell ◽

Neuronal Diversity ◽

Sensory Stimuli ◽

Neuronal Cell Bodies ◽

Single Cell Rna Sequencing ◽

Comprehensive Survey ◽

Peripheral Glia

AbstractThe peripheral nervous system responds to a wide variety of sensory stimuli, a process that requires great neuronal diversity. These diverse peripheral sensory neurons are closely associated with glial cells that originate from the neural crest (NC). However, the molecular nature and origins of diversity among peripheral glia is not understood. Here we used single cell RNA sequencing to profile and compare developing and mature glia from somatosensory lumbar dorsal root ganglia (DRG) and auditory spiral ganglia (SG). We found that the glial precursors (GPs) differ in their transcriptional profile and prevalence in these two systems. Despite their unique features, somatosensory and auditory GPs undergo convergent differentiation to generate myelinating and non-myelinating Schwann cells that are molecularly uniform. By contrast, although satellite glia surround the neuronal cell bodies in both ganglia, we found that those in the SG express multiple myelination-associated genes, while DRG satellite cells express components that suppress myelination. Lastly, we identified a set of glial signature genes that are also expressed by placode-derived supporting cells, providing new insights into commonalities among glia across the nervous system. This comprehensive survey of gene expression in peripheral glia constitutes a valuable resource for understanding how glia acquire specialized functions and how their roles differ across sensory modalities.

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