scholarly journals Single-cell transcriptomic analysis of the adult mouse spinal cord reveals molecular diversity of autonomic and skeletal motor neurons

2021 ◽  
Vol 24 (4) ◽  
pp. 572-583 ◽  
Author(s):  
Jacob A. Blum ◽  
Sandy Klemm ◽  
Jennifer L. Shadrach ◽  
Kevin A. Guttenplan ◽  
Lisa Nakayama ◽  
...  
2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Marie-Josée Beaudet ◽  
Qiurui Yang ◽  
Sébastien Cadau ◽  
Mathieu Blais ◽  
Sabrina Bellenfant ◽  
...  

1992 ◽  
Vol 40 (2-3) ◽  
pp. 235-242 ◽  
Author(s):  
A. Baron-Van Evercooren ◽  
A. Gansmuller ◽  
E. Duhamel ◽  
F. Pascal ◽  
M. Gumpel

2021 ◽  
Author(s):  
Teresa Rayon ◽  
Rory J. Maizels ◽  
Christopher Barrington ◽  
James Briscoe

AbstractThe spinal cord receives input from peripheral sensory neurons and controls motor output by regulating muscle innervating motor neurons. These functions are carried out by neural circuits comprising molecularly and physiologically distinct neuronal subtypes that are generated in a characteristic spatial-temporal arrangement from progenitors in the embryonic neural tube. The systematic mapping of gene expression in mouse embryos has provided insight into the diversity and complexity of cells in the neural tube. For human embryos, however, less information has been available. To address this, we used single cell mRNA sequencing to profile cervical and thoracic regions in four human embryos of Carnegie Stages (CS) CS12, CS14, CS17 and CS19 from Gestational Weeks (W) 4-7. In total we recovered the transcriptomes of 71,219 cells. Analysis of progenitor and neuronal populations from the neural tube, as well as cells of the peripheral nervous system, in dorsal root ganglia adjacent to the neural tube, identified dozens of distinct cell types and facilitated the reconstruction of the differentiation pathways of specific neuronal subtypes. Comparison with existing mouse datasets revealed the overall similarity of mouse and human neural tube development while highlighting specific features that differed between species. These data provide a catalogue of gene expression and cell type identity in the developing neural tube that will support future studies of sensory and motor control systems and can be explored at https://shiny.crick.ac.uk/scviewer/neuraltube/.


2009 ◽  
Vol 183 (2) ◽  
pp. 223-237 ◽  
Author(s):  
Ping K. Yip ◽  
Timothy K.Y. Kaan ◽  
Daniel Fenesan ◽  
Marzia Malcangio

PLoS ONE ◽  
2017 ◽  
Vol 12 (10) ◽  
pp. e0186091 ◽  
Author(s):  
Andrew J. Darr ◽  
Matt C. Danzi ◽  
Lee Brady ◽  
Dorothea Emig-Agius ◽  
Amber Hackett ◽  
...  

2021 ◽  
Vol 2 (3) ◽  
pp. 100786
Author(s):  
Shrivas Chaterji ◽  
Arnab Barik ◽  
Anupama Sathyamurthy

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Daniel E. Russ ◽  
Ryan B. Patterson Cross ◽  
Li Li ◽  
Stephanie C. Koch ◽  
Kaya J. E. Matson ◽  
...  

AbstractSingle-cell RNA sequencing data can unveil the molecular diversity of cell types. Cell type atlases of the mouse spinal cord have been published in recent years but have not been integrated together. Here, we generate an atlas of spinal cell types based on single-cell transcriptomic data, unifying the available datasets into a common reference framework. We report a hierarchical structure of postnatal cell type relationships, with location providing the highest level of organization, then neurotransmitter status, family, and finally, dozens of refined populations. We validate a combinatorial marker code for each neuronal cell type and map their spatial distributions in the adult spinal cord. We also show complex lineage relationships among postnatal cell types. Additionally, we develop an open-source cell type classifier, SeqSeek, to facilitate the standardization of cell type identification. This work provides an integrated view of spinal cell types, their gene expression signatures, and their molecular organization.


2021 ◽  
Vol 218 (8) ◽  
Author(s):  
Lindsay M. Milich ◽  
James S. Choi ◽  
Christine Ryan ◽  
Susana R. Cerqueira ◽  
Sofia Benavides ◽  
...  

The wound healing process that occurs after spinal cord injury is critical for maintaining tissue homeostasis and limiting tissue damage, but eventually results in a scar-like environment that is not conducive to regeneration and repair. A better understanding of this dichotomy is critical to developing effective therapeutics that target the appropriate pathobiology, but a major challenge has been the large cellular heterogeneity that results in immensely complex cellular interactions. In this study, we used single-cell RNA sequencing to assess virtually all cell types that comprise the mouse spinal cord injury site. In addition to discovering novel subpopulations, we used expression values of receptor–ligand pairs to identify signaling pathways that are predicted to regulate specific cellular interactions during angiogenesis, gliosis, and fibrosis. Our dataset is a valuable resource that provides novel mechanistic insight into the pathobiology of not only spinal cord injury but also other traumatic disorders of the CNS.


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