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Massively Parallel Single Nucleus Transcriptional Profiling Defines Spinal Cord Neurons and Their Activity during Behavior

Authors :
Anupama Sathyamurthy
Kory R. Johnson
Kaya J.E. Matson
Courtney I. Dobrott
Li Li
Anna R. Ryba
Tzipporah B. Bergman
Michael C. Kelly
Matthew W. Kelley
Ariel J. Levine
Source :
Cell Reports, Vol 22, Iss 8, Pp 2216-2225 (2018)
Publication Year :
2018
Publisher :
Elsevier, 2018.

Abstract

Summary: To understand the cellular basis of behavior, it is necessary to know the cell types that exist in the nervous system and their contributions to function. Spinal networks are essential for sensory processing and motor behavior and provide a powerful system for identifying the cellular correlates of behavior. Here, we used massively parallel single nucleus RNA sequencing (snRNA-seq) to create an atlas of the adult mouse lumbar spinal cord. We identified and molecularly characterized 43 neuronal populations. Next, we leveraged the snRNA-seq approach to provide unbiased identification of neuronal populations that were active following a sensory and a motor behavior, using a transcriptional signature of neuronal activity. This approach can be used in the future to link single nucleus gene expression data with dynamic biological responses to behavior, injury, and disease.

Details

Language :
English
ISSN :
22111247
Volume :
22
Issue :
8
Database :
Directory of Open Access Journals
Journal :
Cell Reports
Publication Type :
Academic Journal
Accession number :
edsdoj.57026a8a57af4f79b258cd29877bbf0c
Document Type :
article
Full Text :
https://doi.org/10.1016/j.celrep.2018.02.003