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Neuronal atlas of the dorsal horn defines its architecture and links sensory input to transcriptional cell types.

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Title: Neuronal atlas of the dorsal horn defines its architecture and links sensory input to transcriptional cell types.
Authors: Häring, Martin, Zeisel, Amit, Hochgerner, Hannah, Rinwa, Puneet, Jakobsson, Jon E. T., Lönnerberg, Peter, La Manno, Gioele, Sharma, Nilesh, Borgius, Lotta, Kiehn, Ole, Lagerström, Malin C., Linnarsson, Sten, Ernfors, Patrik
Source: Nature Neuroscience. Jun2018, Vol. 21 Issue 6, p869-880. 12p. 4 Diagrams, 1 Graph, 1 Map.
Abstract: The dorsal horn of the spinal cord is critical to processing distinct modalities of noxious and innocuous sensation, but little is known of the neuronal subtypes involved, hampering efforts to deduce principles governing somatic sensation. Here we used single-cell RNA sequencing to classify sensory neurons in the mouse dorsal horn. We identified 15 inhibitory and 15 excitatory molecular subtypes of neurons, equaling the complexity in cerebral cortex. Validating our classification scheme in vivo and matching cell types to anatomy of the dorsal horn by spatial transcriptomics reveals laminar enrichment for each of the cell types. Neuron types, when combined, define a multilayered organization with like neurons layered together. Employing our scheme, we find that heat and cold stimuli activate discrete sets of both excitatory and inhibitory neuron types. This work provides a systematic and comprehensive molecular classification of spinal cord sensory neurons, enabling functional interrogation of sensory processing. Using single-cell RNA-seq, the authors produced a comprehensive atlas of the somatosensory spinal cord. They found that neuron types build the dorsal horn by a discrete layering and to be differentially engaged by noxious heat and cold. [ABSTRACT FROM AUTHOR]
Copyright of Nature Neuroscience is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: <searchLink fieldCode="JN" term="%22Nature+Neuroscience%22">Nature Neuroscience</searchLink>. Jun2018, Vol. 21 Issue 6, p869-880. 12p. 4 Diagrams, 1 Graph, 1 Map.
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  Data: The dorsal horn of the spinal cord is critical to processing distinct modalities of noxious and innocuous sensation, but little is known of the neuronal subtypes involved, hampering efforts to deduce principles governing somatic sensation. Here we used single-cell RNA sequencing to classify sensory neurons in the mouse dorsal horn. We identified 15 inhibitory and 15 excitatory molecular subtypes of neurons, equaling the complexity in cerebral cortex. Validating our classification scheme in vivo and matching cell types to anatomy of the dorsal horn by spatial transcriptomics reveals laminar enrichment for each of the cell types. Neuron types, when combined, define a multilayered organization with like neurons layered together. Employing our scheme, we find that heat and cold stimuli activate discrete sets of both excitatory and inhibitory neuron types. This work provides a systematic and comprehensive molecular classification of spinal cord sensory neurons, enabling functional interrogation of sensory processing. Using single-cell RNA-seq, the authors produced a comprehensive atlas of the somatosensory spinal cord. They found that neuron types build the dorsal horn by a discrete layering and to be differentially engaged by noxious heat and cold. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Nature Neuroscience is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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