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Establishing neuronal diversity in the spinal cord: a time and a place
Open accessAbstract
The vertebrate spinal cord comprises multiple functionally distinct neuronal cell types arranged in characteristic positions. During development, these different types of neurons differentiate from transcriptionally distinct neural progenitors that are arrayed in discrete domains along the dorsal-ventral and anterior-posterior axes of the embryonic spinal cord. This organization arises in response to morphogen gradients acting upstream of a gene regulatory network, the architecture of which determines the spatial and temporal pattern of gene expression. In recent years, substantial progress has been made in deciphering the regulatory network that underlies the specification of distinct progenitor and neuronal cell identities. In this Review, we outline how distinct neuronal cell identities are established in response to spatial and temporal patterning systems, and outline novel experimental approaches to study the emergence and function of neuronal diversity in the spinal cord.
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Metadata
- Authors
- Sagner, A., & Briscoe, J.
- Venue
- Development
- Publisher
- The Company of Biologists
- Published
- 2019-11-15
- Volume
- 146
- Issue
- 22
- ISSN
- 0950-1991 (ISSN-L)
- 1477-9129
- OpenAlex
- W2990650992
- Cited by
- 281
- References
- 156
- FWCI
- 9.09
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.