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The EGR family of transcription-regulatory factors: progress at the interface of molecular and systems neuroscience
Open accessAbstract
The EGR family of transcription regulatory factors, which is implicated in orchestrating the changes in gene expression that underlie neuronal plasticity, has attracted the attention of both molecular and systems neuroscientists. In this article, the advances made in both these fields of research are reviewed. Recent systems-based studies underscore the remarkable sensitivity and specificity of the induction of the expression of genes encoding EGR-family members in naturally occurring plasticity paradigms. However, they also challenge conventional views of the role of this family in plasticity. Recent molecular studies have identified the gonadotropin subunit, luteinizing hormone beta, as an EGR1-regulated gene in vivo and uncovered an essential role for EGR3 in muscle-spindle development. In addition, the discovery of novel proteins that are capable of suppressing EGR-mediated transcription cast doubt over the prevalent assumption that changes in EGR mRNA or protein levels provide an accurate measure of EGR-driven transcriptional activity.
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Metadata
- Authors
- O'Donovan, K. J., Tourtellotte, W. G., Millbrandt, J., & Baraban, J. M.
- Venue
- Trends in Neurosciences
- Publisher
- Elsevier BV
- Published
- 1999-04
- Volume
- 22
- Issue
- 4
- Pages
- 167-173
- ISSN
- 0166-2236 (ISSN-L)
- OpenAlex
- W2072329780
- Cited by
- 457
- References
- 0
- FWCI
- 1.15
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- O'Donovan, K. J., Tourtellotte, W. G., Millbrandt, J., & Baraban, J. M. (1999). The EGR family of transcription-regulatory factors: progress at the interface of molecular and systems neuroscience. Trends in Neurosciences. https://doi.org/10.1016/s0166-2236(98)01343-5
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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.
