| Title |
Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility
|
|---|---|
| Published in |
Neuron, May 2016
|
| DOI | 10.1016/j.neuron.2016.04.015 |
| Pubmed ID | |
| Authors |
Rosemary C. Bagot, Hannah M. Cates, Immanuel Purushothaman, Zachary S. Lorsch, Deena M. Walker, Junshi Wang, Xiaojie Huang, Oliver M. Schlüter, Ian Maze, Catherine J. Peña, Elizabeth A. Heller, Orna Issler, Minghui Wang, Won-min Song, Jason. L. Stein, Xiaochuan Liu, Marie A. Doyle, Kimberly N. Scobie, Hao Sheng Sun, Rachael L. Neve, Daniel Geschwind, Yan Dong, Li Shen, Bin Zhang, Eric J. Nestler |
| Abstract |
Depression is a complex, heterogeneous disorder and a leading contributor to the global burden of disease. Most previous research has focused on individual brain regions and genes contributing to depression. However, emerging evidence in humans and animal models suggests that dysregulated circuit function and gene expression across multiple brain regions drive depressive phenotypes. Here, we performed RNA sequencing on four brain regions from control animals and those susceptible or resilient to chronic social defeat stress at multiple time points. We employed an integrative network biology approach to identify transcriptional networks and key driver genes that regulate susceptibility to depressive-like symptoms. Further, we validated in vivo several key drivers and their associated transcriptional networks that regulate depression susceptibility and confirmed their functional significance at the levels of gene transcription, synaptic regulation, and behavior. Our study reveals novel transcriptional networks that control stress susceptibility and offers fundamentally new leads for antidepressant drug discovery. |
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Mendeley readers
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Demographic breakdown
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| Professor > Associate Professor | 24 | 5% |
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