Use of Laser-Capture Microdissection for the Identification of Marker Genes for the Ventromedial Hypothalamic Nucleus
Open Access
- 20 April 2005
- journal article
- research article
- Published by Society for Neuroscience in Journal of Neuroscience
- Vol. 25 (16) , 4181-4188
- https://doi.org/10.1523/jneurosci.0158-05.2005
Abstract
The ventromedial hypothalamic nucleus (VMH) plays an important role in the control of feeding and energy homeostasis. In contrast to other hypothalamic nuclei that are also known to regulate energy balance, there is a paucity of nucleus-specific marker genes for the VMH, limiting the application of molecular approaches for analyzing VMH information processing, function, and circuitry. Here, we report the use of laser-capture microdissection to isolate a set of cDNAs that are enriched in the VMH relative to two adjacent hypothalamic nuclei, the arcuate and dorsomedial hypothalamus. The relative expression levels of nine of the 12 most robustly expressed VMH-enriched genes were confirmed by real-time PCR analysis using separate RNAs from these three nuclei. Three of these VMH-enriched genes were further characterized byin situhybridization histochemistry, includingpituitary adenylate cyclase activating polypeptide,cerebellin 1, and an expressed sequence tag namedLBH2. Finally, to test whether some of these genes were coordinately regulated, we monitored their expression insteroidogenic factor 1(SF-1) knock-out mice. SF-1 is a transcription factor that controls the development of the VMH. The RNA levels for four of these genes were reduced in these knock-out animals, further suggesting that they are direct or indirect targets of this orphan nuclear receptor. The VMH-enriched genes identified here provide a basis for a functional analysis of VMH neuronal subpopulations via the use of bacterial artificial chromosome transgenics and related technologies. These results also demonstrate the utility of laser-capture microdissection coupled with microarray technology to identify nucleus-specific transcriptional networks.Keywords
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