Research Component 6:
Characterization of Ethanol Response QTL on Chromosome 11
Director: Kari Buck Co-Director: Robert Hitzemann
Susceptibility to physiological dependence on ethanol, which is manifested as a withdrawal syndrome, is influenced by multiple genes and environmental factors. We have identified three chromosomal regions that contain genes that influence acute ethanol withdrawal severity in mice. These chromosomal regions are referred to as quantitative trait loci (QTLs).
This application focuses on the Chr 11 QTL (p=1x10-7 or LOD=7). We have fine mapped this QTL to a 3 cM interval that contains 28 known genes and 6 predicted genes.
This proposal will use novel, genetic animal models for rigorous, unbiased evaluations of the known and predicted genes in this QTL interval as potential candidate genes. In addition, we will evaluate the influence of the QTL (gene) on neuronal activation related to physiological dependence on ethanol and associated withdrawal.
Using a novel congenic strain that isolates the QTL on a uniform (inbred) genetic background, we propose the following:
(1) Evaluate the predicted genes in the QTL interval for expression to determine where and when they are expressed. Expression will be assessed in the postnatal brain and the developing embryo.
(2) Evaluate the expressed genes to identify promising candidates that show genotype-dependent (congenic vs. background strain mice) differences in expression. In addition, expressed genes will be tested for differential regulatory and coding sequence (structural differences) between the two progenitor strains. Whenever feasible, their protein products will be assessed immunohistochemically to determine the anatomical distribution of their expression, and genotype-dependent differences in protein abundance will be assessed using semi-quantitative Western blot analysis.
(3) Evaluate neuronal activation to identify the circuit(s) that show genotype-dependent activation in ethanol withdrawn mice.
(4) Use viral mediated gene transfer and transgenic models to directly test the role of especially promising candidate genes (e.g., Gabrg2) in ethanol withdrawal.
An innovative feature of this proposal is to combine a robust behavioral model of physiological dependence on ethanol with sophisticated molecular techniques to identify candidate genes of high quality as well as the circuit(s) involved in their influence on ethanol withdrawal, and novel transgenic models that can establish with certainty that a promising candidate gene in fact underlies the QTL.
Thus, the proposed work will complete the journey from identifying genetic risk due to multiple anonymous genes to identification of specific genes that confer sensitivity to, or protection from, ethanol withdrawal. This will set the stage for future translational and mechanistic studies.
Mark Rutledge-Gorman
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