This proposal describes a rational system for the identification of genes that control naturally occurring variability for fear conditioning (FC) in mice using a quantitative trait locus (QTL) mapping strategy. As QTL strategies and technologies have matured, it has become increasingly possible to identify the specific genes that cause QTLs. We will take advantage of all available tools, and build on the approaches that we and others have successfully used in previous studies of other phenotypes to identify specific genes that underlie phenotypic variability for FC.
In Specific Aim 1 we will examine QTL that we have already discovered in a cross between C57BL/6J (B6) and DBA/2J (D2) mice by employing a panel of B6 x A/J consomic mice.
In Specific Aim 2 we will extend the precision of our QTL mapping by using an 8th generation B6 x D2 advanced intercross line (AIL). We will employ both conventional and novel tools for the analysis of the AIL. The novel analysis addresses the problems created by the complex pedigree structure of an AIL by employing techniques originally developed for complex human pedigrees. We will also examine correlations between gene expression and extreme FC phenotype in the final generation of the AIL.
In Specific Aim 3 we will examine FC in a panel of inbred mouse strains, which will allow us to employ knowledge about the ancestral single nucleotide polymorphism (SNP) haplotypes that are the basis of genetic diversity in modern laboratory inbred strains. By examining only chromosomal regions already implicated by our preliminary results and the results of the first two Specific Aims, we will mitigate problems that have been associated with this approach in the past. Finally, in Specific Aim 4 we will integrate the information from the prior 3 Specific Aims and employ a battery of complementary experimental and bioinformatic techniques to identify quantitative trait genes (QTGs), which underlie the QTLs that we have identified. We will utilize knowledge of ancestral SNP haplotypes, clues from the published literature, between-strains coding sequence differences, regional expression data, and strain specific expression polymorphisms in order to identify candidate QTGs. This integrated approach builds on the strategies that have proved successful for gene identification in our own prior studies and the studies of others. Relevance: Anxiety disorders are debilitating illnesses characterized by excessive or inappropriate fears. We will identify genes associated with differential fear learning because evidence form both mice and humans suggests that such differences are genetically associated with anxiety disorders. These genes will later be examined in humans and will advance both diagnosis of anxiety disorders and the development of new and more effective treatments for normal and pathological anxiety.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
3R01MH079103-03S1
Application #
7871114
Study Section
Biobehavioral Regulation, Learning and Ethology Study Section (BRLE)
Program Officer
Beckel-Mitchener, Andrea C
Project Start
2009-07-01
Project End
2011-06-30
Budget Start
2009-07-01
Budget End
2011-06-30
Support Year
3
Fiscal Year
2009
Total Cost
$135,111
Indirect Cost
Name
University of Chicago
Department
Genetics
Type
Schools of Medicine
DUNS #
005421136
City
Chicago
State
IL
Country
United States
Zip Code
60637
McMurray, K M J; Ramaker, M J; Barkley-Levenson, A M et al. (2018) Identification of a novel, fast-acting GABAergic antidepressant. Mol Psychiatry 23:384-391
McMurray, Katherine M J; Sidhu, Preetpal S; Cook, James M et al. (2017) Genetic and pharmacological manipulation of glyoxalase 1 regulates voluntary ethanol consumption in mice. Addict Biol 22:381-389
McMurray, K M J; Du, X; Brownlee, M et al. (2016) Neuronal overexpression of Glo1 or amygdalar microinjection of methylglyoxal is sufficient to regulate anxiety-like behavior in mice. Behav Brain Res 301:119-23
French, John E; Gatti, Daniel M; Morgan, Daniel L et al. (2015) Diversity Outbred Mice Identify Population-Based Exposure Thresholds and Genetic Factors that Influence Benzene-Induced Genotoxicity. Environ Health Perspect 123:237-45
Sittig, Laura J; Jeong, Choongwon; Tixier, Emily et al. (2014) Phenotypic instability between the near isogenic substrains BALB/cJ and BALB/cByJ. Mamm Genome 25:564-72
Li, Yan; Cheng, Riyan; Spokas, Kurt A et al. (2014) Genetic variation for life history sensitivity to seasonal warming in Arabidopsis thaliana. Genetics 196:569-77
Coyner, Jennifer; McGuire, Jennifer L; Parker, Clarissa C et al. (2014) Mice selectively bred for High and Low fear behavior show differences in the number of pMAPK (p44/42 ERK) expressing neurons in lateral amygdala following Pavlovian fear conditioning. Neurobiol Learn Mem 112:195-203
McMurray, Katherine M J; Distler, Margaret G; Sidhu, Preetpal S et al. (2014) Glo1 inhibitors for neuropsychiatric and anti-epileptic drug development. Biochem Soc Trans 42:461-7
Distler, Margaret G; Gorfinkle, Naomi; Papale, Ligia A et al. (2013) Glyoxalase 1 and its substrate methylglyoxal are novel regulators of seizure susceptibility. Epilepsia 54:649-57
Cheng, Riyan; Palmer, Abraham A (2013) A simulation study of permutation, bootstrap, and gene dropping for assessing statistical significance in the case of unequal relatedness. Genetics 193:1015-8

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