Association Analyses of Known Genetic Variants with Gene Expression in Brain.
AbstractThe availability of high through-put genome-wide expression technologies has resulted in an unprecedented ability to analyze the consequences of genetic mutations or variants on expression. When a Mendelian disorder is caused by mutations in a gene encoding a protein of unknown function, gene expression analysis can help define molecular pathways affected, and thus place the unknown gene product into functional context. We have used DNA microarray analysis to elucidate the functional deficits in two different mouse models of ataxia. In a mouse model of Cayman ataxia, we found dysregulation of glutamate signaling in the cerebellum. In the second ataxic mouse mutant, waddles, our analysis revealed calcium signaling as the most prominently affected pathway. In contrast to these single gene disorders, in complex disorders many genetic variants are involved, each with only a small contribution to the phenotype, and it is often unclear which variant has functional consequences. Here, we hypothesized that gene expression studies may aid in defining gene targets, especially in the primary tissue of interest. Focusing on genetic markers that were significantly associated with bipolar disorder in several genome-wide association studies (GWAS), we combined expression and genotype information from ~100 postmortem human brain samples. We identified genetic variants that significantly affect gene expression of a nearby gene, although these expression-associated variants were not identical with the best GWAS findings. While each of the three studies addressed different biological questions, common challenges arose. The most prominent one was the heterogeneity and complexity of brain tissue, which resulted in noisier and less striking expression changes than those typically seen from homogenous tissue or cell culture sources. In summary, we successfully addressed these and other technical issues and utilized microarray expression technology to generate new specific biological hypotheses for follow-up studies.
Microarray Gene Expression Analysis
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