Genomics Commons^™

Role Of Clic4 And The Synaptic Transcriptome In The Behavioral And Molecular Neurobiology Of Ethanol, Rory M. Weston

Theses and Dissertations

Alcohol use disorder (AUD) is a prevalent neuropsychiatric disease with profound health, social, and economic consequences. With an estimated 50% heritability, identifying genes that engender risk and contribute to the underlying neurobiological mechanisms represents an important first step in developing effective treatments. Gene expression studies are an important source of candidate genes for studying AUD, providing windows into the molecular machinery engaged by the brain in response to ethanol. Published studies have identified chloride intracellular channel 4 (Clic4) as an ethanol-regulated gene in brain capable of modulating sensitivity to sedation in multiple species. The functions of Clic4 are …

A Systems Biology Approach To Detect Eqtls Associated With Mirna And Mrna Co-Expression Networks In The Nucleus Accumbens Of Chronic Alcoholic Patients, Mohammed Mamdani

Theses and Dissertations

Alcohol Dependence (AD) is a chronic substance use disorder with moderate heritability (60%). Linkage and genome-wide association studies (GWAS) have implicated a number of loci; however, the molecular mechanisms underlying AD are unclear. Advances in systems biology allow genome-wide expression data to be integrated with genetic data to detect expression quantitative trait loci (eQTL), polymorphisms that regulate gene expression levels, influence phenotypes and are significantly enriched among validated genetic signals for many commonly studied traits including AD.

We integrated genome-wide mRNA and miRNA expression data with genotypic data from the nucleus accumbens (NAc), a major addiction-related brain region, of 36 …

Methods For Integrative Analysis Of Genomic Data, Paul Manser

Theses and Dissertations

In recent years, the development of new genomic technologies has allowed for the investigation of many regulatory epigenetic marks besides expression levels, on a genome-wide scale. As the price for these technologies continues to decrease, study sizes will not only increase, but several different assays are beginning to be used for the same samples. It is therefore desirable to develop statistical methods to integrate multiple data types that can handle the increased computational burden of incorporating large data sets. Furthermore, it is important to develop sound quality control and normalization methods as technical errors can compound when integrating multiple genomic …