Our overarching goal is to discover the shared genomic mechanisms underlying alcoholism, addiction, neurobehavioral processes and the relations among these disorders. To do so we have developed a knowledge discovery environment, GeneWeaver.org, which enables users to store and integrate functional genomics data across species and experiment type. We curate data into this system around the behavioral neurosciences with a specific emphasis on alcoholism and addiction studies. Many other data sets are obtained from user submissions and major public resources. These data can be queried through a variety of means based on gene content and study description. User defined query results and user input data are harmonized and integrated through a suite of novel graph algorithms and tools to find genes highly associated to sets of biological processes and to find relations among aspects of alcoholism, addiction and related disorders. These relations are discovered primarily from empirical data via large-scale experimentation. We apply the system to questions in alcoholism and addiction research and perform validation studies on those findings which have sufficient novelty, feasibility and interest. In our renewal period, we will extend our work in several important ways. First, we will expand the breadth of biomolecular entities that the system supports, both by organism and molecular type, to capture the scope of functional genomics with greater precision and depth. Second, we will go beyond the comparison of the many sets of biomolecules that result from functional genomics studies to the comparison of relations among these entities, i.e., we will transition from set comparison to network comparison. Third, we will more explicitly apply the system to the biological comparison of behavioral disorders and the assessment of the conceptual integrity of terms such as anxiety and alcoholism or hyperactivity and addiction and to identify those biological entities that underlie core features of the overlap among these neurobehavioral conditions.
Alcoholism and drug addiction are chronic diseases with limited treatment options. They create a tremendous legal, social, and public health burden both in the US and worldwide with limited treatment options. The relationships among these disorders and the many biological and behavioral phenomena to which they are associated can help to improve the precision with which these disorders are treated in different individuals. By applying and extending our novel computational tools and data resources, we are able to integrate a tremendous amount of existing studies to find evidence for genes and other biological features in various aspects of alcoholism, addiction and associated behavioral disorders. These computational tools can be applied to any other disease area of interest, facilitate cost-effective data reuse, and respond to the growing need to synthesize diverse research findings.
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| Macartney-Coxson, Donia; Benton, Miles C; Blick, Ray et al. (2017) Genome-wide DNA methylation analysis reveals loci that distinguish different types of adipose tissue in obese individuals. Clin Epigenetics 9:48 |
| Cong, Yingnan; Chan, Yao-Ban; Phillips, Charles A et al. (2017) Robust Inference of Genetic Exchange Communities from Microbial Genomes Using TF-IDF. Front Microbiol 8:21 |
| Delprato, A; Algéo, M-P; Bonheur, B et al. (2017) QTL and systems genetics analysis of mouse grooming and behavioral responses to novelty in an open field. Genes Brain Behav 16:790-799 |
| Chesler, Elissa J; Gatti, Daniel M; Morgan, Andrew P et al. (2016) Diversity Outbred Mice at 21: Maintaining Allelic Variation in the Face of Selection. G3 (Bethesda) 6:3893-3902 |
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