In this application, we propose a highly ambitious yet realistically attainable goal: to align existing expertise at UNC-CH into a center of excellence in order to develop as a resource and demonstrate the utility of the murine Collaborative Cross (CC) to delineate genetic and environmental determinants of complex phenotypes drawn from psychiatry, the most intractable set of problems in all of biomedicine. We propose a particularly challenging definition of success - we will identify high probability etiological models (which can be realistically complex) and then prove the predictive capacity of these models by generating novel strains of mice bred to be at either very low or very high risk of the phenotype. Once validated, these high confidence models can then be tested in subsequent human studies. The data collected at the UNC center would be a valuable resource to the wider scientific community and could be used to interrogate any number of biological problems. The development of sophisticated, user-interactive databases to access the large, complex datasets collected represents a key component of the project. Accomplishing this overarching goal requires an exceptional diversity of scientific expertise - psychiatry, human genetics, mouse phenotyping, mouse genetics, statistical genetics, computational biology, and systems biology. Experts in all of these disciplines were deeply involved in the preparation of this application and are committed to the projects described here. Moreover, successful integration of these diverse fields is non-trivial;however, we can document that all scientists on this application have a history of extensive interactions over the past five years, know now how to work together and have a working knowledge of their colleagues'expertise. UNC-Chapel Hill has a shown an intense commitment to promoting inter-disciplinary genomics research and is one of the most collegial biomedical research institutions in the US which provides a fertile backdrop for "Science 2.0" projects such as that proposed here.
Psychiatric disorders are a paradox-the associated morbidity, mortality, and societal costs are enormous and yet, despite over a century of scientific study, there are few hard facts about the etiology of the core diseases. Although GWAS meta-analyses are in progress, early results suggest that strong and replicable findings are elusive. Our proposal provides an alternative model approach to complement the study of fundamental psychiatric phenotypes.
|Rogala, Allison R; Morgan, Andrew P; Christensen, Alexis M et al. (2014) The Collaborative Cross as a resource for modeling human disease: CC011/Unc, a new mouse model for spontaneous colitis. Mamm Genome 25:95-108|
|Crowley, James J; Kim, Yunjung; Lenarcic, Alan B et al. (2014) Genetics of adverse reactions to haloperidol in a mouse diallel: a drug-placebo experiment and Bayesian causal analysis. Genetics 196:321-47|
|Phillippi, J; Xie, Y; Miller, D R et al. (2014) Using the emerging Collaborative Cross to probe the immune system. Genes Immun 15:38-46|
|Zou, Fei; Sun, Wei; Crowley, James J et al. (2014) A novel statistical approach for jointly analyzing RNA-Seq data from F1 reciprocal crosses and inbred lines. Genetics 197:389-99|
|Didion, John P; de Villena, Fernando Pardo-Manuel (2013) Deconstructing Mus gemischus: advances in understanding ancestry, structure, and variation in the genome of the laboratory mouse. Mamm Genome 24:1-20|
|Calaway, John D; Lenarcic, Alan B; Didion, John P et al. (2013) Genetic architecture of skewed X inactivation in the laboratory mouse. PLoS Genet 9:e1003853|
|Wang, Jeremy R; de Villena, Fernando Pardo-Manuel; McMillan, Leonard (2012) Comparative analysis and visualization of multiple collinear genomes. BMC Bioinformatics 13 Suppl 3:S13|
|Collaborative Cross Consortium (2012) The genome architecture of the Collaborative Cross mouse genetic reference population. Genetics 190:389-401|