Our work is centered on advancing systems genetics approaches to study the genetic and environmental factors shaping dynamic, genome-wide processes of epigenetic modification, recombination, gene expression, and metabolism in a mammalian model system. Our approach is based on our previous work providing a detailed molecular understanding of the evolutionary origins of the laboratory mouse, which in turn led to the adoption of two novel populations of mice with extensive genomic diversity. The Collaborative Cross recombinant inbred strains provide a fixed number of reproducible genomes optimal for multiple testing, while Diversity Outbred mice provide high genetic mapping resolution and an endless supply of unique genomes. These populations share the same allelic compositions and are derived from the same set of eight progenitor strains. Together these mouse populations provide an integrating framework for connecting the multiple domains of genomic function we study, as well as complementary approaches for developing and validating predictive models of genetic and environmental effects. By pioneering the application of these resources, our Center aims to establish high community standards and new approaches for systems genetics studies. The Center for Genome Dynamics will engage a group of scientists with diverse specialties in computational, statistical, and biological domains in a common collaborative work environment. The Center will provide mentorship for career development of new faculty and postdoctoral associates. Our unique education program will engage high school and undergraduate students in challenging computational biology research. Our projects are designed to enhance our capabilities for discovering genetic and environmental causes of phenotypic diversity and for elucidating the molecular mechanisms underlying human health and disease. Using the premier mammalian model organism combined with high throughput molecular phenotyping technologies, physiological profiling, and computational modeling, we will develop predictive modeling and validation strategies that test the premises of personalized medicine. Our goal, using a variety of disease phenotypes, is to improve prediction and intervention strategies for complex diseases, with broad implication for multiple areas of human disease.
Differences in disease susceptibility and outcome are linked with variation in an individual's genetic makeup and environment. The Center for Genome Dynamics will use novel mouse populations, animal measurements and computational methods to identify genetic and environmental factors, and probe their role in diseases. Our innovative outreach programs will immerse students in this interdisciplinary approach to research. Center resources and training will be available to the scientific community, accelerating efforts to improve prediction, prevention and intervention strategies for multiple human diseases.
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|Ju, Chelsea J-T; Zhao, Zhuangtian; Wang, Wei (2017) Efficient Approach to Correct Read Alignment for Pseudogene Abundance Estimates. IEEE/ACM Trans Comput Biol Bioinform 14:522-533|
|Simecek, Petr; Forejt, Jiri; Williams, Robert W et al. (2017) High-Resolution Maps of Mouse Reference Populations. G3 (Bethesda) 7:3427-3434|
|Tyler, Anna L; Ji, Bo; Gatti, Daniel M et al. (2017) Epistatic Networks Jointly Influence Phenotypes Related to Metabolic Disease and Gene Expression in Diversity Outbred Mice. Genetics 206:621-639|
|Morgan, Andrew P; Gatti, Daniel M; Najarian, Maya L et al. (2017) Structural Variation Shapes the Landscape of Recombination in Mouse. Genetics 206:603-619|
|Parvanov, Emil D; Tian, Hui; Billings, Timothy et al. (2017) PRDM9 interactions with other proteins provide a link between recombination hotspots and the chromosomal axis in meiosis. Mol Biol Cell 28:488-499|
|Morgan, Andrew P; Didion, John P; Doran, Anthony G et al. (2016) Whole Genome Sequence of Two Wild-Derived Mus musculus domesticus Inbred Strains, LEWES/EiJ and ZALENDE/EiJ, with Different Diploid Numbers. G3 (Bethesda) 6:4211-4216|
|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|
|Gu, Tongjun; Gatti, Daniel M; Srivastava, Anuj et al. (2016) Genetic Architectures of Quantitative Variation in RNA Editing Pathways. Genetics 202:787-98|
|Korstanje, Ron; Deutsch, Konstantin; Bolanos-Palmieri, Patricia et al. (2016) Loss of Kynurenine 3-Mono-oxygenase Causes Proteinuria. J Am Soc Nephrol 27:3271-3277|
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