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.
|Carmody, Rachel N; Gerber, Georg K; Luevano Jr, Jesus M et al. (2015) Diet dominates host genotype in shaping the murine gut microbiota. Cell Host Microbe 17:72-84|
|Kelada, Samir N P; Carpenter, Danielle E; Aylor, David L et al. (2014) Integrative genetic analysis of allergic inflammation in the murine lung. Am J Respir Cell Mol Biol 51:436-45|
|Cheng, Wei; Zhang, Xiang; Guo, Zhishan et al. (2014) Graph-regularized dual Lasso for robust eQTL mapping. Bioinformatics 30:i139-48|
|Mazrouee, Sepideh; Wang, Wei (2014) FastHap: fast and accurate single individual haplotype reconstruction using fuzzy conflict graphs. Bioinformatics 30:i371-8|
|Tyler, A L; McGarr, T C; Beyer, B J et al. (2014) A genetic interaction network model of a complex neurological disease. Genes Brain Behav 13:831-40|
|Huang, Yuan; Caputo, Christina R; Noordmans, Gerda A et al. (2014) Identification of novel genes associated with renal tertiary lymphoid organ formation in aging mice. PLoS One 9:e91850|
|Philip, Vivek M; Tyler, Anna L; Carter, Gregory W (2014) Dissection of complex gene expression using the combined analysis of pleiotropy and epistasis. Pac Symp Biocomput :200-11|
|Noordmans, Gerda A; Huang, Yuan; Savage, Holly et al. (2014) Genetic analysis of intracapillary glomerular lipoprotein deposits in aging mice. PLoS One 9:e111308|
|Baker, Christopher L; Walker, Michael; Kajita, Shimpei et al. (2014) PRDM9 binding organizes hotspot nucleosomes and limits Holliday junction migration. Genome Res 24:724-32|
|Gatti, Daniel M; Svenson, Karen L; Shabalin, Andrey et al. (2014) Quantitative trait locus mapping methods for diversity outbred mice. G3 (Bethesda) 4:1623-33|
Showing the most recent 10 out of 70 publications