Forward genetics approaches using animal models are undergoing a period of change, in part in response to the changes that have occurred in human genetics in the past few years. New experimental designs, including the collaborative cross and advanced heterogeneous stock populations, have the potential to yield large populations of animals with a genetic constitution that more accurately reflects the human genetic state with regard to diversity and heterozygosity. In addition, there has been rapid development of inexpensive high- throughput phenotyping capabilities, notably with gene expression microarrays, but metabolite and protein profiling will soon cross thresholds of quality and affordability. These changes necessitate the development of new computational and statistical tools for interpreting data.
Our aims are to develop statistical methods in anticipation of new experimental approaches, to develop and disseminate software and data resources, and to analyze and interpret new and historical data from forward genetics experiments in mice. Our focus will shift from the historical objectives which emphasized gene discovery to new model-based approaches that exploit high dimensional and cumulative data to model systemic responses to genetic and environmental perturbations. The timely development of statistical methods and software will be critical to the success of mouse genetics in the coming years.
Experimental animals provide an important complement to genetic studies in humans and are essential when experiments involve potentially harmful exposure or are impossible to carry out with human subjects. This project will develop statistical and computational tools that are needed to interpret the outcomes of these experiments including newly developed approaches which enable us to work with mouse populations that more accurately reflect the human genetic state. )
| Gatti, D M; Weber, S N; Goodwin, N C et al. (2018) Genetic background influences susceptibility to chemotherapy-induced hematotoxicity. Pharmacogenomics J 18:319-330 |
| Keller, Mark P; Gatti, Daniel M; Schueler, Kathryn L et al. (2018) Genetic Drivers of Pancreatic Islet Function. Genetics 209:335-356 |
| Keele, Gregory R; Prokop, Jeremy W; He, Hong et al. (2018) Genetic Fine-Mapping and Identification of Candidate Genes and Variants for Adiposity Traits in Outbred Rats. Obesity (Silver Spring) 26:213-222 |
| Palus, Martin; Sohrabi, Yahya; Broman, Karl W et al. (2018) A novel locus on mouse chromosome 7 that influences survival after infection with tick-borne encephalitis virus. BMC Neurosci 19:39 |
| 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 |
| Srivastava, Anuj; Morgan, Andrew P; Najarian, Maya L et al. (2017) Genomes of the Mouse Collaborative Cross. Genetics 206:537-556 |
| Winter, Jean M; Gildea, Derek E; Andreas, Jonathan P et al. (2017) Mapping Complex Traits in a Diversity Outbred F1 Mouse Population Identifies Germline Modifiers of Metastasis in Human Prostate Cancer. Cell Syst 4:31-45.e6 |
| Gu, Tongjun; Gatti, Daniel M; Srivastava, Anuj et al. (2016) Genetic Architectures of Quantitative Variation in RNA Editing Pathways. Genetics 202:787-98 |
| Keller, Mark P; Paul, Pradyut K; Rabaglia, Mary E et al. (2016) The Transcription Factor Nfatc2 Regulates ?-Cell Proliferation and Genes Associated with Type 2 Diabetes in Mouse and Human Islets. PLoS Genet 12:e1006466 |
| Tian, Jianan; Keller, Mark P; Broman, Aimee Teo et al. (2016) The Dissection of Expression Quantitative Trait Locus Hotspots. Genetics 202:1563-74 |
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