? Rodent inbred line crosses are widely used to map genetic loci associated with complex traits. This approach has proven to be powerful for detecting quantitative trait loci (QTL) however the resolution of QTL locations is often not sufficient to identify the gene (or genes) that are involved. We propose to develop analytical methods to combine information available in two or more inbred line crosses that will help to narrow conventional confidence intervals for QTL regions. Furthermore, by exploiting high-density single nucleotide polymorphism (SNP) data that are currently being generated for the common strains of inbred mice, we expect to achieve gene level resolution of QTLs by combining data from multiple crosses. Our strategy is based on the hypothesis that the common mouse strains are derived from a limited ancestral gene pool and thus QTLs detected in multiple crosses are likely to represent shared ancestral polymorphisms. ? ?
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| Keller, Mark P; Gatti, Daniel M; Schueler, Kathryn L et al. (2018) Genetic Drivers of Pancreatic Islet Function. Genetics 209:335-356 |
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| 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 |
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