A set of 1638 informative SNP markers easily assayed by the Amplifluor genotyping system were tested in 102 mouse strains, including the majority of the common and wild-derived inbred strains available from The Jackson Laboratory. Selected from publicly available databases, the markers are on average ∼1.5 Mb apart and, whenever possible, represent the rare allele in at least two strains. Amplifluor assays were developed for each marker and performed on two independent DNA samples from each strain. The mean number of polymorphisms between strains was 608±136 SD. Several tests indicate that the markers provide an effective system for performing genome scans and quantitative trait loci analyses in all but the most closely related strains. Additionally, the markers revealed several subtle differences between closely related mouse strains, including the groups of several 129, BALB, C3H, C57, and DBA strains, and a group of wild-derived inbred strains representing several Mus musculus subspecies. Applying a neighbor-joining method to the data, we constructed a mouse strain family tree, which in most cases confirmed existing genealogies.

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The mouse is the premier model organism in human disease research because all of its life stages are accessible and there are myriad experimental tools for comparative analysis and specific manipulation of its genome. The Mouse Genome Informatics Database (MGI, http://www.informatics.jax.org) supports biological knowledge building for the laboratory mouse by integrating and providing access to a wide range of data from DNA sequence to phenotype and disease associations. The integration of complex disease phenotypes, underlying genetic causes, and gene function information can be used to confirm human disease models and provide insight into disease mechanisms. We will illustrate the utility of MGI using hemochromatosis as an example. To describe phenotypic abnormalities and similarities to human disease in the mouse, we developed and utilize a vocabulary of mouse anomalies (the Mammalian Phenotype Ontology) and utilize the human disease terms provided in the Online Mendelian Inheritance in Man (OMIM). These standard terms provide a backbone for annotation, allowing both easy access and searching for researchers via web forms and computational access for data downloads. Within MGI, more than 12,000 mouse mutant alleles have been catalogued, representing mutations in more than 6,150 genes. Of these, more than 1,000 mutant alleles in 760 genes are associated with Mammalian Phenotype terms for hematopoietic defects and approximately 150 of these have an OMIM human disease association. For example, there are 26 alleles in 13 genes associated with Hermansky-Pudlak syndrome, 6 alleles in 4 genes associated with hereditary spherocytosis, and 9 alleles in 5 genes associated with hemochromatosis. According to OMIM data, hemochromatosis in human is associated with at least 5 different genes including HFE, HFE2, HAMP, TFR2, and SLC40A1. In mouse, 12 mutant alleles in three orthologous mouse genes, Hfe, Tfr2, and Slc40a1, have been described and used as potential models for hemochromatosis. Of these mutant alleles, 6 are associated with hemochromatosis phenotypes in MGI. In addition, there are at least 6 mutant alleles in 4 additional genes (B2m, Heph, Tfrc, and Trfr2) that have been associated with the hemocromatosis phenotype in mice and may yet be discovered to influence disease in humans. Finding an appropriate model system for study of human disease is a critical step toward understanding the biological mechanism leading to disease phenotype in human and mouse. MGI provides researchers with query forms that allow simple and complex questions to be addressed. These can range from queries about a single gene or disease term to precise queries that simultaneously address phenotype, disease, gene function, expression, and genome location data. The vocabulary-based phenotype and disease annotations as well as other structured data types can assist in robust and accurate data mining when posing complex biological questions in both computational and individual formats at MGI.