The broad, long-term objectives of the High-Throughput Genotyping and Genetic Linkage Analysis Facility? (Core E) are to provide the members of the program and their projects with a state-of-the-art facility for high-throughput,? automated genotyping and genetic linkage analysis for the mutation epidemiology of childhood? tumors. The objectives of Core E are: (1) to genotype constitutive DNA samples for genome-wide? linkage and association studies, (2) to allelotype on a genome-wide or targeted basis matched? normal/tumor DNA sample pairs for tumor-specific loss of constitutive heterozygosity (LOH), (3) to? maintain a functioning genotype database, and (4) to conduct genetic analyses on the obtained? genotype data. To this end, human genomic DNA samples of individuals from cancer families ascertained? by Dr. Strong (Core B) segregating either soft tissue sarcomas (STS) or osteosarcomas (OST) and? classified as having Li-Fraumeni syndrome (LFS) or one of its variants (Dr. Strong/Project 1 and Dr.? Krahe/Project 2), or Wilms' tumor (Dr. Huff/Project 4) will be analyzed using various complementing high-throughput? technologies integrating microsatellite and single nucleotide polymorphism (SNP) markers to? identify genomic regions co-segregating with the disease (Projects 1 and 2) and to confirm regions of LOH? (Projects 2 and 4). Genotyping platforms include fluorescent technology with highly informative? microsatellite markers in optimized panels for genome-wide genotyping and custom markers using a? universal primer approach for regional fine mapping (Projects 1, 2, and 4). High-density SNP microarrays? (approximately 10,000 or about 100,000 SNPs) will be used to genotype individuals in both p53 and non-p53 families to identify modifier genes of tumor susceptibility (Projects 1 and 2) and to allelotype matched normal/tumor DNA? sample pairs to identify regions of tumor-specific loss of constitutive heterozygosity (Projects 1 and 2).? Pyrosequencing will be used to type additional SNP markers in targeted regions identified by the above? approaches for fine mapping (Projects 1, 2, and 4). The obtained human genotype data will be analyzed for? genetic linkage and association by complementing parametric and non-parametric analysis methods. For? these analyses, Core E will interact closely with the Statistical Genetics and Bioinformatics Core (Core C)? headed by Dr. Amos. The ultimate goals are to map major cancer susceptibility genes and modifier genes? that underlie the observed increased segregation of certain cancers in the families studied by Drs. Strong? (Projects 1, Core B), Krahe (Project 2), and Huff (Project 4), to map and identify modifiers of tumor? susceptibility (Projects 1 and 2), and to identify additional genomic regions that may be involved in tumor? development and/or progression by providing LOH information (Project 2).
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