Meiotic gene maps have proven to be valuable tools in the field of human genetic research. These maps provide significant insights into human disease, genetic diversity, and chromosome/gene structure. The meiotic maps play a crucial role in integrating the information obtained from physical mapping techniques with the study of genetic disorders of unknown molecular etiology. The construction of multilocus human genetic maps has become common place due to the ubiquity of user-friendly computer analysis programs. Recently, efforts have been focused on the construction on high resolution linkage maps. In these maps, the target interlocus map distances are 5 cMs or less. While theoretically these methods should have similar analytic characteristics, practical differences in the nature of the data and the statistical problem may result in unexpected outcomes. This is particularly true with respect to the influence of aberrant observations. Uncertainty of data validity has resulted in the construction of meiotic maps of unknown integrity. Preliminary studies have shown that genotyping errors can lead to gross inflation of map distances and derivation of incorrect gene orders. There are currently no widely accepted methods for the identification/correction of genotype misclassification. It is the primary goal of this research to construct a high integrity, fine structure, meiotic map of each human chromosome. However, to address the above questions, amp construction will proceed simultaneously with development of statistical tools that allow the assessment of map quality and integrity.
In SPECIFIC AIM I the analytic methods used in the construction of fine structure genetic maps will be extended. The primary focus of these efforts will be the development of statistical diagnostic methods for the evaluation of mapping outcomes.
In SPECIFIC AIM II, the information garnered above will be applied to the DNA polymorphism data collected in PROJECTS 3 and 4 to construct a high resolution meiotic map of each human chromosome. Map construction will be conducted in a two tiered manner. First, a high heterozygosity 10 cM resolution index map of PCR detectable markers will be constructed. Next, crossover minimization techniques will be used to integrate additional points to achieve a 2.5 cM minimum density index map. These techniques will also be applied to obtain likely locations for a large number of gene loci.
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