The major goal in human genetics is to ascertain the relationship between DNA sequence variation and phenotypic variation. For these studies, molecular polymorphisms are indispensable for conventional meiotic mapping, fine-structure mapping and haplotype analysis. However, with the contemplated sequencing of a reference human genome and identification of all human genes, studies of complex genetic disorders are expected to be more efficient if one were to systematically search all human genes for functional variants by association and linkage disequilibrium studies. This requires the development of technology and methods for the systematic discovery of genetic variation in human DNA, primarily the single nucleotide polymorphisms (SNPs) which are the most abundant. Since functional variants may not reside in coding sequences only, we need to understand the relationship between functional variants and neutral variation in contiguous genomic regions, that is, we require studies of the nature and extent of sequence polymorphisms and linkage disequilibrium in genes, intergenic regions and flanking sites. This proposal is a collaborative effort, between human geneticists, a biotechnology company and population geneticists, which aims to use large-scale DNA microarray technologies for efficient genome-scale SNP discovery. The first major goal is to ascertain and refine methods for SNP discovery in contiguous genomic segments in a mixed population resource, assess the density with which robust SNP assays can be developed, and determine the allele frequency distribution of these SNPs. The studies will be conducted on multiple genomic segments 100 kilobases or greater whose nucleotide sequences are available in sequence databases and are known to contain candidate genes for neuropsychiatric disorders. The second major goal is to evaluate, by developing and genotyping multiplexed sets of SNPs, in four population samples of differing ages, the scale of background linkage disequilibrium to assess the density of polymorphisms needed to allow association mapping for complex human diseases and traits.
The second aim will allow us to accurately estimate the density of SNPs needed to efficiently develop haplotypes across the entire human genome for disease association studies.
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