The method of linkage analysis, which is highly successful in identifying major genes, has driven the substantial progress of molecular geneticists in identifying the genetic basis of many human diseases with simple Mendelian inheritance. In contrast, the discovery of genetic factors for complex diseases such as heart disease, diabetes, schizophrenia, and susceptibility to cancer has been slow in coming. For such complex inherited diseases, linkage analysis has limited power, since lesions in a number of genes can contribute incrementally to causation. Despite the small effects of each such gene, however, the magnitude of their attributable risk may be large because they are quite frequent in the population, making them significant for public health. There is increasing agreement that association studies using a set of diallelic markers across the genome with markers evenly distributed at approximately 100 Kbp intervals would provide the necessary power to detect small genetic effects for a given complex disease trait. In order to take full advantage of the fruits of the human genome sequencing effort and begin to identify all the genetic factors important to human health and disease, technologies must be developed to identify up to 500,000 diallelic markers and to test them in up to 1,000 individuals. Our proposal is designed to take advantage of the global human genome sequencing effort to produce diallelic markers for a high density genetic map in a cost-effective way. It will grow with the expected increase in DNA sequence produced over the next few years, and can be expanded over time to produce a high-density genetic map in which the position of each marker is precisely known at the same time that the human genome sequencing is completed. With a minor investment, one adds value to the sequencing data by (a) determining the allele frequencies of a large number of SNPs in 4 major United States subpopulations, (b) verifying independently the DNA sequences generated by all the genome sequencing centers, and (c) establishing the haplotypes of several genomes. In addition, we will develop software tools for automated estimation of allele frequencies based on raw sequencing data, which will also be useful for heterozygote identification in mutation detection, and automate the homogeneous TDI genotyping assay. By employing the proposed approach, the Third Generation Genetic Map with precisely placed diallelic markers that are evenly placed in the genome and can be typed by the highly flexible high-throughput TDI assay will be available for use to study complex genetic traits as soon as the sequencing of the human genome is completed.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
5R01HG001720-02
Application #
2674278
Study Section
Special Emphasis Panel (ZHG1-HGR-N (O1))
Project Start
1997-09-30
Project End
2000-08-31
Budget Start
1998-09-01
Budget End
1999-08-31
Support Year
2
Fiscal Year
1998
Total Cost
Indirect Cost
Name
Washington University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
062761671
City
Saint Louis
State
MO
Country
United States
Zip Code
63130
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