Diabetes Genome Anatomy Project |
|
Projects > Project 5A
Project 5A:
Genetic Variability of Highly Regulated Diabetogenes
Primary Investigator: David Altshuler, M.D., Ph.D. (Broad Institute of Harvard and MIT)
Specific Aims
- To identify genetic variants in these candidate genes by targeted resequencing in an ethnically diverse sample of individuals (12 Caucasians, 12 Hispanics, 12 African-Americans, and 12 Asian-Americans) with type 2 diabetes.
- To validate these polymorphisms, determine their pattern of linkage disequilibrium, and estimate haplotype distributions at each locus by genotyping 48 nuclear families.
Resequencing is carried out by Dr. David Altshuler at the Whitehead Institute, while the haplotype characterization is performed in Dr. Alessandro Doria’s laboratory at the Joslin Diabetes. This effort is expected to generate a well-characterized set of about 2,000 polymorphisms that will be posted on the DGAP website and contributed to the SNP database. This resource will lay a foundation for comprehensive association studies of these loci in well-designed patient populations. It will also foster molecular studies aimed at investigating the effects of these variants on biological functions.
Summary
The Diabetes Genome Anatomy Project (DGAP) is using expression profiling to identify genes with putative roles in insulin action and the pathophysiology of diabetes. Genetic variability at these loci may play a causal role in the development of insulin-resistance and type 2 diabetes. One powerful way to test such hypothesis is to study whether inherited sequence differences are associated with diabetes in human populations. With the advent of the human genome sequence, improved understanding of genetic variation, and high-throughput technologies it is now possible to comprehensively test allelic variation at candidate loci.
In this DGAP subproject, we are characterizing the pattern of sequence variation in a carefully selected set of 100 genes that are identified by the DGAP as being highly insulin-regulated and/or abnormally expressed in type 2 diabetes. In order to compile a catalog as comprehensive as possible, we are using two complementary approaches. We are targeting all known functional regions (coding, immediate upstream "promoter" sequences, and regions of mouse-human non-coding homology), but we are also searching for the most informative polymorphisms to define ancestral haplotypes at each locus. This combination of such direct and indirect approaches will maximize the power to screen known functional regions, while fostering discovery of associations to variants within currently unrecognized regulatory sequences.
