Type 2 diabetes (T2D) affects more than 170 million people worldwide and this number is expected to double by 2025 (91). T2D is a leading cause of kidney failure, blindness and limb amputation and a major risk factor for heart disease and stroke (18). Understanding the genetic mechanisms involved in T2D will help in prevention and treatment of this disease. While many genes have recently been identified in human genome wide association studies (GWAS), these genes explain only a small percentage of the population variance (94), indicating that many more genes have yet to be identified. My laboratory has successfully used a unique genetic resource, heterogeneous stock (HS) rats, to fine- map multiple metabolic traits within a single region on rat chromosome one. The confidence interval of many of these loci was less than 5 Megabases. This resource leverages existing recombinations (the major limitation in positional cloning) in the animals, markedly improving map resolution. We are now poised to accelerate the discovery of loci genome-wide using HS rats. We hypothesize that this resource will be useful for rapidly fine-mapping metabolic traits genome-wide, thereby providing a resource to identify novel genes involved in T2D and other metabolic disorders. To date, our laboratory has phenotyped over 500 HS rats for multiple metabolic phenotypes (glucose and insulin after a glucose challenge, fasting plasma cholesterol and triglyceride levels, body weight and fat pad weight).
In Specific Aim 1 of this proposal, we will fine-map these traits genome-wide using HS rats. We plan to phenotype an additional 500 rats and genotype these 1000 animals using the Affymetrix 10K single nucleotide polymorphism array. We will identify fine-mapped loci using single and multiple locus mapping methods. We expect to identify 3-15 loci across the genome for each trait measured and will follow-up at least one of these new loci in the following aim.
In Specific Aim 2 of this proposal, we plan to identify a gene or genes involved in diabetes or metabolic disorders within one of the fine-mapped regions identified in Specific Aim 1. We will use both sequencing and expression analyses to narrow candidate genes within this region. Importantly, the multiple alleles found in the HS provide increased power for identifying candidate variants. The goal of the sequencing analysis will be to narrow the candidate variants within this region from several thousand to less than 100. These variants will then serve as a means for prioritizing candidate genes to be tested further using mRNA expression analysis in metabolically relevant tissues. The major impact of this work will be to accelerate discovery of genes involved in T2D and related metabolic disorders to a level that has not previously been possible using conventional mapping methods in animal models.
Project Narrative: Type 2 diabetes is the leading cause of kidney failure, blindness and limb amputation and a major risk factor for heart disease and stroke. With the prevalence of this disorder increasing at alarming rates worldwide, it is imperative to understand the underlying genetic mechanisms of this disorder. The work outlined in this proposal will serve as a means for identifying novel genes involved in type 2 diabetes, thereby leading to improved treatment and/or better prevention methods in humans.
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|Solberg Woods, Leah C; Holl, Katie L; Oreper, Daniel et al. (2012) Fine-mapping diabetes-related traits, including insulin resistance, in heterogeneous stock rats. Physiol Genomics 44:1013-26|