Identification of a metabolic syndrome transcriptome signature in the LH rat

University Of Iowa, Iowa City IA

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Abstract

DESCRIPTION (provided by applicant): The human metabolic syndrome, an archetypical complex disease (involving multiple genes and environmental interactions), is a collection of disorders including obesity, dyslipidemia, hypertension, and insulin resistance, leading to end organ failure and death. While genetic studies have had success in identifying genes related to obesity, dyslipidemia, and hypertension, much of the variation remains unknown. The Lyon Hypertensive (LH) rat has several features common to the human metabolic syndrome - high body weight, cholesterol, and triglycerides, increased insulin and insulin/glucose ratio, and high blood pressure exacerbated by a high salt diet. The Lyon normotensive (LN) control strain is genetically quite similar to the LH, but phenotypically very distinct. Mapping studies in an F2 intercross between the LH and LN identified quantitative trait loci (QTL) contributing to body weight, lipid levels, blood pressure and insulin levels. However, the genes that underlie the substantial phenotypic differences between the genetically similar LH and LN rats are not yet known. Identification of the genes underlying QTL can be facilitated by comparing transcriptomes of the disease and control models and by identifying positional candidate genes and perturbed biological pathways. While gene expression arrays allow for analyses in disease related tissues, they are limited by the features contained on the array as well as the current state of genome annotation. Of increasing importance in the metabolic syndrome and other complex diseases is the occurrence of alternative pre-mRNA splicing. However, conventional gene expression arrays cannot examine alternative splicing patterns. We hypothesize that the metabolic syndrome in the LH rat is due to a complex gene regulatory network which contributes to changes in gene expression and RNA processing. Because of the inherent complexity in common disease, we assert that deep RNA sequencing of transcriptomes from LH and LN rat strains will lead to the identification of gene(s) and mechanisms involved in the metabolic syndrome in the LH rat. We propose to carry out a high throughput RNA sequencing analysis of gene expression and alternative splicing in tissues collected from LH and LN strains. Specifically we will 1) identify genomewide gene expression differences between genetically similar LH and LN strains in disease-associated tissues;and 2) identify alternative splicing differences between LH and LN strains by ultra deep RNA sequencing. Identification of transcriptome signatures associated with obesity and dyslipidemia in animal models will lead to novel disease genes and pathways, and ultimately a better understanding and treatment of the human metabolic syndrome. PUBLIC HEALTH RELEVANCE: The human metabolic syndrome (obesity, dyslipidemia, hypertension, and insulin resistance) and its related end organ failure affects nearly 25% of the US population and has a major impact on health care costs in the US, estimated at over $30 billion annually. This project will examine genomewide patterns of gene expression and RNA processing in disease-associated tissues collected from a rat model of the human metabolic syndrome. Identification of a metabolic syndrome transcriptome signature in animal models will lead to better understanding and treatment of the human disease.