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Dataset Information

An integrative systems genetics approach reveals potential causal genes and pathways related to obesity.


ABSTRACT:

Background

Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach.

Methods

Using a selective gene expression profiling approach, we selected 36

SUBMITTER: Kogelman LJ 

PROVIDER: S-EPMC4617184 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature