Abstract
Obesity is a complex condition with world-wide exponentially rising prevalence rates, linked with severe diseases like Type 2 Diabetes. Economic and welfare consequences have led to a raised interest in a better understanding of the biological and genetic background. To date, whole genome investigations focusing on single genetic variants have achieved limited success, and the importance of including genetic interactions is becoming evident. Here, the aim was to perform an integrative genomic analysis in an F2 pig resource population that was constructed with an aim to maximize genetic variation of obesity-related phenotypes and genotyped using the 60K SNP chip. Firstly, Genome Wide Association (GWA) analysis was performed on the Obesity Index to locate candidate genomic regions that were further validated using combined Linkage Disequilibrium Linkage Analysis and investigated by evaluation of haplotype blocks. We built Weighted Interaction SNP Hub (WISH) and differentially wired (DW) networks using genotypic correlations amongst obesity-associated SNPs resulting from GWA analysis. GWA results and SNP modules detected by WISH and DW analyses were further investigated by functional enrichment analyses. The functional annotation of SNPs revealed several genes associated with obesity, e.g., NPC2 and OR4D10. Moreover, gene enrichment analyses identified several significantly associated pathways, over and above the GWA study results, that may influence obesity and obesity related diseases, e.g., metabolic processes. WISH networks based on genotypic correlations allowed further identification of various gene ontology terms and pathways related to obesity and related traits, which were not identified by the GWA study. In conclusion, this is the first study to develop a (genetic) obesity index and employ systems genetics in a porcine model to provide important insights into the complex genetic architecture associated with obesity and many biological pathways that underlie it.
Highlights
Obesity, a complex condition characterized by excessive accumulation of body fat, is an exponentially growing public health problem associated with several severe diseases like Type 2 Diabetes, cardiovascular diseases, and various types of cancers (Bener et al, 2005)
OBESITY INDEX The Obesity Index (OI) was constructed according to the selection index theory (Cameron, 1997), whereby nine obesity and obesity-related (OOR) phenotypes are combined into a single value representative of the genetic predisposition to obesity
We demonstrated the potential of network-based systems genetics approaches to reveal biological and genetic background of complex phenotypes that is otherwise not identified via traditional genetics/genomic analyses
Summary
A complex condition characterized by excessive accumulation of body fat, is an exponentially growing public health problem associated with several severe diseases like Type 2 Diabetes, cardiovascular diseases, and various types of cancers (Bener et al, 2005). Animal (model) studies show that weight gain and adiposity are related to genetic differences in eating behavioral patterns (Do et al, 2013), and it has been shown that epigenetics play a critical role (e.g., nutritional status during pregnancy/fetal programming events) in determining effective partitioning of nutrients to maintaining essential physiological functions (Hou et al, 2013; Do et al, 2014). These environmental and epigenetic factors are difficult to manage, and there is substantial interest in gaining more knowledge about the genetic background of obesity. The well-known obesity-related FTO gene interacts with APOE which in turn, is associated with Alzheimer’s disease (Keller et al, 2011) and with MC4R, resulting in a higher chance of breast cancer
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