The dog (Canis lupus familiaris) is an important companion species and animal model in biomedical studies. Obesity is an increasing problem in dogs. Because obesity decreases life span and is related to several other diseases, we need to understand the causes of obesity for prevention and treatment. Obesity is a polygenic disease; however, most risk variants remain unknown. We hypothesize that some of copy number variations (CNVs) and other DNA variants contribute to obesity. The primary goal of this study is to search for CNVs and other variants associated with obesity in dogs, using whole genome sequencing (WGS) in groups of obese and control dogs. Secondary goals are: a description of the structure of genetic variability of dog genome, a comparison of CNVs in human and dog genomes, an improvement of bioinformatic methods for CNV detection from WGS data.

We use WGS to sequence DNA from obese (Labrador N=25) and control (Labrador N=25) dogs in order to detect CNVs and other variants that are associated with obesity, and to describe structure of genome variability. Selected CNVs will be genotyped with the droplet digital PCR (ddPCR) to validate detected CNVs and also to improve the bioinformatics methods of CNV detection from WGS data. Selected associations will be validated in a sample of random Labrador dogs (N=180) with the use of ddPCR and Sanger sequencing. Using advanced statistical models we will assess the prediction accuracy for obesity from molecular data. Using known and novel CNVs we will compare CNVs in human and dog genotypes.