1 Animal Genetics, Bioinformatics and Breeding, Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, Københavns Universitet2 IKVH Animal Genetics, Bioinformatics, and breeding, Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, Københavns Universitet3 Animal Genetics, Bioinformatics and Breeding, Department of Veterinary Clinical and Animal Sciences, Faculty of Health and Medical Sciences, Københavns Universitet
design and genetic parameters
Obesity is a rising worldwide public health problem. Difficulties to precisely measure various obesity traits and the genetic heterogeneity in human have been major impediments to completely disentangle genetic factors causing obesity. The pig is a relevant model for studying human obesity and obesity-related (OOR) traits. Using founder breeds divergent with respect to obesity traits we have created an F2 pig resource population (454 pigs), which has been intensively phenotyped for 36 OOR traits. The main rationale for our study is to characterize the genetic architecture of OOR traits in the F2 pig design, by estimating heritabilities, genetic and phenotypic correlations using mixed- and multi-trait BLUP animal models. Our analyses revealed high coefficients of variation (15-42 per cent) and moderate to high heritabilities (0.22 - 0.81) in fatness traits, showing large phenotypic and genetic variation in the F2 population, respectively. This fulfills the purpose of creating a resource population divergent for OOR traits. Strong genetic correlations were found between weight and lean mass at dual energy x-ray absorptiometry (DXA) scanning (0.56 – 0.97). Weight and conformation also showed strong genetic correlations with slaughter traits (e.g. rg between abdominal circumference and leaf fat at slaughtering: 0.66). Genetic correlations between fat-related traits and the glucose level vary between 0.35 and 0.74 and show a strong correlation between adipose tissue and impaired glucose metabolism. Our power calculations showed a minimum of 80% power for QTL detection for all phenotypes. We revealed genetic correlations at population level, for the first time, for several difficult to measure and novel OOR traits and diseases. The results underpin the potential of the established F2 pig resource population for further genomic, systems genetics and functional investigations to unravel the genetic background of OOR traits.