Single-gene Effects on Body Weight in Selected and Unselected Mouse Lines Detected by Bayesian Marker-free Segregation Analysis

Published in the Scandinavian Journal of Laboratory Animal Science an international journal of laboratory animal science Introduction Over the last decades, a number of single genes with considerable effects on production and reproduction traits have been identified in livestock and laboratory animals. Mice were often proposed as model animals for human and livestock obesity as well as other characters. Specially created mouse lines (selected inbred, single mutant, congenic, chromosome substitution, transgenic etc.) give a unique opportunity to understand the physiological pathways and genetic background of weight. In some mouse lines mutations with a large effect on body weight were found: Leptin (Zhang et al., 2004), Leptin receptor (Tartaglia et al., 1995), Myostatin (Szabó et al., 1998) and also many QTL studies were performed (Brockmann & Bevova, 2002). However, it should be stressed that the effects are often population specific, and even large effects of single genes may not be seen in other populations. The costs of molecular analysis limit population size, which reduces the power of QTL detection. Some methods like selective DNA pooling were developed to reduce the number of genotypings (Darvasi & Soller, 1994). On the other hand marker-free segregation analysis introduced by Elston & Steward (1971) and developed by Morton & MacLean (1974) can indicate the presence or absence of major genes segregating within the population, based on performance records of a pedigree population. For large populations with complex pedigree structure, a Gibbs sampling algorithm was proposed by Guo & Thompson (1994) and Janss et al. (1995). This approach allows an estimation of genotype effects and allele frequencies. The Gibbs sampling algorithm has many advantages (Van Tassel et al., 1995). Segregation analysis was suggested to be the most powerful statistical method to identify a single gene when DNA marker information is unavailable (Ilahi & Kadarmideen, 2004). The method was successfully applied for studies of the genetic background Single-gene Effects on Body Weight in Selected and Unselected Mouse Lines Detected by Bayesian Marker-free Segregation Analysis