title: Genetic heterogeneity of within-family variance of body weight in Atlantic salmon (Salmo salar).
abstract: BACKGROUND
  Canalization is defined as the stability of a genotype against minor variations in both environment and genetics. Genetic variation in degree of canalization causes heterogeneity of within-family variance. The aims of this study are twofold: (1) quantify genetic heterogeneity of (within-family) residual variance in Atlantic salmon and (2) test whether the observed heterogeneity of (within-family) residual variance can be explained by simple scaling effects.
  
  
  RESULTS
  Analysis of body weight in Atlantic salmon using a double hierarchical generalized linear model (DHGLM) revealed substantial heterogeneity of within-family variance. The 95% prediction interval for within-family variance ranged from ~0.4 to 1.2 kg2, implying that the within-family variance of the most extreme high families is expected to be approximately three times larger than the extreme low families. For cross-sectional data, DHGLM with an animal mean sub-model resulted in severe bias, while a corresponding sire-dam model was appropriate. Heterogeneity of variance was not sensitive to Box-Cox transformations of phenotypes, which implies that heterogeneity of variance exists beyond what would be expected from simple scaling effects.
  
  
  CONCLUSIONS
  Substantial heterogeneity of within-family variance was found for body weight in Atlantic salmon. A tendency towards higher variance with higher means (scaling effects) was observed, but heterogeneity of within-family variance existed beyond what could be explained by simple scaling effects. For cross-sectional data, using the animal mean sub-model in the DHGLM resulted in biased estimates of variance components, which differed substantially both from a standard linear mean animal model and a sire-dam DHGLM model. Although genetic differences in canalization were observed, selection for increased canalization is difficult, because there is limited individual information for the variance sub-model, especially when based on cross-sectional data. Furthermore, potential macro-environmental changes (diet, climatic region, etc.) may make genetic heterogeneity of variance a less stable trait over time and space.
authors.affiliation: Nofima AS, Post Box 210, Ås 1431, Norway. Anna.Sonesson@nofima.no.
authors.forename: Anna K
authors.initials: AK
authors.lastname: Sonesson
authors.forename: Jørgen
authors.initials: J
authors.lastname: Odegård
authors.forename: Lars
authors.initials: L
authors.lastname: Rönnegård
mesh_terms: D000818:Animals; D017756:Aquaculture; D001835:Body Weight / Q000235:genetics*; D005190:Family; D018740:Genetic Heterogeneity; D014644:Genetic Variation; D005838:Genotype; D016014:Linear Models; D008957:Models, Genetic; D010641:Phenotype; D020317:Salmo salar / Q000033:anatomy & histology / Q000235:genetics*