Untangling the positive genetic correlation between rainbow trout growth and survival.

Explanations for positive and negative genetic correlations between growth and fitness traits are essential for life-history theory and selective breeding. Here, we test whether growth and survival display genetic trade-off. Furthermore, we assess the potential of third-party traits to explain observed genetic associations. First, we estimated genetic correlations of growth and survival of rainbow trout. We then explored whether these associations are explained by genetic correlations with health, body composition and maturity traits. Analysis included 14 traits across life stages and environments. Data were recorded from 249 166 individuals belonging to 10 year classes of a pedigreed population. The results revealed that rapid growth during grow-out was genetically associated with enhanced survival (mean r(G) = 0.17). This resulted because genotypes with less nematode caused cataract grew faster and were more likely to survive. Fingerling survival was not genetically related to weight or to grow-out survival. Instead, rapid fingerling growth made fish prone to deformations (r(G) = 0.18). Evolutionary genetics provides a theoretical framework to study variation in genetic correlations. This study demonstrates that genetic correlation patterns of growth and survival can be explained by a set of key explanatory traits recorded at different life stages and that these traits can be simultaneously improved by selective breeding.

Genetic architecture of rainbow trout survival from egg to adult.

Survival from birth to a reproductive adult is a challenge that only robust individuals resistant to a variety of mortality factors will overcome. To assess whether survival traits share genetic architecture throughout the life cycle, we estimated genetic correlations for survival within fingerling stage, and across egg, fingerling and grow-out stages in farmed rainbow trout. Genetic parameters of survival at three life cycle stages were estimated for 249 166 individuals originating from ten year classes of a pedigreed population. Despite being an important fitness component, survival traits harboured significant but modest amount of genetic variation (h2=0.07-0.27). Weak associations between survival during egg-fry and fingerling periods, between early and late fingerling periods (rG=0.30) and generally low genetic correlations between fingerling and grow-out survival (mean rG=0.06) suggested that life-stage specific survival traits are best regarded as separate traits. However, in the sub-set of data with detailed time of death records, positive genetic correlations between early and late fingerling survival (rG=0.89) showed that during certain years the best genotypes in the early period were also among the best in the late period. That survival across fingerling period can be genetically the same, trait was indicated also by only slightly higher heritability (h2=0.15) estimated with the survival analysis of time to death during fingerling period compared to the analysis treating fingerling survival as a binary character (h2=0.11). The results imply that (1) inherited resistance against unknown mortality factors exists, but (2) ranking of genotypes changes across life stages.

Survival of the currently fittest: genetics of rainbow trout survival across time and space.

As a fitness trait, survival is assumed to exhibit low heritability due to strong selection eroding genetic variation and/or spatio-temporal variation in mortality agents reducing genetic and increasing residual variation. The latter phenomenon in particular may contribute to low heritability in multigeneration data, even if certain cohorts exhibit significant genetic variation. Analysis of survival data from 10 year classes of rainbow trout reared at three test stations showed that treating survival as a single trait across all generations resulted in low heritability (h2 = 0.08-0.17). However, when heritabilities were estimated from homogeneous generation and test station-specific cohorts, a wide range of heritability values was revealed (h2 = 0.04-0.71). Of 64 genetic correlations between different cohorts, 20 were positive, but 16 were significantly negative, confirming that genetic architecture of survival is not stable across generations and environments. These results reveal the existence of hidden genetic variation for survival and demonstrate that treating survival as one trait over several generations may not reveal its true genetic architecture. Negative genetic correlations between cohorts indicate that overall survival has limited potential to predict general resistance, and care should be taken when using it as selection criterion.

Changes in the expression of genetic characteristics across cohorts in skeletal deformations of farmed salmonids.

Genetic analysis of disorder incidence in farmed animals is challenged by two factors. Disorders in different cohorts and environments could be caused by different factors, leading to changes in heritability and to less than unity genetic correlations across cohorts. Moreover, due to computational limitations, liability scale heritabilities at very low incidence may differ from those estimated at higher incidence. We tested whether these two dilemmas occur in skeletal deformations of farmed salmonids using multigeneration data from the Finnish rainbow trout breeding programme and previous salmonid studies. The results showed that heritability was close to zero in cohorts in which management practices maintained incidence at a low level. When there was a management failure and incidence was unusually high, heritability was elevated. This may be due to computational limitations at very low incidence and/or because deformations are induced by different factors in different cohorts. Most genetic correlations between deformations recorded in different generations were weakly to strongly positive. However, also negative correlations between generations were present, showing that high liability at one time can be genetically connected to low liability at another time. The results emphasise that genetic architecture of binary traits can be influenced by trait expression.