There is considerable evidence that steelhead reared in hatcheries differ from wild fish in phenotypic traits related to fitness. Genetic selection is often implicated as the underlying cause of these phenotypes, however, environmental conditions experienced during early life can also have long-term effects on fitness related traits. This form of developmental plasticity may be mediated by epigenetic mechanisms such as DNA methylation. We tested whether hatchery-rearing conditions can influence patterns of DNA methylation in steelhead with known genetic backgrounds, and assessed the stability of these changes over time.
In this study, e yed-embryos from 22 O. mykiss families were split across traditional hatchery tanks or a simulated stream-rearing environment for 8 months followed by a second year in a common hatchery tank environment. DNA methylation patterns were examined in the liver of juveniles at two time points: after 8 months of rearing in either a tank or stream environment and after a subsequent year of rearing in a common tank environment. Further, DNA methylation was analyzed in the sperm of mature males to assess the potential of environmentally-induced changes to be passed to offspring.
We found that hepatic DNA methylation changes in response to hatchery versus stream-rearing in yearling fish were substantial, but few persisted after a second year in a tank environment. However, the early rearing environment appeared to affect how fish responded to developmental and environmental signals that shaped the liver methylome, as novel DNA methylation differences were identified after a year of common rearing. Furthermore, we found profound differences in DNA methylation due to age, irrespective of rearing treatment. Although few rearing-treatment effects were observed in the sperm methylome, strong family effects were observed. These data suggest limited potential for intergenerational changes, but highlight the importance of understanding the effects of kinship among studied individuals in order to properly interpret DNA methylation data in natural populations.