Genetic characterisation of farmed rainbow trout in Norway: intra- and inter-strain variation reveals potential for identification of escapees

<p>Abstract</p> <p>Background</p> <p>The rainbow trout (<it>Oncorhynchus mykiss</it>) is one of the most important aquaculture species in the world, and Norway is one of the largest producers. The present study was initiated in response to a request from the Norwegian police authority to identify the farm of origin for 35 escaped rainbow trout captured in a fjord. Eleven samples, each consisting of approximately 47 fish, were collected from the three farms operating in the fjord where the escapees were captured. In order to gain a better general understanding of the genetic structure of rainbow trout strains used in Norwegian aquaculture, seven samples (47 fish per sample) were collected from six farms located outside the region where the escapees were captured. All samples, including the escapees, were genotyped with 12 microsatellite loci.</p> <p>Results</p> <p>All samples displayed considerable genetic variability at all loci (mean number of alleles per locus per sample ranged from 5.4–8.6). Variable degrees of genetic differentiation were observed among the samples, with pair-wise <it>F</it>_STvalues ranging from 0–0.127. Self-assignment tests conducted among the samples collected from farms outside the fjord where the escapees were observed gave an overall correct assignment of 82.5%, demonstrating potential for genetic identification of escapees. In the "real life" assignment of the 35 captured escapees, all were excluded from two of the samples included as controls in the analysis, and 26 were excluded from the third control sample. In contrast, only 1 of the escapees was excluded from the 11 pooled samples collected on the 3 farms operating in the fjord.</p> <p>Conclusion</p> <p>Considerable genetic variation exists within and among rainbow trout strains farmed in Norway. Together with modern statistical methods, this will provide commercial operators with a tool to monitor breeding and fish movements, and management authorities with the ability to identify the source of escapees. The data generated in this study were used by the Norwegian police to initiate an investigation of the company operating the three farms in the fjord where escapees were observed.</p

Standing genetic variation and compensatory evolution in transgenic organisms: a growth-enhanced salmon simulation

Genetically modified strains usually are generated within defined genetic backgrounds to minimize variation for the engineered characteristic in order to facilitate basic research investigations or for commercial application. However, interactions between transgenes and genetic background have been documented in both model and commercial agricultural species, indicating that allelic variation at transgene-modifying loci are not uncommon in genomes. Engineered organisms that have the potential to allow entry of transgenes into natural populations may cause changes to ecosystems via the interaction of their specific phenotypes with ecosystem components and services. A transgene introgressing through natural populations is likely to encounter a range of natural genetic variation (among individuals or sub-populations) that could result in changes in phenotype, concomitant with effects on fitness and ecosystem consequences that differ from that seen in the progenitor transgenic strain. In the present study, using a growth hormone transgenic salmon example, we have modeled selection of modifier loci (single and multiple) in the presence of a transgene and have found that accounting for genetic background can significantly affect the persistence of transgenes in populations, potentially reducing or reversing a “Trojan gene” effect. Influences from altered life history characteristics (e.g., developmental timing, age of maturation) and compensatory demographic/ecosystem controls (e.g., density dependence) also were found to have a strong influence on transgene effects. Further, with the presence of a transgene in a population, genetic backgrounds were found to shift in non-transgenic individuals as well, an effect expected to direct phenotypes away from naturally selected optima. The present model has revealed the importance of understanding effects of selection for background genetics on the evolution of phenotypes in populations harbouring transgenes