Biotechnology Risk Assessment
Because transgenic technology offers potential economic benefits associated with production of agronomic species, such as insect or herbicide resistance in plants or enhanced growth and production in animals, there is tremendous pressure to introduce new transgenic organisms into agriculture. However, anthropogenic introduction of exotic organisms into natural communities is a major concern of ecologists because exotics could adversely affect communities in many ways including eliminating populations of species including wild type conspecifics of the transgenic organism. Since the advent of genetic engineering, release of transgenic organisms into natural environments poses additional ecological risks because transgenic individuals retain most of the characteristics of their wild type counterparts while possessing some novel advantage. To evaluate environmental risks of transgenic organisms, regulatory agencies need methods to access risk before release, because once released, the impact may be permanent and irreversible. The objective of our research was to develop a mathematical model, based on population genetic theory that would allow such risks to be determined from parameters measured in a secure laboratory setting. To access risk, it is necessary to examine the transgene’s impact on all aspects the life cycle. We divided the mechanisms by which the frequency of a transgene in a population could be altered into five selection components: viability (differential ability of genotypes to survive to sexual maturity and beyond), fecundity (reproductive capacity of adult females), fertility (sperm production and sperm viability of adult males), developmental rate (early growth rate and age at sexual maturity) and sexual selection (differential ability to attract or compete for mates). We developed a general model to predict changes in population number and gene frequency incorporating all five selection components. We developed and tested an experimental design to estimate these selection components in wild type and transgenic individuals using Japanese medaka (Oryzias latipes), a small cyprinodont fish, as a model organism. One-cell medaka zygotes were microinjected with a construct containing the human growth hormone gene (hGH) driven by the Atlantic salmon growth hormone (sGH) promoter. Our experiments showed that transgenic young had a reduced early viability relative to wild type (30%); however, surviving transgenic hatchlings grew at a faster rate (20%) than wild type until about the age of sexual maturity, and adult transgenic females produced more eggs (20%) in each clutch than did wild type females. Developmental advantages resulted in reduced cannibalism on young and a decreased generation interval; enhanced fecundity resulted in increased offspring production. With respect to mating behavior, laboratory experiments were conducted using natural body size variation of same-aged wild type fish. Large males obtained a four-fold advantage in mating success relative to small males. The mating advantage occurred because large males were preferred as mates by females and because large males could control access to sexually receptive females better than small males could. In general, our model showed that a transgene can increase in a population in several ways. Results also showed that the interaction of fitness component effects could offset each other. Relative to risk, the model showed that if sexual selection favors transgenic fish, while viability selection favors non-transgenic fish, a potentially dangerous situation can develop whereby the transgene is driven into the population by male mating advantages, but average fitness of the population decreases and causes population extinction. Results of our study show which parameters are critical for risk assessment and which characteristics need to be measured in commercial programs before any release is attempted. Some combinations of fitness components have a high potential to increase risk.
|
|
Research Areas
Links to related info
|
William Muir, Ph.D.
|
