Mutants with heterozygote disadvantage can prevent spread of transgenic animals

Genetically modified organisms must not be allowed to spread uncontrollably. Scientists are therefore keen to take advantage of a mechanism that will localise the spread of mutants. Mutants with a heterozygote disadvantage, as it is known, reduce the evolutionary fitness of their carriers to varying degrees if they are only available to one gene copy (heterozygote) or exist in both gene copies (homozygote). In their study, the Max Planck scientists assumed a fitness loss of 50 percent (compared to wildtypes) for mutant heterozygotes and a 10 percent fitness loss for mutant homozygotes.

A mutant with a heterozygote disadvantage can be maintained in a population if it occurs frequently enough for sufficient homozygote offspring to be produced. Above this value, it can suppress the non-mutated gene variant completely and the mutated form becomes extinct. Populations containing mutants with heterozygote disadvantage develop into one of two stable states. These mutant types therefore seem to be well-suited for the safe release of genetically modified organisms. After all, as soon as sufficient numbers of mutants exist in the environment, these replace the natural variant in a local population. If such genes are joined to resistance genes to combat pathogens, mosquito populations could be rendered resistant to Malaria, for example. By releasing the wildtype at a later stage, the transgenic animals can therefore also be removed again more easily from the environment. In population genetics this is known as underdominance.

The researchers then analyzed computer-based simulations showing the effect of mutants with heterozygote disadvantage on two populations of equal size, which, as in nature, are subject to statistical fluctuations. In doing so, they paid particular attention to the gene flow arising from the mobility of the individuals. At times, such a mutation can survive in a stable state in a population. However, this only happens if the migration rate is less than 5 percent. "Our calculations have also shown that mutants are best released into both populations even if the goal is to establish the new genetic variant in only one of them in the long term. If, for example, 75 percent of transgenic animals are distributed to the target population and the remaining 25 percent to a neighbouring population, the transgenic individuals may find it easier to gain traction on a long-term basis in the target population," explains Philipp Altrock from the Max Planck Institute for Evolutionary Biology.

Scientists in the USA, Brazil, Malaysia and the Cayman Islands have been conducting field experiments on the use of genetically modified animals for several years. These include, for example, experiments involving genetically modified mosquitoes, to protect against infectious diseases such as malaria or dengue fever, and transgenic plant pests. Similar experiments are planned in another nine countries. To date, the males from various insect species, which are generally infertile, are released. In this way, the effective size of the wild population is limited. "One of the disadvantages of this method is that it needs to be repeated very frequently as the transgenic animals cannot reproduce," says Arne Traulsen from the Max Planck Institute in Plön. In addition, in the case of mosquitoes, a few parent individuals can already have a large share of the next generation.

In contrast, mutants with heterozygote disadvantage can survive for many generations. Resistance genes linked to such mutants would therefore be more efficient. The safety aspect also increases, as proliferation across a target population is very unlikely. "Nevertheless, the fitness of the transgenic animals, the population sizes, and the migration rates must be known. These factors can most likely be determined for release experiments on maritime islands," says Arne Traulsen.

More information: Altrock PM, Traulsen A, Reed FA, 2011, Stability Properties of Underdominance in Finite Subdivided Populations. PLoS Comput Biol 7(11): e1002260. doi:10.1371/journal.pcbi.1002260

Provided by Max-Planck-Gesellschaft