Evolution is exciting, you never know exactly what the result will be. Over time, mutations resulting in improved fitness have a good chance of surviving in a population. Mutations which decrease fitness, on the other hand, are much less likely to influence the development of the species. But there are no safe bets, even for beneficial mutations.
Researchers from Wageningen and Cologne wanted to know whether the course of evolution could be predicted. Could for example, the emergence of giraffes with long next been predicted? There are two ways to analyze the predictability of evolution. It can be done by using computer models or by research in nature or in a laboratory. In the laboratory, the predictability of evolution can be examined by monitoring how often fast-evolving microorganisms evolve along the same route. The more often the route and end result are the same, the more the predictable evolution.
Combining laboratories and computer models
The researchers combined genetic information from a fungus with computer models which simulate the course of evolution. They concluded that, while evolution in small populations is known to be unpredictable, this is also the case for very large populations. There is an optimal population size for predicting evolutionary outcomes in every situation.
The Wageningen group used its laboratory to provide knowledge about the fitness profile of a fungus. All 256 possible combinations of eight mutations in the DNA of the fungus were charted. The scientists calculated the effect on the growth of the fungus for each combination of mutations. The growth rate is an important component of the fitness of the fungus. Mutations with a positive effect on growth rates therefore have a greater chance of remaining definitively established after a large number of new generations.
Harder to predict in large populations
In small populations, it is likely that each positive mutation that occurs accidentally will ultimately contribute to the evolution of the organism. The larger the population, the more positive mutations will arise, and the greater the chance will be that the best possible positive mutation is among them. And, as individuals with this mutation will be the fittest, it will repeatedly win the competition and contribute to evolution when the experiment is repeated. This means that, the larger a population, the more predictable its evolution should become. But this turns out to not quite be the case.
The German group processed the fitness data regarding the mutations of the mold in a computer. They discovered that the evolutionary outcome is actually more difficult to predict in very large populations. This phenomenon is caused by the fact that they contain more individuals with not one but two or more mutations. Since the number of beneficial mutation combinations is much higher than the number of favorable mutations themselves, however, the predictability of evolution again declines in very large populations. In other words, evolution can be most easily predicted for populations that are not too small and not too big.
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