Natural selection has been a cornerstone of evolutionary theory ever since Darwin. Yet mathematical models of natural selection have often been dogged by an awkward problem that seemed to make evolution harder than biologists understood it to be. In a new paper appearing in Communications Biology, a multidisciplinary team of scientists in Austria and the United States identify a possible way out of the conundrum. Their answer still needs to be checked against what happens in nature, but in any case, it could be useful for biotechnology researchers and others who need to promote natural selection under artificial circumstances.
A central premise of the theory of evolution through natural selection is that when beneficial mutations appear, they should spread throughout a population. But this outcome isn’t guaranteed. Random accidents, illnesses and other misfortunes can easily erase mutations when they are new and rare — and it’s statistically likely that they often will.
Mutations should theoretically face better odds of survival in some situations than others, however. Picture a huge population of organisms all living together on one island, for example. A mutation might get permanently lost in the crowd unless its advantage is great. Yet if a few individuals regularly migrate to their own islands to breed, then a modestly helpful mutation might have a better chance of establishing a foothold and spreading back to the main population. (Then again, it might not — the outcome would depend entirely on the precise details of the scenario.) Biologists study these population structures to understand how genes flow.
