Population size and the limits of natural selection

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Evolutionary biologists are centrally concerned with understanding and predicting how populations change over time. A wide range of population features and processes can influence evolutionary responses, including genetics, environmental variation, and migration. Under this proposal, we will investigate the influence of population size on the speed and direction of evolution: population size is crucial in determining both the input of variation (that is, mutations) into a population, and in the fate of mutations once they have arisen.We will test important predictions concerning the influence of population size on rates and patterns of evolution. Theory predicts that evolution in small populations should lead to more varied outcomes than in large populations. Moreover, in large populations, genetic exchange between individuals is expected to increase the rate of adaptation. We will test these predictions by experimentally evolving populations of the bacterium Escherichia coli in the laboratory. Use of bacteria for these experiments will allow us to directly control population size and to follow evolution in many replicate populations. We will be able to track evolution both by measuring fitness of the evolved populations, and by sequencing their genomes so as to identify the genetic basis of evolution. Computational analyses of sequenced bacterial genomes will allow us to test additional theoretical predictions. Regions of the genome with low levels of genetic exchange are expected to harbor less genetic variation than regions with high levels of exchange. This prediction has previously been tested in animals, but not in bacteria. Our proposed work will address key gaps in our understanding of the relationship between population size and the evolutionary process. Beyond its relevance to evolutionary theory, our work can inform other evolutionary scenarios where demographic processes are thought to be important, such as pathogen evolution, disease transmission and evolution at range margins.