Population size and the limits of natural selection

进化生物学家主要关注理解和预测种群如何随时间变化。广泛的种群特征和过程可以影响进化反应，包括遗传、环境变化和迁移。根据这一建议，我们将研究种群大小对进化速度和方向的影响：种群大小在决定变异（即突变）输入到种群中以及突变产生后的命运方面至关重要。我们将检验关于种群规模对进化速度和模式的影响的重要预测。理论预测，小群体的进化应该比大群体的进化导致更多不同的结果。此外，在大种群中，个体之间的遗传交换预计会提高适应的速度。我们将在实验室中通过实验进化大肠杆菌种群来测试这些预测。在这些实验中使用细菌将使我们能够直接控制种群规模，并跟踪许多复制种群的进化。我们将能够通过测量进化种群的适应度和测序它们的基因组来追踪进化，从而确定进化的遗传基础。对已测序的细菌基因组进行计算分析，将使我们能够检验更多的理论预测。基因组中基因交换水平低的区域比基因交换水平高的区域有更少的遗传变异。这一预测此前已经在动物身上进行过测试，但没有在细菌身上进行过测试。我们提出的工作将解决我们对种群大小和进化过程之间关系的理解中的关键空白。除了与进化理论的相关性之外，我们的工作还可以为人口统计学过程被认为是重要的其他进化情景提供信息，例如病原体进化、疾病传播和范围边缘进化。

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.