Geographic models of selective sweeps

描述（由申请人提供）：进化基本上是一个空间过程，种群在当地杂交并适应环境。这对我们如何理解种群内遗传多样性的模式有着深远的影响，特别是当我们开始从种群中获得大量的遗传数据时。这些过程的良好模型和预测对于理解我们所看到的模式是必要的，例如，通过允许我们识别适应特征的基因座，并将局部适应与其他过程区分开来。我将创建和研究地理上明确的选择模型，包括平行选择扫描（“软”扫描），中性变异与选定等位基因的“搭便车”，以及新描述的等位基因“冲浪”现象；并将在人口基因组学数据集中分析他们的预期特征。这将开始填补现有种群遗传学理论的一个主要空白，该理论中明确的空间模型相对较少，包含选择的模型更少。这些工具不仅使我们能够更好地重建地理分布物种（如人类）的适应历史，而且还将帮助我们更精确地识别响应选择压力的基因组位点，从而找到与疾病反应和对当地条件的生理适应有关的位点。我将建立在现有的理论基础上，包括群体遗传学、概率论、生态学和统计物理学，并与实证研究人员的目标和问题密切对话。

DESCRIPTION (provided by applicant): Evolution is fundamentally a spatial process, as populations interbreed locally and adapt to their environments. This has profound implications for how we understand patterns of genetic diversity within populations, especially as we begin to obtain large amounts of genetic data from populations. Good models and predictions of these processes will be necessary to understand the pat- terns we see, for instance, by allowing us to identify loci underlying adaptive traits, and to distinguish local adaptation from other processes. I will create and study geographically explicit models of selection, incorporating parallel selective sweeps ("soft" sweeps), the "hitchhiking" of neutral variation along with a selected allele, and the newly-described phenomenon of allele "surfing"; and will analyze their expected signatures in population genomics datasets. This will begin to fill a major gap in existing population genetics theory, which has relatively few explicit spatial models, and even fewer that incorporate selection. Such tools will not only allow us to better reconstruct the history of adaptation in geographically distributed species such as our own, but will also help us to more precisely identify genomic loci responding to selection pressures, and so find loci involved in disease response and in physiological adaptation to local conditions. I will do this by building on existing theory from population genetics, probability, ecology, and statistical physics, in close conversation with the goals and problems of empirical researchers.