Dynamics of Gene Drives in Natural Populations

项目总结/摘要 蚊子传播的疾病，包括疟疾、登革热和寨卡病毒，继续造成毁灭性的损失。基因 驱动系统可以提供一种新的策略，通过传播基因工程来控制这些疾病， 将等位基因引入载体群体，例如使昆虫对病原体具有抗性的等位基因变体，或 有害的等位基因而不是直接抑制它们的种群。 最近开发的CRISPR/Cas9归巢基因驱动系统有望成为一种高度适应性的基因驱动系统。 通过将驱动构建体的杂合子转化为纯合子而起作用的机制。但 目前尚不清楚这种机制是否会在野生种群中起作用，因为预期的高发病率 产生抗性等位基因，当切割被修复时由驱动机制本身产生， 非同源末端连接另一个被提出的基因驱动系统，美狄亚，可能受到较少的影响， 产生抗性等位基因，但它传播得更慢，对适应性成本高度敏感。的目标 我们的项目是确定和量化参数，这些参数对确定这些系统是否可以在 在不同的自然种群中传播。 在我们的第一个目标中，我们将采用归航驱动程序和美狄亚驱动程序的实验室示例来量化驱动程序 在遗传多样但特征良好的品系中， 模式生物黑腹果蝇然后，我们将使用这些结果来绘制相关的遗传位点， 具有驱动效率和阻力水平的差异。 我们的第二个目标是确定每个基因驱动系统入侵遗传多样性种群的能力。 为此，将少量基因驱动果蝇引入种群笼中， 全球多样性线飞行。将在几代人中跟踪表型频率，以确定 基因驱动成功入侵种群的能力。这项工作将在最先进的 节肢动物收容实验室，以防止转基因昆虫逃跑。 在我们的第三个目标中，我们将比较归航司机和美狄亚司机在地理上传播的能力。 使用复杂的群体遗传模拟来构建群体。我们将确定参数， 将允许基因驱动系统建立，传播，并在大型自然环境中固定或持续足够长的时间 根据人口统计学和人口结构的现实假设。 总的来说，我们的实验和建模将为预测基因驱动的动力学提供关键数据 在自然目标人群中。本文的研究结论将对设计具有重要意义的 并实施下一代基因驱动系统，以在现实人群中实现最佳性能。

Project Summary/Abstract Mosquito-transmitted diseases, including malaria, dengue and Zika, continue to take a devastating toll. Gene drive systems could provide a new strategy for controlling these diseases by spreading genetically engineered alleles into vector populations, such as allelic variants that make the insects resistant to a pathogen or deleterious alleles than directly suppress their populations. The recently developed CRISPR/Cas9 homing gene drive system promises to be a highly adaptable mechanism that works by converting heterozygotes for the driver construct into homozygotes. However, it remains unclear whether this mechanism will work in wild populations given the expected high rate of generation of resistance alleles, which are created by the drive mechanism itself when cleavage is repaired by nonhomologous end joining. Another proposed gene drive system, Medea, likely suffers less from the generation of resistance alleles, but it spreads more slowly and is highly sensitive to fitness costs. The goal of our project is to identify and quantify parameters that are critical to determining whether these systems can in fact spread in diverse, natural populations. In our first aim, we will employ laboratory examples of homing drivers and Medea drivers to quantify the drive efficiency and origination rate of resistance alleles in genetically diverse but well characterized lines of the model organism Drosophila melanogaster. We will then use these results to map the genetic loci associated with differences in drive efficiency and resistance levels. Our second aim will determine the ability of each gene drive system to invade genetically diverse populations. For this purpose, a small number of gene drive flies will be introduced into population cages with a mix of Global Diversity Line flies. Phenotype frequencies will be tracked over several generations to determine the ability of the gene drive to successfully invade the population. This work will be done in a state-of-the-art arthropod containment lab to prevent escape of transgenic insects. In our third aim, we will compare the ability of homing drivers and Medea drivers to spread in geographically structured populations using sophisticated population genetic simulations. We will identify the parameters that will allow a gene drive system to establish, spread, and either fix or persist sufficiently long in a large natural population under realistic assumptions of demography and population structure. Overall our experiments and modeling will provide crucial data for predicting the dynamics of gene drive systems in natural target populations. The conclusions from our studies will play an important role in designing and implementing the next generation of gene drive systems for optimal performance in realistic populations.