Genomic signatures of primate-pathogen interactions

项目总结 种群基因组数据携带着进化历史的详细记录，但这一记录同时 受到多种进化力量的影响，使得解释极具挑战性。方法开发 大规模基因组数据集的可及性不断提高，导致了更强大的战略 理清自然选择的影响，找出最近适应的基因座。然而，我们仍然缺乏 了解适应过程的许多方面，包括遗传变异的类型(例如，点 突变与结构变异)、基因座数量和发生的选择性机制。在接下来的五年里 多年来，莱弗勒实验室的研究旨在通过开发新的方法和 在人类和非人类灵长类动物中研究最近病原体驱动的选择压力下的基因座的数据集。 病原体对宿主的健康和生存有严重的影响，因此是 进化变化和学习选择性过程的有效模型系统。我们将联合起来 在计算、种群和进化基因组学中探索一系列签名的方法- 病原体的相互作用留在我们的基因组中，组织在三个项目领域。首先，我们将描述 阿拉伯半岛的种群基因组变异，开发一种新的基于序列的方法来识别 与传染病相关的适应性基因流动后混合和浓缩测试，特别是聚焦 关于血型变异。第二，我们将分析平行基因簇中的拷贝数变异， 开发新的方法来推断拷贝数和选择，以测试它们是否可能 病原体驱动选择的常见靶标。最后，我们将研究野生动物的进化基因组学 东南亚的猕猴。我们将通过比较等位基因来评估病原体驱动选择的证据。 不同病原体负荷和不同程度混合的人群中的频率 生活在没有这些病原体的近亲物种中。总之，这些研究项目的结果将 提供新的工具、数据集和对宿主-病原体共同进化的影响的重要洞察 种群、基因家族和灵长类物种。

PROJECT SUMMARY Population genomic data carry a detailed record of evolutionary history, but this record is simultaneously impacted by multiple evolutionary forces making interpretation extremely challenging. Methods development and increasing accessibility of large-scale genomic datasets have led to more powerful strategies to disentangle the effects of natural selection and identify loci underlying recent adaptation. Yet we still lack understanding of many aspects of adaptive processes, including the types of genetic variation (e.g., point mutations vs. structural variants), numbers of loci, and selective regimes by which it occurs. Over the next five years, research in the Leffler lab aims to probe the genetics of adaptation by developing new approaches and datasets to study loci under recent pathogen-driven selective pressures in humans and non-human primates. Pathogens have a severe impact on host fitness and survival and consequently are a driving force for evolutionary change and an effective model system for learning about selective processes. We will combine approaches in computational, population and evolutionary genomics to explore a range of signatures that host- pathogen interactions leave in our genomes, organized in three project areas. First, we will characterize population genomic variation in the Arabian Peninsula, developing a new sequence-based approach to identify adaptive gene flow post-admixture and test for enrichment related to infectious disease, particularly focusing on blood group variation. Second, we will analyze copy number variation in paralogous gene clusters, developing new methods for inference of both copy number and selection, in order to test whether they may be frequent targets of pathogen-driven selection. Finally, we will investigate evolutionary genomics of wild macaques in southeast Asia. We will assess evidence for pathogen-driven selection by comparing allele frequencies in populations with a range of pathogen burdens and different levels of admixture with closely related species living in the absence of these pathogens. Together, the results of these research projects will provide new tools, datasets, and significant insight into the impact of host-pathogen co-evolution across populations, gene families, and primate species.