Genomic signatures of primate-pathogen interactions

灵长类动物-病原体相互作用的基因组特征

• 批准号: 10701007
• 负责人: Ellen Leffler
• 金额: $ 38.5万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-09 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10701007
• 关键词: Admixture; Area; Base Sequence; Biological Models; Blood typing procedure; Communicable Diseases; Copy Number Polymorphism; Data Set; Gene Cluster; Gene Family; Gene Frequency; Genes; Genetic; Genetic Variation; Genome; Genomics; Human; Individual; Learning; Macaca; Methods; Natural Selections; Pattern; Phenotype; Point Mutation; Population; Primates; Process; Recording of previous events; Research; Research Project Grants; Southeastern Asia; Study models; Testing; Variant; Work; blood group; driving force; fitness; genomic data; genomic signature; genomic variation; host-pathogen coevolution; insight; method development; nonhuman primate; novel strategies; paralogous gene; pathogen; pressure; tool

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.

项目摘要 种群基因组数据承载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访问性越来越高，这导致了更强大的策略， 解开自然选择的影响，并确定最近适应的基因位点。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 突变与结构变体）、基因座的数量以及其发生的选择性机制。在未来五 多年来，莱弗勒实验室的研究旨在通过开发新的方法来探索适应的遗传学， 数据集来研究人类和非人类灵长类动物中最近病原体驱动的选择压力下的基因座。 病原体对宿主的适应性和存活具有严重影响，因此是宿主死亡的驱动力。 进化的变化和有效的模型系统学习选择过程。我们将联合收割机 在计算，人口和进化基因组学的方法，探索一系列的签名，主机- 病原体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 阿拉伯半岛的群体基因组变异，开发一种新的基于序列的方法来识别 适应性基因流后混合和测试富集有关的传染病，特别是集中 血型变异的研究其次，我们将分析旁系同源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是 病原体驱动选择的常见目标。最后，我们将研究野生的进化基因组学， 东南亚的猕猴。我们将通过比较等位基因， 在具有一系列病原体负荷和不同水平的混合物的人群中， 在没有这些病原体的情况下生活的相关物种。这些研究项目的结果将 提供新的工具，数据集，并对宿主-病原体共同进化的影响有重要的见解， 种群、基因家族和灵长类物种。