Characterizing Human-Pathogen Interactions and Natural Selection with Ancient DNA

利用古代 DNA 表征人类与病原体的相互作用和自然选择

• 批准号: 10276190
• 负责人: Carlos Eduardo Guerra Amorim
• 金额: $ 35.25万
• 依托单位: CALIFORNIA STATE UNIVERSITY NORTHRIDGE
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-09 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10276190
• 关键词: Archaeology; Bubonic Plague; Communicable Diseases; DNA; Data; Data Analyses; Data Set; Detection; Development; Disease Outbreaks; Epidemic; European; Event; Evolution; Future; Gene Frequency; Genetic; Genetic Variation; Genome; Goals; Health Policy; Human; Human Genetics; Human Genome; Indigenous; Knowledge; Light; Methods; Modeling; Modernization; Molecular; Mutation; Native Americans; Natural Selections; Plague; Population; Positioning Attribute; Process; Public Health; Recording of previous events; Research Proposals; Resources; Sample Size; Sampling; Series; Site; South America; Specimen; Statistical Methods; Technology; Time; base; combat; experience; fitness; genetic signature; genomic data; host-pathogen coevolution; human pathogen; improved; novel; pathogen; response; statistics; therapeutic target; time use

PROJECT SUMMARY The possibility of recovering ancient DNA (aDNA) molecules from archeological samples has yielded great opportunities for the study of human evolution and history. Compared to traditional datasets composed of a single time point collected in the present, aDNA allows for the detection of lost genetic lineages and enables the direct assessment of allele frequencies in different time transects. Technologies for obtaining genomic data from archeological material have catapulted the development of the field of paleogenomics, but statistical methods to leverage information from time-series genetic datasets lag behind these technological advances. Over the next five years, the Amorim Lab will develop and apply methods to study human host-pathogen coevolution and adaptation using aDNA. We seek to advance the field of paleogenomics by generating aDNA datasets that comprise large sample sizes per archeological site and developing new methods and approaches to leverage information from time-series genetic data. We will use these novel resources to study host-pathogen interactions during the outbreaks of the plague in Eurasia (e.g. the Black Death) and the period of contact between Indigenous peoples from South America and European colonizers. Contrasting models of population evolution, both analytical and computational, with observed allele frequencies and other summary statistics in different time transects, we will identify the genetic signatures of host-pathogen interactions, characterize the evolutionary processes involved in human response to pathogens, and infer the strength and timing of selective sweeps. In addition, we will characterize the Distribution of Fitness Effects (DFE) of new mutations in the human genome across different time transects and analyze its evolution in light of the environmental shifts caused by disease outbreaks and other events. This study represents an advance over the state-of-the-art knowledge in paleogenomics for its focus on evolutionary process not yet characterized with aDNA (in particular, host-pathogen coevolution), the characterization of the DFE using time-series data, and the development of new resources (datasets and methods). The Amorim Lab is uniquely positioned to accomplish these goals because of our experience in combining model-based approaches with genome data analysis from ancient and modern DNA, as well as our previous experience with the study of medieval Europeans and Native American populations.

项目总结