The impact of natural selection and population structure on human genomic variation

自然选择和种群结构对人类基因组变异的影响

• 批准号: 10606542
• 负责人: Graham Coop
• 金额: $ 18.74万
• 依托单位: UNIVERSITY OF CALIFORNIA AT DAVIS
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-04-01 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10606542
• 关键词: Address; Automobile Driving; Biology; DNA Sequence; Data; Environmental Impact; Evolution; Gene Frequency; Genealogy; Genetic; Genomics; Genotype; Goals; Human; Human Genetics; Link; Maps; Medical; Modeling; Natural Selections; Phenotype; Population; Population Genetics; Population Statistics; Recording of previous events; Research Project Grants; Role; Shapes; Signal Transduction; Structure; Time; Variant; Work; genome wide association study; genome-wide; genomic data; genomic predictors; genomic variation; human disease; migration; novel; novel strategies; tool; trait

Project Summary A key goal of evolutionary biology and human genetics is to understand the ways in which natural selection has shaped genetic and phenotypic variation within and among populations. The vast amount of population-genomic data, ancient DNA sequence data, and genotype-phenotype mapping data being generated bring an unprecedented power to address long-standing questions about the impact of adaptation in human evolution and the role of migration and selection in driving genome-wide evolutionary change. Our lab brings new tools from the intersection of population genetics and statistics to address these questions, capitalizing on a range of new approaches, from building genomic predictions of traits to the construction of genome-wide evolutionary genealogies. To maximize the potential of these new data and approaches, we propose to develop novel population-genomic models and statistical tools that address the roles of natural selection and population structure in shaping population-genomic variation. Specifically, the proposed work will: 1) Clarify how GWAS and population genetics can be leveraged to both robustly identify signals of polygenic adaptation and problems with confounding in GWAS; 2) Use genome-wide genealogies to estimate recent histories of dispersal and selection; and 3) Estimate the proportion of allele-frequency change driven by linked selection and the time scales over which selection acts, genome-wide. The results of these projects will address fundamental questions about the structure of human genomic variation.

项目摘要 进化生物学和人类遗传学的一个关键目标是了解 自然选择塑造了内部和内部的遗传和表型变异， 人口。大量的人口基因组数据，古代DNA序列数据， 基因型-表型作图数据的产生带来了前所未有的力量 解决长期存在的关于适应对人类进化的影响的问题 以及迁移和选择在驱动全基因组进化变化中的作用。 我们的实验室从群体遗传学和统计学的交叉点带来了新的工具， 解决这些问题，利用一系列新的方法，从建立 性状的基因组预测到全基因组进化的构建 家谱为了最大限度地发挥这些新数据和方法的潜力，我们建议 开发新的群体基因组模型和统计工具， 自然选择和种群结构在塑造种群基因组变异中的作用。 具体来说，拟议的工作将：1）澄清GWAS和群体遗传学如何能够 利用这两个强大的识别信号的多基因适应和问题， GWAS中的混杂; 2）使用全基因组谱系来估计最近的历史， 估计等位基因频率变化的比例 由连锁选择和选择作用的时间尺度驱动，全基因组。 这些项目的结果将解决有关结构的基本问题， 人类基因组变异