The impact of natural selection and population structure on 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理解 哪些自然选择在内部和之间形成了遗传和表型差异 人口。海量的种群基因组数据，古代DNA序列数据， 而正在产生的基因-表型图谱数据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 以及迁徙和选择在推动全基因组进化变化中的作用。 我们的实验室从种群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，从构建 性状的基因组预测对全基因组进化构建的影响 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 开发新的种群基因组模型和统计工具，以解决这些角色 自然选择和种群结构在塑造种群基因组变异中的作用。 具体地说，拟议的工作将：1)阐明GWA和种群遗传学如何 被用来有力地识别多基因适应的信号和问题 2)使用全基因组系谱来估计近代史。 分散和选择；3)估计等位基因频率变化的比例 由连锁选择和选择在全基因组范围内起作用的时间尺度驱动。 这些项目的成果将解决有关结构的基本问题 人类基因组变异。

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.