Joint inferences of natural selection between sites and populations

项目摘要/摘要 迫切需要群体遗传推断方法来量化自然选择。 种群内部和种群之间的冲突。PI的长期目标是发展全面的 在自然种群中识别选择及其功能的方法 后果。本应用程序的目标是开发和应用新的方法 用于推断基因组位置之间和自然种群之间的相关选择。 拟议研究的理由是，所开发的方法将广泛地 适用，为理解病原体和基因的适应提供基础 人类疾病的架构。 在目标1中，PI提议利用他最近开发的方法来计算 对连锁遗传座位对的统计，以量化自然选择的几个方面。 人类和黑腹果蝇。他将首先将重点放在单个已知的适应性基因座上，fi 量化选拔的力度、时机和方式。然后，他将推断出 新的非同义突变的fi强度效应。最后，我们将推断出联合分布 同一蛋白质中非同义突变的fi程度效应。 在目标2中，PI建议量化人与人之间不同的自然选择。 Mans、黑腹水蚤D.Blackogaster和纤毛蚤Daphnia Pulex.为了做到这一点，他将开发一种推理方法 突变fi度效应的联合分布及其在不同分子基因组中的应用 功能和种群的不同分化。 所提出的研究在方法和概念上都是创新的。这些方法 有待开发的是新的，fi度效应的联合分布的概念也是如此。 网站和人口之间的关系。拟议研究的预期结果是新的。 人类和两种自然选择的群体遗传推断方法和推断 模型生物。预计这些结果将对以下方面产生重要积极影响 群体遗传学的fiEd。这些方法将得到广泛适用和良好支持，以及 这些推论将提供给推断进化历史和预测 进化的未来。 项目摘要/摘要

Project Summary/Abstract There is a critical need for population genetic inference approaches to quantify natural selec- tion within and between populations. The PI's long-term goal is to develop comprehensive approaches for identifying selection in natural populations and understanding its functional consequences. The objectives of this application are to develop and apply novel approaches for inferring correlated selection between genomic sites and between natural populations. The rationale for the proposed research is that the approaches developed will be broadly applicable, providing a foundation understanding adaptation in pathogens and the genetic architecture of human disease. In Aim 1, the PI proposes to leverage his recently developed approach for calculating the statistics of pairs of linked genetic loci to quantify several aspects of natural selection in hu- mans and Drosophila melanogaster. He will first focus on individual known adaptive loci, quantifying the strength, timing, and mode of selection. He will then infer the distribution of fitness effects of new nonsynonymous mutations. Lastly, we will infer the joint distribution of fitness effects of nonsynonymous mutations within the same protein. In Aim 2, the PI proposes to quantify divergent natural selection between populations of hu- mans, D. melanogaster, and Daphnia pulex. To do so, he will develop an approach for inferring joint distributions of mutation fitness effects and apply it to genes sets of differing molecular function and populations of differing divergence. The proposed research is innovative both methodologically and conceptually. The methods to be developed are novel, as are the concepts of joint distributions of fitness effects be- tween sites and populations. The expected outcomes of the proposed research are new population genetic inference methods and inferences of natural selection in humans and two model organisms. These outcomes are expected to have important positive impact on the field of population genetics. The methods will be widely applicable and well-supported, and the inferences will feed into approaches for inferring the evolutionary past and predicting the evolutionary future. Project Summary/Abstract