Identifying human adaptations: theory and applications

人类遗传学的一个核心挑战是确定基因组的哪些区域具有功能性， 重要性，特别是哪个子集影响疾病的风险。这项研究通常包括 关联分析或关联研究。一个互补的、基于群体遗传的方法是 通过检查核苷酸变异的模式，确定人类谱系中可能的适应目标 以及人类与其进化近亲之间的关系。基因变化涉及 人类特有适应性结构本身就具有极大的意义， 复杂疾病易感性的有希望的候选者。 我们建议在各种人口统计学背景下对正选择进行建模， 人类在此基础上，我们会发展稳健的统计方法，以评估 最近适应的多态性数据，并估计其时间和基因组位置。的 新方法的可靠性将在一系列假设下的模拟数据上进行测试。用户友好 实现这些目标的计划将通过网络公开提供。 我们将把我们的新方法应用于人类特异性表达基因的多态性数据 顺式调控区的变化导致的模式。这些基因将从一个 我们以前的工作已经表明，相对于其他人， 猿类一旦通过RT-PCR证实了表达模式，我们将通过报告基因测定进行检测 人类和黑猩猩之间的基因序列差异是否存在于基因组的-1.5kb区域， 转录起始位点影响表达。如果他们这样做，我们将收集多态性数据集中在5' 在30个约鲁巴人的区域，并应用我们的新方法来衡量最近适应的证据。 因此，拟议的研究将产生新的统计工具，用于检测 功能的重要性，并将确定第一组候选人的人类特异性适应， 基因表达调控

A central challenge of human genetics is to determine which regions of the genome are of functional importance and, in particular, which subset influences the risk of disease. This research usually includes linkage analyses or association studies. A complementary, population-genetic based approach is to identify likely targets of adaptation in the human lineage by examining patterns of nucleotide variation within humans and between humans and their close evolutionary relatives. Genetic changes involved in the architecture of human-specific adaptations are of great interest in their own right and represent promising candidates for complex disease susceptibility. We propose to model positive selection in a variety of demographic settings that are plausible for humans. On this basis, we will develop robust statistical methods to assess the support in polymorphism data for a recent adaptation and to estimate its timing and genomic location. The reliability of the new methods will be tested on data simulated under a range of assumptions. User-friendly programs to implement them will be made publicly available via the web. We will apply our new methods to polymorphism data from genes with human-specific expression patterns that result from changes in the cis-regulatory regions. These genes will be identified from a set that our previous work has shown to be differentially expressed in the human brain relative to other apes. Once the expression patterns have been confirmed by RT-PCR, we will test by a reporter gene assay whether sequence differences between humans and chimpanzees in a -1.5kb region around the transcription start site affect expression. If they do, we will collect polymorphism data centered on the 5' region in 30 Yoruba individuals and apply our new methods to gauge the evidence for a recent adaptation. Thus, the proposed research will generate new statistical tools for the detection of regions of functional importance and will identify the first set of candidates for human-specific adaptations in gene expression regulation.