Identifying human adaptations: theory and applications

识别人类适应性：理论与应用

• 批准号: 7011227
• 负责人: MOLLY F PRZEWORSKI
• 金额: $ 18.2万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-03-01 至 2010-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7011227
• 关键词: Internet; cell line; computer human interaction; computer program /software; computer simulation; computer system design /evaluation; gene expression; genetic mapping; genetic polymorphism; genetic regulatory element; genetic susceptibility; human genetic material tag; human population genetics; human tissue; mathematical model; method development; nucleotides; polymerase chain reaction; species difference; statistics /biometry

DESCRIPTION (provided by applicant): 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 approximately 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.

描述（由申请人提供）：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。这项研究通常包括连锁分析或关联研究。一种互补的、基于种群遗传的方法是通过检查人类内部和人类与其近亲之间的核苷酸变异模式来确定人类谱系中可能的适应目标。涉及人类特异性适应结构的遗传变化本身就引起了极大的兴趣，并代表了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环境中对人类合理的积极选择进行建模。在此基础上，我们将开发稳健的统计方法来评估多态性数据对近期适应的支持，并估计其时间和基因组位置。新方法的可靠性将在一系列假设下的模拟数据上进行检验。实现它们的用户友好程序将通过网络公开提供。我们将把我们的新方法应用于由顺式调控区域变化引起的具有人类特异性表达模式的基因的多态性数据。这些基因将从我们之前的工作中发现的一组基因中识别出来，这些基因在人脑中的表达与其他类人猿不同。一旦通过RT-PCR确认了表达模式，我们将通过报告基因分析来测试人类和黑猩猩在转录起始位点附近约1.5kb区域的序列差异是否会影响表达。如果确实如此，我们将收集30个约鲁巴人5'区域的多态性数据，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，用于检测功能重要区域，并将确定基因表达调控中人类特异性适应的第一组候选基因。