Genome-Wide Analysis of Adaptive Evolution in Humans

人类适应性进化的全基因组分析

• 批准号: 7488767
• 负责人: Joshua Michael Akey
• 金额: $ 26.3万
• 依托单位: UNIVERSITY OF WASHINGTON
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-08-01 至 2011-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7488767
• 关键词: African; Age; Alleles; Altitude; Candidate Disease Gene; Cataloging; Catalogs; Chinese People; Chromosome Mapping; Climate; Complex; DNA Resequencing; DNA Sequence; Data; Development; Diabetes Mellitus; Disease; European; Event; Evolution; Frequencies; Functional RNA; Gene Frequency; Genes; Genetic Polymorphism; Genetic Variation; Genome; Genomics; Geographic Distribution; Goals; HSCH2CH(CH2CH(CH3)2)CO-Phe-Ala-NH2; Haplotypes; Human; Human Genetics; Human Genome; Hypertension; Individual; International; Japanese Population; Knowledge; Linkage Disequilibrium; Malignant Neoplasms; Numbers; Pattern; Phylogenetic Analysis; Population; Population Heterogeneity; Public Health; Recording of previous events; Relative (related person); Research; Resolution; Resources; SNP genotyping; Scanning; Shadowing (Histology); Shapes; Spatial Distribution; Structure; Testing; Variant; base; design; driving force; expectation; genome wide association study; genome-wide analysis; insight; interest; nonhuman primate; population genetic structure

DESCRIPTION (provided by applicant): Positive selection, or adaptive evolution, is the driving force of Darwinian evolution and acts to increase the frequency of advantageous alleles in a population. Despite intense interest and study a detailed understanding of the adaptive landscape of the human genome has remained elusive. Identifying regions of the genome that have been targets of adaptive evolution will provide important insights into human evolutionary history and facilitate the identification of complex disease genes. The long-term goal of this project is to further our knowledge of how positive selection has contributed to extant patterns of human genetic variation by identifying genes that have been subject to adaptive evolution. To this end, in specific aim 1, we will use dense catalogs of publicly available SIMP data to perform genome-wide scans for positive selection and identify candidate selection genes. In contrast to the traditional paradigm of studying a small number of loci that one hypothesizes a priori to be influenced by selection, a population genomics approach allows global and unbiased inferences about selection to be made. In specific aim 2, we will confirm the signature of positive selection in 30 candidate selection genes by resequencing them in 88 individuals (22 each from African, Chinese, European, and Japanese populations) and 7 non-human primates. High resolution DNA sequence data will allow detailed evolutionary hypotheses to be tested. Specifically, statistical tests of neutrality based on levels of intraspecific polymorphism and interspecific divergence will be performed, and the magnitude and ages of selective events will be estimated. Finally, in specific aim 3, we will genotype SNPs in confirmed genes subject to adaptive evolution in a geographically diverse panel of 1,064 individuals. These data will provide important insights into the geographic distribution of genetic variation subject to adaptive evolution and allow us to test the hypothesis that selected allele and haplotype frequencies are correlated with environmental attributes such as latitude, altitude, or climate. The data generated in this project will have a significant impact on public health. One of the most difficult challenges confronting human genetics is to find genes that contribute to common complex diseases such as diabetes, cancer, and hypertension. Research that increases our understanding of the evolutionary forces that shape patterns of human genetic variation will facilitate disease gene mapping studies.

描述（由申请人提供）：阳性选择或自适应进化是达尔文进化的驱动力，是增加了人群中有价值等位基因的频率的行为。尽管兴趣并研究了对人类基因组的适应性景观的详细理解仍然难以捉摸。鉴定基因组的区域已成为适应性进化的靶标，将为人类进化史提供重要的见解，并促进对复杂疾病基因的鉴定。该项目的长期目标是进一步了解积极选择如何通过鉴定经过适应性进化的基因来促进人类遗传变异的现有模式。为此，在特定的目标1中，我们将使用密集的公开可用SIMP数据目录来执行全基因组扫描以进行积极选择并识别候选选择基因。与研究少数基因座的传统范式相反，人们假设先验的选择受到选择的影响，人口基因组学方法可以对选择进行选择。在特定的目标2中，我们将通过重新对88个人（非洲，中国，欧洲和日本人口的22个）和7个非人类灵长类动物重新陈述30个候选选择基因的阳性选择签名。高分辨率DNA序列数据将允许测试详细的进化假设。具体而言，将根据种内多态性和种间差异的水平进行中立性的统计检验，并将估计选择性事件的幅度和年龄。最后，在特定的目标3中，我们将在1,064个个体的地理不同面板中受到适应性进化的确认基因中的基因型SNP。这些数据将提供对受适应性进化的遗传变异的地理分布的重要见解，并允许我们测试所选等位基因和单倍型频率与环境属性（如纬度，高度或气候）相关的假设。该项目中产生的数据将对公共卫生产生重大影响。人类遗传学面临的最困难的挑战之一是找到有助于糖尿病，癌症和高血压等常见复杂疾病的基因。提高了我们对塑造人遗传变异模式的进化力的理解的研究将促进疾病基因映射研究。