Population mixture in evolutionary and medical genetics

进化和医学遗传学中的群体混合

• 批准号: 8220483
• 负责人: David E Reich
• 金额: $ 32.11万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-05-01 至 2016-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8220483
• 关键词: Accounting; Admixture; Affect; African American; Area; Biology; Cancer Center Support Grant; Chromosome Mapping; Computer software; Data; Data Set; Development; Disease; Disease Association; European; Frequencies; Funding; Gene Frequency; Generations; Genes; Genetic; Genetic Drift; Genetic Materials; Genetic Variation; Genomics; Geography; Grant; Haplotypes; Health; Hereditary Disease; Human; Human Genetics; Individual; Inherited; Laboratories; Latino; Lead; Linkage Disequilibrium; Medical Genetics; Methods; Modeling; Mutation; Organism; Paper; Phylogenetic Analysis; Population; Population Study; Principal Component Analysis; Process; Prostate; Public Health; Publications; Recording of previous events; Research; Shapes; Software Tools; South Asian; Stratification; Testing; Trees; United States National Institutes of Health; Variant; Work; Writing; analytical method; base; design; disorder risk; gene discovery; genetic linkage; genetic risk factor; genetic variant; genome-wide; human disease; insight; meetings; method development; migration; next generation; novel; pathogen; programs; statistics; tool; user friendly software

DESCRIPTION (provided by applicant): Mixture between populations is a fundamental process that shapes biology, genetic variation, and the risk for disease. Despite its importance, the analytical methods that are available to study mixture on a genome-wide scale are limited. This makes it a priority to develop methods that can analyze this history in the large data sets that are now practical to generate. No federal grant currently supports the development of such methods. This grant proposes to develop methods and make software available for studying mixture. The Aims are: (1) To develop tools that make inferences about mixture based on allele frequency and haplotype frequency differences. (2) To develop tools that estimate dates of mixture based on admixture linkage disequilibrium and genetic divergence data. We expect that this grant will be of value in three areas. (a) It will support the development of methods and user-friendly software that will be important for evolutionary and medical genetics. (b) It will support work that will result in insights relevant to finding disease genes in human populations that are recently or anciently admixed. (c) It will lead to new insights about human history as well as the history of other organisms. The connection to medical genetics is particularly important. Our laboratory's past work on the evolutionary history of populations has been intertwined with our work on disease gene mapping, and the approaches that we developed in both areas were synergistic. In particular, we have leveraged the history of admixture in human populations to make new gene discoveries and to understand variation in disease risk across populations. We expect to be able to make further connections between evolutionary and medical genetics by developing sophisticated approaches for understanding and modeling population mixture. PUBLIC HEALTH RELEVANCE: The history of population mixture is of importance to public health because it determines the genetic variants that individuals and populations inherit, which in turn make some people more or less susceptible to disease. In the last decade, it has become clear that many human populations are the result of mixtures of populations with divergent ancestries: not only African Americans and Latinos, but also South Asians and all non-Africans (who have Neandertal genetic material). For example, our group has developed methods for studying population mixture and directly applied them to discover genetic risk factors for prostate in African Americans. This grant proposes to develop sophisticated methods to understand and quantify mixture in human populations using modern genomic data. We anticipate that a deeper understanding of human population mixture will assist in the development of more powerful methods to discover genetic risk factors for disease.

描述（由申请人提供）：人群之间的混合是塑造生物学、遗传变异和疾病风险的基本过程。尽管它很重要，但可用于在全基因组范围内研究混合物的分析方法仍然有限。这使得开发能够在现在可以实际生成的大型数据集中分析这段历史的方法成为当务之急。目前没有联邦拨款支持此类方法的开发。这笔赠款提议开发方法并提供可用于研究混合物的软件。目标是：（1）开发根据等位基因频率和单倍型频率差异推断混合物的工具。 (2)开发基于混合物连锁不平衡和遗传分化数据估计混合物日期的工具。 我们预计这笔赠款将在三个领域发挥作用。 (a) 它将支持对进化和医学遗传学非常重要的方法和用户友好软件的开发。 (b) 它将支持那些能够产生与在最近或古代混合的人群中寻找疾病基因相关的见解的工作。 (c) 它将带来关于人类历史以及其他生物体历史的新见解。 与医学遗传学的联系尤为重要。我们实验室过去在种群进化史方面的工作与我们在疾病基因图谱方面的工作交织在一起，并且我们在这两个领域开发的方法是协同的。特别是，我们利用人群混合的历史来发现新的基因并了解不同人群疾病风险的差异。我们期望能够通过开发复杂的方法来理解和建模种群混合，从而在进化和医学遗传学之间建立进一步的联系。 公共卫生相关性：人口混合的历史对公共卫生很重要，因为它决定了个人和人群遗传的遗传变异，这反过来又使某些人或多或少容易感染疾病。在过去的十年中，人们已经清楚地看到，许多人口是具有不同血统的人口混合的结果：不仅有非裔美国人和拉丁裔，还有南亚人和所有非非洲人（拥有尼安德特人遗传物质）。例如，我们小组开发了研究人群混合的方法，并直接应用它们来发现非裔美国人前列腺的遗传危险因素。这笔赠款提议开发复杂的方法，利用现代基因组数据来理解和量化人群中的混合物。我们预计，对人口混合的更深入了解将有助于开发更强大的方法来发现疾病的遗传风险因素。