Population genetics to improve homozygosity mapping and mapping in admixed groups

群体遗传学改善混合群体的纯合性作图和作图

• 批准号: 8325692
• 负责人: Amy Lynne Williams
• 金额: $ 5.22万
• 依托单位: HARVARD MEDICAL SCHOOL
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2013-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8325692
• 关键词: Admixture; Affect; African; African American; Algorithms; American; Ashkenazim; Autistic Disorder; Chromosome Mapping; Collaborations; Collection; Complex; Computational algorithm; Consanguinity; DNA Resequencing; Data; Data Set; Development; Diploidy; Disease; Doctor of Philosophy; European; Event; Founder Generation; Frequencies; Genes; Genetic; Genetic Techniques; Genome; Genotype; Haplotypes; Health; Hereditary Disease; High Prevalence; Hispanics; Human; Individual; Industry; Laboratories; Latino; Lead; Maps; Medical Genetics; Mentors; Methods; Minority; Modeling; Native Americans; Non-Insulin-Dependent Diabetes Mellitus; Nuclear Family; Output; Phase; Population; Population Genetics; Research; Risk Factors; Sampling; Scheme; Signal Transduction; Single Nucleotide Polymorphism; Software Tools; Statistical Methods; Stretching; Structure; Techniques; Technology; Thinking; Training; Variant; Work; base; computer science; design; direct application; experience; genetic risk factor; genome sequencing; genome wide association study; improved; insight; novel; professor; tool

Population genetics is a crucial tool for facilitating medical genetics and disease gene mapping studies. This proposal outlines two novel population genetic techniques that each facilitate disease gene mapping in different ways. First, it describes a probabilistic technique for detecting the proportion of homozygosity an individual is likely to have based on SNP array data. This is useful for prioritizing disease case sample individuals for whole genome sequencing and subsequent homozygosity mapping to identify recessive disease genes. Such a tool is useful for large outbred populations such as European Americans for which homozygous regions are likely to be short and therefore cannot be unambiguously detected using existing techniques for SNP array data. I will apply this homozygosity prioritization scheme to a dataset of individuals with autism to identify individuals that will be most informative to resequence and will perform homozygosity mapping on the sequence data to locate recessive disease genes. The second aim is to develop methods to permit combined admixture mapping and genome-wide association (GWA) of Latinos, a population for which current admixture mapping methods fail. Latino admixture mapping is challenging because suitable reference haplotypes for their Native American ancestry are lacking, and because existing techniques cannot model their complex three-way admixture. I will explore three methods for performing admixture mapping of Latinos, including using linear combinations of collections of Native American reference haplotypes and utilizing the information about Native American variation present in the Latinos themselves. To show that my approach works in practice, I will apply this tool to study the genetics of type 2 diabetes, a disease with higher prevalence among Latinos. PUBLIC HEALTH RELEVANCE: Insights from population genetics and statistical methods grounded in medical genetics have been very important in facilitating medical genetics and disease gene mapping studies. This pro- posal describes novel population genetic techniques with direct application to disease gene mapping, both in populations that have experienced founder events and in U.S. Latino populations that are admixed. The technology that I develop will be widely applicable to many disease gene mapping studies, but I will focus as proof-of-principle on two diseases: autism and type 2 diabetes.

群体遗传学是促进医学遗传学和疾病基因定位研究的重要工具。该提案概述了两种新的群体遗传技术，每种技术都以不同的方式促进疾病基因定位。首先，它描述了一种基于SNP阵列数据检测个体可能具有的纯合性比例的概率技术。这对于区分疾病病例样本个体的优先顺序以进行全基因组测序和随后的纯合性作图以鉴定隐性疾病基因是有用的。这样的工具对于大的远系繁殖群体（例如欧洲裔美国人）是有用的，对于这些远系繁殖群体，纯合区域可能很短，因此不能使用SNP阵列数据的现有技术明确地检测。我将把这种纯合性优先化方案应用于自闭症个体的数据集，以识别对重测序信息量最大的个体，并对序列数据进行纯合性映射，以定位隐性疾病基因。第二个目标是开发方法，允许混合映射和全基因组关联（GWA）的拉丁美洲人，人口目前的混合映射方法失败。拉丁美洲混合映射是具有挑战性的，因为缺乏合适的参考单倍型为他们的美洲原住民血统，因为现有的技术不能模拟他们复杂的三向混合。我将探讨三种方法进行混合映射的拉丁美洲人，包括使用线性组合的集合美洲原住民参考单倍型和利用有关美洲原住民的变化存在于拉丁美洲人自己的信息。为了证明我的方法在实践中有效，我将应用这个工具来研究2型糖尿病的遗传学，这种疾病在拉丁美洲人中的患病率较高。 公共卫生关系：基于医学遗传学的群体遗传学和统计学方法对促进医学遗传学和疾病基因定位研究非常重要。这篇文章描述了直接应用于疾病基因定位的新型群体遗传学技术，无论是在经历了创始人事件的人群中，还是在美国拉丁裔人群中。我开发的技术将广泛应用于许多疾病基因图谱研究，但我将重点放在两种疾病上：自闭症和2型糖尿病。