Haplotyping and QTL Mapping in Pedigrees with Missing Data

缺失数据谱系的单倍型分析和 QTL 定位

• 批准号: 7259849
• 负责人: Guimin Gao
• 金额: $ 26.1万
• 依托单位: UNIVERSITY OF ALABAMA AT BIRMINGHAM
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-06-01 至 2012-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7259849
• 关键词: Alzheimer' s Disease; Amish; Animals; Architecture; Asthma; Blood Pressure; Bone Density; Chromosome Mapping; Complex; Computing Methodologies; Data; Data Set; Diabetes Mellitus; Disease; Genes; Genetic; Genotype; Haplotypes; Human; Knowledge; Link; Linkage Disequilibrium; Maps; Methodology; Methods; Milk; Modeling; Numbers; Performance; Persons; Phase; Population; Probability; Production; Quantitative Trait Loci; Research; Single Nucleotide Polymorphism; Work; base; genetic linkage analysis; genetic pedigree; hutterite; improved; software development; trait

DESCRIPTION (provided by applicant): Statistical gene mapping in pedigrees advances our knowledge of the genetic architecture of complex diseases (e.g., diabetes, Alzheimer's disease, asthma) and quantitative traits (e.g., bone density, blood pressure, milk production) in human and animal populations. Unfortunately most observed pedigree data are not complete and have missing data. Efficiently inferring haplotype configurations and calculating identity-by-descent (IBD) probabilities for complex pedigrees with large numbers of linked loci and missing marker data by using the observed genotype data (especially dense single nucleotide polymorphism (SNP) markers) are critical components and remain challenging in statistical gene mapping. The broad, long-term objectives of the proposed work are to develop efficient statistical and computational methods for haplotyping and gene mapping in large pedigrees with missing and phase unknown marker data. The specific aims are to 1) extend our conditional enumeration haplotyping method that currently works with complete pedigree data to pedigrees with missing marker data, and then improve the method so that it can handle linkage disequilibrium (LD) between markers; 2) develop a computationally efficient method for estimating IBD probabilities in large pedigrees with large numbers of linked loci and with missing marker data, develop a fine mapping method by modeling LD information between dense (SNP) markers, and evaluate the performance of the IBD probability estimation method in terms of quantitative trait loci (QTL) mapping accuracy in linkage analysis and fine mapping; 3) apply the proposed methods to linkage analysis and fine mapping of two large, real human pedigree data sets (a 1623-person Hutterite pedigree and a 1412- person Amish pedigree); and 4) develop computer software to implement aims 1 and 2. Our approach to these aims is based on the computation of conditional probabilities of possible ordered genotypes at phase unknown markers and the calculation of likelihood of haplotype configurations. By setting a threshold value for the conditional probabilities of ordered genotypes at phase unknown markers and a threshold value for the conditional probabilities of haplotype configurations, the proposed haplotyping method identifies a subset of haplotype configurations with the highest likelihoods for a pedigree. IBD probabilities are estimated based on this subset of haplotype configurations, and then are used as input to variance components based QTL mapping methods in large pedigrees. The methodologies developed in this research will enhance our ability to map QTL and complex disease genes in human and animal populations.

描述（由申请人提供）：谱系中的统计基因映射促进了我们对复杂疾病的遗传结构（例如糖尿病，阿尔茨海默氏病，哮喘）和量化性状（例如，人和动物种群中的骨密度，血压，血压，血压，血压，血压，血压，血压）的了解。不幸的是，大多数观察到的谱系数据尚未完成，并且缺少数据。通过使用观察到的基因型数据（尤其是密集的单核苷酸多态性（SNP）标记），有效地推断出单倍型配置并计算具有大量链接的基因座和缺失标记数据的复杂的典型概率（IBD）概率是至关重要的组成部分，并且在稳定基因中仍然具有挑战性。所提出的工作的广泛，长期目标是开发有效的统计和计算方法，用于具有缺失和相位未知标记数据的大型谱系中的单倍型和基因映射。具体目的是至1）扩展我们的条件枚举单倍型方法，该方法当前与缺少标记数据的家谱一起使用完整的血统数据，然后改进该方法，以便它可以处理标记之间的链接不平衡（LD）； 2) develop a computationally efficient method for estimating IBD probabilities in large pedigrees with large numbers of linked loci and with missing marker data, develop a fine mapping method by modeling LD information between dense (SNP) markers, and evaluate the performance of the IBD probability estimation method in terms of quantitative trait loci (QTL) mapping accuracy in linkage analysis and fine mapping; 3）将提出的方法应用于两个大型人类谱系数据集的链接分析和精细映射（1623人的Hutterite谱系和1412-人的Amish谱系）； 4）开发以实现目标1和2的计算机软件。我们对这些目标的方法基于相位未知标记处可能有序基因型的条件概率的计算以及单倍型配置的可能性的计算。通过为相位未知标记处有序的基因型的条件概率设置阈值，并为单倍型配置的条件概率设置阈值值，提出的单倍型方法可以标识具有最高可能性的单倍型配置的子集。基于此单倍型配置子集估算IBD概率，然后用作大型谱系中基于方差组件的QTL映射方法的输入。这项研究中开发的方法将增强我们在人类和动物种群中绘制QTL和复杂疾病基因的能力。