DISEQUILIBRIUM MAPPING OF COMPLEX GENETIC DISEASES

复杂遗传疾病的不平衡图谱

• 批准号: 2864903
• 负责人: Bruce RANNALA
• 金额: $ 16.77万
• 依托单位: STATE UNIVERSITY NEW YORK STONY BROOK
• 依托单位国家: 美国
• 财政年份: 1999
• 资助国家: 美国
• 起止时间: 1999-01-01 至 2001-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2864903
• 关键词: alleles; clinical research; computer data analysis; computer program /software; computer simulation; gene expression; gene frequency; gene mutation; genetic disorder; genetic markers; genetic recombination; haploidy; human data; human population genetics; linkage disequilibriums; mathematical model; method development; phenotype; quantitative trait loci; restriction fragment length polymorphism; statistics /biometry

The objective of the proposed research is to develop new theory and methods for high-resolution mapping of the mutations underlying complex genetic diseases of humans. The methods will use information from population level linkage disequilibrium (LD) between one or more genetic markers and a disease phenotype. The basis for LD mapping is that the marker haplotype found on the chromosome on which a disease mutation first arose will tend to have a higher frequency on chromosomes carrying that mutation. This non-random association between genetic markers and a disease phenotype decreases over time, due to recombination, at a rate that depends on the physical distance of the marker from the mutation. This allows the distances between linked genetic markers and a disease mutation to be estimated using a mathematical model of the process of genetic recombination and of the disease allele dynamics in the population. LD mapping methods are most effective when applied to populations that have experienced recent founding events and/or high levels of population growth. New statistical methods for LD mapping will be developed that make use of multiple genetic markers and account for potential complications such as recurrent mutation (the same disease phenotype results from different mutations in a single disease gene) and locus heterogeneity (the same disease phenotype results from mutations in several different disease genes). The statistical performance of the methods will be studied by using computer simulation to generate artificial populations of disease alleles and by analyzing existing genetic marker data for which the location of the disease mutation is now known. The methods will be suitable for use with several different types of genetic markers that are currently widely used including restriction fragment length polymorphisms (RFLPs), microsatellites, and single nucleotide polymorphisms (SNPs).

拟议研究的目的是发展新理论， 突变基础复合物的高分辨率映射的方法 人类的遗传疾病。 这些方法将使用来自 人口水平连锁不平衡（LD）在一个或多个遗传之间 标记和疾病表型。 LD映射的基础是 染色体上发现的标记单倍型，疾病突变 首先出现的染色体往往会具有较高的频率 那突变。遗传标记与 疾病表型随着时间的流逝而降低，由于重组的速度 这取决于标记与突变的物理距离。 这允许链接的遗传标记与疾病之间的距离 使用该过程的数学模型来估算的突变 基因重组和疾病等位基因动力学 人口。 LD映射方法应用于 经历了最近的创始活动和/或高昂的人群 人口增长水平。 LD映射的新统计方法 将开发利用多个遗传标记和帐户的开发 对于潜在的并发症，例如复发突变（相同的疾病 表型是由单个疾病基因中的不同突变引起的）和 基因座异质性（相同的疾病表型是突变引起的 在几种不同的疾病基因中）。 统计表现 将通过使用计算机模拟生成方法来研究方法 人造疾病等位基因的种群，并通过分析现有 疾病突变位置的遗传标记数据 现在已知。 该方法适合与几种不同 当前广泛使用的遗传标记类型 限制片段长度多态性（RFLP），微卫星和 单核苷酸多态性（SNP）。