STATISTICAL METHODS FOR STUDYING DISEASE GENE HISTORY

研究疾病基因史的统计方法

• 批准号: 2889683
• 负责人: Yun-Xin Fu
• 金额: $ 12.32万
• 依托单位: UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-09-30 至 2001-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2889683
• 关键词: DNA; alleles; biochemical evolution; computer assisted sequence analysis; computer program /software; cystic fibrosis; gene mutation; genetic disorder; genetic markers; genetic models; genetic polymorphism; genetic recombination; human population genetics; life cycle; mathematical model; model design /development; natural selections; nucleic acid sequence; pathologic process; point mutation; statistics /biometry

DESCRIPTION: (Applicant's abstract) The Human Genome Project has already produced numerous long human DNA sequences. Such a long sequence may cover an entire gene and also its flanking regions. This progress and the advent of rapid DNA sequencing techniques will allow the sequencing of large DNA regions of samples from human populations, especially regions containing a disease-causing mutation. Alternatively, one may study microsatellite markers closely linked to the mutation. The goal of this project is to develop population genetics theory, statistical methods and computer algorithms for studying the history and the mechanism of maintenance of a disease-causing mutation in a population. The specific aims are (1) to develop a coalescent theory for a DNA region subject to point mutation, natural selection and recombination, (2) to develop a coalescent theory for microsatellite loci subject to stepwise mutation, natural selection and recombination. Current coalescent methods assume an equilibrium population, and are not appropriate for studying a recent mutation subject to natural selection, such as the AF508 mutation of cystic fibrosis. We propose to develop a coalescent approach incorporating a method for simulating the history of the subpopulation bearing the mutant. (3) to develop methods for estimating the age of a disease causing mutation from DNA sequences or from microsatellite markers. (4) to develop methods for estimating the selection coefficients and for testing hypotheses about the selection coefficients of a disease-causing mutation. One of the methods we will develop is for site-by-site polymorphism data, and does not require the determination of DNA haplotype sequences. Therefore, the method will be particularly useful when large scale screening of polymorphisms in a sample is done by DNA "chips". (5) to develop a computer package for the above methods accessible on the World Wide Web, and (6) to apply the theory and methods to estimate the age and selection coefficients of the AF508 mutant of cystic fibrosis.

描述：（申请人的摘要）人类基因组项目已经 产生了许多长的人DNA序列。 如此长的序列可能覆盖 整个基因及其侧翼地区。 这个进度和降临 快速DNA测序技术将允许进行大型DNA的测序 来自人类人群的样本区域，尤其是包含一个的地区 引起疾病的突变。 另外，可以研究微卫星 标记与突变密切相关。 这个项目的目标是 发展人口遗传学理论，统计方法和计算机 研究历史和维持的算法 人群中引起疾病​​的突变。 具体目的是（1） 开发一个与点突变的DNA区域的合并理论， 自然选择和重组，（2）开发一个合并理论 微卫星基因座受到逐步突变，自然选择和 重组。 当前的合并方法假设平衡人口， 并且不适合研究最新突变 选择，例如囊性纤维化的AF508突变。 我们建议 开发一种结合模拟方法的合并方法 子群的历史带有突变体。 （3）开发用于 估计疾病的年龄，导致DNA序列突变或 微卫星标记。 （4）开发估计选择的方法 系数和测试有关选择系数的假设 引起疾病的突变。 我们将开发的方法之一是 逐个站点的多态性数据，不需要确定 DNA单倍型序列。 因此，该方法将特别有用 当通过DNA进行大规模筛查样品中的多态性时 “芯片”。 （5）为上述方法开发计算机包 在万维网上，以及（6）应用理论和方法来估计 囊性纤维化的AF508突变体的年龄和选择系数。