The use of recombining genetic markers for demographic inference

使用重组遗传标记进行人口统计推断

• 批准号: 7293413
• 负责人: JOHN E POOL
• 金额: $ 0.7万
• 依托单位: UNIVERSITY OF COPENHAGEN
• 依托单位国家: 美国
• 财政年份: 2006
• 资助国家: 美国
• 起止时间: 2006-11-16 至 2008-11-15
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7293413
• 关键词: DNA; genetic markers; genetics; human; migrant; model; population genetics

DESCRIPTION (provided by applicant): The proposed research concerns the inference of historical patterns of migration. Traditional population genetic models of migration assume that populations have been exchanging migrants at a constant rate over long periods of time. For many species, however, this assumption may not be appropriate. Therefore, the development of a computational method to test for recent changes in migration rate and to estimate the relevant demographic parameters is proposed. While most methods of demographic inference assume that all of the genetic markers being studied are independent (unlinked), this approach will take advantage of the patterns of linkage along a recombining chromosome. By considering this linkage information (specifically, the lengths of DNA segments that inferred to have migrant origin), one can go beyond estimating how much migration has occurred between two populations, and say something about when, historically, this migration occurred. During the first phase of this project, the effect of various population histories on the length distribution of migrant DNA segments will be investigated, making use of an existing simulation program (ms) and inference method (structure 2.0). Next, the new inference method described above will be developed, using Markov chain Monte Carlo methodology in a maximum likelihood or Bayesian framework. Finally, this method will be applied to existing human polymorphism data sets (both SNP and microsatellite) in order to test the null hypothesis that migration among human populations has been constant since their divergence. This analysis will permit the estimation of demographic parameters for admixed human populations, and will therefore aid in the selection of populations for admixture mapping studies of disease association. Relevance to public health: The goal of the proposed research is to test for historical changes in the rate of migration between populations, and to estimate quantities such as the time since a migration rate change and the magnitude of such a change. The computational method developed will have a variety of applications, including the estimation of demographic parameters in human populations with a history of recent admixture (ancestry from multiple sources), such as African-American, Hispanic, Central Asian and Northern African populations. That information will be relevant in assessing the utility of such populations for admixture mapping studies, which aim to identify genetic variants associated with complex diseases that occur at different frequencies in different populations.

描述（由申请人提供）：拟议的研究涉及移民历史模式的推断。传统的人口遗传迁移模型假设人口在长时间以来一直以恒定的速度交换移民。但是，对于许多物种而言，此假设可能不合适。因此，提出了一种计算方法来测试迁移率最近变化并估算相关人口参数的开发。尽管大多数人口统计学推论方法都假定所研究的所有遗传标记都是独立的（未链接），但这种方法将利用沿重组染色体的链接模式。通过考虑这些链接信息（特别是推断为具有移民起源的DNA段的长度），一个人可以超越估计两个人群之间发生了多少迁移，并说了一些关于何时发生这种迁移的何时发生。在该项目的第一阶段，将研究各种人口历史对移民DNA段长度分布的影响，利用现有的仿真程序（MS）和推理方法（结构2.0）。接下来，将使用Markov Chain Monte Carlo方法制定上述新的推理方法，以最大的可能性或贝叶斯框架。最后，该方法将应用于现有的人类多态性数据集（SNP和微卫星），以检验零假设，即自分散以来，人类种群之间的迁移一直是恒定的。该分析将允许估算混合人群的人口统计学参数，因此将有助于选择疾病关联研究的掺杂映射研究的人群。 与公共卫生有关：拟议研究的目的是测试人群之间迁移率的历史变化，并估算诸如移民率变化以来的时间和这种变化的幅度之类的时间。开发的计算方法将具有多种应用，包括在人口中的人口参数的估计，这些人口具有最近的混合历史（来自多种来源的祖先），例如非洲裔美国人，西班牙裔，中亚和北非人群。该信息将与评估此类人群对混合图研究的实用性有关，该研究旨在鉴定与不同人群中不同频率发生的复杂疾病相关的遗传变异。