Integrating SNPs and STRPs in Population Genetics

描述（由申请人提供）：分子标记的变异模式为自然种群的进化提供了令人兴奋的见解。在两个最常用的分子标记，单核苷酸多态性（SNPs）和短串联重复序列多态性（STRP）的变化，来自不同的突变过程，导致进化力量的互补推论。由于较高的突变率，STRP更好地揭示了最近的进化事件，而缓慢突变的SNP更有力地应用于重建旧的进化事件。尽管存在这一重要差异，但在经验或理论研究中很少直接比较SNP和STRP的多态性模式。拟议的研究将通过联合检查人类群体中SNP和STRP的基因组变异模式，并通过进行计算机模拟来明确模拟两个标记类别的对比突变过程，来解决这一重要挑战。具体而言，本项目将（1）比较在不同进化过程中产生的SNP、STRP和SNP + STRP的多态性的预期模式，（2）比较SNP、STRP和SNP + STRP作为复杂性状关联研究标记的性能，（3）表征连锁SNP和STRP之间的预期连锁不平衡和其他多样性相关性，和（4）测量整个人类基因组中连锁的SNP和STRP之间的共变异模式。这种结合经验和理论的努力将产生SNP和STRP多态性模式的第一个系统的比较。进化的情况下，产生模式的多态性是相对强大的STRP突变模型的变化将特别寻求有前途的途径进行推断。拟议的研究的重要成果包括：基于时间尺度和进化过程的目标标记选择的指导，在整个人类基因组中整合邻近SNP和STRP的多态性的框架，以及联合收割机这两个标记，以提高人口遗传推断的统计方法的发展的基础。通过直接检查人类基因组中SNP和STRP之间的连锁不平衡，并定量比较使用不同或组合标记类型的分析能力，这项研究还将产生用于复杂人类疾病关联映射的改进策略。该项目将研究不同类别的人类DNA变异的特性。这些结果将有助于揭示复杂遗传疾病背后的遗传变异的原因。 项目相关性：该项目将研究不同类别的人类DNA变异的特性。这些结果将有助于揭示复杂遗传疾病背后的遗传变异的原因。

DESCRIPTION (provided by applicant): Patterns of variation at molecular markers provide exciting insights into the evolution of natural populations. Variation at the two most commonly used molecular markers, single nucleotide polymorphisms (SNPs) and short tandem repeat polymorphisms (STRPs), arises from different mutational processes, leading to complementary inferences about evolutionary forces. Because of higher mutation rates, STRPs better reveal recent evolutionary events, whereas slowly mutating SNPs are more powerfully applied to reconstructing older evolutionary events. Despite this crucial difference, patterns of polymorphism at SNPs and STRPs have rarely been compared directly in empirical or theoretical studies. The proposed research will address this important challenge by jointly examining genomic patterns of variation at SNPs and STRPs in human populations and by conducting computer simulations that explicitly model the contrasting mutational processes at the two marker classes. Specifically, this project will (1) compare expected patterns of polymorphism at SNPs, STRPs, and SNPs+STRPs generated under different evolutionary processes, (2) compare the performance of SNPs, STRPs, and SNPs+STRPs as markers for association studies of complex traits, (3) characterize expected linkage disequilibrium and other diversity correlations between linked SNPs and STRPs, and (4) measure patterns of co-variation between linked SNPs and STRPs across the human genome. This combined empirical and theoretical effort will yield the first systematic comparison of patterns of SNP and STRP polymorphism. Evolutionary scenarios that produce patterns of polymorphism that are relatively robust to variation in the STRP mutational model will be specifically sought as promising avenues for inference. Important outcomes of the proposed research include: objective guidance on marker choice based on timescale and evolutionary process of interest, a framework for integrating polymorphism at neighboring SNPs and STRPs throughout the human genome, and a foundation for the development of statistical methods that combine these two markers to enhance population genetic inference. By directly examining linkage disequilibrium between SNPs and STRPs across the human genome and quantitatively comparing the power of analyses using different or combined marker types, this research will also yield improved strategies for association mapping of complex human diseases. This project will examine the properties of different classes of human DNA variation. The results will help reveal the causes of the genetic variation that underlies complex inherited diseases. Project Relevance: This project will examine the properties of different classes of human DNA variation. The results will help reveal the causes of the genetic variation that underlies complex inherited diseases.