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。两种最常用的分子标记——单核苷酸多态性（SNPs）和短串联重复多态性（STRPs）的变异源于不同的突变过程，导致对进化力量的互补推断。由于较高的突变率，STRPs可以更好地揭示最近的进化事件，而缓慢突变的snp则更有效地用于重建较早的进化事件。尽管存在这种关键差异，但在经验或理论研究中很少直接比较snp和STRPs的多态性模式。提出的研究将通过联合检查人类群体中snp和STRPs的基因组变异模式，并通过进行计算机模拟，明确模拟两种标记类的对比突变过程，来解决这一重要挑战。具体而言，该项目将(1)比较不同进化过程下产生的SNPs、STRPs和SNPs+STRPs的预期多态性模式，(2)比较SNPs、STRPs和SNPs+STRPs作为复杂性状关联研究标记的性能，(3)表征连锁SNPs和STRPs之间的预期连锁不平衡和其他多样性相关性，(4)测量整个人类基因组中连锁SNPs和STRPs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比较。在STRP突变模型中产生相对健壮的多态性模式的进化情景将被特别寻求作为有希望的推断途径。该研究的重要成果包括：基于时间尺度和进化过程对标记选择的客观指导，在整个人类基因组中整合邻近snp和STRPs多态性的框架，以及发展结合这两个标记的统计方法以增强群体遗传推断的基础。通过直接检测人类基因组中snp和STRPs之间的连锁不平衡，并定量比较使用不同或组合标记类型分析的能力，本研究还将为复杂人类疾病的关联定位提供改进的策略。这个项目将研究不同种类的人类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基因变异的原因。

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.