The Population Genetics of Divergence

分歧的群体遗传学

• 批准号: 7921487
• 负责人: Emanuel Hey
• 金额: $ 21.5万
• 依托单位: RUTGERS, THE STATE UNIV OF N.J.
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-01 至 2012-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7921487
• 关键词: Case Study; Confidence Intervals; DNA; Data Set; Genes; Genetic Drift; Human; Joints; Life; Markov Chains; Methods; Modeling; Pan Genus; Phylogenetic Analysis; Phylogeny; Population; Population Genetics; Population Sizes; Probability; Process; Relative (related person); Research; Research Project Grants; Sampling; Structure; Testing; base; density; novel strategies; simulation

DESCRIPTION (provided by applicant): Population divergence, including speciation and the origins of population structure, is the fundamental evolutionary process leading to the diversity of life. This research project will extend recent advances in a likelihood-based approach to divergence models. The new approach employs analytic integration over prior distributions of model parameters within a Markov chain Monte Carlo framework. The method leads to a joint probability density function, proportional to the likelihood that can be used for parameter estimation and log- likelihood ratio tests of nested demographic models. The new method will be adapted to general multi-population problems in divergence. Such problems have long been appreciated as requiring both a population genetic perspective and a phylogenetic perspective. The research plan outlines how these two can be brought together under a common MCMC simulation. This will be the first such method that does not assume a given phylogeny; that does not assume that gene flow has not occurred; and that makes no assumptions about the relative population sizes of sampled or ancestral populations. By providing estimates of the joint posterior density, proportional to the likelihood, the method will provide direct access to log-likelihood ratio tests and to likelihood-based confidence intervals. The approach will also be extended to problems in sample identification and DNA barcoding. These new methods will be applied to a case study of divergence among species and subspecies of Chimpanzee. The methods will also be applied to large multi-population multi-locus data sets from human populations.

描述（由申请人提供）：种群分化，包括物种形成和种群结构起源，是导致生命多样性的基本进化过程。该研究项目将扩展基于可能性的分歧模型方法的最新进展。新方法在马尔可夫链蒙特卡罗框架内对模型参数的先验分布进行分析积分。该方法产生联合概率密度函数，与可用于嵌套人口统计模型的参数估计和对数似然比测试的可能性成比例。新方法将适应分歧中的一般多群体问题。长期以来，此类问题一直被认为需要群体遗传学视角和系统发育视角。该研究计划概述了如何将这两者结合到一个共同的 MCMC 模拟中。这将是第一个不假设给定系统发育的方法；这并不假设基因流动尚未发生；并且没有对抽样人口或祖先人口的相对人口规模做出假设。通过提供与似然成比例的联合后验密度估计，该方法将提供对对数似然比检验和基于似然的置信区间的直接访问。该方法还将扩展到解决样本识别和 DNA 条形码问题。这些新方法将应用于黑猩猩物种和亚种之间差异的案例研究。这些方法还将应用于来自人群的大型多群体多位点数据集。