The Population Genetics of Divergence

分歧的群体遗传学

• 批准号: 7320183
• 负责人: Emanuel Hey
• 金额: $ 22.75万
• 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 2011-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7320183
• 关键词: Address; Americas; Case Study; Chromosome Mapping; Confidence Intervals; DNA; Data; Data Set; Development; Event; Evolution; Genealogy; General Population; Genes; Genetic; Genetic Drift; Human; Individual; Joints; Life; Linkage Disequilibrium; Markov Chains; Methods; Modeling; Monte Carlo Method; Numbers; Pan Genus; Pan troglodytes; Pattern; Phylogenetic Analysis; Phylogeny; Population; Population Genetics; Population Group; Population Sizes; Probability; Process; Protocols documentation; Recording of previous events; Relative (related person); Research; Research Personnel; Research Project Grants; Sampling; Space Simulation; Structure; Testing; Today; Trees; Uncertainty; Update; base; density; improved; novel strategies; simulation; tool

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的起源，是导致生命多样性的基本进化过程。本研究项目将扩展基于可能性方法的散度模型的最新进展。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解析积分。该方法产生一个与似然成正比的联合概率密度函数，可用于嵌套人口统计模型的参数估计和对数似然比检验。该方法适用于一般的多种群散度问题。这些问题长期以来一直被认为需要群体遗传学和系统发育的观点。研究计划概述了如何在通用MCMC模拟下将这两者结合在一起。这将是第一个这样的方法，不假设一个给定的系统发育；这并不是说基因流动没有发生；而且这并没有假设样本或祖先群体的相对人口规模。通过提供与似然成比例的关节后验密度的估计，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。该方法还将扩展到样品鉴定和DNA条形码问题。这些新方法将应用于黑猩猩种和亚种分化的案例研究。该方法还将应用于来自人类种群的大型多种群多位点数据集。