Computational Methods for Detecting Natural Selection using Comparative Population Genomic Data

进化遗传学的一个中心问题是确定具有重要生物学意义的动植物种群之间的遗传差异。例如，在人类和黑猩猩之间的所有基因差异中，有一些在生物学上是重要的，赋予了我们说话和直立行走的能力，而其他的则没有明显的影响，这是由于从共同祖先分化而来的偶然突变的随机固定。同样，人们对鉴定自然种群中分离的有害/破坏生物功能的突变有着极大的兴趣。因为即使是关系密切的物种，也可能有数百万种遗传差异（其中大多数可能不显著），因此需要计算工具来识别那些最重要或最有趣的基因。这个项目的目标是开发统计模型，用于比较物种内部和物种之间的遗传变异模式，以确定哪些变化属于适应性（有益），中性或有害的类别。该项目的范围集中于发展数学模型和统计方法，以便使模型与日益增长的遗传数据相适应。该项目将重点分析人类、果蝇和其他“模型”生物种群的变异，其他群体正在收集大量数据集。这项工作更广泛的意义在于开发了计算机程序，其他科学家可以使用这些程序将开发的方法/模型应用于他们的数据。博士和博士后也将作为这些研究项目的工作结果而得到培训。特别的重点将放在涉及历史上代表性不足的少数民族研究生统计遗传学研究。这项工作在科学上的重要性在于，有可能发现包括人类及其近亲在内的物种之间有意义的遗传差异。

A central problem in evolutionary genetics is identifying genetic differences among populations of plants and animals that are biologically significant. For example, of all the genetic differences between humans and chimpanzees a few are biologically important and confer our ability to speak and walk upright while others have no discernable effect and are due to the random fixation of chance mutations since the divergence from a common ancestor. Likewise, there is tremendous interest in identifying mutations segregating in natural populations that are deleterious / disruptive of biological function. Since even for closely related species there are likely to be millions of genetic differences (most of which are likely non-significant), computational tools are needed for identifying those that are most important or interesting. The goal of this project is to develop statistical models for comparing patterns of genetic variation within and between species in order to identify which changes fall into adaptive (beneficial), neutral, or deleterious categories. The scope of the project is focused on development of mathematical models and statistical methods for fitting the models to the growing amount of genetic data. This project will focus on analyzing variation within populations of humans, Drosophila (fruit fly), and other ``model'' organisms where large data sets are being collected by other groups.The broader significance of this work is the development of computer programs that can be used by other scientists to apply the methods/ models developed to their data. Doctoral and post-doctoral students will also be trained as a result of working on these research projects. Special emphasis will be placed on involving historically underrepresented minority graduate students in statistical genetic research. The scientific importance of this work is the potential discovery of meaningful genetic differences between species including humans and their closest relatives.