Computational Methods for Detecting Natural Selection using Comparative Population Genomic Data

进化遗传学中的一个中心问题是识别具有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遗传差异中，有几个是生物学上重要的，赋予了我们说话和直立行走的能力，而其他的没有明显的影响，是由于与共同祖先的分歧而随机固定的随机突变。同样，人们对识别自然种群中分离的有害/破坏生物功能的突变也有极大的兴趣。由于即使是关系密切的物种，也可能存在数以百万计的遗传差异(其中大多数可能不显著)，因此需要计算工具来识别最重要或最有趣的那些。该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)、中性或有害类别。该项目的范围集中在开发数学模型和统计方法，使模型适应不断增长的遗传数据。这个项目将集中于分析人类、果蝇(果蝇)和其他被其他群体收集大量数据集的“模型”生物体的种群内的变异。这项工作的更广泛的意义是开发计算机程序，其他科学家可以使用这些程序来应用开发的方法/模型来处理他们的数据。从事这些研究项目的博士后和博士后也将接受培训。将特别强调让历史上代表性不足的少数族裔研究生参与统计遗传学研究。这项工作的科学重要性在于可能发现包括人类在内的物种及其近亲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.