AF: Medium: Statistical Inference of Complex Evolutionary Histories

基因是所有生命形式的基本组成部分。了解基因如何进化和多样化其功能将大大有助于阐明生物学中的许多现象和过程，包括疾病如何出现和如何治疗。基因经历了从小规模的进化事件（例如，一个核苷酸被另一个替换）到大规模的（例如，一个基因被复制，导致同一基因的不止一个拷贝）。准确识别不同基因家族的这些进化事件是本项目的重点。特别是，该项目旨在设计数学模型，计算技术和软件产品，用于根据各种进化过程绘制基因随时间的轨迹。该项目将对生物学和生物医学产生影响，将产生公开的软件产品，使新的分析，并将培养学生在计算机科学，统计学和生物学的交叉点。推断物种的准确进化历史或进化史是进化生物学的一项主要奋进，对生物学的各个方面都有影响。这种推断通常是通过从被调查物种的基因组中对某个感兴趣的区域进行测序，为该区域建立一个谱系或基因树，并宣布该树是物种的谱系。在后基因组时代，这种做法已被利用数百个基因组区域所取代。虽然这种新的做法有望产生更准确的估计物种的进化，它也带来了一个新的重大挑战，即占不同的进化过程，可能同时作用于不同的基因组区域。在后基因组进化分析中，有三个进化过程是突出的：不完全谱系分类（ILS）、水平转移（或基因流动）和基因复制/丢失（GDL）。目前，没有统计方法存在的任务，推断基因和基因组的进化关系，同时占所有这三个过程。该项目的首要目标是为这项任务开发数学模型和算法技术。拟议的项目将产生数学和算法结果，以及开源软件，使物种遗传推断从全基因组数据，同时占ILS，基因流和GDL。

Genes are an essential building block of all forms of life. Understanding how genes evolve and diversify their function would contribute significantly to elucidating many phenomena and processes in biology, including how diseases emerge and how to treat them. Genes undergo evolutionary events that range from small-scale ones (e.g., one nucleotide is replaced by another) to large-scale ones (e.g., a gene gets duplicated resulting in more than one copy of the same gene). Accurately identifying these evolutionary events for different gene families is the focus of this project. In particular, the project is aimed at devising mathematical models, computational techniques, and software products for mapping the trajectory of a gene through time in light of a variety of evolutionary processes. The project will have impact on biology and biomedicine, will result in publicly available software products that enable new analyses, and will train students at the intersection of computer science, statistics, and biology. Inferring accurate evolutionary histories, or phylogenies, of species is a major endeavor in evolutionary biology, and has implications on all aspects of biology. This inference used to be conducted by sequencing a certain region of interest from the genomes of species under investigation, building a genealogy, or gene tree, for the region, and declaring the tree to be the species phylogeny. In the post-genomic era, this practice has been replaced by utilizing hundreds of genomic regions. While this new practice promises to yield more accurate estimates of the species phylogeny, it also gives rise to a new major challenge, namely accounting for the different evolutionary processes that could be acting simultaneously on the different genomic regions. In particular, three evolutionary processes have been prominent in post-genomic evolutionary analysis: incomplete lineage sorting (ILS), horizontal transfer (or, gene flow), and gene duplication/loss (GDL). Currently, no statistical methods exist for the task of inferring evolutionary relationships of genes and genomes while accounting for all these three processes simultaneously. The overarching goal of the project is to develop mathematical models and algorithmic techniques for this task. The proposed project will produce mathematical and algorithmic results, as well as open-source software that would enable species phylogeny inference from genome-wide data while simultaneously accounting for ILS, gene flow, and GDL.