Coalescent-based Species Tree Inference Using Algebraic Statistics

由于获得DNA序列数据变得越来越容易，目前的许多系统发育学涉及使用一组采样生物体的代表性DNA序列中包含的信息进行估计。可用于系统发育分析的序列数据通常包括从每个生物体内的多个基因获取的样本，因此有必要在两个不同的尺度上对进化过程进行建模。首先，给定代表物种实际进化历史的总体系统发育图，单个基因进化它们自己的历史，称为基因树。然后，沿着每个基因树，序列数据进化，合并模型提供了给定物种树的基因树的进化与给定基因树的序列数据的进化之间的联系。系统发育不变量已经被提出作为一种工具来利用来自单基因的数据来推断系统发育，但还没有在多基因合并的背景下进行研究。研究人员使用系统发育不变量来研究物种树推理的合并模型，解决了树的可识别性和相关模型参数等问题。此外，他们还开发和实现了利用系统发育不变量从经验DNA序列数据中估计物种树的方法。基于DNA序列中包含的信息来推断一组生物的进化历史是进化生物学中一个基本的重要问题。基因组测序项目产生的丰富的DNA序列数据导致了对这些系统发育关系推断的重大挑战。这些挑战之一是根据从整个基因组中采样的几个不同基因的DNA序列信息来推断一组物种的进化史。这个项目的两个主要目标是：(1)确定在给定典型DNA序列数据集中的可用信息的情况下，真实系统发育历史的哪些方面可以被准确识别；(2)开发从DNA序列中提取可用信息的方法，以便准确和有效地估计真实的进化关系。这两个目标都是使用代数统计学的方法来实现的。

Due to the increasing ease with which DNA sequence data can be obtained, much of current phylogenetics involves use of  the information contained in representative DNA sequences for a set of sampled organisms for estimation.  The sequence data available for a phylogenetic analysis often include samples taken from multiple genes within each organism, and thus it becomes necessary to model the evolutionary process at two distinct scales.  First, given an overall phylogeny representing the actual evolutionary history of the species, individual genes evolve their own histories, called gene trees.  Then, along each gene tree, sequence data evolve, leading to the observed data that is used for inference.  The coalescent model provides the link between the evolution of the gene trees given the species tree, and the evolution of the sequence data given the gene trees. Phylogenetic invariants have been proposed as a tool for inferring phylogenies using data from a single gene, but have not been studied in the multi-gene coalescent setting. The investigators use phylogenetic invariants to study the coalescent model for species tree inference by addressing questions such as the identifiability of the tree and associated model parameters. In addition, they develop and implement methods to utilize phylogenetic invariants to estimate species trees from empirical DNA sequence data.The inference of the evolutionary history of a collection of organisms based on the information contained in their DNA sequences is a problem of fundamental importance in evolutionary biology. The abundance of DNA sequence data arising from genome sequencing projects has led to significant challenges in the inference of these phylogenetic relationships. Among these challenges is the inference of the evolutionary history of a collection of species based on DNA sequence information from several distinct genes sampled throughout the genome. The two primary goals of this project are: (1) to determine what aspects of the true phylogenetic history can be accurately identified given the information available in typical DNA sequence data sets; (2) to develop methods for extracting the available information from the DNA sequences in order to accurately and efficiently estimate the true evolutionary relationships.  Both of these objectives are approached using methods from algebraic statistics.