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Coalescent-based Species Tree Inference Using Algebraic Statistics

Coalescent-based Species Tree Inference Using Algebraic Statistics
使用代数统计进行基于合并的物种树推理
批准号:
1106706
负责人:
Laura Kubatko
金额:
$18.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2011
资助国家:
美国
项目状态:
已结题
起止时间:
2011-10-01 至 2016-09-30

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中文摘要
翻译
由于获得DNA序列数据越来越容易,目前的许多系统发育涉及使用一组取样生物体的代表性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中提取的样本,因此有必要在两个不同的尺度上模拟进化过程。首先,给定一个代表物种实际进化历史的整体系统发育,单个基因进化自己的历史,称为基因树。然后,沿着每个基因树,序列数据进化,导致用于推理的观察数据。聚结模型提供了给定物种树的基因树的进化和给定基因树的序列数据的进化之间的联系。系统发育不变量已被提出作为使用单基因数据推断系统发育的工具,但尚未在多基因聚合设置中进行研究。研究人员使用系统发育不变量来研究物种树推理的聚结模型,解决诸如树和相关模型参数的可识别性等问题。此外,他们还开发和实现了利用系统发育不变量从经验DNA序列数据估计物种树的方法。基于包含在生物体DNA序列中的信息来推断生物体的进化史是进化生物学中一个非常重要的问题。基因组测序项目产生的大量DNA序列数据导致了这些系统发育关系推断的重大挑战。这些挑战之一是基于来自基因组中几个不同基因的DNA序列信息来推断物种集合的进化史。该项目的两个主要目标是:(1)确定在给定典型DNA序列数据集中可用的信息的情况下,可以准确识别真实系统发育历史的哪些方面;(2)开发从DNA序列中提取可用信息的方法,以便准确有效地估计真正的进化关系。这两个目标都是使用代数统计方法来实现的。
英文摘要
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.
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