Collaborative Research: Novel Methodologies for Genome-Scale Evolutionary Analysis of Multi-Locus Data

合作研究：多位点数据基因组规模进化分析的新方法

• 批准号: 1062394
• 负责人: Noah Rosenberg
• 金额: $ 46.74万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 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
• 起止时间: 2011-07-01 至 2011-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1062394&HistoricalAwards=false
• 关键词: Collaborative; Research; Novel; Methodologies; Genome

Rice University, the University of Michigan, and the University of Texas at Austin are awarded collaborative grants to develop and implement algorithms and software tools for the analysis of gene genealogies and inference of species phylogenies from them. A gene genealogy, also known as gene tree, models how genes replicate and get transmitted from one generation to the next during evolution. A species phylogeny models how species arise and diverge. A species phylogeny is traditionally inferred by a three-step process: (1) a genomic region from the set of species under study is sequenced; (2) a "gene tree" is inferred for the genomic region; and, (3) the gene tree is declared to be the species tree. However, recent evolutionary genomic analyses of various groups of organisms have demonstrated that different genomic regions may have evolutionary histories that disagree with each other as well as with that of the species. Further, evolutionary processes such as horizontal gene transfer, result in network-like, rather than tree-like, species phylogenies. This joint project will develop accurate computational methods for determining the causes of gene tree discordance, and inferring species phylogenies (trees as well as networks) from gene trees despite their discordance. Special emphasis will be put on the efficiency of the methods so that they allow for analysis of genome-scale data sets. All methods will be implemented and extensively tested for performance. All methods developed will be made publicly available in software packages that we have been developing in the respective groups. The material will be integrated into courses that the PIs regularly teach at their respective institutions. Last but not least, the project will culminate with a two-day workshop, open to students and post-doctoral fellows from around the country, with presentations by the investigators on the methodologies developed, as well as hands-on tutorials on using the tools in analyzing data.

赖斯大学，密歇根大学和德克萨斯大学奥斯汀分校获得了合作赠款，以开发和实施算法和软件工具，用于分析基因家谱和从中分析物种系统发育。基因家谱，也称为基因树，在进化过程中如何复制并从一代复制并传播基因。物种的系统发育模型物种是如何出现和分歧的。传统上，由三步过程推断出物种系统发育：（1）测序了研究中的基因组区域； （2）基因组区域推断了“基因树”； （3）宣布基因树是物种树。然而，各种生物群的最新进化基因组分析表明，不同的基因组区域可能具有彼此不同意以及物种的进化史。此外，诸如水平基因转移之类的进化过程导致类似网络的，而不是类似树的物种系统发育。该联合项目将开发准确的计算方法，以确定基因树不一致的原因，并从基因树中推断出物种的系统发育（树和网络），尽管它们不一致。将特别重点放在方法的效率上，以便它们可以分析基因组规模的数据集。所有方法将被实施并进行广泛测试以进行性能。所有开发的方法都将在我们在各个组中开发的软件包中公开提供。这些材料将被整合到PIS定期在各自机构中教授的课程中。最后但并非最不重要的一点是，该项目将以为期两天的研讨会达到顶峰，向来自全国各地的学生和博士后研究员开放，调查人员就开发的方法论以及对使用工具进行分析数据的动物启动教程进行了演讲。