ABI Innovation: Collaborative Research: Novel Methodologies for Genome-scale Evolutionary Analysis of Multi-locus Data

ABI 创新：协作研究：多位点数据基因组规模进化分析的新方法

• 批准号: 1062463
• 负责人: Luay Nakhleh
• 金额: $ 42.5万
• 依托单位: William Marsh Rice University
• 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 2015-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1062463&HistoricalAwards=false
• 关键词: ABI; Innovation; Collaborative; Research; Novel

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.

莱斯大学、密歇根大学和德克萨斯大学奥斯汀分校获得合作赠款，用于开发和实施算法和软件工具，以分析基因谱系并从中推断物种的遗传。基因谱系，也称为基因树，模拟了基因在进化过程中如何复制和从一代传递到下一代。一个物种进化模型是物种如何产生和分化的。传统上通过三步过程来推断物种的进化：（1）对来自所研究的物种集合的基因组区域进行测序;（2）推断基因组区域的“基因树”;以及（3）将基因树宣布为物种树。然而，最近对不同生物群体的进化基因组分析表明，不同的基因组区域可能具有相互不一致的进化历史，以及与物种的进化历史。此外，进化过程，如水平基因转移，导致网络状，而不是树状，物种共生。该联合项目将开发精确的计算方法，以确定基因树不一致的原因，并从基因树中推断物种的遗传（树以及网络），尽管它们不一致。将特别强调这些方法的效率，以便能够分析基因组规模的数据集。所有方法都将得到实施，并进行广泛的性能测试。所有开发的方法都将以我们在各个小组开发的软件包的形式公开提供。这些材料将被纳入方案研究员在各自机构定期讲授的课程。最后但并非最不重要的是，该项目将以为期两天的研讨会结束，向来自全国各地的学生和博士后研究员开放，研究人员将介绍所开发的方法，以及使用工具分析数据的实践教程。