Maximizing the Utility of Orthologs and Phylogenetic Profiles for Systems-Scale Comparative Genomics

哈佛大学获得了一笔拨款，用于开发一个免费的、可通过网络访问的系统，该系统可以最大程度地提供比较基因组学数据，并将其准确解码为有利于在整个基因组规模上进行进一步生物学研究的形式。具体来说，该项目将基于适当的相似性进化指标，使用改进的算法来构建迄今为止最大的直系同源库，用于识别直系同源物。全基因组直系同源数据将被汇总到系统发育谱矩阵中，从而实现一系列荟萃分析，包括基因组系统发育的重建以及蛋白质功能和网络组织的分析。该项目的具体任务包括（1）开发一种优化算法，以积累所有可用的完全测序基因组的直向同源物和进化距离数据库，其中包括来自信息量最大的参数空间的结果； (2) 开发一个平台，允许用户将所有上述直系同源数据聚合到系统发育谱矩阵中，重要的是，使用这些矩阵来研究蛋白质功能、网络组织和基因组进化； (3) 开发图形用户界面，以便世界各地的研究人员可以通过任何网络浏览器轻松访问该资源。最终产品将成为一种工具，使任何研究生物学家，无论其计算专业知识如何，都能够进行大规模的比较基因组学研究，探索基因之间的功能关系或基因组之间的系统发育关系。它作为比较基因组学和系统生物学培训工具的价值将通过一个由四部分组成的计划得到积极提升，其中包括培训研讨会、项目网页上的虚拟培训材料、与主要生物计算研讨会相关的教程以及哈佛医学院系统生物学系的新课程。

Harvard University is awarded a grant to develop a freely available, web-accessible system that makes comparative genomics data maximally available and accurately decoded into forms that facilitate further biological investigation at the scale of entire genomes. Specifically, the project will build the largest ortholog repository to date using an improved algorithm for identifying orthologs, based on appropriate evolutionary metrics of similarity. Whole-genome orthology data will be aggregated into matrices of phylogenetic profiles, enabling a series of meta-analyses including the reconstruction of genome phylogenies, and analysis of protein function and network organization. The project's specific tasks include (1) Development of an optimized algorithm to amass a database of orthologs and evolutionary distances for all available fully sequenced genomes that includes results from a maximally informative parameter space; (2) Development of a platform that allows a user to aggregate all of the above orthology data into matrices of phylogenetic profiles and, importantly, to use these matrices to study protein function, network organization and genomic evolution; and (3)Development of a graphical user interface to allow easy access to this resource by researchers world-wide from any web browser. The final product will be a tool to enable any research biologist, regardless of computational expertise, to conduct large-scale comparative genomics investigations that probe functional relationships among genes or phylogenetic relationships among genomes. Its value as a tool for training in comparative genomics and systems biology will be actively promoted through a four-part plan involving training workshops, virtual train materials on the project web page, tutorials associated with major biocomputing symposia, and new course offerings in the Department of Systems Biology at Harvard Medical School.