Figuring out genetic functional systems in Prokaryotes through computational genomics and metagenomics

提出的研究计划涉及两个问题：(1)由于一个物种内的原核基因组在基因含量方面表现出高度的可变性，并且由于这种基因差异可以区分无害的细菌菌株和致病的菌株，我们的目标是了解不同的基因集如何整合到宿主基因组的功能网络中。为此，我们将通过与知识数据库和文献进行比较，并通过寻找揭示功能网络插入点的模式，来检查高质量的计算预测关联。我们将集中讨论转录因子在基因组岛与宿主整合中的作用。(2)由于我们已经开发了强大的计算工具来预测原核生物基因组中的功能相互作用，并且有越来越多的半成品基因组和宏基因组序列，我们的目标是扩展这些工具，以预测任何序列中具有相同质量的相互作用，就像使用完整基因组时一样。这些预测将把未知的基因与我们熟知的功能联系起来，并为它们后来在实验室的表征提供线索。拟议的工作将使加拿大和世界受益，因为它为寻找具有相似功能的基因模块的不同版本提供了工具，从致病性到纤维素降解等工业感兴趣的功能。这些信息可能有助于找到对抗疾病的新方法，或指出用于生物技术应用的新基因。

The proposed research program is concerned to two problems: (1) Since prokaryotic genomes within a species show high variability in gene content, and since such gene differences can make the difference between a harmless bacterial strain and a pathogenic one, we aim at understanding how different gene sets incorporate into the functional network of their host genome. To this end, we will examine high-quality computationally predicted associations by comparing against knowledge databases and literature, and by finding patterns revealing points of insertion into functional networks. We will concentrate on the role of transcription factors in the integration of genomic islands to their hosts. (2) Since we have developed powerful computational tools for predicting functional interactions in prokaryotic genomes, and there is an increasing abundance of semi-finished genomes, and metagenomic sequences, we aim at expanding these tools towards predicting such interactions with the same quality in any sequences, as when using complete genomes. These predictions will associate unknown genes to well understood functions and provide hints for their later characterization in the laboratory. The proposed work will benefit Canada and the world by providing instruments for finding different versions of gene modules attaining similar functions, from pathogenicity to functions of interest to industry such as cellulose degradation. Such information might help finding new ways for combating disease, or point to novel genes for biotechnological applications.