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

拟议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显示出高度的基因含量变异性，并且由于这种基因差异可以决定无害细菌菌株和致病细菌菌株之间的差异，我们旨在了解不同的基因集如何整合到它们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。我们将集中于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完成基因组和元基因组序列，我们的目标是将这些工具扩展到预测任何序列中与使用完整基因组时相同质量的这种相互作用。这些预测将把未知基因与人们熟知的功能联系起来，并为以后在实验室中对其进行表征提供线索。拟议的工作将使加拿大和世界受益，因为它提供了工具，用于寻找实现类似功能的不同版本的基因模块，从致病功能到工业感兴趣的功能，如纤维素降解。这些信息可能有助于找到抗击疾病的新方法，或者为生物技术应用指明新的基因。

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.