Wu Hongwei, Mao Fenglou, Olman Victor, Xu Ying
School of Electrical and Computer Engineering, Georgia Institute of Technology, Savannah, GA 31407, USA.
Comput Biol Chem. 2008 Jun;32(3):176-84. doi: 10.1016/j.compbiolchem.2008.02.007. Epub 2008 Mar 2.
Functional classification of genes represents one of the most basic problems in genome analysis and annotation. Our analysis of some of the popular methods for functional classification of genes shows that these methods are not always consistent with each other and may not be specific enough for high-resolution gene functional annotations. We have developed a method to integrate genomic neighborhood information of genes with their sequence similarity information for the functional classification of prokaryotic genes. The application of our method to 93 proteobacterial genomes has shown that (i) the genomic neighborhoods are much more conserved across prokaryotic genomes than expected by chance, and such conservation can be utilized to improve functional classification of genes; (ii) while our method is consistent with the existing popular schemes as much as they are among themselves, it does provide functional classification at higher resolution and hence allows functional assignments of (new) genes at a more specific level; and (iii) our method is fairly stable when being applied to different genomes.
基因的功能分类是基因组分析和注释中最基本的问题之一。我们对一些常用的基因功能分类方法的分析表明,这些方法并不总是相互一致,对于高分辨率的基因功能注释可能不够特异。我们开发了一种方法,将基因的基因组邻域信息与其序列相似性信息整合起来,用于原核生物基因的功能分类。我们的方法应用于93个变形菌门基因组,结果表明:(i)基因组邻域在原核生物基因组中比随机预期的更为保守,这种保守性可用于改进基因的功能分类;(ii)虽然我们的方法与现有的常用方案尽可能保持一致,但它确实能提供更高分辨率的功能分类,从而能在更具体的水平上对(新)基因进行功能分配;(iii)我们的方法应用于不同基因组时相当稳定。