HCG: a database for hierarchical classification of functionally equivalent genes in prokaryotes

Background: The existing gene annotation schemes generally classify genes into twolevels of parallel and unrelated homologous and/or orthologous gene groups, limiting our capabilities for gene function prediction at higher resolution. While homology and orthology are useful concepts for evolutionary studies of genes, they may not be the most appropriate ones for functional classification of genes, especially at a high-resolution level. Results: We present a new gene annotation database: the hierarchical classification system of genes (HCG), which provides functional annotation of prokaryotic genes in general at higher resolution than the existing functional classification schemes. The HCG database consists of clusters, hierarchically organized, of functionally equivalent genes at varying levels of resolution. Gene clusters at the top of the HCG hierarchy representing homologous gene groups and descendent gene clusters representing functionally equivalent genes at an increasingly higher resolution going down from the top to the leaflevel clusters along the classification hierarchy. We also provide several examples to demonstrate how HCG can be used to make specific gene function annotation. For each HCG cluster, we provide a p-value assessing the statistical significance in grouping its genes together, based on the functional relationship among its genes and their relationship with genes outside of the cluster. Conclusion: The HCG database, implemented using MySQL, currently consists of 658,174 genes, 51,205 clusters organized into 21,109 trees, from 224 prokaryotic genomes. The on-line database supports four search capabilities, namely (1) browsing HCG classification by trees, (2) browsing HCG classification by organisms, (3) querying