Predicting Protein Function with Hierarchical Phylogenetic Profiles: The Gene3D Phylo-Tuner Method Applied to Eukaryotic Genomes

@article{citeulike:2084644, abstract = {\&\#8220;Phylogenetic profiling\&\#8221; is based on the hypothesis that during evolution functionally or physically interacting genes are likely to be inherited or eliminated in a codependent manner. Creating presence\&\#8211;absence profiles of orthologous genes is now a common and powerful way of identifying functionally associated genes. In this approach, correctly determining orthology, as a means of identifying functional equivalence between two genes, is a critical and nontrivial step and largely explains why previous work in this area has mainly focused on using presence\&\#8211;absence profiles in prokaryotic species. Here, we demonstrate that eukaryotic genomes have a high proportion of multigene families whose phylogenetic profile distributions are poor in presence\&\#8211;absence information content. This feature makes them prone to orthology mis-assignment and unsuited to standard profile-based prediction methods. Using CATH structural domain assignments from the Gene3D database for 13 complete eukaryotic genomes, we have developed a novel modification of the phylogenetic profiling method that uses genome copy number of each domain superfamily to predict functional relationships. In our approach, superfamilies are subclustered at ten levels of sequence identity\&\#8212;from 30\&\#37; to 100\&\#37;\&\#8212;and phylogenetic profiles built at each level. All the profiles are compared using normalised Euclidean distances to identify those with correlated changes in their domain copy number. We demonstrate that two protein families will \&\#8220;auto-tune\&\#8221; with strong co-evolutionary signals when their profiles are compared at the similarity levels that capture their functional relationship. Our method finds functional relationships that are not detectable by the conventional presence\&\#8211;absence profile comparisons, and it does not require a priori any fixed criteria to define orthologous genes.}, author = {Ranea, Juan A. and Yeats, Corin and Grant, Alastair and Orengo, Christine A. }, citeulike-article-id = {2084644}, doi = {http://dx.doi.org/10.1371/journal.pcbi.0030237}, journal = {PLoS Computational Biology}, keywords = {eukaryota, genome, hierarchical, phylogeny, prediction, protein}, month = {November}, number = {11}, pages = {e237+}, posted-at = {2007-12-10 04:43:48}, priority = {3}, title = {Predicting Protein Function with Hierarchical Phylogenetic Profiles: The Gene3D Phylo-Tuner Method Applied to Eukaryotic Genomes}, url = {http://dx.doi.org/10.1371/journal.pcbi.0030237}, volume = {3}, year = {2007} }

TY - JOUR ID - citeulike:2084644 L3 - citeulike-article-id:2084644 TI - Predicting Protein Function with Hierarchical Phylogenetic Profiles: The Gene3D Phylo-Tuner Method Applied to Eukaryotic Genomes JF - PLoS Computational Biology VL - 3 IS - 11 SP - e237 N2 - “Phylogenetic profiling” is based on the hypothesis that during evolution functionally or physically interacting genes are likely to be inherited or eliminated in a codependent manner. Creating presence–absence profiles of orthologous genes is now a common and powerful way of identifying functionally associated genes. In this approach, correctly determining orthology, as a means of identifying functional equivalence between two genes, is a critical and nontrivial step and largely explains why previous work in this area has mainly focused on using presence–absence profiles in prokaryotic species. Here, we demonstrate that eukaryotic genomes have a high proportion of multigene families whose phylogenetic profile distributions are poor in presence–absence information content. This feature makes them prone to orthology mis-assignment and unsuited to standard profile-based prediction methods. Using CATH structural domain assignments from the Gene3D database for 13 complete eukaryotic genomes, we have developed a novel modification of the phylogenetic profiling method that uses genome copy number of each domain superfamily to predict functional relationships. In our approach, superfamilies are subclustered at ten levels of sequence identity—from 30% to 100%—and phylogenetic profiles built at each level. All the profiles are compared using normalised Euclidean distances to identify those with correlated changes in their domain copy number. We demonstrate that two protein families will “auto-tune” with strong co-evolutionary signals when their profiles are compared at the similarity levels that capture their functional relationship. Our method finds functional relationships that are not detectable by the conventional presence–absence profile comparisons, and it does not require a priori any fixed criteria to define orthologous genes. KW - eukaryota KW - genome KW - hierarchical KW - phylogeny KW - prediction KW - protein AU - Ranea, Juan AU - Yeats, Corin AU - Grant, Alastair AU - Orengo, Christine PY - 2007/11/01/ UR - http://dx.doi.org/10.1371/journal.pcbi.0030237 ER -