The Bologna Annotation Resource: a Non Hierarchical Method for the Functional and Structural Annotation of Protein Sequences Relying on a Comparative Large-Scale Genome Analysis

Abstract

Protein sequence annotation is a major challenge in the postgenomic era. Thanks to the availability of complete genomes and proteomes, protein annotation has recently taken invaluable advantage from cross-genome comparisons. In this work, we describe a new non hierarchical clustering procedure characterized by a stringent metric which ensures a reliable transfer of function between related proteins even in the case of multidomain and distantly related proteins. The method takes advantage of the comparative analysis of 599 completely sequenced genomes, both from prokaryotes and eukaryotes, and of a GO and PDB/SCOP mapping over the clusters. A statistical validation of our method demonstrates that our clustering technique captures the essential information shared between homologous and distantly related protein sequences. By this, uncharacterized proteins can be safely annotated by inheriting the annotation of the cluster. We validate our method by blindly annotating other 201 genomes and finally we develop BAR (the Bologna Annotation Resource), a prediction server for protein functional annotation based on a total of 800 genomes (publicly available at http://microserf.biocomp.unibo.it/bar/).

Extended and Robust Protein Sequence Annotation over Conservative Nonhierarchical Clusters

“…A previous version of our method was already described and validated [Bartoli et al 2009] and here we use, after updating, a complementary and independent annotation resource recently developed (BAR+) [Piovesan et al 2011]. Similarly to BAR, BAR+ is also a nonhierarchical clustering method relying on a comparative large-scale genome analysis.…”

“…This procedure largely increases the number of sequences that can be annotated by annotation transfer in a set of 988 genomes [Bartoli et al 2009]. When in a given cluster distantly related sequences from different genomes coexist, the procedure allows a safe transfer of annotation both for structure and function, independently of the level of sequence identity.…”

BAR-PLUS: the Bologna Annotation Resource Plus for functional and structural annotation of protein sequences

“…For the sake of comparison, we also used the entire SwissProt 03_2011 (8 March). Similarly to BAR (11), BAR + is also a non-hierarchical clustering method relying on a comparative large-scale genome analysis. The method relies on a non-hierarchical clustering procedure characterized by a stringent metric that ensures a reliable transfer of features within clusters.…”

“…Proteins with different combinations of shared domains can have different molecular and biological functions, as recently re-discussed (10). In order to address these problems, we developed BAR (11), an annotation procedure that relies on a non-hierarchical clustering method and a large-scale genome comparison where pairs of sequences are selected with very strict criteria of similarity and overlapping of the alignment as described in the next section. We provided statistical validation that BAR allows reliable functional and structural annotation in addition to that given by commonly used databases (11).…”

“…In order to address these problems, we developed BAR (11), an annotation procedure that relies on a non-hierarchical clustering method and a large-scale genome comparison where pairs of sequences are selected with very strict criteria of similarity and overlapping of the alignment as described in the next section. We provided statistical validation that BAR allows reliable functional and structural annotation in addition to that given by commonly used databases (11). Here, we introduce BAR + , an updated and extended version of BAR that includes: (i) a 5-fold increase in sequences; (ii) GO terms from the three main roots (molecular function, biological process and cellular localization; http://www.geneontology.org/); (iii) Pfam domains (http://pfam.sanger.ac.uk/); (iv) known ligands and (v) for clusters containing PDB structure/s, a Cluster HMM model and the corresponding alignment of the target sequence to the optimal template in the cluster for computing its 3D structure.…”