WNP: A Novel Algorithm for Gene Products Annotation from Weighted Functional Networks

Predicting the biological function of all the genes of an organism is one of the fundamental goals of computational system biology. In the last decade, high-throughput experimental methods for studying the functional interactions between gene products (GPs) have been combined with computational approaches based on Bayesian networks for data integration. The result of these computational approaches is an interaction network with weighted links representing connectivity likelihood between two functionally related GPs. The weighted network generated by these computational approaches can be used to predict annotations for functionally uncharacterized GPs. Here we introduce Weighted Network Predictor (WNP), a novel algorithm for function prediction of biologically uncharacterized GPs. Tests conducted on simulated data show that WNP outperforms other 5 state-of-the-art methods in terms of both specificity and sensitivity and that it is able to better exploit and propagate the functional and topological information of the network. We apply our method to Saccharomyces cerevisiae yeast and Arabidopsis thaliana networks and we predict Gene Ontology function for about 500 and 10000 uncharacterized GPs respectively

Trm112 is required for Bud23-mediated methylation of the 18S rRNA at position G1575.

Posttranscriptional and posttranslational modification of macromolecules is known to fine-tune their functions. Trm112 is unique, acting as an activator of both tRNA and protein methyltransferases. Here we report that in Saccharomyces cerevisiae, Trm112 is required for efficient ribosome synthesis and progression through mitosis. Trm112 copurifies with pre-rRNAs and with multiple ribosome synthesis trans-acting factors, including the 18S rRNA methyltransferase Bud23. Consistent with the known mechanisms of activation of methyltransferases by Trm112, we found that Trm112 interacts directly with Bud23 in vitro and that it is required for its stability in vivo. Consequently, trm112Δ cells are deficient for Bud23-mediated 18S rRNA methylation at position G1575 and for small ribosome subunit formation. Bud23 failure to bind nascent preribosomes activates a nucleolar surveillance pathway involving the TRAMP complexes, leading to preribosome degradation. Trm112 is thus active in rRNA, tRNA, and translation factor modification, ideally placing it at the interface between ribosome synthesis and function.Journal ArticleResearch Support, Non-U.S. Gov'tSCOPUS: ar.jinfo:eu-repo/semantics/publishe