Mapping of Post-Transcriptional Regulatory Networks by Means of Mechanistic and High Throughput Data

Post-transcriptional regulation of gene expression (PTR) is the process responsible for modulating mRNA levels and the related amount of protein. Initially thought to have a limited impact on cell phenotype, it has become increasingly recognized as a strong determinant of the quantitative changes in proteomes, and therefore a driving force for cell phenotypes. Untranslated regions of mRNAs (UTRs) are the core mediator of this process, containing sequence and structural elements bound by various kind of regulators, which influence nuclear export, localization, stability of mRNAs and their translation rates, as well as capping, alternative splicing and polyadenylation of the transcribed pre-mRNA. One of the most important classes of PTR factors are the RNA-binding proteins (RBPs), whose human genome complement is at least 800 genes, characterized by the presence of different functional domains. RBPs bind to the 5’UTR of a transcript often to modulate translation initiation, and to the 3’UTR usually to influence its stability or translatability. Another major group of actors in PTR are noncoding RNAs (ncRNAs). Among them are various classes of long ncRNAs (lncRNAs), the intensively studied microRNAs (miRNAs), siRNAs (small-interfering RNAs) and several other RNA types. miRNAs bind to 3’UTRs by means of short regions of perfect sequence complementation or with some mismatches. Both RBPs and ncRNAs bind mRNAs to the so-called cis-elements, found primarily in 5’ and 3’ UTRs. These elements can be represented as recurring RNA sequences or secondary structures to which the trans factors bind to exert a control over the mRNA. In order to integrate the available experimental data, we have developed AURA, a database offering a comprehensive view of the phenomena through regulatory data including RBP and miRNA binding sites, cis-element annotations, secondary structures, phylogenetic conservation, SNPs, RNA-editing data, gene expression profiles and more. A dynamic graphical interface allows the user to browse through the UTRs in an easy and seamless way. To further enrich this body of data, we also implemented a pipeline for the identification of hyperconserved elements in human UTRs, which we applied to both 5’ and 3’UTRs. We were thus able to recover known and novel PTR mechanisms involving RBPs, including an RBP network controlled by HuR. We are eventually applying the results of these works to infer altered, and thus potentially disease-related, PTR mechanisms in an highthroughput neuroblastoma dataset.