doRiNA: a database of RNA interactions in post-transcriptional regulation

Abstract

In animals, RNA binding proteins (RBPs) and microRNAs (miRNAs) post-transcriptionally regulate the expression of virtually all genes by binding to RNA. Recent advances in experimental and computational methods facilitate transcriptome-wide mapping of these interactions. It is thought that the combinatorial action of RBPs and miRNAs on target mRNAs form a post-transcriptional regulatory code. We provide a database that supports the quest for deciphering this regulatory code. Within doRiNA, we are systematically curating, storing and integrating binding site data for RBPs and miRNAs. Users are free to take a target (mRNA) or regulator (RBP and/or miRNA) centric view on the data. We have implemented a database framework with short query response times for complex searches (e.g. asking for all targets of a particular combination of regulators). All search results can be browsed, inspected and analyzed in conjunction with a huge selection of other genome-wide data, because our database is directly linked to a local copy of the UCSC genome browser. At the time of writing, doRiNA encompasses RBP data for the human, mouse and worm genomes. For computational miRNA target site predictions, we provide an update of PicTar predictions.

CLIP: viewing the RNA world from an RNA-protein interactome perspective

“…There are also some databases that allow for collecting and visualizing CLIP data, such as CLIPZ [41], doRiNA [42] and starBase [43,44]. StarBase v 2.0 is the most comprehensive CLIP database, which integrates 108 CLIP-Seq (HITS-CLIP, PAR-CLIP, iCLIP, CLASH) datasets of different RBPs.…”

Tuning the engine

“…It contains analytical tools to let the user load and analyze the own CLIP-seq data, identify binding sites and annotate them on the reference genome. UTRdb/UTRsite, 12 AURA 13 and doRiNA 31 hold RBPrelated data as the two resources described above, but they differ in still keeping a broader perspective on post-transcriptional regulation. UTRdb/UTRsite contains data about UTRs in a number of species, annotating them with a specific subset of RBP binding sites, cis-regulatory sequence patterns, miRNAs and elements are the AU-Rich Elements (ARE), 10 motifs rich in Us with some interspersed As or Gs shared by several thousand 3'UTRs and bound by a large number of RBPs of which at least 23 are known.…”

“…They can be RBP-oriented when they deal with RBPs and the effect these exert on mRNAs, ncRNAoriented when they analyze regulation by the various families of calculated UTR secondary structures, and experimental mRNA and protein levels; visualization of joint gene expression data of targets and associated regulators can also aid inference of regulatory events. doRiNA 31 integrates RBP and miRNA binding sites, by including only high-throughput assays-derived data sets for RBPs and a set of predictions for miRNAs. It exploits the UCSC database genome viewer annotated with binding sites, offering SNP data.…”

“…A more limited variety of resources dedicated to RBPs, cis-elements and others ncRNAs is also available. Only three tools, among the ones we analyzed, attempt to integrate different component of these networks: RBPs and miRNA binding sites only, 31 or including also predicted RNA secondary structures and cis-elements. 12,13 While these resources considerably ease the task of hypothesizing the existence of new networks, they still contain just a fraction of the data really available in the literature, and obviously are affected by the small number of trans-factor experimentally tested in a high throughput way with respect to the annotated ones.…”

“…[25][26][27][28][29][30] Furthermore, a small number of resources integrating different data types is available. 12,13,31 Predictive tools also exist, in particular for cis-elements pattern-based search 32,33 and ncRNAs. [34][35][36][37][38][39] This review will first introduce the foremost available resources, excluding those related to splicing and the no longer updated ones, and will catalog them in three categories: RBP-oriented, ncRNA-oriented and ciselement-oriented, with a number of resources falling in more than one category (Fig.…”