SARNAclust: Semi-automatic detection of RNA protein binding motifs from immunoprecipitation data

Regulated dicing of pre-mir-144 via reshaping of its terminal loop

Although the route to generate microRNAs (miRNAs) is often depicted as a linear series of sequential and constitutive cleavages, we now appreciate multiple alternative pathways as well as diverse strategies to modulate their processing and function. Here, we identify an unusually profound regulatory role of conserved loop sequences in vertebrate pre-mir-144, which are essential for its cleavage by the Dicer RNase III enzyme in human and zebrafish models. Our data indicate that pre-mir-144 dicing is positively regulated via its terminal loop, and involves the ILF3 complex (NF90 and its partner NF45/ILF2). We provide further evidence that this regulatory switch involves reshaping of the pre-mir-144 apical loop into a structure that is appropriate for Dicer cleavage. In light of our recent findings that mir-144 promotes the nuclear biogenesis of its neighbor mir-451, these data extend the complex hierarchy of nuclear and cytoplasmic regulatory events that can control the maturation of clustered miRNAs.

RNANetMotif: Identifying sequence-structure RNA network motifs in RNA-protein binding sites

RNA molecules can adopt stable secondary and tertiary structures, which are essential in mediating physical interactions with other partners such as RNA binding proteins (RBPs) and in carrying out their cellular functions. In vivo and in vitro experiments such as RNAcompete and eCLIP have revealed in vitro binding preferences of RBPs to RNA oligomers and in vivo binding sites in cells. Analysis of these binding data showed that the structure properties of the RNAs in these binding sites are important determinants of the binding events; however, it has been a challenge to incorporate the structure information into an interpretable model. Here we describe a new approach, RNANetMotif, which takes predicted secondary structure of thousands of RNA sequences bound by an RBP as input and uses a graph theory approach to recognize enriched subgraphs. These enriched subgraphs are in essence shared sequence-structure elements that are important in RBP-RNA binding. To validate our approach, we performed RNA structure modeling via coarse-grained molecular dynamics folding simulations for selected 4 RBPs, and RNA-protein docking for LIN28B. The simulation results, e.g., solvent accessibility and energetics, further support the biological relevance of the discovered network subgraphs.

RNA binding proteins (RBPs) regulate every aspect of RNA biology, including splicing, translation, transportation, and degradation. High-throughput technologies such as eCLIP have identified thousands of binding sites for a given RBP throughout the genome. It has been shown by earlier studies that, in addition to nucleotide sequences, the structure and conformation of RNAs also play important role in RBP-RNA interactions. Analogous to protein-protein interactions or protein-DNA interactions, it is likely that there exist intrinsic sequence-structure motifs common to these RNAs that underlie their binding specificity to specific RBPs. It is known that RNAs form energetically favorable secondary structures, which can be represented as graphs, with nucleotides being nodes and backbone covalent bonds and base-pairing hydrogen bonds representing edges. We hypothesize that these graphs can be mined by graph theory approaches to identify sequence-structure motifs as enriched sub-graphs. In this article, we described the details of this approach, termed RNANetMotif and associated new concepts, namely EKS (Extended K-mer Subgraph) and GraphK graph algorithm. To test the utility of our approach, we conducted 3D structure modeling of selected RNA sequences through molecular dynamics (MD) folding simulation and evaluated the significance of the discovered RNA motifs by comparing their spatial exposure with other regions on the RNA. We believe that this approach has the novelty of treating the RNA sequence as a graph and RBP binding sites as enriched subgraph, which has broader applications beyond RBP-RNA interactions.

Codon bias confers stability to human mRNAs

Codon bias has been implicated as one of the major factors contributing to mRNA stability in several model organisms. However, the molecular mechanisms of codon bias on mRNA stability remain unclear in humans. Here, we show that human cells possess a mechanism to modulate RNA stability through a unique codon bias. Bioinformatics analysis showed that codons could be clustered into two distinct groups-codons with G or C at the third base position (GC3) and codons with either A or T at the third base position (AT3): the former stabilizing while the latter destabilizing mRNA. Quantification of codon bias showed that increased GC3-content entails proportionately higher GC-content. Through bioinformatics, ribosome profiling, and in vitro analysis, we show that decoupling the effects of codon bias reveals two modes of mRNA regulation, one GC3- and one GC-content dependent. Employing an immunoprecipitation-based strategy, we identify ILF2 and ILF3 as RNA-binding proteins that differentially regulate global mRNA abundances based on codon bias. Our results demonstrate that codon bias is a two-pronged system that governs mRNA abundance.

Biological functions, regulatory mechanisms, and disease relevance of RNA localization pathways

The asymmetric subcellular distribution of RNA molecules from their sites of transcription to specific compartments of the cell is an important aspect of post-transcriptional gene regulation. This involves the interplay of intrinsic cis-regulatory elements within the RNA molecules with trans-acting RNA-binding proteins and associated factors. Together, these interactions dictate the intracellular localization route of RNAs, whose downstream impacts have wide-ranging implications in cellular physiology. In this review, we examine the mechanisms underlying RNA localization and discuss their biological significance. We also review the growing body of evidence pointing to aberrant RNA localization pathways in the development and progression of diseases.