Despite studies that have investigated the interactions of double-stranded RNA-binding proteins like Staufen with RNA in vitro, how they achieve target specificity in vivo remains uncertain. We performed RNA co-immunoprecipitations followed by microarray analysis to identify Staufen-associated mRNAs in early Drosophila embryos. Analysis of the localization and functions of these transcripts revealed a number of potentially novel roles for Staufen. Using computational methods, we identified two sequence features that distinguish Staufen's target transcripts from non-targets. First, these Drosophila transcripts, as well as those human transcripts bound by human Staufen1 and 2, have 3' untranslated regions (UTRs) that are 3-4-fold longer than unbound transcripts. Second, the 3'UTRs of Staufen-bound transcripts are highly enriched for three types of secondary structures. These structures map with high precision to previously identified Staufen-binding regions in Drosophila bicoid and human ARF1 3'UTRs. Our results provide the first systematic genome-wide analysis showing how a double-stranded RNA-binding protein achieves target specificity.

In eukaryotes, RNA-binding proteins that contain multiple K homology (KH) domains play a key role in coordinating the different steps of RNA synthesis, metabolism and localization. Understanding how the different KH modules participate in the recognition of the RNA targets is necessary to dissect the way these proteins operate. We have designed a KH mutant with impaired RNA-binding capability for general use in exploring the role of individual KH domains in the combinatorial functional recognition of RNA targets. A double mutation in the hallmark GxxG loop (GxxG-to-GDDG) impairs nucleic acid binding without compromising the stability of the domain. We analysed the impact of the GDDG mutations in individual KH domains on the functional properties of KSRP as a prototype of multiple KH domain-containing proteins. We show how the GDDG mutant can be used to directly link biophysical information on the sequence specificity of the different KH domains of KSRP and their role in mRNA recognition and decay. This work defines a general molecular biology tool for the investigation of the function of individual KH domains in nucleic acid binding proteins.

Lineage-determining transcription factors (LD-TFs) drive the differentiation of progenitor cells into a specific lineage. In CD4+ T cells, T-bet dictates differentiation of the TH1 lineage, whereas GATA3 drives differentiation of the alternative TH2 lineage. However, LD-TFs, including T-bet and GATA3, are frequently co-expressed but how this affects LD-TF function is not known. By expressing T-bet and GATA3 separately or together in mouse T cells, we show that T-bet sequesters GATA3 at its target sites, thereby removing GATA3 from TH2 genes. This redistribution of GATA3 is independent of GATA3 DNA binding activity and is instead mediated by the T-bet DNA binding domain, which interacts with the GATA3 DNA binding domain and changes GATA3's sequence binding preference. This mechanism allows T-bet to drive the TH1 gene expression program in the presence of GATA3. We propose that redistribution of one LD-TF by another may be a common mechanism that could explain how specific cell fate choices can be made even in the presence of other transcription factors driving alternative differentiation pathways.

IGF2 mRNA-binding protein 1 (IMP1) is a key regulator of messenger RNA (mRNA) metabolism and transport in organismal development and, in cancer, its mis-regulation is an important component of tumour metastasis. IMP1 function relies on the recognition of a diverse set of mRNA targets that is mediated by the combinatorial action of multiple RNA-binding domains. Here, we dissect the structure and RNA-binding properties of two key RNA-binding domains of IMP1, KH1 and KH2, and we build a kinetic model for the recognition of RNA targets. Our data and model explain how the two domains are organized as an intermolecular pseudo-dimer and that the important role they play in mRNA target recognition is underpinned by the high RNA-binding affinity and fast kinetics of this KH1KH2-RNA recognition unit. Importantly, the high-affinity RNA-binding by KH1KH2 is achieved by an inter-domain coupling 50-fold stronger than that existing in a second pseudo-dimer in the protein, KH3KH4. The presence of this strong coupling supports a role of RNA re-modelling in IMP1 recognition of known cancer targets.

The multi-protein complex WRAD, formed by WDR5, RbBP5, Ash2L and Dpy30, binds to the MLL SET domain to stabilize the catalytically active conformation required for histone H3K4 methylation. In addition, the WRAD complex contributes to the targeting of the activated complex to specific sites on chromatin. RbBP5 is central to MLL catalytic activation, by making critical contacts with the other members of the complex. Interestingly its only major structural domain, a canonical WD40 repeat β-propeller, is not implicated in this function. Here, we present the structure of the RbBP5 β-propeller domain revealing a distinct, feature rich surface, dominated by clusters of Arginine residues. Our nuclear magnetic resonance binding data supports the hypothesis that in addition to the role of RbBP5 in catalytic activation, its β-propeller domain is a platform for the recruitment of the MLL complexes to chromatin targets through its direct interaction with nucleic acids.

Modelling both primary sequence and secondary structure preferences for RNA binding proteins (RBPs) remains an ongoing challenge. Current models use varied RNA structure representations and can be difficult to interpret and evaluate. To address these issues, we present a universal RNA motif-finding/scanning strategy, termed PRIESSTESS (Predictive RBP-RNA InterpretablE Sequence-Structure moTif regrESSion), that can be applied to diverse RNA binding datasets. PRIESSTESS identifies dozens of enriched RNA sequence and/or structure motifs that are subsequently reduced to a set of core motifs by logistic regression with LASSO regularization. Importantly, these core motifs are easily visualized and interpreted, and provide a measure of RBP secondary structure specificity. We used PRIESSTESS to interrogate new HTR-SELEX data for 23 RBPs with diverse RNA binding modes and captured known primary sequence and secondary structure preferences for each. Moreover, when applying PRIESSTESS to 144 RBPs across 202 RNA binding datasets, 75% showed an RNA secondary structure preference but only 10% had a preference besides unpaired bases, suggesting that most RBPs simply recognize the accessibility of primary sequences.

m6A methylation provides an essential layer of regulation in organismal development, and is aberrant in a range of cancers and neuro-pathologies. The information encoded by m6A methylation is integrated into existing RNA regulatory networks by RNA binding proteins that recognise methylated sites, the m6A readers. m6A readers include a well-characterised class of dedicated proteins, the YTH proteins, as well as a broader group of multi-functional regulators where recognition of m6A is only partially understood. Molecular insight in this recognition is essential to build a mechanistic understanding of global m6A regulation. In this study, we show that the reader IMP1 recognises the m6A using a dedicated hydrophobic platform that assembles on the methyl moiety, creating a stable high-affinity interaction. This recognition is conserved across evolution and independent from the underlying sequence context but is layered upon the strong sequence specificity of IMP1 for GGAC RNA. This leads us to propose a concept for m6A regulation where methylation plays a context-dependent role in the recognition of selected IMP1 targets that is dependent on the cellular concentration of available IMP1, differing from that observed for the YTH proteins.

Defining the RNA target selectivity of the proteins regulating mRNA metabolism is a key issue in RNA biology. Here we present a novel use of principal component analysis (PCA) to extract the RNA sequence preference of RNA binding proteins. We show that PCA can be used to compare the changes in the nuclear magnetic resonance (NMR) spectrum of a protein upon binding a set of quasi-degenerate RNAs and define the nucleobase specificity. We couple this application of PCA to an automated NMR spectra recording and processing protocol and obtain an unbiased and high-throughput NMR method for the analysis of nucleobase preference in protein-RNA interactions. We test the method on the RNA binding domains of three important regulators of RNA metabolism.

KSRP is a multi-domain RNA-binding protein that recruits the exosome-containing mRNA degradation complex to mRNAs coding for cellular proliferation and inflammatory response factors. The selectivity of this mRNA degradation mechanism relies on KSRP recognition of AU-rich elements in the mRNA 3'UTR, that is mediated by KSRP's KH domains. Our structural analysis shows that the inter-domain linker orients the two central KH domains of KSRP-and their RNA-binding surfaces-creating a two-domain unit. We also show that this inter-domain arrangement is important to the interaction with KSRP's RNA targets.

K-homology (KH) splicing regulator protein (KSRP) is a multi-domain RNA-binding protein that regulates different steps of mRNA metabolism, from mRNA splicing to mRNA decay, interacting with a broad range of RNA sequences. To understand how KSRP recognizes its different RNA targets it is necessary to define the general rules of KSRP-RNA interaction. We describe here a complete scaffold-independent analysis of the RNA-binding potential of the four KH domains of KSRP. The analysis shows that KH3 binds to the RNA with a significantly higher affinity than the other domains and recognizes specifically a G-rich target. It also demonstrates that the other KH domains of KSRP display different sequence preferences explaining the broad range of targets recognized by the protein. Further, KSRP shows a strong negative selectivity for sequences containing several adjacent Cytosines limiting the target choice of KSRP within single-stranded RNA regions. The in-depth analysis of the RNA-binding potential of the KH domains of KSRP provides us with an understanding of the role of low sequence specificity domains in RNA recognition by multi-domain RNA-binding proteins.

GeneMANIA (http://genemania.org) is a flexible user-friendly web site for generating hypotheses about gene function, analyzing gene lists and prioritizing genes for functional assays. Given a query gene list, GeneMANIA finds functionally similar genes using a wealth of genomics and proteomics data. In this mode, it weights each functional genomic dataset according to its predictive value for the query. Another use of GeneMANIA is gene function prediction. Given a single query gene, GeneMANIA finds genes likely to share function with it based on their interactions with it. Enriched Gene Ontology categories among this set can point to the function of the gene. Nine organisms are currently supported (Arabidopsis thaliana, Caenorhabditis elegans, Danio rerio, Drosophila melanogaster, Escherichia coli, Homo sapiens, Mus musculus, Rattus norvegicus and Saccharomyces cerevisiae). Hundreds of data sets and hundreds of millions of interactions have been collected from GEO, BioGRID, IRefIndex and I2D, as well as organism-specific functional genomics data sets. Users can customize their search by selecting specific data sets to query and by uploading their own data sets to analyze. We have recently updated the user interface to GeneMANIA to make it more intuitive and make more efficient use of visual space. GeneMANIA can now be used effectively on a variety of devices.

The RNA-Binding Protein DataBase (RBPDB) is a collection of experimental observations of RNA-binding sites, both in vitro and in vivo, manually curated from primary literature. To build RBPDB, we performed a literature search for experimental binding data for all RNA-binding proteins (RBPs) with known RNA-binding domains in four metazoan species (human, mouse, fly and worm). In total, RPBDB contains binding data on 272 RBPs, including 71 that have motifs in position weight matrix format, and 36 sets of sequences of in vivo-bound transcripts from immunoprecipitation experiments. The database is accessible by a web interface which allows browsing by domain or by organism, searching and export of records, and bulk data downloads. Users can also use RBPDB to scan sequences for RBP-binding sites. RBPDB is freely available, without registration at http://rbpdb.ccbr.utoronto.ca/.

RBM10 is an RNA-binding protein that plays an essential role in development and is frequently mutated in the context of human disease. RBM10 recognizes a diverse set of RNA motifs in introns and exons and regulates alternative splicing. However, the molecular mechanisms underlying this seemingly relaxed sequence specificity are not understood and functional studies have focused on 3΄ intronic sites only. Here, we dissect the RNA code recognized by RBM10 and relate it to the splicing regulatory function of this protein. We show that a two-domain RRM1-ZnF unit recognizes a GGA-centered motif enriched in RBM10 exonic sites with high affinity and specificity and test that the interaction with these exonic sequences promotes exon skipping. Importantly, a second RRM domain (RRM2) of RBM10 recognizes a C-rich sequence, which explains its known interaction with the intronic 3΄ site of NUMB exon 9 contributing to regulation of the Notch pathway in cancer. Together, these findings explain RBM10's broad RNA specificity and suggest that RBM10 functions as a splicing regulator using two RNA-binding units with different specificities to promote exon skipping.