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.     

Global signatures of protein binding on structured RNAs in Saccharomyces cerevisiae

Protein binding is essential to the transport,decay and regulation of almost all RNA molecules.However,the structural preference of protein binding on RNAs and their cellular functions and dynamics upon changing environmental conditions are poorly understood.Here,we integrated various high-throughput data and introduced a computational framework to describe the global interactions between RNA binding proteins(RBPs)and structured RNAs in yeast at single-nucleotide resolution.We found that on average,in terms of percent total lengths,~15%of mRNA untranslated regions(UTRs),~37%of canonical non-coding RNAs(ncRNAs)and~11%of long ncRNAs(lncRNAs)are bound by proteins.The RBP binding sites,in general,tend to occur at single-stranded loops,with evolutionarily conserved signatures,and often facilitate a specific RNA structure conformation in vivo.We found that four nucleotide modifications of tRNA are significantly associated with RBP binding.We also identified various structural motifs bound by RBPs in the UTRs of mRNAs,associated with localization,degradation and stress responses.Moreover,we identified>200 novel lncRNAs bound by RBPs,and about half of them contain conserved secondary structures.We present the first ensemble pattern of RBP binding sites in the structured non-coding regions of a eukaryotic genome,emphasizing their structural context and cellular functions.     

RNAmotifs: prediction of multivalent RNA motifs that control alternative splicing

RNA-binding proteins (RBPs) regulate splicing according to position-dependent principles, which can be exploited for analysis of regulatory motifs. Here we present RNAmotifs, a method that evaluates the sequence around differentially regulated alternative exons to identify clusters of short and degenerate sequences, referred to as multivalent RNA motifs. We show that diverse RBPs share basic positional principles, but differ in their propensity to enhance or repress exon inclusion. We assess exons differentially spliced between brain and heart, identifying known and new regulatory motifs, and predict the expression pattern of RBPs that bind these motifs. RNAmotifs is available at https://bitbucket.org/rogrro/rna_motifs.     

Using RNA secondary structures to guide sequence motif finding towards single-stranded regions

RNA binding proteins recognize RNA targets in a sequence specific manner. Apart from the sequence, the secondary structure context of the binding site also affects the binding affinity. Binding sites are often located in single-stranded RNA regions and it was shown that the sequestration of a binding motif in a double-strand abolishes protein binding. Thus, it is desirable to include knowledge about RNA secondary structures when searching for the binding motif of a protein. We present the approach MEMERIS for searching sequence motifs in a set of RNA sequences and simultaneously integrating information about secondary structures. To abstract from specific structural elements, we precompute position-specific values measuring the single-strandedness of all substrings of an RNA sequence. These values are used as prior knowledge about the motif starts to guide the motif search. Extensive tests with artificial and biological data demonstrate that MEMERIS is able to identify motifs in single-stranded regions even if a stronger motif located in double-strand parts exists. The discovered motif occurrences in biological datasets mostly coincide with known protein-binding sites. This algorithm can be used for finding the binding motif of single-stranded RNA-binding proteins in SELEX or other biological sequence data.     

Conformational preference functions for predicting helices in membrane proteins

A suite of FORTRAN programs, PREF, is described for calculating preference functions from the data base of known protein structures and for comparing smoothed profiles of sequence-dependent preferences in proteins of unknown structure. Amino acid preferences for a secondary structure are considered as functions of a sequence environment. Sequence environment of amino acid residue in a protein is defined as an average over some physical, chemical, or statistical property of its primary structure neighbors. The frequency distribution of sequence environments in the data base of soluble protein structures is approximately normal for each amino acid type of known secondary conformation. An analytical expression for the dependence of preferences on sequence environment is obtained after each frequency distribution is replaced by corresponding Gaussian function. The preference for the α-helical conformation increases for each amino acid type with the increase of sequence environment of buried solvent-accessible surface areas. We show that a set of preference functions based on buried surface area is useful for predicting folding motifs in α-class proteins and in integral membrane proteins. The prediction accuracy for helical residues is 79% for 5 integral membrane proteins and 74% for 11 α-class soluble proteins. Most residues found in transmembrane segments of membrane proteins with known α-helical structure are predicted to be indeed in the helical conformation because of very high middle helix preferences. Both extramembrane and transmembrane helices in the photosynthetic reaction center M and L subunits are correctly predicted. We point out in the discussion that our method of conformational preference functions can identify what physical properties of the amino acids are important in the formation of particular secondary structure elements. © 1993 John Wiley & Sons, Inc.     

An atlas of posttranslational modifications on RNA binding proteins

RNA structure and function are intimately tied to RNA binding protein recognition and regulation. Posttranslational modifications are chemical modifications which can control protein biology. The role of PTMs in the regulation RBPs is not well understood, in part due to a lacking analysis of PTM deposition on RBPs. Herein, we present an analysis of posttranslational modifications (PTMs) on RNA binding proteins (RBPs; a PTM RBP Atlas). We curate published datasets and primary literature to understand the landscape of PTMs and use protein–protein interaction data to understand and potentially provide a framework for understanding which enzymes are controlling PTM deposition and removal on the RBP landscape. Intersection of our data with The Cancer Genome Atlas also provides researchers understanding of mutations that would alter PTM deposition. Additional characterization of the RNA–protein interface provided from in-cell UV crosslinking experiments provides a framework for hypotheses about which PTMs could be regulating RNA binding and thus RBP function. Finally, we provide an online database for our data that is easy to use for the community. It is our hope our efforts will provide researchers will an invaluable tool to test the function of PTMs controlling RBP function and thus RNA biology.     

The genome factor in region-specific DNA damage: the DNA-reactive drug U-78779 prefers mixed A/T-G/C sequences at the nucleotide level but is region-specific for long pure AT islands at the genomic level

Bizelesin is the first anticancer drug capable of damaging specific regions of the genome with clusters of its binding sites T(A/T)(4)A. This study characterized the sequence- and region-specificity of a bizelesin analogue, U-78779, designed to interact with mixed A/T-G/C motifs. At the nucleotide level, U-78779 was found to prefer runs of A/Ts interspersed with 1 or 2 G/C pairs, although 25% of the identified sites corresponded to pure AT motifs similar to bizelesin sites. The in silico computational analysis showed that the preferred mixed A/T-G/C motifs distribute uniformly at the genomic level. In contrast, the secondary, pure AT motifs (A/T)(6)A were found densely clustered in the same long islands of AT-rich DNA that bizelesin targets. Mapping the sites and quantitating the frequencies of U-78779 adducts in model AT island and non-AT island naked DNAs demonstrated that clusters of pure AT motifs outcompete isolated mixed A/T-G/C sites in attracting drug binding. Regional preference of U-78779 for AT island domains was verified also in DNA from drug-treated cells. Thus, while the primary sequence preference gives rise to non-region-specific scattered lesions, the clustering of the minor pure AT binding motifs seems to determine region-specificity of U-78779 in the human genome. The closely correlated cytotoxic activities of U-78779 and bizelesin in several cell lines further imply that both drugs may share common cellular targets. This study underscores the significance of the genome factor in a drug's potential for region-specific DNA damage, by showing that it can take precedence over drug binding preferences at the nucleotide level.     

Nucleic acid-binding specificity of human FUS protein

FUS, a nuclear RNA-binding protein, plays multiple roles in RNA processing. Five specific FUS-binding RNA sequence/structure motifs have been proposed, but their affinities for FUS have not been directly compared. Here we find that human FUS binds all these sequences with K_d^app values spanning a 10-fold range. Furthermore, some RNAs that do not contain any of these motifs bind FUS with similar affinity. FUS binds RNA in a length-dependent manner, consistent with a substantial non-specific component to binding. Finally, investigation of FUS binding to different nucleic acids shows that it binds single-stranded DNA with three-fold lower affinity than ssRNA of the same length and sequence, while binding to double-stranded nucleic acids is weaker. We conclude that FUS has quite general nucleic acid-binding activity, with the various proposed RNA motifs being neither necessary for FUS binding nor sufficient to explain its diverse binding partners.