The PETfold and PETcofold web servers for intra- and intermolecular structures of multiple RNA sequences

Phylogenetic and Chemical Probing Information as Soft Constraints in RNA Secondary Structure Prediction

Extrinsic, experimental information can be incorporated into thermodynamics-based RNA folding algorithms in the form of pseudo-energies. Evolutionary conservation of RNA secondary structure elements is detectable in alignments of phylogenetically related sequences and provides evidence for the presence of certain base pairs that can also be converted into pseudo-energy contributions. We show that the centroid base pairs computed from a consensus folding model such as RNAalifold result in a substantial improvement of the prediction accuracy for single sequences. Evidence for specific base pairs turns out to be more informative than a position-wise profile for the conservation of the pairing status. A comparison with chemical probing data, furthermore, strongly suggests that phylogenetic base pairing data are more informative than position-specific data on (un)pairedness as obtained from chemical probing experiments. In this context we demonstrate, in addition, that the conversion of signal from probing data into pseudo-energies is possible using thermodynamic structure predictions as a reference instead of known RNA structures.

A Hitchhiker's guide to RNA-RNA structure and interaction prediction tools

RNA biology has risen to prominence after a remarkable discovery of diverse functions of noncoding RNA (ncRNA). Most untranslated transcripts often exert their regulatory functions into RNA-RNA complexes via base pairing with complementary sequences in other RNAs. An interplay between RNAs is essential, as it possesses various functional roles in human cells, including genetic translation, RNA splicing, editing, ribosomal RNA maturation, RNA degradation and the regulation of metabolic pathways/riboswitches. Moreover, the pervasive transcription of the human genome allows for the discovery of novel genomic functions via RNA interactome investigation. The advancement of experimental procedures has resulted in an explosion of documented data, necessitating the development of efficient and precise computational tools and algorithms. This review provides an extensive update on RNA-RNA interaction (RRI) analysis via thermodynamic- and comparative-based RNA secondary structure prediction (RSP) and RNA-RNA interaction prediction (RIP) tools and their general functions. We also highlighted the current knowledge of RRIs and the limitations of RNA interactome mapping via experimental data. Then, the gap between RSP and RIP, the importance of RNA homologues, the relationship between pseudoknots, and RNA folding thermodynamics are discussed. It is hoped that these emerging prediction tools will deepen the understanding of RNA-associated interactions in human diseases and hasten treatment processes.

Web Services for RNA-RNA Interaction Prediction

Non-coding RNAs have various biological functions such as translational regulation, and RNA-RNA interactions play essential roles in the mechanisms of action of these RNAs. Therefore, RNA-RNA interaction prediction is an important problem in bioinformatics, and many tools have been developed for the computational prediction of RNA-RNA interactions. In addition to the development of novel algorithms with high accuracy, the development and maintenance of web services is essential for enhancing usability by experimental biologists. In this review, we survey web services for RNA-RNA interaction predictions and introduce how to use primary web services. We present various prediction tools, including general interaction prediction tools, prediction tools for specific RNA classes, and RNA-RNA interaction-based RNA design tools. Additionally, we discuss the future perspectives of the development of RNA-RNA interaction prediction tools and the sustainability of web services.

RNA G-Quadruplex within the 5'-UTR of FEN1 Regulates mRNA Stability under Oxidative Stress

Reactive oxygen species (ROS) are a group of highly oxidative molecules that induce DNA damage, affecting DNA damage response (DDR) and gene expression. It is now recognized that DNA base excision repair (BER) is one of the important pathways responsible for sensing oxidative stress to eliminate DNA damage, in which FEN1 plays an important role in this process. However, the regulation of FEN1 under oxidative stress is still unclear. Here, we identified a novel RNA G-quadruplex (rG4) sequence in the 5'untranslated region (5'UTR) of FEN1 mRNA. Under oxidative stress, the G bases in the G4-forming sequence can be oxidized by ROS, resulting in structural disruption of the G-quadruplex. ROS or TMPyP4, a G4-structural ligand, disrupted the formation of G4 structure and affected the expression of FEN1. Furthermore, pull-down experiments identified a novel FEN1 rG4-binding protein, heterogeneous nuclear ribonucleoprotein A1 (hnRNPA1), and cellular studies have shown that hnRNPA1 plays an important role in regulating FEN1 expression. This work demonstrates that rG4 acts as a ROS sensor in the 5'UTR of FEN1 mRNA. Taken together, these results suggest a novel role for rG4 in translational control under oxidative stress.

LaRA 2: parallel and vectorized program for sequence-structure alignment of RNA sequences

BACKGROUND

The function of non-coding RNA sequences is largely determined by their spatial conformation, namely the secondary structure of the molecule, formed by Watson-Crick interactions between nucleotides. Hence, modern RNA alignment algorithms routinely take structural information into account. In order to discover yet unknown RNA families and infer their possible functions, the structural alignment of RNAs is an essential task. This task demands a lot of computational resources, especially for aligning many long sequences, and it therefore requires efficient algorithms that utilize modern hardware when available. A subset of the secondary structures contains overlapping interactions (called pseudoknots), which add additional complexity to the problem and are often ignored in available software.

RESULTS

We present the SeqAn-based software LaRA 2 that is significantly faster than comparable software for accurate pairwise and multiple alignments of structured RNA sequences. In contrast to other programs our approach can handle arbitrary pseudoknots. As an improved re-implementation of the LaRA tool for structural alignments, LaRA 2 uses multi-threading and vectorization for parallel execution and a new heuristic for computing a lower boundary of the solution. Our algorithmic improvements yield a program that is up to 130 times faster than the previous version.

CONCLUSIONS

With LaRA 2 we provide a tool to analyse large sets of RNA secondary structures in relatively short time, based on structural alignment. The produced alignments can be used to derive structural motifs for the search in genomic databases.

Ornithobacterium rhinotracheale: MALDI-TOF MS and Whole Genome Sequencing Confirm That Serotypes K, L and M Deviate from Well-Known Reference Strains and Numerous Field Isolates

Ornithobacterium rhinotracheale is one of the most important bacterial agents of respiratory diseases in poultry. For correct identification and characterization of this fastidious bacterium, reliable diagnostic tools are essential. Still, phenotypic tests are used to identify O. rhinotracheale and serotyping is the most common method for characterization, despite known drawbacks and disadvantages such as divergent results, cross-reactivity between strains, or the non-typeability of strains. The intention of the present study was to evaluate MALDI-TOF MS and whole genome sequencing for the identification and characterization of O. rhinotracheale. For this purpose, a selection of 59 well-defined reference strains and 47 field strains derived from outbreaks on Austrian turkey farms were investigated by MALDI-TOF MS. The field strains originated from different geographical areas in Austria with some of the isolates derived from multiple outbreaks on farms within a year, or recurrent outbreaks over several years. MALDI-TOF MS proved a suitable method for identification of O. rhinotracheale to genus or species level except for 3 strains representing serotypes M, K and F. Phylogenetic analysis showed that most strains grouped within one cluster even though they were comprised of different serotypes, while serotypes F, K, and M clearly formed a different cluster. All field isolates from turkey farms clustered together, independent of the origin of the isolates, e.g., geographical area, multiple outbreaks within a year or recurrent outbreaks over several years. Whole genome sequencing of serotype M, K and F strains confirmed the extraordinary status and deviation from known fully-sequenced strains due to a lack of sequence similarity. This was further confirmed by alignments of single genes (16S-RNA and rpoB) and multilocus sequence typing although the demarcation was less obvious. Altogether, the results indicate that these three serotypes belong to a different species than O. rhinotracheale, and might even be members of multiple new species.

Improved RNA Secondary Structure and Tertiary Base-pairing Prediction Using Evolutionary Profile, Mutational Coupling and Two-dimensional Transfer Learning

MOTIVATION

The recent discovery of numerous non-coding RNAs (long non-coding RNAs, in particular) has transformed our perception about the roles of RNAs in living organisms. Our ability to understand them, however, is hampered by our inability to solve their secondary and tertiary structures in high resolution efficiently by existing experimental techniques. Computational prediction of RNA secondary structure, on the other hand, has received much-needed improvement, recently, through deep learning of a large approximate data, followed by transfer learning with gold-standard base-pairing structures from high-resolution 3-D structures. Here, we expand this single-sequence-based learning to the use of evolutionary profiles and mutational coupling.

RESULTS

The new method allows large improvement not only in canonical base-pairs (RNA secondary structures) but more so in base-pairing associated with tertiary interactions such as pseudoknots, noncanonical and lone base-pairs. In particular, it is highly accurate for those RNAs of more than 1000 homologous sequences by achieving >0.8 F1-score (harmonic mean of sensitivity and precision) for 14/16 RNAs tested. The method can also significantly improve base-pairing prediction by incorporating artificial but functional homologous sequences generated from deep mutational scanning without any modification. The fully automatic method (publicly available as server and standalone software) should provide the scientific community a new powerful tool to capture not only the secondary structure but also tertiary base-pairing information for building three-dimensional models. It also highlights the future of accurately solving the base-pairing structure by using a large number of natural and/or artificial homologous sequences.

AVAILABILITY

Standalone-version of SPOT-RNA2 is available at https://github.com/jaswindersingh2/SPOT-RNA2. Direct prediction can also be made at https://sparks-lab.org/server/spot-rna2/. The datasets used in this research can also be downloaded from the GITHUB and the webserver mentioned above.

How the initiating ribosome copes with ppGpp to translate mRNAs

During host colonization, bacteria use the alarmones (p)ppGpp to reshape their proteome by acting pleiotropically on DNA, RNA, and protein synthesis. Here, we elucidate how the initiating ribosome senses the cellular pool of guanosine nucleotides and regulates the progression towards protein synthesis. Our results show that the affinity of guanosine triphosphate (GTP) and the inhibitory concentration of ppGpp for the 30S-bound initiation factor IF2 vary depending on the programmed mRNA. The TufA mRNA enhanced GTP affinity for 30S complexes, resulting in improved ppGpp tolerance and allowing efficient protein synthesis. Conversely, the InfA mRNA allowed ppGpp to compete with GTP for IF2, thus stalling 30S complexes. Structural modeling and biochemical analysis of the TufA mRNA unveiled a structured enhancer of translation initiation (SETI) composed of two consecutive hairpins proximal to the translation initiation region (TIR) that largely account for ppGpp tolerance under physiological concentrations of guanosine nucleotides. Furthermore, our results show that the mechanism enhancing ppGpp tolerance is not restricted to the TufA mRNA, as similar ppGpp tolerance was found for the SETI-containing Rnr mRNA. Finally, we show that IF2 can use pppGpp to promote the formation of 30S initiation complexes (ICs), albeit requiring higher factor concentration and resulting in slower transitions to translation elongation. Altogether, our data unveil a novel regulatory mechanism at the onset of protein synthesis that tolerates physiological concentrations of ppGpp and that bacteria can exploit to modulate their proteome as a function of the nutritional shift happening during stringent response and infection.

Translational co-regulation of a ligand and inhibitor by a conserved RNA element

In many organisms, transcriptional and post-transcriptional regulation of components of pathways or processes has been reported. However, to date, there are few reports of translational co-regulation of multiple components of a developmental signaling pathway. Here, we show that an RNA element which we previously identified as a dorsal localization element (DLE) in the 3'UTR of zebrafish nodal-related1/squint (ndr1/sqt) ligand mRNA, is shared by the related ligand nodal-related2/cyclops (ndr2/cyc) and the nodal inhibitors, lefty1 (lft1) and lefty2 mRNAs. We investigated the activity of the DLEs through functional assays in live zebrafish embryos. The lft1 DLE localizes fluorescently labeled RNA similarly to the ndr1/sqt DLE. Similar to the ndr1/sqt 3'UTR, the lft1 and lft2 3'UTRs are bound by the RNA-binding protein (RBP) and translational repressor, Y-box binding protein 1 (Ybx1), whereas deletions in the DLE abolish binding to Ybx1. Analysis of zebrafish ybx1 mutants shows that Ybx1 represses lefty1 translation in embryos. CRISPR/Cas9-mediated inactivation of human YBX1 also results in human NODAL translational de-repression, suggesting broader conservation of the DLE RNA element/Ybx1 RBP module in regulation of Nodal signaling. Our findings demonstrate translational co-regulation of components of a signaling pathway by an RNA element conserved in both sequence and structure and an RBP, revealing a 'translational regulon'.

Structure and Interaction Prediction in Prokaryotic RNA Biology

Many years of research in RNA biology have soundly established the importance of RNA-based regulation far beyond most early traditional presumptions. Importantly, the advances in "wet" laboratory techniques have produced unprecedented amounts of data that require efficient and precise computational analysis schemes and algorithms. Hence, many in silico methods that attempt topological and functional classification of novel putative RNA-based regulators are available. In this review, we technically outline thermodynamics-based standard RNA secondary structure and RNA-RNA interaction prediction approaches that have proven valuable to the RNA research community in the past and present. For these, we highlight their usability with a special focus on prokaryotic organisms and also briefly mention recent advances in whole-genome interactomics and how this may influence the field of predictive RNA research.

Full-length RNA structure prediction of the HIV-1 genome reveals a conserved core domain

A distance constrained secondary structural model of the ≈10 kb RNA genome of the HIV-1 has been predicted but higher-order structures, involving long distance interactions, are currently unknown. We present the first global RNA secondary structure model for the HIV-1 genome, which integrates both comparative structure analysis and information from experimental data in a full-length prediction without distance constraints. Besides recovering known structural elements, we predict several novel structural elements that are conserved in HIV-1 evolution. Our results also indicate that the structure of the HIV-1 genome is highly variable in most regions, with a limited number of stable and conserved RNA secondary structures. Most interesting, a set of long distance interactions form a core organizing structure (COS) that organize the genome into three major structural domains. Despite overlapping protein-coding regions the COS is supported by a particular high frequency of compensatory base changes, suggesting functional importance for this element. This new structural element potentially organizes the whole genome into three major domains protruding from a conserved core structure with potential roles in replication and evolution for the virus.

Molecular characterization ofOpisthorchis noverca(Digenea: Opisthorchiidae) based on nuclear ribosomal ITS2 and mitochondrial COI genes

Opisthorchiasis is a public health problem in South-East Asian countries and Eastern Europe. The infection implicates mainly two species ofOpisthorchis, namelyO. viverriniandO. felineus,that occur mostly in fish-eating mammals and humans, although there are rare reports of human cases involving two other species,O. novercaandO. guayaquilensis.Opisthorchis novercahas been reported frequently in dogs and pigs from the Indian subcontinent, with rare reports from cattle and human subjects. With a view to supplementing morphology-based identification of this species, the present study aimed to provide molecular characterization ofO. noverca, using rDNA internal transcribed spacer 2 (ITS2) and mitochondrial cytochrome oxidase I (mt COI) markers so as to determine its genetic correlation with other species of Opisthorchiidae, and also to generate a taxon-specific molecular marker based on the ITS2 region. The phylogenetic relationship betweenO. novercaand other species of the genus was determined using molecular sequence data. To strengthen the result, secondary structure sequence analyses of ITS2 with hemi-compensatory base changes (hCBCs), and amino acid sequence analyses, were also evaluated. Our results confirm thatO. novercais a distinct and valid species.

Joint modeling of RNase footprint sequencing profiles for genome-wide inference of RNA structure

Recent studies have revealed significant roles of RNA structure in almost every step of RNA processing, including transcription, splicing, transport and translation. RNase footprint sequencing (RNase-seq) has emerged to dissect RNA structures at the genome scale. However, it remains challenging to analyze RNase-seq data because of the issues of signal sparsity, variability and correlations among various RNases. We present a probabilistic framework, joint Poisson-gamma mixture (JPGM), for integrative modeling of multiple RNase-seq profiles. Combining JPGM with hidden Markov model allows genome-wide inference of RNA structures. We apply the joint modeling approach for inferring base pairing states on simulated data sets and RNase-seq profiles of the double-strand specific RNase V1 and single-strand specific RNase S1 in yeast. We demonstrate that joint analysis of V1 and S1 profiles outputs interpretable RNA structure states, while approaches that analyze each profile separately do not. The joint modeling approach predicts the structure states of all nucleotides in 3196 transcripts of yeast without compromising accuracy, while the simple thresholding approach misses 43% of the nucleotides. Furthermore, the posterior probabilities outputted by our model are able to resolve the structural ambiguity of ≈300 000 nucleotides with overlapping V1 and S1 cleavage sites. Our model also generates RNA accessibilities, which are associated with three-dimensional conformations.

RNA secondary structure prediction from multi-aligned sequences

It has been well accepted that the RNA secondary structures of most functional non-coding RNAs (ncRNAs) are closely related to their functions and are conserved during evolution. Hence, prediction of conserved secondary structures from evolutionarily related sequences is one important task in RNA bioinformatics; the methods are useful not only to further functional analyses of ncRNAs but also to improve the accuracy of secondary structure predictions and to find novel functional RNAs from the genome. In this review, I focus on common secondary structure prediction from a given aligned RNA sequence, in which one secondary structure whose length is equal to that of the input alignment is predicted. I systematically review and classify existing tools and algorithms for the problem, by utilizing the information employed in the tools and by adopting a unified viewpoint based on maximum expected gain (MEG) estimators. I believe that this classification will allow a deeper understanding of each tool and provide users with useful information for selecting tools for common secondary structure predictions.

Bioinformatics of prokaryotic RNAs

The genome of most prokaryotes gives rise to surprisingly complex transcriptomes, comprising not only protein-coding mRNAs, often organized as operons, but also harbors dozens or even hundreds of highly structured small regulatory RNAs and unexpectedly large levels of anti-sense transcripts. Comprehensive surveys of prokaryotic transcriptomes and the need to characterize also their non-coding components is heavily dependent on computational methods and workflows, many of which have been developed or at least adapted specifically for the use with bacterial and archaeal data. This review provides an overview on the state-of-the-art of RNA bioinformatics focusing on applications to prokaryotes.

Utility of divergent domains of 28S ribosomal RNA in species discrimination of paramphistomes (Trematoda: Digenea: Paramphistomoidea)

Among the digenetic trematodes, paramphistomes are known to be the causative agent of "amphistomiasis" or the stomach fluke disease of domestic and wild animals, mainly ruminants. The use of 28S (divergent domains) and 18S rRNA for phylogenetic inference is significantly warranted for these flukes since it is as yet limited to merely the exploration of the second internal transcribed spacer (ITS2) region. The present study intended to explore the divergent domains (D1-D3) of 28S rRNA and simultaneously equate the phylogenetic information with 18S rRNA in paramphistomes. Divergence of the 28S rRNA domains was evident amongst the divergent (D) domains, where D1 domain emerged as the most variable and D2, the most robust domain, since the latter could provide a higher resolution of the species. D2 was the only domain that comprised compensatory mutations in the helices of its structural constraints; this domain is thus well suited for species distinction and may be considered a potential DNA barcode complementary to mitochondrial DNA. 28S (D1 + D2 + D3) rRNA provided a significant resolution of the taxa corroborating with the taxonomy of these flukes and thus proved to be more robust as a phylogenetic marker for lower levels than 18S rRNA. Phylogenetic inferences of paramphitomes are still scarcely explored; additional data from other taxa belonging to this family may estimate better the biodiversity of these flukes.

MicroRNA discovery by similarity search to a database of RNA-seq profiles

In silico generated search for microRNAs (miRNAs) has been driven by methods compiling structural features of the miRNA precursor hairpin, as well as to some degree combining this with the analysis of RNA-seq profiles for which the miRNA typically leave the drosha/dicer fingerprint of 1-2 ~22 nt blocks of reads corresponding to the mature and star miRNA. In complement to the previous methods, we present a study where we systematically exploit these patterns of read profiles. We created two datasets comprised of 2540 and 4795 read profiles obtained after preprocessing short RNA-seq data from miRBase and ENCODE, respectively. Out of 4795 ENCODE read profiles, 1361 are annotated as non-coding RNAs (ncRNAs) and of which 285 are further annotated as miRNAs. Using deepBlockAlign (dba), we align ncRNA read profiles from ENCODE against the miRBase read profiles (cleaned for "self-matches") and are able to separate ENCODE miRNAs from the other ncRNAs by a Matthews Correlation Coefficient (MCC) of 0.8 and obtain an area under the curve of 0.93. Based on the dba score cut-off of 0.7 at which we observed the maximum MCC of 0.8, we predict 523 novel miRNA candidates. An additional RNA secondary structure analysis reveal that 42 of the candidates overlap with predicted conserved secondary structure. Further analysis reveal that the 523 miRNA candidates are located in genomic regions with MAF block (UCSC) fragmentation and poor sequence conservation, which in part might explain why they have been overlooked in previous efforts. We further analyzed known human and mouse miRNA read profiles and found two distinct classes; the first containing two blocks and the second containing >2 blocks of reads. Also the latter class holds read profiles that have less well defined arrangement of reads in comparison to the former class. On comparison of miRNA read profiles from plants and animals, we observed kingdom specific read profiles that are distinct in terms of both length and distribution of reads within the read profiles to each other. All the data, as well as a server to search miRBase read profiles by uploading a BED file, is available at http://rth.dk/resources/mirdba.

Incorporating phylogenetic-based covarying mutations into RNAalifold for RNA consensus structure prediction

Background

RNAalifold, a popular computational method for RNA consensus structure prediction, incorporates covarying mutations into a thermodynamic model to fold the aligned RNA sequences. When quantifying covariance, it evaluates conserved signals of two aligned columns with base-pairing rules. This scoring scheme performs better than some other approaches, such as mutual information. However it ignores the phylogenetic history of the aligned sequences, which is an important criterion to evaluate the level of sequence covariance.

Results

In this article, in order to improve the accuracy of consensus structure folding, we propose a novel approach named PhyloRNAalifold. It incorporates the number of covarying mutations on the phylogenetic tree of the aligned sequences into the covariance scoring of RNAalifold. The benchmarking results show that the new scoring scheme of PhyloRNAalifold can improve the consensus structure detection of RNAalifold.

Conclusion

Incorporating additional phylogenetic information of aligned sequences into the covariance scoring of RNAalifold can improve its performance of consensus structures folding. This improvement is correlated with alignment characteristics, such as pair-wise identity and the number of sequences in the alignment.

CompaRNA: a server for continuous benchmarking of automated methods for RNA secondary structure prediction

We present a continuous benchmarking approach for the assessment of RNA secondary structure prediction methods implemented in the CompaRNA web server. As of 3 October 2012, the performance of 28 single-sequence and 13 comparative methods has been evaluated on RNA sequences/structures released weekly by the Protein Data Bank. We also provide a static benchmark generated on RNA 2D structures derived from the RNAstrand database. Benchmarks on both data sets offer insight into the relative performance of RNA secondary structure prediction methods on RNAs of different size and with respect to different types of structure. According to our tests, on the average, the most accurate predictions obtained by a comparative approach are generated by CentroidAlifold, MXScarna, RNAalifold and TurboFold. On the average, the most accurate predictions obtained by single-sequence analyses are generated by CentroidFold, ContextFold and IPknot. The best comparative methods typically outperform the best single-sequence methods if an alignment of homologous RNA sequences is available. This article presents the results of our benchmarks as of 3 October 2012, whereas the rankings presented online are continuously updated. We will gladly include new prediction methods and new measures of accuracy in the new editions of CompaRNA benchmarks.

RILogo: visualizing RNA-RNA interactions

SUMMARY

With the increasing amount of newly discovered non-coding RNAs, the interactions between RNA molecules become an increasingly important aspect for characterizing their functionality. Many computational tools have been developed to predict the formation of duplexes between two RNAs, either based on single sequences or alignments of homologous sequences. Here, we present RILogo, a program to visualize inter- and intramolecular base pairing between two RNA molecules. The input for RILogo is a pair of structure-annotated sequences or alignments. In the latter case, RILogo displays the alignments in the form of sequence logos, including the mutual information of base paired columns. We also introduce two novel mutual information based measures that weigh the covariance information by the evolutionary distances of the aligned sequences. We show that the new measures have an increased accuracy compared with previous mutual information measures.

AVAILABILITY AND IMPLEMENTATION

RILogo is freely available as a stand-alone program and is accessible via a web server at http://rth.dk/resources/rilogo.

CONTACT

pmenzel@gmail.com

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Transcripts with in silico predicted RNA structure are enriched everywhere in the mouse brain

Background

Post-transcriptional control of gene expression is mostly conducted by specific elements in untranslated regions (UTRs) of mRNAs, in collaboration with specific binding proteins and RNAs. In several well characterized cases, these RNA elements are known to form stable secondary structures. RNA secondary structures also may have major functional implications for long noncoding RNAs (lncRNAs). Recent transcriptional data has indicated the importance of lncRNAs in brain development and function. However, no methodical efforts to investigate this have been undertaken. Here, we aim to systematically analyze the potential for RNA structure in brain-expressed transcripts.

Results

By comprehensive spatial expression analysis of the adult mouse in situ hybridization data of the Allen Mouse Brain Atlas, we show that transcripts (coding as well as non-coding) associated with in silico predicted structured probes are highly and significantly enriched in almost all analyzed brain regions. Functional implications of these RNA structures and their role in the brain are discussed in detail along with specific examples. We observe that mRNAs with a structure prediction in their UTRs are enriched for binding, transport and localization gene ontology categories. In addition, after manual examination we observe agreement between RNA binding protein interaction sites near the 3’ UTR structures and correlated expression patterns.

Conclusions

Our results show a potential use for RNA structures in expressed coding as well as noncoding transcripts in the adult mouse brain, and describe the role of structured RNAs in the context of intracellular signaling pathways and regulatory networks. Based on this data we hypothesize that RNA structure is widely involved in transcriptional and translational regulatory mechanisms in the brain and ultimately plays a role in brain function.

Rtips: fast and accurate tools for RNA 2D structure prediction using integer programming

We present a web-based tool set Rtips for fast and accurate prediction of RNA 2D complex structures. Rtips comprises two computational tools based on integer programming, IPknot for predicting RNA secondary structures with pseudoknots and RactIP for predicting RNA–RNA interactions with kissing hairpins. Both servers can run much faster than existing services with the same purpose on large data sets as well as being at least comparable in prediction accuracy. The Rtips web server along with the stand-alone programs is freely accessible at http://rna.naist.jp/.

Bidirectional regulation between WDR83 and its natural antisense transcript DHPS in gastric cancer

Natural antisense transcripts (NATs) exist ubiquitously in mammalian genomes and play roles in the regulation of gene expression. However, both the existence of bidirectional antisense RNA regulation and the possibility of protein-coding genes that function as antisense RNAs remain speculative. Here, we found that the protein-coding gene, deoxyhypusine synthase (DHPS), as the NAT of WDR83, concordantly regulated the expression of WDR83 mRNA and protein. Conversely, WDR83 also regulated DHPS by antisense pairing in a concordant manner. WDR83 and DHPS were capable of forming an RNA duplex at overlapping 3' untranslated regions and this duplex increased their mutual stability, which was required for the bidirectional regulation. As a pair of protein-coding cis-sense/antisense transcripts, WDR83 and DHPS were upregulated simultaneously and correlated positively in gastric cancer (GC), driving GC pathophysiology by promoting cell proliferation. Furthermore, the positive relationship between WDR83 and DHPS was also observed in other cancers. The bidirectional regulatory relationship between WDR83 and DHPS not only enriches our understanding of antisense regulation, but also provides a more complete understanding of their functions in tumor development.