In Vivo Mapping of Eukaryotic RNA Interactomes Reveals Principles of Higher-Order Organization and Regulation

Topoisomerase IIα represses transcription by enforcing promoter-proximal pausing

Accumulation of topological stress in the form of DNA supercoiling is inherent to the advance of RNA polymerase II (Pol II) and needs to be resolved by DNA topoisomerases to sustain productive transcriptional elongation. Topoisomerases are therefore considered positive facilitators of transcription. Here, we show that, in contrast to this general assumption, human topoisomerase IIα (TOP2A) activity at promoters represses transcription of immediate early genes such as c-FOS, maintaining them under basal repressed conditions. Thus, TOP2A inhibition creates a particular topological context that results in rapid release from promoter-proximal pausing and transcriptional upregulation, which mimics the typical bursting behavior of these genes in response to physiological stimulus. We therefore describe the control of promoter-proximal pausing by TOP2A as a layer for the regulation of gene expression, which can act as a molecular switch to rapidly activate transcription, possibly by regulating the accumulation of DNA supercoiling at promoter regions.

In vivo structure of the Ty1 retrotransposon RNA genome

Long terminal repeat (LTR)-retrotransposons constitute a significant part of eukaryotic genomes and influence their function and evolution. Like other RNA viruses, LTR-retrotransposons efficiently utilize their RNA genome to interact with host cell machinery during replication. Here, we provide the first genome-wide RNA secondary structure model for a LTR-retrotransposon in living cells. Using SHAPE probing, we explore the secondary structure of the yeast Ty1 retrotransposon RNA genome in its native in vivo state and under defined in vitro conditions. Comparative analyses reveal the strong impact of the cellular environment on folding of Ty1 RNA. In vivo, Ty1 genome RNA is significantly less structured and more dynamic but retains specific well-structured regions harboring functional cis-acting sequences. Ribosomes participate in the unfolding and remodeling of Ty1 RNA, and inhibition of translation initiation stabilizes Ty1 RNA structure. Together, our findings support the dual role of Ty1 genomic RNA as a template for protein synthesis and reverse transcription. This study also contributes to understanding how a complex multifunctional RNA genome folds in vivo, and strengthens the need for studying RNA structure in its natural cellular context.

Inter-dependent Centrosomal Co-localization of the cen and ik2 cis-Natural Antisense mRNAs in Drosophila

Overlapping genes are prevalent in most genomes, but the extent to which this organization influences regulatory events operating at the post-transcriptional level remains unclear. Studying the cen and ik2 genes of Drosophila melanogaster, which are convergently transcribed as cis-natural antisense transcripts (cis-NATs) with overlapping 3' UTRs, we found that their encoded mRNAs strikingly co-localize to centrosomes. These transcripts physically interact in a 3' UTR-dependent manner, and the targeting of ik2 requires its 3' UTR sequence and the presence of cen mRNA, which serves as the main driver of centrosomal co-localization. The cen transcript undergoes localized translation in proximity to centrosomes, and its localization is perturbed by polysome-disrupting drugs. By interrogating global fractionation-sequencing datasets generated from Drosophila and human cellular models, we find that RNAs expressed as cis-NATs tend to co-localize to specific subcellular fractions. This work suggests that post-transcriptional interactions between RNAs with complementary sequences can dictate their localization fate in the cytoplasm.

The role of RNA-binding proteins in mediating adaptive responses in Gram-positive bacteria

Bacteria are constantly subjected to stressful conditions, such as antibiotic exposure, nutrient limitation and oxidative stress. For pathogenic bacteria, adapting to the host environment, escaping defence mechanisms and coping with antibiotic stress are crucial for their survival and the establishment of a successful infection. Stress adaptation relies heavily on the rate at which the organism can remodel its gene expression programme to counteract the stress. RNA-binding proteins mediating co- and post-transcriptional regulation have recently emerged as important players in regulating gene expression during adaptive responses. Most of the research on these layers of gene expression regulation has been done in Gram-negative model organisms where, thanks to a wide variety of global studies, large post-transcriptional regulatory networks have been uncovered. Unfortunately, our understanding of post-transcriptional regulation in Gram-positive bacteria is lagging behind. One possible explanation for this is that many proteins employed by Gram-negative bacteria are not well conserved in Gram-positives. And even if they are conserved, they do not always play similar roles as in Gram-negative bacteria. This raises the important question whether Gram-positive bacteria regulate gene expression in a significantly different way. The goal of this review was to discuss this in more detail by reviewing the role of well-known RNA-binding proteins in Gram-positive bacteria and by highlighting their different behaviours with respect to some of their Gram-negative counterparts. Finally, the second part of this review introduces several unusual RNA-binding proteins of Gram-positive species that we believe could also play an important role in adaptive responses.

Approaches to Identify and Characterise the Post-Transcriptional Roles of lncRNAs in Cancer

It is becoming increasingly evident that the non-coding genome and transcriptome exert great influence over their coding counterparts through complex molecular interactions. Among non-coding RNAs (ncRNA), long non-coding RNAs (lncRNAs) in particular present increased potential to participate in dysregulation of post-transcriptional processes through both RNA and protein interactions. Since such processes can play key roles in contributing to cancer progression, it is desirable to continue expanding the search for lncRNAs impacting cancer through post-transcriptional mechanisms. The sheer diversity of mechanisms requires diverse resources and methods that have been developed and refined over the past decade. We provide an overview of computational resources as well as proven low-to-high throughput techniques to enable identification and characterisation of lncRNAs in their complex interactive contexts. As more cancer research strategies evolve to explore the non-coding genome and transcriptome, we anticipate this will provide a valuable primer and perspective of how these technologies have matured and will continue to evolve to assist researchers in elucidating post-transcriptional roles of lncRNAs in cancer.

Small nucleolar RNAs: continuing identification of novel members and increasing diversity of their molecular mechanisms of action

Identified five decades ago amongst the most abundant cellular RNAs, small nucleolar RNAs (snoRNAs) were initially described as serving as guides for the methylation and pseudouridylation of ribosomal RNA through direct base pairing. In recent years, however, increasingly powerful high-throughput genomic approaches and strategies have led to the discovery of many new members of the family and surprising diversity in snoRNA functionality and mechanisms of action. SnoRNAs are now known to target RNAs of many biotypes for a wider range of modifications, interact with diverse binding partners, compete with other binders for functional interactions, recruit diverse players to targets and affect protein function and accessibility through direct interaction. This mini-review presents the continuing characterization of the snoRNome through the identification of new snoRNA members and the discovery of their mechanisms of action, revealing a highly versatile noncoding family playing central regulatory roles and connecting the main cellular processes.

Specificity of RNA Folding and Its Association with Evolutionarily Adaptive mRNA Secondary Structures

The secondary structure is a fundamental feature of both noncoding and messenger RNAs. However, our understanding of the secondary structure of mRNA, especially that of the coding regions, remains elusive, likely due to translation and the lack of RNA-binding proteins that sustain the consensus structure, such as those that bind to noncoding RNA. Indeed, mRNA has recently been found to adopt diverse alternative structures, the overall functional significance of which remains untested. We hereby approached this problem by estimating the folding specificity, i.e., the probability that a fragment of RNA folds back to the same partner once refolded. We showed that the folding specificity of mRNA is lower than that of noncoding RNA and exhibits moderate evolutionary conservation. Notably, we found that specific rather than alternative folding is likely evolutionarily adaptive since specific folding is frequently associated with functionally important genes or sites within a gene. Additional analysis in combination with ribosome density suggests the ability to modulate ribosome movement as one potential functional advantage provided by specific folding. Our findings revealed a novel facet of the RNA structurome with important functional and evolutionary implications and indicated a potential method for distinguishing the mRNA secondary structures maintained by natural selection from molecular noise.

In vivo structural characterization of the SARS-CoV-2 RNA genome identifies host proteins vulnerable to repurposed drugs

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic. Understanding of the RNA virus and its interactions with host proteins could improve therapeutic interventions for COVID-19. By using icSHAPE, we determined the structural landscape of SARS-CoV-2 RNA in infected human cells and from refolded RNAs, as well as the regulatory untranslated regions of SARS-CoV-2 and six other coronaviruses. We validated several structural elements predicted in silico and discovered structural features that affect the translation and abundance of subgenomic viral RNAs in cells. The structural data informed a deep-learning tool to predict 42 host proteins that bind to SARS-CoV-2 RNA. Strikingly, antisense oligonucleotides targeting the structural elements and FDA-approved drugs inhibiting the SARS-CoV-2 RNA binding proteins dramatically reduced SARS-CoV-2 infection in cells derived from human liver and lung tumors. Our findings thus shed light on coronavirus and reveal multiple candidate therapeutics for COVID-19 treatment.

ChiRA: an integrated framework for chimeric read analysis from RNA-RNA interactome and RNA structurome data

BACKGROUND

With the advances in next-generation sequencing technologies, it is possible to determine RNA-RNA interaction and RNA structure predictions on a genome-wide level. The reads from these experiments usually are chimeric, with each arm generated from one of the interaction partners. Owing to short read lengths, often these sequenced arms ambiguously map to multiple locations. Thus, inferring the origin of these can be quite complicated. Here we present ChiRA, a generic framework for sensitive annotation of these chimeric reads, which in turn can be used to predict the sequenced hybrids.

RESULTS

Grouping reference loci on the basis of aligned common reads and quantification improved the handling of the multi-mapped reads in contrast to common strategies such as the selection of the longest hit or a random choice among all hits. On benchmark data ChiRA improved the number of correct alignments to the reference up to 3-fold. It is shown that the genes that belong to the common read loci share the same protein families or similar pathways. In published data, ChiRA could detect 3 times more new interactions compared to existing approaches. In addition, ChiRAViz can be used to visualize and filter large chimeric datasets intuitively.

CONCLUSION

ChiRA tool suite provides a complete analysis and visualization framework along with ready-to-use Galaxy workflows and tutorials for RNA-RNA interactome and structurome datasets. Common read loci built by ChiRA can rescue multi-mapped reads on paralogous genes without requiring any information on gene relations. We showed that ChiRA is sensitive in detecting new RNA-RNA interactions from published RNA-RNA interactome datasets.

Secondary Structural Model of MALAT1 Becomes Unstructured in Chronic Myeloid Leukemia and Undergoes Structural Rearrangement in Cervical Cancer

Long noncoding RNAs (lncRNAs) influence cellular function through binding events that often depend on the lncRNA secondary structure. One such lncRNA, metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), is upregulated in many cancer types and has a myriad of protein- and miRNA-binding sites. Recently, a secondary structural model of MALAT1 in noncancerous cells was proposed to form 194 hairpins and 13 pseudoknots. That study postulated that, in cancer cells, the MALAT1 structure likely varies, thereby influencing cancer progression. This work analyzes how that structural model is expected to change in K562 cells, which originated from a patient with chronic myeloid leukemia (CML), and in HeLa cells, which originated from a patient with cervical cancer. Dimethyl sulfate-sequencing (DMS-Seq) data from K562 cells and psoralen analysis of RNA interactions and structure (PARIS) data from HeLa cells were compared to the working structural model of MALAT1 in noncancerous cells to identify sites that likely undergo structural alterations. MALAT1 in K562 cells is predicted to become more unstructured, with almost 60% of examined hairpins in noncancerous cells losing at least half of their base pairings. Conversely, MALAT1 in HeLa cells is predicted to largely maintain its structure, undergoing 18 novel structural rearrangements. Moreover, 50 validated miRNA-binding sites are affected by putative secondary structural changes in both cancer types, such as miR-217 in K562 cells and miR-20a in HeLa cells. Structural changes unique to K562 cells and HeLa cells provide new mechanistic leads into how the structure of MALAT1 may mediate cancer in a cell-type specific manner.

In vivo reconstitution finds multivalent RNA-RNA interactions as drivers of mesh-like condensates

Liquid-like condensates have been thought to be sphere-like. Recently, various condensates with filamentous morphology have been observed in cells. One such condensate is the TIS granule network that shares a large surface area with the rough endoplasmic reticulum and is important for membrane protein trafficking. It has been unclear how condensates with mesh-like shapes but dynamic protein components are formed. In vitro and in vivo reconstitution experiments revealed that the minimal components are a multivalent RNA-binding protein that concentrates RNAs that are able to form extensive intermolecular mRNA-mRNA interactions. mRNAs with large unstructured regions have a high propensity to form a pervasive intermolecular interaction network that acts as condensate skeleton. The underlying RNA matrix prevents full fusion of spherical liquid-like condensates, thus driving the formation of irregularly shaped membraneless organelles. The resulting large surface area may promote interactions at the condensate surface and at the interface with other organelles.

Computational modelling of flavivirus dynamics: The ins and outs

Enveloped viruses such as the flaviviruses represent a significant burden to human health around the world, with hundreds of millions of people each year affected by dengue alone. In an effort to improve our understanding of the molecular basis for the infective mechanisms of these viruses, extensive computational modelling approaches have been applied to elucidate their conformational dynamics. Multiscale protocols have been developed to simulate flavivirus envelopes in close accordance with biophysical data, in particular derived from cryo-electron microscopy, enabling high-resolution refinement of their structures and elucidation of the conformational changes associated with adaptation both to host environments and to immunological factors such as antibodies. Likewise, integrative modelling efforts combining data from biophysical experiments and from genome sequencing with chemical modification are providing unparalleled insights into the architecture of the previously unresolved nucleocapsid complex. Collectively, this work provides the basis for the future rational design of new antiviral therapeutics and vaccine development strategies targeting enveloped viruses.

RNA matchmaking in chromatin regulation

Beyond being the product of gene expression, RNA can also influence the regulation of chromatin. The majority of the human genome has the capacity to be transcribed and the majority of the non-protein-coding transcripts made by RNA Polymerase II are enriched in the nucleus. Many chromatin regulators can bind to these ncRNAs in the nucleus; in some cases, there are clear examples of direct RNA-mediated chromatin regulation mechanisms stemming from these interactions, while others have yet to be determined. Recent studies have highlighted examples of chromatin regulation via RNA matchmaking, a term we use broadly here to describe intermolecular base-pairing interactions between one RNA molecule and an RNA or DNA match. This review provides examples of RNA matchmaking that regulates chromatin processes and summarizes the technical approaches used to capture these events.

The Short- and Long-Range RNA-RNA Interactome of SARS-CoV-2

The Coronaviridae is a family of positive-strand RNA viruses that includes SARS-CoV-2, the etiologic agent of the COVID-19 pandemic. Bearing the largest single-stranded RNA genomes in nature, coronaviruses are critically dependent on long-distance RNA-RNA interactions to regulate the viral transcription and replication pathways. Here we experimentally mapped the in vivo RNA-RNA interactome of the full-length SARS-CoV-2 genome and subgenomic mRNAs. We uncovered a network of RNA-RNA interactions spanning tens of thousands of nucleotides. These interactions reveal that the viral genome and subgenomes adopt alternative topologies inside cells and engage in different interactions with host RNAs. Notably, we discovered a long-range RNA-RNA interaction, the FSE-arch, that encircles the programmed ribosomal frameshifting element. The FSE-arch is conserved in the related MERS-CoV and is under purifying selection. Our findings illuminate RNA structure-based mechanisms governing replication, discontinuous transcription, and translation of coronaviruses and will aid future efforts to develop antiviral strategies.

Genome-wide mapping of SARS-CoV-2 RNA structures identifies therapeutically-relevant elements

SARS-CoV-2 is a betacoronavirus with a linear single-stranded, positive-sense RNA genome, whose outbreak caused the ongoing COVID-19 pandemic. The ability of coronaviruses to rapidly evolve, adapt, and cross species barriers makes the development of effective and durable therapeutic strategies a challenging and urgent need. As for other RNA viruses, genomic RNA structures are expected to play crucial roles in several steps of the coronavirus replication cycle. Despite this, only a handful of functionally-conserved coronavirus structural RNA elements have been identified to date. Here, we performed RNA structure probing to obtain single-base resolution secondary structure maps of the full SARS-CoV-2 coronavirus genome both in vitro and in living infected cells. Probing data recapitulate the previously described coronavirus RNA elements (5' UTR and s2m), and reveal new structures. Of these, ∼10.2% show significant covariation among SARS-CoV-2 and other coronaviruses, hinting at their functionally-conserved role. Secondary structure-restrained 3D modeling of these segments further allowed for the identification of putative druggable pockets. In addition, we identify a set of single-stranded segments in vivo, showing high sequence conservation, suitable for the development of antisense oligonucleotide therapeutics. Collectively, our work lays the foundation for the development of innovative RNA-targeted therapeutic strategies to fight SARS-related infections.

The lncRNA Toolkit: Databases and In Silico Tools for lncRNA Analysis

Long non-coding RNAs (lncRNAs) are a rapidly expanding field of research, with many new transcripts identified each year. However, only a small subset of lncRNAs has been characterized functionally thus far. To aid investigating the mechanisms of action by which new lncRNAs act, bioinformatic tools and databases are invaluable. Here, we review a selection of computational tools and databases for the in silico analysis of lncRNAs, including tissue-specific expression, protein coding potential, subcellular localization, structural conformation, and interaction partners. The assembled lncRNA toolkit is aimed primarily at experimental researchers as a useful starting point to guide wet-lab experiments, mainly containing multi-functional, user-friendly interfaces. With more and more new lncRNA analysis tools available, it will be essential to provide continuous updates and maintain the availability of key software in the future.

Direct Interactions with Nascent Transcripts Is Potentially a Common Targeting Mechanism of Long Non-Coding RNAs

Although thousands of mammalian long non-coding RNAs (lncRNAs) have been reported in the last decade, their functional annotation remains limited. A wet-lab approach to detect functions of a novel lncRNA usually includes its knockdown followed by RNA sequencing and identification of the deferentially expressed genes. However, identification of the molecular mechanism(s) used by the lncRNA to regulate its targets frequently becomes a challenge. Previously, we developed the ASSA algorithm that detects statistically significant inter-molecular RNA-RNA interactions. Here we designed a workflow that uses ASSA predictions to estimate the ability of an lncRNA to function via direct base pairing with the target transcripts (co- or post-transcriptionally). The workflow was applied to 300+ lncRNA knockdown experiments from the FANTOM6 pilot project producing statistically significant predictions for 71 unique lncRNAs (104 knockdowns). Surprisingly, the majority of these lncRNAs were likely to function co-transcriptionally, i.e., hybridize with the nascent transcripts of the target genes. Moreover, a number of the obtained predictions were supported by independent iMARGI experimental data on co-localization of lncRNA and chromatin. We detected an evolutionarily conserved lncRNA CHASERR (AC013394.2 or LINC01578) that could regulate target genes co-transcriptionally via interaction with a nascent transcript by directing CHD2 helicase. The obtained results suggested that this nuclear lncRNA may be able to activate expression of the target genes in trans by base-pairing with the nascent transcripts and directing the CHD2 helicase to the regulated promoters leading to open the chromatin and active transcription. Our study highlights the possible importance of base-pairing between nuclear lncRNAs and nascent transcripts for the regulation of gene expression.

RNA structure-wide discovery of functional interactions with multiplexed RNA motif library

Biochemical assays and computational analyses have discovered RNA structures throughout various transcripts. However, the roles of these structures are mostly unknown. Here we develop folded RNA element profiling with structure library (FOREST), a multiplexed affinity assay system to identify functional interactions from transcriptome-wide RNA structure datasets. We generate an RNA structure library by extracting validated or predicted RNA motifs from gene-annotated RNA regions. The RNA structure library with an affinity enrichment assay allows for the comprehensive identification of target-binding RNA sequences and structures in a high-throughput manner. As a proof-of-concept, FOREST discovers multiple RNA-protein interaction networks with quantitative scores, including translational regulatory elements that function in living cells. Moreover, FOREST reveals different binding landscapes of RNA G-quadruplex (rG4) structures-binding proteins and discovers rG4 structures in the terminal loops of precursor microRNAs. Overall, FOREST serves as a versatile platform to investigate RNA structure-function relationships on a large scale.

Structured RNA motifs can be obtained by structure probing, duplex capture, and motif prediction. Here the authors develop a multiplexed affinity assay system to identify functional protein interactors from an RNA structure library with validated or predicted RNA motifs.

The International Virus Bioinformatics Meeting 2020

The International Virus Bioinformatics Meeting 2020 was originally planned to take place in Bern, Switzerland, in March 2020. However, the COVID-19 pandemic put a spoke in the wheel of almost all conferences to be held in 2020. After moving the conference to 8-9 October 2020, we got hit by the second wave and finally decided at short notice to go fully online. On the other hand, the pandemic has made us even more aware of the importance of accelerating research in viral bioinformatics. Advances in bioinformatics have led to improved approaches to investigate viral infections and outbreaks. The International Virus Bioinformatics Meeting 2020 has attracted approximately 120 experts in virology and bioinformatics from all over the world to join the two-day virtual meeting. Despite concerns being raised that virtual meetings lack possibilities for face-to-face discussion, the participants from this small community created a highly interactive scientific environment, engaging in lively and inspiring discussions and suggesting new research directions and questions. The meeting featured five invited and twelve contributed talks, on the four main topics: (1) proteome and RNAome of RNA viruses, (2) viral metagenomics and ecology, (3) virus evolution and classification and (4) viral infections and immunology. Further, the meeting featured 20 oral poster presentations, all of which focused on specific areas of virus bioinformatics. This report summarizes the main research findings and highlights presented at the meeting.

R-chie: a web server and R package for visualizing cis and trans RNA-RNA, RNA-DNA and DNA-DNA interactions

Interactions between biological entities are key to understanding their potential functional roles. Three fields of research have recently made particular progress: the investigation of transRNA-RNA and RNA-DNA transcriptome interactions and of trans DNA-DNA genome interactions. We now have both experimental and computational methods for examining these interactions in vivo and on a transcriptome- and genome-wide scale, respectively. Often, key insights can be gained by visually inspecting figures that manage to combine different sources of evidence and quantitative information. We here present R-chie, a web server and R package for visualizing cis and transRNA-RNA, RNA-DNA and DNA-DNA interactions. For this, we have completely revised and significantly extended an earlier version of R-chie (1) which was initially introduced for visualizing RNA secondary structure features. The new R-chie offers a range of unique features for visualizing cis and transRNA-RNA, RNA-DNA and DNA-DNA interactions. Particularly note-worthy features include the ability to incorporate evolutionary information, e.g. multiple-sequence alignments, to compare two alternative sets of information and to incorporate detailed, quantitative information. R-chie is readily available via a web server as well as a corresponding R package called R4RNA which can be used to run the software locally.

An improved 4'-aminomethyltrioxsalen-based nucleic acid crosslinker for biotinylation of double-stranded DNA or RNA

Nucleic acid crosslinkers that covalently join complementary strands of DNA/RNA have applications in both pharmaceuticals and as biochemical probes. Psoralen is a popular crosslinking moiety that reacts with double stranded DNA and RNA upon exposure to longwave UV light. The commercially available compound EZ-link psoralen-PEG3-biotin has been used in numerous studies to crosslink DNA and double-stranded RNA for genome-wide investigations. Here we present a new probe, AP3B, which uses the psoralen derivative, 4'-aminomethyltrioxsalen, to crosslink and biotinylate nucleic acids. We show that AP3B is 4 to 5 times more effective at labeling DNA in cells and produces a comparable number of crosslinks with over 100 times less compound and less exposure to UV light in vitro than EZ-link psoralen-PEG3-biotin.

Determination of isoform-specific RNA structure with nanopore long reads

Current methods for determining RNA structure with short-read sequencing cannot capture most differences between distinct transcript isoforms. Here we present RNA structure analysis using nanopore sequencing (PORE-cupine), which combines structure probing using chemical modifications with direct long-read RNA sequencing and machine learning to detect secondary structures in cellular RNAs. PORE-cupine also captures global structural features, such as RNA-binding-protein binding sites and reactivity differences at single-nucleotide variants. We show that shared sequences in different transcript isoforms of the same gene can fold into different structures, highlighting the importance of long-read sequencing for obtaining phase information. We also demonstrate that structural differences between transcript isoforms of the same gene lead to differences in translation efficiency. By revealing isoform-specific RNA structure, PORE-cupine will deepen understanding of the role of structures in controlling gene regulation.

On the Way to Understanding the Interplay between the RNA Structure and Functions in Cells: A Genome-Wide Perspective

RNAs adopt specific structures in order to perform their biological activities. The structure of RNA is an important layer of gene expression regulation, and can impact a plethora of cellular processes, starting with transcription, RNA processing, and translation, and ending with RNA turnover. The development of high-throughput technologies has enabled a deeper insight into the sophisticated interplay between the structure of the cellular transcriptome and the living cells environment. In this review, we present the current view on the RNA structure in vivo resulting from the most recent transcriptome-wide studies in different organisms, including mammalians, yeast, plants, and bacteria. We focus on the relationship between the mRNA structure and translation, mRNA stability and degradation, protein binding, and RNA posttranscriptional modifications.

RNA structures in alternative splicing and back-splicing

Alternative splicing greatly expands the transcriptomic and proteomic diversities related to physiological and developmental processes in higher eukaryotes. Splicing of long noncoding RNAs, and back- and trans- splicing further expanded the regulatory repertoire of alternative splicing. RNA structures were shown to play an important role in regulating alternative splicing and back-splicing. Application of novel sequencing technologies made it possible to identify genome-wide RNA structures and interaction networks, which might provide new insights into RNA splicing regulation in vitro to in vivo. The emerging transcription-folding-splicing paradigm is changing our understanding of RNA alternative splicing regulation. Here, we review the insights into the roles and mechanisms of RNA structures in alternative splicing and back-splicing, as well as how disruption of these structures affects alternative splicing and then leads to human diseases. This article is categorized under: RNA Processing > Splicing Regulation/Alternative Splicing RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems.

Mechanisms and Regulation of RNA Condensation in RNP Granule Formation

Ribonucleoprotein (RNP) granules are RNA-protein assemblies that are involved in multiple aspects of RNA metabolism and are linked to memory, development, and disease. Some RNP granules form, in part, through the formation of intermolecular RNA-RNA interactions. In vitro, such trans RNA condensation occurs readily, suggesting that cells require mechanisms to modulate RNA-based condensation. We assess the mechanisms of RNA condensation and how cells modulate this phenomenon. We propose that cells control RNA condensation through ATP-dependent processes, static RNA buffering, and dynamic post-translational mechanisms. Moreover, perturbations in these mechanisms can be involved in disease. This reveals multiple cellular mechanisms of kinetic and thermodynamic control that maintain the proper distribution of RNA molecules between dispersed and condensed forms.

Long non-coding RNAs and transposable elements: A functional relationship

Long non-coding RNAs (lncRNAs) have become increasingly important in the past decade. They are known to regulate gene expression and to interact with chromatin, proteins and other coding and non-coding RNAs. The study of lncRNAs has been challenging due to their low expression and the lack of tools developed to adapt to their particular features. Studies on lncRNAs performed to date have largely focused on cellular functions, whereas details on the mechanism of action has only been thoroughly investigated for a small number of lncRNAs. Nevertheless, some studies have highlighted the potential of these transcripts to contain functional domains, following the same accepted trend as proteins. Interestingly, many of these identified "domains" are attributed to functional units derived from transposable elements. Here, we review several types of functions of lncRNAs and relate these functions to lncRNA-embedded transposable elements.

Principles and innovative technologies for decrypting noncoding RNAs: from discovery and functional prediction to clinical application

Noncoding RNAs (ncRNAs) are a large segment of the transcriptome that do not have apparent protein-coding roles, but they have been verified to play important roles in diverse biological processes, including disease pathogenesis. With the development of innovative technologies, an increasing number of novel ncRNAs have been uncovered; information about their prominent tissue-specific expression patterns, various interaction networks, and subcellular locations will undoubtedly enhance our understanding of their potential functions. Here, we summarized the principles and innovative methods for identifications of novel ncRNAs that have potential functional roles in cancer biology. Moreover, this review also provides alternative ncRNA databases based on high-throughput sequencing or experimental validation, and it briefly describes the current strategy for the clinical translation of cancer-associated ncRNAs to be used in diagnosis.

Intrinsic Regulatory Role of RNA Structural Arrangement in Alternative Splicing Control

Alternative splicing is a highly sophisticated process, playing a significant role in posttranscriptional gene expression and underlying the diversity and complexity of organisms. Its regulation is multilayered, including an intrinsic role of RNA structural arrangement which undergoes time- and tissue-specific alterations. In this review, we describe the principles of RNA structural arrangement and briefly decipher its cis- and trans-acting cellular modulators which serve as crucial determinants of biological functionality of the RNA structure. Subsequently, we engage in a discussion about the RNA structure-mediated mechanisms of alternative splicing regulation. On one hand, the impairment of formation of optimal RNA structures may have critical consequences for the splicing outcome and further contribute to understanding the pathomechanism of severe disorders. On the other hand, the structural aspects of RNA became significant features taken into consideration in the endeavor of finding potential therapeutic treatments. Both aspects have been addressed by us emphasizing the importance of ongoing studies in both fields.

mRNA structural dynamics shape Argonaute-target interactions

Small interfering RNAs (siRNAs) promote RNA degradation in a variety of processes and have important clinical applications. siRNAs direct cleavage of target RNAs by guiding Argonaute2 (AGO2) to its target site. Target site accessibility is critical for AGO2-target interactions, but how target site accessibility is controlled in vivo is poorly understood. Here, we use live-cell single-molecule imaging in human cells to determine rate constants of the AGO2 cleavage cycle in vivo. We find that the rate-limiting step in mRNA cleavage frequently involves unmasking of target sites by translating ribosomes. Target site masking is caused by heterogeneous intramolecular RNA-RNA interactions, which can conceal target sites for many minutes in the absence of translation. Our results uncover how dynamic changes in mRNA structure shape AGO2-target recognition, provide estimates of mRNA folding and unfolding rates in vivo, and provide experimental evidence for the role of mRNA structural dynamics in control of mRNA-protein interactions.

Making ends meet: New functions of mRNA secondary structure

The 5' cap and 3' poly(A) tail of mRNA are known to synergistically regulate mRNA translation and stability. Recent computational and experimental studies revealed that both protein-coding and non-coding RNAs will fold with extensive intramolecular secondary structure, which will result in close distances between the sequence ends. This proximity of the ends is a sequence-independent, universal property of most RNAs. Only low-complexity sequences without guanosines are without secondary structure and exhibit end-to-end distances expected for RNA random coils. The innate proximity of RNA ends might have important biological implications that remain unexplored. In particular, the inherent compactness of mRNA might regulate translation initiation by facilitating the formation of protein complexes that bridge mRNA 5' and 3' ends. Additionally, the proximity of mRNA ends might mediate coupling of 3' deadenylation to 5' end mRNA decay. This article is categorized under: RNA Structure and Dynamics > RNA Structure, Dynamics, and Chemistry RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems Translation > Translation Regulation.

The Sponge RNAs of bacteria - How to find them and their role in regulating the post-transcriptional network

In bacteria small regulatory RNAs (sRNAs) interact with their mRNA targets through non-consecutive base-pairing. The loose base-pairing specificity allows sRNAs to regulate large numbers of genes, either affecting the stability and/or the translation of mRNAs. Mechanisms enabling post-transcriptional regulation of the sRNAs themselves have also been described involving so-called sponge RNAs. Sponge RNAs modulate free sRNA levels in the cell through RNA-RNA interactions that sequester ("soak up") the sRNA and/or promote degradation of the target sRNA or the sponge RNA-sRNA complex. The development of complex RNA sequencing strategies for the detection of RNA-RNA interactions has enabled identification of several sponge RNAs, as well as previously known regulatory RNAs able to act as both regulators and sponges. This review highlights techniques that have enabled the identification of these sponge RNAs, the origins of sponge RNAs and the mechanisms by which they function in the post-transcriptional network.

snoDB: an interactive database of human snoRNA sequences, abundance and interactions

Small nucleolar RNAs (snoRNAs) are an abundant type of non-coding RNA with conserved functions in all known eukaryotes. Classified into two main families, the box C/D and H/ACA snoRNAs, they enact their most well characterized role of guiding site specific modifications in ribosomal RNA, through the formation of specific ribonucleoprotein complexes, with fundamental implications in ribosome biogenesis. However, it is becoming increasingly clear that the landscape of snoRNA cellular functionality is much broader than it once seemed with novel members, non-uniform expression patterns, new and diverse targets as well as several emerging non-canonical functions ranging from the modulation of alternative splicing to the regulation of chromatin architecture. In order to facilitate the further characterization of human snoRNAs in a holistic manner, we introduce an online interactive database tool: snoDB. Its purpose is to consolidate information on human snoRNAs from different sources such as sequence databases, target information, both canonical and non-canonical from the literature and from high-throughput RNA-RNA interaction datasets, as well as high-throughput sequencing data that can be visualized interactively.

RIC-seq for global in situ profiling of RNA-RNA spatial interactions

Highly structured RNA molecules usually interact with each other, and associate with various RNA-binding proteins, to regulate critical biological processes. However, RNA structures and interactions in intact cells remain largely unknown. Here, by coupling proximity ligation mediated by RNA-binding proteins with deep sequencing, we report an RNA in situ conformation sequencing (RIC-seq) technology for the global profiling of intra- and intermolecular RNA-RNA interactions. This technique not only recapitulates known RNA secondary structures and tertiary interactions, but also facilitates the generation of three-dimensional (3D) interaction maps of RNA in human cells. Using these maps, we identify noncoding RNA targets globally, and discern RNA topological domains and trans-interacting hubs. We reveal that the functional connectivity of enhancers and promoters can be assigned using their pairwise-interacting RNAs. Furthermore, we show that CCAT1-5L-a super-enhancer hub RNA-interacts with the RNA-binding protein hnRNPK, as well as RNA derived from the MYC promoter and enhancer, to boost MYC transcription by modulating chromatin looping. Our study demonstrates the power and applicability of RIC-seq in discovering the 3D structures, interactions and regulatory roles of RNA.

RNA Conformation Capture by Proximity Ligation

RNA proximity ligation is a set of molecular biology techniques used to analyze the conformations and spatial proximity of RNA molecules within cells. A typical experiment starts with cross-linking of a biological sample using UV light or psoralen, followed by partial fragmentation of RNA, RNA-RNA ligation, library preparation, and high-throughput sequencing. In the past decade, proximity ligation has been used to study structures of individual RNAs, networks of interactions between small RNAs and their targets, and whole RNA-RNA interactomes, in models ranging from bacteria to animal tissues and whole animals. Here, we provide an overview of the field, highlight the main findings, review the recent experimental and computational developments, and provide troubleshooting advice for new users. In the final section, we draw parallels between DNA and RNA proximity ligation and speculate on possible future research directions.

Functional diversity of small nucleolar RNAs

Small nucleolar RNAs (snoRNAs) are short non-protein-coding RNAs with a long-recognized role in tuning ribosomal and spliceosomal function by guiding ribose methylation and pseudouridylation at targeted nucleotide residues of ribosomal and small nuclear RNAs, respectively. SnoRNAs are increasingly being implicated in regulation of new types of post-transcriptional processes, for example rRNA acetylation, modulation of splicing patterns, control of mRNA abundance and translational efficiency, or they themselves are processed to shorter stable RNA species that seem to be the principal or alternative bioactive isoform. Intriguingly, some display unusual cellular localization under exogenous stimuli, or tissue-specific distribution. Here, we discuss the new and unforeseen roles attributed to snoRNAs, focusing on the presumed mechanisms of action. Furthermore, we review the experimental approaches to study snoRNA function, including high resolution RNA:protein and RNA:RNA interaction mapping, techniques for analyzing modifications on targeted RNAs, and cellular and animal models used in snoRNA biology research.

irCLASH reveals RNA substrates recognized by human ADARs

Adenosine deaminases acting on RNA (ADARs) convert adenosines to inosines in double-stranded RNA (dsRNA) in animals. Despite their importance, ADAR RNA substrates have not been mapped extensively in vivo. Here we develop irCLASH to map RNA substrates recognized by human ADARs and uncover features that determine their binding affinity and editing efficiency. We also observe a dominance of long-range interactions within ADAR substrates and analyze differences between ADAR1 and ADAR2 editing substrates. Moreover, we unexpectedly discovered that ADAR proteins bind dsRNA substrates tandemly in vivo, each with a 50-bp footprint. Using RNA duplexes recognized by ADARs as readout of pre-messenger RNA structures, we reveal distinct higher-order architectures between pre-messenger RNAs and mRNAs. Our transcriptome-wide atlas of ADAR substrates and the features governing RNA editing observed in our study will assist in the rational design of guide RNAs for ADAR-mediated RNA base editing.

Functions and properties of nuclear lncRNAs-from systematically mapping the interactomes of lncRNAs

Protein and DNA have been considered as the major components of chromatin. But beyond that, an increasing number of studies show that RNA occupies a large amount of chromatin and acts as a regulator of nuclear architecture. A significant fraction of long non-coding RNAs (lncRNAs) prefers to stay in the nucleus and cooperate with protein complexes to modulate epigenetic regulation, phase separation, compartment formation, and nuclear organization. An RNA strand also can invade into double-stranded DNA to form RNA:DNA hybrids (R-loops) in living cells, contributing to the regulation of gene expression and genomic instability. In this review, we discuss how nuclear lncRNAs orchestrate cellular processes through their interactions with proteins and DNA and summarize the recent genome-wide techniques to study the functions of lncRNAs by revealing their interactomes in vivo.

A Nested 2-Level Cross-Validation Ensemble Learning Pipeline Suggests a Negative Pressure Against Crosstalk snoRNA-mRNA Interactions in Saccharomyces cerevisiae

The growing number of RNA-mediated regulation mechanisms identified in the past decades suggests a widespread impact of RNA-RNA interactions. The efficiency of the regulation relies on highly specific and coordinated interactions while simultaneously repressing the formation of opportunistic complexes. However, the analysis of RNA interactomes is highly challenging because of the large number of potential partners, discrepancy of the size of RNA families, and the inherent noise in interaction predictions. We designed a recursive two-step cross-validation pipeline to capture the specificity of noncoding RNA (ncRNA) messenger RNA (mRNA) interactomes. Our method has been designed to detect significant loss or gain of specificity between ncRNA-mRNA interaction profiles. Applied to small nucleolar RNA-mRNA in Saccharomyces cerevisiae, our results suggest the existence of a repression of ncRNA affinities with mRNAs and thus the existence of an evolutionary pressure leveling down such interactions.

The landscape of eukaryotic mRNPs

The proper regulation of mRNA processing, localization, translation, and degradation occurs on mRNPs. However, the global principles of mRNP organization are poorly understood. We utilize the limited, but existing, information available to present a speculative synthesis of mRNP organization with the following key points. First, mRNPs form a compacted structure due to the inherent folding of RNA. Second, the ribosome is the principal mechanism by which mRNA regions are partially decompacted. Third, mRNPs are 50%-80% protein by weight, consistent with proteins modulating mRNP organization, but also suggesting the majority of mRNA sequences are not directly interacting with RNA-binding proteins. Finally, the ratio of mRNA-binding proteins to mRNAs is higher in the nucleus to allow effective RNA processing and limit the potential for nuclear RNA based aggregation. This synthesis of mRNP understanding provides a model for mRNP biogenesis, structure, and regulation with multiple implications.

Alternative Splicing Regulatory Networks: Functions, Mechanisms, and Evolution

High-throughput sequencing-based methods and their applications in the study of transcriptomes have revolutionized our understanding of alternative splicing. Networks of functionally coordinated and biologically important alternative splicing events continue to be discovered in an ever-increasing diversity of cell types in the context of physiologically normal and disease states. These studies have been complemented by efforts directed at defining sequence codes governing splicing and their cognate trans-acting factors, which have illuminated important combinatorial principles of regulation. Additional studies have revealed critical roles of position-dependent, multivalent protein-RNA interactions that direct splicing outcomes. Investigations of evolutionary changes in RNA binding proteins, splice variants, and associated cis elements have further shed light on the emergence, mechanisms, and functions of splicing networks. Progress in these areas has emphasized the need for a coordinated, community-based effort to systematically address the functions of individual splice variants associated with normal and disease biology.

RNA: interactions drive functionalities

RNA is produced from the majority of human genomic sequences, although only a relatively small portion of these transcripts has known functions. Diverse RNA species interact with RNA, DNA, proteins, lipids, and metabolites to form intricate molecular networks. In this review, we attempt to delineate diverse RNA functions by interaction types between RNA and other macromolecules. Through such interactions RNAs participate in essentially every major molecular function and process, including information flow and storage, environment sensing, signal transduction, and gene regulation at transcriptional and posttranscriptional levels. Through such interactions, RNAs promote or inhibit diverse biological processes, and act as catalyzer or quencher to modulate the pace of these progresses. Alterations and personal variations of these interactions are mechanistically coupled with disease etiology and phenotypical variations for clinical use.

Multiscale modelling and simulation of viruses

In recent years, advances in structural biology, integrative modelling, and simulation approaches have allowed us to gain unprecedented insights into viral structure and dynamics. In this article we survey recent studies utilizing this wealth of structural information to build computational models of partial or complete viruses and to elucidate mechanisms of viral function. Additionally, the close interplay of viral pathogens with host factors - such as cellular and intracellular membranes, receptors, antibodies, and other host proteins - makes accurate models of viral interactions and dynamics essential. As viruses continue to pose severe challenges in prevention and treatment, enhancing our mechanistic understanding of viral infection is vital to enable the development of novel therapeutic strategies.

Secondary Structural Model of Human MALAT1 Reveals Multiple Structure-Function Relationships

Human metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is an abundant nuclear-localized long noncoding RNA (lncRNA) that has significant roles in cancer. While the interacting partners and evolutionary sequence conservation of MALAT1 have been examined, much of the structure of MALAT1 is unknown. Here, we propose a hypothetical secondary structural model for 8425 nucleotides of human MALAT1 using three experimental datasets that probed RNA structures in vitro and in various human cell lines. Our model indicates that approximately half of human MALAT1 is structured, forming 194 helices, 13 pseudoknots, five structured tetraloops, nine structured internal loops, and 13 intramolecular long-range interactions that give rise to several multiway junctions. Evolutionary conservation and covariation analyses support 153 of 194 helices in 51 mammalian MALAT1 homologs and 42 of 194 helices in 53 vertebrate MALAT1 homologs, thereby identifying an evolutionarily conserved core that likely has important functional roles in mammals and vertebrates. Data mining revealed that RNA modifications, somatic cancer-associated mutations, and single-nucleotide polymorphisms may induce structural rearrangements that sequester or expose binding sites for several cancer-associated microRNAs. Our findings reveal new mechanistic leads into the roles of MALAT1 by identifying several intriguing structure–function relationships in which the dynamic structure of MALAT1 underlies its biological functions.

Frustration and fidelity in influenza genome assembly

The genome of the influenza virus consists of eight distinct single-stranded RNA segments, each encoding proteins essential for the viral life cycle. When the virus infects a host cell, these segments must be replicated and packaged into new budding virions. The viral genome is assembled with remarkably high fidelity: experiments reveal that most virions contain precisely one copy of each of the eight RNA segments. Cell-biological studies suggest that genome assembly is mediated by specific reversible and irreversible interactions between the RNA segments and their associated proteins. However, the precise inter-segment interaction network remains unresolved. Here, we computationally predict that tree-like irreversible interaction networks guarantee high-fidelity genome assembly, while cyclic interaction networks lead to futile or frustrated off-pathway products. We test our prediction against multiple experimental datasets. We find that tree-like networks capture the nearest-neighbour statistics of RNA segments in packaged virions, as observed by electron tomography. Just eight tree-like networks (of a possible 262 144) optimally capture both the nearest-neighbour data and independently measured RNA–RNA binding and co-localization propensities. These eight do not include the previously proposed hub-and-spoke and linear networks. Rather, each predicted network combines hub-like and linear features, consistent with evolutionary models of interaction gain and loss.

CIRDES: an efficient genome-wide method for in vivo RNA-RNA interactome analysis

Complex RNA-RNA interactions underlie fundamental biological processes. However, a large number of RNA-RNA interactions remain unknown. Most existing methods used to map RNA-RNA interactions are based on proximity ligation, but these strategies also capture a huge amount of intramolecular RNA secondary structures, making it almost impossible to detect most RNA-RNA interactions. To overcome this limitation, we developed an efficient, genome-wide method, Capture Interacting RNA and Deep Sequencing (CIRDES) for in vivo capturing of the RNA interactome. We designed multiple 20-nt CIRDES probes tiling the whole RNA sequence of interest. This strategy obtained high selectivity and low background noise proved by qRT-PCR data. CIRDES enriched target RNA and its interacting RNAs from cells crosslinked by formaldehyde in high efficiency. After hybridization and purification, the captured RNAs were converted to the cDNA library after a highly efficient ligation to a 3' end infrared-dye-conjugated RNA adapter based on adapter ligation library construction. Using CIRDES, we detected highly abundant known interacting RNA, as well as a large number of novel targets of U6 snRNA. The enrichment of U4 snRNA, which interacts with U6, confirmed the robustness of the identification of the RNA-RNA interaction by CIRDES. These results suggest that the CIRDES is an efficient strategy for genome-wide RNA-RNA interactome analysis.