RNA Duplex Map in Living Cells Reveals Higher-Order Transcriptome Structure

Identification of RNA structures and their roles in RNA functions

The development of high-throughput RNA structure profiling methods in the past decade has greatly facilitated our ability to map and characterize different aspects of RNA structures transcriptome-wide in cell populations, single cells and single molecules. The resulting high-resolution data have provided insights into the static and dynamic nature of RNA structures, revealing their complexity as they perform their respective functions in the cell. In this Review, we discuss recent technical advances in the determination of RNA structures, and the roles of RNA structures in RNA biogenesis and functions, including in transcription, processing, translation, degradation, localization and RNA structure-dependent condensates. We also discuss the current understanding of how RNA structures could guide drug design for treating genetic diseases and battling pathogenic viruses, and highlight existing challenges and future directions in RNA structure research.

Probing RNA structure and dynamics using nanopore and next generation sequencing

It has become increasingly evident that the structures RNAs adopt are conformationally dynamic; the various structured states that RNAs sample govern their interactions with other nucleic acids, proteins, and ligands to regulate a myriad of biological processes. Although several biophysical approaches have been developed and used to study the dynamic landscape of structured RNAs, technical limitations have limited their application to all classes of RNA due to variable size and flexibility. Recent advances combining chemical probing experiments with next-generation- and direct sequencing have emerged as an alternative approach to exploring the conformational dynamics of RNA. In this review, we provide a methodological overview of the sequencing-based techniques used to study RNA conformational dynamics. We discuss how different techniques have enabled us to better understand the propensity of RNAs from a variety of different classes to sample multiple conformational states. Finally, we present examples of the ways these techniques have reshaped how we think about RNA structure.

ChimericFragments: computation, analysis and visualization of global RNA networks

RNA-RNA interactions are a key feature of post-transcriptional gene regulation in all domains of life. While ever more experimental protocols are being developed to study RNA duplex formation on a genome-wide scale, computational methods for the analysis and interpretation of the underlying data are lagging behind. Here, we present ChimericFragments, an analysis framework for RNA-seq experiments that produce chimeric RNA molecules. ChimericFragments implements a novel statistical method based on the complementarity of the base-pairing RNAs around their ligation site and provides an interactive graph-based visualization for data exploration and interpretation. ChimericFragments detects true RNA-RNA interactions with high precision and is compatible with several widely used experimental procedures such as RIL-seq, LIGR-seq or CLASH. We further demonstrate that ChimericFragments enables the systematic detection of novel RNA regulators and RNA-target pairs with crucial roles in microbial physiology and virulence. ChimericFragments is written in Julia and available at: https://github.com/maltesie/ChimericFragments.

Hidden regulators: the emerging roles of lncRNAs in brain development and disease

Long non-coding RNAs (lncRNAs) have emerged as critical players in brain development and disease. These non-coding transcripts, which once considered as "transcriptional junk," are now known for their regulatory roles in gene expression. In brain development, lncRNAs participate in many processes, including neurogenesis, neuronal differentiation, and synaptogenesis. They employ their effect through a wide variety of transcriptional and post-transcriptional regulatory mechanisms through interactions with chromatin modifiers, transcription factors, and other regulatory molecules. Dysregulation of lncRNAs has been associated with certain brain diseases, including Alzheimer's disease, Parkinson's disease, cancer, and neurodevelopmental disorders. Altered expression and function of specific lncRNAs have been implicated with disrupted neuronal connectivity, impaired synaptic plasticity, and aberrant gene expression pattern, highlighting the functional importance of this subclass of brain-enriched RNAs. Moreover, lncRNAs have been identified as potential biomarkers and therapeutic targets for neurological diseases. Here, we give a comprehensive review of the existing knowledge of lncRNAs. Our aim is to provide a better understanding of the diversity of lncRNA structure and functions in brain development and disease. This holds promise for unravelling the complexity of neurodevelopmental and neurodegenerative disorders, paving the way for the development of novel biomarkers and therapeutic targets for improved diagnosis and treatment.

The selective sponging of miRNAs by OIP5-AS1 regulates metabolic reprogramming of pyruvate in adenoma-carcinoma transition of human colorectal cancer

RNA interactomes and their diversified functionalities have recently benefited from critical methodological advances leading to a paradigm shift from a conventional conception on the regulatory roles of RNA in pathogenesis. However, the dynamic RNA interactomes in adenoma-carcinoma sequence of human CRC remain unexplored. The coexistence of adenoma, cancer, and normal tissues in colorectal cancer (CRC) patients provides an appropriate model to address this issue. Here, we adopted an RNA in situ conformation sequencing technology for mapping RNA-RNA interactions in CRC patients. We observed large-scale paired RNA counts and identified some unique RNA complexes including multiple partners RNAs, single partner RNAs, non-overlapping single partner RNAs. We focused on the antisense RNA OIP5-AS1 and found that OIP5-AS1 could sponge different miRNA to regulate the production of metabolites including pyruvate, alanine and lactic acid. Our findings provide novel perspectives in CRC pathogenesis and suggest metabolic reprogramming of pyruvate for the early diagnosis and treatment of CRC.

Chemical and Enzyme-Mediated Chemical Reactions for Studying Nucleic Acids and Their Modifications

Nucleic acids are genetic information-carrying molecules inside cells. Apart from basic nucleotide building blocks, there exist various naturally occurring chemical modifications on nucleobase and ribose moieties, which greatly increase the encoding complexity of nuclei acids, contribute to the alteration of nucleic acid structures, and play versatile regulation roles in gene expression. To study the functions of certain nucleic acids in various biological contexts, robust tools to specifically label and identify these macromolecules and their modifications, and to illuminate their structures are highly necessary. In this review, we summarize recent technique advances of using chemical and enzyme-mediated chemical reactions to study nucleic acids and their modifications and structures. By highlighting the chemical principles of these techniques, we aim to present a perspective on the advancement of the field as well as to offer insights into developing specific chemical reactions and precise enzyme catalysis utilized for nucleic acids and their modifications.

Discovery and Quantification of Long-Range RNA Base Pairs in Coronavirus Genomes with SEARCH-MaP and SEISMIC-RNA

RNA molecules perform a diversity of essential functions for which their linear sequences must fold into higher-order structures. Techniques including crystallography and cryogenic electron microscopy have revealed 3D structures of ribosomal, transfer, and other well-structured RNAs; while chemical probing with sequencing facilitates secondary structure modeling of any RNAs of interest, even within cells. Ongoing efforts continue increasing the accuracy, resolution, and ability to distinguish coexisting alternative structures. However, no method can discover and quantify alternative structures with base pairs spanning arbitrarily long distances - an obstacle for studying viral, messenger, and long noncoding RNAs, which may form long-range base pairs. Here, we introduce the method of Structure Ensemble Ablation by Reverse Complement Hybridization with Mutational Profiling (SEARCH-MaP) and software for Structure Ensemble Inference by Sequencing, Mutation Identification, and Clustering of RNA (SEISMIC-RNA). We use SEARCH-MaP and SEISMIC-RNA to discover that the frameshift stimulating element of SARS coronavirus 2 base-pairs with another element 1 kilobase downstream in nearly half of RNA molecules, and that this structure competes with a pseudoknot that stimulates ribosomal frameshifting. Moreover, we identify long-range base pairs involving the frameshift stimulating element in other coronaviruses including SARS coronavirus 1 and transmissible gastroenteritis virus, and model the full genomic secondary structure of the latter. These findings suggest that long-range base pairs are common in coronaviruses and may regulate ribosomal frameshifting, which is essential for viral RNA synthesis. We anticipate that SEARCH-MaP will enable solving many RNA structure ensembles that have eluded characterization, thereby enhancing our general understanding of RNA structures and their functions. SEISMIC-RNA, software for analyzing mutational profiling data at any scale, could power future studies on RNA structure and is available on GitHub and the Python Package Index.

RNA: The Unsuspected Conductor in the Orchestra of Macromolecular Crowding

This comprehensive Review delves into the chemical principles governing RNA-mediated crowding events, commonly referred to as granules or biological condensates. We explore the pivotal role played by RNA sequence, structure, and chemical modifications in these processes, uncovering their correlation with crowding phenomena under physiological conditions. Additionally, we investigate instances where crowding deviates from its intended function, leading to pathological consequences. By deepening our understanding of the delicate balance that governs molecular crowding driven by RNA and its implications for cellular homeostasis, we aim to shed light on this intriguing area of research. Our exploration extends to the methodologies employed to decipher the composition and structural intricacies of RNA granules, offering a comprehensive overview of the techniques used to characterize them, including relevant computational approaches. Through two detailed examples highlighting the significance of noncoding RNAs, NEAT1 and XIST, in the formation of phase-separated assemblies and their influence on the cellular landscape, we emphasize their crucial role in cellular organization and function. By elucidating the chemical underpinnings of RNA-mediated molecular crowding, investigating the role of modifications, structures, and composition of RNA granules, and exploring both physiological and aberrant phase separation phenomena, this Review provides a multifaceted understanding of the intriguing world of RNA-mediated biological condensates.

Natural antisense transcripts as versatile regulators of gene expression

Long non-coding RNAs (lncRNAs) are emerging as a major class of gene products that have central roles in cell and developmental biology. Natural antisense transcripts (NATs) are an important subset of lncRNAs that are expressed from the opposite strand of protein-coding and non-coding genes and are a genome-wide phenomenon in both eukaryotes and prokaryotes. In eukaryotes, a myriad of NATs participate in regulatory pathways that affect expression of their cognate sense genes. Recent developments in the study of NATs and lncRNAs and large-scale sequencing and bioinformatics projects suggest that whether NATs regulate expression, splicing, stability or translation of the sense transcript is influenced by the pattern and degrees of overlap between the sense-antisense pair. Moreover, epigenetic gene regulatory mechanisms prevail in somatic cells whereas mechanisms dependent on the formation of double-stranded RNA intermediates are prevalent in germ cells. The modulating effects of NATs on sense transcript expression make NATs rational targets for therapeutic interventions.

Global identification of mRNA-interacting circular RNAs by CLiPPR-Seq

Although the functional role of circular RNA (circRNA) interaction with microRNAs and proteins has been studied extensively, circRNA interactions with the protein-coding mRNAs in intact cells remain largely unknown. Here, by employing AMT-mediated proximity ligation of RNA-RNA duplexes followed by circRNA enrichment and deep sequencing, we report a novel Cross-Linking Poly(A) Pulldown RNase R Sequencing (CLiPPR-seq) technology which identified hundreds of mRNA-interacting circRNAs in three different cell types, including βTC6, C2C12 and HeLa cells. Furthermore, CLiPP-seq without RNase R treatment was also performed to identify the mRNA expression in these cells. BLAST analysis of circRNAs in CLiPPR-seq sample with the mRNAs in CLiPP-seq samples determined their potential complementary sequences for circRNA-mRNA interaction. Pulldown of circRNAs and poly(A) RNAs confirmed the direct interaction of circRNAs with target mRNAs. Silencing of mRNA-interacting circRNAs led to the altered expression of target mRNAs in βTC6 cells, suggesting the role of direct interaction of circRNAs with mRNAs in gene expression regulation. CLiPPR-seq thus represents a novel method for illuminating the myriad of uncharacterized circRNA-mRNA hybrids that may regulate gene expression.

Spectroscopic view on the interaction between the psoralen derivative amotosalen and DNA

Psoralens are eponymous for PUVA (psoralen plus UV-A radiation) therapy, which inter alia can be used to treat various skin diseases. Based on the same underlying mechanism of action, the synthetic psoralen amotosalen (AMO) is utilized in the pathogen reduction technology of the INTERCEPT® Blood System to inactivate pathogens in plasma and platelet components. The photophysical behavior of AMO in the absence of DNA is remarkably similar to that of the recently studied psoralen 4'-aminomethyl-4,5',8-trimethylpsoralen (AMT). By means of steady-state and time-resolved spectroscopy, intercalation and photochemistry of AMO and synthetic DNA were studied. AMO intercalates with a higher affinity into A,T-only DNA (KD = 8.9 × 10-5 M) than into G,C-only DNA (KD = 6.9 × 10-4 M). AMO covalently photobinds to A,T-only DNA with a reaction quantum yield of ΦR = 0.11. Like AMT, it does not photoreact following intercalation into G,C-only DNA. Femto- and nanosecond transient absorption spectroscopy reveals the characteristic pattern of photobinding to A,T-only DNA. For AMO and G,C-only DNA, signatures of a photoinduced electron transfer are recorded.

Unraveling the role of Xist in X chromosome inactivation: insights from rabbit model and deletion analysis of exons and repeat A

X chromosome inactivation (XCI) is a process that equalizes the expression of X-linked genes between males and females. It relies on Xist, continuously expressed in somatic cells during XCI maintenance. However, how Xist impacts XCI maintenance and its functional motifs remain unclear. In this study, we conducted a comprehensive analysis of Xist, using rabbits as an ideal non-primate model. Homozygous knockout of exon 1, exon 6, and repeat A in female rabbits resulted in embryonic lethality. However, X∆ReAX females, with intact X chromosome expressing Xist, showed no abnormalities. Interestingly, there were no significant differences between females with homozygous knockout of exons 2-5 and wild-type rabbits, suggesting that exons 2, 3, 4, and 5 are less important for XCI. These findings provide evolutionary insights into Xist function.

Mapping of the influenza A virus genome RNA structure and interactions reveals essential elements of viral replication

Influenza A virus (IAV) represents a constant public health threat. The single-stranded, segmented RNA genome of IAV is replicated in host cell nuclei as a series of 8 ribonucleoprotein complexes (vRNPs) with RNA structures known to exert essential function to support viral replication. Here, we investigate RNA secondary structures and RNA interactions networks of the IAV genome and construct an in vivo structure model for each of the 8 IAV genome segments. Our analyses reveal an overall in vivo and in virio resemblance of the IAV genome conformation but also wide disparities among long-range and intersegment interactions. Moreover, we identify a long-range RNA interaction that exerts an essential role in genome packaging. Disrupting this structure displays reduced infectivity, attenuating virus pathogenicity in mice. Our findings characterize the in vivo RNA structural landscape of the IAV genome and reveal viral RNA structures that can be targeted to develop antiviral interventions.

YTHDC1 cooperates with the THO complex to prevent RNA damage-induced DNA breaks

Certain environmental toxins are nucleic acid damaging agents, as are many chemotherapeutics used for cancer therapy. These agents induce various adducts in DNA as well as RNA. Indeed, most of the nucleic acid adducts (>90%) formed due to these chemicals, such as alkylating agents, occur in RNA 1 . However, compared to the well-studied mechanisms for DNA alkylation repair, the biological consequences of RNA damage are largely unexplored. Here, we demonstrate that RNA damage can directly result in loss of genome integrity. Specifically, we show that a human YTH domain-containing protein, YTHDC1, regulates alkylation damage responses in association with the THO complex (THOC) 2 . In addition to its established binding to N 6-methyladenosine (m6A)-containing RNAs, YTHDC1 binds to N 1-methyladenosine (m1A)-containing RNAs upon alkylation. In the absence of YTHDC1, alkylation damage results in increased alkylation damage sensitivity and DNA breaks. Such phenotypes are fully attributable to RNA damage, since an RNA-specific dealkylase can rescue these phenotypes. These R NA d amage-induced DNA b reaks (RDIBs) depend on R-loop formation, which in turn are processed by factors involved in transcription-coupled nucleotide excision repair. Strikingly, in the absence of YTHDC1 or THOC, an RNA m1A methyltransferase targeted to the nucleus is sufficient to induce DNA breaks. Our results uncover a unique role for YTHDC1-THOC in base damage responses by preventing RDIBs, providing definitive evidence for how damaged RNAs can impact genomic integrity.

Accurate prediction of RNA secondary structure including pseudoknots through solving minimum-cost flow with learned potentials

Pseudoknots are key structure motifs of RNA and pseudoknotted RNAs play important roles in a variety of biological processes. Here, we present KnotFold, an accurate approach to the prediction of RNA secondary structure including pseudoknots. The key elements of KnotFold include a learned potential function and a minimum-cost flow algorithm to find the secondary structure with the lowest potential. KnotFold learns the potential from the RNAs with known structures using an attention-based neural network, thus avoiding the inaccuracy of hand-crafted energy functions. The specially designed minimum-cost flow algorithm used by KnotFold considers all possible combinations of base pairs and selects from them the optimal combination. The algorithm breaks the restriction of nested base pairs required by the widely used dynamic programming algorithms, thus enabling the identification of pseudoknots. Using 1,009 pseudoknotted RNAs as representatives, we demonstrate the successful application of KnotFold in predicting RNA secondary structures including pseudoknots with accuracy higher than the state-of-the-art approaches. We anticipate that KnotFold, with its superior accuracy, will greatly facilitate the understanding of RNA structures and functionalities.

AStruct: detection of allele-specific RNA secondary structure in structuromic probing data

BACKGROUND

Uncovering functional genetic variants from an allele-specific perspective is of paramount importance in advancing our understanding of gene regulation and genetic diseases. Recently, various allele-specific events, such as allele-specific gene expression, allele-specific methylation, and allele-specific binding, have been explored on a genome-wide scale due to the development of high-throughput sequencing methods. RNA secondary structure, which plays a crucial role in multiple RNA-associated processes like RNA modification, translation and splicing, has emerged as an essential focus of relevant research. However, tools to identify genetic variants associated with allele-specific RNA secondary structures are still lacking.

RESULTS

Here, we develop a computational tool called 'AStruct' that enables us to detect allele-specific RNA secondary structure (ASRS) from RT-stop based structuromic probing data. AStruct shows robust performance in both simulated datasets and public icSHAPE datasets. We reveal that single nucleotide polymorphisms (SNPs) with higher AStruct scores are enriched in coding regions and tend to be functional. These SNPs are highly conservative, have the potential to disrupt sites involved in m6A modification or protein binding, and are frequently associated with disease.

CONCLUSIONS

AStruct is a tool dedicated to invoke allele-specific RNA secondary structure events at heterozygous SNPs in RT-stop based structuromic probing data. It utilizes allelic variants, base pairing and RT-stop information under different cell conditions to detect dynamic and functional ASRS. Compared to sequence-based tools, AStruct considers dynamic cell conditions and outperforms in detecting functional variants. AStruct is implemented in JAVA and is freely accessible at: https://github.com/canceromics/AStruct .

Dissection of protein and RNA regions required for SPEN binding to XIST A-repeat RNA

XIST noncoding RNA promotes the initiation of X chromosome silencing by recruiting the protein SPEN to one X chromosome in female mammals. The SPEN protein is also called SHARP (SMRT and HDAC-associated repressor protein) and MINT (Msx-2 interacting nuclear target) in humans. SPEN recruits N-CoR2 and HDAC3 to initiate histone deacetylation on the X chromosome, leading to the formation of repressive chromatin marks and silencing gene expression. We dissected the contributions of different RNA and protein regions to the formation of a human XIST-SPEN complex in vitro and identified novel sequence and structure determinants that may contribute to X chromosome silencing initiation. Binding of SPEN to XIST RNA requires RRM 4 of the protein, in contrast to the requirement of RRM 3 and RRM 4 for specific binding to SRA RNA. Measurements of SPEN binding to full-length, dimeric, trimeric, or other truncated versions of the A-repeat region revealed that high-affinity binding of XIST to SPEN in vitro requires a minimum of four A-repeat segments. SPEN binding to XIST A-repeat RNA changes the accessibility of the RNA at specific nucleotide sequences, as indicated by changes in RNA reactivity through chemical structure probing. Based on computational modeling, we found that inter-repeat duplexes formed by multiple A-repeats can present an unpaired adenosine in the context of a double-stranded region of RNA. The presence of this specific combination of sequence and structural motifs correlates with high-affinity SPEN binding in vitro. These data provide new information on the molecular basis of the XIST and SPEN interaction.

Recapitulating and reversing human brain ribosomopathy defects via the maladaptive integrated stress response

Animal or human models recapitulating brain ribosomopathies are incomplete, hampering development of urgently needed therapies. Here, we generated genetic mouse and human cerebral organoid models of brain ribosomopathies, caused by mutations in small nucleolar RNA (snoRNA) SNORD118. Both models exhibited protein synthesis loss, proteotoxic stress, and p53 activation and led to decreased proliferation and increased death of neural progenitor cells (NPCs), resulting in brain growth retardation, recapitulating features in human patients. Loss of SNORD118 function resulted in an aberrant upregulation of p-eIF2α, the mediator of integrated stress response (ISR). Using human iPSC cell-based screen, we identified small-molecule 2BAct, an ISR inhibitor, which potently reverses mutant NPC defects. Targeting ISR by 2BAct mitigated ribosomopathy defects in both cerebral organoid and mouse models. Thus, our SNORD118 mutant organoid and mice recapitulate human brain ribosomopathies and cross-validate maladaptive ISR as a key disease-driving mechanism, pointing to a therapeutic intervention strategy.

KARR-seq reveals cellular higher-order RNA structures and RNA-RNA interactions

RNA fate and function are affected by their structures and interactomes. However, how RNA and RNA-binding proteins (RBPs) assemble into higher-order structures and how RNA molecules may interact with each other to facilitate functions remain largely unknown. Here we present KARR-seq, which uses N3-kethoxal labeling and multifunctional chemical crosslinkers to covalently trap and determine RNA-RNA interactions and higher-order RNA structures inside cells, independent of local protein binding to RNA. KARR-seq depicts higher-order RNA structure and detects widespread intermolecular RNA-RNA interactions with high sensitivity and accuracy. Using KARR-seq, we show that translation represses mRNA compaction under native and stress conditions. We determined the higher-order RNA structures of respiratory syncytial virus (RSV) and vesicular stomatitis virus (VSV) and identified RNA-RNA interactions between the viruses and the host RNAs that potentially regulate viral replication.

Causes, functions, and therapeutic possibilities of RNA secondary structure ensembles and alternative states

RNA secondary structure plays essential roles in encoding RNA regulatory fate and function. Most RNAs populate ensembles of alternatively paired states and are continually unfolded and refolded by cellular processes. Measuring these structural ensembles and their contributions to cellular function has traditionally posed major challenges, but new methods and conceptual frameworks are beginning to fill this void. In this review, we provide a mechanism- and function-centric compendium of the roles of RNA secondary structural ensembles and minority states in regulating the RNA life cycle, from transcription to degradation. We further explore how dysregulation of RNA structural ensembles contributes to human disease and discuss the potential of drugging alternative RNA states to therapeutically modulate RNA activity. The emerging paradigm of RNA structural ensembles as central to RNA function provides a foundation for a deeper understanding of RNA biology and new therapeutic possibilities.

Experimental and computational methods for studying the dynamics of RNA-RNA interactions in SARS-COV2 genomes

Long-range ribonucleic acid (RNA)-RNA interactions (RRI) are prevalent in positive-strand RNA viruses, including Beta-coronaviruses, and these take part in regulatory roles, including the regulation of sub-genomic RNA production rates. Crosslinking of interacting RNAs and short read-based deep sequencing of resulting RNA-RNA hybrids have shown that these long-range structures exist in severe acute respiratory syndrome coronavirus (SARS-CoV)-2 on both genomic and sub-genomic levels and in dynamic topologies. Furthermore, co-evolution of coronaviruses with their hosts is navigated by genetic variations made possible by its large genome, high recombination frequency and a high mutation rate. SARS-CoV-2's mutations are known to occur spontaneously during replication, and thousands of aggregate mutations have been reported since the emergence of the virus. Although many long-range RRIs have been experimentally identified using high-throughput methods for the wild-type SARS-CoV-2 strain, evolutionary trajectory of these RRIs across variants, impact of mutations on RRIs and interaction of SARS-CoV-2 RNAs with the host have been largely open questions in the field. In this review, we summarize recent computational tools and experimental methods that have been enabling the mapping of RRIs in viral genomes, with a specific focus on SARS-CoV-2. We also present available informatics resources to navigate the RRI maps and shed light on the impact of mutations on the RRI space in viral genomes. Investigating the evolution of long-range RNA interactions and that of virus-host interactions can contribute to the understanding of new and emerging variants as well as aid in developing improved RNA therapeutics critical for combating future outbreaks.

CheRRI-Accurate classification of the biological relevance of putative RNA-RNA interaction sites

BACKGROUND

RNA-RNA interactions are key to a wide range of cellular functions. The detection of potential interactions helps to understand the underlying processes. However, potential interactions identified via in silico or experimental high-throughput methods can lack precision because of a high false-positive rate.

RESULTS

We present CheRRI, the first tool to evaluate the biological relevance of putative RNA-RNA interaction sites. CheRRI filters candidates via a machine learning-based model trained on experimental RNA-RNA interactome data. Its unique setup combines interactome data and an established thermodynamic prediction tool to integrate experimental data with state-of-the-art computational models. Applying these data to an automated machine learning approach provides the opportunity to not only filter data for potential false positives but also tailor the underlying interaction site model to specific needs.

CONCLUSIONS

CheRRI is a stand-alone postprocessing tool to filter either predicted or experimentally identified potential RNA-RNA interactions on a genomic level to enhance the quality of interaction candidates. It is easy to install (via conda, pip packages), use (via Galaxy), and integrate into existing RNA-RNA interaction pipelines.

LncRTPred: Predicting RNA-RNA mode of interaction mediated by lncRNA

Long non-coding RNAs (lncRNAs) play a significant role in various biological processes. Hence, it is utmost important to elucidate their functions in order to understand the molecular mechanism of a complex biological system. This versatile RNA molecule has diverse modes of interaction, one of which constitutes lncRNA-mRNA interaction. Hence, identifying its target mRNA is essential to understand the function of an lncRNA explicitly. Existing lncRNA target prediction tools mainly adopt thermodynamics approach. Large execution time and inability to perform real-time prediction limit their usage. Further, lack of negative training dataset has been a hindrance in the path of developing machine learning (ML) based lncRNA target prediction tools. In this work, we have developed a ML-based lncRNA-mRNA target prediction model- 'LncRTPred'. Here we have addressed the existing problems by generating reliable negative dataset and creating robust ML models. We have identified the non-interacting lncRNA and mRNAs from the unlabelled dataset using BLAT. It is further filtered to get a reliable set of outliers. LncRTPred provides a cumulative_model_score as the final output against each query. In terms of prediction accuracy, LncRTPred outperforms other popular target prediction protocols like LncTar. Further, we have tested its performance against experimentally validated disease-specific lncRNA-mRNA interactions. Overall, performance of LncRTPred is heavily dependent on the size of the training dataset, which is highly reflected by the difference in its performance for human and mouse species. Its performance for human species shows better as compared to that for mouse when applied on an unknown data due to smaller size of the training dataset in case of mouse compared to that of human. Availability of increased number of lncRNA-mRNA interaction data for mouse will improve the performance of LncRTPred in future. Both webserver and standalone versions of LncRTPred are available. Web server link: http://bicresources.jcbose.ac.in/zhumur/lncrtpred/index.html. Github Link: https://github.com/zglabDIB/LncRTPred.

RIP-PEN-seq identifies a class of kink-turn RNAs as splicing regulators

A kink-turn (K-turn) is a three-dimensional RNA structure that exists in all three primary phylogenetic domains. In this study, we developed the RIP-PEN-seq method to identify the full-length sequences of RNAs bound by the K-turn binding protein 15.5K and discovered a previously uncharacterized class of RNAs with backward K-turn motifs (bktRNAs) in humans and mice. All bktRNAs share two consensus sequence motifs at their fixed terminal position and have complex folding properties, expression and evolution patterns. We found that a highly conserved bktRNA1 guides the methyltransferase fibrillarin to install RNA methylation of U12 small nuclear RNA in humans. Depletion of bktRNA1 causes global splicing dysregulation of U12-type introns by impairing the recruitment of ZCRB1 to the minor spliceosome. Most bktRNAs regulate the splicing of local introns by interacting with the 15.5K protein. Taken together, our findings characterize a class of small RNAs and uncover another layer of gene expression regulation that involves crosstalk among bktRNAs, RNA splicing and RNA methylation.

The myriad roles of RNA structure in the flavivirus life cycle

As positive-sense RNA viruses, the genomes of flaviviruses serve as the template for all stages of the viral life cycle, including translation, replication, and infectious particle production. Yet, they encode just 10 proteins, suggesting that the structure and dynamics of the viral RNA itself helps shepherd the viral genome through these stages. Herein, we highlight advances in our understanding of flavivirus RNA structural elements through the lens of their impact on the viral life cycle. We highlight how RNA structures impact translation, the switch from translation to replication, negative- and positive-strand RNA synthesis, and virion assembly. Consequently, we describe three major themes regarding the roles of RNA structure in flavivirus infections: 1) providing a layer of specificity; 2) increasing the functional capacity; and 3) providing a mechanism to support genome compaction. While the interactions described herein are specific to flaviviruses, these themes appear to extend more broadly across RNA viruses.

Long-range RNA structures in the human transcriptome beyond evolutionarily conserved regions

RNA structure has been increasingly recognized as a critical player in the biogenesis and turnover of many transcripts classes. In eukaryotes, the prediction of RNA structure by thermodynamic modeling meets fundamental limitations due to the large sizes and complex, discontinuous organization of eukaryotic genes. Signatures of functional RNA structures can be found by detecting compensatory substitutions in homologous sequences, but a comparative approach is applicable only within conserved sequence blocks. Here, we developed a computational pipeline called PHRIC, which is not limited to conserved regions and relies on RNA contacts derived from RNA in situ conformation sequencing (RIC-seq) experiments. It extracts pairs of short RNA fragments surrounded by nested clusters of RNA contacts and predicts long, nearly perfect complementary base pairings formed between these fragments. In application to a panel of RIC-seq experiments in seven human cell lines, PHRIC predicted ~12,000 stable long-range RNA structures with equilibrium free energy below -15 kcal/mol, the vast majority of which fall outside of regions annotated as conserved among vertebrates. These structures, nevertheless, show some level of sequence conservation and remarkable compensatory substitution patterns in other clades. Furthermore, we found that introns have a higher propensity to form stable long-range RNA structures between each other, and moreover that RNA structures tend to concentrate within the same intron rather than connect adjacent introns. These results for the first time extend the application of proximity ligation assays to RNA structure prediction beyond conserved regions.

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.

tRNA renovatio: Rebirth through fragmentation

tRNA function is based on unique structures that enable mRNA decoding using anticodon trinucleotides. These structures interact with specific aminoacyl-tRNA synthetases and ribosomes using 3D shape and sequence signatures. Beyond translation, tRNAs serve as versatile signaling molecules interacting with other RNAs and proteins. Through evolutionary processes, tRNA fragmentation emerges as not merely random degradation but an act of recreation, generating specific shorter molecules called tRNA-derived small RNAs (tsRNAs). These tsRNAs exploit their linear sequences and newly arranged 3D structures for unexpected biological functions, epitomizing the tRNA "renovatio" (from Latin, meaning renewal, renovation, and rebirth). Emerging methods to uncover full tRNA/tsRNA sequences and modifications, combined with techniques to study RNA structures and to integrate AI-powered predictions, will enable comprehensive investigations of tRNA fragmentation products and new interaction potentials in relation to their biological functions. We anticipate that these directions will herald a new era for understanding biological complexity and advancing pharmaceutical engineering.

Chromatin-mediated silencing on the inactive X chromosome

In mammals, the second X chromosome in females is silenced to enable dosage compensation between XX females and XY males. This essential process involves the formation of a dense chromatin state on the inactive X (Xi) chromosome. There is a wealth of information about the hallmarks of Xi chromatin and the contribution each makes to silencing, leaving the tantalising possibility of learning from this knowledge to potentially remove silencing to treat X-linked diseases in females. Here, we discuss the role of each chromatin feature in the establishment and maintenance of the silent state, which is of crucial relevance for such a goal.

Small but strong: the emerging role of small nucleolar RNA in cardiovascular diseases

Cardiovascular diseases (CVDs) are the leading cause of mortality and disability worldwide. Numerous studies have demonstrated that non-coding RNAs (ncRNAs) play a primary role in CVD development. Therefore, studies on the mechanisms of ncRNAs are essential for further efforts to prevent and treat CVDs. Small nucleolar RNAs (snoRNAs) are a novel species of non-conventional ncRNAs that guide post-transcriptional modifications and the subsequent maturation of small nuclear RNA and ribosomal RNA. Evidently, snoRNAs are extensively expressed in human tissues and may regulate different illnesses. Particularly, as the next-generation sequencing techniques have progressed, snoRNAs have been shown to be differentially expressed in CVDs, suggesting that they may play a role in the occurrence and progression of cardiac illnesses. However, the molecular processes and signaling pathways underlying the function of snoRNAs remain unidentified. Therefore, it is of great value to comprehensively investigate the association between snoRNAs and CVDs. The aim of this review was to collate existing literature on the biogenesis, characteristics, and potential regulatory mechanisms of snoRNAs. In particular, we present a scientific update on these snoRNAs and their relevance to CVDs in an effort to cast new light on the functions of snoRNAs in the clinical diagnosis of CVDs.

IndiSPENsable for X Chromosome Inactivation and Gene Silencing

For about 30 years, SPEN has been the subject of research in many different fields due to its variety of functions and its conservation throughout a wide spectrum of species, like worms, arthropods, and vertebrates. To date, 216 orthologues have been documented. SPEN had been studied for its role in gene regulation in the context of cell signaling, including the NOTCH or nuclear hormone receptor signaling pathways. More recently, SPEN has been identified as a major regulator of initiation of chromosome-wide gene silencing during X chromosome inactivation (XCI) in mammals, where its function remains to be fully understood. Dependent on the biological context, SPEN functions via mechanisms which include different domains. While some domains of SPEN are highly conserved in sequence and secondary structure, species-to-species differences exist that might lead to mechanistic differences. Initiation of XCI appears to be different between humans and mice, which raises additional questions about the extent of generalization of SPEN's function in XCI. In this review, we dissect the mechanism of SPEN in XCI. We discuss its subregions and domains, focusing on its role as a major regulator. We further highlight species-related research, specifically of mouse and human SPEN, with the aim to reveal and clarify potential species-to-species differences in SPEN's function.

G·U base pairing motifs in long non-coding RNAs

Long non-coding RNAs (lncRNAs) are recently-discovered transcripts involved in gene expression regulation and associated with diseases. Despite the unprecedented molecular complexity of these transcripts, recent studies of the secondary and tertiary structure of lncRNAs are starting to reveal the principles of lncRNA structural organization, with important functional implications. It therefore starts to be possible to analyze lncRNA structures systematically. Here, using a set of prototypical and medically-relevant lncRNAs of known secondary structure, we specifically catalogue the distribution and structural environment of one of the first-identified and most frequently occurring non-canonical Watson-Crick interactions, the G·U base pair. We compare the properties of G·U base pairs in our set of lncRNAs to those of the G·U base pairs in other well-characterized transcripts, like rRNAs, tRNAs, ribozymes, and riboswitches. Furthermore, we discuss how G·U base pairs in these targets participate in establishing interactions with proteins or miRNAs, and how they enable lncRNA tertiary folding by forming intramolecular or metal-ion interactions. Finally, by identifying highly-G·U-enriched regions of yet unknown function in our target lncRNAs, we provide a new rationale for future experimental investigation of these motifs, which will help obtain a more comprehensive understanding of lncRNA functions and molecular mechanisms in the future.

Long noncoding RNA study: Genome-wide approaches

Long noncoding RNAs (lncRNAs) have been confirmed to play a crucial role in various biological processes across several species. Though many efforts have been devoted to the expansion of the lncRNAs landscape, much about lncRNAs is still unknown due to their great complexity. The development of high-throughput technologies and the constantly improved bioinformatic methods have resulted in a rapid expansion of lncRNA research and relevant databases. In this review, we introduced genome-wide research of lncRNAs in three parts: (i) novel lncRNA identification by high-throughput sequencing and computational pipelines; (ii) functional characterization of lncRNAs by expression atlas profiling, genome-scale screening, and the research of cancer-related lncRNAs; (iii) mechanism research by large-scale experimental technologies and computational analysis. Besides, primary experimental methods and bioinformatic pipelines related to these three parts are summarized. This review aimed to provide a comprehensive and systemic overview of lncRNA genome-wide research strategies and indicate a genome-wide lncRNA research system.

Formation, function, and pathology of RNP granules

Ribonucleoprotein (RNP) granules are diverse membrane-less organelles that form through multivalent RNA-RNA, RNA-protein, and protein-protein interactions between RNPs. RNP granules are implicated in many aspects of RNA physiology, but in most cases their functions are poorly understood. RNP granules can be described through four key principles. First, RNP granules often arise because of the large size, high localized concentrations, and multivalent interactions of RNPs. Second, cells regulate RNP granule formation by multiple mechanisms including posttranslational modifications, protein chaperones, and RNA chaperones. Third, RNP granules impact cell physiology in multiple manners. Finally, dysregulation of RNP granules contributes to human diseases. Outstanding issues in the field remain, including determining the scale and molecular mechanisms of RNP granule function and how granule dysfunction contributes to human disease.

The plant noncoding transcriptome: a versatile environmental sensor

Plant noncoding RNA transcripts have gained increasing attention in recent years due to growing evidence that they can regulate developmental plasticity. In this review article, we comprehensively analyze the relationship between noncoding RNA transcripts in plants and their response to environmental cues. We first provide an overview of the various noncoding transcript types, including long and small RNAs, and how the environment modulates their performance. We then highlight the importance of noncoding RNA secondary structure for their molecular and biological functions. Finally, we discuss recent studies that have unveiled the functional significance of specific long noncoding transcripts and their molecular partners within ribonucleoprotein complexes during development and in response to biotic and abiotic stress. Overall, this review sheds light on the fascinating and complex relationship between dynamic noncoding transcription and plant environmental responses, and highlights the need for further research to uncover the underlying molecular mechanisms and exploit the potential of noncoding transcripts for crop resilience in the context of global warming.

Cooperation and Competition of RNA Secondary Structure and RNA-Protein Interactions in the Regulation of Alternative Splicing

The regulation of alternative splicing in eukaryotic cells is carried out through the coordinated action of a large number of factors, including RNA-binding proteins and RNA structure. The RNA structure influences alternative splicing by blocking cis-regulatory elements, or bringing them closer or farther apart. In combination with RNA-binding proteins, it generates transcript conformations that help to achieve the necessary splicing outcome. However, the binding of regulatory proteins depends on RNA structure and, vice versa, the formation of RNA structure depends on the interaction with regulators. Therefore, RNA structure and RNA-binding proteins are inseparable components of common regulatory mechanisms. This review highlights examples of alternative splicing regulation by RNA-binding proteins, the regulation through local and long-range RNA structures, as well as how these elements work together, cooperate, and compete.

The International Virus Bioinformatics Meeting 2023

The 2023 International Virus Bioinformatics Meeting was held in Valencia, Spain, from 24-26 May 2023, attracting approximately 180 participants worldwide. The primary objective of the conference was to establish a dynamic scientific environment conducive to discussion, collaboration, and the generation of novel research ideas. As the first in-person event following the SARS-CoV-2 pandemic, the meeting facilitated highly interactive exchanges among attendees. It served as a pivotal gathering for gaining insights into the current status of virus bioinformatics research and engaging with leading researchers and emerging scientists. The event comprised eight invited talks, 19 contributed talks, and 74 poster presentations across eleven sessions spanning three days. Topics covered included machine learning, bacteriophages, virus discovery, virus classification, virus visualization, viral infection, viromics, molecular epidemiology, phylodynamic analysis, RNA viruses, viral sequence analysis, viral surveillance, and metagenomics. This report provides rewritten abstracts of the presentations, a summary of the key research findings, and highlights shared during the meeting.

Alu transposable elements rewire enhancer-promoter network through RNA pairing

A recent study by Liang et al.1 reveals that interacting enhancer RNAs (eRNAs) and promoter-transcribed upstream antisense RNAs (uaRNAs) can identify enhancer-promoter interactions. Complementary sequences within the interacting eRNAs and uaRNAs, predominantly Alu sequences, confer the specificity for eRNA-uaRNA pairing and hence enhancer-promoter recognition.

Genome-wide probing of eukaryotic nascent RNA structure elucidates cotranscriptional folding and its antimutagenic effect

The transcriptional intermediates of RNAs fold into secondary structures with multiple regulatory roles, yet the details of such cotranscriptional RNA folding are largely unresolved in eukaryotes. Here, we present eSPET-seq (Structural Probing of Elongating Transcripts in eukaryotes), a method to assess the cotranscriptional RNA folding in Saccharomyces cerevisiae. Our study reveals pervasive structural transitions during cotranscriptional folding and overall structural similarities between nascent and mature RNAs. Furthermore, a combined analysis with genome-wide R-loop and mutation rate approximations provides quantitative evidence for the antimutator effect of nascent RNA folding through competitive inhibition of the R-loops, known to facilitate transcription-associated mutagenesis. Taken together, we present an experimental evaluation of cotranscriptional folding in eukaryotes and demonstrate the antimutator effect of nascent RNA folding. These results suggest genome-wide coupling between the processing and transmission of genetic information through RNA folding.

RNA in situ conformation sequencing reveals novel long-range RNA structures with impact on splicing

Over recent years, long-range RNA structure has emerged as a factor that is fundamental to alternative splicing regulation. An increasing number of human disorders are now being associated with splicing defects; hence it is essential to develop methods that assess long-range RNA structure experimentally. RNA in situ conformation sequencing (RIC-seq) is a method that recapitulates RNA structure within physiological RNA-protein complexes. In this work, we juxtapose pairs of conserved complementary regions (PCCRs) that were predicted in silico with the results of RIC-seq experiments conducted in seven human cell lines. We show statistically that RIC-seq support of PCCRs correlates with their properties, such as equilibrium free energy, presence of compensatory substitutions, and occurrence of A-to-I RNA editing sites and forked eCLIP peaks. Exons enclosed in PCCRs that are supported by RIC-seq tend to have weaker splice sites and lower inclusion rates, which is indicative of post-transcriptional splicing regulation mediated by RNA structure. Based on these findings, we prioritize PCCRs according to their RIC-seq support and show, using antisense nucleotides and minigene mutagenesis, that PCCRs in two disease-associated human genes, PHF20L1 and CASK, and also PCCRs in their murine orthologs, impact alternative splicing. In sum, we demonstrate how RIC-seq experiments can be used to discover functional long-range RNA structures, and particularly those that regulate alternative splicing.

The RNA interactome in the Hallmarks of Cancer

Ribonucleic acid (RNA) molecules are indispensable for cellular homeostasis in healthy and malignant cells. However, the functions of RNA extend well beyond that of a protein-coding template. Rather, both coding and non-coding RNA molecules function through critical interactions with a plethora of cellular molecules, including other RNAs, DNA, and proteins. Deconvoluting this RNA interactome, including the interacting partners, the nature of the interaction, and dynamic changes of these interactions in malignancies has yielded fundamental advances in knowledge and are emerging as a novel therapeutic strategy in cancer. Here, we present an RNA-centric review of recent advances in the field of RNA-RNA, RNA-protein, and RNA-DNA interactomic network analysis and their impact across the Hallmarks of Cancer. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Interactions with Proteins and Other Molecules > RNA-Protein Complexes.

RNA structure determination: From 2D to 3D

RNA molecules serve a wide range of functions that are closely linked to their structures. The basic structural units of RNA consist of single- and double-stranded regions. In order to carry out advanced functions such as catalysis and ligand binding, certain types of RNAs can adopt higher-order structures. The analysis of RNA structures has progressed alongside advancements in structural biology techniques, but it comes with its own set of challenges and corresponding solutions. In this review, we will discuss recent advances in RNA structure analysis techniques, including structural probing methods, X-ray crystallography, nuclear magnetic resonance, cryo-electron microscopy, and small-angle X-ray scattering. Often, a combination of multiple techniques is employed for the integrated analysis of RNA structures. We also survey important RNA structures that have been recently determined using various techniques.

RNA-RNA competitive interactions: a molecular civil war ruling cell physiology and diseases

The idea that proteins are the main determining factors in the functioning of cells and organisms, and their dysfunctions are the first cause of pathologies, has been predominant in biology and biomedicine until recently. This protein-centered view was too simplistic and failed to explain the physiological and pathological complexity of the cell. About 80% of the human genome is dynamically and pervasively transcribed, mostly as non-protein-coding RNAs (ncRNAs), which competitively interact with each other and with coding RNAs generating a complex RNA network regulating RNA processing, stability, and translation and, accordingly, fine-tuning the gene expression of the cells. Qualitative and quantitative dysregulations of RNA-RNA interaction networks are strongly involved in the onset and progression of many pathologies, including cancers and degenerative diseases. This review will summarize the RNA species involved in the competitive endogenous RNA network, their mechanisms of action, and involvement in pathological phenotypes. Moreover, it will give an overview of the most advanced experimental and computational methods to dissect and rebuild RNA networks.

Landscape of semi-extractable RNAs across five human cell lines

Phase-separated membraneless organelles often contain RNAs that exhibit unusual semi-extractability using the conventional RNA extraction method, and can be efficiently retrieved by needle shearing or heating during RNA extraction. Semi-extractable RNAs are promising resources for understanding RNA-centric phase separation. However, limited assessments have been performed to systematically identify and characterize semi-extractable RNAs. In this study, 1074 semi-extractable RNAs, including ASAP1, DANT2, EXT1, FTX, IGF1R, LIMS1, NEAT1, PHF21A, PVT1, SCMH1, STRG.3024.1, TBL1X, TCF7L2, TVP23C-CDRT4, UBE2E2, ZCCHC7, ZFAND3 and ZSWIM6, which exhibited consistent semi-extractability were identified across five human cell lines. By integrating publicly available datasets, we found that semi-extractable RNAs tend to be distributed in the nuclear compartments but are dissociated from the chromatin. Long and repeat-containing semi-extractable RNAs act as hubs to provide global RNA-RNA interactions. Semi-extractable RNAs were divided into four groups based on their k-mer content. The NEAT1 group preferred to interact with paraspeckle proteins, such as FUS and NONO, implying that RNAs in this group are potential candidates of architectural RNAs that constitute nuclear bodies.

RNA Structural Dynamics Modulate EGFR-TKI Resistance Through Controlling YRDC Translation in NSCLC Cells

Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) positively affect the initial control of non-small cell lung cancer (NSCLC). Rapidly acquired resistance to EGFR-TKIs is a major hurdle in successful treatment. However, the mechanisms that control the resistance of EGFR-TKIs remain largely unknown. RNA structures have widespread and crucial functions in many biological regulations; however, the functions of RNA structures in regulating cancer drug resistance remain unclear. Here, the psoralen analysis of RNA interactions and structures (PARIS) method is used to establish the higher-order RNA structure maps of EGFR-TKIs-resistant and -sensitive cells of NSCLC. Our results show that RNA structural regions are enriched in untranslated regions (UTRs) and correlate with translation efficiency (TE). Moreover, yrdC N6-threonylcarbamoyltransferase domain containing (YRDC) promotes resistance to EGFR-TKIs. RNA structure formation in YRDC 3' UTR suppresses embryonic lethal abnormal vision-like 1 (ELAVL1) binding, leading to EGFR-TKI sensitivity by impairing YRDC translation. A potential therapeutic strategy for cancer treatment is provided using antisense oligonucleotide (ASO) to perturb the interaction between RNA and protein. Our study reveals an unprecedented mechanism through which the RNA structure switch modulates EGFR-TKI resistance by controlling YRDC mRNA translation in an ELAVL1-dependent manner.

Machine learning modeling of RNA structures: methods, challenges and future perspectives

The three-dimensional structure of RNA molecules plays a critical role in a wide range of cellular processes encompassing functions from riboswitches to epigenetic regulation. These RNA structures are incredibly dynamic and can indeed be described aptly as an ensemble of structures that shifts in distribution depending on different cellular conditions. Thus, the computational prediction of RNA structure poses a unique challenge, even as computational protein folding has seen great advances. In this review, we focus on a variety of machine learning-based methods that have been developed to predict RNA molecules' secondary structure, as well as more complex tertiary structures. We survey commonly used modeling strategies, and how many are inspired by or incorporate thermodynamic principles. We discuss the shortcomings that various design decisions entail and propose future directions that could build off these methods to yield more robust, accurate RNA structure predictions.

Complementary Alu sequences mediate enhancer-promoter selectivity

Enhancers determine spatiotemporal gene expression programs by engaging with long-range promoters^1-4. However, it remains unknown how enhancers find their cognate promoters. We recently developed a RNA in situ conformation sequencing technology to identify enhancer-promoter connectivity using pairwise interacting enhancer RNAs and promoter-derived noncoding RNAs^5,6. Here we apply this technology to generate high-confidence enhancer-promoter RNA interaction maps in six additional cell lines. Using these maps, we discover that 37.9% of the enhancer-promoter RNA interaction sites are overlapped with Alu sequences. These pairwise interacting Alu and non-Alu RNA sequences tend to be complementary and potentially form duplexes. Knockout of Alu elements compromises enhancer-promoter looping, whereas Alu insertion or CRISPR-dCasRx-mediated Alu tethering to unregulated promoter RNAs can create new loops to homologous enhancers. Mapping 535,404 noncoding risk variants back to the enhancer-promoter RNA interaction maps enabled us to construct variant-to-function maps for interpreting their molecular functions, including 15,318 deletions or insertions in 11,677 Alu elements that affect 6,497 protein-coding genes. We further demonstrate that polymorphic Alu insertion at the PTK2 enhancer can promote tumorigenesis. Our study uncovers a principle for determining enhancer-promoter pairing specificity and provides a framework to link noncoding risk variants to their molecular functions.

Intronic small nucleolar RNAs regulate host gene splicing through base pairing with their adjacent intronic sequences

BACKGROUND

Small nucleolar RNAs (snoRNAs) are abundant noncoding RNAs best known for their involvement in ribosomal RNA maturation. In mammals, most expressed snoRNAs are embedded in introns of longer genes and produced through transcription and splicing of their host. Intronic snoRNAs were long viewed as inert passengers with little effect on host expression. However, a recent study reported a snoRNA influencing the splicing and ultimate output of its host gene. Overall, the general contribution of intronic snoRNAs to host expression remains unclear.

RESULTS

Computational analysis of large-scale human RNA-RNA interaction datasets indicates that 30% of detected snoRNAs interact with their host transcripts. Many snoRNA-host duplexes are located near alternatively spliced exons and display high sequence conservation suggesting a possible role in splicing regulation. The study of the model SNORD2-EIF4A2 duplex indicates that the snoRNA interaction with the host intronic sequence conceals the branch point leading to decreased inclusion of the adjacent alternative exon. Extended SNORD2 sequence containing the interacting intronic region accumulates in sequencing datasets in a cell-type-specific manner. Antisense oligonucleotides and mutations that disrupt the formation of the snoRNA-intron structure promote the splicing of the alternative exon, shifting the EIF4A2 transcript ratio away from nonsense-mediated decay.

CONCLUSIONS

Many snoRNAs form RNA duplexes near alternative exons of their host transcripts, placing them in optimal positions to control host output as shown for the SNORD2-EIF4A2 model system. Overall, our study supports a more widespread role for intronic snoRNAs in the regulation of their host transcript maturation.

A comprehensive evaluation of full-spectrum cell-free RNAs highlights cell-free RNA fragments for early-stage hepatocellular carcinoma detection

BACKGROUND

Various studies have reported cell-free RNAs (cfRNAs) as noninvasive biomarkers for detecting hepatocellular carcinoma (HCC). However, they have not been independently validated, and some results are contradictory. We provided a comprehensive evaluation of various types of cfRNA biomarkers and a full mining of the biomarker potential of new features of cfRNA.

METHODS

We first systematically reviewed reported cfRNA biomarkers and calculated dysregulated post-transcriptional events and cfRNA fragments. In 3 independent multicentre cohorts, we further selected 6 cfRNAs using RT-qPCR, built a panel called HCCMDP with AFP using machine learning, and internally and externally validated HCCMDP's performance.

FINDINGS

We identified 23 cfRNA biomarker candidates from a systematic review and analysis of 5 cfRNA-seq datasets. Notably, we defined the cfRNA domain to describe cfRNA fragments systematically. In the verification cohort (n = 183), cfRNA fragments were more likely to be verified, while circRNA and chimeric RNA candidates were neither abundant nor stable as qPCR-based biomarkers. In the algorithm development cohort (n = 287), we build and test the panel HCCMDP with 6 cfRNA markers and AFP. In the independent validation cohort (n = 171), HCCMDP can distinguish HCC patients from control groups (all: AUC = 0.925; CHB: AUC = 0.909; LC: AUC = 0.916), and performs well in distinguishing early-stage HCC patients (all: AUC = 0.936; CHB: AUC = 0.917; LC: AUC = 0.928).

INTERPRETATION

This study comprehensively evaluated full-spectrum cfRNA biomarker types for HCC detection, highlighted the cfRNA fragment as a promising biomarker type in HCC detection, and provided a panel HCCMDP.

FUNDING

National Natural Science Foundation of China, and The National Key Basic Research Program (973 program).

Systematic detection of tertiary structural modules in large RNAs and RNP interfaces by Tb-seq

Compact RNA structural motifs control many aspects of gene expression, but we lack methods for finding these structures in the vast expanse of multi-kilobase RNAs. To adopt specific 3-D shapes, many RNA modules must compress their RNA backbones together, bringing negatively charged phosphates into close proximity. This is often accomplished by recruiting multivalent cations (usually Mg2+), which stabilize these sites and neutralize regions of local negative charge. Coordinated lanthanide ions, such as terbium (III) (Tb3+), can also be recruited to these sites, where they induce efficient RNA cleavage, thereby revealing compact RNA 3-D modules. Until now, Tb3+ cleavage sites were monitored via low-throughput biochemical methods only applicable to small RNAs. Here we present Tb-seq, a high-throughput sequencing method for detecting compact tertiary structures in large RNAs. Tb-seq detects sharp backbone turns found in RNA tertiary structures and RNP interfaces, providing a way to scan transcriptomes for stable structural modules and potential riboregulatory motifs.