Cross-linking, ligation, and sequencing of hybrids reveals RNA-RNA interactions in yeast. Proc Natl Acad Sci U S A. 2011;108:10010-10015. [PMID: 21610164 DOI: 10.1073/pnas.1017386108]

Technological advancements in deciphering RNA-RNA interactions

RNA-RNA interactions (RRIs) can dictate RNA molecules to form intricate higher-order structures and bind their RNA substrates in diverse biological processes. To elucidate the function, binding specificity, and regulatory mechanisms of various RNA molecules, especially the vast repertoire of non-coding RNAs, advanced technologies and methods that globally map RRIs are extremely valuable. In the past decades, many state-of-the-art technologies have been developed for this purpose. This review focuses on those high-throughput technologies for the global mapping of RRIs. We summarize the key concepts and the pros and cons of different technologies. In addition, we highlight the novel biological insights uncovered by these RRI mapping methods and discuss the future challenges for appreciating the crucial roles of RRIs in gene regulation across bacteria, viruses, archaea, and mammals.

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.

Mapping snoRNA-target RNA interactions in an RNA binding protein-dependent manner with chimeric eCLIP

Small nucleolar RNAs (snoRNAs) are non-coding RNAs that function in ribosome and spliceosome biogenesis, primarily by guiding modifying enzymes to specific sites on ribosomal RNA (rRNA) and spliceosomal RNA (snRNA). However, many orphan snoRNAs remain uncharacterized, with unidentified or unvalidated targets, and studies on additional snoRNA-associated proteins are limited. We adapted an enhanced chimeric eCLIP approach to comprehensively profile snoRNA-target RNA interactions using both core and accessory snoRNA binding proteins as baits. Using core snoRNA binding proteins, we confirmed most annotated snoRNA-rRNA and snoRNA-snRNA interactions in mouse and human cell lines and called novel, high-confidence interactions for orphan snoRNAs. While some of these interactions result in chemical modification, others may have modification-independent functions. We then showed that snoRNA ribonucleoprotein complexes containing certain accessory proteins, like WDR43 and NOLC1, enriched for specific subsets of snoRNA-target RNA interactions with distinct roles in ribosome and spliceosome biogenesis. Notably, we discovered that SNORD89 guides 2'-O-methylation at two neighboring sites in U2 snRNA that are important for activating splicing, but also appear to ensure imperfect splicing for a subset of near-constitutive exons. Thus, chimeric eCLIP of snoRNA-associating proteins enables a comprehensive framework for studying snoRNA-target interactions in an RNA binding protein-dependent manner, revealing novel interactions and regulatory roles in RNA biogenesis.

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.

Decoding protein-RNA interactions using CLIP-based methodologies

Protein-RNA interactions are central to all RNA processing events, with pivotal roles in the regulation of gene expression and cellular functions. Dysregulation of these interactions has been increasingly linked to the pathogenesis of human diseases. High-throughput approaches to identify RNA-binding proteins and their binding sites on RNA - in particular, ultraviolet crosslinking followed by immunoprecipitation (CLIP) - have helped to map the RNA interactome, yielding transcriptome-wide protein-RNA atlases that have contributed to key mechanistic insights into gene expression and gene-regulatory networks. Here, we review these recent advances, explore the effects of cellular context on RNA binding, and discuss how these insights are shaping our understanding of cellular biology. We also review the potential therapeutic applications arising from new knowledge of protein-RNA interactions.

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.

Untacking small RNA profiling and RNA fragment footprinting: Approaches and challenges in library construction

Small RNAs (sRNAs) with sizes ranging from 15 to 50 nucleotides (nt) are critical regulators of gene expression control. Prior studies have shown that sRNAs are involved in a broad range of biological processes, such as organ development, tumorigenesis, and epigenomic regulation; however, emerging evidence unveils a hidden layer of diversity and complexity of endogenously encoded sRNAs profile in eukaryotic organisms, including novel types of sRNAs and the previously unknown post-transcriptional RNA modifications. This underscores the importance for accurate, unbiased detection of sRNAs in various cellular contexts. A multitude of high-throughput methods based on next-generation sequencing (NGS) are developed to decipher the sRNA expression and their modifications. Nonetheless, distinct from mRNA sequencing, the data from sRNA sequencing suffer frequent inconsistencies and high variations emanating from the adapter contaminations and RNA modifications, which overall skew the sRNA libraries. Here, we summarize the sRNA-sequencing approaches, and discuss the considerations and challenges for the strategies and methods of sRNA library construction. The pros and cons of sRNA sequencing have significant implications for implementing RNA fragment footprinting approaches, including CLIP-seq and Ribo-seq. We envision that this review can inspire novel improvements in small RNA sequencing and RNA fragment footprinting in future. This article is categorized under: RNA Evolution and Genomics > Computational Analyses of RNA RNA Processing > Processing of Small RNAs Regulatory RNAs/RNAi/Riboswitches > Biogenesis of Effector Small RNAs.

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.

Genome-wide annotation of transcript boundaries using bacterial Rend-seq datasets

Accurate annotation to single-nucleotide resolution of the transcribed regions in genomes is key to optimally analyse RNA-seq data, understand regulatory events and for the design of experiments. However, currently most genome annotations provided by GenBank generally lack information about untranslated regions. Additionally, information regarding genomic locations of non-coding RNAs, such as sRNAs, or anti-sense RNAs is frequently missing. To provide such information, diverse RNA-seq technologies, such as Rend-seq, have been developed and applied to many bacterial species. However, incorporating this vast amount of information into annotation files has been limited and is bioinformatically challenging, resulting in UTRs and other non-coding elements being overlooked or misrepresented. To overcome this problem, we present pyRAP (python Rend-seq Annotation Pipeline), a software package that analyses Rend-seq datasets to accurately resolve transcript boundaries genome-wide. We report the use of pyRAP to find novel transcripts, transcript isoforms, and RNase-dependent sRNA processing events. In Bacillus subtilis we uncovered 63 novel transcripts and provide genomic coordinates with single-nucleotide resolution for 2218 5'UTRs, 1864 3'UTRs and 161 non-coding RNAs. In Escherichia coli, we report 117 novel transcripts, 2429 5'UTRs, 1619 3'UTRs and 91 non-coding RNAs, and in Staphylococcus aureus, 16 novel transcripts, 664 5'UTRs, 696 3'UTRs, and 81 non-coding RNAs. Finally, we use pyRAP to produce updated annotation files for B. subtilis 168, E. coli K-12 MG1655, and S. aureus 8325 for use in the wider microbial genomics research community.

The miRNA-target interactions: An underestimated intricacy

MicroRNAs (miRNAs) play indispensable roles in posttranscriptional gene regulation. Their cellular regulatory impact is determined not solely by their sheer number, which likely amounts to >2000 individual miRNAs in human, than by the regulatory effectiveness of single miRNAs. Although, one begins to develop an understanding of the complex mechanisms underlying miRNA-target interactions (MTIs), the overall knowledge of MTI functionality is still rather patchy. In this critical review, we summarize key features of mammalian MTIs. We especially highlight latest insights on (i) the dynamic make-up of miRNA binding sites including non-canonical binding sites, (ii) the cooperativity between miRNA binding sites, (iii) the adaptivity of MTIs through sequence modifications, (iv) the bearing of intra-cellular miRNA localization changes and (v) the role of cell type and cell status specific miRNA interaction partners. The MTI biology is discussed against the background of state-of-the-art approaches with particular emphasis on experimental strategies for evaluating miRNA functionality.

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.

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.

The Mechanisms of miRNAs on Target Regulation and their Recent Advances in Atherosclerosis

miRNAs are crucial regulators in a variety of physiological and pathological processes, while their regulation mechanisms were usually described as negatively regulating gene expression by targeting the 3'-untranslated region(3'-UTR) of target gene miRNAs through seed sequence in tremendous studies. However, recent evidence indicated the existence of non-canonical mechanisms mediated by binding other molecules besides mRNAs. Additionally, accumulating evidence showed that functions of intracellular and intercellular miRNAs exhibited spatiotemporal patterns. Considering that detailed knowledge of the miRNA regulating mechanism is essential for understanding the roles and further clinical applications associated with their dysfunction and dysregulation, which is complicated and not fully clarified. Based on that, we summarized the recently reported regulation mechanisms of miRNAs, including recognitions, patterns of actions, and chemical modifications. And we also highlight the novel findings of miRNAs in atherosclerosis progression researches to provide new insights for non-coding RNA-based therapy in intractable diseases.

Analysis of chimeric reads characterises the diverse targetome of AGO2-mediated regulation

Argonaute proteins are instrumental in regulating RNA stability and translation. AGO2, the major mammalian Argonaute protein, is known to primarily associate with microRNAs, a family of small RNA 'guide' sequences, and identifies its targets primarily via a 'seed' mediated partial complementarity process. Despite numerous studies, a definitive experimental dataset of AGO2 'guide'-'target' interactions remains elusive. Our study employs two experimental methods-AGO2 CLASH and AGO2 eCLIP, to generate thousands of AGO2 target sites verified by chimeric reads. These chimeric reads contain both the AGO2 loaded small RNA 'guide' and the target sequence, providing a robust resource for modeling AGO2 binding preferences. Our novel analysis pipeline reveals thousands of AGO2 target sites driven by microRNAs and a significant number of AGO2 'guides' derived from fragments of other small RNAs such as tRNAs, YRNAs, snoRNAs, rRNAs, and more. We utilize convolutional neural networks to train machine learning models that accurately predict the binding potential for each 'guide' class and experimentally validate several interactions. In conclusion, our comprehensive analysis of the AGO2 targetome broadens our understanding of its 'guide' repertoire and potential function in development and disease. Moreover, we offer practical bioinformatic tools for future experiments and the prediction of AGO2 targets. All data and code from this study are freely available at https://github.com/ML-Bioinfo-CEITEC/HybriDetector/ .

Hybkit: a Python API and command-line toolkit for hybrid sequence data from chimeric RNA methods

SUMMARY

Experimental methods using microRNA/target ligation have recently provided significant insights into microRNA functioning through generation of chimeric (hybrid) RNA sequences. Here, we introduce Hybkit, a Python3 API, and command-line toolkit for analysis of hybrid sequence data in the "hyb" file format to enable customizable evaluation and annotation of hybrid characteristics. The Hybkit API includes a suite of python objects for developing custom analyses of hybrid data as well as miRNA-specific analysis methods, built-in plotting of analysis results, and incorporation of predicted miRNA/target interactions in Vienna format.

AVAILABILITY AND IMPLEMENTATION

Hybkit is provided free and open source under the GNU GPL license at github.com/RenneLab/hybkit and archived on Zenodo (doi.org/10.5281/zenodo.7834299). Hybkit distributions are also provided via PyPI (pypi.org/project/hybkit), Conda (bioconda.github.io/recipes/hybkit/README.html), and Docker (quay.io/repository/biocontainers/hybkit).

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.

RNA-Guided RNA Modifications: Biogenesis, Functions, and Applications

Post-transcriptional modifications are ubiquitous in both protein-coding and noncoding RNAs (ncRNAs), playing crucial functional roles in diverse biological processes across all kingdoms of life. These RNA modifications can be achieved through two distinct mechanisms: RNA-independent and RNA-guided (also known as RNA-dependent). In the RNA-independent mechanism, modifications are directly introduced onto RNA molecules by enzymes without the involvement of other RNA molecules, while the cellular RNA-guided RNA modification system exists in the form of RNA-protein complexes, wherein one guide RNA collaborates with a set of proteins, including the modifying enzyme. The primary function of guide RNAs lies in their ability to bind to complementary regions within the target RNAs, orchestrating the installation of specific modifications. Both mechanisms offer unique advantages and are critical to the diverse and dynamic landscape of RNA modifications. RNA-independent modifications provide rapid and direct modification of RNA molecules, while RNA-guided mechanisms offer precise and programmable means to introduce modifications at specific RNA sites. Recently, emerging evidence has shed light on RNA-guided RNA modifications as a captivating area of research, providing precise and programmable control over RNA sequences and functions.In this Account, we focus on RNA modifications synthesized in an RNA-guided manner, including 2'-O-methylated nucleotides (Nm), pseudouridine (Ψ), N4-acetylcytidine (ac4C), and inosine (I). This Account sheds light on the intricate processes of biogenesis and elucidates the regulatory roles of these modifications in RNA metabolism. These roles include pivotal functions such as RNA stability, translation, and splicing, where each modification contributes to the diverse and finely tuned regulatory landscape of RNA biology. In addition to elucidating the biogenesis and functions of these modifications, we also provide an overview of high-throughput methods and their underlying biochemical principles used for the transcriptome-wide investigation of these modifications and their fundamental interactions in RNA-guided systems. This includes exploring RNA-protein interactions and RNA-RNA interactions, which play crucial roles in the dynamic regulatory networks of RNA-guided modifications. The ever-advancing methodologies have greatly enhanced our understanding of the dynamic and widespread nature of RNA-guided RNA modifications and their regulatory functions. Furthermore, the applications of RNA-guided RNA modifications are discussed, illuminating their potential in diverse fields. From basic research to gene therapy, the programmable nature of RNA-guided modifications presents exciting opportunities for manipulating gene expression and developing innovative therapeutic strategies.

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.

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.

A snoRNA-tRNA modification network governs codon-biased cellular states

The dynamic balance between tRNA supply and codon usage demand is a fundamental principle in the cellular translation economy. However, the regulation and functional consequences of this balance remain unclear. Here, we use PARIS2 interactome capture, structure modeling, conservation analysis, RNA-protein interaction analysis, and modification mapping to reveal the targets of hundreds of snoRNAs, many of which were previously considered orphans. We identify a snoRNA-tRNA interaction network that is required for global tRNA modifications, including 2'-O-methylation and others. Loss of Fibrillarin, the snoRNA-guided 2'-O-methyltransferase, induces global upregulation of tRNA fragments, a large group of regulatory RNAs. In particular, the snoRNAs D97/D133 guide the 2'-O-methylation of multiple tRNAs, especially for the amino acid methionine (Met), a protein-intrinsic antioxidant. Loss of D97/D133 snoRNAs in human HEK293 cells reduced target tRNA levels and induced codon adaptation of the transcriptome and translatome. Both single and double knockouts of D97 and D133 in HEK293 cells suppress Met-enriched proliferation-related gene expression programs, including, translation, splicing, and mitochondrial energy metabolism, and promote Met-depleted programs related to development, differentiation, and morphogenesis. In a mouse embryonic stem cell model of development, knockdown and knockout of D97/D133 promote differentiation to mesoderm and endoderm fates, such as cardiomyocytes, without compromising pluripotency, consistent with the enhanced development-related gene expression programs in human cells. This work solves a decades-old mystery about orphan snoRNAs and reveals a function of snoRNAs in controlling the codon-biased dichotomous cellular states of proliferation and development.

lhCLIP reveals the in vivo RNA-RNA interactions recognized by hnRNPK

RNA-RNA interactions play a crucial role in regulating gene expression and various biological processes, but identifying these interactions on a transcriptomic scale remains a challenge. To address this, we have developed a new biochemical technique called pCp-biotin labelled RNA hybrid and ultraviolet crosslinking and immunoprecipitation (lhCLIP) that enables the transcriptome-wide identification of intra- and intermolecular RNA-RNA interactions mediated by a specific RNA-binding protein (RBP). Using lhCLIP, we have uncovered a diverse landscape of intermolecular RNA interactions recognized by hnRNPK in human cells, involving all major classes of noncoding RNAs (ncRNAs) and mRNA. Notably, hnRNPK selectively binds with snRNA U4, U11, and U12, and shapes the secondary structure of these snRNAs, which may impact RNA splicing. Our study demonstrates the potential of lhCLIP as a user-friendly and widely applicable method for discovering RNA-RNA interactions mediated by a particular protein of interest and provides a valuable tool for further investigating the role of RBPs in gene expression and biological processes.

Advantages and limitations of UV cross-linking analysis of protein-RNA interactomes in microbes

RNA-binding proteins (RBPs) govern the lifespan of nearly all transcripts and play key roles in adaptive responses in microbes. A robust approach to examine protein-RNA interactions involves irradiating cells with UV light to form covalent adducts between RBPs and their cognate RNAs. Combined with RNA or protein purification, these procedures can provide global RBP censuses or transcriptomic maps for all target sequences of a single protein in living cells. The recent development of novel methods has quickly populated the RBP landscape in microorganisms. Here, we provide an overview of prominent UV cross-linking techniques which have been applied to investigate RNA interactomes in microbes. By assessing their advantages and caveats, this technical evaluation intends to guide the selection of appropriate methods and experimental design as well as to encourage the use of complementary UV-dependent techniques to inspect RNA-binding activity.

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-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.

Insights in piRNA targeting rules

PIWI-interacting RNAs (piRNAs) play an important role in the defense against transposons in the germline and stem cells of animals. To what extent other transcripts are also regulated by piRNAs is an ongoing topic of debate. The amount of sequence complementarity between piRNA and target that is required for effective downregulation of the targeted transcript is guiding in this discussion. Over the years, various methods have been applied to infer targeting requirements from the collections of piRNAs and potential target transcripts, and recent structural studies of the PIWI proteins have provided an additional perspective. In this review, I summarize the findings from these studies and propose a set of requirements that can be used to predict targets to the best of our current abilities. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications RNA-Based Catalysis > RNA-Mediated Cleavage.

Molecular functions of RNA helicases during ribosomal subunit assembly

During their biogenesis, the ribosomal subunits undergo numerous structural and compositional changes to achieve their final architecture. RNA helicases are a key driving force of such remodelling events but deciphering their particular functions has long been challenging due to lack of knowledge of their molecular functions and RNA substrates. Advances in the biochemical characterisation of RNA helicase activities together with new insights into RNA helicase binding sites on pre-ribosomes and structural snapshots of pre-ribosomal complexes containing RNA helicases now open the door to a deeper understanding of precisely how different RNA helicases contribute to ribosomal subunit maturation.

Quality control ensures fidelity in ribosome assembly and cellular health

The coordinated integration of ribosomal RNA and protein into two functional ribosomal subunits is safeguarded by quality control checkpoints that ensure ribosomes are correctly assembled and functional before they engage in translation. Quality control is critical in maintaining the integrity of ribosomes and necessary to support healthy cell growth and prevent diseases associated with mistakes in ribosome assembly. Its importance is demonstrated by the finding that bypassing quality control leads to misassembled, malfunctioning ribosomes with altered translation fidelity, which change gene expression and disrupt protein homeostasis. In this review, we outline our understanding of quality control within ribosome synthesis and how failure to enforce quality control contributes to human disease. We first provide a definition of quality control to guide our investigation, briefly present the main assembly steps, and then examine stages of assembly that test ribosome function, establish a pass-fail system to evaluate these functions, and contribute to altered ribosome performance when bypassed, and are thus considered "quality control."

Capture RIC-seq reveals positional rules of PTBP1-associated RNA loops in splicing regulation

RNA-binding proteins (RBPs) bind at different positions of the pre-mRNA molecules to promote or reduce the usage of a particular exon. Seeking to understand the working principle of these positional effects, we develop a capture RIC-seq (CRIC-seq) method to enrich specific RBP-associated in situ proximal RNA-RNA fragments for deep sequencing. We determine hnRNPA1-, SRSF1-, and PTBP1-associated proximal RNA-RNA contacts and regulatory mechanisms in HeLa cells. Unexpectedly, the 3D RNA map analysis shows that PTBP1-associated loops in individual introns preferentially promote cassette exon splicing by accelerating asymmetric intron removal, whereas the loops spanning across cassette exon primarily repress splicing. These "positional rules" can faithfully predict PTBP1-regulated splicing outcomes. We further demonstrate that cancer-related splicing quantitative trait loci can disrupt RNA loops by reducing PTBP1 binding on pre-mRNAs to cause aberrant splicing in tumors. Our study presents a powerful method for exploring the functions of RBP-associated RNA-RNA proximal contacts in gene regulation and disease.

Chemical crosslinking and ligation methods for in vivo analysis of RNA structures and interactions

RNA structures and interactions in living cells drive a variety of biological processes and play critical roles in physiology and disease states. However, studies of RNA structures and interactions have been challenging due to limitations in available technologies. Direct determination of structures in vitro has been only possible to a small number of RNAs with limited sizes and conformations. We recently introduced two chemical crosslink-ligation techniques that enabled studies of transcriptome-wide secondary and tertiary structures and their dynamics. In a dramatically improved version of the psoralen analysis of RNA interactions and structures (PARIS2) method, we detailed the synthesis and use of amotosalen, a highly soluble psoralen analogue, and enhanced enzymology for higher efficiency duplex capture. We also introduced spatial 2'-hydroxyl acylation reversible crosslinking (SHARC) with exonuclease (exo) trimming, a method which utilizes a novel crosslinker class that targets the 2'-OH to capture three-dimensional (3D) structures. Both are powerful orthogonal approaches for solving in vivo RNA structure and interactions, integrating crosslinking, exo trimming, proximity ligation, and high throughput sequencing. In this chapter, we present a detailed protocol for the methods and highlight steps that outperform existing crosslink-ligation approaches.

Chemical RNA Cross-Linking: Mechanisms, Computational Analysis, and Biological Applications

In recent years, RNA has emerged as a multifaceted biomolecule that is involved in virtually every function of the cell and is critical for human health. This has led to a substantial increase in research efforts to uncover the many chemical and biological aspects of RNA and target RNA for therapeutic purposes. In particular, analysis of RNA structures and interactions in cells has been critical for understanding their diverse functions and druggability. In the last 5 years, several chemical methods have been developed to achieve this goal, using chemical cross-linking combined with high-throughput sequencing and computational analysis. Applications of these methods resulted in important new insights into RNA functions in a variety of biological contexts. Given the rapid development of new chemical technologies, a thorough perspective on the past and future of this field is provided. In particular, the various RNA cross-linkers and their mechanisms, the computational analysis and challenges, and illustrative examples from recent literature are discussed.

Non-coding RNAs in human health and disease: potential function as biomarkers and therapeutic targets

Human diseases have been a critical threat from the beginning of human history. Knowing the origin, course of action and treatment of any disease state is essential. A microscopic approach to the molecular field is a more coherent and accurate way to explore the mechanism, progression, and therapy with the introduction and evolution of technology than a macroscopic approach. Non-coding RNAs (ncRNAs) play increasingly important roles in detecting, developing, and treating all abnormalities related to physiology, pathology, genetics, epigenetics, cancer, and developmental diseases. Noncoding RNAs are becoming increasingly crucial as powerful, multipurpose regulators of all biological processes. Parallel to this, a rising amount of scientific information has revealed links between abnormal noncoding RNA expression and human disorders. Numerous non-coding transcripts with unknown functions have been found in addition to advancements in RNA-sequencing methods. Non-coding linear RNAs come in a variety of forms, including circular RNAs with a continuous closed loop (circRNA), long non-coding RNAs (lncRNA), and microRNAs (miRNA). This comprises specific information on their biogenesis, mode of action, physiological function, and significance concerning disease (such as cancer or cardiovascular diseases and others). This study review focuses on non-coding RNA as specific biomarkers and novel therapeutic targets.

Non-coding RNAs in immunoregulation and autoimmunity: Technological advances and critical limitations

Immune cell function is critically dependent on precise control over transcriptional output from the genome. In this respect, integration of environmental signals that regulate gene expression, specifically by transcription factors, enhancer DNA elements, genome topography and non-coding RNAs (ncRNAs), are key components. The first three have been extensively investigated. Even though non-coding RNAs represent the vast majority of cellular RNA species, this class of RNA remains historically understudied. This is partly because of a lag in technological and bioinformatic innovations specifically capable of identifying and accurately measuring their expression. Nevertheless, recent progress in this domain has enabled a profusion of publications identifying novel sub-types of ncRNAs and studies directly addressing the function of ncRNAs in human health and disease. Many ncRNAs, including circular and enhancer RNAs, have now been demonstrated to play key functions in the regulation of immune cells and to show associations with immune-mediated diseases. Some ncRNAs may function as biomarkers of disease, aiding in diagnostics and in estimating response to treatment, while others may play a direct role in the pathogenesis of disease. Importantly, some are relatively stable and are amenable to therapeutic targeting, for example through gene therapy. Here, we provide an overview of ncRNAs and review technological advances that enable their study and hold substantial promise for the future. We provide context-specific examples by examining the associations of ncRNAs with four prototypical human autoimmune diseases, specifically rheumatoid arthritis, psoriasis, inflammatory bowel disease and multiple sclerosis. We anticipate that the utility and mechanistic roles of these ncRNAs in autoimmunity will be further elucidated in the near future.

miRBind: A Deep Learning Method for miRNA Binding Classification

The binding of microRNAs (miRNAs) to their target sites is a complex process, mediated by the Argonaute (Ago) family of proteins. The prediction of miRNA:target site binding is an important first step for any miRNA target prediction algorithm. To date, the potential for miRNA:target site binding is evaluated using either co-folding free energy measures or heuristic approaches, based on the identification of binding 'seeds', i.e., continuous stretches of binding corresponding to specific parts of the miRNA. The limitations of both these families of methods have produced generations of miRNA target prediction algorithms that are primarily focused on 'canonical' seed targets, even though unbiased experimental methods have shown that only approximately half of in vivo miRNA targets are 'canonical'. Herein, we present miRBind, a deep learning method and web server that can be used to accurately predict the potential of miRNA:target site binding. We trained our method using seed-agnostic experimental data and show that our method outperforms both seed-based approaches and co-fold free energy approaches. The full code for the development of miRBind and a freely accessible web server are freely available.

Studying miRNA-mRNA Interactions: An Optimized CLIP-Protocol for Endogenous Ago2-Protein

Transcriptome-wide analysis of RNA-binding partners is commonly achieved using UV crosslinking and immunoprecipitation (CLIP). Individual-nucleotide-resolution CLIP (iCLIP)enables identification of the specific position of the protein-RNA interaction. In addition to RNA-binding proteins (RBPs), microRNA (miRNA)-mRNA interactions also play a crucial role in the regulation of gene expression. Argonaute-2 (Ago2) mediates miRNA binding to a multitude of mRNA target sites, enabling the identification of miRNA-mRNA interactions by employing modified Ago2-CLIP protocols. Here, we describe an Ago2-specific CLIP protocol optimized for the use of small quantities of cell material, targeting endogenous Ago2 while avoiding possible methodological biases such as metabolic labeling or Ago2 overexpression and applying the latest advances in CLIP library preparation, the iCLIP2 protocol. In particular, we focus on the optimization of lysis conditions and improved radioactive labeling of the 5' end of the miRNA.

tRNA derived small RNAs—Small players with big roles

In the past 2 decades, small non-coding RNAs derived from tRNA (tsRNAs or tRNA derived fragments; tRFs) have emerged as new powerful players in the field of small RNA mediated regulation of gene expression, translation, and epigenetic control. tRFs have been identified from evolutionarily divergent organisms from Archaea, the higher plants, to humans. Recent studies have confirmed their roles in cancers and other metabolic disorders in humans and experimental models. They have been implicated in biotic and abiotic stress responses in plants as well. In this review, we summarize the current knowledge on tRFs including types of tRFs, their biogenesis, and mechanisms of action. The review also highlights recent studies involving differential expression profiling of tRFs and elucidation of specific functions of individual tRFs from various species. We also discuss potential considerations while designing experiments involving tRFs identification and characterization and list the available bioinformatics tools for this purpose.

Detecting RNA-RNA interactome

The last decade has seen a robust increase in various types of novel RNA molecules and their complexity in gene regulation. RNA molecules play a critical role in cellular events by interacting with other biomolecules, including protein, DNA, and RNA. It has been established that RNA-RNA interactions play a critical role in several biological processes by regulating the biogenesis and function of RNA molecules. Interestingly, RNA-RNA interactions regulate the biogenesis of diverse RNA molecules, including mRNAs, microRNAs, tRNAs, and circRNAs, through splicing or backsplicing. Structured RNAs like rRNA, tRNA, and snRNAs achieve their functional conformation by intramolecular RNA-RNA interactions. In addition, functional consequences of many intermolecular RNA-RNA interactions have been extensively studied in the regulation of gene expression. Hence, it is essential to understand the mechanism and functions of RNA-RNA interactions in eukaryotes. Conventionally, RNA-RNA interactions have been identified through diverse biochemical methods for decades. The advent of high-throughput RNA-sequencing technologies has revolutionized the identification of global RNA-RNA interactome in cells and their importance in RNA structure and function in gene expression regulation. Although these technologies revealed tens of thousands of intramolecular and intermolecular RNA-RNA interactions, we further look forward to future unbiased and quantitative high-throughput technologies for detecting transcriptome-wide RNA-RNA interactions. With the ability to detect RNA-RNA interactome, we expect that future studies will reveal the higher-order structures of RNA molecules and multi-RNA hybrids impacting human health and diseases. This article is categorized under: RNA Methods > RNA Analyses In Vitro and In Silico RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems.

Recent advances in RNA structurome

RNA structures are essential to support RNA functions and regulation in various biological processes. Recently, a range of novel technologies have been developed to decode genome-wide RNA structures and novel modes of functionality across a wide range of species. In this review, we summarize key strategies for probing the RNA structurome and discuss the pros and cons of representative technologies. In particular, these new technologies have been applied to dissect the structural landscape of the SARS-CoV-2 RNA genome. We also summarize the functionalities of RNA structures discovered in different regulatory layers-including RNA processing, transport, localization, and mRNA translation-across viruses, bacteria, animals, and plants. We review many versatile RNA structural elements in the context of different physiological and pathological processes (e.g., cell differentiation, stress response, and viral replication). Finally, we discuss future prospects for RNA structural studies to map the RNA structurome at higher resolution and at the single-molecule and single-cell level, and to decipher novel modes of RNA structures and functions for innovative applications.

Advances and Trends in Omics Technology Development

The human history has witnessed the rapid development of technologies such as high-throughput sequencing and mass spectrometry that led to the concept of “omics” and methodological advancement in systematically interrogating a cellular system. Yet, the ever-growing types of molecules and regulatory mechanisms being discovered have been persistently transforming our understandings on the cellular machinery. This renders cell omics seemingly, like the universe, expand with no limit and our goal toward the complete harness of the cellular system merely impossible. Therefore, it is imperative to review what has been done and is being done to predict what can be done toward the translation of omics information to disease control with minimal cell perturbation. With a focus on the “four big omics,” i.e., genomics, transcriptomics, proteomics, metabolomics, we delineate hierarchies of these omics together with their epiomics and interactomics, and review technologies developed for interrogation. We predict, among others, redoxomics as an emerging omics layer that views cell decision toward the physiological or pathological state as a fine-tuned redox balance.

RNase III CLASH in MRSA uncovers sRNA regulatory networks coupling metabolism to toxin expression

Methicillin-resistant Staphylococcus aureus (MRSA) is a bacterial pathogen responsible for significant human morbidity and mortality. Post-transcriptional regulation by small RNAs (sRNAs) has emerged as an important mechanism for controlling virulence. However, the functionality of the majority of sRNAs during infection is unknown. To address this, we performed UV cross-linking, ligation, and sequencing of hybrids (CLASH) in MRSA to identify sRNA-RNA interactions under conditions that mimic the host environment. Using a double-stranded endoribonuclease III as bait, we uncovered hundreds of novel sRNA-RNA pairs. Strikingly, our results suggest that the production of small membrane-permeabilizing toxins is under extensive sRNA-mediated regulation and that their expression is intimately connected to metabolism. Additionally, we also uncover an sRNA sponging interaction between RsaE and RsaI. Taken together, we present a comprehensive analysis of sRNA-target interactions in MRSA and provide details on how these contribute to the control of virulence in response to changes in metabolism.

Classification and clustering of RNA crosslink-ligation data reveal complex structures and homodimers

The recent development and application of methods based on the general principle of "crosslinking and proximity ligation" (crosslink-ligation) are revolutionizing RNA structure studies in living cells. However, extracting structure information from such data presents unique challenges. Here, we introduce a set of computational tools for the systematic analysis of data from a wide variety of crosslink-ligation methods, specifically focusing on read mapping, alignment classification, and clustering. We design a new strategy to map short reads with irregular gaps at high sensitivity and specificity. Analysis of previously published data reveals distinct properties and bias caused by the crosslinking reactions. We perform rigorous and exhaustive classification of alignments and discover eight types of arrangements that provide distinct information on RNA structures and interactions. To deconvolve the dense and intertwined gapped alignments, we develop a network/graph-based tool Crosslinked RNA Secondary Structure Analysis using Network Techniques (CRSSANT), which enables clustering of gapped alignments and discovery of new alternative and dynamic conformations. We discover that multiple crosslinking and ligation events can occur on the same RNA, generating multisegment alignments to report complex high-level RNA structures and multi-RNA interactions. We find that alignments with overlapped segments are produced from potential homodimers and develop a new method for their de novo identification. Analysis of overlapping alignments revealed potential new homodimers in cellular noncoding RNAs and RNA virus genomes in the Picornaviridae family. Together, this suite of computational tools enables rapid and efficient analysis of RNA structure and interaction data in living cells.

Global mapping of RNA homodimers in living cells

RNA homodimerization is important for various physiological processes, including the assembly of membraneless organelles, RNA subcellular localization, and packaging of viral genomes. However, understanding RNA dimerization has been hampered by the lack of systematic in vivo detection methods. Here, we show that CLASH, PARIS, and other RNA proximity ligation methods detect RNA homodimers transcriptome-wide as "overlapping" chimeric reads that contain more than one copy of the same sequence. Analyzing published proximity ligation data sets, we show that RNA:RNA homodimers mediated by direct base-pairing are rare across the human transcriptome, but highly enriched in specific transcripts, including U8 snoRNA, U2 snRNA, and a subset of tRNAs. Mutations in the homodimerization domain of U8 snoRNA impede dimerization in vitro and disrupt zebrafish development in vivo, suggesting an evolutionarily conserved role of this domain. Analysis of virus-infected cells reveals homodimerization of SARS-CoV-2 and Zika genomes, mediated by specific palindromic sequences located within protein-coding regions of N gene in SARS-CoV-2 and NS2A gene in Zika. We speculate that regions of viral genomes involved in homodimerization may constitute effective targets for antiviral therapies.

Uncovering Novel Viral Innate Immune Evasion Strategies: What Has SARS-CoV-2 Taught Us?

The ongoing SARS-CoV-2 pandemic has tested the capabilities of public health and scientific community. Since the dawn of the twenty-first century, viruses have caused several outbreaks, with coronaviruses being responsible for 2: SARS-CoV in 2007 and MERS-CoV in 2013. As the border between wildlife and the urban population continue to shrink, it is highly likely that zoonotic viruses may emerge more frequently. Furthermore, it has been shown repeatedly that these viruses are able to efficiently evade the innate immune system through various strategies. The strong and abundant antiviral innate immunity evasion strategies shown by SARS-CoV-2 has laid out shortcomings in our approach to quickly identify and modulate these mechanisms. It is thus imperative that there be a systematic framework for the study of the immune evasion strategies of these viruses, to guide development of therapeutics and curtail transmission. In this review, we first provide a brief overview of general viral evasion strategies against the innate immune system. Then, we utilize SARS-CoV-2 as a case study to highlight the methods used to identify the mechanisms of innate immune evasion, and pinpoint the shortcomings in the current paradigm with its focus on overexpression and protein-protein interactions. Finally, we provide a recommendation for future work to unravel viral innate immune evasion strategies and suitable methods to aid in the study of virus-host interactions. The insights provided from this review may then be applied to other viruses with outbreak potential to remain ahead in the arms race against viral diseases.

Promising Assays for Examining a Putative Role of Ribosomal Heterogeneity in COVID-19 Susceptibility and Severity

The heterogeneity of ribosomes, characterized by structural variations, arises from differences in types, numbers, and/or post-translational modifications of participating ribosomal proteins (RPs), ribosomal RNAs (rRNAs) sequence variants plus post-transcriptional modifications, and additional molecules essential for forming a translational machinery. The ribosomal heterogeneity within an individual organism or a single cell leads to preferential translations of selected messenger RNA (mRNA) transcripts over others, especially in response to environmental cues. The role of ribosomal heterogeneity in SARS-CoV-2 coronavirus infection, propagation, related symptoms, or vaccine responses is not known, and a technique to examine these has not yet been developed. Tools to detect ribosomal heterogeneity or to profile translating mRNAs independently cannot identify unique or specialized ribosome(s) along with corresponding mRNA substrate(s). Concurrent characterizations of RPs and/or rRNAs with mRNA substrate from a single ribosome would be critical to decipher the putative role of ribosomal heterogeneity in the COVID-19 disease, caused by the SARS-CoV-2, which hijacks the host ribosome to preferentially translate its RNA genome. Such a protocol should be able to provide a high-throughput screening of clinical samples in a large population that would reach a statistical power for determining the impact of a specialized ribosome to specific characteristics of the disease. These characteristics may include host susceptibility, viral infectivity and transmissibility, severity of symptoms, antiviral treatment responses, and vaccine immunogenicity including its side effect and efficacy. In this study, several state-of-the-art techniques, in particular, chemical probing of ribosomal components or rRNA structures, proximity ligation to generate rRNA-mRNA chimeras for sequencing, nanopore gating of individual ribosomes, nanopore RNA sequencing and/or structural analyses, single-ribosome mass spectrometry, and microfluidic droplets for separating ribosomes or indexing rRNAs/mRNAs, are discussed. The key elements for further improvement and proper integration of the above techniques to potentially arrive at a high-throughput protocol for examining individual ribosomes and their mRNA substrates in a clinical setting are also presented.

Emerging roles of RNA-RNA interactions in transcriptional regulation

Pervasive transcription of the human genome generates a massive amount of noncoding RNAs (ncRNAs) that lack protein-coding potential but play crucial roles in development, differentiation, and tumorigenesis. To achieve these biological functions, ncRNAs must first fold into intricate structures via intramolecular RNA-RNA interactions (RRIs) and then interact with different RNA substrates via intermolecular RRIs. RRIs are usually facilitated, stabilized, or mediated by RNA-binding proteins. With this guiding principle, several protein-based high-throughput methods have been developed for unbiased mapping of defined or all RNA-binding protein-mediated RRIs in various species and cell lines. In addition, some chemical-based approaches are also powerful to detect RRIs globally based on the fact that RNA duplex can be cross-linked by psoralen or its derivative 4'-aminomethyltrioxsalen. These efforts have significantly expanded our understanding of RRIs in determining the specificity and variability of gene regulation. Here, we review the current knowledge of the regulatory roles of RRI, focusing on their emerging roles in transcriptional regulation and nuclear body formation. This article is categorized under: RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry.

CLASH Analyst: A Web Server to Identify In Vivo RNA–RNA Interactions from CLASH Data

Non-coding RNAs, such as miRNAs and piRNAs, play critical roles in gene regulation through base-pairing interactions with their target molecules. The recent development of the crosslinking, ligation, and sequencing of hybrids (CLASH) method has allowed scientists to map transcriptome-wide RNA–RNA interactions by identifying chimeric reads consisting of fragments from regulatory RNAs and their targets. However, analyzing CLASH data requires scientists to use advanced bioinformatics, and currently available tools are limited for users with little bioinformatic experience. In addition, many published CLASH studies do not show the full scope of RNA–RNA interactions that were captured, highlighting the importance of reanalyzing published data. Here, we present CLASH Analyst, a web server that can analyze raw CLASH data within a fully customizable and easy-to-use interface. CLASH Analyst accepts raw CLASH data as input and identifies the RNA chimeras containing the regulatory and target RNAs according to the user’s interest. Detailed annotation of the captured RNA–RNA interactions is then presented for the user to visualize within the server or download for further analysis. We demonstrate that CLASH Analyst can identify miRNA- and piRNA-targeting sites reported from published CLASH data and should be applicable to analyze other RNA–RNA interactions. CLASH Analyst is freely available for academic use.

Architecture of RNA-RNA interactions

RNA molecules tend to form intricate tertiary structures via intramolecular RNA-RNA interactions (RRIs) to regulate transcription, RNA processing, and translation processes. In these biological processes, RNAs, especially noncoding RNAs, usually achieve their regulatory specificity through intermolecular RNA-RNA base pairing and execute their regulatory outcomes via associated RNA-binding proteins. Decoding intramolecular and intermolecular RRIs is a prerequisite for understanding the architecture of various RNA molecules and their regulatory roles in development, differentiation, and disease. Many sequencing-based methods have recently been invented and have revealed extraordinarily complicated RRIs in mammalian cells. Here, we discuss the technical advances and limitations of various methodologies developed for studying cellular RRIs, with a focus on the emerging architectural roles of RRIs in gene regulation.

Identifying proximal RNA interactions from cDNA-encoded crosslinks with ShapeJumper

SHAPE-JuMP is a concise strategy for identifying close-in-space interactions in RNA molecules. Nucleotides in close three-dimensional proximity are crosslinked with a bi-reactive reagent that covalently links the 2'-hydroxyl groups of the ribose moieties. The identities of crosslinked nucleotides are determined using an engineered reverse transcriptase that jumps across crosslinked sites, resulting in a deletion in the cDNA that is detected using massively parallel sequencing. Here we introduce ShapeJumper, a bioinformatics pipeline to process SHAPE-JuMP sequencing data and to accurately identify through-space interactions, as observed in complex JuMP datasets. ShapeJumper identifies proximal interactions with near-nucleotide resolution using an alignment strategy that is optimized to tolerate the unique non-templated reverse-transcription profile of the engineered crosslink-traversing reverse-transcriptase. JuMP-inspired strategies are now poised to replace adapter-ligation for detecting RNA-RNA interactions in most crosslinking experiments.

Small but Mighty-The Emerging Role of snoRNAs in Hematological Malignancies

Over recent years, the long known class of small nucleolar RNAs (snoRNAs) have gained interest among the scientific community, especially in the clinical context. The main molecular role of this interesting family of non-coding RNAs is to serve as scaffolding RNAs to mediate site-specific RNA modification of ribosomal RNAs (rRNAs) and small nuclear RNAs (snRNAs). With the development of new sequencing techniques and sophisticated analysis pipelines, new members of the snoRNA family were identified and global expression patterns in disease backgrounds could be determined. We will herein shed light on the current research progress in snoRNA biology and their clinical role by influencing disease outcome in hematological diseases. Astonishingly, in recent studies snoRNAs emerged as potent biomarkers in a variety of these clinical setups, which is also highlighted by the frequent deregulation of snoRNA levels in the hema-oncological context. However, research is only starting to reveal how snoRNAs might influence cellular functions and the connected disease hallmarks in hematological malignancies.

Identifying piRNA targets on mRNAs in C. elegans using a deep multi-head attention network

Background

Piwi-interacting RNAs (piRNAs) are the small non-coding RNAs (ncRNAs) that silence genomic transposable elements. And researchers found out that piRNA also regulates various endogenous transcripts. However, there is no systematic understanding of the piRNA binding patterns and how piRNA targets genes. While various prediction methods have been developed for other similar ncRNAs (e.g., miRNAs), piRNA holds distinctive characteristics and requires its own computational model for binding target prediction.

Results

Recently, transcriptome-wide piRNA binding events in C. elegans were probed by PRG-1 CLASH experiments. Based on the probed piRNA-messenger RNAs (mRNAs) binding pairs, in this research, we devised the first deep learning architecture based on multi-head attention to computationally identify piRNA targeting mRNA sites. In the devised deep network, the given piRNA and mRNA segment sequences are first one-hot encoded and undergo a combined operation of convolution and squeezing-extraction to unravel motif patterns. And we incorporate a novel multi-head attention sub-network to extract the hidden piRNA binding rules that can simulate the biological piRNA target recognition process. Finally, the true piRNA–mRNA binding pairs are identified by a deep fully connected sub-network. Our model obtains a supreme discriminatory power of AUC \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$=$$\end{document}= 93.3% on an independent test set and successfully extracts the verified binding pattern of a synthetic piRNA. These results demonstrated that the devised model achieves high prediction performance and suggests testable potential biological piRNA binding rules.

Conclusions

In this research, we developed the first deep learning method to identify piRNA targeting sites on C. elegans mRNAs. And the developed deep learning method is demonstrated to be of high accuracy and can provide biological insights into piRNA–mRNA binding patterns. The piRNA binding target identification network can be downloaded from http://cosbi2.ee.ncku.edu.tw/data_download/piRNA_mRNA_binding.

Mapping the miRNA-mRNA Interactome in Human Hepatocytes and Identification of Functional mirSNPs in Pharmacogenes

MiRNAs regulate the expression of hepatic genes involved in pharmacokinetics and pharmacodynamics. Genetic variants affecting miRNA binding (mirSNPs) have been associated with altered drug response, but previously used methods to identify miRNA binding sites and functional mirSNPs in pharmacogenes are indirect and limited by low throughput. We utilized the high-throughput chimeric-eCLIP assay to directly map thousands of miRNA-mRNA interactions and define the miRNA binding sites in primary hepatocytes. We then used the high-throughput PASSPORT-seq assay to functionally test 262 potential mirSNPs with coordinates overlapping the identified miRNA binding sites. Using chimeric-eCLIP, we identified a network of 448 miRNAs that collectively target 11,263 unique genes in primary hepatocytes pooled from 100 donors. Our data provide an extensive map of miRNA binding of each gene, including pharmacogenes, expressed in primary hepatocytes. For example, we identified the hsa-mir-27b-DPYD interaction at a previously validated binding site. A second example is our identification of 19 unique miRNAs that bind to CYP2B6 across 20 putative binding sites on the transcript. Using PASSPORT-seq, we then identified 24 mirSNPs that functionally impacted reporter mRNA levels. To our knowledge, this is the most comprehensive identification of miRNA binding sites in pharmacogenes. Combining chimeric-eCLIP with PASSPORT-seq successfully identified functional mirSNPs in pharmacogenes that may affect transcript levels through altered miRNA binding. These results provide additional insights into potential mechanisms contributing to interindividual variability in drug response.