Methods for comprehensive experimental identification of RNA-protein interactions

Rapid and Efficient Isolation of Total RNA-Bound Proteomes by Liquid Emulsion-Assisted Purification of RNA-Bound Protein (LEAP-RBP)

The critical roles of RNA-binding proteins (RBPs) in all aspects of RNA biology fostered the development of methods utilizing ultraviolet (UV) crosslinking and method-specific RNA enrichment steps for proteome-wide identification and assessment of RBP function. Despite the substantial contributions of these UV-based RNA-centric methods to our understanding of RNA-protein interaction networks, their utility is constrained by biases in RBP recovery and significant noise contributions, which can confound meaningful interpretation. To overcome these issues, we recently developed a method termed Liquid Emulsion-Assisted Purification of RNA-Bound Protein (LEAP-RBP) and introduced quantitative signal-to-noise (S:N)-based metrics for the proteome-wide identification of RNA interactomes and accurate assessment of global RBP occupancy dynamics. Compared to existing methodologies, LEAP-RBP provides significant advantages in speed, cost, efficiency, and selectivity for RNA-bound proteins. In this work, we provide a step-by-step guide for the successful application of the LEAP-RBP method for both small- and large-scale investigations of RNA-bound proteomes. Key features • Unbiased and efficient isolation of total RNA-bound protein, RNA, and protein from biological samples. • Cost-effective identification of proteome-wide RNA interactomes and validation of direct RNA-binding protein functionality. • Robust and accurate assessment of context- and/or condition-dependent RBP occupancy state dynamics.

RNA-binding proteins in cardiovascular biology and disease: the beat goes on

Cardiac development and function are becoming increasingly well understood from different angles, including signalling, transcriptional and epigenetic mechanisms. By contrast, the importance of the post-transcriptional landscape of cardiac biology largely remains to be uncovered, building on the foundation of a few existing paradigms. The discovery during the past decade of hundreds of additional RNA-binding proteins in mammalian cells and organs, including the heart, is expected to accelerate progress and has raised intriguing possibilities for better understanding the intricacies of cardiac development, metabolism and adaptive alterations. In this Review, we discuss the progress and new concepts on RNA-binding proteins and RNA biology and appraise them in the context of common cardiovascular clinical conditions, from cell and organ-wide perspectives. We also discuss how a better understanding of cardiac RNA-binding proteins can fill crucial knowledge gaps in cardiology and might pave the way to developing better treatments to reduce cardiovascular morbidity and mortality.

High-throughput quantitation of protein-RNA UV-crosslinking efficiencies as a predictive tool for high-confidence identification of RNA-binding proteins

UV-crosslinking has proven to be an invaluable tool for the identification of RNA-protein interactomes. The paucity of methods for distinguishing background from bona fide RNA-protein interactions, however, makes attribution of RNA-binding function on UV-crosslinking alone challenging. To address this need, we previously reported an RNA-binding protein (RBP) confidence scoring metric (RCS), incorporating both signal-to-noise (S:N) and protein abundance determinations to distinguish high- and low-confidence candidate RBPs. Although RCS has utility, we sought a direct metric for quantification and comparative evaluation of protein-RNA interactions. Here we propose the use of protein-specific UV-crosslinking efficiency (%CL), representing the molar fraction of a protein that is crosslinked to RNA, for functional evaluation of candidate RBPs. Application to the HeLa RNA interactome yielded %CL values for 1097 proteins. Remarkably, %CL values span over five orders of magnitude. For the HeLa RNA interactome, %CL values comprise a range from high efficiency, high specificity interactions, e.g., the Elav protein HuR and the Pumilio homolog Pum2, with %CL values of 45.9 and 24.2, respectively, to very low efficiency and specificity interactions, for example, the metabolic enzymes glyceraldehyde-3-phosphate dehydrogenase, fructose-bisphosphate aldolase, and alpha-enolase, with %CL values of 0.0016, 0.006, and 0.008, respectively. We further extend the utility of %CL through prediction of protein domains and classes with known RNA-binding functions, thus establishing it as a useful metric for RNA interactome analysis. We anticipate that this approach will benefit efforts to establish functional RNA interactomes and support the development of more predictive computational approaches for RBP identification.

eCRUIS captures RNA-protein interaction in vitro and in vivo

As an information bridge between DNA and protein, RNA regulates cellular processes and gene expression in various ways. From its synthesis to degradation, RNA is associated with a range of RNA-binding proteins. Therefore, it is necessary to develop innovative methods to study the interaction between RNA and proteins. Previously, we developed an RNA-centric method, called CRISPR-based RNA-United Interacting System (CRUIS), to capture RNA-protein interaction in cells. On this basis, here we develop an enhanced CRUIS (eCRUIS) by combining the power of dCas13d and the engineered promiscuous ligase TurboID. The current version allows us to rapidly label RNA-binding proteins on the target RNA within 30 minutes, potentially for in vivo use. By introducing bait-assay with exogenous RNA, we confirm that eCRUIS can effectively label RNA-binding proteins on bait RNA in a short time. eCRUIS provides a broader range of in vitro and in vivo applications for studying RNA-protein interactions.

GRAS1 non-coding RNA protects against DNA damage and cell death by binding and stabilizing NKAP

Non-coding RNA (ncRNA) gene products are involved in diverse biological processes including splicing, epigenetic regulation, gene expression, proliferation, and metabolism. The biological mechanisms by which ncRNAs contribute to cell survival remain poorly understood. We found that the Growth Regulator Antisense 1 (GRAS1) long non-coding RNA (lncRNA) transcript promotes growth in multiple human cell types by protecting against DNA damage. Knockdown of GRAS1 induced DNA damage and cell death, along with significant expression changes in DNA damage response, intrinsic apoptotic signaling, and cellular response to environmental stimulus genes. Extensive DNA damage occurred after GRAS1 knockdown, with numerous double strand breaks occurring in each cell. The number of cells undergoing apoptosis and with fragmented nuclei increased significantly after GRAS1 knockdown. We used RNA antisense purification and mass spectrometry (RAP-MS) to identify the NF-κB activating protein (NKAP) as a direct protein interaction partner of GRAS1 lncRNA. NKAP protein was degraded after GRAS1 knockdown, in a proteasome-dependent manner. Overexpression of GRAS1 or NKAP mitigated the DNA damage effects of GRAS1 knockdown. In summary, GRAS1 and NKAP directly interact to protect against DNA damage and cell death in multiple human cell lines.

Intensity and retention time prediction improves the rescoring of protein-nucleic acid cross-links

In protein-RNA cross-linking mass spectrometry, UV or chemical cross-linking introduces stable bonds between amino acids and nucleic acids in protein-RNA complexes that are then analyzed and detected in mass spectra. This analytical tool delivers valuable information about RNA-protein interactions and RNA docking sites in proteins, both in vitro and in vivo. The identification of cross-linked peptides with oligonucleotides of different length leads to a combinatorial increase in search space. We demonstrate that the peptide retention time prediction tasks can be transferred to the task of cross-linked peptide retention time prediction using a simple amino acid composition encoding, yielding improved identification rates when the prediction error is included in rescoring. For the more challenging task of including fragment intensity prediction of cross-linked peptides in the rescoring, we obtain, on average, a similar improvement. Further improvement in the encoding and fine-tuning of retention time and intensity prediction models might lead to further gains, and merit further research.

Implication of lncRNA MSTRG.81401 in Hippocampal Pyroptosis Induced by P2X7 Receptor in Type 2 Diabetic Rats with Neuropathic Pain Combined with Depression

Major depressive disorder (MDD) is a common complication of diabetes and is often observed alongside diabetic neuropathic pain (DNP) as a comorbidity in diabetic patients. Long non-coding RNA (lncRNA) plays an important role in various pathophysiological processes. The P2X7 receptor is responsible for triggering inflammatory responses, such as pyroptosis, linked to pain and depression. The aim of this study was to investigate the effect of lncRNA MSTRG.81401 on hippocampal pyroptosis induced by the P2X7 receptor in diabetic rats with DNP combined with MDD (DNP + MDD). Our results showed that the expression of lncRNA MSTRG.81401 was significantly elevated in the hippocampus of DNP + MDD rats compared with the control group. Following the administration of shRNA targeting lncRNA MSTRG.81401, a notable elevation in mechanical and thermal pain thresholds was observed in rats with comorbid DNP and MDD. Additionally, significant improvements in depression-like behaviors were evident in the open-field test (OFT), sucrose preference test (SPT), and forced swim test (FST). In the DNP + MDD rats, elevated levels in hippocampal P2X7 receptor mRNA and protein were observed, along with increased co-expression of P2X7 and the astrocytic marker glial fibrillary acidic protein (GFAP). Meanwhile, in DNP + MDD rats, the heightened mRNA expression of NOD-like receptor protein 3 (NLRP3), apoptosis-associated speck-like protein (ASC), pyroptosis-related protein Gasdermin D (GSDMD), caspase-1, IL-1β, IL-18, and TNF-α was detected, in addition to increased serum levels of IL-1β, IL-18 and TNF-α. After shRNA treatment with lncRNA MSTRG.81401, the above abnormal changes in indicators for pyroptosis and inflammation were improved. Therefore, our study demonstrates that shRNA of lncRNA MSTRG.81401 can alleviate the pain and depression-like behaviors in diabetic rats associated with the comorbidity of DNP and MDD by inhibiting the hippocampal P2X7 receptor-mediated pyroptosis pathway and pro-inflammatory responses. This suggests that the P2X7R/NLRP3/caspase-1 implicated pyroptosis and inflammatory scenario may serve as a potential target for the management of comorbid DNP and MDD in diabetes.

Immunoprecipitation Methods to Isolate Messenger Ribonucleoprotein Complexes (mRNP)

Throughout their life cycle, messenger RNAs (mRNAs) associate with proteins to form ribonucleoproteins (mRNPs). Each mRNA is part of multiple successive mRNP complexes that participate in their biogenesis, cellular localization, translation and decay. The dynamic composition of mRNP complexes and their structural remodelling play crucial roles in the control of gene expression. Studying the endogenous composition of different mRNP complexes is a major challenge. In this chapter, we describe the variety of protein-centric immunoprecipitation methods available for the identification of mRNP complexes and the requirements for their experimental settings.

Preparation of Cardiac Extracts from Embryonal Hearts to Capture RNA-protein Interactions by CLIP

The interaction of RNA with specific RNA-binding proteins (RBP) leads to the establishment of complex regulatory networks through which gene expression is controlled. Careful consideration should be given to the exact environment where a given RNA/RBP interplay occurs, as the functional responses might depend on the type of organism as well as the specific cellular or subcellular contexts. This requisite becomes particularly crucial for the study of long non-coding RNAs (lncRNA), as a consequence of their peculiar tissue-specificity and timely regulated expression. The functional characterization of lncRNAs has traditionally relied on the use of established cell lines that, although useful, are unable to fully recapitulate the complexity of a tissue or organ. Here, we detail an optimized protocol, with comments and tips, to identify the RNA interactome of given RBPs by performing cross-linking immunoprecipitation (CLIP) from mouse embryonal hearts. We tested the efficiency of this protocol on the murine pCharme, a muscle-specific lncRNA interacting with Matrin3 (MATR3) and forming RNA-enriched condensates of biological significance in the nucleus. Key features • The protocol refines previous methods of cardiac extracts preparation to use for CLIP assays. • The protocol allows the quantitative RNA-seq analysis of transcripts interacting with selected proteins. • Depending on the embryonal stage, a high number of hearts can be required as starting material. • The steps are adaptable to other tissues and biochemical assays.

Targeting MALAT1 Augments Sensitivity to PARP Inhibition by Impairing Homologous Recombination in Prostate Cancer

PARP inhibitors (PARPi) have emerged as a promising targeted therapeutic intervention for metastatic castrate-resistant prostate cancer (mCRPC). However, the clinical utility of PARPi is limited to a subset of patients who harbor aberrations in the genes associated with the homologous recombination (HR) pathway. Here, we report that targeting metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), an oncogenic long noncoding RNA (lncRNA), contrives a BRCAness-like phenotype, and augments sensitivity to PARPi. Mechanistically, we show that MALAT1 silencing reprograms the homologous recombination (HR) transcriptome and makes prostate cancer cells more vulnerable to PARPi. Particularly, coinhibition of MALAT1 and PARP1 exhibits a decline in clonogenic survival, delays resolution of γH2AX foci, and reduces tumor burden in mice xenograft model. Moreover, we show that miR-421, a tumor suppressor miRNA, negatively regulates the expression of HR genes, while in aggressive prostate cancer cases, miR-421 is sequestered by MALAT1, leading to increased expression of HR genes. Conclusively, our findings suggest that MALAT1 ablation confers sensitivity to PARPi, thus highlighting an alternative therapeutic strategy for patients with castration-resistant prostate cancer (CRPC), irrespective of the alterations in HR genes.

SIGNIFICANCE

PARPi are clinically approved for patients with metastatic CRPC carrying mutations in HR genes, but are ineffective for HR-proficient prostate cancer. Herein, we show that oncogenic lncRNA, MALAT1 is frequently overexpressed in advanced stage prostate cancer and plays a crucial role in maintaining genomic integrity. Importantly, we propose a novel therapeutic strategy that emphasizes MALAT1 inhibition, leading to HR dysfunction in both HR-deficient and -proficient prostate cancer, consequently augmenting their susceptibility to PARPi.

Functional knockout of long non-coding RNAs with genome editing

An effective loss-of-function study is necessary to investigate the biological function of long non-coding RNA (lncRNA). Various approaches are available, including RNA silencing, antisense oligos, and CRISPR-based genome editing. CRISPR-based genome editing is the most widely used for inactivating lncRNA function at the genomic level. Knocking out the lncRNA function can be achieved by removing the promoter and the first exon (PE1), introducing pre-termination poly(A) signals, or deleting the entire locus, unlike frameshift strategies used for messenger RNA (mRNA). However, the intricate genomic interplay between lncRNA and neighbor genes makes it challenging to interpret lncRNA function accurately. This article discusses the advantages and disadvantages of each lncRNA knockout method and envisions the potential future directions to facilitate lncRNA functional study.

Streamlined Purification of RNA-Protein Complexes Using UV Cross-Linking and RNA Antisense Purification

RNA-protein interactions are important in development and disease, but identification of novel RNA-protein interactions remains challenging. Here, we describe an updated capture method to identify direct and specific RNA-protein interactions. First, RNA and protein are covalently cross-linked in living cells by treatment with UV light at 254 nanometers wavelength. The antisense purification approach is dependent upon nucleic acid hybridization between biotinylated DNA probes and a target RNA. Target protein:RNA:DNA complexes are enriched by capture on streptavidin magnetic beads and purified through several denaturing washes that remove nonspecific protein and nucleic acid interactors. Mass spectrometry is used to identify proteins that are specifically enriched in the target RNA capture. This method has been applied to discover the protein interactions of noncoding RNAs but can be used to capture any RNA where the target sequence is known.

Proximity-dependent biotinylation technologies for mapping RNA-protein interactions in live cells

Proximity ligation technologies are extremely powerful tools for unveiling RNA-protein interactions occurring at different stages in living cells. These approaches mainly rely on the inducible activity of enzymes (biotin ligases or peroxidases) that promiscuously biotinylate macromolecules within a 20 nm range. These enzymes can be either fused to an RNA binding protein or tethered to any RNA of interest and expressed in living cells to biotinylate the amino acids and nucleic acids of binding partners in proximity. The biotinylated molecules can then be easily affinity purified under denaturing conditions and analyzed by mass spectrometry or next generation sequencing. These approaches have been widely used in recent years, providing a potent instrument to map the molecular interactions of specific RNA-binding proteins as well as RNA transcripts occurring in mammalian cells. In addition, they permit the identification of transient interactions as well as interactions among low expressed molecules that are often missed by standard affinity purification strategies. This review will provide a brief overview of the currently available proximity ligation methods, highlighting both their strengths and shortcomings. Furthermore, it will bring further insights to the way these technologies could be further used to characterize post-transcriptional modifications that are known to regulate RNA-protein interactions.

Profiling RNA at chromatin targets in situ by antibody-targeted tagmentation

Whereas techniques to map chromatin-bound proteins are well developed, mapping chromatin-associated RNAs remains a challenge. Here, we describe Reverse Transcribe and Tagment (RT&Tag), in which RNAs associated with a chromatin epitope are targeted by an antibody followed by a protein A-Tn5 transposome. Localized reverse transcription generates RNA/cDNA hybrids that are subsequently tagmented by Tn5 transposases for downstream sequencing. We demonstrate the utility of RT&Tag in Drosophila cells for capturing the noncoding RNA roX2 with the dosage compensation complex and maturing transcripts associated with silencing histone modifications. We also show that RT&Tag can detect N6-methyladenosine-modified mRNAs, and show that genes producing methylated transcripts are characterized by extensive promoter pausing of RNA polymerase II. The high efficiency of in situ antibody tethering and tagmentation makes RT&Tag especially suitable for rapid low-cost profiling of chromatin-associated RNAs.

Regulatory Network of Serine/Arginine-Rich (SR) Proteins: The Molecular Mechanism and Physiological Function in Plants

Serine/arginine-rich (SR) proteins are a type of splicing factor. They play significant roles in constitutive and alternative pre-mRNA splicing, and are involved in post-splicing activities, such as mRNA nuclear export, nonsense-mediated mRNA decay, mRNA translation, and miRNA biogenesis. In plants, SR proteins function under a complex regulatory network by protein–protein and RNA–protein interactions between SR proteins, other splicing factors, other proteins, or even RNAs. The regulatory networks of SR proteins are complex—they are regulated by the SR proteins themselves, they are phosphorylated and dephosphorylated through interactions with kinase, and they participate in signal transduction pathways, whereby signaling cascades can link the splicing machinery to the exterior environment. In a complex network, SR proteins are involved in plant growth and development, signal transduction, responses to abiotic and biotic stresses, and metabolism. Here, I review the current status of research on plant SR proteins, construct a model of SR proteins function, and ask many questions about SR proteins in plants.

Ribonomics Approaches to Identify RBPome in Plants and Other Eukaryotes: Current Progress and Future Prospects

RNA-binding proteins (RBPs) form complex interactions with RNA to regulate the cell’s activities including cell development and disease resistance. RNA-binding proteome (RBPome) aims to profile and characterize the RNAs and proteins that interact with each other to carry out biological functions. Generally, RNA-centric and protein-centric ribonomic approaches have been successfully developed to profile RBPome in different organisms including plants and animals. Further, more and more novel methods that were firstly devised and applied in mammalians have shown great potential to unravel RBPome in plants such as RNA-interactome capture (RIC) and orthogonal organic phase separation (OOPS). Despise the development of various robust and state-of-the-art ribonomics techniques, genome-wide RBP identifications and characterizations in plants are relatively fewer than those in other eukaryotes, indicating that ribonomics techniques have great opportunities in unraveling and characterizing the RNA–protein interactions in plant species. Here, we review all the available approaches for analyzing RBPs in living organisms. Additionally, we summarize the transcriptome-wide approaches to characterize both the coding and non-coding RBPs in plants and the promising use of RBPome for booming agriculture.

Next-generation sequencing: A new avenue to understand viral RNA-protein interactions

The genomes of RNA viruses present an astonishing source of both sequence and structural diversity. From intracellular viral RNA-host interfaces to interactions between the RNA genome and structural proteins in virus particles themselves, almost the entire viral lifecycle is accompanied by a myriad of RNA-protein interactions that are required to fulfill their replicative potential. It is therefore important to characterize such rich and dynamic collections of viral RNA-protein interactions to understand virus evolution and their adaptation to their hosts and environment. Recent advances in next-generation sequencing technologies have allowed the characterization of viral RNA-protein interactions, including both transient and conserved interactions, where molecular and structural approaches have fallen short. In this review, we will provide a methodological overview of the high-throughput techniques used to study viral RNA-protein interactions, their biochemical mechanisms, and how they evolved from classical methods as well as one another. We will discuss how different techniques have fueled virus research to characterize how viral RNA and proteins interact, both locally and on a global scale. Finally, we will present examples on how these techniques influence the studies of clinically important pathogens such as HIV-1 and SARS-CoV-2.

Compartment-Specific Proximity Ligation Expands the Toolbox to Assess the Interactome of the Long Non-Coding RNA NEAT1

The nuclear paraspeckle assembly transcript 1 (NEAT1) locus encodes two long non-coding (lnc)RNA isoforms that are upregulated in many tumours and dynamically expressed in response to stress. NEAT1 transcripts form ribonucleoprotein complexes with numerous RNA-binding proteins (RBPs) to assemble paraspeckles and modulate the localisation and activity of gene regulatory enzymes as well as a subset of messenger (m)RNA transcripts. The investigation of the dynamic composition of NEAT1-associated proteins and mRNAs is critical to understand the function of NEAT1. Interestingly, a growing number of biochemical and genetic tools to assess NEAT1 interactomes has been reported. Here, we discuss the Hybridisation Proximity (HyPro) labeling technique in the context of NEAT1. HyPro labeling is a recently developed method to detect spatially ordered interactions of RNA-containing nuclear compartments in cultured human cells. After introducing NEAT1 and paraspeckles, we describe the advantages of the HyPro technology in the context of other methods to study RNA interactomes, and review the key findings in mapping NEAT1-associated RNA transcripts and protein binding partners. We further discuss the limitations and potential improvements of HyPro labeling, and conclude by delineating its applicability in paraspeckles-related cancer research.

The acetyltransferase p300 is recruited in trans to multiple enhancer sites by lncSmad7

The histone acetyltransferase p300 (also known as KAT3B) is a general transcriptional coactivator that introduces the H3K27ac mark on enhancers triggering their activation and gene transcription. Genome-wide screenings demonstrated that a large fraction of long non-coding RNAs (lncRNAs) plays a role in cellular processes and organ development although the underlying molecular mechanisms remain largely unclear (1,2). We found 122 lncRNAs that interacts directly with p300. In depth analysis of one of these, lncSmad7, is required to maintain ESC self-renewal and it interacts to the C-terminal domain of p300. lncSmad7 also contains predicted RNA-DNA Hoogsteen forming base pairing. Combined Chromatin Isolation by RNA precipitation followed by sequencing (ChIRP-seq) together with CRISPR/Cas9 mutagenesis of the target sites demonstrate that lncSmad7 binds and recruits p300 to enhancers in trans, to trigger enhancer acetylation and transcriptional activation of its target genes. Thus, these results unveil a new mechanism by which p300 is recruited to the genome.

Towards an Ideal In Cell Hybridization-Based Strategy to Discover Protein Interactomes of Selected RNA Molecules

RNA-binding proteins are crucial to the function of coding and non-coding RNAs. The disruption of RNA–protein interactions is involved in many different pathological states. Several computational and experimental strategies have been developed to identify protein binders of selected RNA molecules. Amongst these, ‘in cell’ hybridization methods represent the gold standard in the field because they are designed to reveal the proteins bound to specific RNAs in a cellular context. Here, we compare the technical features of different ‘in cell’ hybridization approaches with a focus on their advantages, limitations, and current and potential future applications.

Capture of the newly transcribed RNA interactome using click chemistry

Application of synthetic nucleoside analogues to capture newly transcribed RNAs has unveiled key features of RNA metabolism. Whether this approach could be adapted to isolate the RNA-bound proteome (RNA interactome) was, however, unexplored. We have developed a new method (capture of the newly transcribed RNA interactome using click chemistry, or RICK) for the systematic identification of RNA-binding proteins based on the incorporation of 5-ethynyluridine into newly transcribed RNAs followed by UV cross-linking and click chemistry-mediated biotinylation. The RNA-protein adducts are then isolated by affinity capture using streptavidin-coated beads. Through high-throughput RNA sequencing and mass spectrometry, the RNAs and proteins can be elucidated globally. A typical RICK experimental procedure takes only 1 d, excluding the steps of cell preparation, 5-ethynyluridine labeling, validation (silver staining, western blotting, quantitative reverse-transcription PCR (qRT-PCR) or RNA sequencing (RNA-seq)) and proteomics. Major advantages of RICK are the capture of RNA-binding proteins interacting with any type of RNA and, particularly, the ability to discern between newly transcribed and steady-state RNAs through controlled labeling. Thanks to its versatility, RICK will facilitate the characterization of the total and newly transcribed RNA interactome in different cell types and conditions.

Translational Applications of Linear and Circular Long Noncoding RNAs in Endometriosis

Endometriosis is a chronic gynecologic disease that negatively affects the quality of life of many women. Unfortunately, endometriosis does not have a cure. The current medical treatments involve hormonal manipulation with unwanted side effects and high recurrence rates after stopping the medication. Sadly, a definitive diagnosis for endometriosis requires invasive surgical procedures, with the risk of complications, additional surgeries in the future, and a high rate of recurrence. Both improved therapies and noninvasive diagnostic tests are needed. The unique molecular features of endometriosis have been studied at the coding gene level. While the molecular components of endometriosis at the small RNA level have been studied extensively, other noncoding RNAs, such as long intergenic noncoding RNAs and the more recently discovered subset of long noncoding RNAs called circular RNAs, have been studied more limitedly. This review describes the molecular formation of long noncoding and the unique circumstances of the formation of circular long noncoding RNAs, their expression and function in endometriosis, and promising preclinical studies. Continued translational research on long noncoding RNAs, including the more stable circular long noncoding RNAs, may lead to improved therapeutic and diagnostic opportunities.

Muscle Regeneration and RNA: New Perspectives for Ancient Molecules

The ability of the ribonucleic acid (RNA) to self-replicate, combined with a unique cocktail of chemical properties, suggested the existence of an RNA world at the origin of life. Nowadays, this hypothesis is supported by innovative high-throughput and biochemical approaches, which definitively revealed the essential contribution of RNA-mediated mechanisms to the regulation of fundamental processes of life. With the recent development of SARS-CoV-2 mRNA-based vaccines, the potential of RNA as a therapeutic tool has received public attention. Due to its intrinsic single-stranded nature and the ease with which it is synthesized in vitro, RNA indeed represents the most suitable tool for the development of drugs encompassing every type of human pathology. The maximum effectiveness and biochemical versatility is achieved in the guise of non-coding RNAs (ncRNAs), which are emerging as multifaceted regulators of tissue specification and homeostasis. Here, we report examples of coding and ncRNAs involved in muscle regeneration and discuss their potential as therapeutic tools. Small ncRNAs, such as miRNA and siRNA, have been successfully applied in the treatment of several diseases. The use of longer molecules, such as lncRNA and circRNA, is less advanced. However, based on the peculiar properties discussed below, they represent an innovative pool of RNA biomarkers and possible targets of clinical value.

Capsule-LPI: a LncRNA-protein interaction predicting tool based on a capsule network

BACKGROUND

Long noncoding RNAs (lncRNAs) play important roles in multiple biological processes. Identifying LncRNA-protein interactions (LPIs) is key to understanding lncRNA functions. Although some LPIs computational methods have been developed, the LPIs prediction problem remains challenging. How to integrate multimodal features from more perspectives and build deep learning architectures with better recognition performance have always been the focus of research on LPIs.

RESULTS

We present a novel multichannel capsule network framework to integrate multimodal features for LPI prediction, Capsule-LPI. Capsule-LPI integrates four groups of multimodal features, including sequence features, motif information, physicochemical properties and secondary structure features. Capsule-LPI is composed of four feature-learning subnetworks and one capsule subnetwork. Through comprehensive experimental comparisons and evaluations, we demonstrate that both multimodal features and the architecture of the multichannel capsule network can significantly improve the performance of LPI prediction. The experimental results show that Capsule-LPI performs better than the existing state-of-the-art tools. The precision of Capsule-LPI is 87.3%, which represents a 1.7% improvement. The F-value of Capsule-LPI is 92.2%, which represents a 1.4% improvement.

CONCLUSIONS

This study provides a novel and feasible LPI prediction tool based on the integration of multimodal features and a capsule network. A webserver ( http://csbg-jlu.site/lpc/predict ) is developed to be convenient for users.

A live-cell assay for the detection of pre-microRNA-protein interactions

Recent efforts in genome-wide sequencing and proteomics have revealed the fundamental roles that RNA-binding proteins (RBPs) play in the life cycle and function of coding and non-coding RNAs. While these methodologies provide a systems-level view of the networking of RNA and proteins, approaches to enable the cellular validation of discovered interactions are lacking. Leveraging the power of bioorthogonal chemistry- and split-luciferase-based assay technologies, we have devised a conceptually new assay for the live-cell detection of RNA-protein interactions (RPIs), RNA interaction with Protein-mediated Complementation Assay, or RiPCA. As proof-of-concept, we utilized the interaction of the pre-microRNA, pre-let-7, with its binding partner, Lin28. Using this system, we have demonstrated the selective detection of the pre-let-7-Lin28 RPI in both the cytoplasm and nucleus. Furthermore, we determined that this technology can be used to discern relative affinities for specific sequences as well as of individual RNA binding domains. Thus, RiPCA has the potential to serve as a useful tool in supporting the investigation of cellular RPIs.

M(R)apping RNA-Protein Interactions

The systematic investigation of RNA-protein interactions is a key step towards a better understanding of the functions of RNA molecules.We developed an easy-to-use method to isolate and identify RNAs and proteins bound to long non-coding RNAs (lncRNAs ) in their native configuration. Similar to other methodologies, we utilize biotinylated antisense oligonucleotides (ASOs) to purify the lncRNA of interest and its associated proteins from different cellular compartments.

Enzymatic RNA Biotinylation for Affinity Purification and Identification of RNA-Protein Interactions

Throughout their cellular lifetime, RNA transcripts are bound to proteins, playing crucial roles in RNA metabolism, trafficking, and function. Despite the importance of these interactions, identifying the proteins that interact with an RNA of interest in mammalian cells represents a major challenge in RNA biology. Leveraging the ability to site-specifically and covalently label an RNA of interest using E. coli tRNA guanine transglycosylase and an unnatural nucleobase substrate, we establish the identification of RNA-protein interactions and the selective enrichment of cellular RNA in mammalian systems. We demonstrate the utility of this approach through the identification of known binding partners of 7SK snRNA via mass spectrometry. Through a minimal 4-nucleotide mutation of the long noncoding RNA HOTAIR, enzymatic biotinylation enables identification of putative HOTAIR binding partners in MCF7 breast cancer cells that suggest new potential pathways for oncogenic function. Furthermore, using RNA sequencing and qPCR, we establish that an engineered enzyme variant achieves high levels of labeling selectivity against the human transcriptome allowing for 145-fold enrichment of cellular RNA directly from mammalian cell lysates. The flexibility and breadth of this approach suggests that this system could be routinely applied to the functional characterization of RNA, greatly expanding the toolbox available for studying mammalian RNA biology.

Detection of RNA in Ribonucleoprotein Complexes by Blue Native Northern Blotting

Northern blotting is a classical technique that allows the detection of specific nucleic acids using radioactive or non-radioactive probes. Normally, nucleic acids are denatured and separated by agarose or polyacrylamide gel electrophoresis and transferred and fixed to a membrane prior to detection. Here, we describe a method to analyze specific RNA in native ribonucleoprotein complexes using blue native PAGE with subsequent northern blotting, crosslinking of RNA onto a suitable membrane, and detection using non-radioactive probes.

HOTAIRM1 regulates neuronal differentiation by modulating NEUROGENIN 2 and the downstream neurogenic cascade

Neuronal differentiation is a timely and spatially regulated process, relying on precisely orchestrated gene expression control. The sequential activation/repression of genes driving cell fate specification is achieved by complex regulatory networks, where transcription factors and noncoding RNAs work in a coordinated manner. Herein, we identify the long noncoding RNA HOTAIRM1 (HOXA Transcript Antisense RNA, Myeloid-Specific 1) as a new player in neuronal differentiation. We demonstrate that the neuronal-enriched HOTAIRM1 isoform epigenetically controls the expression of the proneural transcription factor NEUROGENIN 2 that is key to neuronal fate commitment and critical for brain development. We also show that HOTAIRM1 activity impacts on NEUROGENIN 2 downstream regulatory cascade, thus contributing to the achievement of proper neuronal differentiation timing. Finally, we identify the RNA-binding proteins HNRNPK and FUS as regulators of HOTAIRM1 biogenesis and metabolism. Our findings uncover a new regulatory layer underlying NEUROGENIN 2 transitory expression in neuronal differentiation and reveal a previously unidentified function for the neuronal-induced long noncoding RNA HOTAIRM1.

Human Long Noncoding RNA Interactome: Detection, Characterization and Function

The application of a new generation of sequencing techniques has revealed that most of the genome has already been transcribed. However, only a small part of the genome codes proteins. The rest of the genome "dark matter" belongs to divergent groups of non-coding RNA (ncRNA), that is not translated into proteins. There are two groups of ncRNAs, which include small and long non-coding RNAs (sncRNA and lncRNA respectively). Over the last decade, there has been an increased interest in lncRNAs and their interaction with cellular components. In this review, we presented the newest information about the human lncRNA interactome. The term lncRNA interactome refers to cellular biomolecules, such as nucleic acids, proteins, and peptides that interact with lncRNA. The lncRNA interactome was characterized in the last decade, however, understanding what role the biomolecules associated with lncRNA play and the nature of these interactions will allow us to better understand lncRNA's biological functions in the cell. We also describe a set of methods currently used for the detection of lncRNA interactome components and the analysis of their interactions. We think that such a holistic and integrated analysis of the lncRNA interactome will help to better understand its potential role in the development of organisms and cancers.

Ribonucleoprotein Immunoprecipitation (RIP) Analysis

RNAs and RNA-binding proteins (RBPs) can interact dynamically in ribonucleoprotein (RNP) complexes that play important roles in controlling gene expression programs. One of the powerful ways to investigate changes in the association of RNAs with an RBP of interest is by immunoprecipitation (IP) analysis of native RNPs. RIP (RNP immunoprecipitation) analysis enables the rapid identification of endogenous RNAs bound to an RBP and to monitor time-dependent changes in this association, as well as changes in response to different metabolic and stress conditions. The protocol is based on the use of an antibody, typically an anti-RBP antibody, to immunoprecipitate the RNP complex. The RNA within the immunoprecipitated complex can then be isolated and further studied using different approaches such as PCR, microarray, Northern blot, and sequencing analyses. Among other advantages, RIP analysis (i) measures RNP associations in many samples relatively quickly, (ii) can be adapted easily to different endogenous RBPs, and (iii) provides extensive information at low cost. Among its limitations, RIP analysis does not inform on the specific sites of interaction of an RBP with a given target RNAs, although recent adaptations of RIP have been developed to overcome this problem. Here we provide an optimized protocol for RIP analysis that can be used to study RNA-protein interactions relevant to many areas of biology.

Approaches for Understanding the Mechanisms of Long Noncoding RNA Regulation of Gene Expression

Mammalian genomes encode tens of thousands of long noncoding RNAs (lncRNAs) that have been implicated in a diverse array of biological processes and human diseases. In recent years, the development of new tools for studying lncRNAs has enabled important progress in defining the mechanisms by which Xist and other lncRNAs function. This collective work provides a framework for how to define the mechanisms by which lncRNAs act. This includes defining lncRNA function, identifying and characterizing lncRNA-protein interactions, and lncRNA localization in the cell. In this review, we discuss various experimental approaches for deciphering lncRNA mechanisms and discuss issues and limitations in interpreting these results. We explore what these data can reveal about lncRNA function and mechanism as well as emerging insights into lncRNA biology that have been derived from these studies.

In-cell identification and measurement of RNA-protein interactions

Regulatory RNAs exert their cellular functions through RNA-binding proteins (RBPs). Identifying RNA-protein interactions is therefore key for a molecular understanding of regulatory RNAs. To date, RNA-bound proteins have been identified primarily through RNA purification followed by mass spectrometry. Here, we develop incPRINT (in cell protein-RNA interaction), a high-throughput method to identify in-cell RNA-protein interactions revealed by quantifiable luminescence. Applying incPRINT to long noncoding RNAs (lncRNAs), we identify RBPs specifically interacting with the lncRNA Firre and three functionally distinct regions of the lncRNA Xist. incPRINT confirms previously known lncRNA-protein interactions and identifies additional interactions that had evaded detection with other approaches. Importantly, the majority of the incPRINT-defined interactions are specific to individual functional regions of the large Xist transcript. Thus, we present an RNA-centric method that enables reliable identification of RNA-region-specific RBPs and is applicable to any RNA of interest.

RNA-interacting proteome can be identified by RNA affinity purification followed by mass spectrometry. Here the authors developed a different RNA-centric technology that combines high-throughput immunoprecipitation of RNA binding proteins and luciferase-based detection of their interaction with the RNA.

lncRNAs: function and mechanism in cartilage development, degeneration, and regeneration

With the increasing incidence of cartilage-related diseases such as osteoarthritis (OA) and intervertebral disc degeneration (IDD), heavier financial and social burdens need to be faced. Unfortunately, there is no satisfactory clinical method to target the pathophysiology of cartilage-related diseases. Many gene expressions, signaling pathways, and biomechanical dysregulations were involved in cartilage development, degeneration, and regeneration. However, the underlying mechanism was not clearly understood. Recently, lots of long non-coding RNAs (lncRNAs) were identified in the biological processes, including cartilage development, degeneration, and regeneration. It is clear that lncRNAs were important in regulating gene expression and maintaining chondrocyte phenotypes and homeostasis. In this review, we summarize the recent researches studying lncRNAs’ expression and function in cartilage development, degeneration, and regeneration and illustrate the potential mechanism of how they act in the pathologic process. With continued efforts, regulating lncRNA expression in the cartilage regeneration may be a promising biological treatment approach.

Proximity labeling to detect RNA-protein interactions in live cells

RNA biology is orchestrated by the dynamic interactions of RNAs and RNA-binding proteins (RBPs). In the present study, we describe a new method of proximity-dependent protein labeling to detect RNA-protein interactions [RNA-bound protein proximity labeling (RBPL)]. We selected the well-studied RNA-binding protein PUF to examine the current proximity labeling enzymes birA* and APEX2. A new version of birA*, BASU, was used to validate that the PUF protein binds its RNA motif. We further optimized the RBPL labeling system using an inducible expression system. The RBPL (λN-BASU) labeling experiments exhibited high signal-to-noise ratios. We subsequently determined that RBPL (λN-BASU) is more suitable than RBPL (λN-APEX2) for the detection of RNA-protein interactions in live cells. Interestingly, our results also reveal that proximity labeling is probably capable of biotinylating proximate nascent peptide.

Recent Advances in Machine Learning Based Prediction of RNA-protein Interactions

The interactions between RNAs and proteins play critical roles in many biological processes. Therefore, characterizing these interactions becomes critical for mechanistic, biomedical, and clinical studies. Many experimental methods can be used to determine RNA-protein interactions in multiple aspects. However, due to the facts that RNA-protein interactions are tissuespecific and condition-specific, as well as these interactions are weak and frequently compete with each other, those experimental techniques can not be made full use of to discover the complete spectrum of RNA-protein interactions. To moderate these issues, continuous efforts have been devoted to developing high quality computational techniques to study the interactions between RNAs and proteins. Many important progresses have been achieved with the application of novel techniques and strategies, such as machine learning techniques. Especially, with the development and application of CLIP techniques, more and more experimental data on RNA-protein interaction under specific biological conditions are available. These CLIP data altogether provide a rich source for developing advanced machine learning predictors. In this review, recent progresses on computational predictors for RNA-protein interaction were summarized in the following aspects: dataset, prediction strategies, and input features. Possible future developments were also discussed at the end of the review.

Endothelial function and dysfunction in the cardiovascular system: the long non-coding road

Present throughout the vasculature, endothelial cells (ECs) are essential for blood vessel function and play a central role in the pathogenesis of diverse cardiovascular diseases. Understanding the intricate molecular determinants governing endothelial function and dysfunction is essential to develop novel clinical breakthroughs and improve knowledge. An increasing body of evidence demonstrates that long non-coding RNAs (lncRNAs) are active regulators of the endothelial transcriptome and function, providing emerging insights into core questions surrounding EC contributions to pathology, and perhaps the emergence of novel therapeutic opportunities. In this review, we discuss this class of non-coding transcripts and their role in endothelial biology during cardiovascular development, homeostasis, and disease, highlighting challenges during discovery and characterization and how these have been overcome to date. We further discuss the translational therapeutic implications and the challenges within the field, highlighting lncRNA that support endothelial phenotypes prevalent in cardiovascular disease.

CLIPick: a sensitive peak caller for expression-based deconvolution of HITS-CLIP signals

High-throughput sequencing of RNAs isolated by crosslinking immunoprecipitation (HITS-CLIP, also called CLIP-Seq) has been used to map global RNA–protein interactions. However, a critical caveat of HITS-CLIP results is that they contain non-linear background noise—different extent of non-specific interactions caused by individual transcript abundance—that has been inconsiderately normalized, resulting in sacrifice of sensitivity. To properly deconvolute RNA–protein interactions, we have implemented CLIPick, a flexible peak calling pipeline for analyzing HITS-CLIP data, which statistically determines the signal-to-noise ratio for each transcript based on the expression-dependent background simulation. Comprising of streamlined Python modules with an easy-to-use standalone graphical user interface, CLIPick robustly identifies significant peaks and quantitatively defines footprint regions within which RNA–protein interactions were occurred. CLIPick outperforms other peak callers in accuracy and sensitivity, selecting the largest number of peaks particularly in lowly expressed transcripts where such marginal signals are hard to discriminate. Specifically, the application of CLIPick to Argonaute (Ago) HITS-CLIP data were sensitive enough to uncover extended features of microRNA target sites, and these sites were experimentally validated. CLIPick enables to resolve critical interactions in a wide spectrum of transcript levels and extends the scope of HITS-CLIP analysis. CLIPick is available at: http://clip.korea.ac.kr/clipick/

CAPRI enables comparison of evolutionarily conserved RNA interacting regions

RNA-protein complexes play essential regulatory roles at nearly all levels of gene expression. Using in vivo crosslinking and RNA capture, we report a comprehensive RNA-protein interactome in a metazoan at four levels of resolution: single amino acids, domains, proteins and multisubunit complexes. We devise CAPRI, a method to map RNA-binding domains (RBDs) by simultaneous identification of RNA interacting crosslinked peptides and peptides adjacent to such crosslinked sites. CAPRI identifies more than 3000 RNA proximal peptides in Drosophila and human proteins with more than 45% of them forming new interaction interfaces. The comparison of orthologous proteins enables the identification of evolutionary conserved RBDs in globular domains and intrinsically disordered regions (IDRs). By comparing the sequences of IDRs through evolution, we classify them based on the type of motif, accumulation of tandem repeats, conservation of amino acid composition and high sequence divergence.

Comprehensive characterisation of RNA-protein interactions requires different levels of resolution. Here, the authors present an integrated mass spectrometry-based approach that allows them to define the Drosophila RNA-protein interactome from the level of multisubunit complexes down to the RNA-binding amino acid.

Serine/Arginine-rich protein family of splicing regulators: New approaches to study splice isoform functions

Serine/arginine-rich (SR) proteins are conserved RNA-binding proteins that play major roles in RNA metabolism. They function as molecular adaptors, facilitate spliceosome assembly and modulate constitutive and alternative splicing of pre-mRNAs. Pre-mRNAs encoding SR proteins and many other proteins involved in stress responses are extensively alternatively spliced in response to diverse stresses. Hence, it is proposed that stress-induced changes in splice isoforms contribute to the adaptation of plants to stress responses. However, functions of most SR genes and their splice isoforms in stress responses are not known. Lack of easy and robust tools hindered the progress in this area. Emerging technologies such as CRISPR/Cas9 will facilitate studies of SR function by enabling the generation of single and multiple knock-out mutants of SR subfamily members. Moreover, CRISPR/Cas13 allows targeted manipulation of splice isoforms from SR and other genes in a constitutive or tissue-specific manner to evaluate functions of individual splice variants. Identification of the in vivo targets of SR proteins and their splice variants using the recently developed TRIBE (Targets of RNA-binding proteins Identified By Editing) and other methods will help unravel their mode of action and splicing regulatory elements under various conditions. These new approaches are expected to provide significant new insights into the roles of SRs and splice isoforms in plants adaptation to diverse stresses.

Understanding the Contributions of Conformational Changes, Thermodynamics, and Kinetics of RNA-Small Molecule Interactions

The implication of RNA in multiple cellular processes beyond protein coding has revitalized interest in the development of small molecules for therapeutically targeting RNA and for further probing its cellular biology. However, the process of rationally designing such small molecule probes is hampered by the paucity of information about fundamental molecular recognition principles of RNA. In this Review, we summarize two important and often underappreciated aspects of RNA-small molecule recognition: RNA conformational dynamics and the biophysical properties of interactions of small molecules with RNA, specifically thermodynamics and kinetics. While conformational flexibility is often said to impede RNA ligand development, the ability of small molecules to influence the RNA conformational landscape can have a significant effect on the cellular functions of RNA. An analysis of the conformational landscape of RNA and the interactions of individual conformations with ligands can thus guide the development of new small molecule probes, which needs to be investigated further. Additionally, while it is common practice to quantify the binding affinities ( K_a or K_d) of small molecules for biomacromolecules as a measure of their activity, further biophysical characterization of their interaction can provide a deeper understanding. Studies that focus on the thermodynamic and kinetic parameters for interaction between RNA and ligands are next discussed. Finally, this Review provides the reader with a perspective on how such in-depth analysis of biophysical characteristics of the interaction of RNA and small molecules can impact our understanding of these interactions and how they will benefit the future design of small molecule probes.

Post-transcriptional regulatory patterns revealed by protein-RNA interactions

The coordination of the synthesis of functionally-related proteins can be achieved at the post-transcriptional level by the action of common regulatory molecules, such as RNA–binding proteins (RBPs). Despite advances in the genome-wide identification of RBPs and their binding transcripts, the protein–RNA interaction space is still largely unexplored, thus hindering a broader understanding of the extent of the post-transcriptional regulation of related coding RNAs. Here, we propose a computational approach that combines protein–mRNA interaction networks and statistical analyses to provide an inferred regulatory landscape for more than 800 human RBPs and identify the cellular processes that can be regulated at the post-transcriptional level. We show that 10% of the tested sets of functionally-related mRNAs can be post-transcriptionally regulated. Moreover, we propose a classification of (i) the RBPs and (ii) the functionally-related mRNAs, based on their distinct behaviors in the functional landscape, hinting towards mechanistic regulatory hypotheses. In addition, we demonstrate the usefulness of the inferred functional landscape to investigate the cellular role of both well-characterized and novel RBPs in the context of human diseases.

Profiling of rotavirus 3'UTR-binding proteins reveals the ATP synthase subunit ATP5B as a host factor that supports late-stage virus replication

Genome replication and virion assembly of segmented RNA viruses are highly coordinated events, tightly regulated by sequence and structural elements in the UTRs of viral RNA. This process is poorly defined and likely requires the participation of host proteins in concert with viral proteins. In this study, we employed a proteomics-based approach, named RNA-protein interaction detection (RaPID), to comprehensively screen for host proteins that bind to a conserved motif within the rotavirus (RV) 3' terminus. Using this assay, we identified ATP5B, a core subunit of the mitochondrial ATP synthase, as having high affinity to the RV 3'UTR consensus sequences. During RV infection, ATP5B bound to the RV 3'UTR and co-localized with viral RNA and viroplasm. Functionally, siRNA-mediated genetic depletion of ATP5B or other ATP synthase subunits such as ATP5A1 and ATP5O reduced the production of infectious viral progeny without significant alteration of intracellular viral RNA levels or RNA translation. Chemical inhibition of ATP synthase diminished RV yield in both conventional cell culture and in human intestinal enteroids, indicating that ATP5B positively regulates late-stage RV maturation in primary intestinal epithelial cells. Collectively, our results shed light on the role of host proteins in RV genome assembly and particle formation and identify ATP5B as a novel pro-RV RNA-binding protein, contributing to our understanding of how host ATP synthases may galvanize virus growth and pathogenesis.

RNA Structure and Cellular Applications of Fluorescent Light-Up Aptamers

The cellular functions of RNA are not limited to their role as blueprints for protein synthesis. In particular, noncoding RNA, such as, snRNAs, lncRNAs, miRNAs, play important roles. With increasing numbers of RNAs being identified, it is well known that the transcriptome outnumbers the proteome by far. This emphasizes the great importance of functional RNA characterization and the need to further develop tools for these investigations, many of which are still in their infancy. Fluorescent light-up aptamers (FLAPs) are RNA sequences that can bind nontoxic, cell-permeable small-molecule fluorogens and enhance their fluorescence over many orders of magnitude upon binding. FLAPs can be encoded on the DNA level using standard molecular biology tools and are subsequently transcribed into RNA by the cellular machinery, so that they can be used as fluorescent RNA tags (FLAP-tags). In this Minireview, we give a brief overview of the fluorogens that have been developed and their binding RNA aptamers, with a special focus on published crystal structures. A summary of current and future cellular FLAP applications with an emphasis on the study of RNA-RNA and RNA-protein interactions using split-FLAP and Förster resonance energy transfer (FRET) systems is given.

Large Noncoding RNAs in Bacteria

Bacterial noncoding RNA (ncRNA) classes longer than 200 nucleotides are rare but are responsible for performing some of the most fundamental tasks in living cells. RNAs such as 16S and 23S rRNA, group I and group II introns, RNase P ribozymes, transfer-messenger RNAs, and coenzyme B₁₂ riboswitches are diverse in structure and accomplish biochemical functions that rival the activities of proteins. Over the last decade, a number of new classes of large ncRNAs have been uncovered in bacteria. A total of 21 classes with no established functions have been identified through the use of bioinformatics search strategies. Based on precedents for bacterial large ncRNAs performing sophisticated functions, it seems likely that some of these structured ncRNAs also will prove to carry out complex functions. Thus, determining their roles will provide a better understanding of fundamental biological processes. A few studies have produced data that provide clues to the purposes of some of these recently found classes, but the true functions of most classes remain mysterious.

Functional Classification and Experimental Dissection of Long Noncoding RNAs

Over the last decade, it has been increasingly demonstrated that the genomes of many species are pervasively transcribed, resulting in the production of numerous long noncoding RNAs (lncRNAs). At the same time, it is now appreciated that many types of DNA regulatory elements, such as enhancers and promoters, regularly initiate bi-directional transcription. Thus, discerning functional noncoding transcripts from a vast transcriptome is a paramount priority, and challenge, for the lncRNA field. In this review, we aim to provide a conceptual and experimental framework for classifying and elucidating lncRNA function. We categorize lncRNA loci into those that regulate gene expression in cis versus those that perform functions in trans and propose an experimental approach to dissect lncRNA activity based on these classifications. These strategies to further understand lncRNAs promise to reveal new and unanticipated biology with great potential to advance our understanding of normal physiology and disease.

Diverging RNPs: Toward Understanding lncRNA-Protein Interactions and Functions

RNA-protein interactions are essential to a variety of biological processes. The realization that mammalian genomes are pervasively transcribed brought a tidal wave of tens of thousands of newly identified long noncoding RNAs (lncRNAs) and raised questions about their purpose in cells. The vast majority of lncRNAs have yet to be studied, and it remains to be determined to how many of these transcripts a function can be ascribed. However, results gleaned from studying a handful of these macromolecules have started to reveal common themes of biological function and mechanism of action involving intricate RNA-protein interactions. Some lncRNAs were shown to regulate the chromatin and transcription of distant and neighboring genes in the nucleus, while others regulate the translation or localization of proteins in the cytoplasm. Some lncRNAs were found to be crucial during development, while mutations and aberrant expression of others have been associated with several types of cancer and a plethora of diseases. Over the last few years, the establishment of new technologies has been key in providing the tools to decode the rules governing lncRNA-protein interactions and functions. This chapter will highlight the general characteristics of lncRNAs, their function, and their mode of action, with a special focus on protein interactions. It will also describe the methods at the disposition of scientists to help them cross this next frontier in our understanding of lncRNA biology.

RNA Structural Differentiation: Opportunities with Pattern Recognition

Our awareness and appreciation of the many regulatory roles of RNA have dramatically increased in the past decade. This understanding, in addition to the impact of RNA in many disease states, has renewed interest in developing selective RNA-targeted small molecule probes. However, the fundamental guiding principles in RNA molecular recognition that could accelerate these efforts remain elusive. While high-resolution structural characterization can provide invaluable insight, examples of well-characterized RNA structures, not to mention small molecule:RNA complexes, remain limited. This Perspective provides an overview of the current techniques used to understand RNA molecular recognition when high-resolution structural information is unavailable. We will place particular emphasis on a new method, pattern recognition of RNA with small molecules (PRRSM), that provides rapid insight into critical components of RNA recognition and differentiation by small molecules as well as into RNA structural features.