Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP

The role of MiRNA-34 family in different signaling pathways and its therapeutic options

MiRNAs are short non-coding RNA molecules that have been shown to affect a vast number of genes at the post-transcriptional level, hence regulating several signaling pathways. Because the miRNA-34 family regulates a number of different signaling pathways, including those linked to cancer, the immune system, metabolism, cellular structure, and neurological disorders, it has garnered a great deal of attention from researchers. Members of the miRNA-34 family have been shown to inhibit tumors in a variety of cancer types. This family is also important for obesity, the cardiovascular system, and glycolysis. It's interesting to note that the miRNA-34 family is known to play a role in major depressive disorder, schizophrenia, Parkinson's disease (PD), adverse childhood experiences or trauma, regulation of stress responses, Alzheimer's disease (AD), and stress-related psychatric conditions. In this review, the expected targets of the miRNA-34 family are presented alongside the well-established targets identified by pathway analysis. Furthermore, the therapeutic potential of this miRNA family will be discussed.

Mature microRNA-binding protein QKI suppresses extracellular microRNA let-7b release

Argonaute (AGO), a component of RNA-induced silencing complexes (RISCs), is a representative RNA-binding protein (RBP) known to bind with mature microRNAs (miRNAs) and is directly involved in post-transcriptional gene silencing. However, despite the biological significance of miRNAs, the roles of other miRNA-binding proteins (miRBPs) remain unclear in the regulation of miRNA loading, dissociation from RISCs and extracellular release. In this study, we performed protein arrays to profile miRBPs and identify 118 RBPs that directly bind to miRNAs. Among those proteins, the RBP quaking (QKI) inhibits extracellular release of the mature microRNA let-7b by controlling the loading of let-7b into extracellular vesicles via additional miRBPs such as AUF1 (also known as hnRNPD) and hnRNPK. The enhanced extracellular release of let-7b after QKI depletion activates Toll-like receptor 7 (TLR7) and promotes the production of proinflammatory cytokines in recipient cells, leading to brain inflammation in the mouse cortex. Thus, this study reveals the contribution of QKI to the inhibition of brain inflammation via regulation of extracellular let-7b release.

IGF2BP3/NCBP1 complex inhibits renal tubular senescence through regulation of CDK6 mRNA stability

Renal aging and the subsequent rise in kidney-related diseases are attributed to senescence in renal tubular epithelial cells (RTECs). Our study revealed that the abnormal expression of insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3), a reader of RNA N6-methyladenosine, is critically involved in cisplatin-induced renal tubular senescence. In cisplatin-induced senescence of RTECs, the promoter activity and transcription of IGF2BP3 is markedly suppressed. It was due to the down regulation of MYC proto-oncogene (MYC), which regulates IGF2BP3 transcription by binding to the putative site at 1852-1863 of the IGF2BP3 promoter. Overexpression of IGF2BP3 ameliorated cisplatin-induced renal tubular senescence in vitro. Mechanistic studies revealed that IGF2BP3 inhibits cellular senescence in RTECs by enhancing cyclin-dependent kinase 6 (CDK6) mRNA stability and increasing its expression. The inhibition effect of IGF2BP3 on tubular senescence is partially reversed by the knockdown of CDK6. Further, IGF2BP3 recruits nuclear cap binding protein subunit 1 (NCBP1) and inhibits CDK6 mRNA decay, by recognizing m6A modification. Specifically, IGF2BP3 recognizes m6A motif "GGACU" at nucleotides 110-114 in the 5' untranslated region (UTR) field of CDK6 mRNA. The involvement of IGF2BP3/CDK6 in alleviating tubular senescence was confirmed in a cisplatin-induced acute kidney injury (AKI)-to-chronic kidney disease (CKD) model. Clinical data also suggests an age-related decrease in IGF2BP3 and CDK6 levels in renal tissue or serum samples from patients. These findings suggest that IGF2BP3/CDK6 may be a promising target in cisplatin-induced tubular senescence and renal failure.

Systematic analysis of the target recognition and repression by the Pumilio proteins

RNA binding proteins orchestrate the post-transcriptional fate of RNA molecules, but the principles of their action remain poorly understood. Pumilio (PUM) proteins bind 3' UTRs of mRNAs and lead to mRNA decay. To comprehensively map the determinants of recognition of sequences by PUM proteins in cells and to study the binding outcomes, we developed a massively parallel RNA assay that profiled thousands of PUM-binding sites in cells undergoing various perturbations or RNA immunoprecipitation. By studying fragments from the NORAD long non-coding RNA, we find two features that antagonize repression by PUM proteins - G/C rich sequences, particularly those upstream of the PUM recognition element, and binding of FAM120A, which limits the repression elicited by PUM-binding sites. We also find that arrays of PUM sites separated by 8-12 bases offer particularly strong repression and use them to develop a particularly sensitive reporter for PUM repression. In contrast, PUM sites separated by shorter linkers, such as some of those found in NORAD, exhibit strong activity interdependence, likely mediated by competition between PUM binding and formation of strong secondary structures. Overall, our findings expand our understanding of the determinants of PUM protein activity in human cells.

IGF2BP1 phosphorylation in the disordered linkers regulates ribonucleoprotein condensate formation and RNA metabolism

The insulin-like growth factor 2 mRNA binding protein 1 (IGF2BP1) is a conserved RNA-binding protein that regulates RNA stability, localization and translation. IGF2BP1 is part of various ribonucleoprotein (RNP) condensates. However, the mechanism that regulates its assembly into condensates remains unknown. By using proteomics, we demonstrate that phosphorylation of IGF2BP1 at S181 in a disordered linker is regulated in a stress-dependent manner. Phosphomimetic mutations in two disordered linkers, S181E and Y396E, modulate RNP condensate formation by IGF2BP1 without impacting its binding affinity for RNA. Intriguingly, the S181E mutant, which lies in linker 1, impairs IGF2BP1 condensate formation in vitro and in cells, whereas a Y396E mutant in the second linker increases condensate size and dynamics. Structural approaches show that the first linker binds RNAs nonspecifically through its RGG/RG motif, an interaction weakened in the S181E mutant. Notably, linker 2 interacts with IGF2BP1's folded domains and these interactions are partially impaired in the Y396E mutant. Importantly, the phosphomimetic mutants impact IGF2BP1's interaction with RNAs and remodel the transcriptome in cells. Our data reveal how phosphorylation modulates low-affinity interaction networks in disordered linkers to regulate RNP condensate formation and RNA metabolism.

RNA binding protein ZCCHC24 promotes tumorigenicity in triple-negative breast cancer

Triple-negative breast cancer (TNBC) lacks the expression of hormone and HER2 receptors and is highly malignant with no effective therapeutic targets. In TNBC, the cancer stem-like cell (CSC) population is considered to be the main cause of resistance to treatment. Thus, the therapeutic targeting of this population could substantially improve patient survival. Here, we identify the RNA-binding protein ZCCHC24 as enriched in the mesenchymal-like TNBC population. ZCCHC24 promotes the expression of a set of genes related to tumorigenicity and treatment resistance by directly binding to the cis-element "UGUWHWWA" in their mRNAs, thereby stabilizing them. One of the ZCCHC24 targets, ZEB1, is a transcription factor that promotes the expression of cancer stemness genes and reciprocally induces ZCCHC24 expression. ZCCHC24 knockdown by siRNAs shows a therapeutic effect and reduces the mesenchymal-like cell population in TNBC patient-derived xenografts. ZCCHC24 knockdown also has additive effects with the BET inhibitor JQ1 in suppressing tumor growth in TNBC patient-derived xenografts.

RNA infrastructure profiling illuminates transcriptome structure in crowded spaces

RNAs fold into compact structures and undergo protein interactions in cells. These occluded environments can block reagents that probe the underlying RNAs. Probes that can analyze structure in crowded settings can shed light on RNA biology. Here, we employ 2'-OH-reactive probes that are small enough to access folded RNA structure underlying close molecular contacts within cells, providing considerably broader coverage for intracellular RNA structural analysis. The data are analyzed first with well-characterized human ribosomal RNAs and then applied transcriptome-wide to polyadenylated transcripts. The smallest probe acetylimidazole (AcIm) yields 80% greater structural coverage than larger conventional reagent NAIN3, providing enhanced structural information in hundreds of transcripts. The acetyl probe also provides superior signals for identifying m6A modification sites in transcripts, particularly in sites that are inaccessible to a standard probe. Our strategy enables profiling RNA infrastructure, enhancing analysis of transcriptome structure, modification, and intracellular interactions, especially in spatially crowded settings.

miR-191-5p suppresses PRRSV replication by targeting porcine EGFR to enhance interferon signaling

Porcine reproductive and respiratory syndrome virus (PRRSV) is a major thread to the global swine industry, lack of effective control strategies. This study explores the regulatory role of a small non-coding RNA, miR-191-5p, in PRRSV infection. We observed that miR-191-5p significantly inhibits PRRSV in porcine alveolar macrophages (PAMs), contrasting with negligible effects in MARC-145 and HEK293-CD163 cells, suggesting a cell-specific antiviral effect. Further investigation unveiled that miR-191-5p directly targets the porcine epidermal growth factor receptor (EGFR), whose overexpression or EGF-induced activation suppresses type I interferon (IFN-I) signaling, promoting PRRSV replication. In contrast, siRNA-or miR-191-5p-induced EGFR downregulation or EGFR inhibitor boosts IFN-I signaling, reducing viral replication. Notably, this miRNA alleviates the suppressive effect of EGF on IFN-I signaling, underscoring its regulatory function. Further investigation revealed interconnections among miR-191-5p, EGFR and signal transducer and activator of transcription 3 (STAT3). Modulation of STAT3 activity influenced IFN-I signaling and PRRSV replication, with STAT3 knockdown countering EGFR activation-induced virus replication. Combination inhibition of STAT3 and miR-191-5p suggests that STAT3 acts downstream in EGFR's antiviral response. Furthermore, miR-191-5p's broad efficacy in restricting various PRRSV strains in PAMs was identified. Collectively, these findings elucidate a novel mechanism of miR-191-5p in activating host IFN-I signaling to inhibit PRRSV replication, highlighting its potential in therapeutic applications against PRRSV.

SMARCD1 is an essential expression-restricted metastasis modifier

Breast cancer is the most frequently diagnosed cancer worldwide, constituting 15% of cases in 2023. The predominant cause of breast cancer-related mortality is metastasis, and a lack of metastasis-targeted therapies perpetuates dismal outcomes for late-stage patients. By using meiotic genetics to study inherited transcriptional network regulation, we have identified, to the best of our knowledge, a new class of "essential expression-restricted" genes as potential candidates for metastasis-targeted therapeutics. Building upon previous work implicating the CCR4-NOT RNA deadenylase complex in metastasis, we demonstrate that RNA-binding proteins NANOS1, PUM2, and CPSF4 also regulate metastatic potential. Using various models and clinical data, we pinpoint Smarcd1 mRNA as a target of all three RNA-BPs. Strikingly, both high and low expression of Smarcd1 correlate with positive clinical outcomes, while intermediate expression significantly reduces the probability of survival. Applying the theory of "essential genes" from evolution, we identify 50 additional genes that require precise expression levels for metastasis to occur. Specifically, small perturbations in Smarcd1 expression significantly reduce metastasis in mouse models and alter splicing programs relevant to the ER+/HER2-enriched breast cancer. Identification subtype-specific essential expression-restricted metastasis modifiers introduces a novel class of genes that, when therapeutically "nudged" in either direction, may significantly improve late-stage breast cancer patients.

An ancient competition for the conserved branchpoint sequence influences physiological and evolutionary outcomes in splicing

Recognition of the intron branchpoint during spliceosome assembly is a multistep process that defines both mRNA structure and amount. A branchpoint sequence motif UACUAAC is variably conserved in eukaryotic genomes, but in some organisms more than one protein can recognize it. Here we show that SF1 and Quaking (QKI) compete for a subset of intron branchpoints with the sequence ACUAA. SF1 activates exon inclusion through this sequence, but QKI represses the inclusion of alternatively spliced exons with this intron branchpoint sequence. Using mutant reporters derived from a natural intron with two branchpoint-like sequences, we find that when either branchpoint sequence is mutated, the other is used as a branchpoint, but when both are present, neither is used due to high affinity binding and strong splicing repression by QKI. QKI occupancy at the dual branchpoint site directly prevents SF1 binding and subsequent recruitment of spliceosome-associated factors. Finally, the ectopic expression of QKI in budding yeast (which lacks QKI) is lethal, due at least in part to widespread splicing repression. In conclusion, QKI can function as a splicing repressor by directly competing with SF1/BBP for a subset of branchpoint sequences that closely mirror its high affinity binding site. This suggests that QKI and degenerate branchpoint sequences may have co-evolved as a means through which specific gene expression patterns could be maintained in QKI-expressing or non-expressing cells in metazoans, plants, and animals.

Exploring the expanding universe of host-virus interactions mediated by viral RNA

RNA is a central molecule in RNA virus biology; however, the interactions that it establishes with the host cell are only starting to be elucidated. In recent years, a methodology revolution has dramatically expanded the scope of host-virus interactions involving the viral RNA (vRNA). A second wave of method development has enabled the precise study of these protein-vRNA interactions in a life cycle stage-dependent manner, as well as providing insights into the interactome of specific vRNA species. This review discusses these technical advances and describes the new regulatory mechanisms that have been identified through their use. Among these, we discuss the importance of vRNA in regulating protein function through a process known as riboregulation. We envision that the elucidation of vRNA interactomes will open new avenues of research, including pathways to the discovery of host factors with therapeutic potential against viruses.

MicroRNA let-7a regulation of Hantaan virus replication by Targeting FAS Signaling Pathways

Hantaan virus (HTNV) infection in humans can cause hemorrhagic fever and renal syndrome (HFRS). Understanding host responses to HTNV infection is crucial for developing effective disease intervention strategies. Previous RNA-sequencing studies have investigated the role of microRNAs (miRNAs) in the post-transcriptional regulation of host genes in response to HTNV infection. In this study, we demonstrated that HTNV infection induces let-7a expression in human umbilical vein endothelial cells (HUVEC) and that HTNV G protein upregulates the expression of let-7a. miRNA let-7a mimics and inhibitors validated the predicted targets, including cell apoptosis genes (FAS, caspase-8, and caspase-3) and inflammatory factors (IL-6 and its related factors). Modulation of miRNA let-7a levels by miRNA mimics and inhibitors affected HTNV replication, indicating that HTNV modulates host miRNA expression to affect the outcome of the antiviral host response.

Nuclear PKM2 binds pre-mRNA at folded G-quadruplexes and reveals their gene regulatory role

Nuclear localization of the metabolic enzyme PKM2 is widely observed in various cancer types. We identify nuclear PKM2 as a non-canonical RNA-binding protein (RBP) that specifically interacts with folded RNA G-quadruplex (rG4) structures in precursor mRNAs (pre-mRNAs). PKM2 occupancy at rG4s prevents the binding of repressive RBPs, such as HNRNPF, and promotes the expression of rG4-containing pre-mRNAs (the "rG4ome"). We observe an upregulation of the rG4ome during epithelial-to-mesenchymal transition and a negative correlation of rG4 abundance with patient survival in different cancer types. By preventing the nuclear accumulation of PKM2, we could repress the rG4ome in triple-negative breast cancer cells and reduce migration and invasion of cancer cells in vitro and in xenograft mouse models. Our data suggest that the balance of folded and unfolded rG4s controlled by RBPs impacts gene expression during tumor progression.

A protocol for time-resolved transcriptomics through metabolic labeling and combinatorial indexing

The snapshot nature of single-cell transcriptomics presents a challenge for studying the dynamics of gene expression. Metabolic labeling, where nascent RNA is labeled with 4-thiouridine (4sU), captures temporal information at the single-cell level, providing greater insight into expression dynamics. Here, we present an optimized, automation-friendly protocol for the metabolic labeling of RNA alongside single-cell RNA sequencing through combinatorial indexing. We describe steps for 4sU labeling, cell fixation and chemical treatment, and automated two-level combinatorial indexing. For complete details on the use and execution of this protocol, please refer to Maizels et al.1.

RNA-binding protein PTENα blocks RIG-I activation to prevent viral inflammation

A timely inflammatory response is crucial for early viral defense, but uncontrolled inflammation harms the host. Retinoic acid-inducible gene I (RIG-I) has a pivotal role in detecting RNA viruses, yet the regulatory mechanisms governing its sensitivity remain elusive. Here we identify PTENα, an N-terminally extended form of PTEN, as an RNA-binding protein with a preference for the CAUC(G/U)UCAU motif. Using both in vivo and in vitro viral infection assays, we demonstrated that PTENα restricted the host innate immune response, relying on its RNA-binding capacity and phosphatase activity. Mechanistically, PTENα directly bound to viral RNA and enzymatically converted its 5'-triphosphate to 5'-monophosphate, thereby reducing RIG-I sensitivity. Physiologically, brain-intrinsic PTENα exerted protective effects against viral inflammation, while peripheral PTENα restricted host antiviral immunity and, to some extent, promoted viral replication. Collectively, our findings underscore the significance of PTENα in modulating viral RNA- and RIG-I-mediated immune recognition, offering potential therapeutic implications for infectious diseases.

Oligonucleotide-Based Photoaffinity Probes: Chemical Tools and Applications for Protein Labeling

A variety of proteins interact with DNA and RNA, including polymerases, histones, ribosomes, transcription factors, and repair enzymes. However, the transient non-covalent nature of these interactions poses challenges for analysis. Introducing a covalent bond between proteins and DNA via photochemical activation of a photosensitive functional group introduced onto nucleic acids offers a means to stabilize these often weak interactions without significantly altering the binding interface. Consequently, photoactivatable oligonucleotides are powerful tools for investigating nucleic acid-protein interactions involved in numerous biological and pathological processes. In this review, we provide a comprehensive overview of the chemical tools developed so far and the different strategies used for incorporating the most commonly used photoreactive reagents into oligonucleotide probes or nucleic acids. Furthermore, we illustrate their application with several examples including protein binding site mapping, identification of protein binding partners, and in cell studies.

RNAelem: an algorithm for discovering sequence-structure motifs in RNA bound by RNA-binding proteins

Motivation

RNA-binding proteins (RBPs) play a crucial role in the post-transcriptional regulation of RNA. Given their importance, analyzing the specific RNA patterns recognized by RBPs has become a significant research focus in bioinformatics. Deep Neural Networks have enhanced the accuracy of prediction for RBP-binding sites, yet understanding the structural basis of RBP-binding specificity from these models is challenging due to their limited interpretability. To address this, we developed RNAelem, which combines profile context-free grammar and the Turner energy model for RNA secondary structure to predict sequence-structure motifs in RBP-binding regions.

Results

RNAelem exhibited superior detection accuracy compared to existing tools for RNA sequences with structural motifs. Upon applying RNAelem to the eCLIP database, we were not only able to reproduce many known primary sequence motifs in the absence of secondary structures, but also discovered many secondary structural motifs that contained sequence-nonspecific insertion regions. Furthermore, the high interpretability of RNAelem yielded insightful findings such as long-range base-pairing interactions in the binding region of the U2AF protein.

Availability and implementation

The code is available at https://github.com/iyak/RNAelem.

A new perspective on microRNA-guided gene regulation specificity, and its potential generalization to transcription factors and RNA-binding proteins

Our conception of gene regulation specificity has undergone profound changes over the last 20 years. Previously, regulators were considered to control few genes, recognized with exquisite specificity by a 'lock and key' mechanism. However, recently genome-wide exploration of regulator binding site occupancy (whether on DNA or RNA targets) revealed extensive lists of molecular targets for every studied regulator. Such poor biochemical specificity suggested that each regulator controls many genes, collectively contributing to biological phenotypes. Here, I propose a third model, whereby regulators' biological specificity is only partially due to 'lock and key' biochemistry. Rather, regulators affect many genes at the microscopic scale, but biological consequences for most interactions are attenuated at the mesoscopic scale: only a few regulatory events propagate from microscopic to macroscopic scale; others are made inconsequential by homeostatic mechanisms. This model is well supported by the microRNA literature, and data suggest that it extends to other regulators. It reconciles contradicting observations from biochemistry and comparative genomics on one hand and in vivo genetics on the other hand, but this conceptual unification is obscured by common misconceptions and counter-intuitive modes of graphical display. Profound understanding of gene regulation requires conceptual clarification, and better suited statistical analyses and graphical representation.

eIF3 engages with 3'-UTR termini of highly translated mRNAs

Stem cell differentiation involves a global increase in protein synthesis to meet the demands of specialized cell types. However, the molecular mechanisms underlying this translational burst and the involvement of initiation factors remains largely unknown. Here, we investigate the role of eukaryotic initiation factor 3 (eIF3) in early differentiation of human pluripotent stem cell (hPSC)-derived neural progenitor cells (NPCs). Using Quick-irCLIP and alternative polyadenylation (APA) Seq, we show eIF3 crosslinks predominantly with 3' untranslated region (3'-UTR) termini of multiple mRNA isoforms, adjacent to the poly(A) tail. Furthermore, we find that eIF3 engagement at 3'-UTR ends is dependent on polyadenylation. High eIF3 crosslinking at 3'-UTR termini of mRNAs correlates with high translational activity, as determined by ribosome profiling. The results presented here show that eIF3 engages with 3'-UTR termini of highly translated mRNAs, likely reflecting a general rather than specific regulatory function of eIF3, and supporting a role of mRNA circularization in the mechanisms governing mRNA translation.

PAR-dCLIP: Enabling detection of RNA binding protein target transcripts bound at 5' termini through the incorporation of a decapping step

RNA binding proteins (RBPs) are responsible for facilitating a wealth of post-transcriptional gene regulatory functions. The role of an RBP on regulated transcripts can be investigated through a pull-down of the RBP and high-throughput sequencing (HTS) of the associated transcripts. Photoactivatable Ribonucleoside-Enhanced Crosslinking and Immunoprecipitation (PAR-CLIP), is one such pull-down method that isolates, detects, and sequences the cDNA of RBP-associated transcripts. PAR-CLIP relies on a photoactivatable ribonucleoside analogue, 4-thiouridine, to facilitate covalent RNA-protein crosslinks at 365 nm. These crosslinks permit stringent wash conditions and result in T to C mismatch incorporations during reverse transcription, a unique parameter for the computational analysis of high-confidence binding sites. However, until now, RBPs that bind at the 5'-termini of RNAs have been uniquely restricted from the full potential bandwidth of autoradiographic detection and HTS library preparation. The 5'-termini of RNAs are highly modified, including the most common Pol-II derived modification: the 7-methylguanosine (m7G) cap. In the conventional PAR-CLIP protocol, cap-binding proteins protect the m7G cap from the RNase treatment that generates the necessary substrate for autoradiographic detection and 5' adapter ligation-thus occluding entire populations of RNA from visualization and HTS. Here, we introduce decapping-PAR-CLIP or PAR-dCLIP. We incorporate a decapping step into the PAR-CLIP protocol to generate the necessary substrate to sequence m7G capped transcripts. While PAR-dCLIP was originally targeted towards known m7G-cap binding proteins, we argue that all RBP inquiries, and particularly those suspected to regulate translation, should incorporate this decapping step to ensure that all possible populations of bound transcripts are identified.

Genome-Wide Mapping of RNA-Protein Associations via Sequencing

RNA-protein interactions are crucial for regulating gene expression and cellular functions, with their dysregulation potentially impacting disease progression. Systematically mapping these interactions is resource-intensive due to the vast number of potential RNA and protein interactions. Here, we introduce PRIM-seq (Protein-RNA Interaction Mapping by sequencing), a method for the concurrent de novo identification of RNA-binding proteins (RBPs) and the elucidation of their associated RNAs. PRIM-seq works by converting each RNA-protein pair into a unique chimeric DNA sequence, which is then decoded through DNA sequencing. Applied to two human cell types, PRIM-seq generated a comprehensive human RNA-protein association network (HuRPA), consisting of more than 350,000 RNA-proteins pairs involving approximately 7,000 RNAs and 11,000 proteins. The data revealed an enrichment of previously reported RBPs and RNA-protein interactions within HuRPA. We also identified LINC00339 as a protein-associating non-coding RNA and PHGDH as an RNA-associating protein. Notably, PHGDH interacts with BECN1 and ATF4 mRNAs, suppressing their protein expression and consequently inhibiting autophagy, apoptosis, and neurite outgrowth while promoting cell proliferation. PRIM-seq offers a powerful tool for discovering RBPs and RNA-protein associations, contributing to more comprehensive functional genome annotations.

CRISPR-based dissection of miRNA binding sites using isogenic cell lines is hampered by pervasive noise

Non-coding regulatory sequences play essential roles in adjusting gene output to cellular needs and are thus critical to animal development and health. Numerous such sequences have been identified in mammalian genomes ranging from transcription factors binding motifs to recognition sites for RNA-binding proteins and non-coding RNAs. The advent of CRISPR has raised the possibility of assigning functionality to individual endogenous regulatory sites by facilitating the generation of isogenic cell lines that differ by a defined set of genetic modifications. Here we investigate the usefulness of this approach to assign function to individual miRNA binding sites. We find that the process of generating isogenic pairs of mammalian cell lines with CRISPR-mediated mutations introduces extensive molecular and phenotypic variability between biological replicates making any attempt of assigning function to the binding site essentially impossible. Our work highlights an important consideration when employing CRISPR editing to characterize non-coding regulatory sequences in cell lines and calls for the development and adoption of alternative strategies to address this question in the future.

Exportin-5 binding precedes 5'- and 3'-end processing of tRNA precursors in Drosophila

Exportin5 (Exp5) is the major miRNA nuclear export factor and recognizes structural features of pre-miRNA hairpins, while it also exports other minihelix-containing RNAs. In Drosophila, Exp5 is suggested to play a major role in tRNA export because the gene encoding the canonical tRNA export factor Exportin-t is missing in its genome. To understand molecular functions of fly Exp5, we studied the Exp5/RNA interactome in the cell line S2R + using the crosslinking and immunoprecipitation (CLIP) technology. The CLIP experiment captured known substrates such as tRNAs and miRNAs and detected candidates of novel Exp5 substrates including various mRNAs and long non-coding RNAs (lncRNAs). Some mRNAs and lncRNAs enriched PAR-CLIP tags compared to their expression levels, suggesting selective binding of Exp5 to them. Intronless mRNAs tended to enrich PAR-CLIP tags; therefore, we proposed that Exp5 might play a role in the export of specific classes of mRNAs/lncRNAs. This result suggested that Drosophila Exp5 might have a wider variety of substrates than initially thought. Surprisingly, Exp5 CLIP reads often contained sequences corresponding to the flanking 5'-leaders and 3'-trailers of tRNAs, which were thought to be removed prior to nuclear export. In fact, we found pre-tRNAs before end-processing were present in the cytoplasm, supporting the idea that tRNA end-processing is a cytoplasmic event. In summary, our results provide a genome-wide list of Exp5 substrate candidates and suggest that flies may lack a mechanism to distinguish pre-tRNAs with or without the flanking sequences.

Human cells contain myriad excised linear intron RNAs with links to gene regulation and potential utility as biomarkers

A previous study using Thermostable Group II Intron Reverse Transcriptase sequencing (TGIRT-seq) found human plasma contains short (≤300 nt) structured full-length excised linear intron (FLEXI) RNAs with potential to serve as blood-based biomarkers. Here, TGIRT-seq identified >9,000 different FLEXI RNAs in human cell lines, including relatively abundant FLEXIs with cell-type-specific expression patterns. Analysis of public CLIP-seq datasets identified 126 RNA-binding proteins (RBPs) that have binding sites within the region corresponding to the FLEXI or overlapping FLEXI splice sites in pre-mRNAs, including 53 RBPs with binding sites for ≥30 different FLEXIs. These included splicing factors, transcription factors, a chromatin remodeling protein, cellular growth regulators, and proteins with cytoplasmic functions. Analysis of ENCODE datasets identified subsets of these RBPs whose knockdown impacted FLEXI host gene mRNA levels or proximate alternative splicing, indicating functional interactions. Hierarchical clustering identified six subsets of RBPs whose FLEXI binding sites were co-enriched in six subsets of functionally related host genes: AGO1-4 and DICER, including but not limited to agotrons or mirtron pre-miRNAs; DKC1, NOLC1, SMNDC1, and AATF (Apoptosis Antagonizing Transcription Factor), including but not limited to snoRNA-encoding FLEXIs; two subsets of alternative splicing factors; and two subsets that included RBPs with cytoplasmic functions (e.g., LARP4, PABPC4, METAP2, and ZNF622) together with regulatory proteins. Cell fractionation experiments showed cytoplasmic enrichment of FLEXI RNAs with binding sites for RBPs with cytoplasmic functions. The subsets of host genes encoding FLEXIs with binding sites for different subsets of RBPs were co-enriched with non-FLEXI other short and long introns with binding sites for the same RBPs, suggesting overarching mechanisms for coordinately regulating expression of functionally related genes. Our findings identify FLEXIs as a previously unrecognized large class of cellular RNAs and provide a comprehensive roadmap for further analyzing their biological functions and the relationship of their RBPs to cellular regulatory mechanisms.

Immune modulatory microRNAs in tumors, their clinical relevance in diagnosis and therapy

The importance of the immune system in regulating tumor growth by inducing immune cell-mediated cytotoxicity associated with patients' outcomes has been highlighted in the past years by an increasing life expectancy in patients with cancer on treatment with different immunotherapeutics. However, tumors often escape immune surveillance, which is accomplished by different mechanisms. Recent studies demonstrated an essential role of small non-coding RNAs, such as microRNAs (miRNAs), in the post-transcriptional control of immune modulatory molecules. Multiple methods have been used to identify miRNAs targeting genes involved in escaping immune recognition including miRNAs targeting CTLA-4, PD-L1, HLA-G, components of the major histocompatibility class I antigen processing machinery (APM) as well as other immune response-relevant genes in tumors. Due to their function, these immune modulatory miRNAs can be used as (1) diagnostic and prognostic biomarkers allowing to discriminate between tumor stages and to predict the patients' outcome as well as response and resistance to (immuno) therapies and as (2) therapeutic targets for the treatment of tumor patients. This review summarizes the role of miRNAs in tumor-mediated immune escape, discuss their potential as diagnostic, prognostic and predictive tools as well as their use as therapeutics including alternative application methods, such as chimeric antigen receptor T cells.

High-sensitivity in situ capture of endogenous RNA-protein interactions in fixed cells and primary tissues

RNA-binding proteins (RBPs) have pivotal functions in RNA metabolism, but current methods are limited in retrieving RBP-RNA interactions within endogenous biological contexts. Here, we develop INSCRIBE (IN situ Sensitive Capture of RNA-protein Interactions in Biological Environments), circumventing the challenges through in situ RNA labeling by precisely directing a purified APOBEC1-nanobody fusion to the RBP of interest. This method enables highly specific RNA-binding site identification across a diverse range of fixed biological samples such as HEK293T cells and mouse brain tissue and accurately identifies the canonical binding motifs of RBFOX2 (UGCAUG) and TDP-43 (UGUGUG) in native cellular environments. Applicable to any RBP with available primary antibodies, INSCRIBE enables sensitive capture of RBP-RNA interactions from ultra-low input equivalent to ~5 cells. The robust, versatile, and sensitive INSCRIBE workflow is particularly beneficial for precious tissues such as clinical samples, empowering the exploration of genuine RBP-RNA interactions in RNA-related disease contexts.

Regulations of m6A and other RNA modifications and their roles in cancer

RNA modification is an essential component of the epitranscriptome, regulating RNA metabolism and cellular functions. Several types of RNA modifications have been identified to date; they include N6-methyladenosine (m6A), N1-methyladenosine (m1A), 5-methylcytosine (m5C), N7-methylguanosine (m7G), N6,2'-O-dimethyladenosine (m6Am), N4-acetylcytidine (ac4C), etc. RNA modifications, mediated by regulators including writers, erasers, and readers, are associated with carcinogenesis, tumor microenvironment, metabolic reprogramming, immunosuppression, immunotherapy, chemotherapy, etc. A novel perspective indicates that regulatory subunits and post-translational modifications (PTMs) are involved in the regulation of writer, eraser, and reader functions in mediating RNA modifications, tumorigenesis, and anticancer therapy. In this review, we summarize the advances made in the knowledge of different RNA modifications (especially m6A) and focus on RNA modification regulators with functions modulated by a series of factors in cancer, including regulatory subunits (proteins, noncoding RNA or peptides encoded by long noncoding RNA) and PTMs (acetylation, SUMOylation, lactylation, phosphorylation, etc.). We also delineate the relationship between RNA modification regulator functions and carcinogenesis or cancer progression. Additionally, inhibitors that target RNA modification regulators for anticancer therapy and their synergistic effect combined with immunotherapy or chemotherapy are discussed.

NPI-DCGNN: An Accurate Tool for Identifying ncRNA-Protein Interactions Using a Dual-Channel Graph Neural Network

Noncoding RNA (NcRNA)-protein interactions (NPIs) play fundamentally important roles in carrying out cellular activities. Although various predictors based on molecular features and graphs have been published to boost the identification of NPIs, most of them often ignore the information between known NPIs or exhibit insufficient learning ability from graphs, posing a significant challenge in effectively identifying NPIs. To develop a more reliable and accurate predictor for NPIs, in this article, we propose NPI-DCGNN, an end-to-end NPI predictor based on a dual-channel graph neural network (DCGNN). NPI-DCGNN initially treats the known NPIs as an ncRNA-protein bipartite graph. Subsequently, for each ncRNA-protein pair, NPI-DCGNN extracts two local subgraphs centered around the ncRNA and protein, respectively, from the bipartite graph. After that, it utilizes a dual-channel graph representation learning layer based on GNN to generate high-level feature representations for the ncRNA-protein pair. Finally, it employs a fully connected network and output layer to predict whether an interaction exists between the pair of ncRNA and protein. Experimental results on four experimentally validated datasets demonstrate that NPI-DCGNN outperforms several state-of-the-art NPI predictors. Our case studies on the NPInter database further demonstrate the prediction power of NPI-DCGNN in predicting NPIs. With the availability of the source codes (https://github.com/zhangxin11111/NPI-DCGNN), we anticipate that NPI-DCGNN could facilitate the studies of ncRNA interactome by providing highly reliable NPI candidates for further experimental validation.

circADAMTS6 via stabilizing CAMK2A is involved in smoking-induced emphysema through driving M2 macrophage polarization

Cigarette smoke (CS), an indoor environmental pollutant, is a prominent risk factor for emphysema, which is a pathological feature of chronic obstructive pulmonary disease (COPD). Emerging function of circRNAs in immune responses and disease progression shed new light to explore the pathogenesis of emphysema. In this research, we demonstrated, by single-cell RNA sequencing (scRNAseq), that the ratio of M2 macrophages were increased in lung tissues of humans and mice with smoking-related emphysema. Further, our data showed that circADAMTS6 was associated with cigarette smoke extract (CSE)-induced M2 macrophage polarization. Mechanistically, in macrophages, circADAMTS6 stabilized CAMK2A mRNA via forming a circADAMTS6/IGF2BP2/CAMK2A RNA-protein ternary complex to activate CREB, which drives M2 macrophage polarization and leads to emphysema. In addition, in macrophages of mouse lung tissues, downregulation of circADAMTS6 reversed M2 macrophage polarization, the proteinase/anti-proteinase imbalance, and the elastin degradation, which protecting against CS-induced emphysema. Moreover, for macrophages and in a model with co-cultured lung organoids, the target of circADAMTS6 restored the growth of lung organoids compared to CSE-treated macrophages. Our results also demonstrated that, for smokers and COPD smokers, elevation of circADAMTS6 negatively correlated with lung function. Overall, this study reveals a novel mechanism for circADAMTS6-driven M2 macrophage polarization in smoking-related emphysema and postulates that circADAMTS6 could serve as a diagnostic and therapeutic marker for smoking-related emphysema.

Detection of transcriptome-wide microRNA-target interactions in single cells with agoTRIBE

MicroRNAs (miRNAs) exert their gene regulatory effects on numerous biological processes based on their selection of target transcripts. Current experimental methods available to identify miRNA targets are laborious and require millions of cells. Here we have overcome these limitations by fusing the miRNA effector protein Argonaute2 to the RNA editing domain of ADAR2, allowing the detection of miRNA targets transcriptome-wide in single cells. miRNAs guide the fusion protein to their natural target transcripts, causing them to undergo A>I editing, which can be detected by sensitive single-cell RNA sequencing. We show that agoTRIBE identifies functional miRNA targets, which are supported by evolutionary sequence conservation. In one application of the method we study microRNA interactions in single cells and identify substantial differential targeting across the cell cycle. AgoTRIBE also provides transcriptome-wide measurements of RNA abundance and allows the deconvolution of miRNA targeting in complex tissues at the single-cell level.

Benchmarking the negatives: Effect of negative data generation on the classification of miRNA-mRNA interactions

MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression post-transcriptionally. In animals, this regulation is achieved via base-pairing with partially complementary sequences on mainly 3' UTR region of messenger RNAs (mRNAs). Computational approaches that predict miRNA target interactions (MTIs) facilitate the process of narrowing down potential targets for experimental validation. The availability of new datasets of high-throughput, direct MTIs has led to the development of machine learning (ML) based methods for MTI prediction. To train an ML algorithm, it is beneficial to provide entries from all class labels (i.e., positive and negative). Currently, no high-throughput assays exist for capturing negative examples. Therefore, current ML approaches must rely on either artificially generated or inferred negative examples deduced from experimentally identified positive miRNA-target datasets. Moreover, the lack of uniform standards for generating such data leads to biased results and hampers comparisons between studies. In this comprehensive study, we collected methods for generating negative data for animal miRNA-target interactions and investigated their impact on the classification of true human MTIs. Our study relies on training ML models on a fixed positive dataset in combination with different negative datasets and evaluating their intra- and cross-dataset performance. As a result, we were able to examine each method independently and evaluate ML models' sensitivity to the methodologies utilized in negative data generation. To achieve a deep understanding of the performance results, we analyzed unique features that distinguish between datasets. In addition, we examined whether one-class classification models that utilize solely positive interactions for training are suitable for the task of MTI classification. We demonstrate the importance of negative data in MTI classification, analyze specific methodological characteristics that differentiate negative datasets, and highlight the challenge of ML models generalizing interaction rules from training to testing sets derived from different approaches. This study provides valuable insights into the computational prediction of MTIs that can be further used to establish standards in the field.

A primer for junior trainees: Recognition of RNA modifications by RNA-binding proteins

The complexity of RNA cannot be fully expressed with the canonical A, C, G, and U alphabet. To date, over 170 distinct chemical modifications to RNA have been discovered in living systems. RNA modifications can profoundly impact the cellular outcomes of messenger RNAs (mRNAs), transfer and ribosomal RNAs, and noncoding RNAs. Additionally, aberrant RNA modifications are associated with human disease. RNA modifications are a rising topic within the fields of biochemistry and molecular biology. The role of RNA modifications in gene regulation, disease pathogenesis, and therapeutic applications increasingly captures the attention of the scientific community. This review aims to provide undergraduates, junior trainees, and educators with an appreciation for the significance of RNA modifications in eukaryotic organisms, alongside the skills required to identify and analyze fundamental RNA-protein interactions. The pumilio RNA-binding protein and YT521-B homology (YTH) family of modified RNA-binding proteins serve as examples to highlight the fundamental biochemical interactions that underlie the specific recognition of both unmodified and modified ribonucleotides, respectively. By instilling these foundational, textbook concepts through practical examples, this review contributes an analytical toolkit that facilitates engagement with RNA modifications research at large.

Unraveling the complexity: Advanced methods in analyzing DNA, RNA, and protein interactions

Exploring the intricate interplay within and between nucleic acids, as well as their interactions with proteins, holds pivotal significance in unraveling the molecular complexities steering cancer initiation and progression. To investigate these interactions, a diverse array of highly specific and sensitive molecular techniques has been developed. The selection of a particular technique depends on the specific nature of the interactions. Typically, researchers employ an amalgamation of these different techniques to obtain a comprehensive and holistic understanding of inter- and intramolecular interactions involving DNA-DNA, RNA-RNA, DNA-RNA, or protein-DNA/RNA. Examining nucleic acid conformation reveals alternative secondary structures beyond conventional ones that have implications for cancer pathways. Mutational hotspots in cancer often lie within sequences prone to adopting these alternative structures, highlighting the importance of investigating intra-genomic and intra-transcriptomic interactions, especially in the context of mutations, to deepen our understanding of oncology. Beyond these intramolecular interactions, the interplay between DNA and RNA leads to formations like DNA:RNA hybrids (known as R-loops) or even DNA:DNA:RNA triplex structures, both influencing biological processes that ultimately impact cancer. Protein-nucleic acid interactions are intrinsic cellular phenomena crucial in both normal and pathological conditions. In particular, genetic mutations or single amino acid variations can alter a protein's structure, function, and binding affinity, thus influencing cancer progression. It is thus, imperative to understand the differences between wild-type (WT) and mutated (MT) genes, transcripts, and proteins. The review aims to summarize the frequently employed methods and techniques for investigating interactions involving nucleic acids and proteins, highlighting recent advancements and diverse adaptations of each technique.

N6-methyladenosine modification of circMARK2 enhances cytoplasmic export and stabilizes LIN28B, contributing to the progression of Wilms tumor

BACKGROUND

The potential involvement of circular RNAs (circRNAs) and N6-methyladenosine (m6A) modification in the progression of Wilms tumor (WT) has not been fully elucidated. This study investigates the regulatory mechanisms and clinical significance of m6A-modified circMARK2 and its role in WT progression.

METHODS

We identified dysregulated circRNAs through deep sequencing and validated their expression by qRT-PCR in WT tissues. The biological functions of circMARK2 were assessed using clone formation, transwell migration, and orthotopic animal models. To dissect the underlying mechanisms, we employed RNA immunoprecipitation, RNA pull-down, dual-luciferase reporter assays, Western blotting, and immunofluorescence and immunohistochemical staining.

RESULTS

CircMARK2, upregulated in WT tissues, was found to be m6A-modified and promoted cytoplasmic export. It facilitated WT progression by stabilizing LIN28B mRNA through the circMARK2/IGF2BP2 interaction. In vitro and in vivo studies demonstrated that circMARK2 enhances the malignant behavior of WT cells. Clinically, higher circMARK2 levels in tumor tissues of WT patients were linked to increased tumor aggressiveness and reduced survival rates.

CONCLUSIONS

Our study provides the first comprehensive evidence that m6A-modified circMARK2 contributes to WT progression by enhancing LIN28B mRNA stability, promoting cellular aggressiveness. CircMARK2 emerges as a potential biomarker for prognosis and a promising target for therapeutic intervention in WT, underscoring the clinical relevance of m6A modification in pediatric renal cancer.

Mudskipper detects combinatorial RNA binding protein interactions in multiplexed CLIP data

The uncovering of protein-RNA interactions enables a deeper understanding of RNA processing. Recent multiplexed crosslinking and immunoprecipitation (CLIP) technologies such as antibody-barcoded eCLIP (ABC) dramatically increase the throughput of mapping RNA binding protein (RBP) binding sites. However, multiplex CLIP datasets are multivariate, and each RBP suffers non-uniform signal-to-noise ratio. To address this, we developed Mudskipper, a versatile computational suite comprising two components: a Dirichlet multinomial mixture model to account for the multivariate nature of ABC datasets and a softmasking approach that identifies and removes non-specific protein-RNA interactions in RBPs with low signal-to-noise ratio. Mudskipper demonstrates superior precision and recall over existing tools on multiplex datasets and supports analysis of repetitive elements and small non-coding RNAs. Our findings unravel splicing outcomes and variant-associated disruptions, enabling higher-throughput investigations into diseases and regulation mediated by RBPs.

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.

RNA 2'-O-methylation promotes persistent R-loop formation and AID-mediated IgH class switch recombination

BACKGROUND

RNA-DNA hybrids or R-loops are associated with deleterious genomic instability and protective immunoglobulin class switch recombination (CSR). However, the underlying phenomenon regulating the two contrasting functions of R-loops is unknown. Notably, the underlying mechanism that protects R-loops from classic RNase H-mediated digestion thereby promoting persistence of CSR-associated R-loops during CSR remains elusive.

RESULTS

Here, we report that during CSR, R-loops formed at the immunoglobulin heavy (IgH) chain are modified by ribose 2'-O-methylation (2'-OMe). Moreover, we find that 2'-O-methyltransferase fibrillarin (FBL) interacts with activation-induced cytidine deaminase (AID) associated snoRNA aSNORD1C to facilitate the 2'-OMe. Moreover, deleting AID C-terminal tail impairs its association with aSNORD1C and FBL. Disrupting FBL, AID or aSNORD1C expression severely impairs 2'-OMe, R-loop stability and CSR. Surprisingly, FBL, AID's interaction partner and aSNORD1C promoted AID targeting to the IgH locus.

CONCLUSION

Taken together, our results suggest that 2'-OMe stabilizes IgH-associated R-loops to enable productive CSR. These results would shed light on AID-mediated CSR and explain the mechanism of R-loop-associated genomic instability.

Hsa_circ_0005320 affects cell proliferation and the cell cycle via the IGF2BP3/CDK2 axis in bladder cancer

BACKGROUND

Circular RNAs (circRNAs), which are covalently closed non-coding RNAs, are frequently dysregulated in cancer. However, their precise role in bladder cancer (BCa) remains largely unknown.

METHODS

Expression of hsa_circ_0005320 in tissues and cell lines was detected using quantitative real-time PCR. Proliferation and colony forming capacity of BCa cells were assessed using Cell Counting Kit-8, ethynyl-labeled deoxyuridine, and colony formation assays. The cell cycle was analyzed using flow cytometry. Protein expression of insulin-like growth factor II mRNA-binding protein 3 (IGF2BP3) and cyclin dependent kinase 2 (CDK2) was examined using western blots. The binding of RNA and protein was validated using RNA immunoprecipitation. Additionally, xenograft tumor models were established to validate the function of hsa_circ_0005320 in vivo.

RESULTS

We screened hsa_circ_0005320 from previous high-throughput sequencing and found that it was highly expressed in BCa tissues and associated with tumor differentiation and depth of invasion in BCa patients. Through functional experiments, we demonstrated that hsa_circ_0005320 promoted cell proliferation and regulated the cell cycle. Mechanistically, hsa_circ_0005320 interacted with and upregulated the expression of IGF2BP3, which binds to and enhances the stability of CDK2 mRNA. Furthermore, knockdown of hsa_circ_0005320 resulted in a reduction in tumor burden in vivo.

CONCLUSIONS

Collectively, these findings highlight the pro-oncogenic role of hsa_circ_0005320 in BCa through the IGF2BP3/CDK2 axis, providing valuable insights into the mechanism of circRNAs in tumor progression.

The Biological Roles of microRNAs in Drosophila Development

Drosophila is a well-established insect model system for studying various physiological phenomena and developmental processes, with a focus on gene regulation. Drosophila development is controlled by programmed regulatory mechanisms specific to individual tissues. When key developmental processes are shared among various insects, the associated regulatory networks are believed to be conserved across insects. Thus, studies of developmental regulation in Drosophila have substantially contributed to our understanding of insect development. Over the past two decades, studies on microRNAs (miRNAs) in Drosophila have revealed their crucial regulatory roles in various developmental processes. This review focuses on the biological roles of miRNAs in specific tissues and processes associated with Drosophila development. Additionally, as a future direction, we discuss sequencing technologies that can analyze the interactions between miRNAs and their target genes, with the aim of enhancing miRNA studies in Drosophila development.

Pumilio-1 mediated translational control of claudin-5 at the blood-brain barrier

Claudin-5 is one of the most essential tight junction proteins at the blood-brain barrier. A single nucleotide polymorphism rs10314 is located in the 3'-untranslated region of claudin-5 and has been shown to be a risk factor for schizophrenia. Here, we show that the pumilio RNA-binding protein, pumilio-1, is responsible for rs10314-mediated claudin-5 regulation. The RNA sequence surrounding rs10314 is highly homologous to the canonical pumilio-binding sequence and claudin-5 mRNA with rs10314 produces 25% less protein due to its inability to bind to pumilio-1. Pumilio-1 formed cytosolic granules under stress conditions and claudin-5 mRNA appeared to preferentially accumulate in these granules. Added to this, we observed granular pumilio-1 in endothelial cells in human brain tissues from patients with psychiatric disorders or epilepsy with increased/accumulated claudin-5 mRNA levels, suggesting translational claudin-5 suppression may occur in a brain-region specific manner. These findings identify a key regulator of claudin-5 translational processing and how its dysregulation may be associated with neurological and neuropsychiatric disorders.

RNA N6-methyladenosine methylation in influenza A virus infection

Influenza A virus (IAV) is a negative-sense single-stranded RNA virus that causes acute lung injury and acute respiratory distress syndrome, posing a serious threat to both animal and human health. N6-methyladenosine (m6A), a prevalent and abundant post-transcriptional methylation of RNA in eukaryotes, plays a crucial regulatory role in IAV infection by altering viral RNA and cellular transcripts to affect viral infection and the host immune response. This review focuses on the molecular mechanisms underlying m6A modification and its regulatory function in the context of IAV infection and the host immune response. This will provide a better understanding of virus-host interactions and offer insights into potential anti-IAV strategies.

Mapping RNA-protein interactions with subcellular resolution using colocalization CLIP

RNA-binding proteins (RBPs) are essential for RNA metabolism and profoundly impact health and disease. The subcellular organization of RBP interaction networks with target RNAs remains largely unexplored. Here, we develop colocalization CLIP (coCLIP), a method that combines cross-linking and immunoprecipitation (CLIP) with proximity labeling, to explore in-depth the subcellular RNA interactions of the RBP human antigen R (HuR). Using this method, we uncover HuR's dynamic and location-specific interactions with RNA, revealing alterations in sequence preferences and interactions in the nucleus, cytosol, or stress granule (SG) compartments. We uncover HuR's unique binding preferences within SGs during arsenite stress, illuminating intricate interactions that conventional methodologies cannot capture. Overall, coCLIP provides a powerful method for revealing RBP-RNA interactions based on localization and lays the foundation for an advanced understanding of RBP models that incorporate subcellular location as a critical determinant of their functions.

Epitranscriptomic cytidine methylation of the hepatitis B viral RNA is essential for viral reverse transcription and particle production

Epitranscriptomic RNA modifications have emerged as important regulators of the fate and function of viral RNAs. One prominent modification, the cytidine methylation 5-methylcytidine (m5C), is found on the RNA of HIV-1, where m5C enhances the translation of HIV-1 RNA. However, whether m5C functionally enhances the RNA of other pathogenic viruses remains elusive. Here, we surveyed a panel of commonly found RNA modifications on the RNA of hepatitis B virus (HBV) and found that HBV RNA is enriched with m5C as well as ten other modifications, at stoichiometries much higher than host messenger RNA (mRNA). Intriguingly, m5C is mostly found on the epsilon hairpin, an RNA element required for viral RNA encapsidation and reverse transcription, with these m5C mainly deposited by the cellular methyltransferase NSUN2. Loss of m5C from HBV RNA due to NSUN2 depletion resulted in a partial decrease in viral core protein (HBc) production, accompanied by a near-complete loss of the reverse transcribed viral DNA. Similarly, mutations introduced to remove the methylated cytidines resulted in a loss of HBc production and reverse transcription. Furthermore, pharmacological disruption of m5C deposition led to a significant decrease in HBV replication. Thus, our data indicate m5C methylations as a critical mediator of the epsilon elements' function in HBV virion production and reverse transcription, suggesting the therapeutic potential of targeting the m5C methyltransfer process on HBV epsilon as an antiviral strategy.

Massively parallel dissection of RNA in RNA-protein interactions in vivo

Many of the biological functions performed by RNA are mediated by RNA-binding proteins (RBPs), and understanding the molecular basis of these interactions is fundamental to biology. Here, we present massively parallel RNA assay combined with immunoprecipitation (MPRNA-IP) for in vivo high-throughput dissection of RNA-protein interactions and describe statistical models for identifying RNA domains and parsing the structural contributions of RNA. By using custom pools of tens of thousands of RNA sequences containing systematically designed truncations and mutations, MPRNA-IP is able to identify RNA domains, sequences, and secondary structures necessary and sufficient for protein binding in a single experiment. We show that this approach is successful for multiple RNAs of interest, including the long noncoding RNA NORAD, bacteriophage MS2 RNA, and human telomerase RNA, and we use it to interrogate the hitherto unknown sequence or structural RNA-binding preferences of the DNA-looping factor CTCF. By integrating systematic mutation analysis with crosslinking immunoprecipitation, MPRNA-IP provides a novel high-throughput way to elucidate RNA-based mechanisms behind RNA-protein interactions in vivo.

Big data and deep learning for RNA biology

The exponential growth of big data in RNA biology (RB) has led to the development of deep learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL studies in other fields, the successful implementation of DL in RB depends heavily on the effective utilization of large-scale datasets from public databases. In achieving this goal, data encoding methods, learning algorithms, and techniques that align well with biological domain knowledge have played pivotal roles. In this review, we provide guiding principles for applying these DL concepts to various problems in RB by demonstrating successful examples and associated methodologies. We also discuss the remaining challenges in developing DL models for RB and suggest strategies to overcome these challenges. Overall, this review aims to illuminate the compelling potential of DL for RB and ways to apply this powerful technology to investigate the intriguing biology of RNA more effectively.

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.

LPI-SKMSC: Predicting LncRNA-Protein Interactions with Segmented k-mer Frequencies and Multi-space Clustering

 Long noncoding RNAs (lncRNAs) have significant regulatory roles in gene expression. Interactions with proteins are one of the ways lncRNAs play their roles. Since experiments to determine lncRNA-protein interactions (LPIs) are expensive and time-consuming, many computational methods for predicting LPIs have been proposed as alternatives. In the LPIs prediction problem, there commonly exists the imbalance in the distribution of positive and negative samples. However, there are few existing methods that give specific consideration to this problem. In this paper, we proposed a new clustering-based LPIs prediction method using segmented k-mer frequencies and multi-space clustering (LPI-SKMSC). It was dedicated to handling the imbalance of positive and negative samples. We constructed segmented k-mer frequencies to obtain global and local features of lncRNA and protein sequences. Then, the multi-space clustering was applied to LPI-SKMSC. The convolutional neural network (CNN)-based encoders were used to map different features of a sample to different spaces. It used multiple spaces to jointly constrain the classification of samples. Finally, the distances between the output features of the encoder and the cluster center in each space were calculated. The sum of distances in all spaces was compared with the cluster radius to predict the LPIs. We performed cross-validation on 3 public datasets and LPI-SKMSC showed the best performance compared to other existing methods. Experimental results showed that LPI-SKMSC could predict LPIs more effectively when faced with imbalanced positive and negative samples. In addition, we illustrated that our model was better at uncovering potential lncRNA-protein interaction pairs.

MicroRNA-mediated regulation of nonsense-mediated mRNA decay factors: Insights into microRNA prediction tools and profiling techniques

Nonsense-mediated mRNA decay (NMD) stands out as a prominent RNA surveillance mechanism within eukaryotes, meticulously overseeing both RNA abundance and integrity by eliminating aberrant transcripts. These defective transcripts are discerned through the concerted efforts of translating ribosomes, eukaryotic release factors (eRFs), and trans-acting NMD factors, with Up-Frameshift 3 (UPF3) serving as a noteworthy component. Remarkably, in humans, UPF3 exists in two paralogous forms, UPF3A (UPF3) and UPF3B (UPF3X). Beyond its role in quality control, UPF3 wields significant influence over critical cellular processes, including neural development, synaptic plasticity, and axon guidance. However, the precise regulatory mechanisms governing UPF3 remain elusive. MicroRNAs (miRNAs) emerge as pivotal post-transcriptional gene regulators, exerting substantial impact on diverse pathological and physiological pathways. This comprehensive review encapsulates our current understanding of the intricate regulatory nexus between NMD and miRNAs, with particular emphasis on the essential role played by UPF3B in neurodevelopment. Additionally, we bring out the significance of the 3'-untranslated region (3'-UTR) as the molecular bridge connecting NMD and miRNA-mediated gene regulation. Furthermore, we provide an in-depth exploration of diverse computational tools tailored for the prediction of potential miRNA targets. To complement these computational approaches, we delineate experimental techniques designed to validate predicted miRNA-mRNA interactions, empowering readers with the knowledge necessary to select the most appropriate methodology for their specific research objectives.

Time-resolved profiling of RNA binding proteins throughout the mRNA life cycle

mRNAs continually change their protein partners throughout their lifetimes, yet our understanding of mRNA-protein complex (mRNP) remodeling is limited by a lack of temporal data. Here, we present time-resolved mRNA interactome data by performing pulse metabolic labeling with photoactivatable ribonucleoside in human cells, UVA crosslinking, poly(A)+ RNA isolation, and mass spectrometry. This longitudinal approach allowed the quantification of over 700 RNA binding proteins (RBPs) across ten time points. Overall, the sequential order of mRNA binding aligns well with known functions, subcellular locations, and molecular interactions. However, we also observed RBPs with unexpected dynamics: the transcription-export (TREX) complex recruited posttranscriptionally after nuclear export factor 1 (NXF1) binding, challenging the current view of transcription-coupled mRNA export, and stress granule proteins prevalent in aged mRNPs, indicating roles in late stages of the mRNA life cycle. To systematically identify mRBPs with unknown functions, we employed machine learning to compare mRNA binding dynamics with Gene Ontology (GO) annotations. Our data can be explored at chronology.rna.snu.ac.kr.

Revealing the hidden RBP-RNA interactions with RNA modification enzyme-based strategies

RNA-binding proteins (RBPs) are powerful and versatile regulators in living creatures, playing fundamental roles in organismal development, metabolism, and various diseases by the regulation of gene expression at multiple levels. The requirements of deep research on RBP function have promoted the rapid development of RBP-RNA interplay detection methods. Recently, the detection method of fusing RNA modification enzymes (RME) with RBP of interest has become a hot topic. Here, we reviewed RNA modification enzymes in adenosine deaminases that act on RNA (ADAR), terminal nucleotidyl transferase (TENT), and activation-induced cytosine deaminase/ApoB mRNA editing enzyme catalytic polypeptide-like (AID/APOBEC) protein family, regarding the biological function, biochemical activity, and substrate specificity originated from enzyme selves, their domains and partner proteins. In addition, we discussed the RME activity screening system, and the RME mutations with engineered enzyme activity. Furthermore, we provided a systematic overview of the basic principles, advantages, disadvantages, and applications of the RME-based and cross-linking and immunopurification (CLIP)-based RBP target profiling strategies, including targets of RNA-binding proteins identified by editing (TRIBE), RNA tagging, surveying targets by APOBEC-mediated profiling (STAMP), CLIP-seq, and their derivative technology. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Processing > RNA Editing and Modification.