A large-scale binding and functional map of human RNA-binding proteins

RBProkCNN: Deep learning on appropriate contextual evolutionary information for RNA binding protein discovery in prokaryotes

RNA-binding proteins (RBPs) are central to key functions such as post-transcriptional regulation, mRNA stability, and adaptation to varied environmental conditions in prokaryotes. While the majority of research has concentrated on eukaryotic RBPs, recent developments underscore the crucial involvement of prokaryotic RBPs. Although computational methods have emerged in recent years to identify RBPs, they have fallen short in accurately identifying prokaryotic RBPs due to their generic nature. To bridge this gap, we introduce RBProkCNN, a novel machine learning-driven computational model meticulously designed for the accurate prediction of prokaryotic RBPs. The prediction process involves the utilization of eight shallow learning algorithms and four deep learning models, incorporating PSSM-based evolutionary features. By leveraging a convolutional neural network (CNN) and evolutionarily significant features selected through extreme gradient boosting variable importance measure, RBProkCNN achieved the highest accuracy in five-fold cross-validation, yielding 98.04% auROC and 98.19% auPRC. Furthermore, RBProkCNN demonstrated robust performance with an independent dataset, showcasing a commendable 95.77% auROC and 95.78% auPRC. Noteworthy is its superior predictive accuracy when compared to several state-of-the-art existing models. RBProkCNN is available as an online prediction tool (https://iasri-sg.icar.gov.in/rbprokcnn/), offering free access to interested users. This tool represents a substantial contribution, enriching the array of resources available for the accurate and efficient prediction of prokaryotic RBPs.

DOT1L/H3K79me2 represses HIV-1 reactivation via recruiting DCAF1

DOT1L mediates the methylation of histone H3 at lysine 79 and, in turn, the transcriptional activation or repression in a context-dependent manner, yet the regulatory mechanisms and functions of DOT1L/H3K79me remain to be fully explored. Following peptide affinity purification and proteomic analysis, we identified that DCAF1-a component of the E3 ligase complex involved in HIV regulation-is associated with H3K79me2 and DOT1L. Interestingly, blocking the expression or catalytic activity of DOT1L or repressing the expression of DCAF1 significantly enhances the tumor necrosis factor alpha (TNF-α)/nuclear factor κB (NF-κB)-induced reactivation of the latent HIV-1 genome. Mechanistically, upon TNF-α/NF-κB activation, DCAF1 is recruited to the HIV-1 long terminal repeat (LTR) by DOT1L and H3K79me2. Recruited DCAF1 subsequently induces the ubiquitination of NF-κB and restricts its accumulation at the HIV-1 LTR. Altogether, our findings reveal a feedback modulation of HIV reactivation by DOT1L-mediated histone modification regulation and highlight the potential of targeting the DOT1L/DCAF1 axis as a therapeutic strategy for HIV treatment.

ASAR lncRNAs control DNA replication timing through interactions with multiple hnRNP/RNA binding proteins

ASARs are a family of very-long noncoding RNAs that control replication timing on individual human autosomes, and are essential for chromosome stability. The eight known ASAR lncRNAs remain closely associated with their parent chromosomes. Analysis of RNA-protein interaction data (from ENCODE) revealed numerous RBPs with significant interactions with multiple ASAR lncRNAs, with several hnRNPs as abundant interactors. An ~7 kb domain within the ASAR6-141 lncRNA shows a striking density of RBP interaction sites. Genetic deletion and ectopic integration assays indicate that this ~7 kb RNA binding protein domain contains functional sequences for controlling replication timing of entire chromosomes in cis. shRNA-mediated depletion of 10 different RNA binding proteins, including HNRNPA1, HNRNPC, HNRNPL, HNRNPM, HNRNPU, or HNRNPUL1, results in dissociation of ASAR lncRNAs from their chromosome territories, and disrupts the synchronous replication that occurs on all autosome pairs, recapitulating the effect of individual ASAR knockouts on a genome-wide scale. Our results further demonstrate the role that ASARs play during the temporal order of genome-wide replication, and we propose that ASARs function as essential RNA scaffolds for the assembly of hnRNP complexes that help maintain the structural integrity of each mammalian chromosome.

Conserved intronic secondary structures with concealed branch sites regulate alternative splicing of poison exons

Alternative splicing (AS) generates multiple RNA isoforms and increases the complexities of transcriptomes and proteomes. However, it remains unclear how RNA structures contribute to AS regulation. Here, we systematically search transcriptomes for secondary structures with concealed branch sites (BSs) in the alternatively spliced introns and predict thousands of them from six organisms, of which many are evolutionarily conserved. Intriguingly, a highly conserved stem-loop structure with concealed BSs is found in animal SF3B3 genes and colocalizes with a downstream poison exon (PE). Destabilization of this structure allows increased usage of the BSs and results in enhanced PE inclusion in human and Drosophila cells, leading to decreased expression of SF3B3. This structure is experimentally validated using an in-cell SHAPE-MaP assay. Through RNA interference screens of 28 RNA-binding proteins, we find that this stem-loop structure is sensitive to U2 factors. Furthermore, we find that SF3B3 also facilitates DNA repair and protects genome stability by enhancing interaction between ERCC6/CSB and arrested RNA polymerase II. Importantly, both Drosophila and human cells with the secondary structure mutated by genome editing exhibit altered DNA repair in vivo. This study provides a novel and common mechanism for AS regulation of PEs and reveals a physiological function of SF3B3 in DNA repair.

hnRNPM protects against the dsRNA-mediated interferon response by repressing LINE-associated cryptic splicing

RNA splicing is pivotal in post-transcriptional gene regulation, yet the exponential expansion of intron length in humans poses a challenge for accurate splicing. Here, we identify hnRNPM as an essential RNA-binding protein that suppresses cryptic splicing through binding to deep introns, maintaining human transcriptome integrity. Long interspersed nuclear elements (LINEs) in introns harbor numerous pseudo splice sites. hnRNPM preferentially binds at intronic LINEs to repress pseudo splice site usage for cryptic splicing. Remarkably, cryptic exons can generate long dsRNAs through base-pairing of inverted ALU transposable elements interspersed among LINEs and consequently trigger an interferon response, a well-known antiviral defense mechanism. Significantly, hnRNPM-deficient tumors show upregulated interferon-associated pathways and elevated immune cell infiltration. These findings unveil hnRNPM as a guardian of transcriptome integrity by repressing cryptic splicing and suggest that targeting hnRNPM in tumors may be used to trigger an inflammatory immune response, thereby boosting cancer surveillance.

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.

Single-cell long-read sequencing-based mapping reveals specialized splicing patterns in developing and adult mouse and human brain

RNA isoforms influence cell identity and function. However, a comprehensive brain isoform map was lacking. We analyze single-cell RNA isoforms across brain regions, cell subtypes, developmental time points and species. For 72% of genes, full-length isoform expression varies along one or more axes. Splicing, transcription start and polyadenylation sites vary strongly between cell types, influence protein architecture and associate with disease-linked variation. Additionally, neurotransmitter transport and synapse turnover genes harbor cell-type variability across anatomical regions. Regulation of cell-type-specific splicing is pronounced in the postnatal day 21-to-postnatal day 28 adolescent transition. Developmental isoform regulation is stronger than regional regulation for the same cell type. Cell-type-specific isoform regulation in mice is mostly maintained in the human hippocampus, allowing extrapolation to the human brain. Conversely, the human brain harbors additional cell-type specificity, suggesting gain-of-function isoforms. Together, this detailed single-cell atlas of full-length isoform regulation across development, anatomical regions and species reveals an unappreciated degree of isoform variability across multiple axes.

Alternative splicing in EMT and TGF-β signaling during cancer progression

Epithelial to mesenchymal transition (EMT) is a physiological process during development where epithelial cells transform to acquire mesenchymal characteristics, which allows them to migrate and colonize secondary tissues. Many cellular signaling pathways and master transcriptional factors exert a myriad of controls to fine tune this vital process to meet various developmental and physiological needs. Adding to the complexity of this network are post-transcriptional and post-translational regulations. Among them, alternative splicing has been shown to play important roles to drive EMT-associated phenotypic changes, including actin cytoskeleton remodeling, cell-cell junction changes, cell motility and invasiveness. In advanced cancers, transforming growth factor-β (TGF-β) is a major inducer of EMT and is associated with tumor cell metastasis, cancer stem cell self-renewal, and drug resistance. This review aims to provide an overview of recent discoveries regarding alternative splicing events and the involvement of splicing factors in the EMT and TGF-β signaling. It will emphasize the importance of various splicing factors involved in EMT and explore their regulatory mechanisms.

CSDE1: a versatile regulator of gene expression in cancer

RNA-binding proteins (RBPs) have garnered significant attention in the field of cancer due to their ability to modulate diverse tumor traits. Once considered untargetable, RBPs have sparked renewed interest in drug development, particularly in the context of RNA-binding modulators of translation. This review focuses on one such modulator, the protein CSDE1, and its pivotal role in regulating cancer hallmarks. We discuss context-specific functions of CSDE1 in tumor development, its mechanisms of action, and highlight features that support its role as a molecular adaptor. Additionally, we discuss the regulation of CSDE1 itself and its potential value as biomarker and therapeutic target.

Development and validation of AI/ML derived splice-switching oligonucleotides

Splice-switching oligonucleotides (SSOs) are antisense compounds that act directly on pre-mRNA to modulate alternative splicing (AS). This study demonstrates the value that artificial intelligence/machine learning (AI/ML) provides for the identification of functional, verifiable, and therapeutic SSOs. We trained XGboost tree models using splicing factor (SF) pre-mRNA binding profiles and spliceosome assembly information to identify modulatory SSO binding sites on pre-mRNA. Using Shapley and out-of-bag analyses we also predicted the identity of specific SFs whose binding to pre-mRNA is blocked by SSOs. This step adds considerable transparency to AI/ML-driven drug discovery and informs biological insights useful in further validation steps. We applied this approach to previously established functional SSOs to retrospectively identify the SFs likely to regulate those events. We then took a prospective validation approach using a novel target in triple negative breast cancer (TNBC), NEDD4L exon 13 (NEDD4Le13). Targeting NEDD4Le13 with an AI/ML-designed SSO decreased the proliferative and migratory behavior of TNBC cells via downregulation of the TGFβ pathway. Overall, this study illustrates the ability of AI/ML to extract actionable insights from RNA-seq data.

The debranching enzyme Dbr1 regulates lariat turnover and intron splicing

The majority of genic transcription is intronic. Introns are removed by splicing as branched lariat RNAs which require rapid recycling. The branch site is recognized during splicing catalysis and later debranched by Dbr1 in the rate-limiting step of lariat turnover. Through generation of a viable DBR1 knockout cell line, we find the predominantly nuclear Dbr1 enzyme to encode the sole debranching activity in human cells. Dbr1 preferentially debranches substrates that contain canonical U2 binding motifs, suggesting that branchsites discovered through sequencing do not necessarily represent those favored by the spliceosome. We find that Dbr1 also exhibits specificity for particular 5' splice site sequences. We identify Dbr1 interactors through co-immunoprecipitation mass spectrometry. We present a mechanistic model for Dbr1 recruitment to the branchpoint through the intron-binding protein AQR. In addition to a 20-fold increase in lariats, Dbr1 depletion increases exon skipping. Using ADAR fusions to timestamp lariats, we demonstrate a defect in spliceosome recycling. In the absence of Dbr1, spliceosomal components remain associated with the lariat for a longer period of time. As splicing is co-transcriptional, slower recycling increases the likelihood that downstream exons will be available for exon skipping.

ePRINT: exonuclease assisted mapping of protein-RNA interactions

RNA-binding proteins (RBPs) regulate key aspects of RNA processing including alternative splicing, mRNA degradation and localization by physically binding RNA molecules. Current methods to map these interactions, such as CLIP, rely on purifying single proteins at a time. Our new method, ePRINT, maps RBP-RNA interaction networks on a global scale without purifying individual RBPs. ePRINT uses exoribonuclease XRN1 to precisely map the 5' end of the RBP binding site and uncovers direct and indirect targets of an RBP of interest. Importantly, ePRINT can also uncover RBPs that are differentially activated between cell fate transitions, including neural progenitor differentiation into neurons.

Developmental isoform diversity in the human neocortex informs neuropsychiatric risk mechanisms

RNA splicing is highly prevalent in the brain and has strong links to neuropsychiatric disorders; yet, the role of cell type-specific splicing and transcript-isoform diversity during human brain development has not been systematically investigated. In this work, we leveraged single-molecule long-read sequencing to deeply profile the full-length transcriptome of the germinal zone and cortical plate regions of the developing human neocortex at tissue and single-cell resolution. We identified 214,516 distinct isoforms, of which 72.6% were novel (not previously annotated in Gencode version 33), and uncovered a substantial contribution of transcript-isoform diversity-regulated by RNA binding proteins-in defining cellular identity in the developing neocortex. We leveraged this comprehensive isoform-centric gene annotation to reprioritize thousands of rare de novo risk variants and elucidate genetic risk mechanisms for neuropsychiatric disorders.

Live cell screening to identify RNA-binding small molecule inhibitors of the pre-let-7-Lin28 RNA-protein interaction

Dysregulation of the networking of RNA-binding proteins (RBPs) and RNAs drives many human diseases, including cancers, and the targeting of RNA-protein interactions (RPIs) has emerged as an exciting area of RNA-targeted drug discovery. Accordingly, methods that enable the discovery of cell-active small molecule modulators of RPIs are needed to propel this emerging field forward. Herein, we describe the application of live-cell assay technology, RNA interaction with protein-mediated complementation assay (RiPCA), for high-throughput screening to identify small molecule inhibitors of the pre-let-7d-Lin28A RPI. Utilizing a combination of RNA-biased small molecules and virtual screening hits, we discovered an RNA-binding small molecule that can disrupt the pre-let-7-Lin28 interaction demonstrating the potential of RiPCA for advancing RPI-targeted drug discovery.

U3 snoRNA inter-regulates with DDX21 in the perichromosomal region to control mitosis

U3 snoRNA is essential for ribosome biogenesis during interphase. Upon mitotic onset, the nucleolus disassembles and U3 snoRNA relocates to the perichromosomal region (PR) to be considered as a chromosome passenger. Whether U3 controls mitosis remains unknown. Here, we demonstrate that U3 snoRNA is required for mitotic progression. We identified DDX21 as the predominant U3-binding protein during mitosis and confirmed that U3 snoRNA colocalizes with DDX21 in the PR. DDX21 knockdown induces mitotic catastrophe and similar mitotic defects caused by U3 snoRNA depletion. Interestingly, the uniform PR distribution of U3 snoRNA and DDX21 is interdependent. DDX21 functions in mitosis depending on its PR localization. Mechanistically, U3 snoRNA regulates DDX21 PR localization through maintaining its mobility. Moreover, Cy5-U3 snoRNA downsizes the fibrous condensates of His-DDX21 at proper molecular ratios in vitro. This work highlights the importance of the equilibrium between U3 snoRNA and DDX21 in PR formation and reveals the potential relationship between the PR assembly and mitotic regulation.

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.

Deep Learning for Elucidating Modifications to RNA-Status and Challenges Ahead

RNA-binding proteins and chemical modifications to RNA play vital roles in the co- and post-transcriptional regulation of genes. In order to fully decipher their biological roles, it is an essential task to catalogue their precise target locations along with their preferred contexts and sequence-based determinants. Recently, deep learning approaches have significantly advanced in this field. These methods can predict the presence or absence of modification at specific genomic regions based on diverse features, particularly sequence and secondary structure, allowing us to decipher the highly non-linear sequence patterns and structures that underlie site preferences. This article provides an overview of how deep learning is being applied to this area, with a particular focus on the problem of mRNA-RBP binding, while also considering other types of chemical modification to RNA. It discusses how different types of model can handle sequence-based and/or secondary-structure-based inputs, the process of model training, including choice of negative regions and separating sets for testing and training, and offers recommendations for developing biologically relevant models. Finally, it highlights four key areas that are crucial for advancing the field.

MAPP unravels frequent co-regulation of splicing and polyadenylation by RNA-binding proteins and their dysregulation in cancer

Maturation of eukaryotic pre-mRNAs via splicing and polyadenylation is modulated across cell types and conditions by a variety of RNA-binding proteins (RBPs). Although there exist over 1,500 RBPs in human cells, their binding motifs and functions still remain to be elucidated, especially in the complex environment of tissues and in the context of diseases. To overcome the lack of methods for the systematic and automated detection of sequence motif-guided pre-mRNA processing regulation from RNA sequencing (RNA-Seq) data we have developed MAPP (Motif Activity on Pre-mRNA Processing). Applying MAPP to RBP knock-down experiments reveals that many RBPs regulate both splicing and polyadenylation of nascent transcripts by acting on similar sequence motifs. MAPP not only infers these sequence motifs, but also unravels the position-dependent impact of the RBPs on pre-mRNA processing. Interestingly, all investigated RBPs that act on both splicing and 3' end processing exhibit a consistently repressive or activating effect on both processes, providing a first glimpse on the underlying mechanism. Applying MAPP to normal and malignant brain tissue samples unveils that the motifs bound by the PTBP1 and RBFOX RBPs coordinately drive the oncogenic splicing program active in glioblastomas demonstrating that MAPP paves the way for characterizing pre-mRNA processing regulators under physiological and pathological conditions.

Alternative 3'UTR expression induced by T cell activation is regulated in a temporal and signal dependent manner

The length of 3' untranslated regions (3'UTR) is highly regulated during many transitions in cell state, including T cell activation, through the process of alternative polyadenylation (APA). However, the regulatory mechanisms and functional consequences of APA remain largely unexplored. Here we present a detailed analysis of the temporal and condition-specific regulation of APA following activation of primary human CD4+ T cells. We find that global APA changes are regulated temporally and CD28 costimulatory signals enhance a subset of these changes. Most APA changes upon T cell activation involve 3'UTR shortening, although a set of genes enriched for function in the mTOR pathway exhibit 3'UTR lengthening. While upregulation of the core polyadenylation machinery likely induces 3'UTR shortening following prolonged T cell stimulation; a significant program of APA changes occur prior to cellular proliferation or upregulation of the APA machinery. Motif analysis suggests that at least a subset of these early changes in APA are driven by upregulation of RBM3, an RNA-binding protein which competes with the APA machinery for binding. Together this work expands our understanding of the impact and mechanisms of APA in response to T cell activation and suggests new mechanisms by which APA may be regulated.

An interpretable model of pre-mRNA splicing for animal and plant genes

Pre-mRNA splicing is a fundamental step in gene expression, conserved across eukaryotes, in which the spliceosome recognizes motifs at the 3' and 5' splice sites (SSs), excises introns, and ligates exons. SS recognition and pairing is often influenced by protein splicing factors (SFs) that bind to splicing regulatory elements (SREs). Here, we describe SMsplice, a fully interpretable model of pre-mRNA splicing that combines models of core SS motifs, SREs, and exonic and intronic length preferences. We learn models that predict SS locations with 83 to 86% accuracy in fish, insects, and plants and about 70% in mammals. Learned SRE motifs include both known SF binding motifs and unfamiliar motifs, and both motif classes are supported by genetic analyses. Our comparisons across species highlight similarities between non-mammals, increased reliance on intronic SREs in plant splicing, and a greater reliance on SREs in mammalian splicing.

All exons are not created equal-exon vulnerability determines the effect of exonic mutations on splicing

It is now widely accepted that aberrant splicing of constitutive exons is often caused by mutations affecting cis-acting splicing regulatory elements (SREs), but there is a misconception that all exons have an equal dependency on SREs and thus a similar vulnerability to aberrant splicing. We demonstrate that some exons are more likely to be affected by exonic splicing mutations (ESMs) due to an inherent vulnerability, which is context dependent and influenced by the strength of exon definition. We have developed VulExMap, a tool which is based on empirical data that can designate whether a constitutive exon is vulnerable. Using VulExMap, we find that only 25% of all exons can be categorized as vulnerable, whereas two-thirds of 359 previously reported ESMs in 75 disease genes are located in vulnerable exons. Because VulExMap analysis is based on empirical data on splicing of exons in their endogenous context, it includes all features important in determining the vulnerability. We believe that VulExMap will be an important tool when assessing the effect of exonic mutations by pinpointing whether they are located in exons vulnerable to ESMs.

CRISPR-dCas13d-based deep screening of proximal and distal splicing-regulatory elements

Pre-mRNA splicing, a key process in gene expression, can be therapeutically modulated using various drug modalities, including antisense oligonucleotides (ASOs). However, determining promising targets is hampered by the challenge of systematically mapping splicing-regulatory elements (SREs) in their native sequence context. Here, we use the catalytically inactive CRISPR-RfxCas13d RNA-targeting system (dCas13d/gRNA) as a programmable platform to bind SREs and modulate splicing by competing against endogenous splicing factors. SpliceRUSH, a high-throughput screening method, was developed to map SREs in any gene of interest using a lentivirus gRNA library that tiles the genetic region, including distal intronic sequences. When applied to SMN2, a therapeutic target for spinal muscular atrophy, SpliceRUSH robustly identifies not only known SREs but also a previously unknown distal intronic SRE, which can be targeted to alter exon 7 splicing using either dCas13d/gRNA or ASOs. This technology enables a deeper understanding of splicing regulation with applications for RNA-based drug discovery.

Annotation of nuclear lncRNAs based on chromatin interactions

The human genome is pervasively transcribed and produces a wide variety of long non-coding RNAs (lncRNAs), constituting the majority of transcripts across human cell types. Some specific nuclear lncRNAs have been shown to be important regulatory components acting locally. As RNA-chromatin interaction and Hi-C chromatin conformation data showed that chromatin interactions of nuclear lncRNAs are determined by the local chromatin 3D conformation, we used Hi-C data to identify potential target genes of lncRNAs. RNA-protein interaction data suggested that nuclear lncRNAs act as scaffolds to recruit regulatory proteins to target promoters and enhancers. Nuclear lncRNAs may therefore play a role in directing regulatory factors to locations spatially close to the lncRNA gene. We provide the analysis results through an interactive visualization web portal at https://fantom.gsc.riken.jp/zenbu/reports/#F6_3D_lncRNA.

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.

Identification and classification of glioma subtypes based on RNA-binding proteins

BACKGROUND

Glioma is a common and aggressive primary malignant cancer known for its high morbidity, mortality, and recurrence rates. Despite this, treatment options for glioma are currently restricted. The dysregulation of RBPs has been linked to the advancement of several types of cancer, but their precise role in glioma evolution is still not fully understood. This study sought to investigate how RBPs may impact the development and prognosis of glioma, with potential implications for prognosis and therapy.

METHODS

RNA-seq profiles of glioma and corresponding clinical data from the CGGA database were initially collected for analysis. Unsupervised clustering was utilized to identify crucial tumor subtypes in glioma development. Subsequent time-series analysis and MS model were employed to track the progression of these identified subtypes. RBPs playing a significant role in glioma progression were then pinpointed using WGCNA and Lasso Cox regression models. Functional analysis of these key RBP-related genes was conducted through GSEA. Additionally, the CIBERSORT algorithm was utilized to estimate immune infiltrating cells, while the STRING database was consulted to uncover potential mechanisms of the identified biomarkers.

RESULTS

Six tumor subgroups were identified and found to be highly homogeneous within each subgroup. The progression stages of these tumor subgroups were determined using time-series analysis and a MS model. Through WGCNA, Lasso Cox, and multivariate Cox regression analysis, it was confirmed that BCLAF1 is correlated with survival in glioma patients and is closely linked to glioma progression. Functional annotation suggests that BCLAF1 may impact glioma progression by influencing RNA splicing, which in turn affects the cell cycle, Wnt signaling pathway, and other cancer development pathways.

CONCLUSIONS

The study initially identified six subtypes of glioma progression and assessed their malignancy ranking. Furthermore, it was determined that BCLAF1 could serve as an RBP-related prognostic marker, offering significant implications for the clinical diagnosis and personalized treatment of glioma.

Neuronal activity rapidly reprograms dendritic translation via eIF4G2:uORF binding

Learning and memory require activity-induced changes in dendritic translation, but which mRNAs are involved and how they are regulated are unclear. In this study, to monitor how depolarization impacts local dendritic biology, we employed a dendritically targeted proximity labeling approach followed by crosslinking immunoprecipitation, ribosome profiling and mass spectrometry. Depolarization of primary cortical neurons with KCl or the glutamate agonist DHPG caused rapid reprogramming of dendritic protein expression, where changes in dendritic mRNAs and proteins are weakly correlated. For a subset of pre-localized messages, depolarization increased the translation of upstream open reading frames (uORFs) and their downstream coding sequences, enabling localized production of proteins involved in long-term potentiation, cell signaling and energy metabolism. This activity-dependent translation was accompanied by the phosphorylation and recruitment of the non-canonical translation initiation factor eIF4G2, and the translated uORFs were sufficient to confer depolarization-induced, eIF4G2-dependent translational control. These studies uncovered an unanticipated mechanism by which activity-dependent uORF translational control by eIF4G2 couples activity to local dendritic remodeling.

Nuclear export is a limiting factor in eukaryotic mRNA metabolism

The eukaryotic mRNA life cycle includes transcription, nuclear mRNA export and degradation. To quantify all these processes simultaneously, we perform thiol-linked alkylation after metabolic labeling of RNA with 4-thiouridine (4sU), followed by sequencing of RNA (SLAM-seq) in the nuclear and cytosolic compartments of human cancer cells. We develop a model that reliably quantifies mRNA-specific synthesis, nuclear export, and nuclear and cytosolic degradation rates on a genome-wide scale. We find that nuclear degradation of polyadenylated mRNA is negligible and nuclear mRNA export is slow, while cytosolic mRNA degradation is comparatively fast. Consequently, an mRNA molecule generally spends most of its life in the nucleus. We also observe large differences in the nuclear export rates of different 3'UTR transcript isoforms. Furthermore, we identify genes whose expression is abruptly induced upon metabolic labeling. These transcripts are exported substantially faster than average mRNAs, suggesting the existence of alternative export pathways. Our results highlight nuclear mRNA export as a limiting factor in mRNA metabolism and gene regulation.

Population genetics and phylogeographic history of the insular lizard Podarcis lilfordi (Gunther, 1874) from the Balearic Islands based on genome-wide polymorphic data

Islands provide a great system to explore the processes that maintain genetic diversity and promote local adaptation. We explored the genomic diversity of the Balearic lizard Podarcis lilfordi, an endemic species characterized by numerous small insular populations with large phenotypic diversity. Using the newly available genome for this species, we characterized more than 300,000 SNPs, merging genotyping-by-sequencing (GBS) data with previously published restriction site-associated DNA sequencing (RAD-Seq) data, providing a dataset of 16 island populations (191 individuals) across the range of species distribution (Menorca, Mallorca, and Cabrera). Results indicate that each islet hosts a well-differentiated population (F ST = 0.247 ± 0.09), with no recent immigration/translocation events. Contrary to expectations, most populations harbor a considerable genetic diversity (mean nucleotide diversity, P i = 0.144 ± 0.021), characterized by overall low inbreeding values (F IS < 0.1). While the genetic diversity significantly decreased with decreasing islet surface, maintenance of substantial genetic diversity even in tiny islets suggests variable selection or other mechanisms that buffer genetic drift. Maximum-likelihood tree based on concatenated SNP data confirmed the existence of the two major independent lineages of Menorca and Mallorca/Cabrera. Multiple lines of evidence, including admixture and root testing, robustly placed the origin of the species in the Mallorca Island, rather than in Menorca. Outlier analysis mainly retrieved a strong signature of genome differentiation between the two major archipelagos, especially in the sexual chromosome Z. A set of proteins were target of multiple outliers and primarily associated with binding and catalytic activity, providing interesting candidates for future selection studies. This study provides the framework to explore crucial aspects of the genetic basis of phenotypic divergence and insular adaptation.

Heterogenous nuclear ribonucleoprotein D-like controls endothelial cell functions

HnRNPs are ubiquitously expressed RNA-binding proteins, tightly controlling posttranscriptional gene regulation. Consequently, hnRNP networks are essential for cellular homeostasis and their dysregulation is associated with cancer and other diseases. However, the physiological function of hnRNPs in non-cancerous cell systems are poorly understood. We analyzed the importance of HNRNPDL in endothelial cell functions. Knockdown of HNRNPDL led to impaired proliferation, migration and sprouting of spheroids. Transcriptome analysis identified cyclin D1 (CCND1) and tropomyosin 4 (TPM4) as targets of HNRNPDL, reflecting the phenotypic changes after knockdown. Our findings underline the importance of HNRNPDL for the homeostasis of physiological processes in endothelial cells.

Protocol to process crosslinking and immunoprecipitation data into annotated binding sites

Here, we present a protocol for using Skipper, a pipeline designed to process crosslinking and immunoprecipitation (CLIP) data into annotated binding sites. We describe steps for partitioning annotated transcript regions and fitting data to a beta-binomial model to call windows of enriched binding. From raw CLIP data, we detail how users can map reproducible RNA-binding sites to call enriched windows and perform downstream analysis. This protocol supports optional customizations for different use cases. For complete details on the use and execution of this protocol, please refer to Boyle et al.1.

Systematic identification and characterization of exon-intron circRNAs

Exon-intron circRNAs (EIciRNAs) are a circRNA subclass with retained introns. Global features of EIciRNAs remain largely unexplored, mainly owing to the lack of bioinformatic tools. The regulation of intron retention (IR) in EIciRNAs and the associated functionality also require further investigation. We developed a framework, FEICP, which efficiently detected EIciRNAs from high-throughput sequencing (HTS) data. EIciRNAs are distinct from exonic circRNAs (EcircRNAs) in aspects such as with larger length, localization in the nucleus, high tissue specificity, and enrichment mostly in the brain. Deep learning analyses revealed that compared with regular introns, the retained introns of circRNAs (CIRs) are shorter in length, have weaker splice site strength, and have higher GC content. Compared with retained introns in linear RNAs (LIRs), CIRs are more likely to form secondary structures and show greater sequence conservation. CIRs are closer to the 5'-end, whereas LIRs are closer to the 3'-end of transcripts. EIciRNA-generating genes are more actively transcribed and associated with epigenetic marks of gene activation. Computational analyses and genome-wide CRISPR screening revealed that SRSF1 binds to CIRs and inhibits the biogenesis of most EIciRNAs. SRSF1 regulates the biogenesis of EIciLIMK1, which enhances the expression of LIMK1 in cis to boost neuronal differentiation, exemplifying EIciRNA physiological function. Overall, our study has developed the FEICP pipeline to identify EIciRNAs from HTS data, and reveals multiple features of CIRs and EIciRNAs. SRSF1 has been identified to regulate EIciRNA biogenesis. EIciRNAs and the regulation of EIciRNA biogenesis play critical roles in neuronal differentiation.

RAVER1 hinders lethal EMT and modulates miR/RISC activity by the control of alternative splicing

The RAVER1 protein serves as a co-factor in guiding the polypyrimidine tract-binding protein (PTBP)-dependent control of alternative splicing (AS). Whether RAVER1 solely acts in concert with PTBPs and how it affects cancer cell fate remained elusive. Here, we provide the first comprehensive investigation of RAVER1-controlled AS in cancer cell models. This reveals a pro-oncogenic role of RAVER1 in modulating tumor growth and epithelial-mesenchymal-transition (EMT). Splicing analyses and protein-association studies indicate that RAVER1 guides AS in association with other splicing regulators, including PTBPs and SRSFs. In cancer cells, one major function of RAVER1 is the stimulation of proliferation and restriction of apoptosis. This involves the modulation of AS events within the miR/RISC pathway. Disturbance of RAVER1 impairs miR/RISC activity resulting in severely deregulated gene expression, which promotes lethal TGFB-driven EMT. Among others, RAVER1-modulated splicing events affect the insertion of protein interaction modules in factors guiding miR/RISC-dependent gene silencing. Most prominently, in all three human TNRC6 proteins, RAVER1 controls AS of GW-enriched motifs, which are essential for AGO2-binding and the formation of active miR/RISC complexes. We propose, that RAVER1 is a key modulator of AS events in the miR/RISC pathway ensuring proper abundance and composition of miR/RISC effectors. This ensures balanced expression of TGFB signaling effectors and limits TGFB induced lethal EMT.

A circular RNA-gawky-chromatin regulatory axis modulates stress-induced transcription

In response to heavy metal stress, the RNA-binding protein (RBP) gawky translocates into the nucleus and acts as a chromatin-interacting factor to activate the transcription of many stress-responsive genes. However, the upstream regulators of gawky-mediated transcription and their mechanistic details remain unknown. Here, we identified a class of metal-responsive element-containing circRNAs (MRE circRNAs) which specifically interact with gawky during copper stress. Using classic stress-responsive genes as a readout (Drosophila MT), we found that overexpression of MRE circRNAs led to a significant repression in stress-induced transcription. Mechanistically, MRE circRNAs promote the dissociation of gawky from chromatin and increase its aberrant cytoplasmic accumulation, which ultimately impedes the loading of RNA polymerase II to the active gene loci. The MRE motif serves as an important RNA regulon for maintaining the circRNA-gawky interaction, loss of which impaired the inhibitory effects of MRE circRNAs on gawky. Through RNA-seq analyses, we then identified over 500 additional stress-responsive genes whose induced transcription was attenuated upon MRE circRNA overexpression. Finally, we uncovered the physiological relevance of MRE circRNA-mediated regulation in cellular defense against copper overloading. Taken together, this study proposes that the circRNA-RBP-chromatin axis may represent a fundamental regulatory network for gene expression in eukaryotic cells.

The RNA binding proteins LARP4A and LARP4B promote sarcoma and carcinoma growth and metastasis

RNA-binding proteins (RBPs) are emerging as important regulators of cancer pathogenesis. We reveal that the RBPs LARP4A and LARP4B are differentially overexpressed in osteosarcoma and osteosarcoma lung metastases, as well as in prostate cancer. Depletion of LARP4A and LARP4B reduced tumor growth and metastatic spread in xenografts, as well as inhibiting cell proliferation, motility, and migration. Transcriptomic profiling and high-content multiparametric analyses unveiled a central role for LARP4B, but not LARP4A, in regulating cell cycle progression in osteosarcoma and prostate cancer cells, potentially through modulating key cell cycle proteins such as Cyclins B1 and E2, Aurora B, and E2F1. This first systematic comparison between LARP4A and LARP4B assigns new pro-tumorigenic functions to LARP4A and LARP4B in bone and prostate cancer, highlighting their similarities while also indicating distinct functional differences. Uncovering clear biological roles for these paralogous proteins provides new avenues for identifying tissue-specific targets and potential druggable intervention.

RBM22 regulates RNA polymerase II 5' pausing, elongation rate, and termination by coordinating 7SK-P-TEFb complex and SPT5

BACKGROUND

Splicing factors are vital for the regulation of RNA splicing, but some have also been implicated in regulating transcription. The underlying molecular mechanisms of their involvement in transcriptional processes remain poorly understood.

RESULTS

Here, we describe a direct role of splicing factor RBM22 in coordinating multiple steps of RNA Polymerase II (RNAPII) transcription in human cells. The RBM22 protein widely occupies the RNAPII-transcribed gene locus in the nucleus. Loss of RBM22 promotes RNAPII pause release, reduces elongation velocity, and provokes transcriptional readthrough genome-wide, coupled with production of transcripts containing sequences from downstream of the gene. RBM22 preferentially binds to the hyperphosphorylated, transcriptionally engaged RNAPII and coordinates its dynamics by regulating the homeostasis of the 7SK-P-TEFb complex and the association between RNAPII and SPT5 at the chromatin level.

CONCLUSIONS

Our results uncover the multifaceted role of RBM22 in orchestrating the transcriptional program of RNAPII and provide evidence implicating a splicing factor in both RNAPII elongation kinetics and termination control.

Massively parallel screen uncovers many rare 3' UTR variants regulating mRNA abundance of cancer driver genes

Understanding the function of rare non-coding variants represents a significant challenge. Using MapUTR, a screening method, we studied the function of rare 3' UTR variants affecting mRNA abundance post-transcriptionally. Among 17,301 rare gnomAD variants, an average of 24.5% were functional, with 70% in cancer-related genes, many in critical cancer pathways. This observation motivated an interrogation of 11,929 somatic mutations, uncovering 3928 (33%) functional mutations in 155 cancer driver genes. Functional MapUTR variants were enriched in microRNA- or protein-binding sites and may underlie outlier gene expression in tumors. Further, we introduce untranslated tumor mutational burden (uTMB), a metric reflecting the amount of somatic functional MapUTR variants of a tumor and show its potential in predicting patient survival. Through prime editing, we characterized three variants in cancer-relevant genes (MFN2, FOSL2, and IRAK1), demonstrating their cancer-driving potential. Our study elucidates the function of tens of thousands of non-coding variants, nominates non-coding cancer driver mutations, and demonstrates their potential contributions to cancer.

The splicing regulators RBM5 and RBM10 are subunits of the U2 snRNP engaged with intron branch sites on chromatin

Understanding the mechanisms of pre-mRNA splicing is limited by the technical challenges to examining spliceosomes in vivo. Here, we report the isolation of RNP complexes derived from precatalytic A or B-like spliceosomes solubilized from the chromatin pellet of mammalian cell nuclei. We found that these complexes contain U2 snRNP proteins and a portion of the U2 snRNA bound with protected RNA fragments that precisely map to intronic branch sites across the transcriptome. These U2 complexes also contained the splicing regulators RBM5 and RBM10. We found RBM5 and RBM10 bound to nearly all branch site complexes and not simply those at regulated exons. The deletion of a conserved RBM5/RBM10 peptide sequence, including a zinc finger motif, disrupted U2 interaction and rendered the proteins inactive for the repression of many alternative exons. We propose a model where RBM5 and RBM10 regulate splicing as components of the U2 snRNP complex following branch site base pairing.

The je ne sais quoi of 5-methylcytosine in messenger RNA

The potential presence of 5-methylcytosine as a sparse internal modification of mRNA was first raised in 1975, and a first map of the modification was also part of the epitranscriptomics "big bang" in 2012. Since then, the evidence for its presence in mRNA has firmed up, and initial insights have been gained into the molecular function and broader biological relevance of 5-methylcytosine when present in mRNA. Here, we summarize the status quo of the field, outline some of its current challenges, and suggest how to address them in future work.

circRNAs as prognostic markers in pediatric acute myeloid leukemia

Circular RNAs (circRNAs) arise from precursor mRNA processing through back-splicing and have been increasingly recognized for their functions in various cancers including acute myeloid leukemia (AML). However, the prognostic implications of circRNA in AML remain unclear. We conducted a comprehensive genome-wide analysis of circRNAs using RNA-seq data in pediatric AML. We revealed a group of circRNAs associated with inferior outcomes, exerting effects on cancer-related pathways. Several of these circRNAs were transcribed directly from genes with established functions in AML, such as circRUNX1, circWHSC1, and circFLT3. Further investigations indicated the increased number of circRNAs and linear RNAs splicing were significantly correlated with inferior clinical outcomes, highlighting the pivotal role of splicing dysregulation. Subsequent analysis identified a group of upregulated RNA binding proteins in AMLs associated with high number of circRNAs, with TROVE2 being a prominent candidate, suggesting their involvement in circRNA associated prognosis. Through the integration of drug sensitivity data, we pinpointed 25 drugs that could target high-risk AMLs characterized by aberrant circRNA transcription. These findings underscore prognostic significance of circRNAs in pediatric AML and offer an alternative perspective for treating high-risk cases in this malignancy.

Prediction of protein-RNA interactions from single-cell transcriptomic data

Proteins are crucial in regulating every aspect of RNA life, yet understanding their interactions with coding and noncoding RNAs remains limited. Experimental studies are typically restricted to a small number of cell lines and a limited set of RNA-binding proteins (RBPs). Although computational methods based on physico-chemical principles can predict protein-RNA interactions accurately, they often lack the ability to consider cell-type-specific gene expression and the broader context of gene regulatory networks (GRNs). Here, we assess the performance of several GRN inference algorithms in predicting protein-RNA interactions from single-cell transcriptomic data, and propose a pipeline, called scRAPID (single-cell transcriptomic-based RnA Protein Interaction Detection), that integrates these methods with the catRAPID algorithm, which can identify direct physical interactions between RBPs and RNA molecules. Our approach demonstrates that RBP-RNA interactions can be predicted from single-cell transcriptomic data, with performances comparable or superior to those achieved for the well-established task of inferring transcription factor-target interactions. The incorporation of catRAPID significantly enhances the accuracy of identifying interactions, particularly with long noncoding RNAs, and enables the identification of hub RBPs and RNAs. Additionally, we show that interactions between RBPs can be detected based on their inferred RNA targets. The software is freely available at https://github.com/tartaglialabIIT/scRAPID.

Revealing the grammar of small RNA secretion using interpretable machine learning

Small non-coding RNAs can be secreted through a variety of mechanisms, including exosomal sorting, in small extracellular vesicles, and within lipoprotein complexes. However, the mechanisms that govern their sorting and secretion are not well understood. Here, we present ExoGRU, a machine learning model that predicts small RNA secretion probabilities from primary RNA sequences. We experimentally validated the performance of this model through ExoGRU-guided mutagenesis and synthetic RNA sequence analysis. Additionally, we used ExoGRU to reveal cis and trans factors that underlie small RNA secretion, including known and novel RNA-binding proteins (RBPs), e.g., YBX1, HNRNPA2B1, and RBM24. We also developed a novel technique called exoCLIP, which reveals the RNA interactome of RBPs within the cell-free space. Together, our results demonstrate the power of machine learning in revealing novel biological mechanisms. In addition to providing deeper insight into small RNA secretion, this knowledge can be leveraged in therapeutic and synthetic biology applications.

Denaturing purifications demonstrate that PRC2 and other widely reported chromatin proteins do not appear to bind directly to RNA in vivo

Polycomb repressive complex 2 (PRC2) is reported to bind to many RNAs and has become a central player in reports of how long non-coding RNAs (lncRNAs) regulate gene expression. Yet, there is a growing discrepancy between the biochemical evidence supporting specific lncRNA-PRC2 interactions and functional evidence demonstrating that PRC2 is often dispensable for lncRNA function. Here, we revisit the evidence supporting RNA binding by PRC2 and show that many reported interactions may not occur in vivo. Using denaturing purification of in vivo crosslinked RNA-protein complexes in human and mouse cell lines, we observe a loss of detectable RNA binding to PRC2 and chromatin-associated proteins previously reported to bind RNA (CTCF, YY1, and others), despite accurately mapping bona fide RNA-binding sites across others (SPEN, TET2, and others). Taken together, these results argue for a critical re-evaluation of the broad role of RNA binding to orchestrate various chromatin regulatory mechanisms.

Mapping protein-RNA binding in plants with individual-nucleotide-resolution UV cross-linking and immunoprecipitation (plant iCLIP2)

Despite crucial roles of RNA-binding proteins (RBPs) in plant physiology and development, methods for determining their transcriptome-wide binding landscape are less developed than those used in other model organisms. Cross-linking and immunoprecipitation (CLIP) methods (based on UV-mediated generation of covalent bonds between RNAs and cognate RBPs in vivo, purification of the cross-linked complexes and identification of the co-purified RNAs by high-throughput sequencing) have been applied mainly in mammalian cells growing in monolayers or in translucent tissue. We have developed plant iCLIP2, an efficient protocol for performing individual-nucleotide-resolution CLIP (iCLIP) in plants, tailored to overcome the experimental hurdles posed by plant tissue. We optimized the UV dosage to efficiently cross-link RNA and proteins in plants and expressed epitope-tagged RBPs under the control of their native promoters in loss-of-function mutants. We select epitopes for which nanobodies are available, allowing stringent conditions for immunopurification of the RNA-protein complexes to be established. To overcome the inherently high RNase content of plant cells, RNase inhibitors are added and the limited RNA fragmentation step is modified. We combine the optimized isolation of RBP-bound RNAs with iCLIP2, a streamlined protocol that greatly enhances the efficiency of library preparation for high-throughput sequencing. Plant researchers with experience in molecular biology and handling of RNA can complete this iCLIP2 protocol in ~5 d. Finally, we describe a bioinformatics workflow to determine targets of Arabidopsis RBPs from iCLIP data, covering all steps from downloading sequencing reads to identifying cross-linking events ( https://github.com/malewins/Plant-iCLIPseq ), and present the R/Bioconductor package BindingSiteFinder to extract reproducible binding sites ( https://bioconductor.org/packages/release/bioc/html/BindingSiteFinder.html ).

rMATS-turbo: an efficient and flexible computational tool for alternative splicing analysis of large-scale RNA-seq data

Pre-mRNA alternative splicing is a prevalent mechanism for diversifying eukaryotic transcriptomes and proteomes. Regulated alternative splicing plays a role in many biological processes, and dysregulated alternative splicing is a feature of many human diseases. Short-read RNA sequencing (RNA-seq) is now the standard approach for transcriptome-wide analysis of alternative splicing. Since 2011, our laboratory has developed and maintained Replicate Multivariate Analysis of Transcript Splicing (rMATS), a computational tool for discovering and quantifying alternative splicing events from RNA-seq data. Here we provide a protocol for the contemporary version of rMATS, rMATS-turbo, a fast and scalable re-implementation that maintains the statistical framework and user interface of the original rMATS software, while incorporating a revamped computational workflow with a substantial improvement in speed and data storage efficiency. The rMATS-turbo software scales up to massive RNA-seq datasets with tens of thousands of samples. To illustrate the utility of rMATS-turbo, we describe two representative application scenarios. First, we describe a broadly applicable two-group comparison to identify differential alternative splicing events between two sample groups, including both annotated and novel alternative splicing events. Second, we describe a quantitative analysis of alternative splicing in a large-scale RNA-seq dataset (~1,000 samples), including the discovery of alternative splicing events associated with distinct cell states. We detail the workflow and features of rMATS-turbo that enable efficient parallel processing and analysis of large-scale RNA-seq datasets on a compute cluster. We anticipate that this protocol will help the broad user base of rMATS-turbo make the best use of this software for studying alternative splicing in diverse biological systems.

The leader RNA of SARS-CoV-2 sequesters polypyrimidine tract binding protein (PTBP1) and influences pre-mRNA splicing in infected cells

The large amount of viral RNA produced during infections has the potential to interact with and effectively sequester cellular RNA binding proteins, thereby influencing aspects of post-transcriptional gene regulation in the infected cell. Here we demonstrate that the abundant 5' leader RNA region of SARS-CoV-2 viral RNAs can interact with the cellular polypyrimidine tract binding protein (PTBP1). Interestingly, the effect of a knockdown of PTBP1 protein on cellular gene expression is also mimicked during SARS-CoV-2 infection, suggesting that this protein may be functionally sequestered by viral RNAs. Consistent with this model, the alternative splicing of mRNAs that is normally controlled by PTBP1 is dysregulated during SARS-CoV-2 infection. Collectively, these data suggest that the SARS-CoV-2 leader RNA sequesters the cellular PTBP1 protein during infection, resulting in significant impacts on the RNA biology of the host cell. These alterations in post-transcriptional gene regulation may play a role in SARS-CoV-2 mediated molecular pathogenesis.

Translation machinery: the basis of translational control

Messenger RNA (mRNA) translation consists of initiation, elongation, termination, and ribosome recycling, carried out by the translation machinery, primarily including tRNAs, ribosomes, and translation factors (TrFs). Translational regulators transduce signals of growth and development, as well as biotic and abiotic stresses, to the translation machinery, where global or selective translational control occurs to modulate mRNA translation efficiency (TrE). As the basis of translational control, the translation machinery directly determines the quality and quantity of newly synthesized peptides and, ultimately, the cellular adaption. Thus, regulating the availability of diverse machinery components is reviewed as the central strategy of translational control. We provide classical signaling pathways (e.g., integrated stress responses) and cellular behaviors (e.g., liquid-liquid phase separation) to exemplify this strategy within different physiological contexts, particularly during host-microbe interactions. With new technologies developed, further understanding this strategy will speed up translational medicine and translational agriculture.

The role and mechanism of RNA-binding proteins in bone metabolism and osteoporosis

Osteoporosis is a prevalent chronic metabolic bone disease that poses a significant risk of fractures or mortality in elderly individuals. Its pathophysiological basis is often attributed to postmenopausal estrogen deficiency and natural aging, making the progression of primary osteoporosis among elderly people, especially older women, seemingly inevitable. The treatment and prevention of osteoporosis progression have been extensively discussed. Recently, as researchers delve deeper into the molecular biological mechanisms of bone remodeling, they have come to realize the crucial role of posttranscriptional gene control in bone metabolism homeostasis. RNA-binding proteins, as essential actors in posttranscriptional activities, may exert influence on osteoporosis progression by regulating the RNA life cycle. This review compiles recent findings on the involvement of RNA-binding proteins in abnormal bone metabolism in osteoporosis and describes the impact of some key RNA-binding proteins on bone metabolism regulation. Additionally, we explore the potential and rationale for modulating RNA-binding proteins as a means of treating osteoporosis, with an overview of drugs that target these proteins.

Are non-protein coding RNAs junk or treasure?: An attempt to explain and reconcile opposing viewpoints of whether the human genome is mostly transcribed into non-functional or functional RNAs

The human genome project's lasting legacies are the emerging insights into human physiology and disease, and the ascendance of biology as the dominant science of the 21st century. Sequencing revealed that >90% of the human genome is not coding for proteins, as originally thought, but rather is overwhelmingly transcribed into non-protein coding, or non-coding, RNAs (ncRNAs). This discovery initially led to the hypothesis that most genomic DNA is "junk", a term still championed by some geneticists and evolutionary biologists. In contrast, molecular biologists and biochemists studying the vast number of transcripts produced from most of this genome "junk" often surmise that these ncRNAs have biological significance. What gives? This essay contrasts the two opposing, extant viewpoints, aiming to explain their bases, which arise from distinct reference frames of the underlying scientific disciplines. Finally, it aims to reconcile these divergent mindsets in hopes of stimulating synergy between scientific fields.

Spermatid perinuclear RNA-binding protein promotes UBR5-mediated proteolysis of Dicer to accelerate triple-negative breast cancer progression

Triple-negative breast cancer (TNBC) is the most lethal subtype of breast cancer with no targeted therapy. Spermatid perinuclear RNA binding protein (STRBP), a poorly characterized RNA-binding protein (RBP), has an essential role in normal spermatogenesis and sperm function, but whether and how its dysregulation contributing to cancer progression has not yet been explored. Here, we report that STRBP functions as a novel oncogene to drive TNBC progression. STRBP expression was upregulated in TNBC tissues and correlated with poor disease prognosis. Functionally, STRBP promoted TNBC cell proliferation, migration, and invasion in vitro, and enhanced xenograft tumor growth and lung colonization in mice. Mechanistically, STRBP interacted with Dicer, a core component of the microRNA biogenesis machinery, and promoted its proteasomal degradation through enhancing its interaction with E3 ubiquitin ligase UBR5. MicroRNA-sequencing analysis identified miR-200a-3p as a downstream effector of STRBP, which was regulated by Dicer and affected epithelial-mesenchymal transition. Importantly, the impaired malignant phenotypes of TNBC cells caused by STRBP depletion were largely rescued by knockdown of Dicer, and these effects were compromised by transfection of miR-200a-3p mimics. Collectively, these findings revealed a previously unrecognized oncogenic role of STRBP in TNBC progression and identified STRBP as a promising target against TNBC.

MicroRNAs in Pancreatic Cancer: Advances in Biomarker Discovery and Therapeutic Implications

Pancreatic cancer remains a formidable malignancy characterized by high mortality rates, primarily attributable to late-stage diagnosis and a dearth of effective therapeutic interventions. The identification of reliable biomarkers holds paramount importance in enhancing early detection, prognostic evaluation, and targeted treatment modalities. Small non-coding RNAs, particularly microRNAs, have emerged as promising candidates for pancreatic cancer biomarkers in recent years. In this review, we delve into the evolving role of cellular and circulating miRNAs, including exosomal miRNAs, in the diagnosis, prognosis, and therapeutic targeting of pancreatic cancer. Drawing upon the latest research advancements in omics data-driven biomarker discovery, we also perform a case study using public datasets and address commonly identified research discrepancies, challenges, and limitations. Lastly, we discuss analytical approaches that integrate multimodal analyses incorporating clinical and molecular features, presenting new insights into identifying robust miRNA-centric biomarkers.