ATtRACT-a database of RNA-binding proteins and associated motifs

A searchable atlas of pathogen-sensitive lncRNA networks in human macrophages

Long noncoding RNAs (lncRNA) are crucial yet underexplored regulators of human immunity. Here we develop GRADR, a method integrating gradient profiling with RNA-binding proteome analysis, to map the protein interactomes of all expressed RNAs in a single experiment to study mechanisms of lncRNA-mediated regulation of human primary macrophages. Applying GRADR alongside CRISPR-multiomics, we reveal a network of NFκB-dependent lncRNAs, including LINC01215, AC022816.1 and ROCKI, which modulate distinct aspects of macrophage immunity, particularly through interactions with mRNA-processing factors, such as hnRNP proteins. We further uncover the function of ROCKI in repressing the messenger of the anti-inflammatory GATA2 transcription factor, thus promoting macrophage activation. Lastly, all data are consolidated in the SMyLR web interface, a searchable reference catalog for exploring lncRNA functions and pathway-dependencies in immune cells. Our results thus not only highlight the important functions of lncRNAs in immune regulation, but also provide a rich resource for lncRNA studies.

Multi-dimensional characterization of cellular states reveals clinically relevant immunological subtypes and therapeutic vulnerabilities in ovarian cancer

BACKGROUND

Diverse cell types and cellular states in the tumor microenvironment (TME) are drivers of biological and therapeutic heterogeneity in ovarian cancer (OV). Characterization of the diverse malignant and immunology cellular states that make up the TME and their associations with clinical outcomes are critical for cancer therapy. However, we are still lack of knowledge about the cellular states and their clinical relevance in OV.

METHODS

We manually collected the comprehensive transcriptomes of OV samples and characterized the cellular states and ecotypes based on a machine-learning framework. The robustness of the cellular states was validated in independent cohorts and single-cell transcriptomes. The functions and regulators of cellular states were investigated. Meanwhile, we thoroughly examined the associations between cellular states and various clinical factors, including clinical prognosis and drug responses.

RESULTS

We depicted and characterized an immunophenotypic landscape of 3,099 OV samples and 80,044 cells based on a machine learning framework. We identified and validated 32 distinct transcriptionally defined cellular states from 12 cell types and three cellular communities or ecotypes, extending the current immunological subtypes in OV. Functional enrichment and upstream transcriptional regulator analyses revealed cancer hallmark-related pathways and potential immunological biomarkers. We further investigated the spatial patterns of identified cellular states by integrating the spatially resolved transcriptomes. Moreover, prognostic landscape and drug sensitivity analysis exhibited clinically relevant immunological subtypes and therapeutic vulnerabilities.

CONCLUSION

Our comprehensive analysis of TME helps leveraging various immunological subtypes to highlight new directions and targets for the treatment of cancer.

RBPsuite 2.0: an updated RNA-protein binding site prediction suite with high coverage on species and proteins based on deep learning

BACKGROUND

RNA-binding proteins (RBPs) play crucial roles in many biological processes, and computationally identifying RNA-RBP interactions provides insights into the biological mechanism of diseases associated with RBPs.

RESULTS

To make the RBP-specific deep learning-based RBP binding sites prediction methods easily accessible, we developed an updated easy-to-use webserver, RBPsuite 2.0, with an updated web interface for predicting RBP binding sites from linear and circular RNA sequences. RBPsuite 2.0 has a higher coverage on the number of supported RBPs and species compared to the original RBPsuite, supporting an increased number of RBPs from 154 to 353 and expanding the supported species from one to seven. Additionally, RBPsuite 2.0 replaces the CRIP built into RBPsuite 1.0 with iDeepC, a more accurate RBP binding site predictor for circular RNAs. Furthermore, RBPsuite 2.0 estimates the contribution score of individual nucleotides on the input sequences as potential binding motifs and links to the UCSC browser track for better visualization of the prediction results.

CONCLUSIONS

RBPsuite 2.0 is an updated, more comprehensive webserver for predicting RBP binding sites in both linear and circular RNA sequences. It supports more RBPs and species and provides more accurate predictions for circular RNAs. The tool is freely available at http://www.csbio.sjtu.edu.cn/bioinf/RBPsuite/ .

Inverted Alu repeats in loop-out exon skipping across hominoid evolution

Background

Changes in RNA splicing over the course of evolution have profoundly diversified the functional landscape of the human genome. While DNA sequences proximal to intron-exon junctions are known to be critical for RNA splicing, the impact of distal intronic sequences remains underexplored. Emerging evidence suggests that inverted pairs of intronic Alu elements can promote exon skipping by forming RNA stem-loop structures. However, their prevalence and influence throughout evolution remain unknown.

Results

Here, we present a systematic analysis of inverted Alu pairs across the human genome to assess their impact on exon skipping through predicted RNA stem-loop formation and their relevance to hominoid evolution. We found that inverted Alu pairs, particularly pairs of AluY-AluSx1 and AluSz-AluSx, are enriched in the flanking regions of skippable exons genome-wide and are predicted to form stable stem-loop structures. Exons defined by weak 3' acceptor and strong 5' donor splice sites appear especially prone to this skipping mechanism. Through comparative genome analysis across nine primate species, we identified 67,126 hominoid-specific Alu insertions, primarily from AluY and AluS subfamilies, which form inverted pairs enriched across skippable exons in genes of ubiquitination-related pathways. Experimental validation of exon skipping among several hominoid-specific inverted Alu pairs further reinforced their potential evolutionary significance.

Conclusion

This work extends our current knowledge of the roles of RNA secondary structure formed by inverted Alu pairs and details a newly emerging mechanism through which transposable elements have contributed to genomic innovation across hominoid evolution at the transcriptomic level.

Multiplexed assays of human disease-relevant mutations reveal UTR dinucleotide composition as a major determinant of RNA stability

Untranslated regions (UTRs) contain crucial regulatory elements for RNA stability, translation and localization, so their integrity is indispensable for gene expression. Approximately 3.7% of genetic variants associated with diseases occur in UTRs, yet a comprehensive understanding of UTR variant functions remains limited due to inefficient experimental and computational assessment methods. To systematically evaluate the effects of UTR variants on RNA stability, we established a massively parallel reporter assay on 6555 UTR variants reported in human disease databases. We examined the RNA degradation patterns mediated by the UTR library in two cell lines, and then applied LASSO regression to model the influential regulators of RNA stability. We found that UA dinucleotides and UA-rich motifs are the most prominent destabilizing element. Gain of UA dinucleotide outlined mutant UTRs with reduced stability. Studies on endogenous transcripts indicate that high UA-dinucleotide ratios in UTRs promote RNA degradation. Conversely, elevated GC content and protein binding on UA dinucleotides protect high-UA RNA from degradation. Further analysis reveals polarized roles of UA-dinucleotide-binding proteins in RNA protection and degradation. Furthermore, the UA-dinucleotide ratio of both UTRs is a common characteristic of genes in innate immune response pathways, implying a coordinated stability regulation through UTRs at the transcriptomic level. We also demonstrate that stability-altering UTRs are associated with changes in biobank-based health indices, underscoring the importance of precise UTR regulation for wellness. Our study highlights the importance of RNA stability regulation through UTR primary sequences, paving the way for further exploration of their implications in gene networks and precision medicine.

RNA sequence analysis landscape: A comprehensive review of task types, databases, datasets, word embedding methods, and language models

Deciphering information of RNA sequences reveals their diverse roles in living organisms, including gene regulation and protein synthesis. Aberrations in RNA sequence such as dysregulation and mutations can drive a diverse spectrum of diseases including cancers, genetic disorders, and neurodegenerative conditions. Furthermore, researchers are harnessing RNA's therapeutic potential for transforming traditional treatment paradigms into personalized therapies through the development of RNA-based drugs and gene therapies. To gain insights of biological functions and to detect diseases at early stages and develop potent therapeutics, researchers are performing diverse types RNA sequence analysis tasks. RNA sequence analysis through conventional wet-lab methods is expensive, time-consuming and error prone. To enable large-scale RNA sequence analysis, empowerment of wet-lab experimental methods with Artificial Intelligence (AI) applications necessitates scientists to have a comprehensive knowledge of both DNA and AI fields. While molecular biologists encounter challenges in understanding AI methods, computer scientists often lack basic foundations of RNA sequence analysis tasks. Considering the absence of a comprehensive literature that bridges this research gap and promotes the development of AI-driven RNA sequence analysis applications, the contributions of this manuscript are manifold: It equips AI researchers with biological foundations of 47 distinct RNA sequence analysis tasks. It sets a stage for development of benchmark datasets related to 47 distinct RNA sequence analysis tasks by facilitating cruxes of 64 different biological databases. It presents word embeddings and language models applications across 47 distinct RNA sequence analysis tasks. It streamlines the development of new predictors by providing a comprehensive survey of 58 word embeddings and 70 language models based predictive pipelines performance values as well as top performing traditional sequence encoding based predictors and their performances across 47 RNA sequence analysis tasks.

RNA splicing controls organ-wide maturation of postnatal heart in mice

Postnatal cardiac development requires the orchestrated maturation of diverse cellular components for which unifying control mechanisms are still lacking. Using full-length sequencing, we examined the transcriptomic landscape of the maturating mouse heart (E18.5-P28) at single-cell and transcript isoform resolution. We identified dynamically changing intercellular networks as a molecular basis of the maturing heart and alternative splicing (AS) as a common mechanism that distinguished developmental age. Manipulation of RNA-binding proteins (RBPs) remodeled the AS landscape, cardiac cell maturation, and intercellular communication through direct binding of splice targets, which were enriched for functions related to general, as well as cell-type-specific, maturation. Overexpression of an RBP nuclear cap-binding protein subunit 2 (NCBP2) in neonatal hearts repressed cardiac maturation. Together, our data suggest AS regulation by RBPs as an organ-level control mechanism in mammalian postnatal cardiac development and provide insight into the possibility of manipulating RBPs for therapeutic purposes.

A deep learning model for characterizing protein-RNA interactions from sequences at single-base resolution

Protein-RNA interactions play pivotal roles in regulating transcription, translation, and RNA metabolism. Characterizing these interactions offers key insights into RNA dysregulation mechanisms. Here, we introduce Reformer, a deep learning model that predicts protein-RNA binding affinity from sequence data. Trained on 225 enhanced cross-linking and immunoprecipitation sequencing (eCLIP-seq) datasets encompassing 155 RNA-binding proteins across three cell lines, Reformer achieves high accuracy in predicting binding affinity at single-base resolution. The model uncovers binding motifs that are often undetectable through traditional eCLIP-seq methods. Notably, the motifs learned by Reformer are shown to correlate with RNA processing functions. Validation via electrophoretic mobility shift assays confirms the model's precision in quantifying the impact of mutations on RNA regulation. In summary, Reformer improves the resolution of RNA-protein interaction predictions and aids in prioritizing mutations that influence RNA regulation.

RBPWorld for exploring functions and disease associations of RNA-binding proteins across species

RNA-binding proteins (RBPs) play key roles in a wide range of physiological and pathological processes. To facilitate the investigation of RBP functions and disease associations, we updated the EuRBPDB and renamed it as RBPWorld (http://research.gzsys.org.cn/rbpworld/#/home). Leveraging 998 RNA-binding domains (RBDs) and 87 RNA-binding Proteome (RBPome) datasets, we successfully identified 1 393 413 RBPs from 445 species, including 3030 human RBPs (hRBPs). RBPWorld includes primary RNA targets of diverse hRBPs, as well as potential downstream regulatory pathways and alternative splicing patterns governed by various hRBPs. These insights were derived from analyses of 1515 crosslinking immunoprecipitation-seq datasets and 616 RNA-seq datasets from cells with hRBP gene knockdown or knockout. Furthermore, we systematically identified 929 RBPs with multi-functions, including acting as metabolic enzymes and transcription factors. RBPWorld includes 838 disease-associated hRBPs and 970 hRBPs that interact with 12 disease-causing RNA viruses. This provision allows users to explore the regulatory roles of hRBPs within the context of diseases. Finally, we developed an intuitive interface for RBPWorld, facilitating users easily access all the included data. We believe that RBPWorld will be a valuable resource in advancing our understanding of the biological roles of RBPs across different species.

SpliceTransformer predicts tissue-specific splicing linked to human diseases

We present SpliceTransformer (SpTransformer), a deep-learning framework that predicts tissue-specific RNA splicing alterations linked to human diseases based on genomic sequence. SpTransformer outperforms all previous methods on splicing prediction. Application to approximately 1.3 million genetic variants in the ClinVar database reveals that splicing alterations account for 60% of intronic and synonymous pathogenic mutations, and occur at different frequencies across tissue types. Importantly, tissue-specific splicing alterations match their clinical manifestations independent of gene expression variation. We validate the enrichment in three brain disease datasets involving over 164,000 individuals. Additionally, we identify single nucleotide variations that cause brain-specific splicing alterations, and find disease-associated genes harboring these single nucleotide variations with distinct expression patterns involved in diverse biological processes. Finally, SpTransformer analysis of whole exon sequencing data from blood samples of patients with diabetic nephropathy predicts kidney-specific RNA splicing alterations with 83% accuracy, demonstrating the potential to infer disease-causing tissue-specific splicing events. SpTransformer provides a powerful tool to guide biological and clinical interpretations of human diseases.

Study of the RNA splicing kinetics via in vivo 5-EU labeling

Splicing is an important step of gene expression in all eukaryotes. Splice sites might be used with different efficiency, giving rise to alternative splicing products. At the same time, splice sites might be used at a variable rate. We used 5-ethynyl uridine labeling to sequence a nascent transcriptome of HeLa cells and deduced the rate of splicing for each donor and acceptor splice site. The following correlation analysis showed a correspondence of primary transcript features with the rate of splicing. Some dependencies we revealed were anticipated, such as a splicing rate decrease with a decreased complementarity of the donor splice site to U1 and acceptor sites to U2 snRNAs. Other dependencies were more surprising, like a negative influence of a distance to the 5' end on the rate of the acceptor splicing site utilization, or the differences in splicing rate between long, short, and RBM17-dependent introns. We also observed a deceleration of last intron splicing with an increase of the distance to the poly(A) site, which might be explained by the cooperativity of the splicing and polyadenylation. Additional analysis of splicing kinetics of SF3B4 knockdown cells suggested the impairment of a U2 snRNA recognition step. As a result, we deconvoluted the effects of several examined features on the splicing rate into a single regression model. The data obtained here are useful for further studies in the field, as they provide general splicing rate dependencies as well as help to justify the existence of slowly removed splice sites.

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.

CanCellVar: A database for single-cell variants map in human cancer

Numerous variants, including both single-nucleotide variants (SNVs) in DNA and A>G RNA edits in mRNA as essential drivers of cellular proliferation and tumorigenesis, are commonly associated with cancer progression and growth. Thus, mining and summarizing single-cell variants will provide a refined and higher-resolution view of cancer and further contribute to precision medicine. Here, we established a database, CanCellVar, which aims to provide and visualize the comprehensive atlas of single-cell variants in tumor microenvironment. The current CanCellVar identified ∼3 million variants (∼1.4 million SNVs and ∼1.4 million A>G RNA edits) involved in 2,754,531 cells of 5 major cell types across 37 cancer types. CanCellVar provides the basic annotation information as well as cellular and molecular function properties of variants. In addition, the clinical relevance of variants can be obtained including tumor grade, treatment, metastasis, and others. Several flexible tools were also developed to aid retrieval and to analyze cell-cell interactions, gene expression, cell-development trajectories, regulation, and molecular structure affected by variants. Collectively, CanCellVar will serve as a valuable resource for investigating the functions and characteristics of single-cell variations and their roles in human tumor evolution and treatment.

Gene and protein sequence features augment HLA class I ligand predictions

The sensitivity of malignant tissues to T cell-based immunotherapies depends on the presence of targetable human leukocyte antigen (HLA) class I ligands. Peptide-intrinsic factors, such as HLA class I affinity and proteasomal processing, have been established as determinants of HLA ligand presentation. However, the role of gene and protein sequence features as determinants of epitope presentation has not been systematically evaluated. We perform HLA ligandome mass spectrometry to evaluate the contribution of 7,135 gene and protein sequence features to HLA sampling. This analysis reveals that a number of predicted modifiers of mRNA and protein abundance and turnover, including predicted mRNA methylation and protein ubiquitination sites, inform on the presence of HLA ligands. Importantly, integration of such "hard-coded" sequence features into a machine learning approach augments HLA ligand predictions to a comparable degree as experimental measures of gene expression. Our study highlights the value of gene and protein features for HLA ligand predictions.

Altered nucleocytoplasmic export of adenosine-rich circRNAs by PABPC1 contributes to neuronal function

Circular RNAs (circRNAs) are upregulated during neurogenesis. Where and how circRNAs are localized and what roles they play during this process have remained elusive. Comparing the nuclear and cytoplasmic circRNAs between H9 cells and H9-derived forebrain (FB) neurons, we identify that a subset of adenosine (A)-rich circRNAs are restricted in H9 nuclei but exported to cytosols upon differentiation. Such a subcellular relocation of circRNAs is modulated by the poly(A)-binding protein PABPC1. In the H9 nucleus, newly produced (A)-rich circRNAs are bound by PABPC1 and trapped by the nuclear basket protein TPR to prevent their export. Modulating (A)-rich motifs in circRNAs alters their subcellular localization, and introducing (A)-rich circRNAs in H9 cytosols results in mRNA translation suppression. Moreover, decreased nuclear PABPC1 upon neuronal differentiation enables the export of (A)-rich circRNAs, including circRTN4(2,3), which is required for neurite outgrowth. These findings uncover subcellular localization features of circRNAs, linking their processing and function during neurogenesis.

Characterization of trans-spliced chimeric RNAs: insights into the mechanism of trans-splicing

Trans-splicing is a post-transcriptional processing event that joins exons from separate RNAs to produce a chimeric RNA. However, the detailed mechanism of trans-splicing remains poorly understood. Here, we characterize trans-spliced genes and provide insights into the mechanism of trans-splicing in the tunicate Ciona. Tunicates are the closest invertebrates to humans, and their genes frequently undergo trans-splicing. Our analysis revealed that, in genes that give rise to both trans-spliced and non-trans-spliced messenger RNAs, trans-splice acceptor sites were preferentially located at the first functional acceptor site, and their paired donor sites were weak in both Ciona and humans. Additionally, we found that Ciona trans-spliced genes had GU- and AU-rich 5' transcribed regions. Our data and findings not only are useful for Ciona research community, but may also aid in a better understanding of the trans-splicing mechanism, potentially advancing the development of gene therapy based on trans-splicing.

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.

Human brain small extracellular vesicles contain selectively packaged, full-length mRNA

Brain cells release and take up small extracellular vesicles (sEVs) containing bioactive nucleic acids. sEV exchange is hypothesized to contribute to stereotyped spread of neuropathological changes in the diseased brain. We assess mRNA from sEVs of postmortem brain from non-diseased (ND) individuals and those with Alzheimer's disease (AD) using short- and long-read sequencing. sEV transcriptomes are distinct from those of bulk tissue, showing enrichment for genes including mRNAs encoding ribosomal proteins and transposable elements such as human-specific LINE-1 (L1Hs). AD versus ND sEVs show enrichment of inflammation-related mRNAs and depletion of synaptic signaling mRNAs. sEV mRNAs from cultured murine primary neurons, astrocytes, or microglia show similarities to human brain sEVs and reveal cell-type-specific packaging. Approximately 80% of neural sEV transcripts sequenced using long-read sequencing are full length. Motif analyses of sEV-enriched isoforms elucidate RNA-binding proteins that may be associated with sEV loading. Collectively, we show that mRNA in brain sEVs is intact, selectively packaged, and altered in disease.

RNA Binding Proteins that Mediate LPS-induced Alternative Splicing of the MyD88 Innate Immune Regulator

Inflammation driven by Toll-like receptor (TLR) signaling pathways is required to combat infection. However, inflammation can damage host tissues; thus it is essential that TLR signaling ultimately is terminated to prevent chronic inflammatory disorders. One mechanism that terminates persistent TLR signaling is alternative splicing of the MyD88 signaling adaptor, which functions in multiple TLR signaling pathways. While the canonical long isoform of MyD88 (MyD88-L) mediates TLR signaling and promotes inflammation, an alternatively-spliced shorter isoform of MyD88 (MyD88-S) produces a dominant negative inhibitor of TLR signaling. MyD88-S production is induced by inflammatory agonists including lipopolysaccharide (LPS), and thus MyD88-S induction is thought to act as a negative feedback loop that prevents chronic inflammation. Despite the potential role that MyD88-S production plays in inflammatory disorders, the mechanisms controlling MyD88 alternative splicing remain unclear. Here, we identify two RNA binding proteins, SRSF1 and HNRNPU, that regulate LPS-induced alternative splicing of MyD88.

Hammerhead-type FXR agonists induce an enhancer RNA Fincor that ameliorates nonalcoholic steatohepatitis in mice

The nuclear receptor, farnesoid X receptor (FXR/NR1H4), is increasingly recognized as a promising drug target for metabolic diseases, including nonalcoholic steatohepatitis (NASH). Protein-coding genes regulated by FXR are well known, but whether FXR also acts through regulation of long non-coding RNAs (lncRNAs), which vastly outnumber protein-coding genes, remains unknown. Utilizing RNA-seq and global run-on sequencing (GRO-seq) analyses in mouse liver, we found that FXR activation affects the expression of many RNA transcripts from chromatin regions bearing enhancer features. Among these we discovered a previously unannotated liver-enriched enhancer-derived lncRNA (eRNA), termed FXR-induced non-coding RNA (Fincor). We show that Fincor is specifically induced by the hammerhead-type FXR agonists, including GW4064 and tropifexor. CRISPR/Cas9-mediated liver-specific knockdown of Fincor in dietary NASH mice reduced the beneficial effects of tropifexor, an FXR agonist currently in clinical trials for NASH and primary biliary cholangitis (PBC), indicating that amelioration of liver fibrosis and inflammation in NASH treatment by tropifexor is mediated in part by Fincor. Overall, our findings highlight that pharmacological activation of FXR by hammerhead-type agonists induces a novel eRNA, Fincor, contributing to the amelioration of NASH in mice. Fincor may represent a new drug target for addressing metabolic disorders, including NASH.

Biosensing circulating MicroRNAs in autoinflammatory skin diseases: Focus on Hidradenitis suppurativa

MicroRNAs (miRNAs) play a crucial role in the early diagnosis of autoinflammatory diseases, with Hidradenitis Suppurativa (HS) being a notable example. HS, an autoinflammatory skin disease affecting the pilosebaceous unit, profoundly impacts patients' quality of life. Its hidden nature, with insidious initial symptoms and patient reluctance to seek medical consultation, often leads to a diagnostic delay of up to 7 years. Recognizing the urgency for early diagnostic tools, recent research identified significant differences in circulating miRNA expression, including miR-24-1-5p, miR-146a-5p, miR26a-5p, miR-206, miR338-3p, and miR-338-5p, between HS patients and healthy controls. These miRNAs serve as potential biomarkers for earlier disease detection. Traditional molecular biology techniques, like reverse transcription quantitative-polymerase chain reaction (RT-qPCR), are employed for their detection using specific primers and probes. Alternatively, short peptides offer a versatile and effective means for capturing miRNAs, providing specificity, ease of synthesis, stability, and multiplexing potential. In this context, we present a computational simulation pipeline designed for crafting peptide sequences that can capture circulating miRNAs in the blood of patients with autoinflammatory skin diseases, including HS. This innovative approach aims to expedite early diagnosis and enhance therapeutic follow-up, addressing the critical need for timely intervention in HS and similar conditions.

Improving the performance of supervised deep learning for regulatory genomics using phylogenetic augmentation

MOTIVATION

Supervised deep learning is used to model the complex relationship between genomic sequence and regulatory function. Understanding how these models make predictions can provide biological insight into regulatory functions. Given the complexity of the sequence to regulatory function mapping (the cis-regulatory code), it has been suggested that the genome contains insufficient sequence variation to train models with suitable complexity. Data augmentation is a widely used approach to increase the data variation available for model training, however current data augmentation methods for genomic sequence data are limited.

RESULTS

Inspired by the success of comparative genomics, we show that augmenting genomic sequences with evolutionarily related sequences from other species, which we term phylogenetic augmentation, improves the performance of deep learning models trained on regulatory genomic sequences to predict high-throughput functional assay measurements. Additionally, we show that phylogenetic augmentation can rescue model performance when the training set is down-sampled and permits deep learning on a real-world small dataset, demonstrating that this approach improves data efficiency. Overall, this data augmentation method represents a solution for improving model performance that is applicable to many supervised deep-learning problems in genomics.

AVAILABILITY AND IMPLEMENTATION

The open-source GitHub repository agduncan94/phylogenetic_augmentation_paper includes the code for rerunning the analyses here and recreating the figures.

An extended wave of global mRNA deadenylation sets up a switch in translation regulation across the mammalian oocyte-to-embryo transition

Without new transcription, gene expression across the oocyte-to-embryo transition (OET) relies instead on regulation of mRNA poly(A) tails to control translation. However, how tail dynamics shape translation across the OET in mammals remains unclear. We perform long-read RNA sequencing to uncover poly(A) tail lengths across the mouse OET and, incorporating published ribosome profiling data, provide an integrated, transcriptome-wide analysis of poly(A) tails and translation across the entire transition. We uncover an extended wave of global deadenylation during fertilization in which short-tailed, oocyte-deposited mRNAs are translationally activated without polyadenylation through resistance to deadenylation. Subsequently, in the embryo, mRNAs are readenylated and translated in a surge of global polyadenylation. We further identify regulation of poly(A) tail length at the isoform level and stage-specific enrichment of mRNA sequence motifs among regulated transcripts. These data provide insight into the stage-specific mechanisms of poly(A) tail regulation that orchestrate gene expression from oocyte to embryo in mammals.

Predicting Alu exonization in the human genome with a deep learning model

Alu exonization, or the recruitment of intronic Alu elements into gene sequences, has contributed to functional diversification; however, its extent and the ways in which it influences gene regulation are not fully understood. We developed an unbiased approach to predict Alu exonization events from genomic sequences implemented in a deep learning model, eXAlu, that overcomes the limitations of tissue or condition specificity and the computational burden of RNA-seq analysis. The model captures previously reported characteristics of exonized Alu sequences and can predict sequence elements important for Alu exonization. Using eXAlu, we estimate the number of Alu elements in the human genome undergoing exonization to be between 55-110K, 11-21 fold more than represented in the GENCODE gene database. Using RT-PCR we were able to validate selected predicted Alu exonization events, supporting the accuracy of our method. Lastly, we highlight a potential application of our method to identify polymorphic Alu insertion exonizations in individuals and in the population from whole genome sequencing data.

Predictive modeling of oocyte maternal mRNA features for five mammalian species reveals potential shared and species-restricted regulators during maturation

Oocyte maturation is accompanied by changes in abundances of thousands of mRNAs, many degraded and many preferentially stabilized. mRNA stability can be regulated by diverse features including GC content, codon bias, and motifs within the 3'-untranslated region (UTR) interacting with RNA binding proteins (RBPs) and miRNAs. Many studies have identified factors participating in mRNA splicing, bulk mRNA storage, and translational recruitment in mammalian oocytes, but the roles of potentially hundreds of expressed factors, how they regulate cohorts of thousands of mRNAs, and to what extent their functions are conserved across species has not been determined. We performed an extensive in silico cross-species analysis of features associated with mRNAs of different stability classes during oocyte maturation (stable, moderately degraded, and highly degraded) for five mammalian species. Using publicly available RNA sequencing data for germinal vesicle (GV) and MII oocyte transcriptomes, we determined that 3'-UTR length and synonymous codon usage are positively associated with stability, while greater GC content is negatively associated with stability. By applying machine learning and feature selection strategies, we identified RBPs and miRNAs that are predictive of mRNA stability, including some across multiple species and others more species-restricted. The results provide new insight into the mechanisms regulating maternal mRNA stabilization or degradation.NEW & NOTEWORTHY Conservation across species of mRNA features regulating maternal mRNA stability during mammalian oocyte maturation was analyzed. 3'-Untranslated region length and synonymous codon usage are positively associated with stability, while GC content is negatively associated. Just three RNA binding protein motifs were predicted to regulate mRNA stability across all five species examined, but associated pathways and functions are shared, indicating oocytes of different species arrive at comparable physiological destinations via different routes.

Computational prediction and experimental validation identify functionally conserved lncRNAs from zebrafish to human

Functional studies of long noncoding RNAs (lncRNAs) have been hindered by the lack of methods to assess their evolution. Here we present lncRNA Homology Explorer (lncHOME), a computational pipeline that identifies a unique class of long noncoding RNAs (lncRNAs) with conserved genomic locations and patterns of RNA-binding protein (RBP) binding sites (coPARSE-lncRNAs). Remarkably, several hundred human coPARSE-lncRNAs can be evolutionarily traced to zebrafish. Using CRISPR-Cas12a knockout and rescue assays, we found that knocking out many human coPARSE-lncRNAs led to cell proliferation defects, which were subsequently rescued by predicted zebrafish homologs. Knocking down coPARSE-lncRNAs in zebrafish embryos caused severe developmental delays that were rescued by human homologs. Furthermore, we verified that human, mouse and zebrafish coPARSE-lncRNA homologs tend to bind similar RBPs with their conserved functions relying on specific RBP-binding sites. Overall, our study demonstrates a comprehensive approach for studying the functional conservation of lncRNAs and implicates numerous lncRNAs in regulating vertebrate physiology.

FURNA: a database for function annotations of RNA structures

Despite the increasing number of 3D RNA structures in the Protein Data Bank, the majority of experimental RNA structures lack thorough functional annotations. As the significance of the functional roles played by non-coding RNAs becomes increasingly apparent, comprehensive annotation of RNA function is becoming a pressing concern. In response to this need, we have developed FURNA (Functions of RNAs), the first database for experimental RNA structures that aims to provide a comprehensive repository of high-quality functional annotations. These include Gene Ontology terms, Enzyme Commission numbers, ligand binding sites, RNA families, protein binding motifs, and cross-references to related databases. FURNA is available at https://seq2fun.dcmb.med.umich.edu/furna/ to enable quick discovery of RNA functions from their structures and sequences.

Srsf1 and Elavl1 act antagonistically on neuronal fate choice in the developing neocortex by controlling TrkC receptor isoform expression

The seat of higher-order cognitive abilities in mammals, the neocortex, is a complex structure, organized in several layers. The different subtypes of principal neurons are distributed in precise ratios and at specific positions in these layers and are generated by the same neural progenitor cells (NPCs), steered by a spatially and temporally specified combination of molecular cues that are incompletely understood. Recently, we discovered that an alternatively spliced isoform of the TrkC receptor lacking the kinase domain, TrkC-T1, is a determinant of the corticofugal projection neuron (CFuPN) fate. Here, we show that the finely tuned balance between TrkC-T1 and the better known, kinase domain-containing isoform, TrkC-TK+, is cell type-specific in the developing cortex and established through the antagonistic actions of two RNA-binding proteins, Srsf1 and Elavl1. Moreover, our data show that Srsf1 promotes the CFuPN fate and Elavl1 promotes the callosal projection neuron (CPN) fate in vivo via regulating the distinct ratios of TrkC-T1 to TrkC-TK+. Taken together, we connect spatio-temporal expression of Srsf1 and Elavl1 in the developing neocortex with the regulation of TrkC alternative splicing and transcript stability and neuronal fate choice, thus adding to the mechanistic and functional understanding of alternative splicing in vivo.

Members of the CUGBP Elav-like family of RNA-binding proteins are expressed in distinct populations of primary sensory neurons

Primary sensory dorsal root ganglia (DRG) neurons are diverse, with distinct populations that respond to specific stimuli. Previously, we observed that functionally distinct populations of DRG neurons express mRNA transcript variants with different 3' untranslated regions (3'UTRs). 3'UTRs harbor binding sites for interaction with RNA-binding proteins (RBPs) for transporting mRNAs to subcellular domains, modulating transcript stability, and regulating the rate of translation. In the current study, analysis of publicly available single-cell RNA-sequencing data generated from adult mice revealed that 17 3'UTR-binding RBPs were enriched in specific populations of DRG neurons. This included four members of the CUG triplet repeat (CUGBP) Elav-like family (CELF): CELF2 and CELF4 were enriched in peptidergic, CELF6 in both peptidergic and nonpeptidergic, and CELF3 in tyrosine hydroxylase-expressing neurons. Immunofluorescence studies confirmed that 60% of CELF4+ neurons are small-diameter C fibers and 33% medium-diameter myelinated (likely Aδ) fibers and showed that CELF4 is distributed to peripheral termini. Coexpression analyses using transcriptomic data and immunofluorescence revealed that CELF4 is enriched in nociceptive neurons that express GFRA3, CGRP, and the capsaicin receptor TRPV1. Reanalysis of published transcriptomic data from macaque DRG revealed a highly similar distribution of CELF members, and reanalysis of single-nucleus RNA-sequencing data derived from mouse and rat DRG after sciatic injury revealed differential expression of CELFs in specific populations of sensory neurons. We propose that CELF RBPs may regulate the fate of mRNAs in populations of nociceptors, and may play a role in pain and/or neuronal regeneration following nerve injury.

RNA trafficking and subcellular localization-a review of mechanisms, experimental and predictive methodologies

RNA localization is essential for regulating spatial translation, where RNAs are trafficked to their target locations via various biological mechanisms. In this review, we discuss RNA localization in the context of molecular mechanisms, experimental techniques and machine learning-based prediction tools. Three main types of molecular mechanisms that control the localization of RNA to distinct cellular compartments are reviewed, including directed transport, protection from mRNA degradation, as well as diffusion and local entrapment. Advances in experimental methods, both image and sequence based, provide substantial data resources, which allow for the design of powerful machine learning models to predict RNA localizations. We review the publicly available predictive tools to serve as a guide for users and inspire developers to build more effective prediction models. Finally, we provide an overview of multimodal learning, which may provide a new avenue for the prediction of RNA localization.

NF-YA isoforms with alternative splicing of exon-5 in Aves

NF-YA, the regulatory subunit of the trimeric CCAAT-binding transcription factor NF-Y, is present in vertebrates in two major alternative spliced isoforms: NF-YAl and NF-YAs, differing for the presence of exon-3. NF-YAx, a third isoform without exon-3/-5, was reported only in human neuronal cells and tumors. These events affect the Trans-Activation Domain. We provide here evidence for the expression of NF-YAx and for the existence of a new isoform, NF-YAg, skipping only exon-5. These isoforms are abundant in Aves, but not in reptiles, and are the prevalent transcripts in the initial phases of embryo development in chicken. Finally, we analyzed NF-YAg and NF-YAx amino acid sequence using AlphaFold: absence of exon-5 denotes a global reduction of β-stranded elements, while removal of the disordered exon-3 sequence has limited effects on TAD architecture. These data identify an expanded program of NF-YA isoforms within the TAD in Aves, implying a role during early development.

Towards in silico CLIP-seq: predicting protein-RNA interaction via sequence-to-signal learning

We present RBPNet, a novel deep learning method, which predicts CLIP-seq crosslink count distribution from RNA sequence at single-nucleotide resolution. By training on up to a million regions, RBPNet achieves high generalization on eCLIP, iCLIP and miCLIP assays, outperforming state-of-the-art classifiers. RBPNet performs bias correction by modeling the raw signal as a mixture of the protein-specific and background signal. Through model interrogation via Integrated Gradients, RBPNet identifies predictive sub-sequences that correspond to known and novel binding motifs and enables variant-impact scoring via in silico mutagenesis. Together, RBPNet improves imputation of protein-RNA interactions, as well as mechanistic interpretation of predictions.

Poison exon annotations improve the yield of clinically relevant variants in genomic diagnostic testing

PURPOSE

Neurodevelopmental disorders (NDDs) often result from rare genetic variation, but genomic testing yield for NDDs remains below 50%, suggesting that clinically relevant variants may be missed by standard analyses. Here, we analyze "poison exons" (PEs), which are evolutionarily conserved alternative exons often absent from standard gene annotations. Variants that alter PE inclusion can lead to loss of function and may be highly penetrant contributors to disease.

METHODS

We curated published RNA sequencing data from developing mouse cortex to define 1937 conserved PE regions potentially relevant to NDDs, and we analyzed variants found by genome sequencing in multiple NDD cohorts.

RESULTS

Across 2999 probands, we found 6 novel clinically relevant variants in PE regions. Five of these variants are in genes that are part of the sodium voltage-gated channel alpha subunit family (SCN1A, SCN2A, and SCN8A), which is associated with epilepsies. One variant is in SNRPB, associated with cerebrocostomandibular syndrome. These variants have moderate to high computational impact assessments, are absent from population variant databases, and in genes with gene-phenotype associations consistent with each probands reported features.

CONCLUSION

With a very minimal increase in variant analysis burden (average of 0.77 variants per proband), annotation of PEs can improve diagnostic yield for NDDs and likely other congenital conditions.

The RNA-Binding Proteins OAS1, ZFP36L2, and DHX58 Are Involved in the Regulation of CD44 mRNA Splicing in Colorectal Cancer Cells

Regulation of alternative splicing is carried out by RNA-binding proteins. Each alternative splicing event is controlled by several RNA-binding proteins, which in combination create the distribution of alternative splicing products in a given cell type. Transmembrane protein CD44 plays an important role at various stages of the metastatic cascade and is considered as a promising molecule for the therapy of tumor diseases and the construction of prognostic classifiers. However, the functions of specific isoforms of this protein may differ significantly. In this work, we performed a bioinformatic search of RNA-binding proteins that can determine the expression of clinically significant isoforms 3 and 4 of CD44 protein. The analysis revealed five RNA-binding proteins, three of which (OAS1, ZFP36L2, and DHX58) are shown for the first time as potential regulators of the studied process.

Identification of Significant RNA-Binding Proteins in the Process of CD44 Splicing Using the Boosted Beta Regression Algorithm

The expression of RNA-binding proteins and their interaction with the spliced pre-mRNA are the key factors in determining the final isoform profile. Transmembrane protein CD44 is involved in differentiation, invasion, motility, growth and survival of tumor cells, and is also a commonly accepted marker of cancer stem cells and epithelial-mesenchymal transition. However, the functions of the isoforms of this protein differ significantly. In this paper, we developed a method based on the boosted beta regression algorithm for identification of the significant RNA-binding proteins in the splicing process by modeling the isoform ratio. The application of this method to the analysis of CD44 splicing in colorectal cancer cells revealed 20 significant RNA-binding proteins. Many of them were previously shown as EMT regulators, but for the first time presented as potential CD44 splicing factors.

Large-scale functional screen identifies genetic variants with splicing effects in modern and archaic humans

Humans coexisted and interbred with other hominins which later became extinct. These archaic hominins are known to us only through fossil records and for two cases, genome sequences. Here, we engineer Neanderthal and Denisovan sequences into thousands of artificial genes to reconstruct the pre-mRNA processing patterns of these extinct populations. Of the 5,169 alleles tested in this massively parallel splicing reporter assay (MaPSy), we report 962 exonic splicing mutations that correspond to differences in exon recognition between extant and extinct hominins. Using MaPSy splicing variants, predicted splicing variants, and splicing quantitative trait loci, we show that splice-disrupting variants experienced greater purifying selection in anatomically modern humans than that in Neanderthals. Adaptively introgressed variants were enriched for moderate-effect splicing variants, consistent with positive selection for alternative spliced alleles following introgression. As particularly compelling examples, we characterized a unique tissue-specific alternative splicing variant at the adaptively introgressed innate immunity gene TLR1, as well as a unique Neanderthal introgressed alternative splicing variant in the gene HSPG2 that encodes perlecan. We further identified potentially pathogenic splicing variants found only in Neanderthals and Denisovans in genes related to sperm maturation and immunity. Finally, we found splicing variants that may contribute to variation among modern humans in total bilirubin, balding, hemoglobin levels, and lung capacity. Our findings provide unique insights into natural selection acting on splicing in human evolution and demonstrate how functional assays can be used to identify candidate causal variants underlying differences in gene regulation and phenotype.

Time-dependent regulation of cytokine production by RNA binding proteins defines T cell effector function

Potent T cell responses against infections and malignancies require a rapid yet tightly regulated production of toxic effector molecules. Their production level is defined by post-transcriptional events at 3' untranslated regions (3' UTRs). RNA binding proteins (RBPs) are key regulators in this process. With an RNA aptamer-based capture assay, we identify >130 RBPs interacting with IFNG, TNF, and IL2 3' UTRs in human T cells. RBP-RNA interactions show plasticity upon T cell activation. Furthermore, we uncover the intricate and time-dependent regulation of cytokine production by RBPs: whereas HuR supports early cytokine production, ZFP36L1, ATXN2L, and ZC3HAV1 dampen and shorten the production duration, each at different time points. Strikingly, even though ZFP36L1 deletion does not rescue the dysfunctional phenotype, tumor-infiltrating T cells produce more cytokines and cytotoxic molecules, resulting in superior anti-tumoral T cell responses. Our findings thus show that identifying RBP-RNA interactions reveals key modulators of T cell responses in health and disease.

Improved analysis of (e)CLIP data with RCRUNCH yields a compendium of RNA-binding protein binding sites and motifs

We present RCRUNCH, an end-to-end solution to CLIP data analysis for identification of binding sites and sequence specificity of RNA-binding proteins. RCRUNCH can analyze not only reads that map uniquely to the genome but also those that map to multiple genome locations or across splice boundaries and can consider various types of background in the estimation of read enrichment. By applying RCRUNCH to the eCLIP data from the ENCODE project, we have constructed a comprehensive and homogeneous resource of in-vivo-bound RBP sequence motifs. RCRUNCH automates the reproducible analysis of CLIP data, enabling studies of post-transcriptional control of gene expression.

Genome-wide identification of tandem repeats associated with splicing variation across 49 tissues in humans

Tandem repeats (TRs) are one of the largest sources of polymorphism, and their length is associated with gene regulation. Although previous studies reported several tandem repeats regulating gene splicing in cis (spl-TRs), no large-scale study has been conducted. In this study, we established a genome-wide catalog of 9537 spl-TRs with a total of 58,290 significant TR-splicing associations across 49 tissues (false discovery rate 5%) by using Genotype-Tissue expression (GTex) Project data. Regression models explaining splicing variation by using spl-TRs and other flanking variants suggest that at least some of the spl-TRs directly modulate splicing. In our catalog, two spl-TRs are known loci for repeat expansion diseases, spinocerebellar ataxia 6 (SCA6) and 12 (SCA12). Splicing alterations by these spl-TRs were compatible with those observed in SCA6 and SCA12. Thus, our comprehensive spl-TR catalog may help elucidate the pathomechanism of genetic diseases.

RBM47 is a Critical Regulator of Mouse Embryonic Stem Cell Differentiation

RNA-binding proteins (RBPs) are pivotal for regulating gene expression as they are involved in each step of RNA metabolism. Several RBPs are essential for viable growth and development in mammals. RNA-binding motif 47 (RBM47) is an RRM-containing RBP whose role in mammalian embryonic development is poorly understood yet deemed to be essential since its loss in mouse embryos leads to perinatal lethality. In this study, we attempted to elucidate the significance of RBM47 in cell-fate decisions of mouse embryonic stem cells (mESCs). Downregulation of Rbm47 did not affect mESC maintenance and the cell cycle but perturbed the expression of primitive endoderm (PrE) markers and increased GATA4 + PrE-like cells. However, the PrE misregulation could be reversed by either overexpressing Rbm47 or treating the knockdown mESCs with the inhibitors of FGFR or MEK, suggesting an implication of RBM47 in regulating FGF-ERK signaling. Rbm47 knockdown affected the multi-lineage differentiation potential of mESCs as it regressed teratoma in NSG mice and led to a skewed expression of differentiation markers in serum-induced monolayer differentiation. Further, lineage-specific differentiation revealed that Rbm47 is essential for proper differentiation of mESCs towards neuroectodermal and endodermal fate. Taken together, we assign a hitherto unknown role(s) to RBM47 in a subtle regulation of mESC differentiation.

Single-cell RNA binding protein regulatory network analyses reveal oncogenic HNRNPK-MYC signalling pathway in cancer

RNA-binding proteins (RBPs) are key players of gene expression and perturbations of RBP-RNA regulatory network have been observed in various cancer types. Here, we propose a computational method, RBPreg, to identify the RBP regulators by integration of single cell RNA-Seq (N = 233,591) and RBP binding data. Pan-cancer analyses suggest that RBP regulators exhibit cancer and cell specificity and perturbations of RBP regulatory network are involved in cancer hallmark-related functions. We prioritize an oncogenic RBP-HNRNPK, which is highly expressed in tumors and associated with poor prognosis of patients. Functional assays performed in cancer cells reveal that HNRNPK promotes cancer cell proliferation, migration, and invasion in vitro and in vivo. Mechanistic investigations further demonstrate that HNRNPK promotes tumorigenesis and progression by directly binding to MYC and perturbed the MYC targets pathway in lung cancer. Our results provide a valuable resource for characterizing RBP regulatory networks in cancer, yielding potential biomarkers for precision medicine.

Functional Relationships between Long Non-Coding RNAs and Estrogen Receptor Alpha: A New Frontier in Hormone-Responsive Breast Cancer Management

In the complex and articulated machinery of the human genome, less than 2% of the transcriptome encodes for proteins, while at least 75% is actively transcribed into non-coding RNAs (ncRNAs). Among the non-coding transcripts, those ≥200 nucleotides long (lncRNAs) are receiving growing attention for their involvement in human diseases, particularly cancer. Genomic studies have revealed the multiplicity of processes, including neoplastic transformation and tumor progression, in which lncRNAs are involved by regulating gene expression at epigenetic, transcriptional, and post-transcriptional levels by mechanism(s) that still need to be clarified. In breast cancer, several lncRNAs were identified and demonstrated to have either oncogenic or tumor-suppressive roles. The functional understanding of the mechanisms of lncRNA action in this disease could represent a potential for translational applications, as these molecules may serve as novel biomarkers of clinical use and potential therapeutic targets. This review highlights the relationship between lncRNAs and the principal hallmark of the luminal breast cancer phenotype, estrogen receptor α (ERα), providing an overview of new potential ways to inhibit estrogenic signaling via this nuclear receptor toward escaping resistance to endocrine therapy.

Analysis of RBP expression and binding sites identifies PTBP1 as a regulator of CD19 expression in B-ALL

Despite massive improvements in the treatment of B-ALL through CART-19 immunotherapy, a large number of patients suffer a relapse due to loss of the targeted epitope. Mutations in the CD19 locus and aberrant splicing events are known to account for the absence of surface antigen. However, early molecular determinants suggesting therapy resistance as well as the time point when first signs of epitope loss appear to be detectable are not enlightened so far. By deep sequencing of the CD19 locus, we identified a blast-specific 2-nucleotide deletion in intron 2 that exists in 35% of B-ALL samples at initial diagnosis. This deletion overlaps with the binding site of RNA binding proteins (RBPs) including PTBP1 and might thereby affect CD19 splicing. Moreover, we could identify a number of other RBPs that are predicted to bind to the CD19 locus being deregulated in leukemic blasts, including NONO. Their expression is highly heterogeneous across B-ALL molecular subtypes as shown by analyzing 706 B-ALL samples accessed via the St. Jude Cloud. Mechanistically, we show that downregulation of PTBP1, but not of NONO, in 697 cells reduces CD19 total protein by increasing intron 2 retention. Isoform analysis in patient samples revealed that blasts, at diagnosis, express increased amounts of CD19 intron 2 retention compared to normal B cells. Our data suggest that loss of RBP functionality by mutations altering their binding motifs or by deregulated expression might harbor the potential for the disease-associated accumulation of therapy-resistant CD19 isoforms.

In silico and in vitro analysis of the impact of single substitutions within EXO-motifs on Hsa-MiR-1246 intercellular transfer in breast cancer cell

MiR-1246 has recently gained much attention and many studies have shown its oncogenic role in colorectal, breast, lung, and ovarian cancers. However, miR-1246 processing, stability, and mechanisms directing miR-1246 into neighbor cells remain still unclear. In this study, we aimed to determine the role of single-nucleotide substitutions within short exosome sorting motifs - so-called EXO-motifs: GGAG and GCAG present in miR-1246 sequence on its intracellular stability and extracellular transfer. We applied in silico methods such as 2D and 3D structure analysis and modeling of protein interactions. We also performed in vitro validation through the transfection of fluorescently labeled miRNA to MDA-MB-231 cells, which we analyzed by flow cytometry and fluorescent microscopy. Our results suggest that nucleotides alterations that disturbed miR-1246 EXO-motifs were able to modulate miRNA-1246 stability and its transfer level to the neighboring cells, suggesting that the molecular mechanism of RNA stability and intercellular transfer can be closely related.

Differential analysis of RNA structure probing experiments at nucleotide resolution: uncovering regulatory functions of RNA structure

RNAs perform their function by forming specific structures, which can change across cellular conditions. Structure probing experiments combined with next generation sequencing technology have enabled transcriptome-wide analysis of RNA secondary structure in various cellular conditions. Differential analysis of structure probing data in different conditions can reveal the RNA structurally variable regions (SVRs), which is important for understanding RNA functions. Here, we propose DiffScan, a computational framework for normalization and differential analysis of structure probing data in high resolution. DiffScan preprocesses structure probing datasets to remove systematic bias, and then scans the transcripts to identify SVRs and adaptively determines their lengths and locations. The proposed approach is compatible with most structure probing platforms (e.g., icSHAPE, DMS-seq). When evaluated with simulated and benchmark datasets, DiffScan identifies structurally variable regions at nucleotide resolution, with substantial improvement in accuracy compared with existing SVR detection methods. Moreover, the improvement is robust when tested in multiple structure probing platforms. Application of DiffScan in a dataset of multi-subcellular RNA structurome and a subsequent motif enrichment analysis suggest potential links of RNA structural variation and mRNA abundance, possibly mediated by RNA binding proteins such as the serine/arginine rich splicing factors. This work provides an effective tool for differential analysis of RNA secondary structure, reinforcing the power of structure probing experiments in deciphering the dynamic RNA structurome.

The authors present DiffScan, an advanced tool for normalization and differential analysis of RNA structure probing experiments, combining their power in deciphering the dynamic RNA structurome and facilitating the discovery of RNA regulatory functions.

A seven-transmembrane protein-TM7SF3, resides in nuclear speckles and regulates alternative splicing

The seven-transmembrane superfamily member 3 protein (TM7SF3) is a p53-regulated homeostatic factor that attenuates cellular stress and the unfolded protein response. Here we show that TM7SF3 localizes to nuclear speckles; eukaryotic nuclear bodies enriched in splicing factors. This unexpected location for a trans -membranal protein enables formation of stable complexes between TM7SF3 and pre-mRNA splicing factors including DHX15, LARP7, HNRNPU, RBM14, and HNRNPK. Indeed, TM7SF3 regulates alternative splicing of >330 genes, mainly at the 3'end of introns by directly modulating the activity of splicing factors such as HNRNPK. These effects are observed both in cell lines and primary human pancreatic islets. Accordingly, silencing of TM7SF3 results in differential expression of 1465 genes (about 7% of the human genome); with 844 and 621 genes being up- or down-regulated, respectively. Our findings implicate TM7SF3, as a resident protein of nuclear speckles and suggest a role for seven-transmembrane proteins as regulators of alternative splicing.

Increased chromatin accessibility facilitates intron retention in specific cell differentiation states

Dynamic intron retention (IR) in vertebrate cells is of widespread biological importance. Aberrant IR is associated with numerous human diseases including several cancers. Despite consistent reports demonstrating that intrinsic sequence features can help introns evade splicing, conflicting findings about cell type- or condition-specific IR regulation by trans-regulatory and epigenetic mechanisms demand an unbiased and systematic analysis of IR in a controlled experimental setting. We integrated matched mRNA sequencing (mRNA-Seq), whole-genome bisulfite sequencing (WGBS), nucleosome occupancy methylome sequencing (NOMe-Seq) and chromatin immunoprecipitation sequencing (ChIP-Seq) data from primary human myeloid and lymphoid cells. Using these multi-omics data and machine learning, we trained two complementary models to determine the role of epigenetic factors in the regulation of IR in cells of the innate immune system. We show that increased chromatin accessibility, as revealed by nucleosome-free regions, contributes substantially to the retention of introns in a cell-specific manner. We also confirm that intrinsic characteristics of introns are key for them to evade splicing. This study suggests an important role for chromatin architecture in IR regulation. With an increasing appreciation that pathogenic alterations are linked to RNA processing, our findings may provide useful insights for the development of novel therapeutic approaches that target aberrant splicing.

circSMARCA5 Is an Upstream Regulator of the Expression of miR-126-3p, miR-515-5p, and Their mRNA Targets, Insulin-like Growth Factor Binding Protein 2 (IGFBP2) and NRAS Proto-Oncogene, GTPase (NRAS) in Glioblastoma

The involvement of non-coding RNAs (ncRNAs) in glioblastoma multiforme (GBM) pathogenesis and progression has been ascertained but their cross-talk within GBM cells remains elusive. We previously demonstrated the role of circSMARCA5 as a tumor suppressor (TS) in GBM. In this paper, we explore the involvement of circSMARCA5 in the control of microRNA (miRNA) expression in GBM. By using TaqMan^® low-density arrays, the expression of 748 miRNAs was assayed in U87MG overexpressing circSMARCA5. Differentially expressed (DE) miRNAs were validated through single TaqMan^® assays in: (i) U87MG overexpressing circSMARCA5; (ii) four additional GBM cell lines (A172; CAS-1; SNB-19; U251MG); (iii) thirty-eight GBM biopsies; (iv) twenty biopsies of unaffected brain parenchyma (UC). Validated targets of DE miRNAs were selected from the databases TarBase and miRTarbase, and the literature; their expression was inferred from the GBM TCGA dataset. Expression was assayed in U87MG overexpressing circSMARCA5, GBM cell lines, and biopsies through real-time PCR. TS miRNAs 126-3p and 515-5p were upregulated following circSMARCA5 overexpression in U87MG and their expression was positively correlated with that of circSMARCA5 (r-values = 0.49 and 0.50, p-values = 9 × 10^-5 and 7 × 10^-5, respectively) in GBM biopsies. Among targets, IGFBP2 (target of miR-126-3p) and NRAS (target of miR-515-5p) mRNAs were positively correlated (r-value = 0.46, p-value = 0.00027), while their expression was negatively correlated with that of circSMARCA5 (r-values = -0.58 and -0.30, p-values = 0 and 0.019, respectively), miR-126-3p (r-value = -0.36, p-value = 0.0066), and miR-515-5p (r-value = -0.34, p-value = 0.010), respectively. Our data identified a new GBM subnetwork controlled by circSMARCA5, which regulates downstream miRNAs 126-3p and 515-5p, and their mRNA targets IGFBP2 and NRAS.

RBP Image Database: A resource for the systematic characterization of the subcellular distribution properties of human RNA binding proteins

RNA binding proteins (RBPs) are central regulators of gene expression implicated in all facets of RNA metabolism. As such, they play key roles in cellular physiology and disease etiology. Since different steps of post-transcriptional gene expression tend to occur in specific regions of the cell, including nuclear or cytoplasmic locations, defining the subcellular distribution properties of RBPs is an important step in assessing their potential functions. Here, we present the RBP Image Database, a resource that details the subcellular localization features of 301 RBPs in the human HepG2 and HeLa cell lines, based on the results of systematic immuno-fluorescence studies conducted using a highly validated collection of RBP antibodies and a panel of 12 markers for specific organelles and subcellular structures. The unique features of the RBP Image Database include: (i) hosting of comprehensive representative images for each RBP-marker pair, with ∼250,000 microscopy images; (ii) a manually curated controlled vocabulary of annotation terms detailing the localization features of each factor; and (iii) a user-friendly interface allowing the rapid querying of the data by target or annotation. The RBP Image Database is freely available at https://rnabiology.ircm.qc.ca/RBPImage/.