Deciphering the role of RNA-binding proteins in the post-transcriptional control of gene expression

Refining the pool of RNA-binding domains advances the classification and prediction of RNA-binding proteins

From transcription to decay, RNA-binding proteins (RBPs) influence RNA metabolism. Using the RBP2GO database that combines proteome-wide RBP screens from 13 species, we investigated the RNA-binding features of 176 896 proteins. By compiling published lists of RNA-binding domains (RBDs) and RNA-related protein family (Rfam) IDs with lists from the InterPro database, we analyzed the distribution of the RBDs and Rfam IDs in RBPs and non-RBPs to select RBDs and Rfam IDs that were enriched in RBPs. We also explored proteins for their content in intrinsically disordered regions (IDRs) and low complexity regions (LCRs). We found a strong positive correlation between IDRs and RBDs and a co-occurrence of specific LCRs. Our bioinformatic analysis indicated that RBDs/Rfam IDs were strong indicators of the RNA-binding potential of proteins and helped predicting new RBP candidates, especially in less investigated species. By further analyzing RBPs without RBD, we predicted new RBDs that were validated by RNA-bound peptides. Finally, we created the RBP2GO composite score by combining the RBP2GO score with new quality factors linked to RBDs and Rfam IDs. Based on the RBP2GO composite score, we compiled a list of 2018 high-confidence human RBPs. The knowledge collected here was integrated into the RBP2GO database at https://RBP2GO-2-Beta.dkfz.de.

Current insight into the role of mRNA decay pathways in fungal pathogenesis

Pathogenic fungal species can cause superficial and mucosal infections, to potentially fatal systemic or invasive infections in humans. These infections are more common in immunocompromised or critically ill patients and have a significant morbidity and fatality rate. Fungal pathogens utilize several strategies to adapt the host environment resulting in efficient and comprehensive alterations in their cellular metabolism. Fungal virulence is regulated by several factors and post-transcriptional regulation mechanisms involving mRNA molecules are one of them. Post-transcriptional controls have emerged as critical regulatory mechanisms involved in the pathogenesis of fungal species. The untranslated upstream and downstream regions of the mRNA, as well as RNA-binding proteins, regulate morphogenesis and virulence by controlling mRNA degradation and stability. The limited number of available therapeutic drugs, the emergence of multidrug resistance, and high death rates associated with systemic fungal illnesses pose a serious risk to human health. Therefore, new antifungal treatments that specifically target mRNA pathway components can decrease fungal pathogenicity and when combined increase the effectiveness of currently available antifungal drugs. This review summarizes the mRNA degradation pathways and their role in fungal pathogenesis.

Role of mRNA-binding proteins in retinal neovascularization

Retinal neovascularization (RNV) is a pathological process that primarily occurs in diabetic retinopathy, retinopathy of prematurity, and retinal vein occlusion. It is a common yet debilitating clinical condition that culminates in blindness. Urgent efforts are required to explore more efficient and less limiting therapeutic strategies. Key RNA-binding proteins (RBPs), crucial for post-transcriptional regulation of gene expression by binding to RNAs, are closely correlated with RNV development. RBP-RNA interactions are altered during RNV. Here, we briefly review the characteristics and functions of RBPs, and the mechanism of RNV. Then, we present insights into the role of the regulatory network of RBPs in RNV. HuR, eIF4E, LIN28B, SRSF1, METTL3, YTHDF1, Gal-1, HIWI1, and ZFR accelerate RNV progression, whereas YTHDF2 and hnRNPA2B1 hinder it. The mechanisms elucidated in this review provide a reference to guide the design of therapeutic strategies to reverse abnormal processes.

LINC00571 drives tricarboxylic acid cycle metabolism in triple-negative breast cancer through HNRNPK/ILF2/IDH2 axis

BACKGROUND

Triple-negative breast cancer is a complex breast malignancy subtype characterized by poor prognosis. The pursuit of effective therapeutic approaches for this subtype is considerably challenging. Notably, recent research has illuminated the key role of the tricarboxylic acid cycle in cancer metabolism and the complex landscape of tumor development. Concurrently, an emerging body of evidence underscores the noteworthy role that long non-coding RNAs play in the trajectory of breast cancer development. Despite this growing recognition, the exploration of whether long non-coding RNAs can influence breast cancer progression by modulating the tricarboxylic acid cycle has been limited. Moreover, the underlying mechanisms orchestrating these interactions have not been identified.

METHODS

The expression levels of LINC00571 and IDH2 were determined through the analysis of the public TCGA dataset, transcriptome sequencing, qRT‒PCR, and Western blotting. The distribution of LINC00571 was assessed using RNA fluorescence in situ hybridization. Alterations in biological effects were evaluated using CCK-8, colony formation, EdU, cell cycle, and apoptosis assays and a tumor xenograft model. To elucidate the interaction between LINC00571, HNRNPK, and ILF2, RNA pull-down, mass spectrometry, coimmunoprecipitation, and RNA immunoprecipitation assays were performed. The impacts of LINC00571 and IDH2 on tricarboxylic acid cycle metabolites were investigated through measurements of the oxygen consumption rate and metabolite levels.

RESULTS

This study revealed the complex interactions between a novel long non-coding RNA (LINC00571) and tricarboxylic acid cycle metabolism. We validated the tumor-promoting role of LINC00571. Mechanistically, LINC00571 facilitated the interaction between HNRNPK and ILF2, leading to reduced ubiquitination and degradation of ILF2, thereby stabilizing its expression. Furthermore, ILF2 acted as a transcription factor to enhance the expression of its downstream target gene IDH2.

CONCLUSIONS

Our study revealed that the LINC00571/HNRNPK/ILF2/IDH2 axis promoted the progression of triple-negative breast cancer by regulating tricarboxylic acid cycle metabolites. This discovery provides a novel theoretical foundation and new potential targets for the clinical treatment of triple-negative breast cancer.

Study on the protective effect of RNA-binding motif protein 3 in mild hypothermia oxygen-glucose deprivation/reoxygenation cell model

Mild hypothermia is proven neuroprotective in clinical practice. While hypothermia leads to the decrease of global protein synthesis rate, it upregulates a small subset of protein including RNA-binding motif protein 3 (RBM3). In this study, we treated mouse neuroblastoma cells (N2a) with mild hypothermia before oxygen-glucose deprivation/reoxygenation (OGD/R) and discovered the decrease of apoptosis rate, down-regulation of apoptosis-associated protein and enhancement of cell viability. Overexpression of RBM3 via plasmid exerted similar effect while silencing RBM3 by siRNAs partially reversed the protective effect exerted by mild hypothermia pretreatment. The protein level of Reticulon 3(RTN3), a downstream gene of RBM3, also increased after mild hypothermia pretreatment. Silencing RTN3 weakened the protective effect of mild hypothermia pretreatment or RBM3 overexpression. Also, the protein level of autophagy gene LC3B increased after OGD/R or RBM3 overexpression while silencing RTN3 decreased this trend. Furthermore, immunofluorescence observed enhanced fluorescence signal of LC3B and RTN3 as well as a large number of overlaps after RBM3 overexpressing. In conclusion, RBM3 plays a cellular protective role by regulating apoptosis and viability via its downstream gene RTN3 in the hypothermia OGD/R cell model and autophagy may participate in it.

Direct and noninvasive fluorescence analysis of an RNA-protein interaction based on a CRISPR/Cas12a-powered assay

RNA-protein interactions (RPIs) play critical roles in gene transcription and protein expression, but current analytical methods for RPIs are mainly performed in an invasive manner, involving special RNA/protein labeling, hampering access to intact and precise information on RPIs. In this work, we present the first CRISPR/Cas12a-based fluorescence assay for the direct analysis of RPIs without RNA/protein labeling steps. Select vascular endothelial growth factor 165 (VEGF₁₆₅)/its RNA aptamer interaction as a model, the RNA sequence simultaneously serves as both the aptamer of VEGF₁₆₅ and crRNA of CRISPR/Cas12a system, and the presence of VEGF₁₆₅ facilitates VEGF₁₆₅/its RNA aptamer interaction, thus prohibiting the formation of Cas12a-crRNA-DNA ternary complex along with low fluorescence signal. The assay showed a detection limit of 0.23 pg mL^-1, and good performance in serum-spiked samples with an RSD of 0.4 %-13.1 %. This simple and selective strategy opens the door for establishing CRISPR/Cas-based biosensors for gaining intact information on RPIs, and shows widespread potential for other RPIs analysis.

Molecular mechanisms of amyotrophic lateral sclerosis as broad therapeutic targets for gene therapy applications utilizing adeno-associated viral vectors

Despite the devastating clinical outcome of the neurodegenerative disease, amyotrophic lateral sclerosis (ALS), its etiology remains mysterious. Approximately 90% of ALS is characterized as sporadic, signifying that the patient has no family history of the disease. The development of an impactful disease modifying therapy across the ALS spectrum has remained out of grasp, largely due to the poorly understood mechanisms of disease onset and progression. Currently, ALS is invariably fatal and rapidly progressive. It is hypothesized that multiple factors can lead to the development of ALS, however, treatments are often focused on targeting specific familial forms of the disease (10% of total cases). There is a strong need to develop disease modifying treatments for ALS that can be effective across the full ALS spectrum of familial and sporadic cases. Although the onset of disease varies significantly between patients, there are general disease mechanisms and progressions that can be seen broadly across ALS patients. Therefore, this review explores the targeting of these widespread disease mechanisms as possible areas for therapeutic intervention to treat ALS broadly. In particular, this review will focus on targeting mechanisms of defective protein homeostasis and RNA processing, which are both increasingly recognized as design principles of ALS pathogenesis. Additionally, this review will explore the benefits of gene therapy as an approach to treating ALS, specifically focusing on the use of adeno-associated virus (AAV) as a vector for gene delivery to the CNS and recent advances in the field.

RNA-Binding Proteins in Bladder Cancer

RNA-binding proteins (RBPs) are key regulators of transcription and translation, with highly dynamic spatio-temporal regulation. They are usually involved in the regulation of RNA splicing, polyadenylation, and mRNA stability and mediate processes such as mRNA localization and translation, thereby affecting the RNA life cycle and causing the production of abnormal protein phenotypes that lead to tumorigenesis and development. Accumulating evidence supports that RBPs play critical roles in vital life processes, such as bladder cancer initiation, progression, metastasis, and drug resistance. Uncovering the regulatory mechanisms of RBPs in bladder cancer is aimed at addressing the occurrence and progression of bladder cancer and finding new therapies for cancer treatment. This article reviews the effects and mechanisms of several RBPs on bladder cancer and summarizes the different types of RBPs involved in the progression of bladder cancer and the potential molecular mechanisms by which they are regulated, with a view to providing information for basic and clinical researchers.

RNA binding protein SAMD4: current knowledge and future perspectives

SAMD4 protein family is a class of novel RNA-binding proteins that can mediate post-transcriptional regulation and translation repression in eukaryotes, which are highly conserved from yeast to humans during evolution. In mammalian cells, SAMD4 protein family consists of two members including SAMD4A/Smaug1 and SAMD4B/Smaug2, both of which contain common SAM domain that can specifically bind to different target mRNAs through stem-loop structures, also known as Smaug recognition elements (SREs), and regulate the mRNA stability, degradation and translation. In addition, SAMD4 can form the cytoplasmic mRNA silencing foci and regulate the translation of SRE-containing mRNAs in neurons. SAMD4 also can form the cytosolic membrane-less organelles (MLOs), termed as Smaug1 bodies, and regulate mitochondrial function. Importantly, many studies have identified that SAMD4 family members are involved in various pathological processes including myopathy, bone development, neural development, and cancer occurrence and progression. In this review, we mainly summarize the structural characteristics, biological functions and molecular regulatory mechanisms of SAMD4 protein family members, which will provide a basis for further research and clinical application of SAMD4 protein family.

Inhibitory effect of calycosin on breast cancer cell progression through downregulating lncRNA HOTAIR and downstream targets: HuR and IGF2BP1

<p indent="0mm">Breast cancer is the most commonly diagnosed cancer worldwide. Previously, we reported that calycosin, a typical isoflavone phytoestrogen, triggers apoptosis and is associated with lncRNA HOTAIR in the estrogen receptor (ER)-positive breast cancer MCF-7-cell line. In the present study, we aim to uncover the mechanism of lncRNA HOTAIR in the inhibitory effect induced by calycosin in both ER-positive and ER-negative breast cancer cell lines. Results show that calycosin significantly inhibits proliferation and triggers apoptosis in both ER-positive (MCF-7 and T47D) and ER-negative (MDA-MB-231 and SK-BR-3) breast cancer cell lines, accompanied by downregulation of lncRNA HOTAIR expression. Accordingly, knockdown of lncRNA HOTAIR promotes the anti-tumor effect of calycosin, while overexpression of lncRNA HOTAIR attenuates this effect. Meanwhile, the expression levels of HuR and IGF2BP1 are also reduced by calycosin. More importantly, calycosin facilitates the downregulation of HuR and IGF2BP1 caused by decreasing lncRNA HOTAIR expression, and the upregulation of HuR and IGF2BP1 caused by overexpression of lncRNA HOTAIR is weakened by calycosin. These results demonstrate that downregulating HuR and IGF2BP1 by suppressing lncRNA HOTAIR results in inhibited growth of breast cancer cells by calycosin. In addition, the binding of HuR and IGF2BP1 to lncRNA HOTAIR is detected by RIP assay, implying an interaction between these two proteins and lncRNA HOTAIR. Together, lncRNA HOTAIR may play a carcinogenic role in breast cancer development and has the potential to be a novel therapeutic target for breast cancer in the future, especially in isoflavone phytoestrogen therapy.</p>.

Modulation of Virulence Factors during Trypanosoma cruzi Differentiation

Chagas disease is a neglected tropical disease caused by Trypanosoma cruzi. This protozoan developed several mechanisms to infect, propagate, and survive in different hosts. The specific expression of proteins is responsible for morphological and metabolic changes in different parasite stages along the parasite life cycle. The virulence strategies at the cellular and molecular levels consist of molecules responsible for mediating resistance mechanisms to oxidative damage, cellular invasion, and immune evasion, performed mainly by surface proteins. Since parasite surface coat remodeling is crucial to invasion and infectivity, surface proteins are essential virulence elements. Understanding the factors involved in these processes improves the knowledge of parasite pathogenesis. Genome sequencing has opened the door to high-throughput technologies, allowing us to obtain a deeper understanding of gene reprogramming along the parasite life cycle and identify critical molecules for survival. This review therefore focuses on proteins regulated during differentiation into infective forms considered virulence factors and addresses the current known mechanisms acting in the modulation of gene expression, emphasizing mRNA signals, regulatory factors, and protein complexes.

Predicting ncRNA-protein interactions based on dual graph convolutional network and pairwise learning

Noncoding RNAs (ncRNAs) have recently attracted considerable attention due to their key roles in biology. The ncRNA-proteins interaction (NPI) is often explored to reveal some biological activities that ncRNA may affect, such as biological traits, diseases, etc. Traditional experimental methods can accomplish this work but are often labor-intensive and expensive. Machine learning and deep learning methods have achieved great success by exploiting sufficient sequence or structure information. Graph Neural Network (GNN)-based methods consider the topology in ncRNA-protein graphs and perform well on tasks like NPI prediction. Based on GNN, some pairwise constraint methods have been developed to apply on homogeneous networks, but not used for NPI prediction on heterogeneous networks. In this paper, we construct a pairwise constrained NPI predictor based on dual Graph Convolutional Network (GCN) called NPI-DGCN. To our knowledge, our method is the first to train a heterogeneous graph-based model using a pairwise learning strategy. Instead of binary classification, we use a rank layer to calculate the score of an ncRNA-protein pair. Moreover, our model is the first to predict NPIs on the ncRNA-protein bipartite graph rather than the homogeneous graph. We transform the original ncRNA-protein bipartite graph into two homogenous graphs on which to explore second-order implicit relationships. At the same time, we model direct interactions between two homogenous graphs to explore explicit relationships. Experimental results on the four standard datasets indicate that our method achieves competitive performance with other state-of-the-art methods. And the model is available at https://github.com/zhuoninnin1992/NPIPredict.

Spliceosomal SL1 RNA binding to U1-70K: the role of the extended RRM

The RNA recognition motif (RRM) occurs widely in RNA-binding proteins, but does not always by itself support full binding. For example, it is known that binding of SL1 RNA to the protein U1-70K in the U1 spliceosomal particle is reduced when a region flanking the RRM is truncated. How the RRM flanking regions that together with the RRM make up an ‘extended RRM’ (eRRM) contribute to complex stability and structural organization is unknown. We study the U1-70K eRRM bound to SL1 RNA by thermal dissociation and laser temperature jump kinetics; long-time molecular dynamics simulations interpret the experiments with atomistic resolution. Truncation of the helix flanking the RRM on its N-terminal side, ‘N-helix,’ strongly reduces overall binding, which is further weakened under higher salt and temperature conditions. Truncating the disordered region flanking the RRM on the C-terminal side, ‘C-IDR’, affects the local binding site. Surprisingly, all-atom simulations show that protein truncation enhances base stacking interactions in the binding site and leaves the overall number of hydrogen bonds intact. Instead, the flanking regions of the eRRM act in a distributed fashion via collective interactions with the RNA when external stresses such as temperature or high salt mimicking osmotic imbalance are applied.

Long noncoding RNA UCA1 promotes glutamine-driven anaplerosis of bladder cancer by interacting with hnRNP I/L to upregulate GPT2 expression

Long noncoding RNA urothelial cancer associated 1 (UCA1), initially identified in bladder cancer, is associated with multiple cellular processes, including metabolic reprogramming. However, its characteristics in the anaplerosis context of bladder cancer (BLCA) remain elusive. We identified UCA1 as a binding partner of heterogeneous nuclear ribonucleoproteins (hnRNPs) I and L, RNA-binding proteins (RBPs) with no previously known role in metabolic reprogramming. UCA1 and hnRNP I/L profoundly affected glycolysis, TCA cycle, glutaminolysis, and proliferation of BLCA. Importantly, UCA1 specifically bound to and facilitated the combination of hnRNP I/L to the promoter of glutamic pyruvate transaminase 2 (GPT2), an enzyme transferring glutamate to α-ketoglutarate, resulting in upregulated expression of GPT2 and enhanced glutamine-derived carbons in the TCA cycle. We also systematically confirmed the influence of UCA1 and hnRNP I/L on metabolism and proliferation via glutamine-driven anaplerosis in BLCA. Our study revealed the critical role of UCA1-mediated mechanisms involved in glutamine-driven anaplerosis and provided novel evidence that lncRNA regulates metabolic reprogramming in tumor cells.

The smallest near-infrared fluorescence complementation system for imaging protein-protein and RNA-protein interactions

Bimolecular fluorescence complementation (BiFC) and its derivative molecular biosensor systems provide effective tools for visualizing biomolecular interactions. The introduction of red and near-infrared fluorescence emission proteins has expanded the spectrum of signal generating modules, enabling BiFC for in vivo imaging. However, the large size of the signal module of BiFC can hinder the interaction between proteins under investigation. In this study, we constructed the near-infrared BiFC and TriFC systems by splitting miRFP670nano, the smallest cyanobacteriochrome-evolved phytochrome available. The miRFP670nano-BiFC sensor system identified and enabled visualization of protein–protein interactions in living cells and live mice, and afforded a faster maturation rate and higher photostability and cellular stability when compared with those of reported near-infrared BiFC systems. We used the miRFP670nano-BiFC sensor system to identify interactions between the nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and cellular stress granule proteins in living cells and found that the N protein downregulated the expression level of granule protein G3BP1. With the advantages of small size and long wavelength emission of the signal module, the proposed molecular biosensor system should be suitable for various applications in cell imaging studies.

The smallest near-infrared fluorescence complementation system for imaging protein–protein and RNA–protein interactions in living cells and live mice.

RNA-binding proteins RBM-HuR, RBM3 and PODXL expression in urothelial carcinoma of the urinary bladder. Prognostic and clinical implications

AIM OF THE STUDY

The clinical significance and predictive and prognostic value of HuR, RBM3, and PODXL expression in patients with urothelial bladder cancer (UBC) are not clear yet. The aim of this study was to assess HuR, RBM3 and PODXL expression in muscle invasive and non-muscle invasive UBC tissues, and to investigate the clinicopathological correlations and their predictive and prognostic impact in patients with such type of cancer.

MATERIAL AND METHODS

RBM-HuR, RBM3 and PODXL expression levels were evaluated in 70 patients with urothelial carcinoma by immunohistochemistry. The relationships between their expression, clinicopathological findings and prognostic data were analyzed.

RESULTS

High RBM-HuR expression was related to muscle invasion (p = 0.008), metastasis to lymph nodes (p = 0.007), and presence of blood spread (p = 0.049). High RBM3 expression was associated with lower grade (p = 0.044), absence of distant metastasis (p = 0.025), and absence of lymph node metastasis (p = 0.018). High PODXL expression was significantly associated with advanced tumor stage (p < 0.001), larger tumor size (p = 0.050), lymphovascular invasion (p = 0.006), lymph node metastasis (p = 0.008), higher grade (p = 0.043) and distant metastasis (p = 0.002).Three-year overall survival rate was negatively associated with high expression of both RBM-HuR and PODXL while it was directly correlated with high expression of RBM3 (p = 0.008, 0.009 and 0.015 respectively). High RBM-HuR and PODXL expression and low expression of RBM3 were related to tumor recurrence (p = 0.022, 0.011 and 0.015).

CONCLUSIONS

RBM-HuR and PODXL expressions are markers of poor prognosis while RBM3 is a good prognostic marker for urothelial carcinoma of the bladder.

The androgen receptor messenger RNA: what do we know?

The Androgen Receptor (AR), transcriptionally activated by its ligands, testosterone and dihydrotestosterone (DHT), is widely expressed in cells and tissues, influencing normal biology and disease states. The protein product of the AR gene is involved in the regulation of numerous biological functions, including the development and maintenance of the normal prostate gland and of the cardiovascular, musculoskeletal and immune systems. Androgen signalling, mediated by AR protein, plays a crucial role in the development of prostate cancer (PCa), and is presumed to be involved in other cancers including those of the breast, bladder, liver and kidney. Significant research and reviews have focused on AR protein function; however, inadequate research and literature exist to define the function of AR mRNA in normal and cancer cells. The AR mRNA transcript is nearly 11 Kb long and contains a long 3’ untranslated region (UTR), suggesting its biological role in post-transcriptional regulation, consequently affecting the overall functions of both normal and cancer cells. Research has demonstrated that many biological activities, including RNA stability, translation, cellular trafficking and localization, are associated with the 3’ UTRs of mRNAs. In this review, we describe the potential role of the AR 3’ UTR and summarize RNA-binding proteins (RBPs) that interact with the AR mRNA to regulate post-transcriptional metabolism. We highlight the importance of AR mRNA as a critical modulator of carcinogenesis and its important role in developing therapy-resistant prostate cancer.

A comparative analysis of machine learning classifiers for predicting protein-binding nucleotides in RNA sequences

•

RNA are master players in various cellular and biological processes and RNA-protein interactions are vital for proper functioning of cellular machineries.

•

Knowledge of binding sites is crucial to decipher their functional implications.

•

RNA NC-triplet and NC-quartet features could give reasonably high performance.

•

RF model outperformed other machine learning classifiers with 85% accuracy and 0.93 AUC and performed better than few existing methods.

•

An online webserver “Nucpred” is developed with trained model and freely accessible for scientific community.

RNA-protein interactions play vital roles in driving the cellular machineries. Despite significant involvement in several biological processes, the underlying molecular mechanism of RNA-protein interactions is still elusive. This may be due to the experimental difficulties in solving co-crystallized RNA-protein complexes. Inherent flexibility of RNA molecules to adopt different conformations makes them functionally diverse. Their interactions with protein have implications in RNA disease biology. Thus, study of binding interfaces can provide a mechanistic insight of the molecular functioning and aberrations caused due to altered interactions. Moreover, high-throughput sequencing technologies have generated huge sequence data compared to available structural data of RNA-protein complexes. In such a scenario, efficient computational algorithms are required for identification of protein-binding interfaces of RNA in the absence of known structures. We have investigated several machine learning classifiers and various features derived from nucleotide sequences to identify protein-binding nucleotides in RNA. We achieve best performance with nucleotide-triplet and nucleotide-quartet feature-based random forest models. An overall accuracy of 84.8%, sensitivity of 83.2%, specificity of 86.1%, MCC of 0.70 and AUC of 0.93 is achieved. We have further implemented the developed models in a user-friendly webserver “Nucpred”, which is freely accessible at “http://www.csb.iitkgp.ac.in/applications/Nucpred/index”.

The dedicated chaperones of eL43, Puf6 and Loc1, can also bind RPL43 mRNA and regulate the production of this ribosomal protein

The level of ribosome biogenesis is highly associated with cell growth rate. Because many ribosomal proteins have extraribosomal functions, overexpression or insufficient supply of these proteins may impair cellular growth. Therefore, the supply of ribosomal proteins is tightly controlled in response to rRNA syntheses and environmental stimuli. In our previous study, 2 RNA-binding proteins, Puf6 and Loc1, were identified as dedicated chaperones of the ribosomal protein eL43, with which they associate to maintain its protein level and proper loading. In this study, we demonstrate that Puf6 and Loc1 interact with RPL43 mRNA. Notably, Puf6 and Loc1 usually function as a dimeric complex to bind other mRNAs; however, in this instance, the individual proteins, but not the complex form, can bind RPL43 mRNA. Thus, Puf6 or Loc1 could bind RPL43 mRNA in loc1Δ or puf6Δ, respectively. The binding of Puf6 or Loc1 caused negative effects for eL43 production: decreased RNA stability and translation of RPL43A/B mRNA. The present results suggest that these dedicated chaperones control the protein levels of eL43 from the standpoint of stability and through regulating its production.

hnRNP A1B, a Splice Variant of HNRNPA1, Is Spatially and Temporally Regulated

RNA binding proteins (RBPs) play a key role in cellular growth, homoeostasis and survival and are tightly regulated. A deep understanding of their spatiotemporal regulation is needed to understand their contribution to physiology and pathology. Here, we have characterized the spatiotemporal expression pattern of hnRNP A1 and its splice variant hnRNP A1B in mice. We have found that hnRNP A1B expression is more restricted to the CNS compared to hnRNP A1, and that it can form an SDS-resistant dimer in the CNS. Also, hnRNP A1B expression becomes progressively restricted to motor neurons in the ventral horn of the spinal cord, compared to hnRNP A1 which is more broadly expressed. We also demonstrate that hnRNP A1B is present in neuronal processes, while hnRNP A1 is absent. This finding supports a hypothesis that hnRNP A1B may have a cytosolic function in neurons that is not shared with hnRNP A1. Our results demonstrate that both isoforms are differentially expressed across tissues and have distinct localization profiles, suggesting that the two isoforms may have specific subcellular functions that can uniquely contribute to disease progression.

Improved SNV Discovery in Barcode-Stratified scRNA-seq Alignments

Currently, the detection of single nucleotide variants (SNVs) from 10 x Genomics single-cell RNA sequencing data (scRNA-seq) is typically performed on the pooled sequencing reads across all cells in a sample. Here, we assess the gaining of information regarding SNV assessments from individual cell scRNA-seq data, wherein the alignments are split by cellular barcode prior to the variant call. We also reanalyze publicly available data on the MCF7 cell line during anticancer treatment. We assessed SNV calls by three variant callers—GATK, Strelka2, and Mutect2, in combination with a method for the cell-level tabulation of the sequencing read counts bearing variant alleles–SCReadCounts (single-cell read counts). Our analysis shows that variant calls on individual cell alignments identify at least a two-fold higher number of SNVs as compared to the pooled scRNA-seq; these SNVs are enriched in novel variants and in stop-codon and missense substitutions. Our study indicates an immense potential of SNV calls from individual cell scRNA-seq data and emphasizes the need for cell-level variant detection approaches and tools, which can contribute to the understanding of the cellular heterogeneity and the relationships to phenotypes, and help elucidate somatic mutation evolution and functionality.

Engineering and standardization of posttranscriptional biocircuitry in Saccharomyces cerevisiae

This short review considers to what extent posttranscriptional steps of gene expression can provide the basis for novel control mechanisms and procedures in synthetic biology and biotechnology. The term biocircuitry is used here to refer to functionally connected components comprising DNA, RNA or proteins. The review begins with an overview of the diversity of devices being developed and then considers the challenges presented by trying to engineer more scaled-up systems. While the engineering of RNA-based and protein-based circuitry poses new challenges, the resulting 'toolsets' of components and novel mechanisms of operation will open up multiple new opportunities for synthetic biology. However, agreed procedures for standardization will need to be placed at the heart of this expanding field if the full potential benefits are to be realized.

Nanoscale Imaging of RNA-Protein Interactions with a Photoactivatable Trimolecular Fluorescence Complementation System

Imaging RNA-protein interaction in the cellular space with single molecule sensitivity is attractive for studying gene expression and regulation, but remains a challenge. In this study, we reported a photoactivatable trimolecular fluorescence complementation (TriFC) system based on fluorescent protein, mIrisFP, to identify and visualize RNA-protein interactions in living mammalian cells. We also combined this TriFC system with photoactivated localization microscopy (PALM), named the TriFC-PALM technique, which allowed us to image the RNA-protein interactions with single molecule sensitivity. Using this TriFC-PALM technique, we identified the actin-bundling protein, FSCN1, specifically interacting with the HOX Transcript Antisense RNA (HOTAIR). The TriFC-PALM imaging acquired a higher resolution compared with the traditional method of total internal reflection (TIRF) imaging. The TriFC-PALM thus provides a useful tool for imaging and identifying the RNA-protein interactions inside cells at the nanometer scale.

Computational methods for predicting hotspots at protein-RNA interfaces

Protein-RNA interactions play essential roles in many critical biological events. A comprehensive understanding of the mechanisms underlying these interactions is helpful when studying cellular activities and therapeutic applications. Hotspots are a small portion of residues contributing much toward protein-RNA binding affinity. In pharmaceutical research, the hotspot residues are seen as the best option for designing small molecules to target proteins of therapeutic interest. With the accumulation of experimental data about protein-RNA interactions, computational methods have been produced for hotspot prediction on a large scale. In this review, we first present an overview of the existing databases for protein-RNA binding data. Furthermore, we outline the most adopted computational methods for hotspots prediction in protein-RNA interactions. Finally, we discuss the applications of hotspot prediction. This article is categorized under: RNA Interactions with Proteins and Other Molecules > Protein-RNA Recognition RNA Interactions with Proteins and Other Molecules > Protein-RNA Interactions: Functional Implications RNA Methods > RNA Analyses In Vitro and In Silico.

Functions of PUF Family RNA-Binding Proteins in Aspergillus nidulans

RNA-binding proteins are involved in RNA metabolism and posttranscriptional regulation of various fundamental biological processes. The PUF family of RNA-binding proteins is highly conserved in eukaryotes, and its members regulate gene expression, mitochondrial biogenesis, and RNA processing. However, their biological functions in Aspergillus species remain mostly unknown in filamentous fungi. Here we have characterized the puf genes in the model organism Aspergillus nidulans. We generated deletion mutant strains for the five putative puf genes present in the A. nidulans genome and investigated their developmental phenotypes. Deletion of pufA or pufE affected fungal growth and asexual development. pufA mutants exhibited decreased production of asexual spores and reduced mRNA expression of genes regulating asexual development. The pufE deletion reduced colony growth, increased formation of asexual spores, and delayed production of sexual fruiting bodies. In addition, the absence of pufE reduced both sterigmatocystin production and the mRNA levels of genes in the sterigmatocystin cluster. Finally, pufE deletion mutants showed reduced trehalose production and lower resistance to thermal stress. Overall, these results demonstrate that PufA and PufE play roles in the development and sterigmatocystin metabolism in A. nidulans.

Lantern: an integrative repository of functional annotations for lncRNAs in the human genome

BACKGROUND

With advancements in omics technologies, the range of biological processes where long non-coding RNAs (lncRNAs) are involved, is expanding extensively, thereby generating the need to develop lncRNA annotation resources. Although, there are a plethora of resources for annotating genes, despite the extensive corpus of lncRNA literature, the available resources with lncRNA ontology annotations are rare.

RESULTS

We present a lncRNA annotation extractor and repository (Lantern), developed using PubMed's abstract retrieval engine and NCBO's recommender annotation system. Lantern's annotations were benchmarked against lncRNAdb's manually curated free text. Benchmarking analysis suggested that Lantern has a recall of 0.62 against lncRNAdb for 182 lncRNAs and precision of 0.8. Additionally, we also annotated lncRNAs with multiple omics annotations, including predicted cis-regulatory TFs, interactions with RBPs, tissue-specific expression profiles, protein co-expression networks, coding potential, sub-cellular localization, and SNPs for ~ 11,000 lncRNAs in the human genome, providing a one-stop dynamic visualization platform.

CONCLUSIONS

Lantern integrates a novel, accurate semi-automatic ontology annotation engine derived annotations combined with a variety of multi-omics annotations for lncRNAs, to provide a central web resource for dissecting the functional dynamics of long non-coding RNAs and to facilitate future hypothesis-driven experiments. The annotation pipeline and a web resource with current annotations for human lncRNAs are freely available on sysbio.lab.iupui.edu/lantern.

CSDE1 attenuates microRNA-mediated silencing of PMEPA1 in melanoma

MicroRNAs and RNA-binding proteins (RBPs) primarily target the 3' UTR of mRNAs to control their translation and stability. However, their co-regulatory effects on specific mRNAs in physiology and disease are yet to be fully explored. CSDE1 is an RBP that promotes metastasis in melanoma and mechanisms underlying its oncogenic activities need to be completely defined. Here we report that CSDE1 interacts with specific miRNA-induced silencing complexes (miRISC) in melanoma. We find an association of CSDE1 with AGO2, the essential component of miRISC, which is facilitated by target mRNAs and depends on the first cold shock domain of CSDE1. Both CSDE1 and AGO2 bind to 3' UTR of PMEPA1. CSDE1 counters AGO2 binding, leading to an increase of PMEPA1 expression. We also identify a miRNA, miR-129-5p, that represses PMEPA1 expression in melanoma. Collectively, our results show that PMEPA1 promotes tumorigenic traits and that CSDE1 along with miR-129-5p/AGO2 miRISC act antagonistically to fine-tune PMEPA1 expression toward the progression of melanoma.

Alternative splicing perturbation landscape identifies RNA binding proteins as potential therapeutic targets in cancer

Alternative splicing (AS) plays an important role in gene regulation, and AS perturbations are frequently observed in cancer. RNA binding protein (RBP) is one of the molecular determinants of AS, and perturbations in RBP-gene network activity are causally associated with cancer development. Here, we performed a systematic analysis to characterize the perturbations in AS events across 18 cancer types. We showed that AS alterations were prevalent in cancer and involved in cancer-related pathways. Given that the extent of AS perturbation was associated with disease severity, we proposed a computational pipeline to identify RBP regulators. Pan-cancer analysis identified a number of conserved RBP regulators, which play important roles in regulating AS of genes involved in cancer hallmark pathways. Our application analysis revealed that the expression of 68 RBP regulators helped in cancer subtyping. Specifically, we identified four subtypes of kidney cancer with differences in cancer hallmark pathway activities and prognosis. Finally, we identified the small molecules that can potentially target the RBP genes and suggested potential candidates for cancer therapy. In summary, our comprehensive AS perturbation landscape analysis identified RBPs as potential therapeutic targets in cancer and provided novel insights into the regulatory functions of RBPs in cancer.

NPI-GNN: Predicting ncRNA-protein interactions with deep graph neural networks

Noncoding RNAs (ncRNAs) play crucial roles in many biological processes. Experimental methods for identifying ncRNA-protein interactions (NPIs) are always costly and time-consuming. Many computational approaches have been developed as alternative ways. In this work, we collected five benchmarking datasets for predicting NPIs. Based on these datasets, we evaluated and compared the prediction performances of existing machine-learning based methods. Graph neural network (GNN) is a recently developed deep learning algorithm for link predictions on complex networks, which has never been applied in predicting NPIs. We constructed a GNN-based method, which is called Noncoding RNA-Protein Interaction prediction using Graph Neural Networks (NPI-GNN), to predict NPIs. The NPI-GNN method achieved comparable performance with state-of-the-art methods in a 5-fold cross-validation. In addition, it is capable of predicting novel interactions based on network information and sequence information. We also found that insufficient sequence information does not affect the NPI-GNN prediction performance much, which makes NPI-GNN more robust than other methods. As far as we can tell, NPI-GNN is the first end-to-end GNN predictor for predicting NPIs. All benchmarking datasets in this work and all source codes of the NPI-GNN method have been deposited with documents in a GitHub repo (https://github.com/AshuiRUA/NPI-GNN).

Multiple Sclerosis-Associated hnRNPA1 Mutations Alter hnRNPA1 Dynamics and Influence Stress Granule Formation

Evidence indicates that dysfunctional heterogeneous ribonucleoprotein A1 (hnRNPA1; A1) contributes to the pathogenesis of neurodegeneration in multiple sclerosis. Understanding molecular mechanisms of neurodegeneration in multiple sclerosis may result in novel therapies that attenuate neurodegeneration, thereby improving the lives of MS patients with multiple sclerosis. Using an in vitro, blue light induced, optogenetic protein expression system containing the optogene Cryptochrome 2 and a fluorescent mCherry reporter, we examined the effects of multiple sclerosis-associated somatic A1 mutations (P275S and F281L) in A1 localization, cluster kinetics and stress granule formation in real-time. We show that A1 mutations caused cytoplasmic mislocalization, and significantly altered the kinetics of A1 cluster formation/dissociation, and the quantity and size of clusters. A1 mutations also caused stress granule formation to occur more quickly and frequently in response to blue light stimulation. This study establishes a live cell optogenetics imaging system to probe localization and association characteristics of A1. It also demonstrates that somatic mutations in A1 alter its function and promote stress granule formation, which supports the hypothesis that A1 dysfunction may exacerbate neurodegeneration in multiple sclerosis.

An integrative approach uncovers transcriptome-wide determinants of mRNA stability regulation in Saccharomyces cerevisiae

mRNA degradation rate is one of the key stages of gene expression regulation in eukaryotic cells. To date, intertwined processes of post-transcriptional control have been widely investigated, but focused rather on the examination of mechanisms controlling stability of particular protein-coding transcripts. Currently, a wealth of information from structural, biochemical, and high-throughput studies makes it tempting to define general rules governing mRNA stability that could be considered as versatile and valid on a genome-wide scale. Basu et al. analyzed multiple experimental and computational data on Saccharomyces cerevisiae mRNA half-lives as well as on secondary structures and protein-binding sites within transcripts, and collated it with available structures of ribonucleases, that is, enzymes responsible for mRNA degradation. This approach allowed to conclude how particular mRNA features such as lengths of unstructured terminal or internal regions or sequestration into ribonucleoprotein complexes impact half-lives of protein-coding transcripts and to define genome-scale principles of mRNA stability control in yeast.

RBP2GO: a comprehensive pan-species database on RNA-binding proteins, their interactions and functions

RNA-protein complexes have emerged as central players in numerous key cellular processes with significant relevance in health and disease. To further deepen our knowledge of RNA-binding proteins (RBPs), multiple proteome-wide strategies have been developed to identify RBPs in different species leading to a large number of studies contributing experimentally identified as well as predicted RBP candidate catalogs. However, the rapid evolution of the field led to an accumulation of isolated datasets, hampering the access and comparison of their valuable content. Moreover, tools to link RBPs to cellular pathways and functions were lacking. Here, to facilitate the efficient screening of the RBP resources, we provide RBP2GO (https://RBP2GO.DKFZ.de), a comprehensive database of all currently available proteome-wide datasets for RBPs across 13 species from 53 studies including 105 datasets identifying altogether 22 552 RBP candidates. These are combined with the information on RBP interaction partners and on the related biological processes, molecular functions and cellular compartments. RBP2GO offers a user-friendly web interface with an RBP scoring system and powerful advanced search tools allowing forward and reverse searches connecting functions and RBPs to stimulate new research directions.

scReQTL: an approach to correlate SNVs to gene expression from individual scRNA-seq datasets

BACKGROUND

Recently, pioneering expression quantitative trait loci (eQTL) studies on single cell RNA sequencing (scRNA-seq) data have revealed new and cell-specific regulatory single nucleotide variants (SNVs). Here, we present an alternative QTL-related approach applicable to transcribed SNV loci from scRNA-seq data: scReQTL. ScReQTL uses Variant Allele Fraction (VAFRNA) at expressed biallelic loci, and corelates it to gene expression from the corresponding cell.

RESULTS

Our approach employs the advantage that, when estimated from multiple cells, VAFRNA can be used to assess effects of SNVs in a single sample or individual. In this setting scReQTL operates in the context of identical genotypes, where it is likely to capture RNA-mediated genetic interactions with cell-specific and transient effects. Applying scReQTL on scRNA-seq data generated on the 10 × Genomics Chromium platform using 26,640 mesenchymal cells derived from adipose tissue obtained from three healthy female donors, we identified 1272 unique scReQTLs. ScReQTLs common between individuals or cell types were consistent in terms of the directionality of the relationship and the effect size. Comparative assessment with eQTLs from bulk sequencing data showed that scReQTL analysis identifies a distinct set of SNV-gene correlations, that are substantially enriched in known gene-gene interactions and significant genome-wide association studies (GWAS) loci.

CONCLUSION

ScReQTL is relevant to the rapidly growing source of scRNA-seq data and can be applied to outline SNVs potentially contributing to cell type-specific and/or dynamic genetic interactions from an individual scRNA-seq dataset.

AVAILABILITY

https://github.com/HorvathLab/NGS/tree/master/scReQTL.

RNA-binding proteins La and HuR cooperatively modulate translation repression of PDCD4 mRNA

Posttranscriptional regulation of gene expression plays a critical role in controlling the inflammatory response. An uncontrolled inflammatory response results in chronic inflammation, often leading to tumorigenesis. Programmed cell death 4 (PDCD4) is a proinflammatory tumor-suppressor gene which helps to prevent the transition from chronic inflammation to cancer. PDCD4 mRNA translation is regulated by an interplay between the oncogenic microRNA miR-21 and the RNA-binding protein (RBP) human antigen R (HuR) in response to lipopolysaccharide stimulation, but the role of other regulatory factors remains unknown. Here, we report that the RBP lupus antigen (La) interacts with the 3'-untranslated region of PDCD4 mRNA and prevents miR-21-mediated translation repression. While lipopolysaccharide causes nuclear-cytoplasmic translocation of HuR, it enhances cellular La expression. Remarkably, La and HuR were found to bind cooperatively to the PDCD4 mRNA and mitigate miR-21-mediated translation repression. The cooperative action of La and HuR reduced cell proliferation and enhanced apoptosis, reversing the pro-oncogenic function of miR-21. Together, these observations demonstrate a cooperative interplay between two RBPs, triggered differentially by the same stimulus, which exerts a synergistic effect on PDCD4 expression and thereby helps maintain a balance between inflammation and tumorigenesis.

Deciphering LncRNA-protein interactions using docking complexes

Deciphering RNA-protein interactions are important to study principal biological mechanisms including transcription and translation regulation, gene silencing, among others. Predicting RNA molecule interaction with the target protein could allow us to understand important cellular processes and design novel treatment therapies for various diseases. As non-coding RNAs do not have coding potential our knowledge about their functions is still limited. Therefore, RNA-binding proteins of non-coding RNAs regulating functions, viz. including cellular maturation, nuclear export and stability may play a very important role. Keeping in view of the need for refined methods to understand protein-RNA interactions, we have attempted a docking model to infer binding sites between lncRNA NONHSAT02007 and protein KIF13A for a rare disease phenotype that we are studying in our lab.Communicated by Ramaswamy H. Sarma.

RNA-protein interactions: Central players in coordination of regulatory networks

Changes in the abundance of protein and RNA molecules can impair the formation of complexes in the cell leading to toxicity and death. Here we exploit the information contained in protein, RNA and DNA interaction networks to provide a comprehensive view of the regulation layers controlling the concentration-dependent formation of assemblies in the cell. We present the emerging concept that RNAs can act as scaffolds to promote the formation ribonucleoprotein complexes and coordinate the post-transcriptional layer of gene regulation. We describe the structural and interaction network properties that characterize the ability of protein and RNA molecules to interact and phase separate in liquid-like compartments. Finally, we show that presence of structurally disordered regions in proteins correlate with the propensity to undergo liquid-to-solid phase transitions and cause human diseases. Also see the video abstract here https://youtu.be/kfpqibsNfS0.

Ataxin-2 Dysregulation Triggers a Compensatory Fragile X Mental Retardation Protein Decrease in Drosophila C4da Neurons

Dendrites require precise and timely delivery of protein substrates to distal areas to ensure the correct morphology and function of neurons. Many of these protein substrates are supplied in the form of ribonucleoprotein (RNP) complex consisting of RNA-binding proteins (RBPs) and mRNAs, which are subsequently translated in distal dendritic areas. It remains elusive, however, whether key RBPs supply mRNA according to local demands individually or in a coordinated manner. In this study, we investigated how Drosophila sensory neurons respond to the dysregulation of a disease-associated RBP, Ataxin-2 (ATX2), which leads to dendritic defects. We found that ATX2 plays a crucial role in spacing dendritic branches for the optimal dendritic receptive fields in Drosophila class IV dendritic arborization (C4da) neurons, where both expression level and subcellular location of ATX2 contribute significantly to this effect. We showed that translational upregulation through the expression of eukaryotic translation initiation factor 4E (eIF4E) further enhanced the ATX2-induced dendritic phenotypes. Additionally, we found that the expression level of another disease-associated RBP, fragile X mental retardation protein (FMRP), decreased in both cell bodies and dendrites when neurons were faced with aberrant upregulation of ATX2. Finally, we revealed that the PAM2 motif of ATX2, which mediates its interaction with poly(A)-binding protein (PABP), is potentially necessary for the decrease of FMRP in certain neuronal stress conditions. Collectively, our data suggest that dysregulation of RBPs triggers a compensatory regulation of other functionally-overlapping RBPs to minimize RBP dysregulation-associated aberrations that hinder neuronal homeostasis in dendrites.

UBAC2 promotes bladder cancer proliferation through BCRC-3/miRNA-182-5p/p27 axis

Emerging evidences have demonstrated that ubiquitin-associated domain-containing protein 2 (UBAC2) is closely related to the occurrence and development of malignant tumors. However, the functions and underlying molecular mechanisms of UBAC2 in bladder cancer (BC) development have not been defined. In this study, we found that both UBAC2 mRNA and protein levels were upregulated in BC tissues and cell lines, and knockdown of UBAC2 inhibited BC cells proliferation both in vitro and in vivo. Meanwhile, Kaplan-Meier survival plots of 406 BC cases from TCGA database showed that higher expression of UBAC2 in BC patients was associated with lower survival rate. Mechanistic studies revealed that knockdown of UBAC2 increased the expression of p27 by posttranscriptional regulation. Our previous study indicated that circular RNA BCRC-3 (BCRC-3) promoted the expression of p27 through interacting with miR-182-5p, and reversed miR-182-5p-induced inhibition of p27 3'UTR activity. In the present study, we found that UBAC2 could bind to BCRC-3, and subsequently affected the interaction of BCRC-3 with miR-182-5p to inhibit the expression of p27. Furthermore, knockdown of BCRC-3 partly reversed the upregulation of p27 expression induced by knockdown of UBAC2. Our findings highlight a novel mechanism of UBAC2 in regulating p27 through affecting the function of BCRC-3, and provide a research basis for the diagnostic and therapeutic application of BC.

Implications of RNG140 (caprin2)-mediated translational regulation in eye lens differentiation

Regulation of gene expression at the translational level is key to determining cell fate and function. An RNA-binding protein, RNG140 (caprin2), plays a role in eye lens differentiation and has been reported to function in translational regulation. However, the mechanism and its role in eyes has remained unclear. Here, we show that RNG140 binds to the translation initiation factor eukaryotic initiation factor 3 (eIF3) and suppresses translation through mechanisms involving suppression of eIF3-dependent translation initiation. Comprehensive ribosome profiling revealed that overexpression of RNG140 in cultured Chinese hamster ovary cells reduces translation of long mRNAs, including those associated with cell proliferation. RNG140-mediated translational regulation also operates in the mouse eye, where RNG140 knockout increased the translation of long mRNAs. mRNAs involved in lens differentiation, such as crystallin mRNAs, are short and can escape translational inhibition by RNG140 and be translated in differentiating lenses. Thus, this study provides insights into the mechanistic basis of lens cell transition from proliferation to differentiation via RNG140-mediated translational regulation.

Deletion of Endonuclease V suppresses chemically induced hepatocellular carcinoma

Endonuclease V (EndoV) is a conserved inosine-specific ribonuclease with unknown biological function. Here, we present the first mouse model lacking EndoV, which is viable without visible abnormalities. We show that endogenous murine EndoV cleaves inosine-containing RNA in vitro, nevertheless a series of experiments fails to link an in vivo function to processing of such transcripts. As inosine levels and adenosine-to-inosine editing often are dysregulated in hepatocellular carcinoma (HCC), we chemically induced HCC in mice. All mice developed liver cancer, however, EndoV^−/− tumors were significantly fewer and smaller than wild type tumors. Opposed to human HCC, adenosine deaminase mRNA expression and site-specific editing were unaltered in our model. Loss of EndoV did not affect editing levels in liver tumors, however mRNA expression of a selection of cancer related genes were reduced. Inosines are also found in certain tRNAs and tRNAs are cleaved during stress to produce signaling entities. tRNA fragmentation was dysregulated in EndoV^−/− livers and apparently, inosine-independent. We speculate that the inosine-ribonuclease activity of EndoV is disabled in vivo, but RNA binding allowed to promote stabilization of transcripts or recruitment of proteins to fine-tune gene expression. The EndoV^−/− tumor suppressive phenotype calls for related studies in human HCC.

Increased nuclear but not cytoplasmic activities of CELF1 protein leads to muscle wasting

mRNA processing is highly regulated during development through changes in RNA-binding protein (RBP) activities. CUG-BP, Elav-like family member 1 (CELF1, also called CUGBP1) is an RBP, the expression of which decreases in skeletal muscle soon after birth. CELF1 regulates multiple nuclear and cytoplasmic RNA processing events. In the nucleus, CELF1 regulates networks of postnatal alternative splicing (AS) transitions, while in the cytoplasm, CELF1 regulates mRNA stability and translation. Stabilization and misregulation of CELF1 has been implicated in human diseases including myotonic dystrophy type 1, Alzheimer's disease and multiple cancers. To understand the contribution of nuclear and cytoplasmic CELF1 activity to normal and pathogenic skeletal muscle biology, we generated transgenic mice for doxycycline-inducible and skeletal muscle-specific expression of active CELF1 mutants engineered to be localized predominantly to either the nucleus or the cytoplasm. Adult mice expressing nuclear, but not cytoplasmic, CELF1 are characterized by strong histopathological defects, muscle loss within 10 days and changes in AS. In contrast, mice expressing cytoplasmic CELF1 display changes in protein levels of targets known to be regulated at the level of translation by CELF1, with minimal changes in AS. These changes are in the absence of overt histopathological changes or muscle loss. RNA-sequencing revealed extensive gene expression and AS changes in mice overexpressing nuclear and naturally localized CELF1 protein, with affected genes involved in cytoskeleton dynamics, membrane dynamics, RNA processing and zinc ion binding. These results support a stronger role for nuclear CELF1 functions as compared to cytoplasmic CELF1 functions in skeletal muscle wasting.

PolyASite 2.0: a consolidated atlas of polyadenylation sites from 3' end sequencing

Generated by 3′ end cleavage and polyadenylation at alternative polyadenylation (poly(A)) sites, alternative terminal exons account for much of the variation between human transcript isoforms. More than a dozen protocols have been developed so far for capturing and sequencing RNA 3′ ends from a variety of cell types and species. In previous studies, we have used these data to uncover novel regulatory signals and cell type-specific isoforms. Here we present an update of the PolyASite (https://polyasite.unibas.ch) resource of poly(A) sites, constructed from publicly available human, mouse and worm 3′ end sequencing datasets by enforcing uniform quality measures, including the flagging of putative internal priming sites. Through integrated processing of all data, we identified and clustered sites that are closely spaced and share polyadenylation signals, as these are likely the result of stochastic variations in processing. For each cluster, we identified the representative - most frequently processed - site and estimated the relative use in the transcriptome across all samples. We have established a modern web portal for efficient finding, exploration and export of data. Database generation is fully automated, greatly facilitating incorporation of new datasets and the updating of underlying genome resources.

The prognostic and clinicopathological significance of RBM3 in the survival of patients with tumor: A Prisma-compliant meta-analysis

BACKGROUND

RNA-binding motif protein 3 (RBM3) plays an important role in carcinogenesis and tumor progression. However, the prognostic role of RBM3 in human carcinomas remains controversial. Therefore, we took a meta-analysis to research the association between the overall survival of patients with cancer and the expression of RBM3.

METHODS

Systematic literature research identified 17 potentially eligible studies comprising 4976 patients in ten different cancer types. Two researchers independently screened the content and quality of studies and extracted data. Correlations of RBM3 expression and survival were analyzed and the hazard ratios (HRs) with 95% confidence intervals (95% CIs) were calculated.

RESULTS

In the pooled analysis, overexpression of RBM3 was related to improved overall survival (OS), recurrence-free survival (RFS), and disease-free survival (DFS) in patients with cancer having a pooled HR of 0.61 (HR = 0.61; 95% CI: 0.47-0.69), 0.57 (HR = 0.60; 95% CI: 0.50-0.71) and 0.54 (HR 0.54; 95% CI: 0.38-0.78). Besides, subgroup analysis proved that overexpression of RBM3 was related to improved OS in colorectal cancer (HR = 0.61, 95% CI: 0.43-0.86), melanoma (HR = 0.32, 95% CI: 0.20-0.52), and gastric cancer (HR = 0.51, 95% CI: 0.35-0.73). However, subgroup analysis according to tumor type revealed that overexpression of RBM3 was not related to better OS in breast carcinoma (HR = 0.52, 95% CI: 0.17-0.61).

CONCLUSIONS

Our results indicated that RBM3 overexpression was significantly predictive of better prognosis in various human cancers. For certain tumors, overexpression RBM3 might be a marker of improved survival in humans with cancer, except for breast cancer.

Identification, quantification and bioinformatic analysis of RNA-dependent proteins by RNase treatment and density gradient ultracentrifugation using R-DeeP

Analysis of RNA-protein complexes is central to understanding the molecular circuitry governing cellular processes. In recent years, several proteome-wide studies have been dedicated to the identification of RNA-binding proteins. Here, we describe in detail R-DeeP, an approach built on RNA dependence, defined as the ability of a protein to engage in protein complexes only in the presence of RNA, involving direct or indirect interaction with RNA. This approach provides-for the first time, to our knowledge-quantitative information on the fraction of a protein associated with RNA-protein complexes. R-DeeP is independent of any potentially biased purification procedures. It is based on cellular lysate fractionation by density gradient ultracentrifugation and subsequent analysis by proteome-wide mass spectrometry (MS) or individual western blotting. The comparison of lysates with and without previous RNase treatment enables the identification of differences in the apparent molecular weight and, hence, the size of the complexes. In combination with information from databases of protein-protein complexes, R-DeeP facilitates the computational reconstruction of protein complexes from proteins migrating in the same fraction. In addition, we developed a pipeline for the statistical analysis of the MS dataset to automatically identify RNA-dependent proteins (proteins whose interactome depends on RNA). With this protocol, the individual analysis of proteins of interest by western blotting can be completed within 1-2 weeks. For proteome-wide studies, additional time is needed for the integration of the proteomic and statistical analyses. In the future, R-DeeP can be extended to other fractionation techniques, such as chromatography.

Estimating the Allele-Specific Expression of SNVs From 10× Genomics Single-Cell RNA-Sequencing Data

With the recent advances in single-cell RNA-sequencing (scRNA-seq) technologies, the estimation of allele expression from single cells is becoming increasingly reliable. Allele expression is both quantitative and dynamic and is an essential component of the genomic interactome. Here, we systematically estimate the allele expression from heterozygous single nucleotide variant (SNV) loci using scRNA-seq data generated on the 10×Genomics Chromium platform. We analyzed 26,640 human adipose-derived mesenchymal stem cells (from three healthy donors), sequenced to an average of 150K sequencing reads per cell (more than 4 billion scRNA-seq reads in total). High-quality SNV calls assessed in our study contained approximately 15% exonic and >50% intronic loci. To analyze the allele expression, we estimated the expressed variant allele fraction (VAF_RNA) from SNV-aware alignments and analyzed its variance and distribution (mono- and bi-allelic) at different minimum sequencing read thresholds. Our analysis shows that when assessing positions covered by a minimum of three unique sequencing reads, over 50% of the heterozygous SNVs show bi-allelic expression, while at a threshold of 10 reads, nearly 90% of the SNVs are bi-allelic. In addition, our analysis demonstrates the feasibility of scVAF_RNA estimation from current scRNA-seq datasets and shows that the 3′-based library generation protocol of 10×Genomics scRNA-seq data can be informative in SNV-based studies, including analyses of transcriptional kinetics.

Predicting lncRNA-Protein Interactions With miRNAs as Mediators in a Heterogeneous Network Model

Long non-coding RNAs (lncRNAs) play important roles in various biological processes, where lncRNA–protein interactions are usually involved. Therefore, identifying lncRNA–protein interactions is of great significance to understand the molecular functions of lncRNAs. Since the experiments to identify lncRNA–protein interactions are always costly and time consuming, computational methods are developed as alternative approaches. However, existing lncRNA–protein interaction predictors usually require prior knowledge of lncRNA–protein interactions with experimental evidences. Their performances are limited due to the number of known lncRNA–protein interactions. In this paper, we explored a novel way to predict lncRNA–protein interactions without direct prior knowledge. MiRNAs were picked up as mediators to estimate potential interactions between lncRNAs and proteins. By validating our results based on known lncRNA–protein interactions, our method achieved an AUROC (Area Under Receiver Operating Curve) of 0.821, which is comparable to the state-of-the-art methods. Moreover, our method achieved an improved AUROC of 0.852 by further expanding the training dataset. We believe that our method can be a useful supplement to the existing methods, as it provides an alternative way to estimate lncRNA–protein interactions in a heterogeneous network without direct prior knowledge. All data and codes of this work can be downloaded from GitHub (https://github.com/zyk2118216069/LncRNA-protein-interactions-prediction).

LPGNMF: Predicting Long Non-Coding RNA and Protein Interaction Using Graph Regularized Nonnegative Matrix Factorization

Long non-coding RNAs (lncRNA) play crucial roles in a variety of biological processes and complex diseases. Massive studies have indicated that lncRNAs interact with related proteins to exert regulation of cellular biological processes. Because it is time-consuming and expensive to determine lncRNA-protein interaction by experiment, more accurate predictions of interaction by computational methods are imperative. We propose a novel computational approach, predicting lncRNA-protein interaction using graph regularized nonnegative matrix factorization (LPGNMF), to discover unobserved lncRNA-protein association. First, we calculate lncRNA similarity and protein similarity by integrating the lncRNA expression information and gene ontology information. Subsequently, we utilize graph regularized nonnegative matrix factorization framework to predict potential interactions for all lncRNA simultaneously. In the cross validation test, LPGNMF achieves an AUC of 85.2 percent, higher than those of other compared methods. In addition, novel lncRNA-protein interactions detected by LPGNMF are validated by literatures or database. The results indicate that our method is effective to discover potential lncRNA-protein interaction.

LINC00680 and TTN-AS1 Stabilized by EIF4A3 Promoted Malignant Biological Behaviors of Glioblastoma Cells

Glioblastomas are the most common and malignant intracranial tumors with a low survival rate. Dysregulation of long non-coding RNAs and RNA-binding protein causes various diseases, including cancers. However, the function of LINC00680 and TTN-AS1 in the progression of glioblastomas is still elusive. In this study, we detected that LINC00680 and TTN-AS1 were upregulated in glioblastoma cells. RNA-binding protein EIF4A3 could prolong the half-life of LINC00680 and TTN-AS1. Knockdown of EIF4A3, LINC00680, and TTN-AS1 impaired proliferation, migration, and invasion and inhibited the growth of tumor in vivo and promoted apoptosis of glioblastoma cells. miR-320b was proven to be a target of LINC00680 and TTN-AS1. They interacted with miR-320b as competing endogenous RNAs, which resulted in the reduction of binding between transcriptional factor EGR3 (early growth response 3) mRNA and miR-320b. The accumulation of EGR3 promoted expression of plakophilin (PKP)2, which could activate the epidermal growth factor receptor (EFGR) pathway, leading to the malignant biological behaviors of glioblastoma cells. In summary, LINC00680 and TTN-AS1 promoted glioblastoma cell malignant biological behaviors via the miR-320b/EGR3/PKP2 axis by being stabilized by EIF4A3, which may provide a novel strategy for glioblastoma therapy.