Dissecting the expression relationships between RNA-binding proteins and their cognate targets in eukaryotic post-transcriptional regulatory networks

PABPN1 loss-of-function causes APA-shift in oculopharyngeal muscular dystrophy

Alternative polyadenylation (APA) at the 3' UTR of transcripts contributes to the cell transcriptome. APA is suppressed by the nuclear RNA-binding protein PABPN1. Aging-associated reduced PABPN1 levels in skeletal muscles lead to muscle wasting. Muscle weakness in oculopharyngeal muscular dystrophy (OPMD) is caused by short alanine expansion in PABPN1 exon1. The expanded PABPN1 forms nuclear aggregates, an OPMD hallmark. Whether the expanded PABPN1 affects APA and how it contributes to muscle pathology is unresolved. To investigate these questions, we developed a procedure including RNA library preparation and a simple pipeline calculating the APA-shift ratio as a readout for PABPN1 activity. Comparing APA-shift results to previously published PAS utilization and APA-shift results, we validated this procedure. The procedure was then applied on the OPMD cell model and on RNA from OPMD muscles. APA-shift was genome-wide in the mouse OPMD model, primarily affecting muscle transcripts. In OPMD individuals, APA-shift was enriched with muscle transcripts. In an OPMD cell model APA-shift was not significant. APA-shift correlated with reduced expression levels of a subset of PABPN1 isoforms, whereas the expression of the expanded PABPN1 did not correlate with APA-shift. PABPN1 activity is not affected by the expression of expanded PABPN1, but rather by reduced PABPN1 expression levels. In muscles, PABPN1 activity initially affects muscle transcripts. We suggest that muscle weakness in OPMD is caused by PABPN1 loss-of-function leading to APA-shift that primarily affects in muscle transcripts.

Manipulating mRNA-binding protein Cth2 function in budding yeast Saccharomyces cerevisiae

Here, we present a protocol for modulating the function of the Cth2 mRNA-binding protein (RBP) in Saccharomyces cerevisiae. We describe steps to amplify and integrate mutations in Cth2 that affect its stability and function. Next, we detail the functional assay to verify the activity of the wild-type and mutant versions of Cth2 in yeast cells. This protocol can be adopted to modify the function of other RBPs with their respective functional mutations. For complete details on the use and execution of this protocol, please refer to Patnaik et al. (2022).1.

Integrated Analysis of the Roles of RNA Binding Proteins and Their Prognostic Value in Clear Cell Renal Cell Carcinoma

Methods

We downloaded the RNA sequencing data of ccRCC from the Cancer Genome Atlas (TCGA) database and identified differently expressed RBPs in different tissues. In this study, we used bioinformatics to analyze the expression and prognostic value of RBPs; then, we performed functional analysis and constructed a protein interaction network for them. We also screened out some RBPs related to the prognosis of ccRCC. Finally, based on the identified RBPs, we constructed a prognostic model that can predict patients' risk of illness and survival time. Also, the data in the HPA database were used for verification.

Results

In our experiment, we obtained 539 ccRCC samples and 72 normal controls. In the subsequent analysis, 87 upregulated RBPs and 38 downregulated RBPs were obtained. In addition, 9 genes related to the prognosis of patients were selected, namely, RPL36A, THOC6, RNASE2, NOVA2, TLR3, PPARGC1A, DARS, LARS2, and U2AF1L4. We further constructed a prognostic model based on these genes and plotted the ROC curve. This ROC curve performed well in judgement and evaluation. A nomogram that can judge the patient's life span is also made.

Conclusion

In conclusion, we have identified differentially expressed RBPs in ccRCC and carried out a series of in-depth research studies, the results of which may provide ideas for the diagnosis of ccRCC and the research of new targeted drugs.

A Non-amyloid Prion Particle that Activates a Heritable Gene Expression Program

Spatiotemporal gene regulation is often driven by RNA-binding proteins that harbor long intrinsically disordered regions in addition to folded RNA-binding domains. We report that the disordered region of the evolutionarily ancient developmental regulator Vts1/Smaug drives self-assembly into gel-like condensates. These proteinaceous particles are not composed of amyloid, yet they are infectious, allowing them to act as a protein-based epigenetic element: a prion [SMAUG⁺]. In contrast to many amyloid prions, condensation of Vts1 enhances its function in mRNA decay, and its self-assembly properties are conserved over large evolutionary distances. Yeast cells harboring [SMAUG⁺] downregulate a coherent network of mRNAs and exhibit improved growth under nutrient limitation. Vts1 condensates formed from purified protein can transform naive cells to acquire [SMAUG⁺]. Our data establish that non-amyloid self-assembly of RNA-binding proteins can drive a form of epigenetics beyond the chromosome, instilling adaptive gene expression programs that are heritable over long biological timescales.

MERIT: Systematic Analysis and Characterization of Mutational Effect on RNA Interactome Topology

The interaction between RNA-binding proteins (RBPs) and RNA plays an important role in regulating cellular function. However, decoding genome-wide protein-RNA regulatory networks as well as how cancer-related mutations impair RNA regulatory activities in hepatocellular carcinoma (HCC) remains mostly undetermined. We explored the genetic alteration patterns of RBPs and found that deleterious mutations are likely to occur on the surface of RBPs. We then constructed protein-RNA interactome networks by integration of target binding screens and expression profiles. Network analysis highlights regulatory principles among interacting RBPs. In addition, somatic mutations selectively target functionally important genes (cancer genes, core fitness genes, or conserved genes) and perturb the RBP-gene regulatory networks in cancer. These regulatory patterns were further validated using independent data. A computational method (Mutational Effect on RNA Interactome Topology) and a web-based, user-friendly resource were further proposed to analyze the RBP-gene regulatory networks across cancer types. Pan-cancer analysis also suggests that cancer cells selectively target "vulnerability" genes to perturb protein-RNA interactome that is involved in cancer hallmark-related functions. Specifically, we experimentally validated four pairs of RBP-gene interactions perturbed by mutations in HCC, which play critical roles in cell proliferation. Based on the expression of perturbed RBP and target genes, we identified three subtypes of HCC with different survival rates. Conclusion: Our results provide a valuable resource for characterizing somatic mutation-perturbed protein-RNA regulatory networks in HCC, yielding valuable insights into the genotype-phenotype relationships underlying human cancer, and potential biomarkers for precision medicine.

RNA-protein interactions: disorder, moonlighting and junk contribute to eukaryotic complexity

RNA-protein interactions are crucial for most biological processes in all organisms. However, it appears that the complexity of RNA-based regulation increases with the complexity of the organism, creating additional regulatory circuits, the scope of which is only now being revealed. It is becoming apparent that previously unappreciated features, such as disordered structural regions in proteins or non-coding regions in DNA leading to higher plasticity and pliability in RNA-protein complexes, are in fact essential for complex, precise and fine-tuned regulation. This review addresses the issue of the role of RNA-protein interactions in generating eukaryotic complexity, focusing on the newly characterized disordered RNA-binding motifs, moonlighting of metabolic enzymes, RNA-binding proteins interactions with different RNA species and their participation in regulatory networks of higher order.

Computational approaches for the analysis of RNA-protein interactions: A primer for biologists

RNA-binding proteins (RBPs) play important roles in the control of gene expression and the coordination of different layers of post-transcriptional regulation. Interactions between certain RBPs and mRNA transcripts are notoriously difficult to predict, as any given protein-RNA interaction may rely not only on RNA sequence, but also on three-dimensional RNA structures, competitive inhibition from other RBPs, and input from cellular signaling pathways. Advanced and high-throughput technologies for the identification of RNA-protein interactions have come to the rescue, but the identification of binding sites and downstream functional effects of RBPs from the resulting data can be challenging. In this review, we discuss statistical inference and machine-learning approaches and tools relevant for the study of RBPs and the analysis of large-scale RNA-protein interaction datasets. This primer is intended for life scientists who are interested in incorporating these tools into their own research. We begin with the demystification of regression models, as used in the analysis of next-generation sequencing data, and progress to a discussion of Hidden Markov Models, which are of particular value in analyzing cross-linking followed by immunoprecipitation data. We then continue with examples of machine learning techniques, such as support vector machines and gradient tree boosting. We close with a brief discussion of current trends in the field, including deep learning architectures.

Nuclear Speckle RNA Binding Proteins Remodel Alternative Splicing and the Non-coding Arabidopsis Transcriptome to Regulate a Cross-Talk Between Auxin and Immune Responses

Nuclear speckle RNA binding proteins (NSRs) act as regulators of alternative splicing (AS) and auxin-regulated developmental processes such as lateral root formation in Arabidopsis thaliana. These proteins were shown to interact with specific alternatively spliced mRNA targets and at least with one structured lncRNA, named Alternative Splicing Competitor RNA. Here, we used genome-wide analysis of RNAseq to monitor the NSR global role on multiple tiers of gene expression, including RNA processing and AS. NSRs affect AS of 100s of genes as well as the abundance of lncRNAs particularly in response to auxin. Among them, the FPA floral regulator displayed alternative polyadenylation and differential expression of antisense COOLAIR lncRNAs in nsra/b mutants. This may explains the early flowering phenotype observed in nsra and nsra/b mutants. GO enrichment analysis of affected lines revealed a novel link of NSRs with the immune response pathway. A RIP-seq approach on an NSRa fusion protein in mutant background identified that lncRNAs are privileged direct targets of NSRs in addition to specific AS mRNAs. The interplay of lncRNAs and AS mRNAs in NSR-containing complexes may control the crosstalk between auxin and the immune response pathway.

The yeast noncoding RNA interaction network

This article describes the creation of the first expert manually curated noncoding RNA interaction networks for S. cerevisiae The RNA-RNA and RNA-protein interaction networks have been carefully extracted from the experimental literature and made available through the IntAct database (www.ebi.ac.uk/intact). We provide an initial network analysis and compare their properties to the much larger protein-protein interaction network. We find that the proteins that bind to ncRNAs in the network contain only a small proportion of classical RNA binding domains. We also see an enrichment of WD40 domains suggesting their direct involvement in ncRNA interactions. We discuss the challenges in collecting noncoding RNA interaction data and the opportunities for worldwide collaboration to fill the unmet need for this data.

T-Cell Intracellular Antigens and Hu Antigen R Antagonistically Modulate Mitochondrial Activity and Dynamics by Regulating Optic Atrophy 1 Gene Expression

Mitochondria undergo frequent morphological changes to control their function. We show here that T-cell intracellular antigens (TIA1b/TIARb) and Hu antigen R (HuR) have antagonistic roles in mitochondrial function by modulating the expression of mitochondrial shaping proteins. Expression of TIA1b/TIARb alters the mitochondrial dynamic network by enhancing fission and clustering, which is accompanied by a decrease in respiration. In contrast, HuR expression promotes fusion and cristae remodeling and increases respiratory activity. Mechanistically, TIA proteins downregulate the expression of optic atrophy 1 (OPA1) protein via switching of the splicing patterns of OPA1 to facilitate the production of OPA1 variant 5 (OPA1v5). Conversely, HuR enhances the expression of OPA1 mRNA isoforms through increasing steady-state levels and targeting translational efficiency at the 3' untranslated region. Knockdown of TIA1/TIAR or HuR partially reversed the expression profile of OPA1, whereas knockdown of OPA1 or overexpression of OPA1v5 provoked mitochondrial clustering. Middle-term expression of TIA1b/TIARb triggers reactive oxygen species production and mitochondrial DNA damage, which is accompanied by mitophagy, autophagy, and apoptosis. In contrast, HuR expression promotes mitochondrion-dependent cell proliferation. Collectively, these results provide molecular insights into the antagonistic functions of TIA1b/TIARb and HuR in mitochondrial activity dynamics and suggest that their balance might contribute to mitochondrial physiopathology.