The RNA secondary structure of androgen receptor-FL and V7 transcripts reveals novel regulatory regions.

The androgen receptor (AR) is a ligand-dependent nuclear transcription factor belonging to the steroid hormone nuclear receptor family. Due to its roles in regulating cell proliferation and differentiation, AR is tightly regulated to maintain proper levels of itself and the many genes it controls. AR dysregulation is a driver of many human diseases including prostate cancer. Though this dysregulation often occurs at the RNA level, there are many unknowns surrounding post-transcriptional regulation of AR mRNA, particularly the role that RNA secondary structure plays. Thus, a comprehensive analysis of AR transcript secondary structure is needed. We address this through the computational and experimental analyses of two key isoforms, full length (AR-FL) and truncated (AR-V7). Here, a combination of in-cell RNA secondary structure probing experiments (targeted DMS-MaPseq) and computational predictions were used to characterize the static structural landscape and conformational dynamics of both isoforms. Additionally, in-cell assays were used to identify functionally relevant structures in the 5' and 3' UTRs of AR-FL. A notable example is a conserved stem loop structure in the 5'UTR of AR-FL that can bind to Poly(RC) Binding Protein 2 (PCBP2). Taken together, our results reveal novel features that regulate AR expression.

Identification of MYC intron 2 regions that modulate expression.

MYC pre-mRNA is spliced with high fidelity to produce the transcription factor known to regulate cellular differentiation, proliferation, apoptosis, and alternative splicing. The mechanisms underpinning the pre-mRNA splicing of MYC, however, remain mostly unexplored. In this study, we examined the interaction of heterogeneous nuclear ribonucleoprotein C (HNRNPC) with MYC intron 2. Building off published eCLIP studies, we confirmed this interaction with poly(U) regions in intron 2 of MYC and found that full binding is correlated with optimal protein production. The interaction appears to be compensatory, as mutational disruption of all three poly(U) regions was required to reduce both HNRNPC binding capacity and fidelity of either splicing or translation. Poly(U) sequences in MYC intron 2 were relatively conserved across sequences from several different species. Lastly, we identified a short sequence just upstream of an HNRNPC binding region that when removed enhances MYC translation.

SARS-CoV-2 Orphan Gene ORF10 Contributes to More Severe COVID-19 Disease.

The orphan gene of SARS-CoV-2, ORF10, is the least studied gene in the virus responsible for the COVID-19 pandemic. Recent experimentation indicated ORF10 expression moderates innate immunity in vitro. However, whether ORF10 affects COVID-19 in humans remained unknown. We determine that the ORF10 sequence is identical to the Wuhan-Hu-1 ancestral haplotype in 95% of genomes across five variants of concern (VOC). Four ORF10 variants are associated with less virulent clinical outcomes in the human host: three of these affect ORF10 protein structure, one affects ORF10 RNA structural dynamics. RNA-Seq data from 2070 samples from diverse human cells and tissues reveals ORF10 accumulation is conditionally discordant from that of other SARS-CoV-2 transcripts. Expression of ORF10 in A549 and HEK293 cells perturbs immune-related gene expression networks, alters expression of the majority of mitochondrially-encoded genes of oxidative respiration, and leads to large shifts in levels of 14 newly-identified transcripts. We conclude ORF10 contributes to more severe COVID-19 clinical outcomes in the human host.

Discovery of RNA secondary structural motifs using sequence-ordered thermodynamic stability and comparative sequence analysis.

Major advances in RNA secondary structural motif prediction have been achieved in the last few years; however, few methods harness the predictive power of multiple approaches to deliver in-depth characterizations of local RNA motifs and their potential functionality. Additionally, most available methods do not predict RNA pseudoknots. This work combines complementary bioinformatic systems into one robust discovery pipeline where: •RNA sequences are folded to search for thermodynamically favorable motifs utilizing ScanFold.•Motifs are expanded and refolded into alternate pseudoknot conformations by Knotty/Iterative HFold.•All conformations are evaluated for covariance via the cm-builder pipeline (Infernal and R-scape).

Direct interaction of small non-coding RNAs CjNC140 and CjNC110 optimizes expression of key pathogenic phenotypes of Campylobacter jejuni.

Small non-coding RNAs (sRNAs) are important players in modulating gene expression in bacterial pathogens, but their functions are largely undetermined in Campylobacter jejuni, an important cause of foodborne gastroenteritis in humans. In this study, we elucidated the functions of sRNA CjNC140 and its interaction with CjNC110, a previously characterized sRNA involved in the regulation of several virulence phenotypes of C. jejuni. Inactivation of CjNC140 increased motility, autoagglutination, L-methionine concentration, autoinducer-2 production, hydrogen peroxide resistance, and early chicken colonization, indicating a primarily inhibitory role of CjNC140 for these phenotypes. Apart from motility, all these effects directly contrasted the previously demonstrated positive regulation by CjNC110, suggesting that CjNC110 and CjNC140 operate in an opposite manner to modulate physiologic processes in C. jejuni. RNAseq and northern blotting further demonstrated that expression of CjNC140 increased in the absence of CjNC110, while expression of CjNC110 decreased in the absence of CjNC140, suggesting a possibility of their direct interaction. Indeed, electrophoretic mobility shift assay demonstrated a direct binding between the two sRNAs via GA- (CjNC110) and CU- (CjNC140) rich stem-loops. Additionally, RNAseq and follow-up experiments identified that CjNC140 positively regulates p19, which encodes a key iron uptake transporter in Campylobacter. Furthermore, computational analysis revealed both CjNC140 and CjNC110 are highly conserved in C. jejuni, and the predicted secondary structures support CjNC140 as a functional homolog of the iron regulatory sRNA, RyhB. These findings establish CjNC140 and CjNC110 as a key checks-and- balances mechanism in maintaining homeostasis of gene expression and optimizing phenotypes critical for C. jejuni pathobiology. IMPORTANCE Gene regulation is critical to all aspects of pathogenesis of bacterial disease, and small non-coding RNAs (sRNAs) represent a new frontier in gene regulation of bacteria. In Campylobacter jejuni, the role of sRNAs remains largely unexplored. Here, we investigate the role of two highly conserved sRNAs, CjNC110 and CjNC140, and demonstrate that CjNC140 displays a primarily inhibitory role in contrast to a primarily activating role for CjNC110 for several key virulence-associated phenotypes. Our results also revealed that the sRNA regulatory pathway is intertwined with the iron uptake system, another virulence mechanism critical for in vivo colonization. These findings open a new direction for understanding C. jejuni pathobiology and identify potential targets for intervention for this major foodborne pathogen.

In vivo secondary structural analysis of Influenza A virus genomic RNA.

Influenza A virus (IAV) is a respiratory virus that causes epidemics and pandemics. Knowledge of IAV RNA secondary structure in vivo is crucial for a better understanding of virus biology. Moreover, it is a fundament for the development of new RNA-targeting antivirals. Chemical RNA mapping using selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) coupled with Mutational Profiling (MaP) allows for the thorough examination of secondary structures in low-abundance RNAs in their biological context. So far, the method has been used for analyzing the RNA secondary structures of several viruses including SARS-CoV-2 in virio and in cellulo. Here, we used SHAPE-MaP and dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) for genome-wide secondary structure analysis of viral RNA (vRNA) of the pandemic influenza A/California/04/2009 (H1N1) strain in both in virio and in cellulo environments. Experimental data allowed the prediction of the secondary structures of all eight vRNA segments in virio and, for the first time, the structures of vRNA5, 7, and 8 in cellulo. We conducted a comprehensive structural analysis of the proposed vRNA structures to reveal the motifs predicted with the highest accuracy. We also performed a base-pairs conservation analysis of the predicted vRNA structures and revealed many highly conserved vRNA motifs among the IAVs. The structural motifs presented herein are potential candidates for new IAV antiviral strategies.

ScanFold 2.0: a rapid approach for identifying potential structured RNA targets in genomes and transcriptomes.

A major limiting factor in target discovery for both basic research and therapeutic intervention is the identification of structural and/or functional RNA elements in genomes and transcriptomes. This was the impetus for the original ScanFold algorithm, which provides maps of local RNA structural stability, evidence of sequence-ordered (potentially evolved) structure, and unique model structures comprised of recurring base pairs with the greatest structural bias. A key step in quantifying this propensity for ordered structure is the prediction of secondary structural stability for randomized sequences which, in the original implementation of ScanFold, is explicitly evaluated. This slow process has limited the rapid identification of ordered structures in large genomes/transcriptomes, which we seek to overcome in this current work introducing ScanFold 2.0. In this revised version of ScanFold, we no longer explicitly evaluate randomized sequence folding energy, but rather estimate it using a machine learning approach. For high randomization numbers, this can increase prediction speeds over 100-fold compared to ScanFold 1.0, allowing for the analysis of large sequences, as well as the use of additional folding algorithms that may be computationally expensive. In the testing of ScanFold 2.0, we re-evaluate the Zika, HIV, and SARS-CoV-2 genomes and compare both the consistency of results and the time of each run to ScanFold 1.0. We also re-evaluate the SARS-CoV-2 genome to assess the quality of ScanFold 2.0 predictions vs several biochemical structure probing datasets and compare the results to those of the original ScanFold program.

Thermodynamic and structural characterization of an EBV infected B-cell lymphoma transcriptome.

Epstein-Barr virus (EBV) is a widely prevalent human herpes virus infecting over 95% of all adults and is associated with a variety of B-cell cancers and induction of multiple sclerosis. EBV accomplishes this in part by expression of coding and noncoding RNAs and alteration of the host cell transcriptome. To better understand the structures which are forming in the viral and host transcriptomes of infected cells, the RNA structure probing technique Structure-seq2 was applied to the BJAB-B1 cell line (an EBV infected B-cell lymphoma). This resulted in reactivity profiles and secondary structural analyses for over 10000 human mRNAs and lncRNAs, along with 19 lytic and latent EBV transcripts. We report in-depth structural analyses for the human MYC mRNA and the human lncRNA CYTOR. Additionally, we provide a new model for the EBV noncoding RNA EBER2 and provide the first reported model for the EBV tandem terminal repeat RNA. In-depth thermodynamic and structural analyses were carried out with the motif discovery tool ScanFold and RNAfold prediction tool; subsequent covariation analyses were performed on resulting models finding various levels of support. ScanFold results for all analyzed transcripts are made available for viewing and download on the user-friendly RNAStructuromeDB.

Expansion of the RNAStructuromeDB to include secondary structural data spanning the human protein-coding transcriptome.

RNA plays vital functional roles in almost every component of biology, and these functional roles are often influenced by its folding into secondary and tertiary structures. An important role of RNA secondary structure is in maintaining proper gene regulation; therefore, making accurate predictions of the structures involved in these processes is important. In this study, we have expanded on our previous work that led to the creation of the RNAStructuromeDB. Unlike this previous study that analyzed the human genome at low resolution, we have now scanned the protein-coding human transcriptome at high (single nt) resolution. This provides more robust structure predictions for over 100,000 isoforms of known protein-coding genes. Notably, we also utilize the motif identification tool, ScanFold, to model structures with high propensity for ordered/evolved stability. All data have been uploaded to the RNAStructuromeDB, allowing for easy searching of transcripts, visualization of data tracks (via the Integrative Genomics Viewer or IGV), and download of ScanFold data-including unique highly-ordered motifs. Herein, we provide an example analysis of MAT2A to demonstrate the utility of ScanFold at finding known and novel secondary structures, highlighting regions of potential functionality, and guiding generation of functional hypotheses through use of the data.

Structural Context of a Critical Exon of Spinal Muscular Atrophy Gene.

Humans contain two nearly identical copies of Survival Motor Neuron genes, SMN1 and SMN2. Deletion or mutation of SMN1 causes spinal muscular atrophy (SMA), one of the leading genetic diseases associated with infant mortality. SMN2 is unable to compensate for the loss of SMN1 due to predominant exon 7 skipping, leading to the production of a truncated protein. Antisense oligonucleotide and small molecule-based strategies aimed at the restoration of SMN2 exon 7 inclusion are approved therapies of SMA. Many cis-elements and transacting factors have been implicated in regulation of SMN exon 7 splicing. Also, several structural elements, including those formed by a long-distance interaction, have been implicated in the modulation of SMN exon 7 splicing. Several of these structures have been confirmed by enzymatic and chemical structure-probing methods. Additional structures formed by inter-intronic interactions have been predicted by computational algorithms. SMN genes generate a vast repertoire of circular RNAs through inter-intronic secondary structures formed by inverted Alu repeats present in large number in SMN genes. Here, we review the structural context of the exonic and intronic cis-elements that promote or prevent exon 7 recognition. We discuss how structural rearrangements triggered by single nucleotide substitutions could bring drastic changes in SMN2 exon 7 splicing. We also propose potential mechanisms by which inter-intronic structures might impact the splicing outcomes.

Transcriptome-Wide Mapping of Small-Molecule RNA-Binding Sites in Cells Informs an Isoform-Specific Degrader of QSOX1 mRNA.

The interactions between cellular RNAs in MDA-MB-231 triple negative breast cancer cells and a panel of small molecules appended with a diazirine cross-linking moiety and an alkyne tag were probed transcriptome-wide in live cells. The alkyne tag allows for facile pull-down of cellular RNAs bound by each small molecule, and the enrichment of each RNA target defines the compound's molecular footprint. Among the 34 chemically diverse small molecules studied, six bound and enriched cellular RNAs. The most highly enriched interaction occurs between the novel RNA-binding compound F1 and a structured region in the 5' untranslated region of quiescin sulfhydryl oxidase 1 isoform a (QSOX1-a), not present in isoform b. Additional studies show that F1 specifically bound RNA over DNA and protein; that is, we studied the entire DNA, RNA, and protein interactome. This interaction was used to design a ribonuclease targeting chimera (RIBOTAC) to locally recruit Ribonuclease L to degrade QSOX1 mRNA in an isoform-specific manner, as QSOX1-a, but not QSOX1-b, mRNA and protein levels were reduced. The RIBOTAC alleviated QSOX1-mediated phenotypes in cancer cells. This approach can be broadly applied to discover ligands that bind RNA in cells, which could be bioactive themselves or augmented with functionality such as targeted degradation.

Secondary Structure of Influenza A Virus Genomic Segment 8 RNA Folded in a Cellular Environment.

Influenza A virus (IAV) is a member of the single-stranded RNA (ssRNA) family of viruses. The most recent global pandemic caused by the SARS-CoV-2 virus has shown the major threat that RNA viruses can pose to humanity. In comparison, influenza has an even higher pandemic potential as a result of its high rate of mutations within its relatively short (<13 kbp) genome, as well as its capability to undergo genetic reassortment. In light of this threat, and the fact that RNA structure is connected to a broad range of known biological functions, deeper investigation of viral RNA (vRNA) structures is of high interest. Here, for the first time, we propose a secondary structure for segment 8 vRNA (vRNA8) of A/California/04/2009 (H1N1) formed in the presence of cellular and viral components. This structure shows similarities with prior in vitro experiments. Additionally, we determined the location of several well-defined, conserved structural motifs of vRNA8 within IAV strains with possible functionality. These RNA motifs appear to fold independently of regional nucleoprotein (NP)-binding affinity, but a low or uneven distribution of NP in each motif region is noted. This research also highlights several accessible sites for oligonucleotide tools and small molecules in vRNA8 in a cellular environment that might be a target for influenza A virus inhibition on the RNA level.

Secondary Structure of Subgenomic RNA M of SARS-CoV-2.

SARS-CoV-2 belongs to the Coronavirinae family. Like other coronaviruses, SARS-CoV-2 is enveloped and possesses a positive-sense, single-stranded RNA genome of ~30 kb. Genomic RNA is used as the template for replication and transcription. During these processes, positive-sense genomic RNA (gRNA) and subgenomic RNAs (sgRNAs) are created. Several studies presented the importance of the genomic RNA secondary structure in SARS-CoV-2 replication. However, the structure of sgRNAs has remained largely unsolved so far. In this study, we probed the sgRNA M model of SARS-CoV-2 in vitro. The presented model molecule includes 5'UTR and a coding sequence of gene M. This is the first experimentally informed secondary structure model of sgRNA M, which presents features likely to be important in sgRNA M function. The knowledge of sgRNA M structure provides insights to better understand virus biology and could be used for designing new therapeutics.

Analyses of human cancer driver genes uncovers evolutionarily conserved RNA structural elements involved in posttranscriptional control.

Experimental breakthroughs have provided unprecedented insights into the genes involved in cancer. The identification of such cancer driver genes is a major step in gaining a fuller understanding of oncogenesis and provides novel lists of potential therapeutic targets. A key area that requires additional study is the posttranscriptional control mechanisms at work in cancer driver genes. This is important not only for basic insights into the biology of cancer, but also to advance new therapeutic modalities that target RNA-an emerging field with great promise toward the treatment of various cancers. In the current study we performed an in silico analysis on the transcripts associated with 800 cancer driver genes (10,390 unique transcripts) that identified 179,190 secondary structural motifs with evidence of evolutionarily ordered structures with unusual thermodynamic stability. Narrowing to one transcript per gene, 35,426 predicted structures were subjected to phylogenetic comparisons of sequence and structural conservation. This identified 7,001 RNA secondary structures embedded in transcripts with evidence of covariation between paired sites, supporting structure models and suggesting functional significance. A select set of seven structures were tested in vitro for their ability to regulate gene expression; all were found to have significant effects. These results indicate potentially widespread roles for RNA structure in posttranscriptional control of human cancer driver genes.

Nuclear magnetic resonance reveals a two hairpin equilibrium near the 3'-splice site of influenza A segment 7 mRNA that can be shifted by oligonucleotides.

Influenza A kills hundreds of thousands of people globally every year and has the potential to generate more severe pandemics. Influenza A's RNA genome and transcriptome provide many potential therapeutic targets. Here, nuclear magnetic resonance (NMR) experiments suggest that one such target could be a hairpin loop of 8 nucleotides in a pseudoknot that sequesters a 3' splice site in canonical pairs until a conformational change releases it into a dynamic 2 × 2-nt internal loop. NMR experiments reveal that the hairpin loop is dynamic and able to bind oligonucleotides as short as pentamers. A 3D NMR structure of the complex contains 4 and likely 5 bp between pentamer and loop. Moreover, a hairpin sequence was discovered that mimics the equilibrium of the influenza hairpin between its structure in the pseudoknot and upon release of the splice site. Oligonucleotide binding shifts the equilibrium completely to the hairpin secondary structure required for pseudoknot folding. The results suggest this hairpin can be used to screen for compounds that stabilize the pseudoknot and potentially reduce splicing.

In silico analysis of local RNA secondary structure in influenza virus A, B and C finds evidence of widespread ordered stability but little evidence of significant covariation.

Influenza virus is a persistent threat to human health; indeed, the deadliest modern pandemic was in 1918 when an H1N1 virus killed an estimated 50 million people globally. The intent of this work is to better understand influenza from an RNA-centric perspective to provide local, structural motifs with likely significance to the influenza infectious cycle for therapeutic targeting. To accomplish this, we analyzed over four hundred thousand RNA sequences spanning three major clades: influenza A, B and C. We scanned influenza segments for local secondary structure, identified/modeled motifs of likely functionality, and coupled the results to an analysis of evolutionary conservation. We discovered 185 significant regions of predicted ordered stability, yet evidence of sequence covariation was limited to 7 motifs, where 3-found in influenza C-had higher than expected amounts of sequence covariation.

Prediction and analysis of functional RNA structures within the integrative genomics viewer.

In recent years, interest in RNA secondary structure has exploded due to its implications in almost all biological functions and its newly appreciated capacity as a therapeutic agent/target. This surge of interest has driven the development and adaptation of many computational and biochemical methods to discover novel, functional structures across the genome/transcriptome. To further enhance efforts to study RNA secondary structure, we have integrated the functional secondary structure prediction tool ScanFold, into IGV. This allows users to directly perform structure predictions and visualize results-in conjunction with probing data and other annotations-in one program. We illustrate the utility of this new tool by mapping the secondary structural landscape of the human MYC precursor mRNA. We leverage the power of vast 'omics' resources by comparing individually predicted structures with published data including: biochemical structure probing, RNA binding proteins, microRNA binding sites, RNA modifications, single nucleotide polymorphisms, and others that allow functional inferences to be made and aid in the discovery of potential drug targets. This new tool offers the RNA community an easy to use tool to find, analyze, and characterize RNA secondary structures in the context of all available data, in order to find those worthy of further analyses.

Analysis of key genes in Mycobacterium ulcerans reveals conserved RNA structural motifs and regions with apparent pressure to remain unstructured.

Buruli Ulcer is a neglected tropical disease that results in disfiguring and dangerous lesions in affected persons across a wide geographic area, including much of West Africa. The causative agent of Buruli Ulcer is Mycobacterium ulcerans, a relative of the bacterium that causes tuberculosis and leprosy. Few therapeutic options exist for the treatment of this disease beyond antibiotics in the early stages, which are frequently ineffective, and surgical removal in the later stage. In this study we analyze six genes in Mycobacterium ulcerans that have high potential of therapeutic targeting. We focus our analysis on a combined in silico and comparative sequence study of potential RNA secondary structure across these genes. The result of this work was the comprehensive local RNA structural landscape across each of these significant genes. This revealed multiple sites of ordered and evolved RNA structure interspersed between sequences that either have no bias for structure or, indeed, appear to be ordered to be unstructured and (potentially) accessible. In addition to providing data that could be of interest to basic biology, our results provide guides for efforts aimed at targeting this pathogen at the RNA level. We explore this latter possibility through the in silico analysis of antisense oligonucleotides that could potentially be used to target pathogen RNA.

SARS-CoV-2 expresses a microRNA-like small RNA able to selectively repress host genes.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of coronavirus disease (COVID-19), continues to be a pressing health concern. In this study, we investigated the impact of SARS-CoV-2 infection on host microRNA (miRNA) populations in three human lung-derived cell lines, as well as in nasopharyngeal swabs from SARS-CoV-2-infected individuals. We did not detect any major and consistent differences in host miRNA levels after SARS-CoV-2 infection. However, we unexpectedly discovered a viral miRNA-like small RNA, named CoV2-miR-O7a (for SARS-CoV-2 miRNA-like ORF7a-derived small RNA). Its abundance ranges from low to moderate as compared to host miRNAs and it associates with Argonaute proteins-core components of the RNA interference pathway. We identify putative targets for CoV2-miR-O7a, including Basic Leucine Zipper ATF-Like Transcription Factor 2 (BATF2), which participates in interferon signaling. We demonstrate that CoV2-miR-O7a production relies on cellular machinery, yet is independent of Drosha protein, and is enhanced by the presence of a strong and evolutionarily conserved hairpin formed within the ORF7a sequence.