RNA Secondary Structure Research Articles

Alternative translation initiation produces synaptic organizer proteoforms with distinct localization and functions

While many mRNAs contain more than one translation initiation site (TIS), the functions of most alternative TISs and their corresponding protein isoforms (proteoforms) remain undetermined. Here, we showed that alternative usage of CUG and AUG TISs in neuronal pentraxin receptor (NPR) mRNA produced two proteoforms, of which the ratio was regulated by RNA secondary structure and neuronal activity. Downstream AUG initiation truncated the N-terminal transmembrane domain and produced a secreted NPR proteoform sufficient in promoting synaptic clustering of AMPA-type glutamate receptors. Mutations that altered the ratio of NPR proteoforms reduced AMPA receptors in parvalbumin-positive interneurons and affected learning behaviors in mice. In addition to NPR, upstream AUU-initiated N-terminal extension of C1q-like synaptic organizers anchored these otherwise secreted factors to the membrane. Together, these results uncovered the plasticity of N-terminal signal sequences regulated by alternative TIS usage as a potentially widespread mechanism in diversifying protein localization and functions.

Nmix: a hybrid deep learning model for precise prediction of 2'-O-methylation sites based on multi-feature fusion and ensemble learning.

RNA 2'-O-methylation (Nm) is a crucial post-transcriptional modification with significant biological implications. However, experimental identification of Nm sites is challenging and resource-intensive. While multiple computational tools have been developed to identify Nm sites, their predictive performance, particularly in terms of precision and generalization capability, remains deficient. We introduced Nmix, an advanced computational tool for precise prediction of Nm sites in human RNA. We constructed the largest, low-redundancy dataset of experimentally verified Nm sites and employed an innovative multi-feature fusion approach, combining one-hot, Z-curve and RNA secondary structure encoding. Nmix utilizes a meticulously designed hybrid deep learning architecture, integrating 1D/2D convolutional neural networks, self-attention mechanism and residual connection. We implemented asymmetric loss function and Bayesian optimization-based ensemble learning, substantially improving predictive performance on imbalanced datasets. Rigorous testing on two benchmark datasets revealed that Nmix significantly outperforms existing state-of-the-art methods across various metrics, particularly in precision, with average improvements of 33.1% and 60.0%, and Matthews correlation coefficient, with average improvements of 24.7% and 51.1%. Notably, Nmix demonstrated exceptional cross-species generalization capability, accurately predicting 93.8% of experimentally verified Nm sites in rat RNA. We also developed a user-friendly web server (https://tubic.org/Nm) and provided standalone prediction scripts to facilitate widespread adoption. We hope that by providing a more accurate and robust tool for Nm site prediction, we can contribute to advancing our understanding of Nm mechanisms and potentially benefit the prediction of other RNA modification sites.

Prediction of the effects of the top 10 synonymous mutations from 26645 SARS-CoV-2 genomes of early pandemic phase

Background The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) had led to a global pandemic since December 2019. SARS-CoV-2 is a single-stranded RNA virus, which mutates at a higher rate. Multiple works had been done to study nonsynonymous mutations, which change protein sequences. However, there is little study on the effects of SARS-CoV-2 synonymous mutations, which may affect viral fitness. This study aims to predict the effect of synonymous mutations on the SARS-CoV-2 genome. Methods A total of 26645 SARS-CoV-2 genomic sequences retrieved from Global Initiative on Sharing all Influenza Data (GISAID) database were aligned using MAFFT. Then, the mutations and their respective frequency were identified. Multiple RNA secondary structures prediction tools, namely RNAfold, IPknot++ and MXfold2 were applied to predict the effect of the mutations on RNA secondary structure and their base pair probabilities was estimated using MutaRNA. Relative synonymous codon usage (RSCU) analysis was also performed to measure the codon usage bias (CUB) of SARS-CoV-2. Results A total of 150 synonymous mutations were identified. The synonymous mutation identified with the highest frequency is C3037U mutation in the nsp3 of ORF1a. Of these top 10 highest frequency synonymous mutations, C913U, C3037U, U16176C and C18877U mutants show pronounced changes between wild type and mutant in all 3 RNA secondary structure prediction tools, suggesting these mutations may have some biological impact on viral fitness. These four mutations show changes in base pair probabilities. All mutations except U16176C change the codon to a more preferred codon, which may result in higher translation efficiency. Conclusion Synonymous mutations in SARS-CoV-2 genome may affect RNA secondary structure, changing base pair probabilities and possibly resulting in a higher translation rate. However, lab experiments are required to validate the results obtained from prediction analysis.

Genetic polymorphism in untranslated regions of PRKCZ influences mRNA structure, stability and binding sites

BackgroundVariations in untranslated regions (UTR) alter regulatory pathways impacting phenotype, disease onset, and course of disease. Protein kinase C Zeta (PRKCZ), a serine-threonine kinase, is implicated in cardiovascular, neurological and oncological disorders. Due to limited research on PRKCZ, this study aimed to investigate the impact of UTR genetic variants’ on binding sites for transcription factors and miRNA. RNA secondary structure, eQTLs, and variation tolerance analysis were also part of the study.MethodsThe data related to PRKCZ gene variants was downloaded from the Ensembl genome browser, COSMIC and gnomAD. The RegulomeDB database was used to assess the functional impact of 5’ UTR and 3’UTR variants. The analysis of the transcription binding sites (TFBS) was done through the Alibaba tool, and the Kyoto Encyclopaedia of Genes and Genomes (KEGG) was employed to identify pathways associated with PRKCZ. To predict the effect of variants on microRNA binding sites, PolymiRTS was utilized for 3’ UTR variants, and the SNPinfo tool was used for 5’ UTR variants.ResultsThe results obtained indicated that a total of 24 variants present in the 3’ UTR and 25 variants present in the 5’ UTR were most detrimental. TFBS analysis revealed that 5’ UTR variants added YY1, repressor, and Oct1, whereas 3’ UTR variants added AP-2alpha, AhR, Da, GR, and USF binding sites. The study predicted TFs that influenced PRKCZ expression. RNA secondary structure analysis showed that eight 5’ UTR and six 3’ UTR altered the RNA structure by either removal or addition of the stem-loop. The microRNA binding site analysis highlighted that seven 3’ UTR and one 5’ UTR variant altered the conserved site and also created new binding sites. eQTLs analysis showed that one variant was associated with PRKCZ expression in the lung and thyroid. The variation tolerance analysis revealed that PRKCZ was an intolerant gene.ConclusionThis study laid the groundwork for future studies aimed at targeting PRKCZ as a therapeutic target.

RNA helicase Brr2a promotes miRNA biogenesis by properly remodelling secondary structure of pri-miRNAs.

RNA secondary structure (RSS) of primary microRNAs (pri-miRNAs) is a key determinant for miRNA production. Here we report that RNA helicase (RH) Brr2a, best known as a spliceosome component, modulates the structural complexity of pri-miRNAs to fine tune miRNA yield. Brr2a interacts with microprocessor component HYL1 and its loss reduces the levels of miRNAs derived from both intron-containing and intron-lacking pri-miRNAs. Brr2a binds to pri-miRNAs in vivo and in vitro. Furthermore, Brr2a hydrolyses ATP and the activity can be significantly enhanced by pri-miRNAs. Consequently, Brr2a unwinds pri-miRNAs in vitro. Moreover, Brr2a variants with compromised ATPase or RH activity are incapable of unwinding pri-miRNA, and their transgenic plants fail to restore miRNA levels in brr2a-2. Importantly, most of tested pri-miRNAs display distinct RSS, rendering them unsuitable for efficient processing in brr2a mutants vs Col-0. Collectively, this study reveals that Brr2a plays a non-canonical role in miRNA production beyond splicing regulation.

A Machine Learning Method for RNA-Small Molecule Binding Preference Prediction.

The interaction between RNA and small molecules is crucial in various biological functions. Identifying molecules targeting RNA is essential for the inhibitor design and RNA-related studies. However, traditional methods focus on learning RNA sequence and secondary structure features and neglect small molecule characteristics, and resulting in poor performance on unknown small molecule testing. To overcome this limitation, we developed a double-layer stacking-based machine learning model called ZHMol-RLinter. This approach more effectively predicts RNA-small molecule binding preferences by learning RNA and small molecule features to capture their interaction information. ZHMol-RLinter also combines sequence and secondary structural features with structural geometric and physicochemical environment information to capture the specificity of RNA spatial conformations in recognizing small molecules. Our results demonstrate that ZHMol-RLinter has a success rate of 90.8% on the published RL98 testing set, representing a significant improvement over existing methods. Additionally, ZHMol-RLinter achieved a success rate of 77.1% on the unknown small molecule UNK96 testing set, showing substantial improvement over the existing methods. The evaluation of predicted structures confirms that ZHMol-RLinter is reliable and accurate for predicting RNA-small molecule binding preferences, even for challenging unknown small molecule testing. Predicting RNA-small molecule binding preferences can help in the understanding of RNA-small molecule interactions and promote the design of RNA-related drugs for biological and medical applications.

Complete mitochondrial genome of the terrestrial isopod Cubaris murina Brandt, 1833: new family gene order and novel tRNA secondary structures

ABSTRACT Among isopods (order Isopoda), species belonging to the suborder Oniscidea are the most successful colonisers of terrestrial habitats and the largest family in this order is Armadillidae. In this study, the complete mitochondrial genome of an armadillid isopod, Cubaris murina, was assembled and characterised in detail for the first time. The gene order and secondary structure of transfer RNA (tRNA) genes were compared among isopods. The 14,212-bp-long mitogenome consists of 13 protein-coding genes, 20 tRNAs, two ribosomal RNAs, and four non-coding regions (NCRs), each longer than 100 bp. Two tRNA genes (trnG and trnI) were missing and several other tRNA genes exhibited secondary structures that departed from the typical cloverleaf pattern. Deletions and nucleotide insertions in the T- and D-arms and mismatches in the acceptor stem were commonly observed in these tRNAs. Notably, the mitogenome of C. murina exhibited a new gene order containing four tRNA rearrangements, and differences in the location of the NCRs were detected when compared to those reported for other isopods, including oniscid species. Interestingly, the second NCR had a similar number of secondary structures and repetitive elements to those reported in the control region of other crustaceans. The novel gene order, tRNA secondary structures, and NCR organisation reported herein for the mitogenome of C. murina confirms the hyper-variability of mitochondrial genomes in isopods. This study is the first to characterise in detail the mitogenome of the invasive isopod C. murina, belonging to the species-rich family Armadillidae within the Isopoda, and advances our understanding of mitochondrial genome architecture in isopods.

The knockout of SlMTC impacts tomato seed size and reduces resistance to salt stress in tomato

Members of the MT-A70 family are key catalytic proteins involved in m6A methylation modifications in plants. They play diverse roles at the posttranscriptional level by regulating RNA secondary structure, selective splicing, stability, and translational efficiency, which collectively affect plant growth, development, and stress responses. In this study, we explored the function of the gene SlMTC, a Class C member of the MT-A70 family, in tomatoes by using CRISPR/Cas9 technology. Compared with the wild-type (WT), the CR-slmtc mutants exhibited decreased seed size and slower growth rates during the seedling stage, along with weaker salt tolerance and significant downregulation of stress-related genes, such as PR1, PR5, and P5CS. The qRT-PCR results revealed that the expression levels of genes involved in auxin biosynthesis (FZY1, FZY3, and FZY4) and polar transport (PIN1, PIN4, and PIN8) were lower in CR-slmtc plants than in the WT plants. In addition, yeast two-hybrid assays showed that SlMTC could interact with SlMTA, a Class A member of the MT-A70 family, providing insights into the potential mode of action of SlMTC in tomatoes. Overall, our findings indicate the critical role of SlMTC in plant growth and development as well as in response to salt stress.

Chikungunya Virus RNA Secondary Structures Impact Defective Viral Genome Production.

Chikungunya virus (CHIKV) is a mosquito-borne RNA virus that poses an emerging threat to humans. In a manner similar to other RNA viruses, CHIKV encodes an error-prone RNA polymerase which, in addition to producing full-length genomes, gives rise to truncated, non-functional genomes, which have been coined defective viral genomes (DVGs). DVGs have been intensively studied in the context of therapy, as they can inhibit viral replication and dissemination in their hosts. In this work, we interrogate the influence of viral RNA secondary structures on the production of CHIKV DVGs. We experimentally map RNA secondary structures of the CHIKV genome using selective 2'-hydroxyl acylation analyzed by primer extension and mutational profiling (SHAPE-MaP), which couples chemical labelling with next-generation sequencing. We correlate the inferred secondary structure with preferred deletion sites of CHIKV DVGs. We document an increased probability of DVG generation with truncations at unpaired nucleotides within the secondary structure. We then generated a CHIKV mutant bearing synonymous changes at the nucleotide level to disrupt the existing RNA secondary structure (CHIKV-D2S). We show that CHIKV-D2S presents altered DVG generation compared to wild-type virus, correlating with the change in RNA secondary structure obtained by SHAPE-MaP. Our work thus demonstrates that RNA secondary structure impacts CHIKV DVG production during replication.

Diverse RNA Structures Induce PRC2 Dimerization and Inhibit Histone Methyltransferase Activity.

Methyltransferase PRC2 (Polycomb Repressive Complex 2) introduces histone H3K27 trimethylation, a repressive chromatin mark, to tune the differential expression of genes. PRC2 is precisely regulated by accessory proteins, histone post-translational modifications and, notably, RNA. Research on PRC2-associated RNA has mostly focused on the tight-binding G-quadruplex (G4) RNAs, which inhibit PRC2 enzymatic activity in vitro and in cells. Our recent cryo-EM structure provided a molecular mechanism for G4 RNA inactivating PRC2 via dimerization, but it remained unclear how diverse RNAs associate with and regulate PRC2. Here, we show that a single-stranded G-rich RNA and an atypical G4 structure called pUG-fold unexpectedly also mediate near-identical PRC2 dimerization resulting in inhibition of PRC2 methyltransferase activity. The conformational flexibility of arginine-rich loops within subunits EZH2 and AEBP2 of PRC2 can accommodate diverse RNA secondary structures, resulting in protein-RNA and protein-protein interfaces similar to those observed previously with G4 RNA. Furthermore, we address a recent report that failed to detect PRC2-associated RNAs in living cells by demonstrating the insensitivity of PRC2-RNA interaction to photochemical crosslinking. Our results support the significance of RNA-mediated PRC2 regulation by showing that this interaction is not limited to a single RNA secondary structure, consistent with the broad PRC2 transcriptome containing many G-tract RNAs incapable of folding into G4 structures.

Capture of RNA G-quadruplex structures using an l-RNA aptamer.

G-quadruplexes (dG4 and rG4) are nucleic acid secondary structures formed by the self-assembly of certain G-rich sequences, and they have distinctive chemical properties and play crucial roles in fundamental biological processes. Small molecule G4 ligands were shown to be crucial in characterizing G4s and understanding their functions. Nevertheless, concerns regarding the specificity of these synthetic ligands for further investigation of G4s, especially for rG4 isolation purposes, have been raised. In comparison to G4 ligands, we propose a novel magnetic bead-based pulldown assay that enables the selective capture of general rG4s using functionalized l-Apt.4-1c from both simple buffer and complex media, including total RNA and the cell lysate. We found that our l-RNA aptamer can pulldown general rG4s with a higher efficiency and specificity than the G4 small molecule ligand BioTASQ v.1 in the presence of non-target competitors, including dG4 and non-G4 structures. Our findings reveal that biotinylated l-aptamers can serve as effective molecular tools for the affinity-based enrichment of rG4 of interest using this new assay, which was also verified by quantitative reverse transcription-polymerase chain reaction (RT-qPCR) on endogenous transcripts. This work provides new and important insights into rG4 isolation using a functionalized l-aptamer, which can potentially be applied in a transcript-specific or transcriptome-wide manner in the future.

Regulation viral RNA transcription and replication by higher-order RNA structures within the nsp1 coding region of MERS coronavirus

Coronavirus (CoV) possesses numerous functional cis-acting elements in its positive-strand genomic RNA. Although most of these RNA structures participate in viral replication, the functions of RNA structures in the genomic RNA of CoV in viral replication remain unclear. In this study, we investigated the functions of the higher-order RNA stem-loop (SL) structures SL5B, SL5C, and SL5D in the ORF1a coding region of Middle East respiratory syndrome coronavirus (MERS-CoV) in viral replication. Our approach, using reverse genetics of a bacterial artificial chromosome system, revealed that SL5B and SL5C play essential roles in the discontinuous transcription of MERS-CoV. In silico analyses predicted that SL5C interacts with a bulged stem-loop (BSL) in the 3′ untranslated region, suggesting that the RNA structure of SL5C is important for viral RNA transcription. Conversely, SL5D did not affect transcription, but mediated the synthesis of positive-strand genomic RNA. Additionally, the RNA secondary structure of SL5 in the revertant virus of the SL5D mutant was similar to that of the wild-type, indicating that the RNA structure of SL5D can finely tune RNA replication in MERS-CoV. Our data indicate novel regulatory mechanisms of viral RNA transcription and replication by higher-order RNA structures in the MERS-CoV genomic RNA.

Advancing mRNA subcellular localization prediction with graph neural network and RNA structure.

The asymmetrical distribution of expressed mRNAs tightly controls the precise synthesis of proteins within human cells. This non-uniform distribution, a cornerstone of developmental biology, plays a pivotal role in numerous cellular processes. To advance our comprehension of gene regulatory networks, it is essential to develop computational tools for accurately identifying the subcellular localizations of mRNAs. However, considering multi-localization phenomena remains limited in existing approaches, with none considering the influence of RNA's secondary structure. In this study, we propose Allocator, a multi-view parallel deep learning framework that seamlessly integrates the RNA sequence-level and structure-level information, enhancing the prediction of mRNA multi-localization. The Allocator models equip four efficient feature extractors, each designed to handle different inputs. Two are tailored for sequence-based inputs, incorporating multilayer perceptron and multi-head self-attention mechanisms. The other two are specialized in processing structure-based inputs, employing graph neural networks. Benchmarking results underscore Allocator's superiority over state-of-the-art methods, showcasing its strength in revealing intricate localization associations. The webserver of Allocator is available at http://Allocator.unimelb-biotools.cloud.edu.au; the source code and datasets are available on GitHub (https://github.com/lifuyi774/Allocator) and Zenodo (https://doi.org/10.5281/zenodo.13235798).

Recognition of RNA secondary structures with a programmable peptide nucleic acid-based platform

Recognition of RNA secondary structures with a programmable peptide nucleic acid-based platform

IGF2BP1-Mediated Regulation of CCN1 Expression by Specific Binding to G-Quadruplex Structure in Its 3'UTR.

The intricate regulation of gene expression is fundamental to the biological complexity of higher organisms, and is primarily governed by transcriptional and post-transcriptional mechanisms. The 3'-untranslated region (3'UTR) of mRNA is rich in cis-regulatory elements like G-quadruplexes (G4s), and plays a crucial role in post-transcriptional regulation. G4s have emerged as significant gene regulators, impacting mRNA stability, translation, and localization. In this study, we investigate the role of a robust parallel G4 structure situated within the 3'UTR of CCN1 mRNA in post-transcriptional regulation. This G4 structure is proximal to the stop codon of human CCN1, and evolutionarily conserved. We elucidated its interaction with the insulin-like growth factor 2 binding protein 1 (IGF2BP1), a noncanonical RNA N6-methyladenosine (m6A) modification reader, revealing a novel interplay between RNA modifications and G-quadruplex structures. Knockdown experiments and mutagenesis studies demonstrate that IGF2BP1 binds specifically to the G4 structure, modulating CCN1 mRNA stability. Additionally, we unveil the role of IGF2BP1's RNA recognition motifs in G4 recognition, highlighting this enthalpically driven interaction. Our findings offer fresh perspectives on the complex mechanisms of post-transcriptional gene regulation mediated by G4 RNA secondary structures.

Nonequilibrium phases of a biomolecular condensate facilitated by enzyme activity.

Biomolecular condensates represent a frontier in cellular organization, existing as dynamic materials driven out of equilibrium by active cellular processes. Here we explore active mechanisms of condensate regulation by examining the interplay between DEAD-box helicase activity and RNA base-pairing interactions within ribonucleoprotein condensates. We demonstrate how the ATP-dependent activity of DEAD-box helicases-a key class of enzymes in condensate regulation-acts as a nonequilibrium driver of condensate properties through the continuous remodeling of RNA interactions. By combining the LAF-1 DEAD-box helicase with a designer RNA hairpin concatemer, we unveil a complex landscape of dynamic behaviors, including time-dependent alterations in RNA partitioning, evolving condensate morphologies, and shifting condensate dynamics. Importantly, we reveal an antagonistic relationship between RNA secondary structure and helicase activity which promotes condensate homogeneity via a nonequilibrium steady state. By elucidating these nonequilibrium mechanisms, we gain a deeper understanding of cellular organization and expand the potential for active synthetic condensate systems.

Novel Therapeutic Horizons: SNCA Targeting in Parkinson's Disease.

Alpha-synuclein (αSyn) aggregates are the primary component of Lewy bodies, which are pathological hallmarks of Parkinson's disease (PD). The toxicity of αSyn seems to increase with its elevated expression during injury, suggesting that therapeutic approaches focused on reducing αSyn burden in neurons could be beneficial. Additionally, studies have shown higher levels of SNCA mRNA in the midbrain tissues and substantia nigra dopaminergic neurons of sporadic PD post-mortem brains compared to controls. Therefore, the regulation of SNCA expression and inhibition of αSyn synthesis could play an important role in the pathogenesis of injury, resulting in an effective treatment approach for PD. In this context, we summarized the most recent and innovative strategies proposed that exploit the targeting of SNCA to regulate translation and efficiently knock down cytoplasmatic levels of αSyn. Significant progress has been made in developing antisense technologies for treating PD in recent years, with a focus on antisense oligonucleotides and short-interfering RNAs, which achieve high specificity towards the desired target. To provide a more exhaustive picture of this research field, we also reported less common but highly innovative strategies, including small molecules, designed to specifically bind 5'-untranslated regions and, targeting secondary nucleic acid structures present in the SNCA gene, whose formation can be modulated, acting as a transcription and translation control. To fully describe the efficiency of the reported strategies, the effect of αSyn reduction on cellular viability and dopamine homeostasis was also considered.

MirtronStructDB: A Comprehensive Database of Mirtrons with Predicted Secondary Structures

Motivation Mirtrons, a vital category of non-canonical microRNAs (miRNAs) originating from exon-intron boundaries through splicing mechanisms, play crucial roles in cellular processes. However, existing databases lack the latest data and structural information, hindering understandings of mirtron formation and functions. Results We introduce MirtronStructDB, an online database addressing these gaps by incorporating over 350 novel mirtrons. Significantly, it provides corresponding predicted RNA secondary structures, offering a deeper understanding of the functional roles and mechanisms of all mirtrons. This enhances previous repositories, offering a total of 4,209 mirtron records spanning 25 species from 46 publications. Our database contributes for unraveling patterns and functions in mirtrons across species and diverse structural features. MirtronStructDB allows users to freely browse, search, visualize, and download data via a user-friendly interface. Availability MirtronStructDB is accessible at: http://www.bio8.cs.hku.hk/msdb/. Contact lishumin@connect.hku.hk, rbluo@cs.hku.hk

Selective and non-selective evolutionary signatures found in the simplest replicative biological entities.

Mitoviruses, which are considered evolutionary relics of extinct alpha-proteobacteria RNA phages, represent one of the simplest self-replicating biological systems. This study aims to quantitatively describe genomes and identify potential genomic signatures that support the protein phylogenetic-based classification criterion. Genomic variables, such as mononucleotide and dinucleotide composition, codon usage bias, and minimal free energy derived from optimized predicted RNA secondary structure, were analyzed. From the values obtained, the main evolutionary pressures were discussed, indicating that natural selection plays a significant role in shaping mitovirus genomes. However, neutral evolution also makes a significant contribution. This study reveals a significant discovery of structural divergence in Kvaramitovirus. The energy minimization approach employed to study 2D folding in this study reveals a distinct spatial organization of their genomes, providing evidence for the hypothesis of a single evolutionary event of circularization in the most recent common ancestor of the lineage. This hypothesis was discussed in light of recent discoveries by other researchers that partially support the existence of mitoviruses with circular genomes. Finally, this study represents a significant advancement in the understanding of mitoviruses, as it quantitatively describes the nucleotide sequence at the family and genus taxonomic levels. Additionally, we provide hypotheses that can be experimentally validated to inspire new research and address the gaps in knowledge of this fascinating, basally divergent RNA virus lineage.

The dual role of a highly structured RNA (the S fragment) in the replication of foot-and-mouth disease virus.

Secondary and tertiary RNA structures play key roles in genome replication of single-stranded positive sense RNA viruses. Complex, functional structures are particularly abundant in the untranslated regions of picornaviruses, where they are involved in initiation of translation, priming of new strand synthesis and genome circularization. The 5' UTR of foot-and-mouth disease virus (FMDV) is predicted to include a c. 360 nucleotide-long stem-loop, termed the short (S) fragment. This structure is highly conserved and essential for viral replication, but the precise function(s) are unclear. Here, we used selective 2' hydroxyl acetylation analyzed by primer extension (SHAPE) to experimentally determine aspects of the structure, alongside comparative genomic analyses to confirm structure conservation from a wide range of field isolates. To examine its role in virus replication in cell culture, we introduced a series of deletions to the distal and proximal regions of the stem-loop. These truncations affected genome replication in a size-dependent and, in some cases, host cell-dependent manner. Furthermore, during the passage of viruses incorporating the largest tolerated deletion from the proximal region of the S fragment stem-loop, an additional mutation was selected in the viral RNA-dependent RNA polymerase, 3Dpol. These data suggest that the S fragment and 3Dpol interact in the formation of the FMDV replication complex.