RNA Secondary Structure Research Articles

DEBFold: Computational Identification of RNA Secondary Structures for Sequences across Structural Families Using Deep Learning.

It is now known that RNAs play more active roles in cellular pathways beyond simply serving as transcription templates. These biological mechanisms might be mediated by higher RNA stereo conformations, triggering the need to understand RNA secondary structures first. However, experimental protocols for solving RNA structures are unavailable for large-scale investigation due to their high costs and time-consuming nature. Various computational tools were thus developed to predict the RNA secondary structures from sequences. Recently, deep networks have been investigated to help predict RNA structures directly from their sequences. However, existing deep-learning-based tools are more or less suffering from model overfitting due to their complicated problem formulation and defective model training processes, limiting their applications across sequences from different structural families. In this research, we designed a two-stage RNA structure prediction strategy called DEBFold (deep ensemble boosting and folding) based on convolution encoding/decoding and self-attention mechanisms to enhance the existing thermodynamic structure models. Moreover, the model training process followed rigorous steps to achieve an acceptable prediction generalization. On the family-wise reserved test sets and the PDB-derived test set, DEBFold achieves better structure prediction performance over traditional tools and existing deep-learning methods. In summary, we obtained a cutting-edge deep-learning-based structure prediction tool with supreme across-family generalization performance. The DEBFold tool can be accessed at https://cobis.bme.ncku.edu.tw/DEBFold/.

High frequency of transition to transversion ratio in the stem region of RNA secondary structure of untranslated region of SARS-CoV-2.

The propensity of nucleotide bases to form pairs, causes folding and the formation of secondary structure in the RNA. Therefore, purine (R): pyrimidine (Y) base-pairing is vital to maintain uniform lateral dimension in RNA secondary structure. Transversions or base substitutions between R and Y bases, are more detrimental to the stability of RNA secondary structure, than transitions derived from substitutions between A and G or C and T. The study of transversion and transition base substitutions is important to understand evolutionary mechanisms of RNA secondary structure in the 5' and 3' untranslated (UTR) regions of SARS-CoV-2. In this work, we carried out comparative analysis of transition and transversion base substitutions in the stem and loop regions of RNA secondary structure of SARS-CoV-2. We have considered the experimentally determined and well documented stem and loop regions of 5' and 3' UTR regions of SARS-CoV-2 for base substitution analysis. The secondary structure comprising of stem and loop regions were visualized using the RNAfold web server. The GISAID repository was used to extract base sequence alignment of the UTR regions. Python scripts were developed for comparative analysis of transversion and transition frequencies in the stem and the loop regions. The results of base substitution analysis revealed a higher transition (ti) to transversion (tv) ratio (ti/tv) in the stem region of UTR of RNA secondary structure of SARS-CoV-2 reported during the early stage of the pandemic. The higher ti/tv ratio in the stem region suggested the influence of secondary structure in selecting the pattern of base substitutions. This differential pattern of ti/tv values between stem and loop regions was not observed among the Delta and Omicron variants that dominated the later stage of the pandemic. It is noteworthy that the ti/tv values in the stem and loop regions were similar among the later dominant Delta and Omicron variant strains which is to be investigated to understand the rapid evolution and global adaptation of SARS-CoV-2. Our findings implicate the lower frequency of transversions than the transitions in the stem regions of UTRs of SARS-CoV-2. The RNA secondary structures are associated with replication, translation, and packaging, further investigations are needed to understand these base substitutions across different variants of SARS-CoV-2.

Determinants of minor satellite RNA function in chromosome segregation in mouse embryonic stem cells.

The centromere is a fundamental higher-order structure in chromosomes ensuring their faithful segregation upon cell division. Centromeric transcripts have been described in several species and suggested to participate in centromere function. However, low sequence conservation of centromeric repeats appears inconsistent with a role in recruiting highly conserved centromeric proteins. Here, we hypothesized that centromeric transcripts may function through a secondary structure rather than sequence conservation. Using mouse embryonic stem cells (ESCs), we show that an imbalance in the levels of forward or reverse minor satellite (MinSat) transcripts leads to severe chromosome segregation defects. We further show that MinSat RNA adopts a stem-loop secondary structure, which is conserved in human α-satellite transcripts. We identify an RNA binding region in CENPC and demonstrate that MinSat transcripts function through the structured region of the RNA. Importantly, mutants that disrupt MinSat secondary structure do not cause segregation defects. We propose that the conserved role of centromeric transcripts relies on their secondary RNA structure.

Conservation and distribution of the DRACH motif for potential m6A sites in avian leukosis virus subgroup J.

N6-methyladenosine (m6A) methylation is an internal post-transcriptional modification that has been linked to viral multiplication and pathogenicity. To elucidate the conservation patterns of potential 5'-DRACH-3' motifs in avian leukosis virus subgroup J (ALV-J), 149 ALV-J strains (139 isolates from China; ALV-J prototype HPRS-103 from the UK; and 9 strains from the USA, Russia, India, and Pakistan) available in GenBank before December 2023 were retrieved. According to the prediction results of the SRAMP web-server, these ALV-J genomes contained potential DRACH motifs, with the total number ranging from 43 to 64, which were not determined based on the isolation region and time. Conservative analysis suggested that 37 motifs exhibited a conservation of >80%, including 17 motifs with a grading above "high confidence." Although these motifs were distributed in the U5 region of LTRs and major coding regions, they were enriched in the coding regions of p27, p68, p32, and gp85. The most common m6A-motif sequence of the DRACH motif in the ALV-J genome was GGACU. The RNA secondary structure of each conserved motif predicted by SRAMP and RNAstructure web-server was mainly of two types-A-U pair (21/37) and hairpin loop (16/37)-based on the core adenosine. Considering the systematic comparative analysis performed in this study, future thorough biochemical research is warranted to determine the role of m6A modification during the replication and infection of ALV-J. These conservation and distribution analysis of the DRACH motif for potential m6A sites in ALV-J would provide a foundation for the future intervention of ALV-J infection and m6A modification.

The potential up-regulation risk of 3′ UTR SNP (rs10787760 G > A) for the VAX1 gene is associated with NSCLP in the northwest Chinese population

AimsTo investigate the association between single nucleotide polymorphisms (SNPs) in 3′UTR region of VAX1, SYT14 and PAX7 genes and the risk of non-syndromic cleft palate (NSCLP) in a northwest Chinese population. Main methodsA case-control study was conducted in 406 normal controls and 399 NSCLP patients. Using iMLDRTM genotyping technology, eight SNPs of three genes ((rs10787760, rs7086344 at VAX1), (rs1010113, rs851114, and rs485874 at PAX7), and (rs61820397, rs4609425, rs12133399 at SYT14)) were genotyped to investigate the differences in alleles and genotype distribution frequencies between NSCLP patients and healthy controls. RNA Folding Form software was used to predict RNA secondary structure and expression vectors were constructed to explore the function of the relevant SNP. The effect of SNP polymorphism of gene transcription and translation was assessed using qPCR and Western blot analysis.Key findings.Among the eight SNPs of three genes, rs10787760 of VAX1 gene was found to be associated with an increased risk of NSCLP (OR = 1.341, CI = 1.004–1.790) and the GA genotype of rs10787760 increased the risk of cleft lip and/or palate (CL/P) about 1.42 times (p < 0.05), and carrying the A allele might increase the risk of NSCL/P in male (OR = 1.356, 95 % CI = 1.010–1.823). But there was no association observed with cleft palate only (CPO). Cell function experiments revealed that the G to A mutation in rs10787760 up-regulated GFP-VAX1 transcriptional level by 2.39 and 3.13 times in two cell lines respectively, and enhance the protein expression of the VAX1 gene further. RNA secondary structure study showed that the rs10787760 (G > A) had two different secondary structures in 3′UTR region. SignificanceThe rs10787760 variant in the 3′UTR region of VAX1 gene is associated with CL/P in northwest Chinese population. We hypothesize that the machanism of it might be caused by the RNA differenct fold in the 3′UTR region caused by the polymorphism of the gene. Level of evidenceOriginal Reports.

Alternative polyadenylation quantitative trait loci contribute to acute myeloid leukemia risk genes regulation

Acute myeloid leukemia (AML) is a hematopoietic malignancy with a high relapse rate and progressive drug resistance. Alternative polyadenylation (APA) contributes to post-transcriptional dysregulation, but little is known about the association between APA and AML. The APA quantitative trait locus (apaQTL) is a powerful method to investigate the relationship between APA and single nucleotide polymorphisms (SNPs). We quantified APA usage in 195 Chinese AML patients and identified 4922 cis-apaQTLs related to 1875 genes, most of which were newly reported. Cis-apaQTLs may modulate the APA selection of 115 genes through poly(A) signals. Colocalization analysis revealed that cis-apaQTLs colocalized with cis-eQTLs may regulate gene expression by affecting miRNA binding sites or RNA secondary structures. We discovered 207 cis-apaQTLs related to AML risk by comparing genotype frequency with the East Asian healthy controls from the 1000 Genomes Project. Genes with cis-apaQTLs were associated with hematological phenotypes and tumor incidence according to the PHARMGKB and MGI databases. Collectively, we profiled an atlas of cis-apaQTLs in Asian AML patients and found their association with APA selection, gene expression, AML risk, and complex traits. Cis-apaQTLs may provide insights into the regulatory mechanisms related to APA in AML occurrence, progression, and prognosis.

LncRNA GAS8-AS1 dinucleotide genetic variantn.713A>G, n.714T>C is associated with early-stage disease, lymph node, and distant metastasis in differentiated thyroid cancer.

Long noncoding RNAs (lncRNAs) play an essential role in the epigenetic regulation of various key genes involved in vital cellular functions. A somatic dinucleotide mutation in the lncRNA GAS8-AS1 was reported in Chinese papillary thyroid cancer. However, GAS8-AS1 dinucleotide alteration and its impact have never been explored in differentiated thyroid cancers and other populations. We extracted genomic DNA from 265 DTCs and 97 normal healthy subjects, PCR amplified and Sanger sequenced to examine the GAS8-AS1 dinucleotide alteration. Calculated genotype/allele frequency to test Hardy-Weinberg Equilibrium (HWE) and performed a genetic model of inheritance to determine its association with DTC risk. Correlated the GAS8-AS1 dinucleotide variant distribution with clinical characteristics to find the association. Predicted GAS8-AS1 RNA secondary structure for wild type and variant using RemuRNA and RNAfold to assess the conformational changes. GAS8-AS1 dinucleotide alteration (n.713A > G, rs55742939; n.714T > C, rs61118444) identified in DTCs is a germline variant not somatic. The GAS8-AS1 genotype and allele frequency significantly deviated for HWE in DTCs (χ2 = 37.954; p = 0.0001) though not associated with its risk. Dinucleotide variant distribution was remarkably associated with early-stage disease (p = 0.002), lymph node (p = 0.01), and distant metastasis (p = 0.01) in DTCs. The GAS8-AS1 bearing dinucleotide variant markedly showed conformational change compared to that of its wild type. These findings indicate that GAS8-AS1 is genetically deregulated and implicated in several stages of DTC tumorigenesis suggesting it could be a promising prognostic biomarker in DTCs.

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.

Denaturing and dNTPs reagents improve SARS-CoV-2 detection via single and multiplex RT-qPCR

Background The COVID-19 pandemic, caused by the SARS-CoV-2, can be effectively managed with diagnostic tools such as RT-qPCR. However, it can produce false-negative results due to viral mutations and RNA secondary structures from the target gene sequence. Methods With High Performance Computing, the complete SARS-CoV-2 genome was obtained from the GenBank/GISAID to generate consensus sequences to design primers/probes for RT-qPCR. ORF8 gene was selected, meanwhile, E and N and RNAse P were according to CDC protocol. Nasopharyngeal swab samples were collected from patients diagnosed with SARS-CoV-2. Total RNA was purified according MagMAX kit, it was used in single, and multiplex RT-qPCR. To avoid templated secondary structures, compensate nucleotide proportions and improve Ct values, a solution composed of tetraethylammonium chloride and dimethyl sulfoxide and other with corresponding to dNTPs proportions in accordance SARS-CoV-2 genome were included. Sensitivity and specificity according to Ct values were determined with the Caret package in R software. Results 126,576 SARS-CoV-2 genomes from January to December 2020 comprised a database. From this, a region near of 5′ ORF8 gene showed three stem-loops was used for primers/FAM-probe. 49 samples were obtained, from them, 22 were positive to gene selected regions. Interestingly, samples from October to November 2020 were positive for all regions, however, in January 2021 different results were observed in ORF8. An improvement in Ct with the adjuvant solutions was determined in all samples with others SARS-CoV-2 primers/probes, for both single and multiplex RT-qPCR. The inclusion of the denaturing solution in single RT-qPCR increased its sensitivity with respect to the commercial method, while in multiplex the opposite was generated. Conclusions Including adjuvant solutions to prevent the formation of RNA secondary structures and the adjustment of the nucleotide ratios of SARS-CoV-2 improved single and multiplex RT-qPCR for viral identification, demonstrating its potential application in health public.

NNDB: An Expanded Database of Nearest Neighbor Parameters for Predicting Stability of Nucleic Acid Secondary Structures

Nearest neighbor thermodynamic parameters are widely used for RNA and DNA secondary structure prediction and to model thermodynamic ensembles of secondary structures. The Nearest Neighbor Database (NNDB) is a freely available web resource (https://rna.urmc.rochester.edu/NNDB) that provides the functional forms, parameter values, and example calculations. The NNDB provides the 1999 and 2004 set of RNA folding nearest neighbor parameters. We expanded the database to include a set of DNA parameters and a set of RNA parameters that includes m6A in addition to the canonical RNA nucleobases. The site was redesigned using the Quarto open-source publishing system. A downloadable PDF version of the complete resource and downloadable sets of nearest neighbor parameters are available.

Identification of an N-terminal tag (580N) that improves the biosynthesis of fluorescent proteins in Francisella tularensis and other Gram-negative bacteria

Utilization of fluorescent proteins is widespread for the study of microbial pathogenesis and host-pathogen interactions. Here, we discovered that linkage of the 36 N-terminal amino acids of FTL_0580 (a hypothetical protein of Francisella tularensis) to fluorescent proteins increases the fluorescence emission of bacteria that express these recombinant fusions. This N-terminal peptide will be referred to as 580N. Western blotting revealed that the linkage of 580N to Emerald Green Fluorescent Protein (EmGFP) in F. tularensis markedly improved detection of this protein. We therefore hypothesized that transcripts containing 580N may be translated more efficiently than those lacking the coding sequence for this leader peptide. In support, expression of emGFPFt that had been codon-optimized for F. tularensis, yielded significantly enhanced fluorescence than its non-optimized counterpart. Furthermore, fusing emGFP with coding sequence for a small N-terminal peptide (Serine-Lysine-Isoleucine-Lysine), which had previously been shown to inhibit ribosomal stalling, produced robust fluorescence when expressed in F. tularensis. These findings support the interpretation that 580N enhances the translation efficiency of fluorescent proteins in F. tularensis. Interestingly, expression of non-optimized 580N-emGFP produced greater fluorescence intensity than any other construct. Structural predictions suggested that RNA secondary structure also may be influencing translation efficiency. When expressed in Escherichia coli and Klebsiella pneumoniae bacteria, 580N-emGFP produced increased green fluorescence compared to untagged emGFP (neither allele was codon optimized for these bacteria). In conclusion, fusing the coding sequence for the 580N leader peptide to recombinant genes might serve as an economical alternative to codon optimization for enhancing protein expression in bacteria.

Transcription termination and readthrough in African swine fever virus.

African swine fever virus (ASFV) is a nucleocytoplasmic large DNA virus (NCLDV) that encodes its own host-like RNA polymerase (RNAP) and factors required to produce mature mRNA. The formation of accurate mRNA 3' ends by ASFV RNAP depends on transcription termination, likely enabled by a combination of sequence motifs and transcription factors, although these are poorly understood. The termination of any RNAP is rarely 100% efficient, and the transcriptional "readthrough" at terminators can generate long mRNAs which may interfere with the expression of downstream genes. ASFV transcriptome analyses reveal a landscape of heterogeneous mRNA 3' termini, likely a combination of bona fide termination sites and the result of mRNA degradation and processing. While short-read sequencing (SRS) like 3' RNA-seq indicates an accumulation of mRNA 3' ends at specific sites, it cannot inform about which promoters and transcription start sites (TSSs) directed their synthesis, i.e., information about the complete and unprocessed mRNAs at nucleotide resolution. Here, we report a rigorous analysis of full-length ASFV transcripts using long-read sequencing (LRS). We systematically compared transcription termination sites predicted from SRS 3' RNA-seq with 3' ends mapped by LRS during early and late infection. Using in-vitro transcription assays, we show that recombinant ASFV RNAP terminates transcription at polyT stretches in the non-template strand, similar to the archaeal RNAP or eukaryotic RNAPIII, unaided by secondary RNA structures or predicted viral termination factors. Our results cement this T-rich motif (U-rich in the RNA) as a universal transcription termination signal in ASFV. Many genes share the usage of the same terminators, while genes can also use a range of terminators to generate transcript isoforms varying enormously in length. A key factor in the latter phenomenon is the highly abundant terminator readthrough we observed, which is more prevalent during late compared with early infection. This indicates that ASFV mRNAs under the control of late gene promoters utilize different termination mechanisms and factors to early promoters and/or that cellular factors influence the viral transcriptome landscape differently during the late stages of infection.

Spotlight on G-Quadruplexes: From Structure and Modulation to Physiological and Pathological Roles.

G-quadruplexes or G4s are non-canonical secondary structures of nucleic acids characterized by guanines arranged in stacked tetraplex arrays. Decades of research into these peculiar assemblies of DNA and RNA, fueled by the development and optimization of a vast array of techniques and assays, has resulted in a large amount of information regarding their structure, stability, localization, and biological significance in native systems. A plethora of articles have reported the roles of G-quadruplexes in multiple pathways across several species, ranging from gene expression regulation to RNA biogenesis and trafficking, DNA replication, and genome maintenance. Crucially, a large amount of experimental evidence has highlighted the roles of G-quadruplexes in cancer biology and other pathologies, pointing at these structurally unique guanine assemblies as amenable drug targets. Given the rapid expansion of this field of research, this review aims at summarizing all the relevant aspects of G-quadruplex biology by combining and discussing results from seminal works as well as more recent and cutting-edge experimental evidence. Additionally, the most common methodologies used to study G4s are presented to aid the reader in critically interpreting and integrating experimental data.

Accurate prediction of RNA secondary structure including pseudoknots through solving minimum-cost flow with learned potentials

Pseudoknots are key structure motifs of RNA and pseudoknotted RNAs play important roles in a variety of biological processes. Here, we present KnotFold, an accurate approach to the prediction of RNA secondary structure including pseudoknots. The key elements of KnotFold include a learned potential function and a minimum-cost flow algorithm to find the secondary structure with the lowest potential. KnotFold learns the potential from the RNAs with known structures using an attention-based neural network, thus avoiding the inaccuracy of hand-crafted energy functions. The specially designed minimum-cost flow algorithm used by KnotFold considers all possible combinations of base pairs and selects from them the optimal combination. The algorithm breaks the restriction of nested base pairs required by the widely used dynamic programming algorithms, thus enabling the identification of pseudoknots. Using 1,009 pseudoknotted RNAs as representatives, we demonstrate the successful application of KnotFold in predicting RNA secondary structures including pseudoknots with accuracy higher than the state-of-the-art approaches. We anticipate that KnotFold, with its superior accuracy, will greatly facilitate the understanding of RNA structures and functionalities.

Structural Impact of the Interaction of the Influenza A Virus Nucleoprotein with Genomic RNA Segments.

Influenza A viruses (IAVs) possess a segmented genome consisting of eight viral RNAs (vRNAs) associated with multiple copies of viral nucleoprotein (NP) and a viral polymerase complex. Despite the crucial role of RNA structure in IAV replication, the impact of NP binding on vRNA structure is not well understood. In this study, we employed SHAPE chemical probing to compare the structure of NS and M vRNAs of WSN IAV in various states: before the addition of NP, in complex with NP, and after the removal of NP. Comparison of the RNA structures before the addition of NP and after its removal reveals that NP, while introducing limited changes, remodels local structures in both vRNAs and long-range interactions in the NS vRNA, suggesting a potentially biologically relevant RNA chaperone activity. In contrast, NP significantly alters the structure of vRNAs in vRNA/NP complexes, though incorporating experimental data into RNA secondary structure prediction proved challenging. Finally, our results suggest that NP not only binds single-stranded RNA but also helices with interruptions, such as bulges or small internal loops, with a preference for G-poor and C/U-rich regions.

Determinant of m6A regional preference by transcriptional dynamics.

N6-Methyladenosine (m6A) is the most abundant chemical modification occurring on eukaryotic mRNAs, and has been reported to be involved in almost all stages of mRNA metabolism. The distribution of m6A sites is notably asymmetric along mRNAs, with a strong preference toward the 3' terminus of the transcript. How m6A regional preference is shaped remains incompletely understood. In this study, by performing m6A-seq on chromatin-associated RNAs, we found that m6A regional preference arises during transcription. Nucleosome occupancy is remarkedly increased in the region downstream of m6A sites, suggesting an intricate interplay between m6A methylation and nucleosome-mediated transcriptional dynamics. Notably, we found a remarkable slowdown of Pol-II movement around m6A sites. In addition, inhibiting Pol-II movement increases nearby m6A methylation levels. By analyzing massively parallel assays for m6A, we found that RNA secondary structures inhibit m6A methylation. Remarkably, the m6A sites associated with Pol-II pausing tend to be embedded within RNA secondary structures. These results suggest that Pol-II pausing could affect the accessibility of m6A motifs to the methyltransferase complex and subsequent m6A methylation by mediating RNA secondary structure. Overall, our study reveals a crucial role of transcriptional dynamics in the formation of m6A regional preference.

SparseRNAfolD: optimized sparse RNA pseudoknot-free folding with dangle consideration

MotivationComputational RNA secondary structure prediction by free energy minimization is indispensable for analyzing structural RNAs and their interactions. These methods find the structure with the minimum free energy (MFE) among exponentially many possible structures and have a restrictive time and space complexity (O(n3)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$O(n^3)$$\\end{document} time and O(n2)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$O(n^2)$$\\end{document} space for pseudoknot-free structures) for longer RNA sequences. Furthermore, accurate free energy calculations, including dangle contributions can be difficult and costly to implement, particularly when optimizing for time and space requirements.ResultsHere we introduce a fast and efficient sparsified MFE pseudoknot-free structure prediction algorithm, SparseRNAFolD, that utilizes an accurate energy model that accounts for dangle contributions. While the sparsification technique was previously employed to improve the time and space complexity of a pseudoknot-free structure prediction method with a realistic energy model, SparseMFEFold, it was not extended to include dangle contributions due to the complexity of computation. This may come at the cost of prediction accuracy. In this work, we compare three different sparsified implementations for dangle contributions and provide pros and cons of each method. As well, we compare our algorithm to LinearFold, a linear time and space algorithm, where we find that in practice, SparseRNAFolD has lower memory consumption across all lengths of sequence and a faster time for lengths up to 1000 bases.ConclusionOur SparseRNAFolD algorithm is an MFE-based algorithm that guarantees optimality of result and employs the most general energy model, including dangle contributions. We provide a basis for applying dangles to sparsified recursion in a pseudoknot-free model that has the potential to be extended to pseudoknots.

AStruct: detection of allele-specific RNA secondary structure in structuromic probing data

BackgroundUncovering functional genetic variants from an allele-specific perspective is of paramount importance in advancing our understanding of gene regulation and genetic diseases. Recently, various allele-specific events, such as allele-specific gene expression, allele-specific methylation, and allele-specific binding, have been explored on a genome-wide scale due to the development of high-throughput sequencing methods. RNA secondary structure, which plays a crucial role in multiple RNA-associated processes like RNA modification, translation and splicing, has emerged as an essential focus of relevant research. However, tools to identify genetic variants associated with allele-specific RNA secondary structures are still lacking.ResultsHere, we develop a computational tool called ‘AStruct’ that enables us to detect allele-specific RNA secondary structure (ASRS) from RT-stop based structuromic probing data. AStruct shows robust performance in both simulated datasets and public icSHAPE datasets. We reveal that single nucleotide polymorphisms (SNPs) with higher AStruct scores are enriched in coding regions and tend to be functional. These SNPs are highly conservative, have the potential to disrupt sites involved in m6A modification or protein binding, and are frequently associated with disease.ConclusionsAStruct is a tool dedicated to invoke allele-specific RNA secondary structure events at heterozygous SNPs in RT-stop based structuromic probing data. It utilizes allelic variants, base pairing and RT-stop information under different cell conditions to detect dynamic and functional ASRS. Compared to sequence-based tools, AStruct considers dynamic cell conditions and outperforms in detecting functional variants. AStruct is implemented in JAVA and is freely accessible at: https://github.com/canceromics/AStruct.

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

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. 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. 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. 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.

Ribosomal quality control factors inhibit repeat-associated non-AUG translation from GC-rich repeats.

A GGGGCC (G4C2) hexanucleotide repeat expansion in C9ORF72 causes amyotrophic lateral sclerosis and frontotemporal dementia (C9ALS/FTD), while a CGG trinucleotide repeat expansion in FMR1 leads to the neurodegenerative disorder Fragile X-associated tremor/ataxia syndrome (FXTAS). These GC-rich repeats form RNA secondary structures that support repeat-associated non-AUG (RAN) translation of toxic proteins that contribute to disease pathogenesis. Here we assessed whether these same repeats might trigger stalling and interfere with translational elongation. We find that depletion of ribosome-associated quality control (RQC) factors NEMF, LTN1and ANKZF1 markedly boost RAN translation product accumulation from both G4C2 and CGG repeats while overexpression of these factors reduces RAN production in both reporter assays and C9ALS/FTD patient iPSC-derived neurons. We also detected partially made products from both G4C2 and CGG repeats whose abundance increased with RQC factor depletion. Repeat RNA sequence, rather than amino acid content, is central to the impact of RQC factor depletion on RAN translation-suggesting a role for RNA secondary structure in these processes. Together, these findings suggest that ribosomal stalling and RQC pathway activation during RAN translation inhibits the generation of toxic RAN products. We propose augmenting RQC activity as a therapeutic strategy in GC-rich repeat expansion disorders.