Consensus Secondary Structure Research Articles

Rfam 15: RNA families database in 2025.

The Rfam database, a widely-used repository of non-coding RNA (ncRNA) families, has undergone significant updates in release 15.0. This paper introduces major improvements, including the expansion of Rfamseq to 26, 106 genomes, a 76% increase, incorporating the latest UniProt reference proteomes and additional viral genomes. Sixty-five RNA families were enhanced using experimentally determined 3D structures, improving the accuracy of consensus secondary structures and annotations. R-scape covariation analysis was used to refine structural predictions in 26 families. Gene Ontology and Sequence Ontology annotations were comprehensively updated, increasing GO term coverage to 75% of families. The release adds 14 new Hepatitis C Virus RNA families and completes microRNA family synchronisation with miRBase, resulting in 1, 603 microRNA families. New data types, including FULL alignments, have been implemented. Integration with APICURON for improved curator attribution and multiple website enhancements further improve user experience. These updates significantly expand Rfam's coverage and improve annotation quality, reinforcing its critical role in RNA research, genome annotation, and the development of machine learning models. Rfam is freely available at https://rfam.org .

Graphical models for identifying pore-forming proteins.

Pore-forming toxins (PFTs) are proteins that form lesions in biological membranes. Better understanding of the structure and function of these proteins will be beneficial in a number of biotechnological applications, including the development of new pest control methods in agriculture. When searching for new pore formers, existing sequence homology-based methods fail to discover truly novel proteins with low sequence identity to known proteins. Search methodologies based on protein structures would help us move beyond this limitation. As the number of known structures for PFTs is very limited, it's quite challenging to identify new proteins having similar structures using computational approaches like deep learning. In this article, we therefore propose a sample-efficient graphical model, where a protein structure graph is first constructed according to consensus secondary structures. A semi-Markov conditional random fields model is then developed to perform protein sequence segmentation. We demonstrate that our method is able to distinguish structurally similar proteins even in the absence of sequence similarity (pairwise sequence identity < 0.4)-a feat not achievable by traditional approaches like HMMs. To extract proteins of interest from a genome-wide protein database for further study, we also develop an efficient framework for UniRef50 with 43 million proteins.

Deep generative design of RNA family sequences.

RNA engineering has immense potential to drive innovation in biotechnology and medicine. Despite its importance, a versatile platform for the automated design of functional RNA is still lacking. Here, we propose RNA family sequence generator (RfamGen), a deep generative model that designs RNA family sequences in a data-efficient manner by explicitly incorporating alignment and consensus secondary structure information. RfamGen can generate novel and functional RNA family sequences by sampling points from a semantically rich and continuous representation. We have experimentally demonstrated the versatility of RfamGen using diverse RNA families. Furthermore, we confirmed the high success rate of RfamGen in designing functional ribozymes through a quantitative massively parallel assay. Notably, RfamGen successfully generates artificial sequences with higher activity than natural sequences. Overall, RfamGen significantly improves our ability to design functional RNA and opens up new potential for generative RNA engineering in synthetic biology.

Identification of consensus hairpin loop structure among the negative sense subgenomic RNAs of SARS-CoV-2

BackgroundSARS-CoV-2 is the causative agent of worldwide pandemic disease coronavirus disease 19. SARS-CoV-2 bears positive sense RNA genome that has organized and complex pattern of replication/transcription process including the generation of subgenomic RNAs. Transcription regulatory sequences have important role in the pausing of replication/transcription and generation of subgenomic RNAs.ResultsIn the present bioinformatics analysis, a consensus secondary structure was identified among negative sense subgenomic RNAs of SARS-CoV-2. This consensus region is present at the adjacent of initiation codon.ConclusionsThis study proposed that consensus structured domain could involve in mediating the long pausing of replication/transcription complex and responsible for subgenomic RNA production.

Structural Organization of S516 Group I Introns in Myxomycetes.

Group I introns are mobile genetic elements encoding self-splicing ribozymes. Group I introns in nuclear genes are restricted to ribosomal DNA of eukaryotic microorganisms. For example, the myxomycetes, which represent a distinct protist phylum with a unique life strategy, are rich in nucleolar group I introns. We analyzed and compared 75 group I introns at position 516 in the small subunit ribosomal DNA from diverse and distantly related myxomycete taxa. A consensus secondary structure revealed a conserved group IC1 ribozyme core, but with a surprising RNA sequence complexity in the peripheral regions. Five S516 group I introns possess a twintron organization, where a His-Cys homing endonuclease gene insertion was interrupted by a small spliceosomal intron. Eleven S516 introns contained direct repeat arrays with varying lengths of the repeated motif, a varying copy number, and different structural organizations. Phylogenetic analyses of S516 introns and the corresponding host genes revealed a complex inheritance pattern, with both vertical and horizontal transfers. Finally, we reconstructed the evolutionary history of S516 nucleolar group I introns from insertion of mobile-type introns at unoccupied cognate sites, through homing endonuclease gene degradation and loss, and finally to the complete loss of introns. We conclude that myxomycete S516 introns represent a family of genetic elements with surprisingly dynamic structures despite a common function in RNA self-splicing.

LinAliFold and CentroidLinAliFold: fast RNA consensus secondary structure prediction for aligned sequences using beam search methods.

RNA consensus secondary structure prediction from aligned sequences is a powerful approach for improving the secondary structure prediction accuracy. However, because the computational complexities of conventional prediction tools scale with the cube of the alignment lengths, their application to long RNA sequences, such as viral RNAs or long non-coding RNAs, requires significant computational time. In this study, we developed LinAliFold and CentroidLinAliFold, fast RNA consensus secondary structure prediction tools based on minimum free energy and maximum expected accuracy principles, respectively. We achieved software acceleration using beam search methods that were successfully used for fast secondary structure prediction from a single RNA sequence. Benchmark analyses showed that LinAliFold and CentroidLinAliFold were much faster than the existing methods while preserving the prediction accuracy. As an empirical application, we predicted the consensus secondary structure of coronaviruses with approximately 30000 nt in 5 and 79 min by LinAliFold and CentroidLinAliFold, respectively. We confirmed that the predicted consensus secondary structure of coronaviruses was consistent with the experimental results. The source codes of LinAliFold and CentroidLinAliFold are freely available at https://github.com/fukunagatsu/LinAliFold-CentroidLinAliFold. Supplementary data are available at Bioinformatics Advances online.

ConsAlifold: considering RNA structural alignments improves prediction accuracy of RNA consensus secondary structures.

By detecting homology among RNAs, the probabilistic consideration of RNA structural alignments has improved the prediction accuracy of significant RNA prediction problems. Predicting an RNA consensus secondary structure from an RNA sequence alignment is a fundamental research objective because in the detection of conserved base-pairings among RNA homologs, predicting an RNA consensus secondary structure is more convenient than predicting an RNA structural alignment. We developed and implemented ConsAlifold, a dynamic programming-based method that predicts the consensus secondary structure of an RNA sequence alignment. ConsAlifold considers RNA structural alignments. ConsAlifold achieves moderate running time and the best prediction accuracy of RNA consensus secondary structures among available prediction methods. ConsAlifold, data and Python scripts for generating both figures and tables are freely available at https://github.com/heartsh/consalifold. Supplementary data are available at Bioinformatics online.

NcDLRES: a novel method for non-coding RNAs family prediction based on dynamic LSTM and ResNet

BackgroundStudies have proven that the same family of non-coding RNAs (ncRNAs) have similar functions, so predicting the ncRNAs family is helpful to the research of ncRNAs functions. The existing calculation methods mainly fall into two categories: the first type is to predict ncRNAs family by learning the features of sequence or secondary structure, and the other type is to predict ncRNAs family by the alignment among homologs sequences. In the first type, some methods predict ncRNAs family by learning predicted secondary structure features. The inaccuracy of predicted secondary structure may cause the low accuracy of those methods. Different from that, ncRFP directly learning the features of ncRNA sequences to predict ncRNAs family. Although ncRFP simplifies the prediction process and improves the performance, there is room for improvement in ncRFP performance due to the incomplete features of its input data. In the secondary type, the homologous sequence alignment method can achieve the highest performance at present. However, due to the need for consensus secondary structure annotation of ncRNA sequences, and the helplessness for modeling pseudoknots, the use of the method is limited.ResultsIn this paper, a novel method “ncDLRES”, which according to learning the sequence features, is proposed to predict the family of ncRNAs based on Dynamic LSTM (Long Short-term Memory) and ResNet (Residual Neural Network).ConclusionsncDLRES extracts the features of ncRNA sequences based on Dynamic LSTM and then classifies them by ResNet. Compared with the homologous sequence alignment method, ncDLRES reduces the data requirement and expands the application scope. By comparing with the first type of methods, the performance of ncDLRES is greatly improved.

A Phylogenetic Approach to Structural Variation in Organization of Nuclear Group I Introns and Their Ribozymes.

Nuclear group I introns are restricted to the ribosomal DNA locus where they interrupt genes for small subunit and large subunit ribosomal RNAs at conserved sites in some eukaryotic microorganisms. Here, the myxomycete protists are a frequent source of nuclear group I introns due to their unique life strategy and a billion years of separate evolution. The ribosomal DNA of the myxomycete Mucilago crustacea was investigated and found to contain seven group I introns, including a direct repeat-containing intron at insertion site S1389 in the small subunit ribosomal RNA gene. We collected, analyzed, and compared 72 S1389 group IC1 introns representing diverse myxomycete taxa. The consensus secondary structure revealed a conserved ribozyme core, but with surprising sequence variations in the guanosine binding site in segment P7. Some S1389 introns harbored large extension sequences in the peripheral region of segment P9 containing direct repeat arrays. These repeats contained up to 52 copies of a putative internal guide sequence motif. Other S1389 introns harbored homing endonuclease genes in segment P1 encoding His-Cys proteins. Homing endonuclease genes were further interrupted by small spliceosomal introns that have to be removed in order to generate the open reading frames. Phylogenetic analyses of S1389 intron and host gene indicated both vertical and horizontal intron transfer during evolution, and revealed sporadic appearances of direct repeats, homing endonuclease genes, and guanosine binding site variants among the myxomycete taxa.

Structural landscape of the complete genomes of dengue virus serotypes and other viral hemorrhagic fevers

BackgroundWith more than 300 million potentially infected people every year, and with the expanded habitat of mosquitoes due to climate change, Dengue virus (DENV) cannot be considered anymore only a tropical disease. The RNA secondary structure is a functional characteristic of RNA viruses, and together with the accumulated high-throughput sequencing data could provide general insights towards understanding virus biology. Here, we profiled the RNA secondary structure of > 7000 complete viral genomes from 11 different species focusing on viral hemorrhagic fevers, including DENV serotypes, EBOV, and YFV.ResultsIn our work we demonstrated that the secondary structure and presence of protein-binding domains in the genomes can be used as intrinsic signature to further classify the viruses. With our predictive approach, we achieved high prediction scores of the secondary structure (AUC up to 0.85 with experimental data), and computed consensus secondary structure profiles using hundreds of in silico models. We observed that viruses show different structural patterns, where e.g., DENV-2 and Ebola virus tend to be less structured than the other viruses. Furthermore, we observed virus-specific correlations between secondary structure and the number of interaction sites with human proteins, reaching a correlation of 0.89 in the case of Zika virus. We also identified that helicases-encoding regions are more structured in several flaviviruses, while the regions encoding for the contact proteins exhibit virus-specific clusters in terms of RNA structure and potential protein-RNA interactions. We also used structural data to study the geographical distribution of DENV, finding a significant difference between DENV-3 from Asia and South-America, where the structure is also driving the clustering more than sequence identity, which could imply different evolutionary routes of this subtype.ConclusionsOur massive computational analysis provided novel results regarding the secondary structure and the interaction with human proteins, not only for DENV serotypes, but also for other flaviviruses and viral hemorrhagic fevers-associated viruses. We showed how the RNA secondary structure can be used to categorise viruses, and even to further classify them based on the interaction with proteins. We envision that these approaches can be used to further classify and characterise these complex viruses.

An expanded class of histidine-accepting viral tRNA-like structures.

Structured RNA elements are common in the genomes of RNA viruses, often playing critical roles during viral infection. Some viral RNA elements use forms of tRNA mimicry, but the diverse ways this mimicry can be achieved are poorly understood. Histidine-accepting tRNA-like structures (TLSHis) are examples found at the 3′ termini of some positive-sense single-stranded RNA (+ssRNA) viruses where they interact with several host proteins, induce histidylation of the RNA genome, and facilitate processes important for infection, to include genome replication. As only five TLSHis examples had been reported, we explored the possible larger phylogenetic distribution and diversity of this TLS class using bioinformatic approaches. We identified many new examples of TLSHis, yielding a rigorous consensus sequence and secondary structure model that we validated by chemical probing of representative TLSHis RNAs. We confirmed new examples as authentic TLSHis by demonstrating their ability to be histidylated in vitro, then used mutational analyses to imply a tertiary interaction that is likely analogous to the D- and T-loop interaction found in canonical tRNAs. These results expand our understanding of how diverse RNA sequences achieve tRNA-like structure and function in the context of viral RNA genomes and lay the groundwork for high-resolution structural studies of tRNA mimicry by histidine-accepting TLSs.

Widespread inspection and comparative analysis of ITS secondary structure conservation and covariation of Coccinellidae

ITS1 and ITS2 of ribosomal DNA (rDNA) of six subfamilies i.e. Epilachaninae, Chilocorinae, Coccinellinae, Coccidulinae, Scymininae Ortaliinae and Sticholotidinae were examined, aligned and conserved motifs in folding patterns of stable consensus secondary structures were assessed. RNAalifold and RNA fold algorithms applied by RNAz program to compute consensus secondary structures and MFE efficiently and derive a number of statistical scores i.e. SCI, Z-score and MPI. Assembled subsets in ITS1 (three sets) and ITS2 (ten sets) were significantly conserved. In this study, analysis of these consensus secondary structures shows that a motif sequence is remain conserved in all the species. Helices in subsets of ITS1 showed compensatory base involvement to maintain the stability and conservation of secondary structures during natural selection. Secondary structures of ITS2 found more conserved than ITS1. MP, BI and ML methods used to establish the evolutionary relationship, compared the topology significance on the basis of SCI and MPI in defined sets. Coccinellinae, Epilachaninae and Scymninae (all strains of species) were monophyletic whereas Coccidulinae, and Chilocorinae had inadequate sequence information. Of Ortaliinae and Sticholotidinae, yet no ITS sequences have been submitted. Thus, analysis of the structural folding patterns of ITS regions provided further prime information of species relatedness and inter-intra-specific variations.

RNAconTest: comparing tools for noncoding RNA multiple sequence alignment based on structural consistency.

The importance of noncoding RNA sequences has become increasingly clear over the past decade. New RNA families are often detected and analyzed using comparative methods based on multiple sequence alignments. Accordingly, a number of programs have been developed for aligning and deriving secondary structures from sets of RNA sequences. Yet, the best tools for these tasks remain unclear because existing benchmarks contain too few sequences belonging to only a small number of RNA families. RNAconTest (RNA consistency test) is a new benchmarking approach relying on the observation that secondary structure is often conserved across highly divergent RNA sequences from the same family. RNAconTest scores multiple sequence alignments based on the level of consistency among known secondary structures belonging to reference sequences in their output alignment. Similarly, consensus secondary structure predictions are scored according to their agreement with one or more known structures in a family. Comparing the performance of 10 popular alignment programs using RNAconTest revealed that DAFS, DECIPHER, LocARNA, and MAFFT created the most structurally consistent alignments. The best consensus secondary structure predictions were generated by DAFS and LocARNA (via RNAalifold). Many of the methods specific to noncoding RNAs exhibited poor scalability as the number or length of input sequences increased, and several programs displayed substantial declines in score as more sequences were aligned. Overall, RNAconTest provides a means of testing and improving tools for comparative RNA analysis, as well as highlighting the best available approaches. RNAconTest is available from the DECIPHER website (http://DECIPHER.codes/Downloads.html).

Adenine·cytosine substitutions are an alternative pathway of compensatory mutation in angiosperm ITS2.

Compensatory mutations are crucial for functional RNA because they maintain RNA configuration and thus function. Compensatory mutation has traditionally been considered to be a two-step substitution through the GU-base-pair intermediate. We tested for an alternative AC-mediated compensatory mutation (ACCM). We investigated ACCMs by using a comprehensive sampling of ribosomal internal transcribed spacer 2 (ITS2) from 3934 angiosperm species in 80 genera and 55 families. We predicted ITS2 consensus secondary structures by using LocARNA for structure-based alignment and partitioning paired and unpaired regions. We examined and compared the substitution rates and frequencies among base pairs by using RNA-specific models. Base-pair states of ACCMs were mapped onto the inferred phylogenetic trees to infer their evolution. All types of compensatory mutations involving the AC intermediate were observed, but the most frequent substitutions were with AU or GC pairs, which are part of the AU–AC–GC pathway. Compared with the GU intermediate, AC had a lower frequency and higher mutability. Within the AU–AC–GC pathway, the AU–AC substitution rate was much slower than the AC–GC substitution rate. No consistently higher overall rate was identified for either pathway among all 80 sampled lineages, though compensatory mutations through the AC intermediate averaged about half that through the GU intermediate. These results demonstrate an alternative compensatory mutation between AU and GC that helps address the controversial inference of inferred simultaneous double substitutions.

Secondary structure of the internal transcribed rDNA (ITS) regions of Cosmopolites sordidus (Germar) and Odoiporus longicollis (Olivier): a first report in family Curculionidae

In the present work the consensus secondary structure of the internal transcribed rDNA spacers ITS1 and ITS2 of two weevils i.e. Cosmopolites sordidus (Germar) and Odoiporus longicollis (Olivier) has been described. The secondary structures of the ITS1 region of C.sordidus and O.longicollis have ten and five helices respectively, emerging from a central core. Two and five helices emerge from a central core in the ITS2 secondary structures of C.sordidus and O.longicollis respectively, and do not conform to the `paneukaryotic’ four domain model. The ITS2 sequences of these two weevils share three regions with maximum sequence identity. Of these, two are present at the 5’ and 3’ end and share structural similarity, suggesting their possible role in the processing of the rRNA. This is the first report of the secondary structure of the ITS region in family Curculionidae which can serve as a valuable resource for homology modelling and phylogenetic studies.

TOPAS: network-based structural alignment of RNA sequences.

For many RNA families, the secondary structure is known to be better conserved among the member RNAs compared to the primary sequence. For this reason, it is important to consider the underlying folding structures when aligning RNA sequences, especially for those with relatively low sequence identity. Given a set of RNAs with unknown structures, simultaneous RNA alignment and folding algorithms aim to accurately align the RNAs by jointly predicting their consensus secondary structure and the optimal sequence alignment. Despite the improved accuracy of the resulting alignment, the computational complexity of simultaneous alignment and folding for a pair of RNAs is O(N6), which is too costly to be used for large-scale analysis. In order to address this shortcoming, in this work, we propose a novel network-based scheme for pairwise structural alignment of RNAs. The proposed algorithm, TOPAS, builds on the concept of topological networks that provide structural maps of the RNAs to be aligned. For each RNA sequence, TOPAS first constructs a topological network based on the predicted folding structure, which consists of sequential edges and structural edges weighted by the base-pairing probabilities. The obtained networks can then be efficiently aligned by using probabilistic network alignment techniques, thereby yielding the structural alignment of the RNAs. The computational complexity of our proposed method is significantly lower than that of the Sankoff-style dynamic programming approach, while yielding favorable alignment results. Furthermore, another important advantage of the proposed algorithm is its capability of handling RNAs with pseudoknots while predicting the RNA structural alignment. We demonstrate that TOPAS generally outperforms previous RNA structural alignment methods on RNA benchmarks in terms of both speed and accuracy. Source code of TOPAS and the benchmark data used in this paper are available at https://github.com/bjyoontamu/TOPAS.

RPredictorDB: a predictive database of individual secondary structures of RNAs and their formatted plots.

Secondary data structure of RNA molecules provides insights into the identity and function of RNAs. With RNAs readily sequenced, the question of their structural characterization is increasingly important. However, RNA structure is difficult to acquire. Its experimental identification is extremely technically demanding, while computational prediction is not accurate enough, especially for large structures of long sequences. We address this difficult situation with rPredictorDB, a predictive database of RNA secondary structures that aims to form a middle ground between experimentally identified structures in PDB and predicted consensus secondary structures in Rfam. The database contains individual secondary structures predicted using a tool for template-based prediction of RNA secondary structure for the homologs of the RNA families with at least one homolog with experimentally solved structure. Experimentally identified structures are used as the structural templates and thus the prediction has higher reliability than de novo predictions in Rfam. The sequences are downloaded from public resources. So far rPredictorDB covers 7365 RNAs with their secondary structures. Plots of the secondary structures use the Traveler package for readable display of RNAs with long sequences and complex structures, such as ribosomal RNAs. The RNAs in the output of rPredictorDB are extensively annotated and can be viewed, browsed, searched and downloaded according to taxonomic, sequence and structure data. Additionally, structure of user-provided sequences can be predicted using the templates stored in rPredictorDB.

A consensus secondary structure of ITS2 for the diatom Order Cymatosirales (Mediophyceae, Bacillariophyta) and reappraisal of the order based on DNA, morphology, and reproduction

In 1983, Hasle and colleagues removed cymatosiroid diatoms from the pennates, and erected a new centric diatom family, the Cymatosiraceae, mainly to accommodate for their newly discovered mode of sexual reproduction. The new family consisted of two subfamilies differing in frustule structure. The family was later elevated to the rank of Order Cymatosirales Round and Crawford. We revisited intra-ordinal relationships within Cymatosirales using combined genetic (DNA sequences), morphological (valve and frustule structure), and reproductive (auxospore type) characters. In total, 36 cymatosiroid strains from 19 species representing 13 genera (80% of the total number of extant genera; nine of them represented by their generitypes) were used in this study. Instead of only the commonly used loci (18S rRNA and plastidal genes) to infer diatom phylogeny, we developed a consensus secondary structure model of the Internal Transcribed Spacer 2 (ITS2) for this order and applied it to aid in sequence alignments for ITS2. This improved the alignment and thus the robustness of the phylogenetic framework. The compensatory base changes (CBCs) found in ITS2 secondary structures were mapped onto the multi-gene (18S rRNA + ITS2 + rbcL) phylogenetic tree topology. In all these trees, all species grouped into two morphologically and genetically distinct clades. Each clade was supported by multiple CBCs, as did all the clades representing genera. However, these clades did not correspond to the previously established subfamilies. Consequently, we amend the Order Cymatosirales and family Cymatosiraceae, and propose a new family, the Leyanellaceae. The structure of the auxospore was an additional synapomorphic character for Cymatosirales. Overall, we demonstrate a novel approach to study diatom phylogeny across a broader taxonomic range using ITS2 secondary structural information. Our results suggest that this approach might be useful in establishing higher taxonomic relationships in other groups of diatoms.

Non-Coding RNA Analysis Using the Rfam Database.

Rfam is a database of non-coding RNA families in which each family is represented by a multiple sequence alignment, a consensus secondary structure, and a covariance model. Using a combination of manual and literature-based curation and a custom software pipeline, Rfam converts descriptions of RNA families found in the scientific literature into computational models that can be used to annotate RNAs belonging to those families in any DNA or RNA sequence. Valuable research outputs that are often locked up in figures and supplementary information files are encapsulated in Rfam entries and made accessible through the Rfam Web site. The data produced by Rfam have a broad application, from genome annotation to providing training sets for algorithm development. This article gives an overview of how to search and navigate the Rfam Web site, and how to annotate sequences with RNA families. The Rfam database is freely available at http://rfam.org. © 2018 by John Wiley & Sons, Inc.

Rfam 13.0: shifting to a genome-centric resource for non-coding RNA families.

The Rfam database is a collection of RNA families in which each family is represented by a multiple sequence alignment, a consensus secondary structure, and a covariance model. In this paper we introduce Rfam release 13.0, which switches to a new genome-centric approach that annotates a non-redundant set of reference genomes with RNA families. We describe new web interface features including faceted text search and R-scape secondary structure visualizations. We discuss a new literature curation workflow and a pipeline for building families based on RNAcentral. There are 236 new families in release 13.0, bringing the total number of families to 2687. The Rfam website is http://rfam.org.