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Biology subjects

Petrov, A. I.

Publications and source records attributed to Petrov, A. I..

5 recordsLinked to original sources

Viral non-coding RNA structure annotation and API-based data retrieval with Rfam and R2DT

Rfam is a comprehensive database of non-coding RNA (ncRNA) families providing curated sequence alignments, consensus secondary structures, and covariance models for thousands of RNA families. The database is essential for identifying structured non-coding RNAs in newly sequenced genomes and understanding RNA structure-function relationships. Here we present computational protocols for automated ncRNA annotation of viral genomes, and for programmatic interaction with Rfam through its RESTful API. We showcase genome-wide RNA structure visualization from a genome sequence and from a multiple sequence alignment by generating comprehensive 2D structure diagrams using newly developed features in R2DT. We also present practical examples for retrieving family metadata, downloading alignments, accessing secondary structures, and searching user sequences from the Rfam API. These methods enable researchers in virology and RNA biology to integrate Rfam data into custom bioinformatics pipelines, comparative analyses, and machine learning workflows.

bioinformatics↗

R2DT: a comprehensive platform for visualising RNA secondary structure

RNA secondary (2D) structure visualisation is an essential tool for understanding RNA function. R2DT is a software package designed to visualise RNA 2D structures in consistent, recognisable, and reproducible layouts. The latest release, R2DT 2.0, introduces multiple significant features, including the ability to display position-specific information, such as single nucleotide polymorphisms (SNPs) or SHAPE reactivities. It also offers a new template-free mode allowing visualisation of RNAs without pre-existing templates, alongside a constrained folding mode and support for animated visualisations. Users can interactively modify R2DT diagrams, either manually or using natural language prompts, to generate new templates or create publication-quality images. Additionally, R2DT features faster performance, an expanded template library, and a growing collection of compatible tools and utilities. Already integrated into multiple biological databases, R2DT has evolved into a comprehensive platform for RNA 2D visualisation, accessible at https://r2dt.bio.

bioinformatics↗

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 Rfams 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 Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/614430v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@9b1898org.highwire.dtl.DTLVardef@6bc030org.highwire.dtl.DTLVardef@16b789org.highwire.dtl.DTLVardef@16b8577_HPS_FORMAT_FIGEXP M_FIG Rfam has undergone a major update with the release of 15.0. We have increased the number of genomes in our sequence database Rfamseq by 75%, completed the synchronisation with miRBase and improved 65 families using 3D structures. C_FIG

genomics↗

Comprehensive Survey of Conserved RNA Secondary Structures in Full-Genome Alignment of Hepatitis C Virus

Hepatitis C virus (HCV) is a plus-stranded RNA virus that often chronically infects liver hepatocytes and causes liver cirrhosis and cancer. These viruses replicate their genomes employing error-prone replicases. Thereby, they routinely generate a large "cloud" of RNA genomes which - by trial and error - comprehensively explore the sequence space available for functional RNA genomes that maintain the ability for efficient replication and immune escape. In this context, it is important to identify which RNA secondary structures in the sequence space of the HCV genome are conserved, likely due to functional requirements. Here, we provide the first genome-wide multiple sequence alignment (MSA) with the prediction of RNA secondary structures throughout all representative full-length HCV genomes. We selected 57 representative genomes by clustering all complete HCV genomes from the BV-BRC database based on k-mer distributions and dimension reduction and adding RefSeq sequences. We include annotations of previously recognized features for easy comparison to other studies. Our results indicate that mainly the core coding region, the C-terminal NS5A region, and the NS5B region contain secondary structure elements that are conserved beyond coding sequence requirements, indicating functionality on the RNA level. In contrast, the genome regions in between contain less highly conserved structures. The results provide a complete description of all conserved RNA secondary structures and make clear that functionally important RNA secondary structures are present in certain HCV genome regions but are largely absent from other regions. Full-genome alignments of all branches of Hepacivirus C are provided in the supplement.

genomics↗

R2DT: computational framework for template-based RNA secondary structure visualisation across non-coding RNA types

Non-coding RNAs (ncRNA) are essential for all life, and the functions of many ncRNAs depend on their secondary (2D) and tertiary (3D) structure. Despite proliferation of 2D visualisation software, there is a lack of methods for automatically generating 2D representations in consistent, reproducible, and recognisable layouts, making them difficult to construct, compare and analyse. Here we present R2DT, a comprehensive method for visualising a wide range of RNA structures in standardised layouts. R2DT is based on a library of 3,632 templates representing the majority of known structured RNAs, from small RNAs to the large subunit ribosomal RNA. R2DT has been applied to ncRNA sequences from the RNAcentral database and produced >13 million diagrams, creating the worlds largest RNA 2D structure dataset. The software is freely available at https://github.com/rnacentral/R2DT and a web server is found at https://rnacentral.org/r2dt.

bioinformatics↗