NCBI RefSeq: reference sequence standards through 25 years of curation and annotation

MAFin: motif detection in multiple alignment files

MOTIVATION

Whole Genome and Proteome Alignments, represented by the multiple alignment file format, have become a standard approach in comparative genomics and proteomics. These often require identifying conserved motifs, which is crucial for understanding functional and evolutionary relationships. However, current approaches lack a direct method for motif detection within MAF files. We present MAFin, a novel tool that enables efficient motif detection and conservation analysis in MAF files to address this gap, streamlining genomic and proteomic research.

RESULTS

We developed MAFin, the first motif detection tool for Multiple Alignment Format files. MAFin enables the multithreaded search of conserved motifs using three approaches: (i) using user-specified k-mers to search the sequences. (ii) with regular expressions, in which case one or more patterns are searched, and (iii) with predefined Position Weight Matrices. Once the motif has been found, MAFin detects the motif instances and calculates the conservation across the aligned sequences. MAFin also calculates a conservation percentage, which provides information about the conservation levels of each motif across the aligned sequences, based on the number of matches relative to the length of the motif. A set of statistics enables the interpretation of each motif's conservation level, and the detected motifs are exported in JSON and CSV files for downstream analyses.

AVAILABILITY AND IMPLEMENTATION

MAFin is offered as a Python package under the GPL license as a multi-platform application and is available at: https://github.com/Georgakopoulos-Soares-lab/MAFin.

BioRels' data infrastructure: a scientific schema and exchange standard to transform and enhance biological data sciences

Our understanding of biology and medicinal sciences augmented by advances in data structures and algorithms has resulted in proliferation of thousands of open-sourced resources, tools, and websites that are made by the scientific community to access, process, store, and visualize biological data. However, such data have become increasingly complex and heterogeneous, leading to an entangled web of relationships and external identifiers. Despite emergence of infrastructure such as data lakes, the scientists are still responsible for the time consuming and costly exercise to find, extract, clean, prepare, and maintain such data sources while following the FAIR principles. To better understand the complexity, we lay down a representation of the mainstream data ecosystem, describing the natural relationships and concepts found in biology. Built upon it and the fundamental principles of data unicity and atomicity, we introduce BioRels, an automated and standardized data preparation workstream aiming at improving reproducibility and speed for all scientists and handling up to 145 billion data points. BioRels allows complex querying capabilities across several data sources seamlessly and provides an exchange format, BIORJ, to export and import data with all its dependency and metadata. At last, we describe the advantages, limitations, applications, and perspectives of a future approach BioRels-KB to expand future data preparation capabilities.

Expansion of the tmRNA sequence database and new tools for search and visualization

Transfer-messenger RNA (tmRNA) contributes essential tRNA-like and mRNA-like functions during the process of trans-translation, a mechanism of quality control for the translating bacterial ribosome. Proper tmRNA identification benefits the study of trans-translation and also the study of genomic islands, which frequently use the tmRNA gene as an integration site. Automated tmRNA gene identification tools are available, but manual inspection is still important for eliminating false positives. We have increased our database of precisely mapped tmRNA sequences over 50-fold to 97 179 unique sequences. Group I introns had previously been found integrated within a single subsite within the TψC-loop; they have now been identified at four distinct subsites, suggesting multiple founding events of invasion of tmRNA genes by group I introns, all in the same vicinity. tmRNA genes were found in metagenomic archaeal genomes, perhaps a result of misbinning of bacterial sequences during genome assembly. With the expanded database, we have produced new covariance models for improved tmRNA sequence search and new secondary structure visualization tools.

SHIP identifies genomic safe harbors in eukaryotic organisms using genomic general feature annotation

Integrating foreign genes into loci, allowing their transcription without affecting endogenous gene expression, is the desirable strategy in genomic engineering. However, these loci, known as genomic safe harbors (GSHs), have been mainly identified by empirical methods. Furthermore, the most prominent available GSHs are localized within regions of high gene density, raising concerns about unstable expression. As synthetic biology is moving towards investigating polygenic modules rather than single genes, there is an increasing demand for tools to identify GSHs systematically. To expand the GSH repertoire, we present SHIP, an algorithm designed to detect potential GSHs in eukaryotes. Using the chassis organism Saccharomyces cerevisiae, five GSHs were experimentally curated based on data from DNA sequencing, stability, flow cytometry, qPCR, electron microscopy, RT-qPCR, and RNA-Seq assays. Our study places SHIP as a valuable tool for providing a list of promising candidates to assist in the experimental assessment of GSHs in eukaryotic organisms with available annotated genomes.

GenBank 2025 update

GenBank® (https://www.ncbi.nlm.nih.gov/genbank/) is a comprehensive, public data repository that contains 34 trillion base pairs from over 4.7 billion nucleotide sequences for 581 000 formally described species. Daily data exchange with the European Nucleotide Archive and the DNA Data Bank of Japan ensures worldwide coverage. We summarize the content of the database in 2025 and recent updates such as accelerated processing of influenza sequences and the ability to upload feature tables to Submission Portal for messenger RNA sequences. We provide an overview of the web, application programming and command-line interfaces that allow users to access GenBank data. We also discuss the importance of creating BioProject and BioSample records during submissions, particularly for viruses and metagenomes. Finally, we summarize educational materials and recent community outreach efforts.

The 2025 Nucleic Acids Research database issue and the online molecular biology database collection

The 2025 Nucleic Acids Research database issue contains 185 papers spanning biology and related areas. Seventy three new databases are covered, while resources previously described in the issue account for 101 update articles. Databases most recently published elsewhere account for a further 11 papers. Nucleic acid databases include EXPRESSO for multi-omics of 3D genome structure (this issue's chosen Breakthrough Resource and Article) and NAIRDB for Fourier transform infrared data. New protein databases include structure predictions for human isoforms at ASpdb and for viral proteins at BFVD. UniProt, Pfam and InterPro have all provided updates: metabolism and signalling are covered by new descriptions of STRING, KEGG and CAZy, while updated microbe-oriented databases include Enterobase, VFDB and PHI-base. Biomedical research is supported, among others, by ClinVar, PubChem and DrugMAP. Genomics-related resources include Ensembl, UCSC Genome Browser and dbSNP. New plant databases cover the Solanaceae (SolR) and Asteraceae (AMIR) families while an update from NCBI Taxonomy also features. The Database Issue is freely available on the Nucleic Acids Research website (https://academic.oup.com/nar). At the NAR online Molecular Biology Database Collection (http://www.oxfordjournals.org/nar/database/c/), 932 entries have been reviewed in the last year, 74 new resources added and 226 discontinued URLs eliminated bringing the current total to 2236 databases.

Database resources of the National Center for Biotechnology Information in 2025

The National Center for Biotechnology Information (NCBI) provides online information resources for biology, including the GenBank® nucleic acid sequence repository and the PubMed® repository of citations and abstracts published in life science journals. NCBI provides search and retrieval operations for most of these data from 31 distinct repositories and knowledgebases. The E-utilities serve as the programming interface for most of these. Resources receiving significant updates in the past year include PubMed, PubMed Central, Bookshelf, the NIH Comparative Genomics Resource, BLAST, Sequence Read Archive, Taxonomy, iCn3D, Conserved Domain Database, Pathogen Detection, antimicrobial resistance resources and PubChem. These resources can be accessed through the NCBI home page at https://www.ncbi.nlm.nih.gov.