The International Nucleotide Sequence Database Collaboration (INSDC) consists of a joint effort to collect and disseminate databases containing DNA and RNA sequences.

NIH genetic sequence database that provides annotated collection of all publicly available DNA sequences for almost 280 000 formally described species (Jan 2014) .These sequences are obtained primarily through submissions from individual laboratories and batch submissions from large-scale sequencing projects, including whole-genome shotgun (WGS) and environmental sampling projects. Most submissions are made using web-based BankIt or standalone Sequin programs, and GenBank staff assigns accession numbers upon data receipt. It is part of International Nucleotide Sequence Database Collaboration and daily data exchange with European Nucleotide Archive (ENA) and DNA Data Bank of Japan (DDBJ) ensures worldwide coverage. GenBank is accessible through NCBI Entrez retrieval system, which integrates data from major DNA and protein sequence databases along with taxonomy, genome, mapping, protein structure and domain information, and biomedical journal literature via PubMed. BLAST provides sequence similarity searches of GenBank and other sequence databases. Complete bimonthly releases and daily updates of GenBank database are available by FTP.

Databases of protein sequences and 3D structures of proteins. Collection of sequences from several sources, including translations from annotated coding regions in GenBank, RefSeq and TPA, as well as records from SwissProt, PIR, PRF, and PDB.

NIH Genetic sequence database; an annotated collection of all publicly available DNA sequences.

Eurotiales is a diverse and speciose order and includes economically important genera like Aspergillus, Penicillium, Paecilomyces and Talaromyces. Historically, species identifications based on morphology are challenging. The publication of accepted species lists and the availability of representative DNA sequences for type strains have contributed greatly towards accurate species identification and facilitated the description of many new species. However, despite current advancements, a proportion of newly described species within these taxonomically challenging genera represent, in fact, existing species, which raises obvious concerns.

This study thus aimed to further modernise the taxonomy of Eurotiales by addressing key challenges in species identification and classification. Our study objectives were threefold: to review species described after 2023, update the accepted species list, and release a curated DNA sequence dataset to facilitate future species identifications. We conclude that a move to a phylogenetic species concept is necessary but continue to support the inclusion of morphological descriptions and, where possible, associated secondary metabolite, exoenzyme, physiology and ecological data when introducing new species.

Our list now contains 1393 species classified into four families and 26 genera, with Aspergillus (n=465), Penicillium (n=598) and Talaromyces (n=236) containing the most species. To aid sequence-based identifications and species descriptions under a phylogenetic species concept, we release a curated DNA reference sequence database containing 18837 DNA sequences (3867 ITS, 5277 BenA, 5110 CaM and 4583 RPB2) generated from 5325 strains. Sequences were selected to best cover the infraspecies variation under our current understanding of each species. The sequence database will be kept up to date as new information becomes available. This manuscript presents a major leap towards our goal to facilitate work with Eurotiales, while providing the taxonomic framework to support research excellence related to this important fungal group.

This dataset is curated and kept up to date by the International Commission of Penicillium and Aspergillus (ICPA). If you have questions or suggestions, please get in contact with ICPA members.

The tpm metabarcoding DNA sequence database for taxonomic allocations using the Mothur and DADA2 bio-informatic tools A.C.M. Pozzi1, R. Bouchali1, L. Marjolet1, B. Cournoyer1 1 University of Lyon, UMR Ecologie Microbienne Lyon (LEM), CNRS 5557, INRAE 1418, Université Claude Bernard Lyon 1, VetAgro Sup, Research Team “Bacterial Opportunistic Pathogens and Environment” (BPOE), 69280 Marcy L’Etoile, France. Corresponding authors: A.C.M. Pozzi, UMR Microbial Ecology, CNRS 5557, CNRS 1418, VetAgro Sup, Main building, aisle 3, 1st floor, 69280 Marcy-L’Etoile, France. Tel. (+33) 478 87 39 47. Fax. (+33) 472 43 12 23. Email: adrien.meynier_pozzi@vetagro-sup.fr B. Cournoyer, UMR Microbial Ecology, CNRS 5557, CNRS 1418, VetAgro Sup, Main building, aisle 3, 1st floor, 69280 Marcy-L’Etoile, France. Tel. (+33) 478 87 56 47. Fax. (+33) 472 43 12 23. Email: and benoit.cournoyer@vetagro-sup.fr Keywords: BACtpm, Bacteria, tpm, thiopurine-S-methyltransferase EC:2.1.1.67, Nucleotide sequences, PCR products, Next-Generation-Sequencing, OTHU Description: The tpm gene codes for the thiopurine-S-methyltransferase (TPMT), an enzyme that can detoxify metalloid-containing oxyanions and xenobiotics (Cournoyer et al., 1998). Bacterial TPMTs radiated apart from human and animal TPMTs, and showed a vertical evolution in line with the 16S rRNA gene molecular phylogeny (Favre‐Bonté et al., 2005). The tpm database, named BACtpm, was designed to apply the tpm-metabarcoding analytical scheme published in Aigle et al. (2021). It includes the full tpm identifiers, GenBank accession numbers, complete taxonomic records (domain down to strain code) of about 215 nucleotide-long tpm sequences of 840 unique taxa belonging to 139 genera. Nucleotide sequences of tpm (range: 190-233 nucleotides) were either retrieved from public repositories (GenBank) or made available by B. Cournoyer’s research group. Colin et al. (2020) described the PCR and high throughput Illumina Miseq DNA sequencing procedures used to produce tpm sequences. BACtpm v.2.0.1 (June 2021 release) is made available under the Creative Commons Attribution 4.0 International Licence. It can be used for the taxonomic allocations of tpm sequences down to the species and strain levels. Data is stored in the csv format enabling future user to reformat it to fit their specific needs. Acknowledgments: We thank the worldwide community of microbiologists who made contributions to public databases in the past decades, and made possible the elaboration of the BACtpm database. We also thank the Field Observatory in Urban Hydrology (OTHU, www.graie.org/othu/), Labex IMU (Intelligence des Mondes Urbains), the Greater Lyon Urban Community, the School of Integrated Watershed Sciences H2O'LYON, and the Lyon Urban School for their support in the development of this database. This work was funded by the French national research program for environmental and occupational health of ANSES under the terms of project “Iouqmer” EST 2016/1/120, l'Agence Nationale de la Recherche through ANR-16-CE32-0006, ANR-17-CE04-0010, ANR-17-EURE-0018 and ANR-17-CONV-0004, by the MITI CNRS project named Urbamic, and the French water agency for the Rhône, Mediterranean and Corsica areas through the Desir and DOmic projects. We thank former BPOE lab members who contributed to start and expand the BACtpm database: Céline COLINON, Romain MARTI, Emilie BOURGEOIS, Sébastien RIBUN and Yannick COLIN. References: Aigle, A., Colin, Y., Bouchali, R., Bourgeois, E., Marti, R., Ribun, S., Marjolet, L., Pozzi, A.C.M., Misery, B., Colinon, C., Bernardin-Souibgui, C., Wiest, L., Blaha, D., Galia, W., Cournoyer, B., 2021. Spatio-temporal variations in chemical pollutants found among urban deposits match changes in thiopurine S-methyltransferase-harboring bacteria tracked by the tpm metabarcoding approach. Sci. Total Environ. 767, 145425. https://doi.org/10.1016/j.scitotenv.2021.145425 Colin, Y., Bouchali, R., Marjolet, L., Marti, R., Vautrin, F., Voisin, J., Bourgeois, E., Rodriguez-Nava, V., Blaha, D., Winiarski, T., Mermillod-Blondin, F., Cournoyer, B., 2020. Coalescence of bacterial groups originating from urban runoffs and artificial infiltration systems among aquifer microbiomes. Hydrol. Earth Syst. Sci. 24, 4257–4273. https://doi.org/10.5194/hess-24-4257-2020 Cournoyer, B., Watanabe, S., Vivian, A., 1998. A tellurite-resistance genetic determinant from phytopathogenic pseudomonads encodes a thiopurine methyltransferase: evidence of a widely-conserved family of methyltransferases1The International Collaboration (IC) accession number of the DNA sequence is L49178.1. Biochim. Biophys. Acta BBA - Gene Struct. Expr. 1397, 161–168. https://doi.org/10.1016/S0167-4781(98)00020-7 Favre‐Bonté, S., Ranjard, L., Colinon, C., Prigent‐Combaret, C., Nazaret, S., Cournoyer, B., 2005. Freshwater selenium-methylating bacterial thiopurine methyltransferases: diversity and molecular phylogeny. Environ. Microbiol. 7, 153–164. https://doi.org/10.1111/j.1462-2920.2004.00670.x;Change Log; [2.0.1] - 2021-06-23: tpm nucleotide sequences now provided in two separated columns, either aligned with gaps for repeatable use in Mothur or not aligned and without gaps for use with DADA2. [2.1.1] - 2023-10-10: tpm nucleotide sequences added for 20 taxa (Actinoplanes sp. N902-109, Ancylobacter polymorphus DSM2457, Aromatoleum toluclasticum ATCC700605, Aromatoleum bremense PbN1, Aromatoleum diolicum, Candidatus_Macondimonas diazotrophica, Collimonas sp. PAH2, Collimonas humicolas, Emcibacter nanhaiensis CGMCC112471, Leptospira yasudae, Lysobacter sp. TY298, Lysobacter spongiae KACC19276, Lysobacter sp. CF310, Nitrospira sp. ND1, Pseudanabaena biceps PCC7429, Pseudomonas eucalypticola NP1, Pseudomonas alcaligenes MB-090714 , Pseudomonas peli DSM17833, Pseudomonas sp. 9AZ, and Pseudomonas sp. NFACC02), Proteobacteria updated to Pseudomonadota, database formatted uniquely for use with RDP/dada2.

This is a public database of DNA sequences with annotations. It is a part of the International Nucleotide Sequence Database Collaboration, and cooperates with the DNA DataBank of Japan (DDBJ) as well as the European Molecular Biology Laboratory (EMBL).

COI DNA sequences from select fish in lakes and wadeable streams

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A database of information on bacterial phages. It contains multiple phage genomes, which users can BLAST and MegaBLAST, and also hosts a Phage Forum in which users can discuss phage data. Interactive browsing of completed phage genomes is available using the program. The browser allows users to scan the genome for particular features and to download sequence information plus analyses of those features. Views of the genome are generated showing named genes BLAST similarities to other phages predicted tRNAs and other sequence features.

An international partnership created a zooplankton genomic (ZooGene) database of DNA type sequences for calanoid copepods and euphausiids. The ZooGene database was designed to include all species of these groups and to allow expansion to additional zooplankton groups. The ZooGene partnership includes four P.I.s and thirteen expert taxonomic consultants from seven countries. Zooplankton samples are sorted from existing archival collections, obtained in coordination with planned oceanographic research efforts, and collected during National Marine Fisheries Service field surveys. The taxonomic experts confirm species' identifications; DNA sequencing is done at the University of New Hampshire and, in some cases, in other partners' laboratories. For each species, a DNA type sequence is determined for a portion of the mitochondrial cytochrome oxidase I (mtCOI) gene; multiple mtCOI sequences are included as necessary to reflect intraspecific variation. The ZooGene database is designed, created, managed, maintained, and distributed as part of the proposed work; the data is integrated into the Ocean Biogeographical Information System (OBIS).

If you use this dataset please cite: Visagie CM, Houbraken J, Overy DP, et al. (2025). From chaos to tranquillity: a modern approach to the identification, nomenclature and phylogeny of Aspergillus, Penicillium and other Eurotiales, including an updated accepted species list. Studies in Mycology 112: 117–260. https://doi.org/10.3114/sim.2025.112.04.

Eurotiales is a diverse and speciose order and includes economically important genera like Aspergillus, Penicillium, Paecilomyces and Talaromyces. Historically, species identifications based on morphology are challenging. The publication of accepted species lists and the availability of representative DNA sequences for type strains have contributed greatly towards accurate species identification and facilitated the description of many new species. However, despite current advancements, a proportion of newly described species within these taxonomically challenging genera represent, in fact, existing species, which raises obvious concerns.

This study thus aimed to further modernise the taxonomy of Eurotiales by addressing key challenges in species identification and classification. Our study objectives were threefold: to review species described after 2023, update the accepted species list, and release a curated DNA sequence dataset to facilitate future species identifications. We conclude that a move to a phylogenetic species concept is necessary but continue to support the inclusion of morphological descriptions and, where possible, associated secondary metabolite, exoenzyme, physiology and ecological data when introducing new species.

Our list now contains 1393 species classified into four families and 26 genera, with Aspergillus (n=465), Penicillium (n=598) and Talaromyces (n=236) containing the most species. To aid sequence-based identifications and species descriptions under a phylogenetic species concept, we release a curated DNA reference sequence database containing 18837 DNA sequences (3867 ITS, 5277 BenA, 5110 CaM and 4583 RPB2) generated from 5325 strains. Sequences were selected to best cover the infraspecies variation under our current understanding of each species. The sequence database will be kept up to date as new information becomes available. This manuscript presents a major leap towards our goal to facilitate work with Eurotiales, while providing the taxonomic framework to support research excellence related to this important fungal group.

This dataset is curated and kept up to date by the International Commission of Penicillium and Aspergillus (ICPA). If you have questions or suggestions, please get in contact with ICPA members.

Environmental DNA (eDNA) methods complement traditional monitoring and can be configured to detect multiple species simultaneously. One such approach, eDNA metabarcoding, uses high-throughput DNA sequencing to indirectly detect many different organisms, spanning broad taxonomic boundaries, from water samples. We are optimizing a non-invasive, low cost eDNA metabarcoding protocol to be used in conjunction with existing monitoring programs. One resource that is currently lacking for metabarcoding studies in general, including those in the San Francisco Estuary (SFE), is a comprehensive database of DNA barcode reference sequences. Without this foundational data, many species go undetected or misidentified in metabarcoding studies. To meet this need, we generated a custom barcode sequence database for the SFE by DNA sequencing and mining of public DNA seqeunce data for estuarine and freshwater species of interest to monitoring programs and ecological studies. Here we present custom reference sequence databases for three barcodes: Cytochrome C Oxidase I (COI), 12S MiFish and 16S. Methods Data were collected from two sources. Specimens of fish and invertebrates collected from the San Francisco Estuary were used for Sanger DNA sequencing. DNA extractions were performed using the Qiagen Blood and Tissue kit and PCR was performed using primers to amplify the entire barcode sequence. Raw chromatogram data files were manually examined for quality control, aligned, and flanking and primer sequences were trimmed using CodonCode Aligner. For species without physical specimens, or for those specimens that failed PCR/sequencing/QC, publicly available DNA sequences were downloaded from GenBank, and aligned and trimmed to the barcode region using CodonCode Aligner. The combined experimental and downloaded sequences for each barcode were placed into a single .txt file formatted for use with the DADA2 metabarcoding software. For all sequences, an additional verification step was performed by querying the BLASTn database. A separate metadata file (.csv) was also generated for each barcode that includes the specimen name (if applicable), GenBank Accession numbers (if applicable), taxonomic information, common name, and specimen locality, US state, and collection date, if available.

Museomics is an approach to the DNA sequencing of museum specimens that can generate both biodiversity and sequence information. In this study, we surveyed both the biodiversity information-based database BOLD (Barcode of Life System) and the sequence information database GenBank, by using DNA barcoding data as an example, with the aim of integrating the data from these two databases. DNA barcoding is a method of identifying species from DNA sequences by using short genetic markers. We surveyed how many entries had biodiversity information (such as links to BOLD and specimen IDs) by downloading all fish, insect, and flowering plant data available from the GenBank Nucleotide, and BOLD ID was assigned to 26.2% of entries for insects. In the same way, we downloaded the respective BOLD data and checked the status of links to sequence information. We also investigated how many species do these databases cover, and 7,693 species were found to exist only in BOLD. In the future, as museomics develops as a field, the targeted sequences will be extended not only to DNA barcodes, but also to mitochondrial genomes, other genes, and genome sequences. Consequently, the value of the sequence data will increase. In addition, various species will be sequenced and, thus, biodiversity information such as the evidence specimen photographs used as a basis for species identification, will become even more indispensable. This study contributes to the acceleration of museomics-associated research by using databases in a cross-sectional manner.

ISfinder is a database of bacterial insertion sequences (IS). It assigns IS nomenclature and acts as a repository for ISs. Each IS is annotated with information such as the open reading frame DNA sequence, the sequence of the ends of the element and target sites, its origin and distribution together with a bibliography, where available.

Database of high-throughput genome sequences from large-scale genome sequencing centers, including unfinished and finished sequences. It was created to accommodate a growing need to make unfinished genomic sequence data rapidly available to the scientific community in a coordinated effort among the International Nucleotide Sequence databases, DDBJ, EMBL, and GenBank. Sequences are prepared for submission by using NCBI's software tools Sequin or tbl2asn. Each center has an FTP directory into which new or updated sequence files are placed. Sequence data in this division are available for BLAST homology searches against either the htgs database or the month database, which includes all new submissions for the prior month. Unfinished HTG sequences containing contigs greater than 2 kb are assigned an accession number and deposited in the HTG division. A typical HTG record might consist of all the first-pass sequence data generated from a single cosmid, BAC, YAC, or P1 clone, which together make up more than 2 kb and contain one or more gaps. A single accession number is assigned to this collection of sequences, and each record includes a clear indication of the status (phase 1 or 2) plus a prominent warning that the sequence data are unfinished and may contain errors. The accession number does not change as sequence records are updated; only the most recent version of a HTG record remains in GenBank.

Database of peer-reviewed, continually updated annotation for the Pseudomonas aeruginosa PAO1 reference strain genome expanded to include all Pseudomonas species to facilitate cross-strain and cross-species genome comparisons with high quality comparative genomics. The database contains robust assessment of orthologs, a novel ortholog clustering method, and incorporates five views of the data at the sequence and annotation levels (Gbrowse, Mauve and custom views) to facilitate genome comparisons. Other features include more accurate protein subcellular localization predictions and a user-friendly, Boolean searchable log file of updates for the reference strain PAO1. The current annotation is updated using recent research literature and peer-reviewed submissions by a worldwide community of PseudoCAP (Pseudomonas aeruginosa Community Annotation Project) participating researchers. If you are interested in participating, you are invited to get involved. Many annotations, DNA sequences, Orthologs, Intergenic DNA, and Protein sequences are available for download.

UNITE is a rDNA sequence database designed to provide a stable and reliable platform for sequence-borne identification of all fungal species. UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the International Nucleotide Sequence Databases (INSD: GenBank, ENA, DDBJ) are clustered to approximately the species level by applying a set of dynamic distance values (0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.

A database of human mitochondrial genomes containing mtDNA sequences, polymorphic sites, and the ability to search for specific variants. It contains 1865 complete sequences and 839 coding region sequences.

Graph theory provides a systematic method for modeling and analysing complicated biological data as an effective bioinformatics tool. Based on current trends, the number of DNA sequences in the DNA database is growing quickly. To determine the origin of a species and identify homologous sequences, it is crucial to detect similarities in DNA sequences. Alignment-free techniques are required for accurate measures of sequence similarity, which has been one of the main issues facing computational biologists. The current study provides a mathematical technique for comparing DNA sequences that are constructed in graph theory. The sequences of each DNA were divided into pairs of nucleotides, from which weighted loop digraphs and corresponding weighted vectors were computed. To check the sequence similarity, distance measures like Cosine, Correlation, and Jaccard were employed. To verify the method, DNA segments from the genomes of ten species of cotton were tested. Furthermore, to evaluate the efficacy of the proposed methodology, a K-means clustering method was performed. This study proposes a proof-of-model that utilises a distance matrix approach that promises impressive outcomes with future optimisations to be made to the suggested solution to get the hundred percent accurate result. In the realm of bioinformatics, this paper highlights the use of graph theory as an effective tool for biological data study and sequence comparison. It’s expected that further optimization in the proposed solution can bring remarkable results, as this paper presents a proof-of-concept implementation for a given set of data using the proposed distance matrix technique.

Maintains and provides archival, retrieval and analytical resources for biological information. Central DDBJ resource consists of public, open-access nucleotide sequence databases including raw sequence reads, assembly information and functional annotation. Database content is exchanged with EBI and NCBI within the framework of the International Nucleotide Sequence Database Collaboration (INSDC). In 2011, DDBJ launched two new resources: DDBJ Omics Archive and BioProject. DOR is archival database of functional genomics data generated by microarray and highly parallel new generation sequencers. Data are exchanged between the ArrayExpress at EBI and DOR in the common MAGE-TAB format. BioProject provides organizational framework to access metadata about research projects and data from projects that are deposited into different databases.