International Nucleotide Sequence Database Collaboration Research Articles

Molnupiravir increases SARS-CoV-2 genome diversity and complexity: A case-control cohort study.

Molnupiravir, an oral direct-acting antiviral effective in vitro against SARS-CoV-2, has been largely employed during the COVID-19 pandemic, since December 2021. After marketing and widespread usage, a progressive increase in SARS-CoV-2 lineages characterized by a higher transition/transversion ratio, a characteristic signature of molnupiravir action, appeared in the Global Initiative on Sharing All Influenza Data(GISAID) and International Nucleotide Sequence Database Collaboration(INSDC) databases. Here, we assessed the drug effects by SARS-CoV-2 whole-genome sequencing on 38 molnupiravir-treated persistently positive COVID-19 outpatients tested before and after treatment. Seventeen tixagevimab/cilgavimab-treated outpatients served as controls. Mutational analyses confirmed that SARS-CoV-2 exhibits an increased transition/transversion ratio seven days after initiation of molnupiravir. Moreover we observed an increased G->A ratio compared to controls, which was not related to apolipoprotein B mRNAediting enzyme, catalytic polypeptide-like (APOBEC) activity. In addition, we demonstrated for the first time an increased diversity and complexity of the viral quasispecies.

KoNA: Korean Nucleotide Archive as A New Data Repository for Nucleotide Sequence Data

Abstract During the last decade, the generation and accumulation of petabase-scale high-throughput sequencing data have resulted in great challenges, including access to human data, as well as transfer, storage, and sharing of enormous amounts of data. To promote data-driven biological research, the Korean government announced that all biological data generated from government-funded research projects should be deposited at the Korea BioData Station (K-BDS), which consists of multiple databases for individual data types. We introduce the Korean Nucleotide Archive (KoNA), a repository of nucleotide sequence data. As of July 2022, the Korean Read Archive in KoNA has collected over 477 TB of raw next-generation sequencing data from national genome projects. To ensure data quality and prepare for international alignment, a standard operating procedure was adopted, which is similar to that of the International Nucleotide Sequence Database Collaboration. The standard operating procedure includes quality control processes for submitted data and metadata using an automated pipeline, followed by manual examination. To ensure fast and stable data transfer, a high-speed transmission system called GBox is used in KoNA. Furthermore, the data uploaded to or downloaded from KoNA through GBox can be readily processed using a cloud computing service called Bio-Express. This seamless coupling of KoNA, GBox, and Bio-Express enhances the data experience, including submission, access, and analysis of raw nucleotide sequences. KoNA not only satisfies the unmet needs for a national sequence repository in Korea but also provides datasets to researchers globally and contributes to advances in genomics. The KoNA is available at https://www.kobic.re.kr/kona/.

Putting everything in its place: using the INSDC compliant Pathogen Data Object Model to better structure genomic data submitted for public health applications.

Fast, efficient public health actions require well-organized and coordinated systems that can supply timely and accurate knowledge. Public databases of pathogen genomic data, such as the International Nucleotide Sequence Database Collaboration (INSDC), have become essential tools for efficient public health decisions. However, these international resources began primarily for academic purposes, rather than for surveillance or interventions. Now, queries need to access not only the whole genomes of multiple pathogens but also make connections using robust contextual metadata to identify issues of public health relevance. Databases that over time developed a patchwork of submission formats and requirements need to be consistently organized and coordinated internationally to allow effective searches.To help resolve these issues, we propose a common pathogen data structure called the Pathogen Data Object Model (DOM) that will formalize the minimum pieces of sequence data and contextual data necessary for general public health uses, while recognizing that submitters will likely withhold a wide range of non-public contextual data. Further, we propose contributors use the Pathogen DOM for all pathogen submissions (bacterial, viral, fungal, and parasites), which will simplify data submissions and provide a consistent and transparent data structure for downstream data analyses. We also highlight how improved submission tools can support the Pathogen DOM, offering users additional easy-to-use methods to ensure this structure is followed.

DDBJ update in 2023: the MetaboBank for metabolomics data and associated metadata.

The Bioinformation and DNA Data Bank of Japan (DDBJ) Center (https://www.ddbj.nig.ac.jp) provides database archives that cover a wide range of fields in life sciences. As a founding member of the International Nucleotide Sequence Database Collaboration (INSDC), DDBJ accepts and distributes nucleotide sequence data as well as their study and sample information along with the National Center for Biotechnology Information in the United States and the European Bioinformatics Institute (EBI). Besides INSDC databases, the DDBJ Center provides databases for functional genomics (GEA: Genomic Expression Archive), metabolomics (MetaboBank) and human genetic and phenotypic data (JGA: Japanese Genotype-phenotype Archive). These database systems have been built on the National Institute of Genetics (NIG) supercomputer, which is also open for domestic life science researchers to analyze large-scale sequence data. This paper reports recent updates on the archival databases and the services of the DDBJ Center, highlighting the newly redesigned MetaboBank. MetaboBank uses BioProject and BioSample in its metadata description making it suitable for multi-omics large studies. Its collaboration with MetaboLights at EBI brings synergy in locating and reusing public data.

DNA sequences from type specimens and type strains - how to increase their number and improve their annotation in NCBI GenBank and related databases.

Scientific names permit humans and search engines to access knowledge about the biodiversity that surrounds us, and names linked to DNA sequences are playing an ever-greater role in search-and-match identification procedures. Here, we analyze how users and curators of the National Center for Biotechnology Information (NCBI) are flagging and curating sequences derived from nomenclatural type material, which is the only way to improve the quality of DNA-based identification in the long run. For prokaryotes, 18,281 genome assemblies from type strains have been curated by NCBI staff and improve the quality of prokaryote naming. For Fungi, type-derived sequences representing over 21,000 species are now essential for fungus naming and identification. For the remaining eukaryotes, however, the numbers of sequences identifiable as type-derived are minuscule, representing only 1,000 species of arthropods, 8,441 vertebrates, and 430 embryophytes. An increase in the production and curation of such sequences will come from (i) sequencing of types or topotypic specimens in museum collections, (ii) the March 2023 rule changes at the International Nucleotide Sequence Database Collaboration requiring more metadata for specimens, and (iii) efforts by data submitters to facilitate curation, including informing NCBI curators about a specimen's type status. We illustrate different type-data submission journeys and provide best-practice examples from a range of organisms. Expanding the number of type-derived sequences in DNA databases, especially of eukaryotes, is crucial for capturing, documenting, and protecting biodiversity.

The European Nucleotide Archive in 2023.

The European Nucleotide Archive (ENA; https://www.ebi.ac.uk/ena) is maintained by the European Molecular Biology Laboratory's European Bioinformatics Institute (EMBL-EBI). The ENA is one of the three members of the International Nucleotide Sequence Database Collaboration (INSDC). It serves the bioinformatics community worldwide via the submission, processing, archiving and dissemination of sequence data. The ENA supports data types ranging from raw reads, through alignments and assemblies to functional annotation. The data is enriched with contextual information relating to samples and experimental configurations. In this article, we describe recent progress and improvements to ENA services. In particular, we focus upon three areas of work in 2023: FAIRness of ENA data, pandemic preparedness and foundational technology. For FAIRness, we have introduced minimal requirements for spatiotemporal annotation, created a metadata-based classification system, incorporated third party metadata curations with archived records, and developed a new rapid visualisation platform, the ENA Notebooks. For foundational enhancements, we have improved the INSDC data exchange and synchronisation pipelines, and invested in site reliability engineering for ENA infrastructure. In order to support genomic surveillance efforts, we have continued to provide ENA services in support of SARS-CoV-2 data mobilisation and have adapted these for broader pathogen surveillance efforts.

Improving FAIRness of eDNA and Metabarcoding Data: Standards and tools for European Nucleotide Archive data deposition

The advancements in sequencing technologies have promoted the generation of molecular data for cataloguing and describing biodiversity. The analysis of environmental DNA (eDNA) through the application of metabarcoding techniques enables comprehensive descriptions of communities and their function, being fundamental for understanding and preserving biodiversity. Metabarcoding is becoming widely used and standard methods are being generated for a growing range of applications with high scalability. The generated data can be made available in its unprocessed form, as raw data (the sequenced reads) or as interpreted data, including sets of sequences derived after bioinformatics processing (Amplicon Sequence Variants (ASVs) or Operational Taxonomic Units (OTUs)) and occurrence tables (tables that describe the occurrences and abundances of species or OTUs/ASVs). However, for this data to be Findable, Accessible, Interoperable and Reusable (FAIR), and therefore fully available for meaningful interpretation, it needs to be deposited in public repositories together with enriched sample metadata, protocols and analysis workflows (ten Hoopen et al. 2017). Metabarcoding raw data and associated sample metadata is often stored and made available through the International Nucleotide Sequence Database Collaboration (INSDC) archives (Arita et al. 2020), of which the European Nucleotide Archive (ENA, Burgin et al. 2022) is its European database, but it is often deposited with minimal information, which hinders data reusability. Within the scope of the Horizon 2020 project, Biodiversity Community Integrated Knowledge Library (BiCIKL), which is building a community of interconnected data for biodiversity research (Penev et al. 2022), we are working towards improving the standards for molecular ecology data sharing, developing tools to facilitate data deposition and retrieval, and linking between data types. Here we will present the ENA data model, showcasing how metabarcoding data can be shared, while providing enriched metadata, and how this data is linked with existing data in other research infrastructures in the biodiversity domain, such as the Global Biodiversity Information Facility (GBIF), where data is deposited following the guidelines published in Abarenkov et al. (2023). We will also present the results of our recent discussions on standards for this data type and discuss future plans towards continuing to improve data sharing and interoperability for molecular ecology.

A model industrial workhorse: Bacillus subtilis strain 168 and its genome after a quarter of a century.

The vast majority of genomic sequences are automatically annotated using various software programs. The accuracy of these annotations depends heavily on the very few manual annotation efforts that combine verified experimental data with genomic sequences from model organisms. Here, we summarize the updated functional annotation of Bacillus subtilis strain 168, a quarter century after its genome sequence was first made public. Since the last such effort 5 years ago, 1168 genetic functions have been updated, allowing the construction of a new metabolic model of this organism of environmental and industrial interest. The emphasis in this review is on new metabolic insights, the role of metals in metabolism and macromolecule biosynthesis, functions involved in biofilm formation, features controlling cell growth, and finally, protein agents that allow class discrimination, thus allowing maintenance management, and accuracy of all cell processes. New 'genomic objects' and an extensive updated literature review have been included for the sequence, now available at the International Nucleotide Sequence Database Collaboration (INSDC: AccNum AL009126.4).

Importance of timely metadata curation to the global surveillance of genetic diversity.

Genetic diversity within species represents a fundamental yet underappreciated level of biodiversity. Because genetic diversity can indicate species resilience to changing climate, its measurement is relevant to many national and global conservation policy targets. Many studies produce large amounts of genome-scale genetic diversity data for wild populations, but most (87%) do not include the associated spatial and temporal metadata necessary for them to be reused in monitoring programs or for acknowledging the sovereignty of nations or Indigenous peoples. We undertook a distributed datathon to quantify the availability of these missing metadata and to test the hypothesis that their availability decays with time. We also worked to remediate missing metadata by extracting them from associated published papers, online repositories, and direct communication with authors. Starting with 848 candidate genomic data sets (reduced representation and whole genome) from the International Nucleotide Sequence Database Collaboration, we determined that 561 contained mostly samples from wild populations. We successfully restored spatiotemporal metadata for 78% of these 561 data sets (n=440 data sets with data on 45,105 individuals from 762 species in 17 phyla). Examining papers and online repositories was much more fruitful than contacting 351 authors, who replied to our email requests 45% of the time. Overall, 23% of our email queries to authors unearthed useful metadata. The probability of retrieving spatiotemporal metadata declined significantly as age of the data set increased. There was a 13.5% yearly decrease in metadata associated with published papers or online repositories and up to a 22% yearly decrease in metadata that were only available from authors. This rapid decay in metadata availability, mirrored in studies of other types of biological data, should motivate swift updates to data-sharing policies and researcher practices to ensure that the valuable context provided by metadata is not lost to conservation science forever.

Development of two new sets of PCR primers for eDNA metabarcoding of brittle stars (Echinodermata, Ophiuroidea)

Brittle stars (class Ophiuroidea) are marine invertebrates comprising approximately 2,100 extant species, and are considered to constitute the most diverse taxon of the phylum Echinodermata. As a non-invasive method for monitoring biodiversity, we developed two new sets of PCR primers for metabarcoding environmental DNA (eDNA) from brittle stars. The new primer sets were designed to amplify 2 short regions of the mitochondrial 16S rRNA gene, comprising a conserved region (111–115 bp, 112 bp on average; named “16SOph1”) and a hyper-variable region (180–195 bp, 185 bp on average; named “16SOph2”) displaying interspecific variation. The performance of the primers was tested using eDNA obtained from two sources: a) rearing water of an 2.5 or 170 L aquarium tanks containing 15 brittle star species and b) from natural seawater collected around Misaki, the Pacific coast of central Japan, at depths ranging from shallow (2 m) to deep (> 200 m) sea. To build a reference library, we obtained 16S rRNA sequences of brittle star specimens collected from around Misaki and from similar depths in Japan, and sequences registered in International Nucleotide Sequence Database Collaboration. As a result of comparison of the obtained eDNA sequences with the reference library 37 (including cryptic species) and 26 brittle star species were detected with certain identities by 16SOph1 and 16SOph2 analyses, respectively. In shallow water, the number of species and reads other than the brittle stars detected with 16SOph1 was less than 10% of the total number. On the other hand, the number of brittle star species and reads detected with 16SOph2 was less than half of the total number, and the number of detected non-brittle star metazoan species ranged from 20 to 46 species across 6 to 8 phyla (only the reads at the “Tank” were less than 0.001%). The number of non-brittle star species and reads at 80 m was less than 10% with both of the primer sets. These findings suggest that 16SOph1 is specific to the brittle star and 16SOph2 is suitable for a variety of marine metazoans. It appears, however, that further optimization of primer sequences would still be necessary to avoid possible PCR dropouts from eDNA extracts. Moreover, a detailed elucidation of the brittle star fauna in the examined area, and the accurate identification of brittle star species in the current DNA databank is required.

DNA Data Bank of Japan (DDBJ) update report 2022.

The Bioinformation and DNA Data Bank of Japan (DDBJ) Center (https://www.ddbj.nig.ac.jp) maintains database archives that cover a wide range of fields in life sciences. As a founding member of the International Nucleotide Sequence Database Collaboration (INSDC), our primary mission is to collect and distribute nucleotide sequence data, as well as their study and sample information, in collaboration with the National Center for Biotechnology Information in the United States and the European Bioinformatics Institute. In addition to INSDC resources, the Center operates databases for functional genomics (GEA: Genomic Expression Archive), metabolomics (MetaboBank), and human genetic and phenotypic data (JGA: Japanese Genotype-Phenotype Archive). These databases are built on the supercomputer of the National Institute of Genetics, whose remaining computational capacity is actively utilized by domestic researchers for large-scale biological data analyses. Here, we report our recent updates and the activities of our services.

Recommendations for use of annotations and persistent identifiers in taxonomy and biodiversity publishing

The paper summarises many years of discussions and experience of biodiversity publishers, organisations, research projects and individual researchers, and proposes recommendations for implementation of persistent identifiers for article metadata, structural elements (sections, subsections, figures, tables, references, supplementary materials and others) and data specific to biodiversity (taxonomic treatments, treatment citations, taxon names, material citations, gene sequences, specimens, scientific collections) in taxonomy and biodiversity publishing. The paper proposes best practices on how identifiers should be used in the different cases and on how they can be minted, cited, and expressed in the backend article XML to facilitate conversion to and further re-use of the article content as FAIR data. The paper also discusses several specific routes for post-publication re-use of semantically enhanced content through large biodiversity data aggregators such as the Global Biodiversity Information Facility (GBIF), the International Nucleotide Sequence Database Collaboration (INSDC) and others, and proposes specifications of both identifiers and XML tags to be used for that purpose. A summary table provides an account and overview of the recommendations. The guidelines are supported with examples from the existing publishing practices.

Enabling Community Curation of Biological Source Annotations of Molecular Data Through PlutoF and the ELIXIR Contextual Data Clearinghouse

The advancements in sequencing technologies have greatly contributed to the documentation of Earth’s biodiversity. However, for exploring the full potential of molecular resources for biodiversity, there needs to be a good linkage between sequence data and its biological source, contributing to a network of connected data in the biodiversity research cycle. This requires a foundation of well-structured and accessible annotations in the molecular sequence repositories. The International Nucleotide Sequence Database Collaboration (INSDC), of which the European Nucleotide Archive (ENA) is its European node, holds a large amount of annotations associated with sequence data, relating to its biological source (e.g., specimens in natural history collections). However, for a number of records, these annotations may be incomplete (e.g., missing voucher information), ambiguous or even inaccurate. Therefore, we have implemented a workflow that allows third-party annotations to be attached to sequence and sample records using two existing services, the PlutoF platform and the ELIXIR Contextual Data ClearingHouse. This work was developed within the scope of the BiCIKL (Biodiversity Community Integrated Knowledge Library) project, which aims to establish open science practices in the biodiversity domain. PlutoF is an online data management platform that also provides computing services for biology-related research. PlutoF features allow registered users to enter their own data and access public data at INSDC. Users can enter and manage a range of data, as taxonomic classifications, occurrences, etc. This platform also includes a module that allows the addition of third-party annotations (on material source, taxonomic identification, etc.) linked to specimens or sequence records. This module was already in use by the UNITE community for annotation of INSDC rDNA Internal Transcribed Spacer sequence datasets (Abarenkov et al. 2021). These UNITE annotations are displayed in the National Centre for Biotechnology Information (NCBI) records through links to the PlutoF platform. However, there was the need for an automated solution that allowed third-party annotations to any sequence or sample record at INSDC. This was implemented through the operation of the ELIXIR Contextual Data ClearingHouse (hereafter as Clearinghouse). The Clearinghouse holds a simple RESTful Application Programming Interface (API) to support the submission of additions and improvements to current metadata attributes, such as information on material sources, on records publicly available in the ELIXIR data resources. The Clearinghouse enables the submission of these corrected metadata from databases (such as the PlutoF platform) to the primary data repositories. The workflow developed is shown in Fig. 1 and consists of the following steps: i) users annotate sequence metadata that is regularly downloaded from INSDC using NCBI’s E-utilities; ii) an annotation proposal is created and a verification notification is sent to an assigned reviewer; iii) the reviewer evaluates the annotation proposal and accepts it or rejects it with comments; iv) if the annotation proposal is accepted, the annotated fields that may be mapped to ENA fields are then pushed to the Clearinghouse using their RESTful API. The annotations when received at ENA are then reviewed before being displayed. This workflow is implemented through a web interface in PlutoF, which allows user-friendly and effortless reporting of corrections or additions to biological source metadata in sequence records. Overall, we expect this tool to contribute to the enrichment of metadata associated with sequence records, and therefore increase the links between the molecular and biodiversity resources, and enable sequencing data to deliver their full potential for biodiversity conservation.

Data Flows for Metabarcoding-based Monitoring in the Project Automated Multisensor Stations for Monitoring of Biodiversity

Biodiversity monitoring is an important tool to document rapid ecosystem changes and on-going species loss by collecting high-resolution biodiversity data over long periods of time. Large-scale monitoring provides long-range information on species occurrence, interactions, and migrations. In the German project "Automated Multisensor Stations for Monitoring of BioDiversity" (AMMOD, https://ammod.de/), field stations equipped with different sensors (e.g. acoustic sensors, camera traps, volatile organic compound sensors, pollen and insect traps) are being developed that can be operated largely autonomously. These stations provide continuous data on the occurrence of birds, bats, mammals, insects and plants and associated environmental parameters. Besides the autonomous operation of the stations, a challenge is to master the different requirements that the wide range of sensors bring with them (cf. Wägele et al. 2022). In addition to the detection of fauna and flora by means of sounds, images, films and smells, samples are also collected in malaise and pollen traps with automatically rotating multi samplers. The mixed samples are processed in the laboratory using metabarcoding methods and the resulting sequence data bioinformatically processed into amplicon sequence variants (ASV, Callahan et al. 2017). Unlike data from acoustic sensors or camera traps, which can flow and be analyzed almost entirely automatically, metabarcoding requires a labor-intensive intermediate step in the laboratories at the University of Kassel (pollen) and the LIB (insects). In addition, metabarcoding requires good (preferably local) barcode reference databases, like Barcode Of Life Data system (BOLD) and the German Barcode of Life library (GBOL); long-term data storage for raw and processed data; reliable retrieval of ASV sequences; and versioning of supercharged data through dynamic assignment during taxon annotation. Here, we present the pipeline for acquisition, intersection, management, storage and publication of data from metabarcoding derived from bulk insect and pollen samples. The metabarcoding data pipeline is connected to the overall data flow developed in the AMMOD project (Wägele et al. 2022, Fig. 12) and ultimately delivers processed taxon tables with linked information to the raw sequences published, methods used and other sources of information to the upcoming NFDI4Biodiversity Research Data Commons (RDC, https://www.nfdi4biodiversity.org, Glöckner et al. 2020) using the AMMOD data broker. Raw sequences (i.e., FASTQ files, sampling and laboratory metadata) will be stored and published the in the International Nucleotide Sequence Database Collaboration (GenBank or ENA) using the data flows from the German Federation for Biological Data (GFBio, https://gfbio.org) as proxy. The three data sources for the AMMOD metabarcoding data pipeline are derived from the multisampler with connected malaise or spore traps plus environmental data loggers. Bioinformatic analysis and generation of ASVs is provided by the users, using their own pipelines. For storage, publication and transmission of results to the NFDI4Biodiversity RDC, an ASV table registry is provided along with the possibility of uploading log files, laboratory protocols and collection tables. In the ASV registry, the uploaded tables are taxonomically annotated through the connected reference databases and stored as versioned datasets. The processed and annotated datasets are transmitted to the AMMOD broker in a standardized format as JSON datasets. Connection of the components: an identifier, which uniquely identifies the data from the respective components of field stations and laboratories, is the prerequisite for the unique assignment of data parts. This AMMOD ID consists of the project name, the case number, the sensor type, a time stamp with the number of the sample and the bottle or plate number. For example, the ID AMMOD-T1-M-R210511-B1 denotes a sample of the AMMOD project from trap 1 of type Malaise dated May 11, 2021 from the first bottle. All bottles and data entries from the laboratory, log files and subsequent processes are provided with such an ID. The orchestra of different components was built under the aspect of sustainable software development and compatibility to existing systems such as the Leibniz Institute for the Analysis of Biodiversity Change (LIB) Biobank and the LIB Digital Collection Catalog. All developed software is published at: https://gitlab.leibniz-lib.de/AMMOD/ and https://gitlab.leibniz-lib.de/GBOL/asv-table-registry The portal for ASV registration and upload is available on: https://bolgermany.de/metabarcoding

Bridging a Gap in Metabarcoding Research: The ASV Table Registry

Metabarcoding is a tool to routinely identify species in environmental mass-samples and thereby analyze their species composition. Using metabarcoding techniques outperforms the traditional species identification by human experts in amount, speed and quality when well curated reference data are available. Therefore, metabarcoding can be seen as the future standard method for all biological research areas where species occurrence and distribution is in question, e.g., ecological research or monitoring projects (Porter and Hajibabaei 2018). A common outcome of metabarcoding research are Amplicon Sequence Variant tables (ASV, Callahan et al. 2017). These tables combine the extracted sequences of all sampling plots with the occurrences of each sequence within a single plot. To identify the species, each sequence is searched in one or more reference databases that hold sequences and their known taxon identifications (e.g., Barcode Of Life Data system (BOLD) or the German Barcode of Life library (GBOL)). The sequence searches utilise tools like BLAST, BOLD identification engine, or vsearch. Found taxa and their taxonomy are added to the ASV tables as taxon assignments. The number and precision of taxon assignments will increase with the growth of available sequences and quality of identifications in reference databases over time (Weigand et al. 2019). The introduction of new marker sequences and improvements in search tools will further enhance the taxon assignments. Thus, the taxon assignments in ASV tables are subject to change. Projects with the aim of building up species inventories on a large scale (GBOL) or monitoring programs, like the Automated Multisensor Stations for Monitoring of BioDiversity (Wägele et al. 2022), quickly produce data sets with thousands of sequences at numerous locations. Currently, most ASV tables are stored as supplements to publications or in private repositories. This makes analysis across multiple research projects difficult and error prone as sequences and their taxon assignments are often not accessible. Efforts, like the European Bioinformatics Institute metagenomics with Mgnify serve the needs for uploading and annotating environmental DNA samples (Mitchell et al. 2017), but a registry for ASV tables with complete data life cycles is lacking. To fill this gap, we develop an ASV Table Registry as part of the German Barcode of Life III - Dark Taxa project. This allows users to: register ASV tables and sequences upload and manage ASV tables with versioning publish ASV tables with DOIs search by sequences, taxa, and occurrence data retrieve API-based data assign taxonomic names with various tools and reference databases keep track of the applied search methods and parameters register ASV tables and sequences upload and manage ASV tables with versioning publish ASV tables with DOIs search by sequences, taxa, and occurrence data retrieve API-based data assign taxonomic names with various tools and reference databases keep track of the applied search methods and parameters The data life cycle of the uploaded ASV tables consists of several draft versions (each re-annotation with the identification pipeline creates a new draft version) and eventually a published version with a DOI. New draft versions can be created from the published version, then re-annotated and published again. The tracking of former taxon assignments allows researchers to re-evaluate data of former studies, compare them, and add new results. The ASV Table Registry developed here aims to make ASV tables FAIR (Findable, Accessible, Interoperable, and Reusable) and to foster the shared use in research projects. Future development focuses on the incorporation of the MIxS standard (Yilmaz et al. 2011) and on submission of the published data to International Nucleotide Sequence Database Collaboration (INSDC) using established dataflows from the German Federation for Biological Data (GFBio) and NFDI4biodiversity. The ASV data portal is accessible at: https://bolgermany.de/metabarcoding; the source code at: https://gitlab.leibniz-lib.de/GBOL/asv-table-registry.

Towards Connecting Molecular Data and the Biodiversity Research Community: An ENA and ELIXIR biodiversity community perspective

Global and regional efforts for generating molecular sequencing data are fundamental to characterise and monitor the Earth’s biodiversity. However, exploiting the full potential of molecular data for biodiversity monitoring and conservation is still a challenge. There is still the need to fully connect the generation and archiving of sequence data with other biodiversity infrastructures, thereby promoting Findability, Accessability, Interoperability and Reusability (FAIR) of data. Here we present the ongoing activities and future plans of the European Life-Science Infrastructure (ELIXIR) and the European Molecular Biology Laboratory European Bioinformatics Institute’s (EMBL-EBI) European Nucleotide Archive (ENA, the European node of the International Nucleotide Sequence Database Collaboration - INSDC) towards an enriched set of sequence data connected to the wider biodiversity research community. ELIXIR has an emerging Biodiversity Community that was originally created as a focus group in 2019, to better align the work in biodiversity across the ELIXIR Nodes and with global initiatives in the biodiversity domain. This group has been working on understanding the capabilities, interests and ongoing projects that exist across the Nodes, developing connections with external partners in the biodiversity area (e.g. Global Biodiversity Information Facilitiy, GBIF; LifeWatch Eric) and developing a longer term strategy for support of biodiversity by ELIXIR. A recent opinion piece by the group (Waterhouse et al. 2021) highlights opportunities for infrastructure developments in the area of biodiversity and provides recommendations for closer integration of molecular data with biodiversity research. These recommendations include the alignment of taxonomies across domains and the general adoption of standardized metadata. ELIXIR and EMBL-EBI are involved in several biodiversity genomics initiatives, including the Earth BioGenome Project (EBP), the Darwin Tree of Life Project (DToL), the European Reference Genome Atlas (ERGA), and the BIOSCAN Europe, where support is being provided to data curation, submission and visibility and in the definition of standards for the associated metadata (e.g. Lawniczak et al. 2022). Moreover, EMBL-EBI is a partner of UniEuk, an initiative that is working towards building a flexible universal taxonomic framework for eukaryotes. ELIXIR and EMBL-EBI are also part of the Biodiversity Community Integrated Knowledge Library (BiCIKL), an Horizon 2020 project that is working towards establishing FAIR practices in the biodiversity domain, and thereby developing tools and workflows for connecting data along the biodiversity research cycle (Penev et al. 2022). These projects and community efforts are contributing to improving metadata standards and pushing the development of tools and workflows to support enriched metadata and increased linkage with other biodiversity infrastructures. Overall, we need to continue to work towards a strong foundation of interlinked knowledge to be able to effectively respond to global challenges such as biodiversity loss and ecosystem change.

The ENA Source Attribute Helper: An API for improved biological source data

Metadata management for sequence data is essential for the accurate description of Earth’s biodiversity. Within metadata attributes, those that reference the biological sources of sequences and samples and allow linking to the specimen or sample of origin are fundamental for facilitating connections between molecular biology, taxonomy, systematic biology and biodiversity research, increasing the discoverability and usability of data by researchers worldwide. Sequence data is publicly archived at the International Nucleotide Sequence Database Collaboration (INSDC) that includes the National Centre for Biotechnology Information (NCBI), the DNA Data Bank of Japan (DDBJ) and the European Nucleotide Archive (ENA). Sequences stored at INSDC have associated a considerable range of metadata, including attributes related to its biological source, such as references to natural history collections or culture collections. But, these source attributes are not always submitted or may be incomplete, limiting the association of the sequence records to the original source material, hampering further data connections (e.g., biological data associated with the voucher or species distribution data). Therefore, we have developed the ENA Source Attribute Helper API, a tool that aims to assist users on the submission of accurate attributes referring to the biological source of samples and sequence data. This tool was developed within the scope of BiCIKL (Biodiversity Community Integrated Knowledge Library) (Penev et al. 2022), a Horizon 2020 project which targets building a wide, biodiversity related community for connecting data along the different axes of biodiversity research. The first version of the tool was designed to support correct annotation of the attributes that identify the source material from which the sample or sequence were obtained, namely /specimen_voucher, /culture_collection, and /biomaterial (INSDC 2021). These attributes follow a Darwin Core Triplet format (Wieczorek et al. 2012), composed of institution code, collection code and the specimen, culture, or material identifier, accordingly. Since the submission of the biological source attributes to the INSDC may be performed both when data is initially uploaded or on following updates using a variety of tools, we developed the API as an open source tool that is publicly accessible and may be used as a free-standing service. The API is built using Representational State Transfer (REST) API Architecture and it is designed to use the data available in the NCBI BioCollections (Sharma et al. 2018). NCBI Biocollections is a curated database of metadata for natural history collections, associated with records in INSDC, that includes the institution and collection codes. The API main functions include the querying of the metadata (the API presents both exact matches and similar matches) for the institutions and collections based on the user input, validation of institution and collection codes in the attribute strings provided by the user, and the construction of the attribute string based on the user-provided information. The API does not include the search or validation of the voucher specimen codes. The API is designed in a way that it can be extended easily for any future enhancements and initially expected to promote and support the submission and any subsequent curation of better structured and more richly described source data. We expect this tool to contribute to better connected biodiversity data and hence provide a stronger foundation to strengthen the value of natural history collections, taxonomic expertise, and biodiversity knowledge.

Enabling Published Taxonomic Data to be used to Address the Biodiversity Crisis: Biodiversity Literature Repository and TreatmentBank

To understand the loss of species, a benchmark is needed, e.g. the status of biodiversity in 1992 when the Convention on Biological Diversity recognized biodiversity crisis to compare to its status in the successive year. Though we are far from knowning how many species there are on planet Earth, we keep track of their descriptions and number through the information kept in our libraries. Each species discovered is represented therein by at least one taxononic treatment. The library includes an estimated 500 million pages and is updated daily with an estimated 17–18,000 new species annually and over 100,000 treatments augmenting the knowledge of existing species. In reality, we do not know how many species exist. We know that the catalogue of life is incomplete and basic knowlege of known species is often lacking and not even updated regularly. On the other hand, the scientific standard to cite previous works and facts is at the same time an ideal prerequisit to build a knowledge graph in the era of digital knowledge. TreatmentBank (TB) and the Biodiversity Literature Repository (BLR), two European Research Infrastructures, provide a service to convert unstructured biodiversity data from scholarly publications into semantically enhanced, digital accessible knowledge (Fawcett et al. 2022) making it findable, accessible, interoperable, reusable (FAIR, Wilkinson et al. 2016) and providing long term access in collaboration with Zenodo. Data sources are either legacy publications or active journals using an XML workflow such as Zookeys or the Biodiversity Data Journal, published by the pioneer of taxonomically enhanced Taxpub XML publishing, Pensoft. As part of the Horizon 2020-funded project Biodiversity Community Integrated Knowledge Library (BiCIKL), bidirectional linking of taxonomic names with the Catalogue of Life, DNA-sequences with the International Nucleotide Sequence Database Collaboration (INSDC) and material citations with their respective natural history collection or their depositions in the Global Biodiversity Information Facility (GBIF) is targeted. As input to allow queries including text and data mining for traits and biotic interactions, the treatments are uploaded to the Swiss Institute of Bioinformatics (SIB) Library Service (SIBiLS) using TaxPub and schema based on Journal Article Tag Suite (JATS) widely used in life science publishing and PubMed Central, allowing the use of the advanced text and data mining tools in the life science community. Another research infrastructure that ensures an RDF representation and conversion into Linked Open Data (LOD) is OpenBiodiv allowing users to explore DAK as part of growing linked open biodiverstiy and related data. All the data fit for GBIF use is reused by GBIF representing close to 60% of all published data sets, which makes TreatmentBank and BLR, for example, a sole provider of data for approximately 90,000 species not recorded in GBIF by other publishers. The long-term strategy is to build up the momentum to be an infrastructure relevant for global biodiversity conservation and research. Long-term support will be achieved by negotiations with respective agencies and publishers, and through building up a global user community using the biodiversity digital acccessible knowledge.

Genomic Diversity of Bacteriophages Infecting the Genus Acinetobacter.

The number of sequenced Acinetobacter phage genomes in the International Nucleotide Sequence Database Collaboration has increased significantly in recent years, from 37 in 2017 to a total of 139 as of January 2021 with genome sizes ranging from 31 to 378 kb. Here, we explored the genetic diversity of the Acinetobacter phages using comparative genomics approaches that included assessment of nucleotide similarity, shared gene content, single gene phylogeny, and the network-based classification tool vConTACT2. Phages infecting Acinetobacter sp. are genetically diverse and can be grouped into 8 clusters (subfamilies) and 46 sub-clusters (genera), of which 8 represent genomic singletons (additional genera). We propose the creation of five new subfamilies and suggest a reorganisation of the genus Obolenskvirus. These results provide an updated view of the viruses infecting Acinetobacter species, providing insights into their diversity.

Review of genome sequencing technologies in molecular characterization of influenza A viruses in swine.

The rapidly evolving antigenic diversity of influenza A virus (IAV) genomes in swine makes it imperative to detect emerging novel strains and track their circulation. We analyzed in our review the sequencing technologies used for subtyping and characterizing swine IAV genomes. Google Scholar, PubMed, and International Nucleotide Sequence Database Collaboration (INSDC) database searches identified 216 studies that have utilized Sanger, second-, and third-generation sequencing techniques to subtype and characterize swine IAV genomes up to 31 March 2021. Sanger dideoxy sequencing was by far the most widely used sequencing technique for generating either full-length (43.0%) or partial (31.0%) IAV genomes in swine globally; however, in the last decade, other sequencing platforms such as Illumina have emerged as serious competitors for the generation of whole-genome sequences of swine IAVs. Although partial HA and NA gene sequences were sufficient to determine swine IAV subtypes, whole-genome sequences were critical for determining reassortments and identifying unusual or less frequently occurring IAV subtypes. The combination of Sanger and second-generation sequencing technologies also greatly improved swine IAV characterization. In addition, the rapidly evolving third-generation sequencing platform, MinION, appears promising for on-site, real-time sequencing of complete swine IAV genomes. With a higher raw read accuracy, the use of the MinION could enhance the scalability of swine IAV testing in the field and strengthen the swine IAV disease outbreak response.