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.

SARS-CoV-2 HaploGraph: visualization of SARS-CoV-2 haplotype spread in Japan.

Since the early phase of the coronavirus disease 2019 (COVID-19) pandemic, a number of research institutes have been sequencing and sharing high-quality severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomes to trace the route of infection in Japan. To provide insight into the spread of COVID-19, we developed a web platform named SARS-CoV-2 HaploGraph to visualize the emergence timing and geographical transmission of SARS-CoV-2 haplotypes. Using data from the GISAID EpiCoV database as of June 4, 2022, we created a haplotype naming system by determining the ancestral haplotype for each epidemic wave and showed prefecture- or region-specific haplotypes in each of four waves in Japan. The SARS-CoV-2 HaploGraph allows for interactive tracking of virus evolution and of geographical prevalence of haplotypes, and aids in developing effective public health control strategies during the global pandemic. The code and the data used for this study are publicly available at: https://github.com/ktym/covid19/.

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.

The NBDC-DDBJ imputation server facilitates the use of controlled access reference panel datasets in Japan.

Accurate genotype imputation requires large-scale reference panel datasets. When conducting genotype imputation on the Japanese population, researchers can use such datasets under collaborative studies or controlled access conditions in public databases. We developed the NBDC-DDBJ imputation server, which securely provides users with a web user interface to execute genotype imputation on the server. Our benchmarking analysis showed that the accuracy of genotype imputation was improved by leveraging controlled access datasets to increase the number of haplotypes available for analysis compared to using publicly available reference panels such as the 1000 Genomes Project. The NBDC-DDBJ imputation server facilitates the use of controlled access datasets for accurate genotype imputation.

DNA Data Bank of Japan (DDBJ) update report 2021.

The Bioinformation and DDBJ (DNA Data Bank of Japan) Center (DDBJ Center; https://www.ddbj.nig.ac.jp) operates archival databases that collect nucleotide sequences, study and sample information, and distribute them without access restriction to progress life science research as a member of the International Nucleotide Sequence Database Collaboration (INSDC), in collaboration with the National Center for Biotechnology Information (NCBI) and the European Bioinformatics Institute. Besides the INSDC databases, the DDBJ Center also provides the Genomic Expression Archive for functional genomics data and the Japanese Genotype-phenotype Archive for human data requiring controlled access. Additionally, the DDBJ Center started a new public repository, MetaboBank, for experimental raw data and metadata from metabolomics research in October 2020. In response to the COVID-19 pandemic, the DDBJ Center openly shares SARS-CoV-2 genome sequences in collaboration with Shizuoka Prefecture and Keio University. The operation of DDBJ is based on the National Institute of Genetics (NIG) supercomputer, which is open for large-scale sequence data analysis for life science researchers. This paper reports recent updates on the archival databases and the services of DDBJ.

Genome sequencing of the NIES Cyanobacteria collection with a focus on the heterocyst-forming clade.

Cyanobacteria are a diverse group of Gram-negative prokaryotes that perform oxygenic photosynthesis. Cyanobacteria have been used for research on photosynthesis and have attracted attention as a platform for biomaterial/biofuel production. Cyanobacteria are also present in almost all habitats on Earth and have extensive impacts on global ecosystems. Given their biological, economical, and ecological importance, the number of high-quality genome sequences for Cyanobacteria strains is limited. Here, we performed genome sequencing of Cyanobacteria strains in the National Institute for Environmental Studies microbial culture collection in Japan. We sequenced 28 strains that can form a heterocyst, a morphologically distinct cell that is specialized for fixing nitrogen, and 3 non-heterocystous strains. Using Illumina sequencing of paired-end and mate-pair libraries with in silico finishing, we constructed highly contiguous assemblies. We determined the phylogenetic relationship of the sequenced genome assemblies and found potential difficulties in the classification of certain heterocystous clades based on morphological observation. We also revealed a bias on the sequenced strains by the phylogenetic analysis of the 16S rRNA gene including unsequenced strains. Genome sequencing of Cyanobacteria strains deposited in worldwide culture collections will contribute to understanding the enormous genetic and phenotypic diversity within the phylum Cyanobacteria.

Complete sequence and structure of the genome of the harmful algal bloom-forming cyanobacterium Planktothrix agardhii NIES-204T and detailed analysis of secondary metabolite gene clusters.

Planktothrix species are distributed worldwide, and these prevalent cyanobacteria occasionally form potentially devastating toxic blooms. Given the ecological and taxonomic importance of Planktothrix agardhii as a bloom species, we set out to determine the complete genome sequence of the type strain Planktothrix agardhii NIES-204. Remarkably, we found that the 5S ribosomal RNA genes are not adjacent to the 16S and 23S ribosomal RNA genes. The genomic structure of P. agardhii NIES-204 is highly similar to that of another P. agardhii strain isolated from a geographically distant site, although they differ distinctly by a large inversion. We identified numerous gene clusters that encode the components of the metabolic pathways that generate secondary metabolites. We found that the aeruginosin biosynthetic gene cluster was more similar to that of another toxic bloom-forming cyanobacterium Microcystis aeruginosa than to that of other strains of Planktothrix, suggesting horizontal gene transfer. Prenyltransferases encoded in the prenylagaramide gene cluster of Planktothrix strains were classified into two phylogenetically distinct types, suggesting a functional difference. In addition to the secondary metabolite gene clusters, we identified genes for inorganic nitrogen and phosphate uptake components and gas vesicles. Our findings contribute to further understanding of the ecologically important genus Planktothrix.

DDBJ update: streamlining submission and access of human data.

The Bioinformation and DDBJ Center (DDBJ Center, https://www.ddbj.nig.ac.jp) provides databases that capture, preserve and disseminate diverse biological data to support research in the life sciences. This center collects nucleotide sequences with annotations, raw sequencing data, and alignment information from high-throughput sequencing platforms, and study and sample information, in collaboration with the National Center for Biotechnology Information (NCBI) and the European Bioinformatics Institute (EBI). This collaborative framework is known as the International Nucleotide Sequence Database Collaboration (INSDC). In collaboration with the National Bioscience Database Center (NBDC), the DDBJ Center also provides a controlled-access database, the Japanese Genotype-phenotype Archive (JGA), which archives and distributes human genotype and phenotype data, requiring authorized access. The NBDC formulates guidelines and policies for sharing human data and reviews data submission and use applications. To streamline all of the processes at NBDC and JGA, we have integrated the two systems by introducing a unified login platform with a group structure in September 2020. In addition to the public databases, the DDBJ Center provides a computer resource, the NIG supercomputer, for domestic researchers to analyze large-scale genomic data. This report describes updates to the services of the DDBJ Center, focusing on the NBDC and JGA system enhancements.

BioHackathon 2015: Semantics of data for life sciences and reproducible research.

We report on the activities of the 2015 edition of the BioHackathon, an annual event that brings together researchers and developers from around the world to develop tools and technologies that promote the reusability of biological data. We discuss issues surrounding the representation, publication, integration, mining and reuse of biological data and metadata across a wide range of biomedical data types of relevance for the life sciences, including chemistry, genotypes and phenotypes, orthology and phylogeny, proteomics, genomics, glycomics, and metabolomics. We describe our progress to address ongoing challenges to the reusability and reproducibility of research results, and identify outstanding issues that continue to impede the progress of bioinformatics research. We share our perspective on the state of the art, continued challenges, and goals for future research and development for the life sciences Semantic Web.

DDBJ Data Analysis Challenge: a machine learning competition to predict Arabidopsis chromatin feature annotations from DNA sequences.

Recently, the prospect of applying machine learning tools for automating the process of annotation analysis of large-scale sequences from next-generation sequencers has raised the interest of researchers. However, finding research collaborators with knowledge of machine learning techniques is difficult for many experimental life scientists. One solution to this problem is to utilise the power of crowdsourcing. In this report, we describe how we investigated the potential of crowdsourced modelling for a life science task by conducting a machine learning competition, the DNA Data Bank of Japan (DDBJ) Data Analysis Challenge. In the challenge, participants predicted chromatin feature annotations from DNA sequences with competing models. The challenge engaged 38 participants, with a cumulative total of 360 model submissions. The performance of the top model resulted in an area under the curve (AUC) score of 0.95. Over the course of the competition, the overall performance of the submitted models improved by an AUC score of 0.30 from the first submitted model. Furthermore, the 1st- and 2nd-ranking models utilised external data such as genomic location and gene annotation information with specific domain knowledge. The effect of incorporating this domain knowledge led to improvements of approximately 5%-9%, as measured by the AUC scores. This report suggests that machine learning competitions will lead to the development of highly accurate machine learning models for use by experimental scientists unfamiliar with the complexities of data science.

DDBJ Database updates and computational infrastructure enhancement.

The Bioinformation and DDBJ Center (https://www.ddbj.nig.ac.jp) in the National Institute of Genetics (NIG) maintains a primary nucleotide sequence database as a member of the International Nucleotide Sequence Database Collaboration (INSDC) in partnership with the US National Center for Biotechnology Information and the European Bioinformatics Institute. The NIG operates the NIG supercomputer as a computational basis for the construction of DDBJ databases and as a large-scale computational resource for Japanese biologists and medical researchers. In order to accommodate the rapidly growing amount of deoxyribonucleic acid (DNA) nucleotide sequence data, NIG replaced its supercomputer system, which is designed for big data analysis of genome data, in early 2019. The new system is equipped with 30 PB of DNA data archiving storage; large-scale parallel distributed file systems (13.8 PB in total) and 1.1 PFLOPS computation nodes and graphics processing units (GPUs). Moreover, as a starting point of developing multi-cloud infrastructure of bioinformatics, we have also installed an automatic file transfer system that allows users to prevent data lock-in and to achieve cost/performance balance by exploiting the most suitable environment from among the supercomputer and public clouds for different workloads.

Generating Publication-Ready Prokaryotic Genome Annotations with DFAST.

DDBJ Fast Annotation and Submission Tool (DFAST) is a genome annotation pipeline for prokaryotes, which also assists data submission to the public sequence database. It is available both as a web service and as a stand-alone tool that runs on local machines. DFAST can annotate a typical-sized bacterial genome within 5 min. The default annotation workflow contains a gene prediction phase for protein coding sequence, rRNA, tRNA, and CRISPR, and a functional annotation phase to infer protein functions. DFAST generates result files in standard annotation formats and data files for submission to DNA Data Bank of Japan (DDBJ). In this chapter, the annotation workflow and applications of DFAST are introduced.

TogoGenome/TogoStanza: modularized Semantic Web genome database.

TogoGenome is a genome database that is purely based on the Semantic Web technology, which enables the integration of heterogeneous data and flexible semantic searches. All the information is stored as Resource Description Framework (RDF) data, and the reporting web pages are generated on the fly using SPARQL Protocol and RDF Query Language (SPARQL) queries. TogoGenome provides a semantic-faceted search system by gene functional annotation, taxonomy, phenotypes and environment based on the relevant ontologies. TogoGenome also serves as an interface to conduct semantic comparative genomics by which a user can observe pan-organism or organism-specific genes based on the functional aspect of gene annotations and the combinations of organisms from different taxa. The TogoGenome database exhibits a modularized structure, and each module in the report pages is separately served as TogoStanza, which is a generic framework for rendering an information block as IFRAME/Web Components, which can, unlike several other monolithic databases, also be reused to construct other databases. TogoGenome and TogoStanza have been under development since 2012 and are freely available along with their source codes on the GitHub repositories at https://github.com/togogenome/ and https://github.com/togostanza/, respectively, under the MIT license.

Draft Genome Sequence of the Nitrogen-Fixing and Hormogonia-Inducing Cyanobacterium Nostoc cycadae Strain WK-1, Isolated from the Coralloid Roots of Cycas revoluta.

We report here the whole-genome sequence of Nostoc cycadae strain WK-1, which was isolated from cyanobacterial colonies growing in the coralloid roots of the gymnosperm Cycas revoluta It can provide valuable resources to study the mutualistic relationships and the syntrophic metabolisms between the cyanobacterial symbiont and the host plant, C. revoluta.

DFAST: a flexible prokaryotic genome annotation pipeline for faster genome publication.

Summary: We developed a prokaryotic genome annotation pipeline, DFAST, that also supports genome submission to public sequence databases. DFAST was originally started as an on-line annotation server, and to date, over 7000 jobs have been processed since its first launch in 2016. Here, we present a newly implemented background annotation engine for DFAST, which is also available as a standalone command-line program. The new engine can annotate a typical-sized bacterial genome within 10 min, with rich information such as pseudogenes, translation exceptions and orthologous gene assignment between given reference genomes. In addition, the modular framework of DFAST allows users to customize the annotation workflow easily and will also facilitate extensions for new functions and incorporation of new tools in the future. Availability and implementation: The software is implemented in Python 3 and runs in both Python 2.7 and 3.4-on Macintosh and Linux systems. It is freely available at https://github.com/nigyta/dfast_core/under the GPLv3 license with external binaries bundled in the software distribution. An on-line version is also available at https://dfast.nig.ac.jp/. Contact: yn@nig.ac.jp. Supplementary information: Supplementary data are available at Bioinformatics online.

Complete Genome Sequence of a Coastal Cyanobacterium, Synechococcus sp. Strain NIES-970.

Members of the cyanobacterial genus Synechococcus are abundant in marine environments. To better understand the genomic diversity of marine Synechococcus spp., we determined the complete genome sequence of a coastal cyanobacterium, Synechococcus sp. NIES-970. The genome had a size of 3.1 Mb, consisting of one chromosome and four plasmids.

DNApod: DNA polymorphism annotation database from next-generation sequence read archives.

With the rapid advances in next-generation sequencing (NGS), datasets for DNA polymorphisms among various species and strains have been produced, stored, and distributed. However, reliability varies among these datasets because the experimental and analytical conditions used differ among assays. Furthermore, such datasets have been frequently distributed from the websites of individual sequencing projects. It is desirable to integrate DNA polymorphism data into one database featuring uniform quality control that is distributed from a single platform at a single place. DNA polymorphism annotation database (DNApod; http://tga.nig.ac.jp/dnapod/) is an integrated database that stores genome-wide DNA polymorphism datasets acquired under uniform analytical conditions, and this includes uniformity in the quality of the raw data, the reference genome version, and evaluation algorithms. DNApod genotypic data are re-analyzed whole-genome shotgun datasets extracted from sequence read archives, and DNApod distributes genome-wide DNA polymorphism datasets and known-gene annotations for each DNA polymorphism. This new database was developed for storing genome-wide DNA polymorphism datasets of plants, with crops being the first priority. Here, we describe our analyzed data for 679, 404, and 66 strains of rice, maize, and sorghum, respectively. The analytical methods are available as a DNApod workflow in an NGS annotation system of the DNA Data Bank of Japan and a virtual machine image. Furthermore, DNApod provides tables of links of identifiers between DNApod genotypic data and public phenotypic data. To advance the sharing of organism knowledge, DNApod offers basic and ubiquitous functions for multiple alignment and phylogenetic tree construction by using orthologous gene information.

DNA Data Bank of Japan.

The DNA Data Bank of Japan (DDBJ) (http://www.ddbj.nig.ac.jp) has been providing public data services for thirty years (since 1987). We are collecting nucleotide sequence data from researchers as a member of the International Nucleotide Sequence Database Collaboration (INSDC, http://www.insdc.org), in collaboration with the US National Center for Biotechnology Information (NCBI) and European Bioinformatics Institute (EBI). The DDBJ Center also services Japanese Genotype-phenotype Archive (JGA), with the National Bioscience Database Center to collect human-subjected data from Japanese researchers. Here, we report our database activities for INSDC and JGA over the past year, and introduce retrieval and analytical services running on our supercomputer system and their recent modifications. Furthermore, with the Database Center for Life Science, the DDBJ Center improves semantic web technologies to integrate and to share biological data, for providing the RDF version of the sequence data.

CyanoBase: a large-scale update on its 20th anniversary.

The first ever cyanobacterial genome sequence was determined two decades ago and CyanoBase (http://genome.microbedb.jp/cyanobase), the first database for cyanobacteria was simultaneously developed to allow this genomic information to be used more efficiently. Since then, CyanoBase has constantly been extended and has received several updates. Here, we describe a new large-scale update of the database, which coincides with its 20th anniversary. We have expanded the number of cyanobacterial genomic sequences from 39 to 376 species, which consists of 86 complete and 290 draft genomes. We have also optimized the user interface for large genomic data to include the use of semantic web technologies and JBrowse and have extended community-based reannotation resources through the re-annotation of Synechocystis sp. PCC 6803 by the cyanobacterial research community. These updates have markedly improved CyanoBase, providing cyanobacterial genome annotations as references for cyanobacterial research.

Genome sequence and overview of Oligoflexus tunisiensis Shr3T in the eighth class Oligoflexia of the phylum Proteobacteria.

Oligoflexus tunisiensis Shr3T is the first strain described in the newest (eighth) class Oligoflexia of the phylum Proteobacteria. This strain was isolated from the 0.2-µm filtrate of a suspension of sand gravels collected in the Sahara Desert in the Republic of Tunisia. The genome of O. tunisiensis Shr3T is 7,569,109 bp long and consists of one scaffold with a 54.3% G + C content. A total of 6,463 genes were predicted, comprising 6,406 protein-coding and 57 RNA genes. Genome sequence analysis suggested that strain Shr3T had multiple terminal oxidases for aerobic respiration and various transporters, including the resistance-nodulation-cell division-type efflux pumps. Additionally, gene sequences related to the incomplete denitrification pathway lacking the final step to reduce nitrous oxide (N2O) to nitrogen gas (N2) were found in the O. tunisiensis Shr3T genome. The results presented herein provide insight into the metabolic versatility and N2O-producing activity of Oligoflexus species.