BACKGROUND: Accurate taxonomic classification in genome databases is essential for reliable biological research and effective data sharing. Mislabeling or inaccuracies in genome annotations can lead to incorrect scientific conclusions and hinder the reproducibility of research findings. Despite advances in genome analysis techniques, challenges persist in ensuring precise and reliable taxonomic assignments. Existing tools for genome verification often involve extensive computational resources or lengthy processing times, which can limit their accessibility and scalability for large-scale projects. There is a need for more efficient, user-friendly solutions that can handle diverse datasets and provide accurate results with minimal computational demands. This work aimed to address these challenges by introducing a novel tool that enhances taxonomic accuracy, offers a user-friendly interface, and supports large-scale analyses. RESULTS: We introduce a novel tool for the quality control and taxonomic classification tool of prokaryotic genomes, called DFAST_QC, which is available as both a command-line tool and a web service. DFAST_QC can quickly identify species based on NCBI and GTDB taxonomies by combining genome-distance calculations using MASH with ANI calculations using Skani. We evaluated DFAST_QC's performance in species identification and found it to be highly consistent with existing taxonomic standards, successfully identifying species across diverse datasets. In several cases, DFAST_QC identified potential mislabeling of species names in public databases and highlighted discrepancies in current classifications, demonstrating its capability to uncover errors and enhance taxonomic accuracy. Additionally, the tool's efficient design allows it to operate smoothly on local machines with minimal computational requirements, making it a practical choice for large-scale genome projects. CONCLUSIONS: DFAST_QC is a reliable and efficient tool for accurate taxonomic identification and genome quality control, well-suited for large-scale genomic studies. Its compatibility with limited-resource environments, combined with its user-friendly design, ensures seamless integration into existing workflows. DFAST_QC's ability to refine species assignments in public databases highlights its value as a complementary tool for maintaining and enhancing the accuracy of taxonomic data in genomic research. The web version is available at https://dfast.ddbj.nig.ac.jp/dqc/submit/ , and the source code for local use can be found at https://github.com/nigyta/dfast_qc .

Although current long-read sequencing technologies have a long-read length that facilitates assembly for genome reconstruction, they have high sequence errors. While various assemblers with different perspectives have been developed, no systematic evaluation of assemblers with long reads for diploid genomes with varying heterozygosity has been performed. Here, we evaluated a series of processes, including the estimation of genome characteristics such as genome size and heterozygosity, de novo assembly, polishing, and removal of allelic contigs, using six genomes with various heterozygosity levels. We evaluated five long-read-only assemblers (Canu, Flye, miniasm, NextDenovo and Redbean) and five hybrid assemblers that combine short and long reads (HASLR, MaSuRCA, Platanus-allee, SPAdes and WENGAN) and proposed a concrete guideline for the construction of haplotype representation according to the degree of heterozygosity, followed by polishing and purging haplotigs, using stable and high-performance assemblers: Redbean, Flye and MaSuRCA.

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: [email protected]. Supplementary information: Supplementary data are available at Bioinformatics online.

We used principal component analysis to develop measures (called Z-parameters in this study) which reflect the diversity of codon usage in Escherichia coli genes. Protein production levels for 1500 CDSs (protein-coding sequences) identified by E.coli genome projects in Japan and the US were estimated from a correlation equation between Z1 and cellular protein content obtained through analysis of the genes experimentally characterized. Through the profile analysis of Z1 for E.coli sequences obtained by the Japanese Project, we predicted an additional 36 CDSs that had not been annotated in the International DNA Database. Thirty-one out of the 36 CDSs could be assigned to presumptive protein genes through a BLASTX search for recent protein databases in the Genome Net in Japan. Detailed examination of the Z1-parameter profile led us to assess sequencing errors which cause frame-shift.