GSR-DB: a manually curated and optimized taxonomical database for 16S rRNA amplicon analysis

• DOI: 10.1128/msystems.00950-23
• Publication Date: 2024-01-08T14:01:04Z
• Authors: Leidy-Alejandra G...; Sara Vega-Abellaneda; Chaysavanh Manichanh
• Keywords: Databases, Factual; CIENCIA DE LA INFORMACIÓN::Ciencias de la información::clasificación; CHEMICALS AND DRUGS::Nucleic Acids, Nucleotides, and Nucleosides::Nucleic Acids::RNA::RNA, Ribosomal; microbiome; FENÓMENOS Y PROCESOS::fenómenos biológicos::fenómenos ecológicos y ambientales::ambiente::ecosistema::biodiversidad::biota::microbiota; Microbiology; Bases de dades; Database; taxonomy; RNA, Ribosomal, 16S; INFORMATION SCIENCE::Information Science::Informatics::Medical Informatics::Medical Informatics Applications::Information Systems::Databases as Topic::Databases, Factual; Intestins - Microbiologia; INFORMATION SCIENCE::Information Science::Classification; 16S rRNA; PHENOMENA AND PROCESSES::Biological Phenomena::Ecological and Environmental Phenomena::Environment::Ecosystem::Biodiversity::Biota::Microbiota; database; Taxonomy; Bacteria; Microbiota; Archaea; QR1-502; CIENCIA DE LA INFORMACIÓN::Ciencias de la información::informática::informática médica::aplicaciones de la informática médica::sistemas de información::bases de datos como asunto::bases de datos factuales; Microbiome; COMPUESTOS QUÍMICOS Y DROGAS::nucleótidos y nucleósidos de ácidos nucleicos::ácidos nucleicos::ARN::ARN ribosómico; Ribosomes; Research Article

Taxonomic assignments of microorganisms have long been hindered by inconsistent nomenclature and annotation issues in existing databases like SILVA, Greengenes, Greengenes2, Genome Taxonomy Database, or Ribosomal Database Project. To overcome these issues, we created Greengenes-SILVA-RDP database (GSR-DB), accurate and comprehensive taxonomic annotations of 16S amplicon data. Unlike previous approaches, our innovative pipeline includes a unique taxonomy unification step, ensuring consistent and reliable annotations. Our evaluation analyses showed that GSR-DB outperforms existing databases in providing species-level resolution, especially based on mock-community analysis, making it a game-changer for microbiome studies. Moreover, GSR-DB is designed to be accessible to researchers with limited computational resources, making it a powerful tool for scientists across the board. Available for full-length 16S sequences and commonly used hypervariable regions, including V4, V1–V3, V3–V4, and V3–V5, GSR-DB is a go-to database for robust and accurate microbial taxonomy analysis.