This review by Samuel D. Chorlton addresses ten common issues with reference sequence databases used in metagenomic classification and their potential downstream consequences. The issues include taxonomic errors, inappropriate inclusion and exclusion criteria, sequence content errors, contamination, and more. Each issue is discussed with potential mitigation strategies, such as bioinformatic tools and database curation methods. The review emphasizes the importance of accurate and comprehensive reference sequence databases for reliable metagenomic analysis, particularly in high-stakes applications like clinical metagenomics. It highlights the need for frequent updates and maintenance of databases to keep up with the rapid expansion of sequencing technologies and the identification of new species. The article also discusses the challenges and future trends in improving reference sequence databases, including advancements in taxonomy, long-read sequencing, and artificial intelligence.This review by Samuel D. Chorlton addresses ten common issues with reference sequence databases used in metagenomic classification and their potential downstream consequences. The issues include taxonomic errors, inappropriate inclusion and exclusion criteria, sequence content errors, contamination, and more. Each issue is discussed with potential mitigation strategies, such as bioinformatic tools and database curation methods. The review emphasizes the importance of accurate and comprehensive reference sequence databases for reliable metagenomic analysis, particularly in high-stakes applications like clinical metagenomics. It highlights the need for frequent updates and maintenance of databases to keep up with the rapid expansion of sequencing technologies and the identification of new species. The article also discusses the challenges and future trends in improving reference sequence databases, including advancements in taxonomy, long-read sequencing, and artificial intelligence.