Abstract
With the rapid advancements in genome sequencing technologies, microbial genome data has exponentially increased, making it essential to continuously update dataset for accurate microbial identification and classification. We present the development of Microbial Identification using rRNA Operon Region (MIrROR) release 02, an expanded dataset based on 1,690,470 genomes (1,674,514 bacterial and 15,956 archaeal) sourced from NCBI. The final curated dataset covers 476,579 sequences, 249,907 genomes, and 29,051 species, representing increases of 387.39%, 472.49%, and 206.28% over the previous release. Key updates include the addition of archaeal genomes and taxonomy reclassification based on GTDB R220. Extensive curation was performed, including filtering operon lengths (3,500–7,000 bp), removing duplicate sequences, eliminating sequences with ambiguous nucleotides, and clustering of sequences at 99% identity to remove redundancies. The updated dataset showed improved performance in microbial mock community analyses, supporting its accuracy and reliability. These improvements make MIrROR release 02 a valuable resource for microbial profiling and various microbiological research applications.
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Data availability
All data supporting the findings of this study are publicly available. The MIrROR release 02 dataset can be accessed at https://doi.org/10.5281/zenodo.17639192. Sequencing datasets used for performance evaluation, including the ZymoBIOMICS microbial community standards, are available from the NCBI Sequence Read Archive under accession numbers SRR35709965–SRR35709957.
Code availability
Genome retrieval from NCBI GenBank using ncbi-genome-download (v.0.3.1)
ncbi-genome-download archaea -s genbank -F fasta -l all -o {output_directory} --flat-output
ncbi-genome-download bacteria -s genbank -F fasta -l all -o {output_directory}
Clustering using MeShClust (v.3.0)
meshclust3 -d {input_fasta} -o {output_fasta} -t 0.99 -c 50 -r n -e y
Redundancy filtering BLAST (v.2.15.0)
blastn -db {blast_database} -query {input_fasta} -out {output_xml} -outfmt 5 -num_threads{num_threads}
Simulation of long-read sequencing using NanoSim (v.3.2.2)
simulator.py metagenome -gl {genome_list.tsv} -a {abundance.tsv} -c {training_directory} -o{output_directory} --fastq
primersearch (EMBOSS v.6.6.0.0)
primersearch -seqall {input.fasta} -infile {primers.txt} -outfile {output.txt} -mismatchpercent 30
Sequence mapping and taxonomic profiling (with threshold options modified as described in the main text):
https://github.com/seoldh/MIrROR
Custom Python scripts used for dataset curation are available at:
https://github.com/jisoll/MirrorMaker
Custom Python scripts used for in silico primer binding analysis are available at: https://github.com/jisoll/MirrorPrimerChecker
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Acknowledgements
We thank eGnome, Inc. for providing financial and technical support for this study.
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Jisol Lee conceptualized the study, collected and curated the data, evaluated the dataset, developed the website, and wrote the manuscript. Juyong Hong contributed to data curation and manuscript writing. Donghyeok Seol provided the foundational concept for the dataset, gave feedback on data curation, and assisted with manuscript revision. Wonseok Lee contributed to study design. Junho Lee performed the mock community experiment and contributed to manuscript writing. Gyungbu Kim contributed to website development. Seoae Cho contributed to study design and acquired funding. Heebal Kim supervised the study and contributed to manuscript writing. Seoae Cho and Heebal Kim are the corresponding authors.
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The authors declare no competing interests. The study was conducted independently, and the funding organization had no role in the study design, data collection, analysis, or interpretation.
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Lee, J., Hong, J., Seol, D. et al. MIrROR release 02: Expanded and refined 16S-ITS-23S rRNA operon dataset. Sci Data (2026). https://doi.org/10.1038/s41597-026-06729-y
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DOI: https://doi.org/10.1038/s41597-026-06729-y
