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This study presents accessible microbial genomic and proteomic databases, significantly reducing data size for researchers. These resources aid in analyzing microbial genomics and understanding species relationships.

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Area of Science:

  • Bioinformatics
  • Genomics
  • Microbiology

Background:

  • Genomic, metagenomic, and proteomic data analysis is crucial in biology and medicine.
  • Raw data from repositories demands substantial computing power and storage.
  • Accessible reference databases are needed for the scientific community.

Purpose of the Study:

  • To provide a comprehensive, accessible set of microbial genomic and proteomic reference databases.
  • To demonstrate the advantages and usefulness of these reduced-representation databases.
  • To present a case study on genomic coherence within the Brucellacea family.

Main Methods:

  • Collected genomes, proteomes, and metagenomes from NCBI Assembly and GTDB for Bacteria, Archaea, Virus, and Fungi.
  • Utilized the MinHash algorithm in Mash software to create reduced representations (sketched databases).
  • Filtered data for accessibility and usability with limited computational resources.

Main Results:

  • Reduced a 133 GB dataset to 883.25 MB, containing 125,110 records.
  • Demonstrated genomic coherence suggesting two Brucellacea members belong to the same genomospecies.
  • Created user-friendly databases for diverse microbial groups.

Conclusions:

  • The sketched databases offer a practical solution for researchers with limited computational resources.
  • These databases facilitate microbial species delimitation, genomic distance estimation, and comparative analyses.
  • The study highlights the utility of compressed genomic data for ecological and evolutionary research.