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The genomes of eukaryotes are punctuated by long stretches of sequence which do not code for proteins or RNAs. Although some of these regions do contain crucial regulatory sequences, the vast majority of this DNA serves no known function. Typically, these regions of the genome are the ones in which the fastest change, in evolutionary terms, is observed, because there is typically little to no selection pressure acting on these regions to preserve their sequences.
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Updated: Apr 13, 2026

Multi-locus Variable-number Tandem-repeat Analysis of the Fish-pathogenic Bacterium Yersinia ruckeri by Multiplex PCR and Capillary Electrophoresis
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HVRLocator: a computationally efficient tool for identifying hypervariable regions in large 16S rRNA datasets.

Clara Arboleda-Baena1,2, Felipe Borim Correa2, Joao Pedro Saraiva2

  • 1German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig,  Puschstraße 4, 04103 Leipzig, Germany.

Gigascience
|April 11, 2026
PubMed
Summary
This summary is machine-generated.

HVRLocator accurately identifies 16S rRNA gene regions and primers in metabarcoding data. This tool enhances microbial diversity studies by improving data curation and enabling reliable cross-study comparisons.

Keywords:
16S rRNA genebig datahigh throughput sequencingmetabarcodingmetadatamicrobial ecology

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Area of Science:

  • Microbiology
  • Bioinformatics
  • Genomics

Background:

  • 16S rRNA gene metabarcoding is a cost-effective method for microbial diversity assessment.
  • Public datasets often lack standardized metadata, hindering accurate data reuse.
  • Critical metadata includes sequenced hypervariable regions and primers used.

Purpose of the Study:

  • Introduce HVRLocator, a computational tool for analyzing 16S rRNA metabarcoding data.
  • Address the challenge of missing or unreliable metadata in public sequence archives.
  • Enable accurate curation and large-scale processing of 16S rRNA data.

Main Methods:

  • HVRLocator identifies 16S rRNA amplicon start/end positions.
  • The tool determines corresponding hypervariable regions.
  • It detects the presence of primer sequences within the data.

Main Results:

  • HVRLocator processes archived sequences at 6.5 samples/minute.
  • It accurately detects amplicon positions and hypervariable regions across diverse datasets.
  • The tool flags misannotated metadata and problematic sequences, aiding data curation.

Conclusions:

  • HVRLocator overcomes metadata limitations in 16S rRNA studies.
  • Accurate identification of amplicon regions and primers ensures reliable data processing.
  • Enables reproducible microbial studies, syntheses, and meta-analyses.