genomeRxiv: a genome-based identification web server that bridges the gap between taxonomy and strain typing
- 1Virginia Tech
Abstract
Precise identification depends on highly resolved classification. Therefore, whole genome-based strain typing schemes have been implemented for identification of the most important microbial human pathogens. However, there are no dedicated typing schemes for the majority of prokaryotic human, animal, and plant pathogens, or for non-pathogenic microbes, often limiting their identification to taxonomic classification tools that have the species as the smallest unit. To address this deficiency, we created the genomeRxiv web server which contains over 350,000 genomes and leverages the average nucleotide identity (ANI)-based Life Identification Number (LIN) approach, allowing users to identify prokaryotic genomes in real time from approximately genus-rank to near strain-level resolution. LINs are overlaid with circumscriptions of species and infraspecies classes, integrating taxonomy with strain typing. Metadata and distance trees are visualized to complement inferred phylogenetic relationships with epidemiological and ecological information. A command line tool is provided for users to upload k-mer sketches of unpublished genomes and associated metadata, facilitating epidemiological investigations without the need to share complete DNA sequences. In conclusion, genomeRxiv constitutes a much-needed resource for precise, rapid identification of the many prokaryotes not included in any pathogen-specific typing scheme.
Related
- PockFlex: a web server for flexibility-aware binding site identification and prioritisation from structural ensembles
- Genome wide identification and co-expression analysis of the xyloglucan endotransglucosylase/hydrolase gene family in Japanese morning glory
- Genome-Wide Identification of the BhKCS Gene Family in Wax Gourd (Benincasa hispida) and Stress-Responsive Expression of BhKCS8/9/14/15
- Genome-Wide Identification of the Two-Pore Potassium Channel Gene Family in Sugar Beet (Beta vulgaris L.) and Functional Analysis of BvTPK2 in Salt Tolerance
- Exploratory Whole-Genome Profiling of Greek Men with Oligozoospermia: Identification of Candidate Variants, Genes, and Biological Pathways
BibTeX
@misc{vinatzer2026genomerxiv,
title = {{genomeRxiv: a genome-based identification web server that bridges the gap between taxonomy and strain typing}},
author = {B. Vinatzer and R. Mazloom and R. Sharma and J. S. Lorv and S. Kaur and P. Sharma and C. T. Brown and C. T. Brown and N. T. T. Pierce and L. Pritchard and L. S. Heath},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.09.757156},
url = {https://www.biorxiv.org/content/10.64898/2026.10.09.757156v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - genomeRxiv: a genome-based identification web server that bridges the gap between taxonomy and strain typing
AU - B. Vinatzer
AU - R. Mazloom
AU - R. Sharma
AU - J. S. Lorv
AU - S. Kaur
AU - P. Sharma
AU - C. T. Brown
AU - C. T. Brown
AU - N. T. T. Pierce
AU - L. Pritchard
AU - L. S. Heath
PY - 2026
DA - 2026/10/09
PB - bioRxiv
DO - 10.64898/2026.10.09.757156
UR - https://www.biorxiv.org/content/10.64898/2026.10.09.757156v1
AB - Precise identification depends on highly resolved classification. Therefore, whole genome-based strain typing schemes have been implemented for identification of the most important microbial human pathogens. However, there are no dedicated typing schemes for the majority of prokaryotic human, animal, and plant pathogens, or for non-pathogenic microbes, often limiting their identification to taxonomic classification tools that have the species as the smallest unit. To address this deficiency, we created the genomeRxiv web server which contains over 350,000 genomes and leverages the average nucleotide identity (ANI)-based Life Identification Number (LIN) approach, allowing users to identify prokaryotic genomes in real time from approximately genus-rank to near strain-level resolution. LINs are overlaid with circumscriptions of species and infraspecies classes, integrating taxonomy with strain typing. Metadata and distance trees are visualized to complement inferred phylogenetic relationships with epidemiological and ecological information. A command line tool is provided for users to upload k-mer sketches of unpublished genomes and associated metadata, facilitating epidemiological investigations without the need to share complete DNA sequences. In conclusion, genomeRxiv constitutes a much-needed resource for precise, rapid identification of the many prokaryotes not included in any pathogen-specific typing scheme.
ER -