Work

K-FluDB: a novel K-mer-based database for enhanced genomic surveillance of Influenza A viruses

Year: 2025

Type: article

Abstract: Motivation: Influenza A viruses frequently cause seasonal outbreaks and pandemics due to their genetic diversity and reassortment potential. Existing genomic surveillance tools face challenges with redundant databases, delaying subtype identification and obscuring reassortment dynamics. K-FluDB, a novel k-mer-based database, addresses these issues by enhancing subtype identification, capturing genomic diversity, and assisting in the detection of reassortment events critical for understanding viral evolution and improving outbreak proactive measures. Results: K-FluDB provides a comprehensive pangenome for Influenza A, including complete and subtype-specific subsequences from 50 subtype combinations across all 18 hemagglutinin (HA) and 11 neuraminidase (NA) subtypes. Achieving 99.64% compression, K-FluDB eliminates redundancy while preserving essential information. Validation with real-world datasets showed high recovery indices (up to 96.24%) and correct subtype prediction ratios (exceeding 99% for HA and NA). K-FluDB also assists in the detection of reassortment events. Availability and implementation: Three versions of K-FluDB, optimized for read lengths of 75, 150, and 300 nucleotides, are freely available at https://zenodo.org/records/17203072, and the source code is available at https://github.com/usjunco/pangen.

Source: Bioinformatics Advances

DOI: 10.1093/bioadv/vbaf254

Authors: Alejandro Uscanga Junco, Lorena Díaz-González, Blanca Taboada

Institutions: Universidad Autónoma del Estado de Morelos, Universidad Nacional Autónoma de México

Language: English

Topic: Influenza Virus Research Studies

Subfield: Epidemiology

Field: Medicine

Domain: Health Sciences

Open Access status: gold

Estimated APC paid: $2,726

Funder: Universidad Nacional Autónoma de México