Genomic surveillance of SARS-CoV-2 variants using pooled WGS.

ABSTRACT: This study presents the development and validation of a genomic surveillance strategy using Whole Genome Sequencing (WGS) on normalized pooled samples to detect and monitor SARS-CoV-2 variants. A bioinformatics pipeline was designed specifically for analyzing pooled WGS data and was validated using simulated datasets, pooled samples of reference materials, and pooled clinical samples collected during key periods of the Delta and Omicron variant emergence. The approach was evaluated for its accuracy in estimating variant abundance at both the Phylogenetic Assignment of Named Global Outbreak (PANGO) lineage level and the World Health Organization (WHO) variant level. From the simulation datasets, the method achieved an overall sensitivity of 99.1% and a positive predictive value (PPV) of 99.

SUBMITTER: Park I 

PROVIDER: S-EPMC12015266 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature