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SARS-CoV-2 Genome Sequencing Methods Differ in Their Abilities To Detect Variants from Low-Viral-Load Samples

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic surveillance has been vital in understanding the spread of coronavirus disease 2019 (COVID-19), the emergence of viral escape mutants, and variants of concern. However, low viral loads in clinical specimens affect variant calling f...

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Detalles Bibliográficos
Autores principales: Lam, C., Gray, K., Gall, M., Sadsad, R., Arnott, A., Johnson-Mackinnon, J., Fong, W., Basile, K., Kok, J., Dwyer, D. E., Sintchenko, V., Rockett, R. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8525559/
https://www.ncbi.nlm.nih.gov/pubmed/34379527
http://dx.doi.org/10.1128/JCM.01046-21
Descripción
Sumario:Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic surveillance has been vital in understanding the spread of coronavirus disease 2019 (COVID-19), the emergence of viral escape mutants, and variants of concern. However, low viral loads in clinical specimens affect variant calling for phylogenetic analyses and detection of low-frequency variants, important in uncovering infection transmission chains. We systematically evaluated three widely adopted SARS-CoV-2 whole-genome sequencing methods for their sensitivity, specificity, and ability to reliably detect low-frequency variants. Our analyses reveal that the ARTIC v3 protocol consistently displays high sensitivity for generating complete genomes at low viral loads compared with the probe-based Illumina Respiratory Viral Oligo panel and a pooled long-amplicon method. We show substantial variability in the number and location of low-frequency variants detected using the three methods, highlighting the importance of selecting appropriate methods to obtain high-quality sequence data from low-viral-load samples for public health and genomic surveillance purposes.