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

Area of Science:

• Virology
• Genomics
• Epidemiology

Background:

• Genomic surveillance of SARS-CoV-2 is essential for tracking COVID-19, identifying variants, and understanding transmission.
• Low viral loads in clinical samples challenge the accurate detection of variants and low-frequency mutations.

Purpose of the Study:

• To systematically evaluate the sensitivity, specificity, and low-frequency variant detection capabilities of three common SARS-CoV-2 whole-genome sequencing methods.
• To determine the optimal sequencing strategy for analyzing samples with low viral loads.

Main Methods:

• Comparative analysis of three SARS-CoV-2 whole-genome sequencing protocols: ARTIC v3, Illumina Respiratory Viral Oligo panel, and a pooled long-amplicon method.
• Evaluation of sensitivity, specificity, and detection of low-frequency variants using clinical specimens with varying viral loads.

Main Results:

• The ARTIC v3 protocol demonstrated superior sensitivity in generating complete SARS-CoV-2 genomes from low-viral-load samples compared to the other two methods.
• Significant variability was observed in the number and location of low-frequency variants detected across the three methods.
• ARTIC v3 showed higher consistency in detecting variants at low viral loads.

Conclusions:

• The ARTIC v3 method is recommended for robust SARS-CoV-2 genomic surveillance, particularly in samples with low viral loads.
• Method selection significantly impacts the quality of sequence data and the ability to detect low-frequency variants, crucial for public health.
• Optimized sequencing strategies are vital for accurate phylogenetic analyses and uncovering transmission chains.