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Updated: Nov 26, 2025

Unbiased Deep Sequencing of RNA Viruses from Clinical Samples
Published on: July 2, 2016
MINERVA: A Facile Strategy for SARS-CoV-2 Whole-Genome Deep Sequencing of Clinical Samples
Chen Chen1, Jizhou Li2, Lin Di3
1Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University and Beijing Key Laboratory of Emerging Infectious Diseases, Beijing 100015, China.
Abstract:
Analyzing the genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from clinical samples is crucial for understanding viral spread and evolution as well as for vaccine development. Existing RNA sequencing methods are demanding on user technique and time and, thus, not ideal for time-sensitive clinical samples; these methods are also not optimized for high performance on viral genomes. We developed a facile, practical, and robust approach for metagenomic and deep viral sequencing from clinical samples. We demonstrate the utility of our approach on pharyngeal, sputum, and stool samples collected from coronavirus disease 2019 (COVID-19) patients, successfully obtaining whole metatranscriptomes and complete high-depth, high-coverage SARS-CoV-2 genomes with high yield and robustness. With a shortened hands-on time from sample to virus-enriched sequencing-ready library, this rapid, versatile, and clinic-friendly approach will facilitate molecular epidemiology studies during current and future outbreaks.
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