Short-Read and Long-Read Whole Genome Sequencing for SARS-CoV-2 Variants Identification

Genomic surveillance of SARS-CoV-2 is crucial for detecting emerging variants and informing public health responses. Various sequencing technologies are used for whole genome sequencing of SARS-CoV-2. This cross-platform benchmark study applied established bioinformatics tools to assess and improve the performance of Illumina NovaSeq, Oxford Nanopore Technologies MinION, and Pacific Biosciences Sequel II sequencing platforms in identifying SARS-CoV-2 variants and lineage assignment. NovaSeq produced the highest number of reads and bases, depth of coverage, completeness of consensus genomes, stable mapping coverage across open reading frames in the genome, and consistent lineage assignments. The long-read sequencing platforms had lower yields, sequencing depth, and mapping coverage, limiting the number of qualified sequences for lineage assignment and variant identification. However, implementing proper quality controls on sequence data overcame these limitations and achieved consistent SARS-CoV-2 lineage assignments across all three sequencing platforms. The advancements in library preparation and technology for long-read sequencing are likely to enhance sequence quality and expand genome coverage, effectively addressing current limitations in genome analysis. By merging the unique advantages of both short- and long-read methods, we can significantly improve SARS-CoV-2 genomic surveillance and provide insights into sequencing strategies for other RNA viruses, pending further validation. This may lead to precise tracking of viral evolution and support public health policy decisions.