SARS-CoV-2 Co-Infections and Recombinations Identified by Long-Read Single-Molecule Real-Time Sequencing.

Co-infection with at least 2 strains of virus is the prerequisite for recombination, one of the means of genetic diversification. Little is known about the prevalence of these events in SARS-CoV-2, partly because it is difficult to detect them. We used long-read PacBio single-molecule real-time (SMRT) sequencing technology to sequence whole genomes and targeted regions for haplotyping. We identified 17 co-infections with SARS-CoV-2 strains belonging to different clades in 6829 samples sequenced between January and October, 2022 (prevalence 0.25%). There were 3 Delta/Omicron co-infections and 14 Omicron/Omicron co-infections (4 cases of 21K/21L, 1 case of 21L/22A, 2 cases of 21L/22B, 4 cases of 22A/22B, 2 cases of 22B/22C and 1 case of 22B/22E). Four of these patients (24%) also harbored recombinant minor haplotypes, including one with a recombinant virus that was selected in the viral quasispecies over the course of his chronic infection. While co-infections remain rare among SARS-CoV-2-infected individuals, long-read SMRT sequencing is a useful tool for detecting them as well as recombinant events, providing the basis for assessing their clinical impact, and a precise indicator of epidemic evolution. IMPORTANCE SARS-CoV-2 variants have been responsible for the successive waves of infection over the 3 years of pandemic. While co-infection followed by recombination is one driver of virus evolution, there have been few reports of co-infections, mainly between Delta and Omicron variants or between the first 2 Omicron variants 21K_BA.1 and 21L_BA.2. The 17 co-infections we detected during 2022 included cases with the recent clades of Omicron 22A, 22B, 22C, and 22E; 24% harbored recombinant variants. This study shows that long-read SMRT sequencing is well suited to SARS-CoV-2 genomic surveillance.

A Multiplexed, Tiled PCR Method for Rapid Whole-Genome Sequencing of Infectious Spleen and Kidney Necrosis Virus (ISKNV) in Tilapia.

Tilapia farming is one of the most important sectors in aquaculture worldwide and of major importance to global food security. Infectious spleen and kidney necrosis virus (ISKNV) has been identified as an agent of high morbidity and mortality, threatening tilapia aquaculture. ISKNV was detected in Lake Volta, Ghana, in September 2018 and spread rapidly, with mortality rates between 60 and 90% and losses of more than 10 tonnes of fish per day. Understanding the spread and evolution of viral pathogens is important for control strategies. Here, we developed a tiled-PCR sequencing approach for the whole-genome sequencing of ISKNV, using long read sequencing to enable field-based, real-time genomic surveillance. This work represents the first use of tiled-PCR for whole genome recovery of viruses in aquaculture, with the longest genome target (>110 kb dsDNA) to date. Our protocol was applied to field samples collected from the ISKNV outbreaks from four intensive tilapia cage culture systems across Lake Volta, between October 2018 and May 2022. Despite the low mutation rate of dsDNA viruses, 20 single nucleotide polymorphisms accumulated during the sampling period. Droplet digital PCR identified a minimum requirement of template in a sample to recover 50% of an ISKNV genome at 275 femtograms (2410 viral templates per 5 µL sequencing reaction). Overall, tiled-PCR sequencing of ISKNV provides an informative tool to assist in disease control in aquaculture.

Whole-genome single molecule real-time sequencing of SARS-CoV-2 Omicron.

New variants and genetic mutations of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome can only be identified using accurate sequencing methods. Single molecule real-time (SMRT) sequencing has been used to characterize Alpha and Delta variants, but not Omicron variants harboring numerous mutations in the SARS-CoV-2 genome. This study assesses the performance of a target capture SMRT sequencing protocol for whole genome sequencing (WGS) of SARS-CoV-2 Omicron variants and compared it to that of an amplicon SMRT sequencing protocol optimized for Omicron variants. The failure rate of the target capture protocol (6%) was lower than that of the amplicon protocol (34%, p < 0.001) on our data set, and the median genome coverage with the target capture protocol (98.6% [interquartile range (IQR): 86-99.4]) was greater than that with the amplicon protocol (76.6% [IQR: 66-89.6], [p < 0.001]). The percentages of samples with >95% whole genome coverage were 64% with the target capture protocol and 19% with the amplicon protocol (p < 0.05). The clades of 96 samples determined with both protocols were 93% concordant and the lineages of 59 samples were 100% concordant. Thus, target capture SMRT sequencing appears to be an efficient method for WGS, genotyping and detecting mutations of SARS-CoV-2 Omicron variants.

Whole-genome sequencing of SARS-CoV-2: Comparison of target capture and amplicon single molecule real-time sequencing protocols.

Fast, accurate sequencing methods are needed to identify new variants and genetic mutations of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome. Single-molecule real-time (SMRT) Pacific Biosciences (PacBio) provides long, highly accurate sequences by circular consensus reads. This study compares the performance of a target capture SMRT PacBio protocol for whole-genome sequencing (WGS) of SARS-CoV-2 to that of an amplicon PacBio SMRT sequencing protocol. The median genome coverage was higher (p < 0.05) with the target capture protocol (99.3% [interquartile range, IQR: 96.3-99.5]) than with the amplicon protocol (99.3% [IQR: 69.9-99.3]). The clades of 65 samples determined with both protocols were 100% concordant. After adjusting for Ct values, S gene coverage was higher with the target capture protocol than with the amplicon protocol. After stratification on Ct values, higher S gene coverage with the target capture protocol was observed only for samples with Ct > 17 (p < 0.01). PacBio SMRT sequencing protocols appear to be suitable for WGS, genotyping, and detecting mutations of SARS-CoV-2.

High temporal resolution Nanopore sequencing dataset of SARS-CoV-2 and host cell RNAs.

BACKGROUND: Recent studies have disclosed the genome, transcriptome, and epigenetic compositions of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the effect of viral infection on gene expression of the host cells. It has been demonstrated that, besides the major canonical transcripts, the viral genome also codes for noncanonical RNA molecules. While the structural characterizations have revealed a detailed transcriptomic architecture of the virus, the kinetic studies provided poor and often misleading results on the dynamics of both the viral and host transcripts due to the low temporal resolution of the infection event and the low virus/cell ratio (multiplicity of infection [MOI] = 0.1) applied for the infection. It has never been tested whether the alteration in the host gene expressions is caused by aging of the cells or by the viral infection. FINDINGS: In this study, we used Oxford Nanopore's direct cDNA and direct RNA sequencing methods for the generation of a high-coverage, high temporal resolution transcriptomic dataset of SARS-CoV-2 and of the primate host cells, using a high infection titer (MOI = 5). Sixteen sampling time points ranging from 1 to 96 hours with a varying time resolution and 3 biological replicates were used in the experiment. In addition, for each infected sample, corresponding noninfected samples were employed. The raw reads were mapped to the viral and to the host reference genomes, resulting in 49,661,499 mapped reads (54,62 Gbs). The genome of the viral isolate was also sequenced and phylogenetically classified. CONCLUSIONS: This dataset can serve as a valuable resource for profiling the SARS-CoV-2 transcriptome dynamics, the virus-host interactions, and the RNA base modifications. Comparison of expression profiles of the host gene in the virally infected and in noninfected cells at different time points allows making a distinction between the effect of the aging of cells in culture and the viral infection. These data can provide useful information for potential novel gene annotations and can also be used for studying the currently available bioinformatics pipelines.