RSV-GenoScan: An automated pipeline for whole-genome human respiratory syncytial virus (RSV) sequence analysis.

BACKGROUND: Advances in high-throughput sequencing (HTS) technologies and reductions in sequencing costs have revolutionised the study of genomics and molecular biology by making whole-genome sequencing (WGS) accessible to many laboratories. However, the analysis of WGS data requires significant computational effort, which is the major drawback in implementing WGS as a routine laboratory technique. OBJECTIVE: Automated pipelines have been developed to overcome this issue, but they do not exist for all organisms. This is the case for human respiratory syncytial virus (RSV), which is a leading cause of lower respiratory tract infections in infants, the elderly, and immunocompromised adults. RESULTS: We present RSV-GenoScan, a fast and easy-to-use pipeline for WGS analysis of RSV generated by HTS on Illumina or Nanopore platforms. RSV-GenoScan automates the WGS analysis steps directly from the raw sequence data. The pipeline filters the sequence data, maps the reads to the RSV reference genomes, generates a consensus sequence, identifies the RSV subgroup, and lists amino acid mutations, insertions and deletions in the F and G viral genes. This enables the rapid identification of mutations in these coding genes that are known to confer resistance to monoclonal antibodies. AVAILABILITY: RSV-GenoScan is freely available at https://github.com/AlexandreD-bio/RSV-GenoScan.

BA.2.86 variant emergence and spread dynamics through wastewater monitoring in Paris, France.

Numerous SARS-CoV-2 variants are emerging as the epidemic continues, inducing new waves of contamination. In July 2023, a new variant named BA.2.86 was identified, raising concerns about its potential for viral escape, even in an immune population. The reduction in patient-centered testing and the identification of variants by sequencing means that we are now blind to the spread of this new variant. The aim of this study was to track the signature of this variant in wastewater in Paris, France. This variant showed a very rapid spread, highly correlated with national flash studies involving sequencing of clinical samples, but with a moderate impact on virus circulation. This easy-to-implement approach enabled us to monitor the emergence and spread of this new variant in real time at low cost.

Higher Levels of SARS-CoV-2 Genetic Variation in Immunocompromised Patients: A Retrospective Case-Control Study.

BACKGROUND: A severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection lasts longer in immunocompromised hosts than in immunocompetent patients. Prolonged infection is associated with a higher probability of selection for novel SARS-CoV-2 mutations, particularly in the spike protein, a critical target for vaccines and therapeutics. METHODS: From December 2020 to September 2022, respiratory samples from 444 immunocompromised patients and 234 health care workers positive for SARS-CoV-2, diagnosed at 2 hospitals in Paris, France, were analyzed using whole-genome sequencing using Nanopore technology. Custom scripts were developed to assess the SARS-CoV-2 genetic diversity between the 2 groups and within the host. RESULTS: Most infections were SARS-CoV-2 Delta or Omicron lineages. Viral genetic diversity was significantly higher in infections of immunocompromised patients than those of controls. Minor mutations were identified in viruses sequenced from immunocompromised individuals, which became signature mutations for newer SARS-CoV-2 variants as the epidemic progressed. Two patients were coinfected with Delta and Omicron variants. The follow-up of immunocompromised patients revealed that the SARS-CoV-2 genome evolution differed in the upper and lower respiratory tracts. CONCLUSIONS: This study found that SARS-CoV-2 infection in immunocompromised patients is associated with higher genetic diversity, which could lead to the emergence of new SARS-CoV-2 variants with possible immune evasion or different virulence characteristics.

Oxford Nanopore and Bionano Genomics technologies evaluation for plant structural variation detection.

BACKGROUND: Structural Variations (SVs) are genomic rearrangements derived from duplication, deletion, insertion, inversion, and translocation events. In the past, SVs detection was limited to cytological approaches, then to Next-Generation Sequencing (NGS) short reads and partitioned assemblies. Nowadays, technologies such as DNA long read sequencing and optical mapping have revolutionized the understanding of SVs in genomes, due to the enhancement of the power of SVs detection. This study aims to investigate performance of two techniques, 1) long-read sequencing obtained with the MinION device (Oxford Nanopore Technologies) and 2) optical mapping obtained with Saphyr device (Bionano Genomics) to detect and characterize SVs in the genomes of the two ecotypes of Arabidopsis thaliana, Columbia-0 (Col-0) and Landsberg erecta 1 (Ler-1). RESULTS: We described the SVs detected from the alignment of the best ONT assembly and DLE-1 optical maps of A. thaliana Ler-1 against the public reference genome Col-0 TAIR10.1. After filtering (SV > 1 kb), 1184 and 591 Ler-1 SVs were retained from ONT and Bionano technologies respectively. A total of 948 Ler-1 ONT SVs (80.1%) corresponded to 563 Bionano SVs (95.3%) leading to 563 common locations. The specific locations were scrutinized to assess improvement in SV detection by either technology. The ONT SVs were mostly detected near TE and gene features, and resistance genes seemed particularly impacted. CONCLUSIONS: Structural variations linked to ONT sequencing error were removed and false positives limited, with high quality Bionano SVs being conserved. When compared with the Col-0 TAIR10.1 reference genome, most of the detected SVs discovered by both technologies were found in the same locations. ONT assembly sequence leads to more specific SVs than Bionano one, the latter being more efficient to characterize large SVs. Even if both technologies are complementary approaches, ONT data appears to be more adapted to large scale populations studies, while Bionano performs better in improving assembly and describing specificity of a genome compared to a reference.