Published June 30, 2025 | Version v1.0.0
Journal article Open

Data and scripts for manuscript Titled: Optimized workflow for high-throughput whole genome surveillance of Influenza A virus

  • 1. Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland
  • 2. Institute for Infectious Diseases, University of Bern, Bern, Switzerland
  • 3. Multidisciplinary Center for Infectious Diseases, University of Bern, Bern, Switzerland
  • 4. Institute of Virology and Immunology IVI, Bern and Mittelhäusern, Switzerland
  • 5. Department of Infectious Diseases and Pathobiology, Vetsuisse Faculty, University of Bern, Bern, Switzerland
  • 6. Institute of Diagnostic Virology, Friedrich-Loeffler-Institut, Greifswald-Insel Riems, Germany
  • 7. Department of Pathogen Evolution, Helmholtz Institute for One Health, Greifswald, Germany
  • 8. European Virus Bioinformatics Center, Jena, Germany

Description

Abstract

Whole genome sequencing (WGS) is essential for characterizing the genetic diversity of influenza A virus (IAV) across host species and mitigating its impact on human and animal health. While multisegment RT-PCR (mRT-PCR) enables the simultaneous amplification of all genomic segments in a single reaction, its sensitivity for larger segments remains suboptimal. To improve WGS sensitivity, we optimized the mRT-PCR protocol by modifying RT and PCR cycling conditions, resulting in improved recovery and representation of all eight IAV genomic segments. Furthermore, we developed a dual-barcoding approach for the Oxford Nanopore platform, allowing for high-throughput multiplexing of IAV-positive samples without compromising sensitivity. The resulting workflow is robust, scalable, and applicable to samples of avian, swine, and human origin, even at low viral loads. This optimized approach provides a practical solution for genomic surveillance at the human–animal interface, supporting early detection, evolutionary monitoring, and rapid identification of zoonotic spillover events. 

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