Optimized workflow for high-throughput whole genome surveillance of Influenza A virus
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Whole genome sequencing (WGS) is crucial for studying influenza A virus (IAV) genomic diversity in various host species to mitigate its impact on human and animal health. While the multisegment RT-PCR (mRT-PCR) efficiently amplifies all genomic segments in a single reaction, its sensitivity for larger segments is suboptimal. To improve WGS sensitivity, we optimized the mRT-PCR protocol by adjusting RT and PCR cycling conditions, achieving a 1000-fold increase in sensitivity. Additionally, we developed a dual-barcoding approach for the Oxford Nanopore platform, enabling the multiplexing of multiple IAV-positive samples without compromising sensitivity, thereby creating a scalable, high-throughput workflow for IAV surveillance.
