SEQUENCING PROTOCOL AND BIOINFORMATICS PIPELINE FOR THE AVIAN INFLUENZA VIRUS

Abstract

The avian influenza virus (AIV), traditionally confined to avian hosts, has recently been detected in various mammal species, raising significant concerns for both animal and public health, necessitating efficient and accurate methods for virus detection and characterization. This study presents a sequencing protocol combined with a comprehensive bioinformatics pipeline designed for the sequencing and analysis of AIV genomes. The presented streamlined approach encompasses whole genome PCR-amplification of the viral genome, enabling the genome characterization and detection of viral mutations with high precision. An amplicon-based MiniSeq sequencing workflow based on a set of PCR primers targeting all genome segments was developed. Three samples from H5 high pathogenic avian influenza (HPAI) outbreaks in Serbia were sequenced using the MiniSeq platform. The protocol involves optimized sample preparation, tailored specifically for AIV, library preparation and sequencing. This is complemented by a robust bioinformatics pipeline that includes quality control, read mapping, consensus genome generation, subtyping and pathotyping, as well as statistical sequencing data. The pipeline efficiently processes raw sequencing data, ensuring high-quality genome assemblies and accurate identification of viral strains. The protocol was used on AIV samples from various avian species, demonstrating its applicability and reliability. The results highlight the protocol’s capability to generate comprehensive genomic data, which is crucial for monitoring viral evolution and informing public health interventions. The described integrated approach offers a powerful tool for AIV surveillance and research, facilitating timely and informed decision-making in response to avian influenza outbreaks. This protocol can be readily adapted for use in various laboratory settings, contributing to global efforts in combating avian influenza and enhancing our understanding of its genomic landscape.

Keywords

• avian influenza
• high-throughput sequencing
• bioinformatics
• viral genomics
• molecular characterization