Identification of the main genetic clusters of avian reoviruses from a global strain collection

Front Vet Sci. 2023 Jan 12:9:1094761. doi: 10.3389/fvets.2022.1094761. eCollection 2022.

Abstract

Introduction: Avian reoviruses (ARV), an important pathogen of poultry, have received increasing interest lately due to their widespread occurrence, recognized genetic diversity, and association to defined disease conditions or being present as co-infecting agents. The efficient control measures require the characterization of the available virus strains.

Methods: The present study describes an ARV collection comprising over 200 isolates from diagnostic samples collected over a decade from 34 countries worldwide. One hundred and thirty-six ARV isolates were characterized based on σC sequences.

Results and discussion: The samples represented not only arthritis/tenosynovitis and runting-stunting syndrome, but also respiratory symptoms, egg production problems, and undefined disease conditions accompanied with increased mortality, and were obtained from broiler, layer or breeder flocks. In 31 percent of the cases other viral or bacterial agents were demonstrated besides ARV. The most frequent co-infectious agent was infectious bronchitis virus followed by infectious bursal disease virus and adenoviruses. All isolates could be classified in one of the major genetic clusters, although we observed marked discrepancies in the genotyping systems currently in use, a finding that made genotype assignment challenging. Reovirus related clinical symptoms could not be unequivocally connected to any particular virus strains belonging to a specific genetic group, suggesting the lack of strict association between disease forms of ARV infection and the investigated genetic features of ARV strains. Also, large genetic differences were seen between field and vaccine strains. The presented findings reinforce the need to establish a uniform, widely accepted molecular classification scheme for ARV and further, highlight the need for ARV strain identification to support more efficient control measures.

Keywords: avian reovirus; co-infection; collection; diversity; global.