Enhancing Avian Reovirus control strategies through advanced diagnostics, evolutionary insights, and novel genotyping approaches

Abstract

Avian reovirus (ARV) poses a significant threat to poultry industry, causing economic losses through arthritis/tenosynovitis, necrotizing hepatitis, immunosuppression, and enteric diseases in chickens and turkeys, to name a few. Its ubiquitous nature and genetic variability create both diagnostic and disease control challenges. This dissertation integrates knowledge of veterinary pathology, virology, molecular diagnostics, bioinformatics, epidemiology, and poultry medicine to enhance ARV diagnostic workflows, elucidate its evolutionary dynamics, and develop improved genotyping methods for understanding virus transmission. Here, we first address ARV diagnostic challenges due to its non-specific lesions, ubiquity, and the lack of standardized diagnostic protocols by investigating the relationship between lesion severity and viral RNA levels in suspected ARV cases, utilizing both quantitative real-time reverse-transcriptase polymerase chain reaction (qRT-PCR) and RNAScope in situ hybridization (ISH) for ARV detection and evaluation. The study provided insights into ARV diagnostic interpretation by establishing a link between arthritis/tenosynovitis severity and viral RNA levels with a defined Ct cutoff through ISH integration and highlighting the importance of ISH in poultry tenosynovitis cases to enhance diagnostic workflows alongside histopathology and qRT-PCR across different ancillary testing scenarios. Additionally, this study is the first to identify ARV viral transcripts within synoviocytes and fibroblasts in affected synovium and tenson via ISH, providing new insights into disease pathogenesis and highlighting potential areas for improved diagnostic practices and disease investigation. We then explored viral evolutionary dynamics by reconstructing the phylogenic history of ARV across different host species on a genome segment basis. Temporal phylogenetic analyses identified chickens as the ancestral host across all segments, with cross-species transmission events to the turkey host occurring primarily in the mid-20th century. Transmission was largely unidirectional from chickens to turkeys, other galliform species, and wild birds. The M2, σC, and L3 segments exhibited high nucleotide substitution rates, suggesting selective pressures driving adaptation and antigenic diversity. These findings highlight the complexity of ARV evolution and emphasize the need for robust host-dependent genotyping schemes to monitor viral transmission and mitigate outbreaks in poultry populations. Building on evidence of distinct virus evolution in turkeys compared to chickens, the third study introduced a novel genotyping approach using constellation-based classification to enhance ARV epidemiological surveillance. Prioritizing the M2, σC, and L3 segments for their roles in reassortment and biologically important functions, this large-scale genotyping effort helps address the gap in our knowledge looking at epidemiological links between commercial breeder and meat-type farms, revealing both vertical and horizontal transmission pathways. Reassortment events identified through this genotyping scheme highlight the dynamic nature of ARV evolution and emphasize the need for comprehensive genetic surveillance strategies. This dissertation establishes a foundation for enhanced ARV diagnosis, monitoring, and disease management by refining diagnostic workflows, understanding viral evolution, and developing a genotyping scheme. Additionally, it provides valuable insights into disease pathogenesis, pathogenicity identification, and vaccine development, and offers crucial tools for controlling ARV outbreaks in the poultry industry.