CHARACTERIZING THE GENETIC LANDSCAPE OF BLUETONGUE VIRUS (BTV) ACROSS DIVERSE HOSTS AND REGIONS

Abstract

Bluetongue virus (BTV) is an arthropod-borne virus (arbovirus) that infects domestic and wild ruminants and is of major veterinary concern. Infection can result in a range of clinical outcomes, from subclinical to severe disease and death, varying by both host species and viral strain. BTV is a member of the genus Orbivirus and possesses a double-stranded RNA genome consisting of 10 segments. In addition to known mechanisms of RNA virus evolution, segmented genomes also enable reassortment. Reassortment is the process of coinfecting parental viruses exchange genome segments to produce genetically distinct progeny. Currently, 29 distinct serotypes of BTV have been identified, distinguished by neutralizing antibodies against the outer capsid protein encoded by segment 2. However, the frequency of reassortment complicates classification based on a single segment and limits our ability to fully resolve evolutionary histories among isolates. Whole genome sequencing (WGS) offers a comprehensive approach for characterizing genetic diversity across all genome segments. Capturing genome-wide variation allows for improved resolution of reassortment patterns and evolutionary relationships. My dissertation research aimed to further investigate BTV evolution by applying NGS-based methods to better characterize its complex evolutionary history.My first aim developed standardized laboratory and analytical workflows for generating high-quality whole genome consensus sequences for orbiviruses. The laboratory workflows reduced processing time and minimized the number of treatments performed prior to NGS library preparation. In parallel, the bioinformatic pipeline, OrbiSeq, was designed to be reproducible, user-friendly, and scalable for large datasets of short- or long-read sequence data. While the pipeline includes premade reference sequences for specific Orbiviruses, it can be used for other types of viruses with any number of segments. Together, these approaches provide a streamlined system for whole genome characterization that can be used for years to come. These methods were also carried into subsequent studies, where they were applied to investigate the evolutionary dynamics of the BTV genome and its association with clinical outcomes. Using the methods developed in the first aim, I generated novel sequences and integrated them with existing data to curate a large dataset of whole BTV genomes used to investigate the drivers of BTV evolution in the Americas. Rather than relying on single-segment serotype designations, I applied a genome-wide classification approach to enable a more comprehensive understanding of the viral diversity present. Combined with phylogenetic analysis, this framework added clarity to individual viral isolate evolutionary histories, including segments with greater diversity. Coevolutionary relationships and patterns of viral movement across regions differed among segments, indicating that certain segments drive both diversity and movement throughout the Americas. Identifying the segments that co-evolve and drive movement could enable improved classification, anticipation of viral evolution, and development of monitoring and mitigation strategies. My third aim further examined the BTV genome to investigate associations between viral genotype and clinical outcomes in the host. I generated a dataset of BTV sequences from infected animals with differential clinical outcomes and analyzed it using phylogenetic and statistical approaches. Analysis revealed multiple segments that showed clear distinction between the sequences from animals experiencing subclinical infection and overt clinical disease. Within those segments, I identified multiple candidate amino acid substitutions that may contribute to different clinical outcomes. These findings provide a foundation for clarifying viral determinants of disease severity. Identifying high-risk variants and the segments most strongly associated with poor clinical outcomes could improve outbreak forecasting and enable a more precise, segment focused classification system for BTV. Collectively, the findings presented in my dissertation highlight that BTV evolution is largely shaped by reassortment, with certain genome segments playing key roles in driving viral diversity, movement, and differential phenotypic outcomes. Additionally, the experimental and computational workflows I developed provide a system for largescale analysis that can be applied many years into the future. Together, these insights and resources can inform more precise classification, surveillance, and mitigation strategies to protect animal health.