Genetic analysis of the rabies virus

Durrant, Rowan (2025) Genetic analysis of the rabies virus. PhD thesis, University of Glasgow.

Abstract

Rabies is a fatal disease caused by a negative-strand RNA virus with a genome size of approximately 12 kilobases. Rabies kills an estimated 60,000 people per year, most of whom would have been bitten by a rabid domestic dog. In recent years whole genome sequencing of the rabies virus has become more accessible through the development of portable sequencing technologies and inexpensive protocols, which has led to an increase in the amount of publicly available genomic data, and in the capacity to rapidly acquire sequence data from new rabies outbreaks. In this thesis I aim to use rabies genomic and genetic data to investigate how rabies evolves, and how to best use this data to meet the global goal of achieving zero human rabies deaths by 2030. I developed a simulation framework consisting of an existing branching process epidemiological model and a novel mutation model to generate synthetic rabies sequences associated with known underlying transmission dynamics. In chapter 2 I used this framework to investigate whether the lack of temporal signal required to conduct Bayesian phylogenetic analyses on rabies sequence/added datasets could be due to rabies’ variable incubation period lengths. I found that at substitution rates comparable to rabies’, it is not possible to distinguish root-to-tip divergence plots for synthetic genomes generated using a per-unit time or pergeneration model of substitution; it is possible, however, at rates more representative of other RNA viruses, due to distinctive “ridges” that form under the per-generation model after unusually long or short incubation periods. I conclude that rabies’ slow evolution is more likely to be the cause of the lack of temporal signal than its variable incubation periods, but that thinking about evolution on a per-generation scale could be useful in certain contexts. Existing methods of estimating outbreak sizes, such as serological surveys and randomised testing, are unsuitable for estimating rabies outbreak sizes due to the fatality of the virus and the testing method respectively. In chapter 3, using the same simulation framework as in chapter 2, I developed a novel method of estimating outbreak sizes from phylogenetic trees which is simple, computationally inexpensive and takes advantage of the genomic data already usually gathered as part of the outbreak surveillance. I apply this method to a new outbreak of rabies in the Romblon province of the Philippines, confirming that there has been widespread undetected transmission, but that the outbreak surveillance was perhaps more effective at detecting cases than is usual for a rabies outbreak. In chapter 4 I used publicly available rabies sequence data to investigate to what extent codon usage was biased between different host-species-specific minor clades, and whether these differences were evidence of adaptation by the virus to the host. I found that while there was little evidence of the virus adapting its codon usage specifically to new host species, differences exist in RABV’s CpG content which suggest that bat- and carnivore-associated rabies clades are under differing levels of selection pressure from the host immune system on CpG dinucleotides. Together these findings demonstrate that genomic data is a valuable resource that can be used to inform outbreak responses and tell us about how rabies evolves and interacts with its wide range of hosts.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Subjects: Q Science > QH Natural history > QH426 Genetics; Q Science > QR Microbiology > QR355 Virology
• Colleges/Schools: College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
• Funder's Name: Engineering and Physical Sciences Research Council (EPSRC)
• Supervisor's Name: Hampson, Professor Katie and Cobbold, Professor Christina
• Date of Award: 2025
• Depositing User: Theses Team
• Unique ID: glathesis:2025-84927
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 26 Feb 2025 10:50
• Last Modified: 26 Feb 2025 11:06
• Thesis DOI: 10.5525/gla.thesis.84927
• URI: https://theses.gla.ac.uk/id/eprint/84927