Viral shift

Abstract: The ability for RNA viruses to evolve at a high rate has the potential to confound existing medical technology by making it more difficult to accurately diagnosis and treat RNA based infectious disease. The rapid mutation rates of RNA viruses give a virus the ability to adapt to novel selective pressures, which can potentially support zoonosis, sustained outbreaks in a novel host, and resistance to anti-retroviral treatments. A key contributor to an RNA virus’ mutation rate is the lack of a proof reading enzyme to correct for mis-incorporated bases when transcribing a daughter RNA particle. Thus, there are potentially many opportunities for new mutations to be randomly introduced and subsequently fixed in a key subset of the viral population. This is a feature, which we refer to in this report as genetic drift. One of the hurdles to understanding the role of genetic drift in the spread of RNA virus outbreaks is the need to analyze a densely sampled outbreak using whole genome sequencing in order to measure the amount of mutation occurring on a small time scale. The recent advances in sequencing technology have now lowered the data collection cost barriers to allow the measure of evolution not just among the consensus virus sequences on a shorter time scale, but potentially capture all the distinct genetic variants that are circulating within a single infected host. Tracking the distinct genetic variants within an infected individual provides additional information on genetic drift within the host, and can help determine whether mutations that are important for emerging disease are able to persist at the sub consensus level. We thus are undertaking an effort to identify the benefits and challenges to measuring genetic drift and its role in viral outbreaks through the examination of a case study, a rabies virus outbreak in Northern California. In collaboration with the California Department of Public Health, we obtained access to 50 samples of rabies infected animals (primarily foxes, and skunks). In order to gain an understanding of how the sequencing technology can be used to measure small numbers of genetic mutants in a population and determine the degree of sensitivity to detect variation needed, we sequenced three samples with “ultra-high” sequencing coverage using an Illumina sequencer. The results of this experimental work are the focus of this report, which generates the data that is used to devise a sequencing strategy for the remaining