RNA viruses have the highest mutation frequencies in nature, which are in large part attributed to the low fidelity of their viral RNA-dependent RNA polymerases (RdRp). Explosive replication kinetics coupled with high mutation rates quickly generate highly diverse populations that have been observed for all RNA viruses. Recently, we have developed a model system to study the roles that RNA virus mutation rates and population heterogeneity play in virus fitness, virulence and pathogenesis in vivo. The system relies on altering the RdRp fidelity of poliovirus, thereby changing the amount of genetic diversity present in a population. We found that increasing or decreasing genetic diversity strongly attenuates the virus and may constitute a novel strategy to engineer live virus vaccines. However, the poliovirus infection model of transgenic mice presents significant limitations that do not permit more detailed studies of the mechanisms behind these observations. To further extend our preliminary results, we will develop two new infection models, to study the role of genetic diversity and population dynamics of RNA viruses infecting their hosts naturally. These models will be used to uncover the mechanisms by which genetic diversity is generated, the points in infection when it is critical and the specific bottlenecking events or subpopulations that are involved at these critical points. We will use new deep sequencing technology, coupled to concepts in population genetics, to develop new strategies for vaccine discovery based on the modulation of RNA virus populations.