MOTIVATION: RNA viruses generate a cloud of genetic variants within each host. This cloud contains high-frequency genotypes, and many rare variants. The dynamics of these variants is crucial to understand viral evolution and their effect on their host. RESULTS: We use an experimental evolution system to show that the genetic cloud surrounding the Coxsackie virus master sequence slowly, but steadily, evolves over hundreds of generations. This movement is determined by strong context-dependent mutations, where the frequency and type of mutations are affected by neighboring positions, even in silent mutations. This context-dependent mutation pattern serves as a spearhead for the viral population's movement within the adaptive landscape and affects which new dominant variants will emerge. The non-local mutation patterns affect the mutated dinucleotide distribution, and eventually lead to a non-uniform dinucleotide distribution in the main viral sequence. We tested these results on other RNA viruses with similar conclusions. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

MOTIVATION: The study of RNA virus populations is a challenging task. Each population of RNA virus is composed of a collection of different, yet related genomes often referred to as mutant spectra or quasispecies. Virologists using deep sequencing technologies face major obstacles when studying virus population dynamics, both experimentally and in natural settings due to the relatively high error rates of these technologies and the lack of high performance pipelines. In order to overcome these hurdles we developed a computational pipeline, termed ViVan (Viral Variance Analysis). ViVan is a complete pipeline facilitating the identification, characterization and comparison of sequence variance in deep sequenced virus populations. RESULTS: Applying ViVan on deep sequenced data obtained from samples that were previously characterized by more classical approaches, we uncovered novel and potentially crucial aspects of virus populations. With our experimental work, we illustrate how ViVan can be used for studies ranging from the more practical, detection of resistant mutations and effects of antiviral treatments, to the more theoretical temporal characterization of the population in evolutionary studies. AVAILABILITY AND IMPLEMENTATION: Freely available on the web at http://www.vivanbioinfo.org CONTACT: : [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.