How predictable is RNA virus evolution?
Speaker: Richard Neher, PhD
Research Group Leader
Max Planck Institute for Developmental Biology
To quantitatively monitor diversity and dynamics of entire virus populations, we performed whole genome deep sequencing of HIV-1 populations in 9 untreated patients with 6-12 longitudinal samples spanning 5-8 years of infection. Using this data set, we show that a universal landscape of fitness costs controls minor intrapatient variation and the rate of reversion towards the global HIV-1 consensus. These reproducible patterns of diversity and reversion at single sites are possible only because frequent recombination limits coupling between different parts of the genome. In contrast, segments of influenza viruses don’t recombine. Nevertheless, the shape of phylogenetic trees predicts which of the currently circulating virus variants are most likely to dominate future seasons. Predictive models have the potential to improve strain selection for seasonal influenza vaccines.
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