Forecasting evolution from the shape of genealogical trees

Given a sample of genome sequences from an asexual population, can one predict its evolutionary future? Under the assumption that evolution proceeds by accumulation of small effect mutations, it can be demonstrated that the branching patterns of reconstructed genealogical trees contains information about the relative fitness of the sampled sequences and that this information can be used to predict successful strains. This approach does not require species specific input and can be applied to any asexual population under persistent selection pressure. The performance of the forecasting method was tested using historical data on seasonal influenza A/H3N2 virus: it identifies the progenitor lineage of the upcoming influenza season with near optimal performance in 30% of cases and makes informative predictions over 80% of the time, overall. The talk will also discuss approaches to improving forecasting with the help of additional, strain specific data.