Monitoring changes in the genome of influenza A viruses is crucial to understand its rapid evolution. These changes reflect how the virus adapts to changing environmental conditions such as establishment within a novel host species. Selective sweeps represent a rapid mode of adaptation and are typically observed in the evolution of human influenza A viruses. Here we describe a computational method named Sweep Dynamics (SD) plots. These combine phylogenetic algorithms with statistical

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... allowing to characterize the molecular adaptation of rapidly evolving viruses from longitudinal sequence data. To our knowledge, it is the first method that allows not only to identify selective sweeps, but also the time periods in which these occurred and the associated amino acid changes that may have provided a selective advantage to the virus. Using SD plots, we studied the past genome-wide adaptation of the 2009 pandemic H1N1 influenza A (pH1N1) and seasonal H3N2 influenza A (sH3N2) viruses. The pH1N1 influenza virus showed simultaneous amino acid changes in various proteins, particularly in seasons of high pH1N1 activity. Some of these adaptive changes resulted in functional alterations that facilitated virus transmission by respiratory droplets, which is key for sustained human-to-human transmission, directly after pandemic emergence. In the evolution of sH3N2 influenza viruses since 1999, we detected a large number of amino acid changes characterizing vaccine strains. Amino acid changes found in antigenically novel strains rising to predominance were occasionally revealed in a selective sweep one season prior to the recommendation of the WHO, suggesting the value of the technique for the vaccine strain selection problem. Taken together, our results show that SD plots allow to monitor and characterize the adaptive evolution of influenza A viruses by identifying selective sweeps and their associated signatures.