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Understanding how viral mutant spectra organize and explore genotype space is essential for elucidating the mechanisms that drive molecular evolution. Here, we use deep-sequencing data of an amplicon in the A2 protein of the RNA bacteriophage Q[Formula: see text] to reconstruct genotype networks comprising tens of thousands of haplotypes. The study of populations evolved under different temperature regimes reveals robust and reproducible patterns that arise from the interplay between fundamental geometrical motifs of sequence spaces and population dynamics. Mutant swarms exhibit a self-similar, hierarchical organization in which sequences cluster around highly connected, abundant cores that continuously regenerate diversity during evolution. The immediate neighborhood of these cores is rapidly rebuilt and extensively sampled, while a few mutations away sampling becomes dynamical and sparse. This population structure emerges from a dynamic, out-of-equilibrium balance between replication and mutational exploration and suggests that Q[Formula: see text] populations do not rely primarily on neutral networks to navigate genotype space or to generate diversity. Combining genotype networks from populations adapted to different temperatures reveals early evolutionary divergence, with partially overlapping yet distinct populations that remain connected through short mutational paths. Even at the time scale of these experiments, evolutionary trajectories remain multiple, preventing the backward reconstruction of unique trajectories once mutations have been fixed. Together, this analysis provides a detailed view of the fine-scale processes shaping the evolution of heterogeneous viral populations and establishes genotype networks as a powerful framework for visualizing and interpreting the organization and diversification of viral quasispecies.
Published in: Proceedings of the National Academy of Sciences
Volume 123, Issue 14, pp. e2512150123-e2512150123