P68 heads were manually boxed using e2boxer.py from the software package EMAN 2.1 (44). Images of 37,218 particles (600 × 600 pixels) were extracted from the micrographs and background-normalized using RELION 2.1 (45). Multiple rounds of 2D classification of particles were performed using RELION (45). Only particles belonging to high-resolution class averages were used for subsequent reconstruction (36,853 particles). To generate the initial model, we used the random de novo model method as implemented in EMAN2 (44). Particles were divided into two independent sets. From each half, nine subsets of 4× binned images were generated. Each set contained 1000 particles. The particles were assigned random orientations and iteratively reconstructed into 3D volumes using the software package jspr (46). Independent initial models were chosen from both half-datasets by selecting the two models most similar to each other. Afterward, the initial models were unbinned 4× to match the size of the original images and low-pass–filtered to a resolution of 40 Å. The refinement was performed using the program RELION 2.1 (45). After initial auto refinement, 3D classification was performed without the alignment step. Particles belonging to the best class (21,625 particles) were selected for further RELION auto refinement with imposed icosahedral symmetry and maximum allowed deviations from previous orientations of 10°. The resulting map was threshold-masked, divided by the modulation transfer function, and B-factor sharpened during the post-processing in RELION (45).

Capsids of genome release intermediates and empty particles were determined using the same reconstruction strategy. After 2D classification, 4040 and 10,259 images were available for the reconstructions of capsids of genome release intermediate and empty particles, respectively. After 3D classification, the numbers of particles were 2332 and 8580, respectively.

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