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Phylogenetic and population genetic analysis
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A multihost bacterial pathogen overcomes continuous population bottlenecks to adapt to new host species

Procedure

To infer the isolate genealogies and branch lengths, we manually constructed core genome SNP alignments from the variants characterized and used them to build minimum evolution phylogenetic trees using the maximum composite likelihood method in MEGA (Molecular Evolutionary Genetics Analysis) (59). This method was used because of the short evolutionary frames and previous knowledge on the transmission chains. From the variants identified, we estimated the substitution rates as described in Eq. 1: number of mutations (m) divided by the genome size (N) times the generations (t/g). Considering a replication time of 30 min for S. aureus, 1 year is approximately equivalent to 18,000 generations.$μ=mN*(tg)$(1)

To examine within-host dynamics, we calculated the total number of SNPs per isolate, as well as fixed and variable SNPs present in each of the three isolates from individual sheep. We applied a general linear regression model on SNP counts versus number of days to estimate differences between the molecular clocks for transmissions and within single host population dynamics. Pairwise genetic distances were calculated as the number of SNPs between two isolates from the same host.

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