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How sequence populations persist inside bacterial genomes

MPG-Autoren
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Park,  Hye Jin
Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Gokhale,  Chaitanya S.
Research Group Theoretical Models of Eco-Evolutionary Dynamics, Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Bertels,  Frederic
Research Group Microbial Molecular Evolution, Department Microbial Population Biology, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Zitation

Park, H. J., Gokhale, C. S., & Bertels, F. (2021). How sequence populations persist inside bacterial genomes. Genetics, 217(7): iyab027. doi:10.1093/genetics/iyab027.


Zitierlink: https://hdl.handle.net/21.11116/0000-0007-9DCB-4
Zusammenfassung
Compared to their eukaryotic counterparts, bacterial genomes are small and contain extremely tightly packed genes. Therefore, discovering a large number of short repetitive sequences in the genomes of Pseudomonads and Enterobacteria is unexpected. These sequences can independently replicate in the host genome and form populations that persist for millions of years. Here we model the interactions of intragenomic sequence populations with the bacterial host. In a simple model, sequence populations either expand until they drive the host to extinction or the sequence population gets purged from the genome. Including horizontal gene transfer does not change the qualitative outcome of the model and leads to the extinction of the sequence population. However, a sequence population can be stably maintained, if each sequence provides a benefit that decreases with increasing sequence population size. But concurrently, the replication of the sequence population needs to be costly to the host. Surprisingly, in regimes where horizontal gene transfer plays a role, the benefit conferred by the sequence population does not have to exceed the damage it causes. Together, our analyses provide a plausible scenario for the persistence of sequence populations in bacterial genomes. More importantly, we hypothesize a limited biologically relevant parameter range, which can be tested in future experiments.