Simulation of bacterial populations with SLiM

Simulation of genomic data is one of the key tool in population genetics, yet, to date, there is no forward-in-time simulator of bacterial populations that is both computationally efficient and adaptable to a wide range of scenarios. Here we demonstrate how to simulate bacterial populations with SLiM, a forward-in-time simulator built for eukaryotes. SLiM gained lots of traction in the past years, and has exhaustive documentation showcasing the various scenarios that are possible to simulate. This paper focuses on a simple demographic scenario, to explore bacterial specificities and how it translates into SLiM9s language. To foster the development of bacterial simulations with this recipe, we pedagogically walk the reader through the code. We also validate the simulator, by testing extensively the results of the simulations against existing simulators and theoretical expectations of some summary statistics. Finally, the combination of this protocol with the flexibility and power of SLiM enables the community to simulate efficiently bacterial populations under a wide range of evolutionary scenarios.