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Simulation of bacterial populations with SLiM

Cury, Jean 1; Haller, Benjamin C. 2; Achaz, Guillaume 3, 4; Jay, Flora 1
1. Université Paris-Saclay, CNRS, INRIA, Laboratoire Interdisciplinaire des Sciences du Numérique, UMR 9015 Orsay, France
2. Department of Computational Biology, Cornell University, USA
3. UMR7206 Eco-Anthropologie, Université de Paris, CNRS, MNHN, Paris, France
4. UMR7241 Centre Interdisciplinaire de Recherche en Biologie, College de France, CNRS, IN-SERM, Paris, France

10.24072/pcjournal.72 - Peer Community Journal, Volume 2 (2022), article no. e7.

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Simulation of genomic data is a 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 has gained many users in recent years, due to its speed and power, and has extensive documentation showcasing various scenarios that it can simulate. This paper focuses on a simple demographic scenario, to explore unique aspects of modeling bacteria in SLiM’s scripting language. In addition, we illustrate the flexibility of SLiM by simulating the growth of bacteria on a Petri dish with antibiotic. To foster the development of bacterial simulations based upon this recipe, we explain the inner workings of its code. We also validate the simulator, by extensively testing the results of simulations against existing simulators, and against theoretical expectations for some summary statistics. This protocol, with the flexibility and power of SLiM, will enable the community to simulate bacterial populations efficiently under a wide range of evolutionary scenarios.
Published online:
DOI: https://doi.org/10.24072/pcjournal.72
Cury, Jean 1; Haller, Benjamin C. 2; Achaz, Guillaume 3, 4; Jay, Flora 1

1. Université Paris-Saclay, CNRS, INRIA, Laboratoire Interdisciplinaire des Sciences du Numérique, UMR 9015 Orsay, France
2. Department of Computational Biology, Cornell University, USA
3. UMR7206 Eco-Anthropologie, Université de Paris, CNRS, MNHN, Paris, France
4. UMR7241 Centre Interdisciplinaire de Recherche en Biologie, College de France, CNRS, IN-SERM, Paris, France 
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Cury, Jean; Haller, Benjamin C.; Achaz, Guillaume; Jay, Flora. Simulation of bacterial populations with SLiM. Peer Community Journal, Volume 2 (2022), article  no. e7. doi : 10.24072/pcjournal.72. https://peercommunityjournal.org/articles/10.24072/pcjournal.72/

Peer reviewed and recommended by PCI : 10.24072/pci.evolbiol.100123

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