Accessible, realistic genome simulation with selection using stdpopsim

• DOI: 10.1101/2025.03.23.644823
• Publication Date: 2025-03-24T17:38:30Z
• Authors: Graham Gower; Nathaniel S. Pope; Murillo F. Rodrigues; Silas Tittes; Linh N. Tran; Ornob Alam; Maria Izabel A. C...; Peter D. Fields; Benjamin C. Haller; Xin Huang; Ben Jeffrey; Kevin Korfmann; Christopher C. Ky...; Jiseon Min; Inés Rebollo; Clara T. Rehmann; Scott T. Small; Chris C. R. Smith; Georgia Tsambos; Yan Wong; Yu Zhang; Christian D. Huber; Gregor Gorjanc; Aaron P. Ragsdale; Ilan Gronau; Ryan N. Gutenkunst; Jerome Kelleher; Kirk E. Lohmueller; Daniel R. Schrider; Peter L. Ralph; Andrew D. Kern

AbstractSelection is a fundamental evolutionary force that shapes patterns of genetic variation across species. However, simulations incorporating realistic selection along heterogeneous genomes in complex demographic histories are challenging, limiting our ability to benchmark statistical methods aimed at detecting selection and to explore theoretical predictions.stdpopsimis a community-maintained simulation library that already provides an extensive catalog of species-specific population genetic models. Here we present a major extension to thestdpopsimframework that enables simulation of various modes of selection, including background selection, selective sweeps, and arbitrary distributions of fitness effects (DFE) acting on annotated subsets of the genome (for instance, exons). This extension maintainsstdpopsim’s core principles of reproducibility and accessibility while adding support for species-specific genomic annotations and published DFE estimates. We demonstrate the utility of this framework by benchmarking methods for demographic inference, DFE estimation, and selective sweep detection across several species and scenarios. Our results demonstrate the robustness of demographic inference methods to selection on linked sites, reveal the sensitivity of DFE-inference methods to model assumptions, and show how genomic features, like recombination rate and functional sequence density, influence power to detect selective sweeps. This extension tostdpopsimprovides a powerful new resource for the population genetics community to explore the interplay between selection and other evolutionary forces in a reproducible, low-barrier framework.