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Accessible, Realistic Genome Simulation with Selection Using stdpopsim

Abstract:
Selection 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. stdpopsim is a community-maintained simulation library that already provides an extensive catalog of species-specific population genetic models. Here, we present a major extension to the stdpopsim framework 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 maintains stdpopsim’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 comparing 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 to stdpopsim provides a powerful new resource for the population genetics community to explore the interplay between selection and other evolutionary forces in a reproducible, user-friendly framework.
Publication status:
Published
Peer review status:
Peer reviewed

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Author
ORCID:
0000-0002-6197-3872
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Role:
Author
ORCID:
0000-0001-8409-7812
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ORCID:
0000-0001-7508-1384
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ORCID:
0000-0003-4697-7434
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ORCID:
0000-0003-0574-0887



Publisher:
Oxford University Press
Journal:
Molecular Biology and Evolution More from this journal
Volume:
42
Issue:
11
Article number:
msaf236
Publication date:
2025-09-25
Acceptance date:
2025-08-18
DOI:
EISSN:
1537-1719
ISSN:
0737-4038


Language:
English
Pubs id:
2292977
UUID:
uuid_8210bf5d-1b70-433e-9761-95310497fb3e
Local pid:
pubs:2292977
Source identifiers:
3425465
Deposit date:
2025-10-30
ARK identifier:
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