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Predicting the invasiveness of threshold-dependent gene drives
Isabel K Kim1, Philipp W Messer1
1Department of Computational Biology, Cornell University, Ithaca, NY 14853, United States.
Biorxiv : the Preprint Server for Biology
|December 3, 2025
Summary
Threshold-dependent gene drives offer control but spatial spread is complex. Individual-based simulations reveal stochastic effects impact invasion success, especially for suppression drives, necessitating spatially explicit analysis.
Area of Science:
- Ecology
- Genetics
- Mathematical Biology
Background:
- Gene drives can control pests but risk unintended spread.
- Threshold-dependent gene drives aim for safer population control.
- Spatial dynamics of these drives are not well understood.
Purpose of the Study:
- Analyze invasion criteria for threshold-dependent gene drives in continuous-space populations.
- Investigate the impact of spatial structure and stochasticity on gene drive spread.
- Compare outcomes from deterministic and individual-based models.
Main Methods:
- Deterministic reaction-diffusion models.
- Individual-based simulations in continuous space.
- Analysis of invasion criteria and spread dynamics.
Main Results:
- Individual-based models show high variability in invasion outcomes.
- Low-threshold modification drives can spread widely, even below diffusion model predictions.
- Threshold-dependent suppression drives are sensitive to stochasticity, often reducing invasion success.
Conclusions:
- Spatial containment of threshold-dependent gene drives is more complex than previously thought.
- Stochasticity significantly influences invasion dynamics, particularly for suppression drives.
- Spatially explicit analyses are crucial for evaluating real-world gene drive performance.
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