Leveraging eco-evolutionary models for gene drive risk assessment
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M. A. Combs, A. J. Golnar, J. M. Overcash, A. L. Lloyd, K. R. Hayes, D. A. O’Brochta and K. M. Pepin,
Trends in Genetics,
2023.
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As development of gene drive systems accelerates and diversifies, predicting outcomes for target populations and the potential for human and environmental risks requires accounting for numerous eco-evolutionary processes.Gene drive dynamic models quantify the influence of features across genetics (e.g., resistance development and standing genetic diversity), demographics (e.g., mating systems and inbreeding), spatial ecology (e.g., dispersal and competition), biotic and abiotic environments (e.g., climate variation and landscape structure), and implementation strategies (e.g., introduction size and timing) on gene drive outcomes.Synthesizing published gene drive models reveals research trends, knowledge gaps, and emergent principles. Modeling limitations and tradeoffs are discussed.Integrating an iterative modeling approach within the existing phased pathway for gene drive research improves utility for risk assessment.
