COS 241-5 - Twenty years of gene drive dynamic models: research trends, gaps, and application to environmental risk assessment

Abstract: Engineered gene drive systems alter patterns of trait inheritance and/or demographic trajectories of wild populations, enabling novel management solutions across agriculture, public health, and conservation. CRISPR-based technologies have accelerated the application of gene drives to diverse systems and multiple projects now seek to release transgenic individuals for outdoor field trials. While environmental risk assessments (ERAs) are needed to evaluate the potential for detrimental and widespread ecosystem effects caused by gene drives, predicting the system-specific consequences of ecological variation, interspecific interactions, life-history characteristics, implementation strategies, and underlying evolutionary processes remains challenging.

Dynamic process-based models provide flexible quantitative platforms to track how interactions across biological scales mediate the consequences of biased inheritance. We reviewed and synthesized twenty years of gene drive dynamic models (GDDMs) to identify research trends, knowledge gaps, and avenues for improving model integration within ERA frameworks.

We identified 34 common features included in GDDMs organized into five categories reflecting biological scale: genetics, demography, spatial ecology, biotic and abiotic environment, and implementation strategy. Further, we identify the phenomena that most significantly influence model predictions, discuss limitations of biological complexity and uncertainty, and provide insights to promote responsible development and model-assisted risk assessment of gene drives. Ultimately, GDDMs exhibit increasing utility to promote the collaborative research among gene drive developers, ecologists, risk assessors, and community leaders necessary for responsible implementation of novel biotechnology.