Review of gene drive modelling and implications for risk assessment of gene drive organisms

Frieß, Johannes L.; Lalyer, Carina R.; Giese, Bernd; Simon, Samson; Otto, Mathias

doi:10.1016/j.ecolmodel.2023.110285

Cited by 7 publications

(8 citation statements)

References 61 publications

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“…Informative aspects include organisms life histories and those required by the European Food Safety Authority (not regionally applicable) and WHO guidelines for genetically modified organisms. 156 We are currently building a model specific for the golden mussel using the SLiM framework, 157 which allows for the customization of reproductive strategy and is considered one of the most powerful models available for gene drives.…”

Section: Current Approaches In Development For the Genetic Biocontrol...mentioning

confidence: 99%

Toward invasive mussel genetic biocontrol: Approaches, challenges, and perspectives

Hernández Elizárraga,

Ballantyne,

O'Brien

et al. 2023

iScience

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Section: Current Approaches In Development For the Genetic Biocontrol...mentioning

confidence: 99%

Toward invasive mussel genetic biocontrol: Approaches, challenges, and perspectives

Hernández Elizárraga,

Ballantyne,

O'Brien

et al. 2023

iScience

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“…2023) as there will be no risk taken on large-scale exploratory trials (Baltzegar et al . 2018; Frieß et al . 2023).…”

Section: Introductionmentioning

confidence: 99%

“…The effect of controllable variables, alone or in conjunction, on the frequency dynamics and outcome of a gene drive could be tuned by design or by management to achieve a desired results, potentially compensating for imponderable features of the biological system targeted. Gene drive risk assessment should be exhaustive across ecological contexts (Kim et al 2023) as there will be no risk taken on large-scale exploratory trials (Baltzegar et al 2018;Frieß et al 2023). As technology is almost in hand, the challenge is to measure the importance of every feature to deliver eco-evolutionary relevant predictions for a gene drive release (Combs et al 2023).…”

Section: Introductionmentioning

confidence: 99%

“…Previous models have explored how variation in pairs of variables can change either the outcome (Dhole et al 2018;Rode et al 2019) or the internal dynamics (Unckless et al 2015;Dhole et al 2020) of a gene drive. However, many of the features affecting a gene drive vary continuously, potentially interacting with each other to greatly complicate the outcome predictability (Nash et al 2018;Frieß et al 2023). Understanding how the many variables affecting a gene drive influence its fate thus requires their simultaneous testing over a continuous range of values.…”

Section: Introductionmentioning

confidence: 99%

“…It may be safer, and arguably more ethical, to design a gene drive that is transient or reaches equilibrium in a population while the mechanics of the system is not yet fully controlled. A gene drive intended to suppress a local population may have unforeseen consequences that outweigh the potential benefits (Frieß et al 2023). Designing gene drives that are locally self limiting over time and space are ideal candidates for initial gene drive releases (Marshall and Akbari 2018;Dhole et al 2019Dhole et al , 2020.…”

Section: Introductionmentioning

confidence: 99%

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Controlling the frequency dynamics of homing gene drives for intermediate outcomes

Camm,

Fournier-Level

2024

Preprint

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Gene drives have enormous potential for solving biological issues by forcing the spread of desired alleles through populations. However, to safeguard from the potentially irreversible consequences on natural populations, gene drives with intermediate outcomes that neither fixate nor get removed from the population are of outstanding interest. To elucidate the conditions leading to intermediate gene drive frequency, a stochastic, individual allele-focused gene drive model accessible was developed to simulate the diffusion of a homing gene drive in a population. The frequencies of multiple alleles at a locus targeted by a gene drive were tracked under various scenarios. These explored the effect of gene drive conversion efficiency, strength and frequency of resistance alleles, presence and strength of a fitness cost for the gene drive, its dominance and the level of inbreeding. Four outcomes were consistently observed: Fixation, Loss, Temporary and Equilibrium. The latter two are defined by the frequency of the gene drive peaking then crashing or plateauing, respectively. No single variable determined the outcome of a drive, instead requiring a combination of variables. The difference between the conversion efficiency and resistance level differentiated the Temporary and Equilibrium outcomes. The frequency dynamics of the gene drive within outcomes varied extensively, with different variables driving this dynamics between outcomes. These simulation results highlight the possibility of fine-tuning gene drive outcomes and compensating through biotechnological design constraint imposed by population features. To that end, we provide a web application implementing our model which will guide the safer design of gene drives able to achieve a range of controllable outcome tailored to population management needs.

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Leveraging eco-evolutionary models for gene drive risk assessment

et al. 2023

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Review of gene drive modelling and implications for risk assessment of gene drive organisms

Cited by 7 publications

References 61 publications

Toward invasive mussel genetic biocontrol: Approaches, challenges, and perspectives

Toward invasive mussel genetic biocontrol: Approaches, challenges, and perspectives

Controlling the frequency dynamics of homing gene drives for intermediate outcomes

Leveraging eco-evolutionary models for gene drive risk assessment

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