Anopheles homing suppression drive candidates exhibit unexpected performance differences in simulations with spatial structure

Abstract
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Abstract

Recent experiments have produced several Anopheles gambiae homing gene drives that disrupt female fertility genes, thereby eventually inducing population collapse. Such drives may be highly effective tools to combat malaria. One such homing drive, based on the zpg promoter driving CRISPR/Cas9, was able to eliminate a cage population of mosquitoes. A second version, purportedly improved upon the first by incorporating an X-shredder element (which biases inheritance towards male offspring), was similarly successful. Here, we analyze experimental data from each of these gene drives to extract their characteristics and performance parameters and compare these to previous interpretations of their experimental performance. We assess each suppression drive within an individual-based simulation framework that models mosquito population dynamics in continuous space. We find that the combined homing/X-shredder drive is actually less effective at population suppression within the context of our mosquito population model. In particular, the combined drive often fails to completely suppress the population, instead resulting in an unstable equilibrium between drive and wild-type alleles. By contrast, otherwise similar drives based on the nos promoter may prove to be more promising candidates for future development than originally thought.

Data availability

All SLiM files for the implementation of these suppression drives are available on GitHub (https://github.com/jchamper/ChamperLab/tree/main/Mosquito-Drive-Modeling).

The following data sets were generated

(2022) Mosquito-Drive-Modeling
GitHub.

https://github.com/jchamper/ChamperLab/tree/main/Mosquito-Drive-Modeling

Article and author information

Author details

Samuel E Champer

Department of Computational Biology, Cornell University, Ithaca, United States

Competing interests
No competing interests declared.

"This ORCID iD identifies the author of this article:" 0000-0002-4559-7627
Isabel K Kim

Department of Computational Biology, Cornell University, Ithaca, United States

Competing interests
No competing interests declared.
Andrew G Clark

Department of Computational Biology, Cornell University, Ithaca, United States

Competing interests
No competing interests declared.
Philipp W Messer

Department of Computational Biology, Cornell University, Ithaca, United States

Competing interests
Philipp W Messer, Reviewing editor, eLife.

"This ORCID iD identifies the author of this article:" 0000-0001-8453-9377
Jackson Champer

Center for Bioinformatics, Peking University, Beijing, China

For correspondence
jchamper@pku.edu.cn

Competing interests
No competing interests declared.

"This ORCID iD identifies the author of this article:" 0000-0002-3814-3774

Funding

NIH (F32AI138476)

Jackson Champer

NIH (R01GM127418)

Philipp W Messer

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.