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

  1. Samuel E Champer
  2. Isabel K Kim
  3. Andrew G Clark
  4. Philipp W Messer
  5. Jackson Champer  Is a corresponding author
  1. Cornell University, United States
  2. Peking University, China

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

Article and author information

Author details

  1. Samuel E Champer

    Department of Computational Biology, Cornell University, Ithaca, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4559-7627
  2. Isabel K Kim

    Department of Computational Biology, Cornell University, Ithaca, United States
    Competing interests
    No competing interests declared.
  3. Andrew G Clark

    Department of Computational Biology, Cornell University, Ithaca, United States
    Competing interests
    No competing interests declared.
  4. Philipp W Messer

    Department of Computational Biology, Cornell University, Ithaca, United States
    Competing interests
    Philipp W Messer, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8453-9377
  5. Jackson Champer

    Center for Bioinformatics, Peking University, Beijing, China
    For correspondence
    jchamper@pku.edu.cn
    Competing interests
    No competing interests declared.
    ORCID icon "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.

Reviewing Editor

  1. George H Perry, Pennsylvania State University, United States

Version history

  1. Preprint posted: March 28, 2022 (view preprint)
  2. Received: March 31, 2022
  3. Accepted: October 14, 2022
  4. Accepted Manuscript published: October 14, 2022 (version 1)
  5. Version of Record published: October 25, 2022 (version 2)

Copyright

© 2022, Champer et al.

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.

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  1. Samuel E Champer
  2. Isabel K Kim
  3. Andrew G Clark
  4. Philipp W Messer
  5. Jackson Champer
(2022)
Anopheles homing suppression drive candidates exhibit unexpected performance differences in simulations with spatial structure
eLife 11:e79121.
https://doi.org/10.7554/eLife.79121

Share this article

https://doi.org/10.7554/eLife.79121

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