# Dynamics of Gene Drives in Natural Populations

> **NIH NIH F32** · CORNELL UNIVERSITY · 2020 · $2,572

## Abstract

Project Summary/Abstract
Mosquito-transmitted diseases, including malaria, dengue and Zika, continue to take a devastating toll. Gene
drive systems could provide a new strategy for controlling these diseases by spreading genetically engineered
alleles into vector populations, such as allelic variants that make the insects resistant to a pathogen or
deleterious alleles than directly suppress their populations.
The recently developed CRISPR/Cas9 homing gene drive system promises to be a highly adaptable
mechanism that works by converting heterozygotes for the driver construct into homozygotes. However, it
remains unclear whether this mechanism will work in wild populations given the expected high rate of
generation of resistance alleles, which are created by the drive mechanism itself when cleavage is repaired by
nonhomologous end joining. Another proposed gene drive system, Medea, likely suffers less from the
generation of resistance alleles, but it spreads more slowly and is highly sensitive to fitness costs. The goal of
our project is to identify and quantify parameters that are critical to determining whether these systems can in
fact spread in diverse, natural populations.
In our first aim, we will employ laboratory examples of homing drivers and Medea drivers to quantify the drive
efficiency and origination rate of resistance alleles in genetically diverse but well characterized lines of the
model organism Drosophila melanogaster. We will then use these results to map the genetic loci associated
with differences in drive efficiency and resistance levels.
Our second aim will determine the ability of each gene drive system to invade genetically diverse populations.
For this purpose, a small number of gene drive flies will be introduced into population cages with a mix of
Global Diversity Line flies. Phenotype frequencies will be tracked over several generations to determine the
ability of the gene drive to successfully invade the population. This work will be done in a state-of-the-art
arthropod containment lab to prevent escape of transgenic insects.
In our third aim, we will compare the ability of homing drivers and Medea drivers to spread in geographically
structured populations using sophisticated population genetic simulations. We will identify the parameters that
will allow a gene drive system to establish, spread, and either fix or persist sufficiently long in a large natural
population under realistic assumptions of demography and population structure.
Overall our experiments and modeling will provide crucial data for predicting the dynamics of gene drive
systems in natural target populations. The conclusions from our studies will play an important role in designing
and implementing the next generation of gene drive systems for optimal performance in realistic populations.

## Key facts

- **NIH application ID:** 10155874
- **Project number:** 3F32AI138476-02S1
- **Recipient organization:** CORNELL UNIVERSITY
- **Principal Investigator:** JACKSON CHAMPER
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $2,572
- **Award type:** 3
- **Project period:** 2018-04-01 → 2021-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10155874

## Citation

> US National Institutes of Health, RePORTER application 10155874, Dynamics of Gene Drives in Natural Populations (3F32AI138476-02S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10155874. Licensed CC0.

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