# Evolutionary dynamics of CRISPR gene drives in natural populations

> **NIH NIH R01** · CORNELL UNIVERSITY · 2020 · $323,001

## Abstract

Project Summary
CRISPR gene drives can efficiently convert heterozygous cells with one copy of the drive allele into
homozygotes, thereby enabling super-Mendelian inheritance. Such a mechanism could be used, for
example, to rapidly disseminate a genetic payload through a disease-vector population that reduces
pathogen transmission or directly suppresses the vector, promising novel strategies for the control of
vector-borne diseases. However, our current understanding of how such an approach would perform in a
natural population is at best rudimentary. CRISPR gene drive is a complex evolutionary process that
depends on various factors such as the likelihood that resistance evolves against the drive, the spatial
structure and migration patterns of the target population, and genetic variation among individuals. The
overarching goal of this proposal is to gain a better understanding of the evolutionary dynamics of
CRISPR gene drive strategies in realistic models of target populations that take these complexities into
account. In Specific Aim 1 we will develop a comprehensive modeling framework for CRISPR gene
drives that will be informed by our recent experimental findings on drive mechanisms, resistance allele
formation, and variation in resistance rates in genetically diverse populations. This framework will allow
us to explore the performance of different drive strategies aimed at reducing resistance potential, such as
the use of multiple gRNAs and the targeting of haploinsufficient genes. In Specific Aim 2 we will utilize
cutting-edge simulation approaches developed in our lab to study how CRISPR gene drives will perform
in spatially explicit population models, in which individuals move across a continuous landscape and can
experience complex interactions with each other and their local environment. We hypothesize that these
spatial models will give rise to new phenomena that are not present in panmictic population models, such
as the elimination of a drive that has already spread into a large fraction of the population when
populations collapse locally due to the fitness cost of the drive. In Specific Aim 3 we will use the modeling
framework developed in the first two aims to study whether recently proposed safety measures can
reliably confine and control a drive after it has been released into a target population, focusing on the
complex interplay between drive genetics, the evolution of resistance, and the migration dynamics of
individuals over realistic landscapes. Our framework will allow us to probe and predict the population
dynamics of CRISPR gene drive approaches under specific empirical conditions, which will be integral to
any informed discussion about the feasibility, robustness, and risks of such approaches.

## Key facts

- **NIH application ID:** 9994340
- **Project number:** 5R01GM127418-03
- **Recipient organization:** CORNELL UNIVERSITY
- **Principal Investigator:** Philipp W Messer
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $323,001
- **Award type:** 5
- **Project period:** 2018-09-01 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9994340

## Citation

> US National Institutes of Health, RePORTER application 9994340, Evolutionary dynamics of CRISPR gene drives in natural populations (5R01GM127418-03). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9994340. Licensed CC0.

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