Invasion and migration of spatially self-limiting gene drives: A comparative analysis.

Abstract:

:Recent advances in research on gene drives have produced genetic constructs that could theoretically spread a desired gene (payload) into all populations of a species, with a single release in one place. This attribute has advantages, but also comes with risks and ethical concerns. There has been a call for research on gene drive systems that are spatially and/or temporally self-limiting. Here, we use a population genetics model to compare the expected characteristics of three spatially self-limiting gene drive systems: one-locus underdominance, two-locus underdominance and daisy-chain drives. We find large differences between these gene drives in the minimum release size required for successfully driving a payload into a population. The daisy-chain system is the most efficient, requiring the smallest release, followed by the two-locus underdominance system, and then the one-locus underdominance system. However, when the target population exchanges migrants with a nontarget population, the gene drives requiring smaller releases suffer from higher risks of unintended spread. For payloads that incur relatively low fitness costs (up to 30%), a simple daisy-chain drive is practically incapable of remaining localized, even with migration rates as low as 0.5% per generation. The two-locus underdominance system can achieve localized spread under a broader range of migration rates and of payload fitness costs, while the one-locus underdominance system largely remains localized. We also find differences in the extent of population alteration and in the permanence of the alteration achieved by the three gene drives. The two-locus underdominance system does not always spread the payload to fixation, even after successful drive, while the daisy-chain system can, for a small set of parameter values, achieve a temporally limited spread of the payload. These differences could affect the suitability of each gene drive for specific applications.

journal_name

Evol Appl

authors

Dhole S,Vella MR,Lloyd AL,Gould F

doi

10.1111/eva.12583

subject

Has Abstract

pub_date

2018-01-04 00:00:00

pages

794-808

issue

5

issn

1752-4571

pii

EVA12583

journal_volume

11

pub_type

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