Evolution of Resistance Against CRISPR/Cas9 Gene Drive
Robert L. Unckless, Andrew G. Clark, Philipp W. Messer
GENETICS Early online December 10, 2016; DOI: 10.1534/genetics.116.197285
Source/Fonte: The Biologist - Royal Society of Biology
Abstract
CRISPR/Cas9 gene drive (CGD) promises a highly adaptable approach for spreading genetically engineered alleles throughout a species, even if those alleles impair reproductive success. CGD has been shown to be effective in laboratory crosses of insects, yet it remains unclear to what extent potential resistance mechanisms will affect the dynamics of this process in large natural populations. Here we develop a comprehensive population genetic framework for modeling CGD dynamics, which incorporates potential resistance mechanisms as well as random genetic drift. Using this framework, we calculate the probability that resistance against CGD evolves from standing genetic variation, de novo mutation of wildtype alleles, or cleavage-repair by nonhomologous end joining (NHEJ) -- a likely byproduct of CGD itself. We show that resistance to standard CGD approaches should evolve almost inevitably in most natural populations, unless repair of CGD-induced cleavage via NHEJ can be effectively suppressed, or resistance costs are on par with those of the driver. The key factor determining the probability that resistance evolves is the overall rate at which resistance alleles arise at the population level by mutation or NHEJ. By contrast, the conversion efficiency of the driver, its fitness cost, and its introduction frequency have only minor impact. Our results shed light on strategies that could facilitate the engineering of drivers with lower resistance potential, and motivate the possibility to embrace resistance as a possible mechanism for controlling a CGD approach. This study highlights the need for careful modeling of the population dynamics of CGD prior to the actual release of a driver construct into the wild.
CRISPR/CAS9 GENE DRIVE HOMING DRIVE MUTAGENIC CHAIN REACTION WHOLE POPULATION REPLACEMENT
Received October 27, 2016. Accepted December 1, 2016.
Copyright © 2016, The Genetics Society of America
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