Computational and experimental performance of CRISPR homing gene drive strategies with multiplexed gRNAs

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Abstract

The rapid evolution of resistance alleles poses a major obstacle for genetic manipulation of populations with CRISPR homing gene drives. One proposed solution is using multiple guide RNAs (gRNAs), allowing a drive to function even if some resistant target sites are present. Here, we develop a model of homing mechanisms parameterized by experimental studies. Our model incorporates several factors affecting drives with multiple gRNAs, including timing of cleavage, reduction in homology-directed repair efficiency due to imperfect homology, Cas9 activity saturation, gRNA activity level variance, and incomplete homology-directed repair. We find that homing drives have an optimal number of gRNAs, usually between two and eight, depending on the specific drive type and performance parameters. These results contradict the notion that resistance rates can be reduced to arbitrarily low levels by gRNA multiplexing and highlight the need for combined approaches to counter resistance evolution in CRISPR homing drives.

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CITATION STYLE

APA

Champer, S. E., Oh, S. Y., Liu, C., Wen, Z., Clark, A. G., Messer, P. W., & Champer, J. (2020). Computational and experimental performance of CRISPR homing gene drive strategies with multiplexed gRNAs. Science Advances, 6(10). https://doi.org/10.1126/sciadv.aaz0525

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