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Biol Open. 2019 Jan 3;8(1). pii: bio037762. doi: 10.1242/bio.037762.

Integral gene drives for population replacement.

Author information

1
Department of Life Sciences, Imperial College London, Sir Alexander Fleming Building, South Kensington Campus, London SW7 2AZ, UK.
2
Centre of Functional Genomics, Department of Experimental Medicine, University of Perugia, Perugia 06123, Italy.
3
Department of Entomology, Robert H. Smith Faculty of Agriculture, Food and Environment, Hebrew University of Jerusalem, Rehovot 7610001, Israel.
4
Department of Life Sciences, Imperial College London, Sir Alexander Fleming Building, South Kensington Campus, London SW7 2AZ, UK g.christophides@imperial.ac.uk n.windbichler@imperial.ac.uk.

Abstract

A first generation of CRISPR-based gene drives has now been tested in the laboratory in a number of organisms, including malaria vector mosquitoes. Challenges for their use in the area-wide genetic control of vector-borne disease have been identified, including the development of target site resistance, their long-term efficacy in the field, their molecular complexity, and practical and legal limitations for field testing of both gene drive and coupled anti-pathogen traits. We have evaluated theoretically the concept of integral gene drive (IGD) as an alternative paradigm for population replacement. IGDs incorporate a minimal set of molecular components, including drive and anti-pathogen effector elements directly embedded within endogenous genes - an arrangement that in theory allows targeting functionally conserved coding sequences without disrupting their function. Autonomous and non-autonomous IGD strains could be generated, optimized, regulated and imported independently. We performed quantitative modeling comparing IGDs with classical replacement drives and show that selection for the function of the hijacked host gene can significantly reduce the establishment of resistant alleles in the population, while drive occurring at multiple genomic loci prolongs the duration of transmission blockage in the face of pre-existing target site variation. IGD thus has potential as a more durable and flexible population replacement strategy.

KEYWORDS:

CRISPR; Gene drive; Genome editing; Population modeling; Population replacement

Conflict of interest statement

Competing interestsThe authors declare no competing or financial interests.

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