Integral gene drives for population replacement

Alexander Nash, Giulia Mignini Urdaneta, Andrea K. Beaghton, Astrid Hoermann, Philippos Aris Papathanos, George K. Christophides, Nikolai Windbichler

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

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.

Original languageAmerican English
Article numbere0210249
JournalBiology Open
Volume8
Issue number1
DOIs
StatePublished - 2019

Bibliographical note

Publisher Copyright:
© 2019. Published by The Company of Biologists Ltd

Keywords

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

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