Population-level multiplexing: A promising strategy to manage the evolution of resistance against gene drives targeting a neutral locus.

CRISPR gene drive genetic engineering multiplexing population alteration resistance

Journal

Evolutionary applications
ISSN: 1752-4571
Titre abrégé: Evol Appl
Pays: England
ID NLM: 101461828

Informations de publication

Date de publication:
Sep 2020
Historique:
received: 06 12 2019
revised: 19 02 2020
accepted: 25 02 2020
entrez: 10 9 2020
pubmed: 11 9 2020
medline: 11 9 2020
Statut: epublish

Résumé

CRISPR-based gene drives bias inheritance in their favour by inducing double-stranded breaks (DSBs) at wild-type homologous loci and using the drive transgene as a repair template-converting drive heterozygotes into homozygotes. Recent studies have shown that alternate end-joining repair mechanisms produce cut-resistant alleles that rapidly induce drive failure. Multiplexing-simultaneously targeting multiple sites at the wild-type locus-is commonly assumed to overcome this issue since resistance would need to develop at all target sites for the system to fail. This may work for some population suppression drives targeting essential (e.g. viability or fertility) genes if careful design can ensure cut-resistant alleles themselves have low fitness. However, here, models are used to demonstrate that this approach will be ineffective when targeting neutral loci. We then go on to compare the performance of four alternative population-level multiplexing approaches with standard individual-level multiplexing. Two of these approaches have mechanisms preventing them from becoming linked, thus avoiding multiple simultaneous DSBs and giving a large improvement. Releasing multiple unlinked drives gives a modest improvement, while releasing multiple drives that may become linked over time produces a decrease in performance under the conditions tested here. Based on performance and technical feasibility, we then take one approach forward for further investigation, demonstrating its robustness to different performance parameters and its potential for controlling very large target populations.

Identifiants

pubmed: 32908596
doi: 10.1111/eva.12945
pii: EVA12945
pmc: PMC7463328
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1939-1948

Subventions

Organisme : Biotechnology and Biological Sciences Research Council
ID : BBS/E/I/00007038
Pays : United Kingdom

Informations de copyright

© 2020 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.

Déclaration de conflit d'intérêts

The authors have submitted a provisional patent application for this technology.

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Auteurs

Matthew P Edgington (MP)

The Pirbright Institute Woking UK.

Tim Harvey-Samuel (T)

The Pirbright Institute Woking UK.

Luke Alphey (L)

The Pirbright Institute Woking UK.

Classifications MeSH