Evidence map›Paper›PMID 28887462›Full record

ArticleScientific reports2017

Evaluating strategies for reversing CRISPR-Cas9 gene drives.

Michael R Vella, Christian E Gunning, Alun L Lloyd, Fred Gould

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

35 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Natural and Engineered Sex Ratio Distortion in Insects.Frontiers in ecology and evolution · 2022
    Article
  5. Gene drives gaining speed.Nature reviews. Genetics · 2022
    Review
  6. Genetic Approaches for Controlling CRISPR-based Autonomous Homing Gene Drives.Frontiers in bioengineering and biotechnology · 2022
    Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Making gene drive biodegradable.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Michael R VellaNorth Carolina State University, Biomathematics Graduate Program, Department of Mathematics, Raleigh, 27695, USA.
Christian E GunningNorth Carolina State University, Department of Entomology and Plant Pathology, Raleigh, 27695, USA.
Alun L LloydNorth Carolina State University, Biomathematics Graduate Program, Department of Mathematics, Raleigh, 27695, USA.
Fred GouldNorth Carolina State University, Genetic Engineering and Society Center, Raleigh, 27695, USA. fred_gould@ncsu.edu.

Funding

Improving Robustness of a Tactical Model of Aedes/Dengue DynamicsR01AI091980 · NIAID · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI GOULD, FRED · 2011 to 2014
$1.3M
NIAID NIH HHS R01 AI091980
6 · The paper itself

Abstract

A gene drive biases inheritance of a gene so that it increases in frequency within a population even when the gene confers no fitness benefit. There has been renewed interest in environmental releases of engineered gene drives due to recent proof of principle experiments with the CRISPR-Cas9 system as a drive mechanism. Release of modified organisms, however, is controversial, especially when the drive mechanism could theoretically alter all individuals of a species. Thus, it is desirable to have countermeasures to reverse a drive if a problem arises. Several genetic mechanisms for limiting or eliminating gene drives have been proposed and/or developed, including synthetic resistance, reversal drives, and immunizing reversal drives. While predictions about efficacy of these mechanisms have been optimistic, we lack detailed analyses of their expected dynamics. We develop a discrete time model for population genetics of a drive and proposed genetic countermeasures. Efficacy of drive reversal varies between countermeasures. For some parameter values, the model predicts unexpected behavior including polymorphic equilibria and oscillatory dynamics. The timing and number of released individuals containing a genetic countermeasure can substantially impact outcomes. The choice among countermeasures by researchers and regulators will depend on specific goals and population parameters of target populations.

Indexed as

Clustered Regularly Interspaced Short Palindromic RepeatsCRISPR-Associated Protein 9Gene Drive TechnologyGenetics, PopulationModels, StatisticalOrganisms, Genetically ModifiedTime FactorsCRISPR-Associated Protein 9

Identifiers

PMID28887462
PMCPMC5591286

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.