ArticlePLoS computational biology2018
Population dynamics of engineered underdominance and killer-rescue gene drives in the control of disease vectors.
Article in PLoS computational biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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.
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.
Who cites it
22 citing papers in PubMed.
- Self-limiting population suppression gene drive design in the West Nile vector mosquito, Culex quinquefasciatus.Nature communications · 2026Article
- Predicting the invasiveness of threshold-dependent gene drives.bioRxiv : the preprint server for biology · 2025Article
- Harnessing the highly adaptable barnase-barstar system for genetic biocontrol of Aedes aegypti.Communications biology · 2025Article
- A Comparative Assessment of Self-limiting Genetic Control Strategies for Population Suppression.Molecular biology and evolution · 2025Article
- Ecology of Gene Drives: The Role of Density-Dependent Feedbacks on the Efficacy and Dynamics of Two-Locus Underdominance Gene Drive Systems.Evolutionary applications · 2025Article
- Modelling daisy quorum drive: A short-term bridge across engineered fitness valleys.PLoS genetics · 2024Article
- A framework for identifying fertility gene targets for mammalian pest control.Molecular ecology resources · 2024Article
- Harnessing Wolbachia cytoplasmic incompatibility alleles for confined gene drive: A modeling study.PLoS genetics · 2023Article
- Driving down malaria transmission with engineered gene drives.Frontiers in genetics · 2022Review
- Engineered reproductively isolated species drive reversible population replacement.Nature communications · 2021Article
- Design and analysis of CRISPR-based underdominance toxin-antidote gene drives.Evolutionary applications · 2021Article
- Split versions of Cleave and Rescue selfish genetic elements for measured self limiting gene drive.PLoS genetics · 2021Article
- Split drive killer-rescue provides a novel threshold-dependent gene drive.Scientific reports · 2020Article
- Adequacy and sufficiency evaluation of existing EFSA guidelines for the molecular characterisation, environmental risk assessment and post-market environmental monitoring of genetically modified insects containing engineered gene drives.EFSA journal. European Food Safety Authority · 2020Article
- Gene Drive Dynamics in Natural Populations: The Importance of Density Dependence, Space, and Sex.Annual review of ecology, evolution, and systematics · 2020Article
- Development and testing of a novel killer-rescue self-limiting gene drive system inProceedings. Biological sciences · 2020Article
- Population Dynamics of Underdominance Gene Drive Systems in Continuous Space.ACS synthetic biology · 2020Article
- Performance analysis of novel toxin-antidote CRISPR gene drive systems.BMC biology · 2020Article
- A toxin-antidote CRISPR gene drive system for regional population modification.Nature communications · 2020Article
- Modeling the mutation and reversal of engineered underdominance gene drives.Journal of theoretical biology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
A number of different genetics-based vector control methods have been proposed. Two approaches currently under development in Aedes aegypti mosquitoes are the two-locus engineered underdominance and killer-rescue gene drive systems. Each of these is theoretically capable of increasing in frequency within a population, thus spreading associated desirable genetic traits. Thus they have gained attention for their potential to aid in the fight against various mosquito-vectored diseases. In the case of engineered underdominance, introduced transgenes are theoretically capable of persisting indefinitely (i.e. it is self-sustaining) whilst in the killer-rescue system the rescue component should initially increase in frequency (while the lethal component (killer) is common) before eventually declining (when the killer is rare) and being eliminated (i.e. it is temporally self-limiting). The population genetics of both systems have been explored using discrete generation mathematical models. The effects of various ecological factors on these two systems have also been considered using alternative modelling methodologies. Here we formulate and analyse new mathematical models combining the population dynamics and population genetics of these two classes of gene drive that incorporate ecological factors not previously studied and are simple enough to allow the effects of each to be disentangled. In particular, we focus on the potential effects that may be obtained as a result of differing ecological factors such as strengths of larval competition; numbers of breeding sites; and the relative fitness of transgenic mosquitoes compared with their wild-type counterparts. We also extend our models to consider population dynamics in two demes in order to explore the effects of dispersal between neighbouring populations on the outcome of UD and KR gene drive systems.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.