Modeling confinement and reversibility of threshold-dependent gene drive systems in spatially-explicit<i>Aedes aegypti</i>populations

C., Héctor M. Sánchez; Bennett, Jared B.; Wu, Sean L.; Rašić, Gordana; Akbari, Omar S.; Marshall, John M.

doi:10.1101/607267

Cited by 8 publications

(16 citation statements)

References 55 publications

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“…Moreover, globally collated MRR experimental data for Ae. aegypti [14] produced an exponential kernel with σ = 54.1 m [10]. Such high congruence with our genetic-based inferences indicates the robustness of spatial-genetic patterns in reflecting the dispersal characteristics of this mosquito, and it demonstrates the utility of our genetic-based method as a viable alternative to conventional, operationally-demanding MRR experiments.…”

Section: Discussionsupporting

confidence: 71%

“…The above mentioned theoretical approximation of the conditions for Wolbachia initiation and spread [61] assumes isotropic dispersal in a 2-dimensional habitat. Optimal release strategy for the Sterile Insect Technique programs [62], different suppression and replacement strategies [63,64], the effect of larval habitat fragmentation on population crash [65], and confinement and reversibility conditions for threshold-dependent gene drive systems [10] have all been simulated in the spatially explicit models of mosquito populations that applied the exponential dispersal kernel in a 2-dimensional landscape. The approximation of the parametrized dispersal kernel for high-rise landscapes could be achieved by considering the releases of mosquitoes from multiple floors rather than from the ground level only.…”

Section: Discussionmentioning

confidence: 99%

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Using spatial genetics to quantify mosquito dispersal for control programs

Filipović

Hapuarachchi

Tien

et al. 2020

Preprint

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Background: Hundreds of millions of people get a mosquito-borne disease every year, of which nearly one million die. Mosquito-borne diseases are primarily controlled and mitigated through the control of mosquito vectors. Accurately quantified mosquito dispersal in a given landscape is critical for the design and optimization of the control programs, yet the field experiments that measure dispersal of mosquitoes recaptured at certain distances from the release point (markrelease-recapture MRR studies) are challenging for such small insects and often unrepresentative of the insect's true field behavior. Using Singapore as a study site, we show how mosquito dispersal patterns can be characterized from the spatial analyses of genetic relatedness among individuals sampled over a short time span without interruption of their natural behaviors. Methods and Findings:We captured ovipositing females of Aedes aegypti, a major arboviral disease vector, across floors of high-rise apartment blocks and genotyped them using thousands of genome-wide SNP markers. We developed a methodology that produces a dispersal kernel for distance that results from one generation of successful breeding (effective dispersal), using the distances separating full siblings, 2 nd and 3 rd degree relatives (close kin). In Singapore, the estimated dispersal distance kernel was exponential (Laplacian), giving the mean effective dispersal distance (and dispersal kernel spread σ) of 45.2 m (95%CI: 39.7-51.3 m), and 10% probability of dispersal >100 m (95%CI: 92-117 m). Our genetic-based estimates matched the parametrized dispersal kernels from the previously reported MRR experiments. If few close-kin are captured, a conventional genetic isolation-by-distance analysis can be used, and we show that it can produce σ estimates congruent with the close-kin method, conditioned on the accurate estimation of effective population density. We also show that genetic patch size, estimated with the spatial autocorrelation analysis, reflects the spatial extent of the dispersal kernel 'tail' that influences e.g. predictions of critical radii of release zones and Wolbachia wave speed in mosquito replacement programs. Conclusions:We demonstrate that spatial genetics (the newly developed close-kin analysis, and conventional IBD and spatial autocorrelation analyses) can provide a detailed and robust characterization of mosquito dispersal that can guide operational vector control decisions. With the decreasing cost of next generation sequencing, acquisition of spatial genetic data will become increasingly accessible, and given the complexities and criticisms of conventional MRR methods, but the central role of dispersal measures in vector control programs, we recommend genetic-based dispersal characterization as the more desirable means of parameterization.

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Section: Discussionsupporting

confidence: 71%

Section: Discussionmentioning

confidence: 99%

Using spatial genetics to quantify mosquito dispersal for control programs

Filipović

Hapuarachchi

Tien

et al. 2020

Preprint

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“…Though we have not done so here, detailed models are also very valuable in designing deployment strategies (e.g. [20,21]).…”

Section: Discussionmentioning

confidence: 99%

Modelling the suppression of a malaria vector using a CRISPR-Cas9 gene drive to reduce female fertility

2020

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Background: Gene drives based on CRISPR-Cas9 technology are increasingly being considered as tools for reducing the capacity of mosquito populations to transmit malaria, and one of the most promising options is driving endonuclease genes that reduce the fertility of female mosquitoes. In particular, there is much interest in constructs that target the conserved mosquito doublesex (dsx) gene such that the emergence of functional driveresistant alleles is unlikely. Proof of principle that these constructs can lead to substantial population suppression has been obtained in population cages, and they are being evaluated for use in sub-Saharan Africa. Here, we use simulation modelling to understand the factors affecting the spread of this type of gene drive over a one millionsquare kilometre area of West Africa containing substantial environmental and social heterogeneity. Results: We found that a driving endonuclease gene targeting female fertility could lead to substantial reductions in malaria vector populations on a regional scale. The exact level of suppression is influenced by additional fitness costs of the transgene such as the somatic expression of Cas9, and its deposition in sperm or eggs leading to damage to the zygote. In the absence of these costs, or of emergent drive-resistant alleles that restore female fertility, population suppression across the study area is predicted to stabilise at~95% 4 years after releases commence. Small additional fitness costs do not greatly affect levels of suppression, though if the fertility of females whose offspring transmit the construct drops by more than~40%, then population suppression is much less efficient. We show the suppression potential of a drive allele with high fitness costs can be enhanced by engineering it also to express male bias in the progeny of transgenic males. Irrespective of the strength of the drive allele, the spatial model predicts somewhat less suppression than equivalent non-spatial models, in particular in highly seasonal regions where dry season stochasticity reduces drive efficiency. We explored the robustness of these results to uncertainties in mosquito ecology, in particular their method of surviving the dry season and their dispersal rates. Conclusions: The modelling presented here indicates that considerable suppression of vector populations can be achieved within a few years of using a female sterility gene drive, though the impact is likely to be heterogeneous in space and time.

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“…aegypti is too small and too vulnerable to immigration by wild-type mosquitoes [ 8 ]. For the emerging genetic-based control approaches such as gene drive systems [ 9 ], well-characterized mosquito dispersal is crucial for addressing the biosafety concerns around the systems’ confineability and reversibility in the field [ 10 , 11 ].…”

Section: Introductionmentioning

confidence: 99%

Using spatial genetics to quantify mosquito dispersal for control programs

et al. 2020

Self Cite

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Background Hundreds of millions of people get a mosquito-borne disease every year and nearly one million die. Transmission of these infections is primarily tackled through the control of mosquito vectors. The accurate quantification of mosquito dispersal is critical for the design and optimization of vector control programs, yet the measurement of dispersal using traditional mark-release-recapture (MRR) methods is logistically challenging and often unrepresentative of an insect’s true behavior. Using Aedes aegypti (a major arboviral vector) as a model and two study sites in Singapore, we show how mosquito dispersal can be characterized by the spatial analyses of genetic relatedness among individuals sampled over a short time span without interruption of their natural behaviors. Results Using simple oviposition traps, we captured adult female Ae. aegypti across high-rise apartment blocks and genotyped them using genome-wide SNP markers. We developed a methodology that produces a dispersal kernel for distance which results from one generation of successful breeding (effective dispersal), using the distance separating full siblings and 2nd- and 3rd-degree relatives (close kin). The estimated dispersal distance kernel was exponential (Laplacian), with a mean dispersal distance (and dispersal kernel spread σ) of 45.2 m (95% CI 39.7–51.3 m), and 10% probability of a dispersal > 100 m (95% CI 92–117 m). Our genetically derived estimates matched the parametrized dispersal kernels from previous MRR experiments. If few close kin are captured, a conventional genetic isolation-by-distance analysis can be used, as it can produce σ estimates congruent with the close-kin method if effective population density is accurately estimated. Genetic patch size, estimated by spatial autocorrelation analysis, reflects the spatial extent of the dispersal kernel “tail” that influences, for example, the critical radii of release zones and the speed of Wolbachia spread in mosquito replacement programs. Conclusions We demonstrate that spatial genetics can provide a robust characterization of mosquito dispersal. With the decreasing cost of next-generation sequencing, the production of spatial genetic data is increasingly accessible. Given the challenges of conventional MRR methods, and the importance of quantified dispersal in operational vector control decisions, we recommend genetic-based dispersal characterization as the more desirable means of parameterization.

show abstract

Modeling confinement and reversibility of threshold-dependent gene drive systems in spatially-explicitAedes aegyptipopulations

Cited by 8 publications

References 55 publications

Using spatial genetics to quantify mosquito dispersal for control programs

Using spatial genetics to quantify mosquito dispersal for control programs

Modelling the suppression of a malaria vector using a CRISPR-Cas9 gene drive to reduce female fertility

Using spatial genetics to quantify mosquito dispersal for control programs

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