scholarly journals Locally Fixed Alleles: A method to localize gene drive to island populations

2019 ◽  
Author(s):  
Jaye Sudweeks ◽  
Brandon Hollingsworth ◽  
Dimitri V. Blondel ◽  
Karl J. Campbell ◽  
Sumit Dhole ◽  
...  
Keyword(s):  
Target Population ◽  
Small Island ◽  
Island Population ◽  
Threshold Condition ◽  
Gene Drive ◽  
Population Replacement ◽  
Multiple Alleles ◽  
Island Populations ◽  
Wide Range ◽  
Parameter Values

AbstractInvasive species pose a major threat to biodiversity on islands. While successes have been achieved using traditional removal methods, such as toxicants aimed at rodents, these approaches have limitations and various off-target effects on island ecosystems. Gene drive technologies designed to eliminate a population provide an alternative approach, but the potential for drive-bearing individuals to escape from the target release area and impact populations elsewhere is a major concern. Here we propose the “Locally Fixed Alleles” approach as a novel means for localizing elimination by a drive to an island population that exhibits significant genetic isolation from neighboring populations. Our approach is based on the assumption that in small island populations of rodents, genetic drift will lead to multiple genomic alleles becoming fixed. In contrast, multiple alleles are likely to be maintained in larger populations on mainlands. Utilizing the high degree of genetic specificity achievable using homing drives, for example based on the CRISPR/Cas9 system, our approach aims at employing one or more locally fixed alleles as the target for a gene drive on a particular island. Using mathematical modeling, we explore the feasibility of this approach and the degree of localization that can be achieved. We show that across a wide range of parameter values, escape of the drive to a neighboring population in which the target allele is not fixed will at most lead to modest transient suppression of the non-target population. While the main focus of this paper is on elimination of a rodent pest from an island, we also discuss the utility of the locally fixed allele approach for the goals of population suppression or population replacement. Our analysis also provides a threshold condition for the ability of a gene drive to invade a partially resistant population.

scholarly journals Locally Fixed Alleles: A method to localize gene drive to island populations

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Jaye Sudweeks ◽  
Brandon Hollingsworth ◽  
Dimitri V. Blondel ◽  
Karl J. Campbell ◽  
Sumit Dhole ◽  
...  
Keyword(s):  
Target Population ◽  
Small Island ◽  
Island Population ◽  
Threshold Condition ◽  
Gene Drive ◽  
Population Replacement ◽  
Multiple Alleles ◽  
Island Populations ◽  
Wide Range ◽  
Parameter Values

Abstract Invasive species pose a major threat to biodiversity on islands. While successes have been achieved using traditional removal methods, such as toxicants aimed at rodents, these approaches have limitations and various off-target effects on island ecosystems. Gene drive technologies designed to eliminate a population provide an alternative approach, but the potential for drive-bearing individuals to escape from the target release area and impact populations elsewhere is a major concern. Here we propose the “Locally Fixed Alleles” approach as a novel means for localizing elimination by a drive to an island population that exhibits significant genetic isolation from neighboring populations. Our approach is based on the assumption that in small island populations of rodents, genetic drift will lead to alleles at multiple genomic loci becoming fixed. In contrast, multiple alleles are likely to be maintained in larger populations on mainlands. Utilizing the high degree of genetic specificity achievable using homing drives, for example based on the CRISPR/Cas9 system, our approach aims at employing one or more locally fixed alleles as the target for a gene drive on a particular island. Using mathematical modeling, we explore the feasibility of this approach and the degree of localization that can be achieved. We show that across a wide range of parameter values, escape of the drive to a neighboring population in which the target allele is not fixed will at most lead to modest transient suppression of the non-target population. While the main focus of this paper is on elimination of a rodent pest from an island, we also discuss the utility of the locally fixed allele approach for the goals of population suppression or population replacement. Our analysis also provides a threshold condition for the ability of a gene drive to invade a partially resistant population.

scholarly journals Estimating gene flow in island populations

1996 ◽  
Vol 67 (2) ◽  
pp. 147-158 ◽  
Author(s):  
Bruce Rannala ◽  
J. A. Hartigan
Keyword(s):  
Gene Flow ◽  
Island Model ◽  
Least Mean Square ◽  
Island Populations ◽  
Wide Range ◽  
Continuous Generation ◽  
Subdivided Populations ◽  
The Individual ◽  
Pseudo Maximum Likelihood ◽  
Parameter Values

SummaryA new method is presented for estimating the rate of gene flow into island populations using the distribution of alleles in samples from a number of islands. The pseudo maximum likelihood estimator (PMLE) that we derive may be applied to species with either discrete or continuous generation times. For Wright's discrete-generation island model, the method provides an estimate of θ = 2Nm where N is the (haploid) population size on each island and m is the fraction of individuals replaced by immigrants in each generation. For a continuous-generation island model, the corresponding parameter φ is the ratio of the immigration rate φ to the individual birth rate λ. Monte Carlo simulations are used to compare the statistical properties of the PMLE with those of two alternative estimatorsof θ derived from Wright's F-statistics. The PMLE is shown to have greatest efficiency (least mean square error) in most cases for a wide range of sample sizes and parameter values. The PMLE is applied to estimate θ using mtDNA haplotypes and allozymes for subdivided populations of African elephants and Channel Island foxes.

scholarly journals Tethered homing gene drives: a new design for spatially restricted population replacement and suppression

2018 ◽  
Author(s):  
Sumit Dhole ◽  
Alun L. Lloyd ◽  
Fred Gould
Keyword(s):  
Mathematical Model ◽  
Genetic Load ◽  
Target Population ◽  
Gene Drive ◽  
Population Replacement ◽  
Additional Release ◽  
New Gene ◽  
Gene Drives ◽  
Population Suppression ◽  
Proof Of Principle

ABSTRACTOptimism regarding potential epidemiological and conservation applications of modern gene drives is tempered by concern about the potential unintended spread of engineered organisms beyond the target population. In response, several novel gene drive approaches have been proposed that can, under certain conditions, locally alter characteristics of a population. One challenge for these gene drives is the difficulty of achieving high levels of localized population suppression without very large releases in face of gene flow. We present a new gene drive system, Tethered Homing (TH), with improved capacity for localized population alteration, especially for population suppression. The TH drive is based on driving a payload gene using a homing construct that is anchored to a spatially restricted gene drive. We use a proof of principle mathematical model to show the dynamics of a TH drive that uses engineered underdominance as an anchor. This system is composed of a split homing drive and a two-locus engineered underdominance drive linked to one part of the split drive (the Cas endonuclease). In addition to improved localization, the TH system offers the ability to gradually adjust the genetic load in a population after the initial alteration, with minimal additional release effort.

scholarly journals Double drives and private alleles for localised population genetic control

PLoS Genetics ◽  
2021 ◽  
Vol 17 (3) ◽  
pp. e1009333
Author(s):  
Katie Willis ◽  
Austin Burt
Keyword(s):  
Genetic Control ◽  
Population Genetic ◽  
Genomic Analysis ◽  
Target Population ◽  
Pest Species ◽  
Gene Drive ◽  
Population Replacement ◽  
Target Populations ◽  
Control Disease ◽  
Alternative Designs

Synthetic gene drive constructs could, in principle, provide the basis for highly efficient interventions to control disease vectors and other pest species. This efficiency derives in part from leveraging natural processes of dispersal and gene flow to spread the construct and its impacts from one population to another. However, sometimes (for example, with invasive species) only specific populations are in need of control, and impacts on non-target populations would be undesirable. Many gene drive designs use nucleases that recognise and cleave specific genomic sequences, and one way to restrict their spread would be to exploit sequence differences between target and non-target populations. In this paper we propose and model a series of low threshold double drive designs for population suppression, each consisting of two constructs, one imposing a reproductive load on the population and the other inserted into a differentiated locus and controlling the drive of the first. Simple deterministic, discrete-generation computer simulations are used to assess the alternative designs. We find that the simplest double drive designs are significantly more robust to pre-existing cleavage resistance at the differentiated locus than single drive designs, and that more complex designs incorporating sex ratio distortion can be more efficient still, even allowing for successful control when the differentiated locus is neutral and there is up to 50% pre-existing resistance in the target population. Similar designs can also be used for population replacement, with similar benefits. A population genomic analysis of CRISPR PAM sites in island and mainland populations of the malaria mosquitoAnopheles gambiaeindicates that the differentiation needed for our methods to work can exist in nature. Double drives should be considered when efficient but localised population genetic control is needed and there is some genetic differentiation between target and non-target populations.

scholarly journals Gene Drives Across Engineered Fitness Valleys: Modeling a Design to Prevent Drive Spillover

2020 ◽  
Author(s):  
Frederik J.H. de Haas ◽  
Sarah P. Otto
Keyword(s):  
Local Population ◽  
Target Population ◽  
Drive System ◽  
High Threshold ◽  
Gene Drive ◽  
Time Model ◽  
Population Replacement ◽  
Low Threshold ◽  
Drive Systems ◽  
Gene Drives

1AbstractEngineered gene drive techniques for population replacement and/or suppression have potential for tackling complex challenges, including reducing the spread of diseases and invasive species. Unfortunately, the self-propelled behavior of drives can lead to the spread of transgenic elements beyond the target population, which is concerning. Gene drive systems with a low threshold frequency for invasion, such as homing-based gene drive systems, require initially few transgenic individuals to spread and are therefore easy to implement. However their ease of spread presents a double-edged sword; their low threshold makes these drives much more susceptible to spread outside of the target population (spillover). We model a proposed drive system that transitions in time from a low threshold drive system (homing-based gene drive) to a high threshold drive system (underdominance) using daisy chain technology. This combination leads to a spatially restricted drive strategy, while maintaining an attainable release threshold. We develop and analyze a discrete-time model as proof of concept and find that this technique effectively generates stable local population suppression, while preventing the spread of transgenic elements beyond the target population under biologically realistic parameters.

scholarly journals MGDrivE: A modular simulation framework for the spread of gene drives through spatially-explicit mosquito populations

2018 ◽  
Author(s):  
Héctor M. Sánchez C. ◽  
Sean L. Wu ◽  
Jared B. Bennett ◽  
John M. Marshall
Keyword(s):  
Spatial Dynamics ◽  
Population Level ◽  
Spatially Explicit ◽  
Pest Species ◽  
Gene Drive ◽  
Simulation Framework ◽  
Population Replacement ◽  
Wide Range ◽  
Drive Systems ◽  
Genetic Simulation

AbstractMalaria, dengue, Zika, and other mosquito-borne diseases continue to pose a major global health burden through much of the world, despite the widespread distribution of insecticide-based tools and antimalarial drugs. The advent of CRISPR/Cas9-based gene editing and its demonstrated ability to streamline the development of gene drive systems has reignited interest in the application of this technology to the control of mosquitoes and the diseases they transmit. The versatility of this technology has also enabled a wide range of gene drive architectures to be realized, creating a need for their population-level and spatial dynamics to be explored. To this end, we present MGDrivE (Mosquito Gene Drive Explorer): a simulation framework designed to investigate the population dynamics of a variety of gene drive architectures and their spread through spatially-explicit mosquito populations. A key strength of the MGDrivE framework is its modularity: a) a genetic inheritance module accommodates the dynamics of gene drive systems displaying user-defined inheritance patterns, b) a population dynamic module accommodates the life history of a variety of mosquito disease vectors and insect agricultural pest species, and c) a landscape module accommodates the distribution of insect metapopulations connected by migration in space. Example MGDrivE simulations are presented to demonstrate the application of the framework to CRISPR/Cas9-based homing gene drive for: a) driving a disease-refractory gene into a population (i.e. population replacement), and b) disrupting a gene required for female fertility (i.e. population suppression), incorporating homing-resistant alleles in both cases. We compare MGDrivE with other genetic simulation packages, and conclude with a discussion of future directions in gene drive modeling.

scholarly journals Double drives and private alleles for localised population genetic control

2021 ◽  
Author(s):  
Katie Willis ◽  
Austin Burt
Keyword(s):  
Genetic Control ◽  
Population Genetic ◽  
Genomic Analysis ◽  
Target Population ◽  
Pest Species ◽  
Gene Drive ◽  
Population Replacement ◽  
Target Populations ◽  
Mosquito Anopheles Gambiae ◽  
Control Disease

Synthetic gene drive constructs could, in principle, provide the basis for highly efficient interventions to control disease vectors and other pest species. This efficiency derives in part from leveraging natural processes of dispersal and gene flow to spread the construct and its impacts from one population to another. However, sometimes (for example, with invasive species) only specific populations are in need of control, and impacts on non-target populations would be undesirable. Many gene drive designs use nucleases that recognise and cleave specific genomic sequences, and one way to restrict their spread would be to exploit sequence differences between target and non-target populations. In this paper we propose and model a series of low threshold double drive designs for population suppression, each consisting of two constructs, one imposing a reproductive load on the population and the other inserted into a differentiated locus and controlling the drive of the first. Simple deterministic, discrete-generation computer simulations are used to assess the alternative designs. We find that the simplest double drive designs are significantly more robust to pre-existing cleavage resistance at the differentiated locus than single drive designs, and that more complex designs incorporating sex ratio distortion can be more efficient still, even allowing for successful control when the differentiated locus is neutral and there is up to 50% pre-existing resistance in the target population. Similar designs can also be used for population replacement, with similar benefits. A population genomic analysis of PAM sites in island and mainland populations of the malaria mosquito Anopheles gambiae indicates that the differentiation needed for our methods to work can exist in nature. Double drives should be considered when efficient but localised population genetic control is needed and there is some genetic differentiation between target and non-target populations.

scholarly journals Modeling CRISPR gene drives for suppression of invasive rodents

2020 ◽  
Author(s):  
Samuel E. Champer ◽  
Nathan Oakes ◽  
Ronin Sharma ◽  
Pablo García-Díaz ◽  
Jackson Champer ◽  
...  
Keyword(s):  
Machine Learning ◽  
Population Model ◽  
Supervised Machine Learning ◽  
Sensitivity Analyses ◽  
Island Population ◽  
Gene Drive ◽  
Wide Range ◽  
Outcome Space ◽  
Drive Systems ◽  
Invasive Rodents

ABSTRACTInvasive rodent populations pose a threat to biodiversity across the globe. When confronted with these new invaders, native species that evolved independently are often defenseless. CRISPR gene drive systems could provide a solution to this problem by spreading transgenes among invaders that induce population collapse. Such systems might be deployed even where traditional control methods are impractical or prohibitively expensive. Here, we develop a high-fidelity model of an island population of invasive rodents that includes three types of suppression gene drive systems. The individual-based model is spatially explicit and allows for overlapping generations and a fluctuating population size. Our model includes variables for drive fitness, efficiency, resistance allele formation rate, as well as a variety of ecological parameters. The computational burden of evaluating a model with such a high number of parameters presents a substantial barrier to a comprehensive understanding of its outcome space. We therefore accompany our population model with a meta-model that utilizes supervised machine learning to approximate the outcome space of the underlying model with a high degree of accuracy. This enables us to conduct an exhaustive inquiry of the population model, including variance-based sensitivity analyses using tens of millions of evaluations. Our results suggest that sufficiently capable gene drive systems have the potential to eliminate island populations of rodents under a wide range of demographic assumptions, but only if resistance can be kept to a minimal level. This study highlights the power of supervised machine learning for identifying the key parameters and processes that determine the population dynamics of a complex evolutionary system.

scholarly journals Modeling CRISPR gene drives for suppression of invasive rodents using a supervised machine learning framework

2021 ◽  
Vol 17 (12) ◽  
pp. e1009660
Author(s):  
Samuel E. Champer ◽  
Nathan Oakes ◽  
Ronin Sharma ◽  
Pablo García-Díaz ◽  
Jackson Champer ◽  
...  
Keyword(s):  
Machine Learning ◽  
Population Model ◽  
Supervised Machine Learning ◽  
Sensitivity Analyses ◽  
Island Population ◽  
Gene Drive ◽  
Wide Range ◽  
Outcome Space ◽  
Drive Systems ◽  
Invasive Rodents

Invasive rodent populations pose a threat to biodiversity across the globe. When confronted with these invaders, native species that evolved independently are often defenseless. CRISPR gene drive systems could provide a solution to this problem by spreading transgenes among invaders that induce population collapse, and could be deployed even where traditional control methods are impractical or prohibitively expensive. Here, we develop a high-fidelity model of an island population of invasive rodents that includes three types of suppression gene drive systems. The individual-based model is spatially explicit, allows for overlapping generations and a fluctuating population size, and includes variables for drive fitness, efficiency, resistance allele formation rate, as well as a variety of ecological parameters. The computational burden of evaluating a model with such a high number of parameters presents a substantial barrier to a comprehensive understanding of its outcome space. We therefore accompany our population model with a meta-model that utilizes supervised machine learning to approximate the outcome space of the underlying model with a high degree of accuracy. This enables us to conduct an exhaustive inquiry of the population model, including variance-based sensitivity analyses using tens of millions of evaluations. Our results suggest that sufficiently capable gene drive systems have the potential to eliminate island populations of rodents under a wide range of demographic assumptions, though only if resistance can be kept to a minimal level. This study highlights the power of supervised machine learning to identify the key parameters and processes that determine the population dynamics of a complex evolutionary system.

scholarly journals β-Lactoglobulin Adsorption Layers at the Water/Air Surface: 5. Adsorption Isotherm and Equation of State Revisited, Impact of pH

2021 ◽  
Vol 5 (1) ◽  
pp. 14
Author(s):  
Georgi G. Gochev ◽  
Volodymyr I. Kovalchuk ◽  
Eugene V. Aksenenko ◽  
Valentin B. Fainerman ◽  
Reinhard Miller
Keyword(s):  
Theoretical Description ◽  
Fluid Interfaces ◽  
Interfacial Behavior ◽  
Current State ◽  
Air Interface ◽  
Direct Measurements ◽  
Wide Range ◽  
Dilational Viscoelasticity ◽  
Parameter Values ◽  
Β Lactoglobulin

The theoretical description of the adsorption of proteins at liquid/fluid interfaces suffers from the inapplicability of classical formalisms, which soundly calls for the development of more complicated adsorption models. A Frumkin-type thermodynamic 2-d solution model that accounts for nonidealities of interface enthalpy and entropy was proposed about two decades ago and has been continuously developed in the course of comparisons with experimental data. In a previous paper we investigated the adsorption of the globular protein β-lactoglobulin at the water/air interface and used such a model to analyze the experimental isotherms of the surface pressure, Π(c), and the frequency-, f-, dependent surface dilational viscoelasticity modulus, E(c)f, in a wide range of protein concentrations, c, and at pH 7. However, the best fit between theory and experiment proposed in that paper appeared incompatible with new data on the surface excess, Γ, obtained from direct measurements with neutron reflectometry. Therefore, in this work, the same model is simultaneously applied to a larger set of experimental dependences, e.g., Π(c), Γ(c), E(Π)f, etc., with E-values measured strictly in the linear viscoelasticity regime. Despite this ambitious complication, a best global fit was elaborated using a single set of parameter values, which well describes all experimental dependencies, thus corroborating the validity of the chosen thermodynamic model. Furthermore, we applied the model in the same manner to experimental results obtained at pH 3 and pH 5 in order to explain the well-pronounced effect of pH on the interfacial behavior of β-lactoglobulin. The results revealed that the propensity of β-lactoglobulin globules to unfold upon adsorption and stretch at the interface decreases in the order pH 3 > pH 7 > pH 5, i.e., with decreasing protein net charge. Finally, we discuss advantages and limitations in the current state of the model.

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