Resource-explicit interactions in spatial population models.

Continuous-space population models can yield significantly different results from their panmictic counterparts when assessing evolutionary, ecological, or population-genetic processes. However, the computational burden of spatial models is typically much greater than that of panmictic models due to the overhead of determining which individuals interact with one another and how strongly they interact. Though these calculations are necessary to model local competition that regulates the population density, they can lead to prohibitively long runtimes. Here, we present a novel modeling method in which the resources available to a population are abstractly represented as an additional layer of the simulation. Instead of interacting directly with one another, individuals interact indirectly via this resource layer. We find that this method closely matches other spatial models, yet can dramatically increase the speed of the model, allowing the simulation of much larger populations. Additionally, models structured in this manner exhibit other desirable characteristics, including more realistic spatial dynamics near the edge of the simulated area, and an efficient route for modeling more complex heterogeneous landscapes.

A framework for identifying fertility gene targets for mammalian pest control.

Fertility-targeted gene drives have been proposed as an ethical genetic approach for managing wild populations of vertebrate pests for public health and conservation benefit. This manuscript introduces a framework to identify and evaluate target gene suitability based on biological gene function, gene expression and results from mouse knockout models. This framework identified 16 genes essential for male fertility and 12 genes important for female fertility that may be feasible targets for mammalian gene drives and other non-drive genetic pest control technology. Further, a comparative genomics analysis demonstrates the conservation of the identified genes across several globally significant invasive mammals. In addition to providing important considerations for identifying candidate genes, our framework and the genes identified in this study may have utility in developing additional pest control tools such as wildlife contraceptives.

A framework for identifying fertility gene targets for mammalian pest control.

Fertility-targeted gene drives have been proposed as an ethical genetic approach for managing wild populations of vertebrate pests for public health and conservation benefit.This manuscript introduces a framework to identify and evaluate target gene suitability based on biological gene function, gene expression, and results from mouse knockout models.This framework identified 16 genes essential for male fertility and 12 genes important for female fertility that may be feasible targets for mammalian gene drives and other non-drive genetic pest control technology. Further, a comparative genomics analysis demonstrates the conservation of the identified genes across several globally significant invasive mammals.In addition to providing important considerations for identifying candidate genes, our framework and the genes identified in this study may have utility in developing additional pest control tools such as wildlife contraceptives.

Anopheles homing suppression drive candidates exhibit unexpected performance differences in simulations with spatial structure.

Recent experiments have produced several Anopheles gambiae homing gene drives that disrupt female fertility genes, thereby eventually inducing population collapse. Such drives may be highly effective tools to combat malaria. One such homing drive, based on the zpg promoter driving CRISPR/Cas9, was able to eliminate a cage population of mosquitoes. A second version, purportedly improved upon the first by incorporating an X-shredder element (which biases inheritance towards male offspring), was similarly successful. Here, we analyze experimental data from each of these gene drives to extract their characteristics and performance parameters and compare these to previous interpretations of their experimental performance. We assess each suppression drive within an individual-based simulation framework that models mosquito population dynamics in continuous space. We find that the combined homing/X-shredder drive is actually less effective at population suppression within the context of our mosquito population model. In particular, the combined drive often fails to completely suppress the population, instead resulting in an unstable equilibrium between drive and wild-type alleles. By contrast, otherwise similar drives based on the nos promoter may prove to be more promising candidates for future development than originally thought.

Fitness effects of CRISPR endonucleases in Drosophila melanogaster populations.

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 provides a highly efficient and flexible genome editing technology with numerous potential applications ranging from gene therapy to population control. Some proposed applications involve the integration of CRISPR/Cas9 endonucleases into an organism's genome, which raises questions about potentially harmful effects to the transgenic individuals. One example for which this is particularly relevant are CRISPR-based gene drives conceived for the genetic alteration of entire populations. The performance of such drives can strongly depend on fitness costs experienced by drive carriers, yet relatively little is known about the magnitude and causes of these costs. Here, we assess the fitness effects of genomic CRISPR/Cas9 expression in Drosophila melanogaster cage populations by tracking allele frequencies of four different transgenic constructs that allow us to disentangle 'direct' fitness costs due to the integration, expression, and target-site activity of Cas9, from fitness costs due to potential off-target cleavage. Using a maximum likelihood framework, we find that a model with no direct fitness costs but moderate costs due to off-target effects fits our cage data best. Consistent with this, we do not observe fitness costs for a construct with Cas9HF1, a high-fidelity version of Cas9. We further demonstrate that using Cas9HF1 instead of standard Cas9 in a homing drive achieves similar drive conversion efficiency. These results suggest that gene drives should be designed with high-fidelity endonucleases and may have implications for other applications that involve genomic integration of CRISPR endonucleases.

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

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.

Design and analysis of CRISPR-based underdominance toxin-antidote gene drives.

CRISPR gene drive systems offer a mechanism for transmitting a desirable transgene throughout a population for purposes ranging from vector-borne disease control to invasive species suppression. In this simulation study, we assess the performance of several CRISPR-based underdominance gene drive constructs employing toxin-antidote (TA) principles. These drives disrupt the wild-type version of an essential gene using a CRISPR nuclease (the toxin) while simultaneously carrying a recoded version of the gene (the antidote). Drives of this nature allow for releases that could be potentially confined to a desired geographic location. This is because such drives have a nonzero-invasion threshold frequency required for the drive to spread through the population. We model drives which target essential genes that are either haplosufficient or haplolethal, using nuclease promoters with expression restricted to the germline, promoters that additionally result in cleavage activity in the early embryo from maternal deposition, and promoters that have ubiquitous somatic expression. We also study several possible drive architectures, considering both "same-site" and "distant-site" systems, as well as several reciprocally targeting drives. Together, these drive variants provide a wide range of invasion threshold frequencies and options for both population modification and suppression. Our results suggest that CRISPR TA underdominance drive systems could allow for the design of flexible and potentially confinable gene drive strategies.

Suppression gene drive in continuous space can result in unstable persistence of both drive and wild-type alleles.

Rapid evolutionary processes can produce drastically different outcomes when studied in panmictic population models vs. spatial models. One such process is gene drive, which describes the spread of "selfish" genetic elements through a population. Engineered gene drives are being considered for the suppression of disease vectors or invasive species. While laboratory experiments and modelling in panmictic populations have shown that such drives can rapidly eliminate a population, it remains unclear if these results translate to natural environments where individuals inhabit a continuous landscape. Using spatially explicit simulations, we show that the release of a suppression drive can result in what we term "chasing" dynamics, in which wild-type individuals recolonize areas where the drive has locally eliminated the population. Despite the drive subsequently reconquering these areas, complete population suppression often fails to occur or is substantially delayed. This increases the likelihood that the drive is lost or that resistance evolves. We analyse how chasing dynamics are influenced by the type of drive, its efficiency, fitness costs, and ecological factors such as the maximal growth rate of the population and levels of dispersal and inbreeding. We find that chasing is more common for lower efficiency drives when dispersal is low and that some drive mechanisms are substantially more prone to chasing behaviour than others. Our results demonstrate that the population dynamics of suppression gene drives are determined by a complex interplay of genetic and ecological factors, highlighting the need for realistic spatial modelling to predict the outcome of drive releases in natural populations.

Population Dynamics of Underdominance Gene Drive Systems in Continuous Space.

Underdominance systems can quickly spread through a population, but only when introduced in considerable numbers. This promises a gene drive mechanism that is less invasive than homing drives, potentially enabling new approaches in the fight against vector-borne diseases. If regional confinement can indeed be achieved, the decision-making process for a release would likely be much simpler compared to other, more invasive types of drives. The capacity of underdominance gene drive systems to spread in a target population without invading other populations is typically assessed via network models of panmictic demes linked by migration. However, it remains less clear how such systems would behave in more realistic population models where organisms move over a continuous landscape. Here, we use individual-based simulations to study the dynamics of several proposed underdominance systems in continuous-space. We find that all these systems can fail to persist in such environments, even after an initially successful establishment in the release area, confirming previous theoretical results from diffusion theory. At the same time, we find that a two-locus two-toxin-antidote system can invade connected demes through a narrow migration corridor. This suggests that the parameter space where underdominance systems can establish and persist in a release area while at the same time remaining confined to that area could be quite limited, depending on how a population is spatially structured. Overall, these results indicate that realistic spatial context must be considered when assessing strategies for the deployment of underdominance drives.

Computational and experimental performance of CRISPR homing gene drive strategies with multiplexed gRNAs.

The rapid evolution of resistance alleles poses a major obstacle for genetic manipulation of populations with CRISPR homing gene drives. One proposed solution is using multiple guide RNAs (gRNAs), allowing a drive to function even if some resistant target sites are present. Here, we develop a model of homing mechanisms parameterized by experimental studies. Our model incorporates several factors affecting drives with multiple gRNAs, including timing of cleavage, reduction in homology-directed repair efficiency due to imperfect homology, Cas9 activity saturation, gRNA activity level variance, and incomplete homology-directed repair. We find that homing drives have an optimal number of gRNAs, usually between two and eight, depending on the specific drive type and performance parameters. These results contradict the notion that resistance rates can be reduced to arbitrarily low levels by gRNA multiplexing and highlight the need for combined approaches to counter resistance evolution in CRISPR homing drives.

Performance analysis of novel toxin-antidote CRISPR gene drive systems.

BACKGROUND: CRISPR gene drive systems allow the rapid spread of a genetic construct throughout a population. Such systems promise novel strategies for the management of vector-borne diseases and invasive species by suppressing a target population or modifying it with a desired trait. However, current homing-type drives have two potential shortcomings. First, they can be thwarted by the rapid evolution of resistance. Second, they lack any mechanism for confinement to a specific target population. In this study, we conduct a comprehensive performance assessment of several new types of CRISPR-based gene drive systems employing toxin-antidote (TA) principles, which should be less prone to resistance and allow for the confinement of drives to a target population due to invasion frequency thresholds. RESULTS: The underlying principle of the proposed CRISPR toxin-antidote gene drives is to disrupt an essential target gene while also providing rescue by a recoded version of the target as part of the drive allele. Thus, drive alleles tend to remain viable, while wild-type targets are disrupted and often rendered nonviable, thereby increasing the relative frequency of the drive allele. Using individual-based simulations, we show that Toxin-Antidote Recessive Embryo (TARE) drives targeting an haplosufficient but essential gene (lethal when both copies are disrupted) can enable the design of robust, regionally confined population modification strategies with high flexibility in choosing promoters and targets. Toxin-Antidote Dominant Embryo (TADE) drives require a haplolethal target gene and a germline-restricted promoter, but they could permit faster regional population modification and even regionally confined population suppression. Toxin-Antidote Dominant Sperm (TADS) drives can be used for population modification or suppression. These drives are expected to spread rapidly and could employ a variety of promoters, but unlike TARE and TADE, they would not be regionally confined and also require highly specific target genes. CONCLUSIONS: Overall, our results suggest that CRISPR-based TA gene drives provide promising candidates for flexible ecological engineering strategies in a variety of organisms.