Overcoming evolved resistance to population-suppressing homing-based gene drives

Abstract

The use of homing-based gene drive systems to modify or suppress wild populations of a given species has been proposed as a solution to a number of significant ecological and public healthrelated problems, including the control of mosquito-borne diseases. The recent development of a CRISPR-Cas9-based homing system for the suppression of Anopheles gambiae, the main African malaria vector, is encouraging for this approach; however, with current designs, the slow emergence of homing-resistant alleles is expected to result in suppressed populations rapidly rebounding, as homing-resistant alleles have a significant fitness advantage over functional, population-suppressing homing alleles. To explore this concern, we develop a mathematical model to estimate tolerable rates of homing-resistant allele generation to suppress a wild population of a given size. Our results suggest that, to achieve meaningful population suppression, tolerable rates of resistance allele generation are orders of magnitude smaller than those observed for current designs for CRISPR-Cas9-based homing systems. To remedy this, we propose a homing system architecture in which guide RNAs (gRNAs) are multiplexed, increasing the effective homing rate and decreasing the effective resistant allele generation rate.Modeling results suggest that the size of the population that can be suppressed increases exponentially with the number of multiplexed gRNAs and that, with six multiplexed gRNAs, a . CC-BY-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/088427 doi: bioRxiv preprint first posted online Nov. 17, 2016; 2 mosquito species could potentially be suppressed on a continental scale. We also demonstrate successful multiplexing in vivo in Drosophila melanogaster using a ribozyme-gRNA-ribozyme (RGR) approach -a strategy that could readily be adapted to engineer stable, homing-based suppression drives in relevant organisms. Significance StatementHoming-based gene drive systems have the potential to rapidly invade, suppress, and eliminate wild populations of a given species. The recent engineering of a CRISPR-Cas9-based homing drive system in the main African malaria vector, Anopheles gambiae, highlights the potential application of these systems to global public health; however, concerns have been raised regarding the evolution of alleles resistant to the homing system, which have a significant selective advantage over functioning homing alleles. To mitigate this, we propose a design in which guide RNAs are multiplexed, reducing the emergence rate of homing-resistant alleles.Using a mathematical model, we show how this design could potentially enable population suppression on a continental scale. We also demonstrate a multiplexing design in vivo in Drosophila melanogaster.

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

“…The MGDrivE framework is a genetic and spatial extension of the lumped age-class model of mosquito ecology [24] modified and applied by Deredec et al [25] to the spread of homing gene drive systems, and by Marshall et al [26] to population-suppressing homing systems in the presence of resistant alleles. The framework incorporates the egg, larval, pupal and adult life stages, with egg genotypes determined by maternal and paternal genotypes and the allelic inheritance pattern.…”

“…For a homing-based drive system, for instance, the list of input parameters should include the homing efficiency, the rate of in-frame resistant allele generation and the rate of out-of-frame or otherwise costly resistant allele generation [26][27][28]. Input parameters also include those associated with organisms having each genotype -for instance: a) genotype-specific fertility rates, b) male mating fitness, c) sex bias at emergence, d) adult survival rates, and e) male and female pupatory success.…”

“…At the time of publication, the MGDrivE package includes inheritance cubes for: a) standard Mendelian inheritance, b) homing-based drive intended for population replacement or suppression [26,27,29,30], c) Medea (a maternal toxin linked to a zygotic antidote) [31], d) other toxin-antidote-based underdominant systems such as UD MEL [13,15,32], e) reciprocal chromosomal translocations [14,33], f) Wolbachia [34], and g) the RIDL system [35] (release of insects carrying a dominant lethal gene). Details of each of these systems are provided in the S1 User Manual.…”

“…Here, nodes are colored according to their community (as detected by the DBSCAN clustering algorithm [49]), with sizes proportional to their "betweenness centrality" -a measure of their connectedness to other nodes in terms of number of shortest paths that flow through them [50]. resistant alleles [26]. In the stochastic implementation of MGDrivE, daily egg production follows a Poisson distribution, offspring genotype follows a multinomial distribution informed by parental genotypes and the inheritance pattern of the gene drive system, mate choice follows a multinomial distribution determined by adult genotype frequencies, and survival and death events follow binomial distributions at the population level.…”

“…This is similar to the first CRISPR-based homing construct demonstrated in An. gambiae, although with a higher homing efficiency that could be achieved through guide RNA multiplexing [26]. Lines of code that differ for this system are shown in Code sample 2.…”