Mosquito-transmitted diseases, including malaria, dengue and Zika, continue to take a devastating toll. Gene drive systems could provide a new strategy for controlling these diseases by spreading genetically engineered alleles into vector populations, such as allelic variants that make the insects resistant to a pathogen or deleterious alleles than directly suppress their populations. The recently developed CRISPR/Cas9 homing gene drive system promises to be a highly adaptable mechanism that works by converting heterozygotes for the driver construct into homozygotes. However, it remains unclear whether this mechanism will work in wild populations given the expected high rate of generation of resistance alleles, which are created by the drive mechanism itself when cleavage is repaired by nonhomologous end joining. Another proposed gene drive system, Medea, likely suffers less from the generation of resistance alleles, but it spreads more slowly and is highly sensitive to fitness costs. The goal of our project is to identify and quantify parameters that are critical to determining whether these systems can in fact spread in diverse, natural populations. In our first aim, we will employ laboratory examples of homing drivers and Medea drivers to quantify the drive efficiency and origination rate of resistance alleles in genetically diverse but well characterized lines of the model organism Drosophila melanogaster. We will then use these results to map the genetic loci associated with differences in drive efficiency and resistance levels.
Our second aim will determine the ability of each gene drive system to invade genetically diverse populations. For this purpose, a small number of gene drive flies will be introduced into population cages with a mix of Global Diversity Line flies. Phenotype frequencies will be tracked over several generations to determine the ability of the gene drive to successfully invade the population. This work will be done in a state-of-the-art arthropod containment lab to prevent escape of transgenic insects. In our third aim, we will compare the ability of homing drivers and Medea drivers to spread in geographically structured populations using sophisticated population genetic simulations. We will identify the parameters that will allow a gene drive system to establish, spread, and either fix or persist sufficiently long in a large natural population under realistic assumptions of demography and population structure. Overall our experiments and modeling will provide crucial data for predicting the dynamics of gene drive systems in natural target populations. The conclusions from our studies will play an important role in designing and implementing the next generation of gene drive systems for optimal performance in realistic populations.
Gene drive systems designed to spread genetically-modified alleles throughout an insect population are a promising new way of reducing the number of people infected with malaria, dengue, Zika, and other mosquito- borne diseases. However, we are not certain which type of gene drive may function best in wild populations, since each has advantages and disadvantages. We propose to thoroughly quantify and characterize gene drive efficiency and resistance allele generation in diverse genetic backgrounds for two different types of gene drives in the model organism Drosophila melanogaster.
