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

Abstract

Rapid evolutionary processes can produce drastically different outcomes when studied in panmictic population models versus spatial models where the rate of evolution is limited by dispersal. One such process is gene drive, which allows "selfish" genetic elements to quickly spread through a population. Engineered gene drive systems are being considered as a means for suppressing disease vector populations or invasive species. While laboratory experiments and modeling in panmictic populations have shown that such drives can rapidly eliminate a population, it is not yet clear how well these results translate to natural environments where individuals inhabit a continuous landscape. Using spatially explicit simulations, we show that instead of population elimination, release of a suppression drive can result in what we term "chasing" dynamics. This describes a condition in which wild-type individuals quickly recolonize areas where the drive has locally eliminated the population. Despite the drive subsequently chasing the wild-type allele into these newly re-colonized areas, complete population suppression often fails or is substantially delayed. This delay increases the likelihood that the drive becomes lost or that resistance evolves. We systematically analyze how chasing dynamics are influenced by the type of drive, its efficiency, fitness costs, as well as ecological and demographic factors such as the maximal growth rate of the population, the migration rate, and the level of inbreeding. We find that chasing is generally more common for lower efficiency drives and in populations with low dispersal. However, we further find that some drive mechanisms are substantially more prone to chasing behavior 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 modeling to predict the outcome of drive releases in natural populations.

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

“…First, additional aspects of mosquito ecology could be incorporated. These include incorporating population spatial structure at a finer resolution than we have done here [ 8 , 16 ], different forms of density dependence [ 31 ], and the influence of local ecology and topology on mosquito dispersal (e.g. [ 32 ]).…”

“…In the West African spatial model, we found that a polymorphism often occurred where the wild type persisted through colonisation-extinction dynamics. Populations are locally extinguished by the driving Y chromosome only for the vacated sites to be recolonised by mosquitoes dispersing from unaffected populations carrying normal Y chromosomes [ 8 , 14 – 16 ]. Population suppression still happened with this form of dynamics, but it was not as great as in the model without spatial structure.…”

Novel combination of CRISPR-based gene drives eliminates resistance and localises spread

“…In complex landscapes, it might be that gene drive spread is slower or even regionally confined in some situations. Additionally, there might be spatial dynamics to gene drives in general such as 'chasing', which is the perpetual escaping and chasing of wildtype and gene drive animals (Champer et al, 2019). Further efforts are necessary to create a more realistic spatial model before we can consider using a gene drive.…”

“…The rate and extent of suppression can be controlled by the number of gene drive animals supplemented and how many daisy elements the introduced animals carry. In contrast to homing gene drive, X-shredder gene drives face problems with the formation of a population equilibrium, depending on shredding efficiency (Beaghton et al, 2017;Champer et al, 2019). Furthermore, a major challenge in developing X-shredder in mammals is the identification of a highly-specific spermatogenesis promoter to drive Cas-gRNA expression (McFarlane et al, 2018).…”

Modeling CRISPR gene drives for suppression of invasive rodents

“…These models must account for the fact that real-world populations can differ profoundly from the small populations typically studied in laboratory experiments. For example, spatial population structure could have a major impact on the success or failure of a gene drive in a real-world population [36][37][38][39][40] . Large natural populations could also provide a higher chance for resistance to evolve against a drive, which could ultimately thwart its spread 22,27,41,42 .…”