Vector control with driving Y chromosomes: modelling the evolution of resistance

Area of Science:

• Population genetics
• Vector control
• Malaria research

Background:

• Previous malaria control interventions faced resistance from parasites and vectors.
• Genetic interventions offer new possibilities but also risk resistance evolution.
• Understanding resistance evolution is crucial for novel vector control strategies.

Purpose of the Study:

• To model the likelihood of resistance evolving against a Y chromosome gene drive.
• To identify key factors influencing resistance evolution in mosquito populations.

Main Methods:

• Utilized deterministic differential equation models.
• Employed stochastic analyses including branching processes and Gillespie simulations.
• Modeled resistance via target-site mutations and trans-acting suppressor alleles.

Main Results:

• Resistance probability increases with mutation rate and population growth rate.
• Resistance probability decreases with gene drive strength and fitness costs.
• Environmental factors like seasonal variation and allele type influence resistance evolution.

Conclusions:

• Genetic interventions, like Y chromosome gene drives, carry a risk of resistance.
• Minimizing resistance involves reducing mutation rates and imposing fitness costs.
• Careful design of genetic control strategies is essential for long-term efficacy.