Genetic drift
Last updated on 2024-03-12 | Edit this page
Estimated time: 12 minutes
Overview
Questions
- How does random genetic drift influence fixation of alleles?
- What is the influence of population size?
Objectives
- Understand how population size influences the probability of fixation of an allele.
- Understand how slightly deleterious mutations may get fixed in small populations.
Introduction
This exercise is to illustrate the concepts of selection, population size and genetic drift, using simulations. We will use mostly Red Lynx by Reed A. Cartwright.
Another option is to use a web interface to the R learnPopGen package, but the last one is mostly for biallelic genes (and thus not that relevant for bacteria).
Open now the Red Lynx website and get familiar with the different options.
You won’t need the right panel (but feel free to explore). The dominance option in the left panel won’t be used either.
Genetic Drift without selection
In the first part, you will only play with the number of generations, the initial frequency and the population size.
- Lower the number of generations to 200.
- Adjust the population size to 1000.
- Make sure the intial frequency is set to 50%.
- Run a few simulations (ca 20).
Did any allele got fixed? What is the range of frequencies after 200 generations?
In my simulations, no allele got fixed, the final allele frequencies range 20-80%
In my simulations, no allele got fixed, and the final allele frequencies range 45-55%
In my simulations, one allele got fixed quickly, the latest one was at generation 100.
It is clear that stochastic (random) variation in allele frequencies strongly affects the probability of fixation of alleles in small populations, not so much in large ones.
Genetic Drift with selection
So far we’ve only looked at how allele frequencies vary in the absence of selection, that is when the two alleles provide an equal fitness. What’s the influence of random genetic drift when alleles are not neutral?
The selection strength is equivalent to the selection coefficient, i.e. how much higher relative fitness the new allele provides. A selection coefficient of 0.01 means that the organism harboring the new allele has a 1% increased fitness.
- Increase the number of generations to 1000.
- Set the selection strength to 0.01 (1%).
- Set the population size first to 100’000, then to 1000, then to 100.
How long does it take for the allele to get fixed - in average - with the three population sizes?
About the same time, but the trajectories are much smoother with larger populations. In the small population, it happens that the beneficial allele disappears from the population (although not often).
Fixation of slightly deleterious alleles in very small populations
We’re now simulating what would happen in a very small population (or a population that undergoes very narrow bottlenecks), when a gene mutates. We’ll have a very small population (10 individuals), a selection value of -0.01 (the mutated allele provides a 1% lower fitness), and a 10% initial frequency, which corresponds to one individual getting a mutation:
- Set the population to 10 individuals.
- Set generations to 200.
- Set initial frequency to 10%.
- Set the selection strength to -0.01.
Run many simulations. What happens?
Most new alleles go extinct quickly. In my simulations, I usually get one of the slightly deleterious mutations fixed after 20 simulations.
That’s it for that part, but feel free to continue playing with the different settings later.
Key Points
- Random genetic drift has a large influence on the probability of fixation of alleles in small populations, even for non-neutral alleles.
- Random genetic drift has very little influence of the probability of fixation of alleles in large populations.
- Slightly deleterious mutations can get fixed into the population through random genetic drift, if the population is small enough and the selective value is not too large.