Genetic Drift

OK, this one not so quick and easy. Click reset and get ready for some fun.

Drift depends upon random events; in large populations random events tend to cancel each other out, so there is minimal net effect, but in small populations random events can cause dramatic effects on outcomes. Because the effects of drift are due to random events, the effects of drift in any one instance are not predictable, but the effects of drift are predictable in a broader sense. The average effect of random events can be highly predictable even though the outcome in any particular situation is not. To see this, you will need to run simulations multiple times, and see what the typical or average outcome is. It is easiest to do this if you set the software graphing lines to “auto” so feel free to do that.

In very small populations, we expect drift to be strong, random changes in allele frequency might cause alleles to be lost. Click reset, graph lines auto, number of generations = 100, & population size 50.

Click run one time. What happened?

A1 frequency after 100 generations =

Don’t change anything and click run again. What happened this time?

A1 frequency after 100 generations =

Do this 8 more times for a total of 10 times.

A1 frequency after 100 generations =

Now calculate the average and the standard deviation (SD) of the A1 frequencies after 100 generations across those 10 trials. You can use a spreadsheet, or various online calculators, e.g.,

Record your results:

Population size = 50

Average A1 frequency after 100 generations =

SD A1 frequency after 100 generations =

Now do that all again with a population size of 500. Click reset, graph lines auto, number of generations = 100, & population size 500. Collect data for 10 trials.

A1 frequency after 100 generations =

Population size = 500

Average A1 frequency after 100 generations =

SD A1 frequency after 100 generations =

Now do that all again with a population size of 5000. Click reset, graph lines auto, number of generations = 100, & population size 5000. Collect data for 10 trials.

A1 frequency after 100 generations =

Population size = 5000

Average A1 frequency after 100 generations =

SD A1 frequency after 100 generations =

Draw two graphs using your data based on the average and SD outcomes across 10 trials for each of your three different population sizes. First graph should show the Average A1 frequency after 100 generations on the vertical Y axis against Population Size on the horizontal X axis (50, 500, 500).

Second graph should show the Standard Deviation of A1 frequency after 100 generations on the vertical Y axis against Population Size on the horizontal X axis (50, 500, 500).

Graph 1 (average A1 x population size) Graph 2 (SD A1 x population size)

What do you conclude about:

(1) the average effect of drift on allele frequency

(2) how the variation in outcome depends on population size

Drift and allele fixation

What are the chances that an allele goes to fixation (i.e. 100%) by drift alone? After your first experiments on drift, you might reasonably expect that the answer would depend upon population size….but it doesn’t. Let’s explore how and why.

In your first experiments, the starting A1 allele frequency was 0.5, and because random changes are equally likely to increase or decrease the allele frequency, the average expected change is zero (and would be zero in an infinite population), so the average ending allele frequencies typically were (probably) around 0.5. What if you started the A1 allele at a higher or lower frequency?

Click reset, graph lines auto, number of generations = 500, population size = 100, and the starting frequency of the A1 allele = 0.9. Run it 10 times, keeping track of final A1 frequency each time.

A1 frequency after 500 generations =

A1 starts at 0.9.