Essay
BIO1130 LAB 5
- Course
- Bio1130 (BIO1130)
- Institution
- University Of Ottawa (U Of O )
Essay of 10 pages for the course bio1130 at U of O (BIO1130 LAB 5)
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Module 5 – Populus Exercise Luis Punteno 300211345 C6Introduction to computer simulation of
Population genetics using Populus.
I- Populus basic instructions:
Populus is a simulation of population biology software developed by Don Alstad
at the University of Minnesota. You will need to download the program from
their site: https://cbs.umn.edu/populus/download-populus. This program is a
Java-Script that runs on Linus, MacOS and Windows. Read the instructions on
Brightspace to download and run the program.
The simulations we will use during this exercise are accessible from the “Model”
menu. Each simulation model consists of two windows: the input windows in
which you enter values for various parameters of the simulation, and the output
window where the results are displayed. Both windows are resizable.
You can zoom in any region of the display window by selecting the region of
interest with the left mouse button (drag the selection rectangle around the
region you want to zoom in). Right–clicking anywhere on the graph then choose
“Auto Range > Both Axis” to reset the zoom.
Your TA will demonstrate how to use Populous during the live session dedicated
to this exercise.
Follow the instructions below and write your answers directly in this document:
II- Genetic drift:
In the Model menu, select Mendelian Genetics then Genetic Drift. The input
window will appear. Make sure the Monte Carlo tab is selected.
By default, you can enter values for four parameters: population size (N), initial
frequency (p), number of loci and number of generations.
1
, Module 5 – Populus Exercise
Simulation 1-1:
First, let’s simulate a population of 250 individuals and observe what will happen
to an allele with an initial frequency of 0.5.
In the input window enter these parameters: N=250, p=0.5 and number of
loci=6. The number of loci set to 6 allows us to observe 6 simulated populations
at a time. Set the Runtime to 300 generations (click on “other” in the runtime
frame and type 300).
Next, click on “View” at the top of the input window to open the Output
window. A new window appears, showing a graphic representation of the allele
frequency over time (expressed in generation number). Each coloured broken
line represents a locus (or, in our case, a population).
You will notice that a certain number of broken lines may have reached the value
0 or 1. This phenomenon is called allele fixation. If an allele frequency reaches 0,
the allele is lost in the population. On the other hand, if the frequency reaches 1
it is said to be fixed.
Question 1 How many alleles reached fixation at 1? Which allele (blue, red…)?
Only 1 allele reaches fixation at 1, which was the blue allele.
Question 2 What does it mean in terms of genetic diversity for the population when an allele
becomes fixed?
In small populations, a fixed allele that comes from a genetic drift, might result in a loss of
genetic variability. Thus, increasing the risk of extinction, due to the fact that increase
in homozygosity will be a tendency, leading to a bottleneck on a population.
Run the simulation again (in the same conditions) by pressing the “Iterate”
button in the output window.
Question 3 Did you get the same result?
No, it changed
Question 4 How many alleles have been fixed this time?
2
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