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GenEvo 2 Genetic Drift

If you download the NetLogo application, this model is included. You can also Try running it in NetLogo Web

WHAT IS IT?

This model is an example of genetic drift in a population of asexually reproducing bacteria E. coli. It starts with several types of E. coli, each with a different type (which we represent with unique colors). The model shows that competing types of E. coli, each reproducing with equal likelihood on each turn, will ultimately converge on one type without any selection pressure forcing this convergence. The idea, explained in more detail in Dennett's Darwin's Dangerous Idea, is that genetic drifts can occur without any particular purpose or 'selection pressure'.

HOW IT WORKS

The model starts with different colored E. coli cells, randomly distributed across the world. Each turn, each E. coli moves randomly around the world, eats sugar if the patch it is at contains sugar. Eating sugar increases energy of E. coli cell, whereas movement and basic metabolic processes decreases energy. An E. coli cell reproduces when its energy doubles, to form to two daughter cells of its type (of the same color). If energy of an E.coli cell reduces to zero, the cell dies.

The increase in energy by eating sugar is identical for each type (color) of E. coli cell. By statistical advantage, a dominant color becomes more likely to 'win' and take over the population. However, because the process is random, there will usually be a series of dominant colors before one color finally wins.

Note that once a type of E. coli dies out, it can never come back.

HOW TO USE IT

The SETUP button initializes the model.

The GO button runs the model.

Use the TYPES slider to select the number of competing types of E. coli.

Use MAX-INITIAL-POPULATION slider to set the maximum initial population in the world. Each type (color) has the same number of organisms to begin with.

Set CARRYING CAPACITY to very high, high, medium, low or very low.

THINGS TO NOTICE

Notice that in each simulation, the time required for a single type to become dominant varies. Check to see if an increase or decrease in the carrying capacity has any effect on how fast a color wins.

You can observe number of surviving types as time progresses. Notice how fast the number of surviving types reduce is dependent on the carrying capacity of the environment.

Notice that at high carrying capacity colors can achieve a high population count, but still fail to win the race.

THINGS TO TRY

Try and modify the carrying capacity and number of types to create a somewhat 'balanced' population (every type has roughly the same population size). Is it even possible?

EXTENDING THE MODEL

Genetic drift is one mechanism of evolution. The other mechanism is natural selection. Can you incorporate natural selection and make a color of your choice win every time?

NETLOGO FEATURES

This model uses lots of different pens in the Plot editor (right-click on a plot and select 'Edit...') in order to have a multi-color plot.

RELATED MODELS

• GenDrift Sample Models
• GenEvo Curricular Models

HOW TO CITE

If you mention this model or the NetLogo software in a publication, we ask that you include the citations below.

For the model itself:

• Dabholkar, S. and Wilensky, U. (2016). NetLogo GenEvo 2 Genetic Drift model. http://ccl.northwestern.edu/netlogo/models/GenEvo2GeneticDrift. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

Please cite the NetLogo software as:

• Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

To cite the GenEvo Systems Biology curriculum as a whole, please use:

• Dabholkar, S. & Wilensky, U. (2016). GenEvo Systems Biology curriculum. http://ccl.northwestern.edu/curriculum/genevo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.

COPYRIGHT AND LICENSE

Copyright 2016 Uri Wilensky.

This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc-sa/3.0/ or send a letter to Creative Commons, 559 Nathan Abbott Way, Stanford, California 94305, USA.

Commercial licenses are also available. To inquire about commercial licenses, please contact Uri Wilensky at uri@northwestern.edu.

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