GenEvo 3 Genetic Drift and Natural Selection

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My_photo_2 Sugat Dabholkar (Author)

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## WHAT IS IT?

This model allows for the exploration and comparison of two different mechanisms of evolution: natural selection and genetic drift. It models evolution in a population of asexually reproducing bacteria, E. coli.

It starts with different types of E. coli, each with a different trait represented by different colors. When ‘natural selection’ is off, 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. This is called genetic drift, an idea explained in more detail in Dennett's _Darwin's Dangerous Idea_ that explains that trait drifts can occur without any particular purpose or 'selecting pressure'. An important thing to note is this model includes only one case of natural selection called _r-selection_.

## HOW IT WORKS

The model starts with different colored E. coli cells, randomly distributed across the world. The user can select the number of different colors (types) of cells to start with. The cells can then move randomly across the world. Then,

When Natural Selection is OFF:

Each turn, each E. coli has the same likelihood of reproducing to form two daughter cells of its type (of the same color). If the total number of E. coli is greater than the carrying capacity of the system, then some E. coli cells are randomly killed in order to maintain that carrying capacity. By statistical advantage, a dominant color becomes more likely to 'win out', however, because the process is random, there will usually be a number of temporarily dominant colors before one color finally wins.

When Natural Selection is ON:

A user can select which trait (color) has a selective advantage in this world, causing it to reproduce faster. This selective advantage sets the percentage by which a type's reproduction rate (modelled here by the chance to reproduce during each tick) is higher than the others. Through this selective advantage, a dominant color becomes more likely to 'win out'. However, if the selective advantage is low, statistical advantage might still cause another color to 'win out'.

Note that once a color dies out, it can never come back.

## HOW TO USE IT

The SETUP button initializes the model.

The GO button runs the model.

Use CARRYING-CAPACITY slider to change the carrying capacity for the world.

Use the NUMBER-OF-TRAITS slider to select the number of competing colors.

Use the FASTER-REPRODUCING-ECOLI chooser to select the color (type) of E. coli that has a selective advantage.

Use the SELECTIVE-ADVANTAGE slider to set % increase in reproduction rate of "Faster reproducing E. coli" as compared to others.

## THINGS TO NOTICE

Notice that the faster reproducing color with selective advantage often wins the race when the % selective advantage is high. When the % selective advantage is low, statistical advantage in favor of any of the other colors might result in different outcomes. Check if there is any tipping point above which % selective advantage always makes the color win.

## THINGS TO TRY

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. Now check this same phenomenon in the presence and absence of natural selection.

## EXTENDING THE MODEL

The type of natural selection incorporated in this model is _r-selection_. The other possible type is _k-selection_. Think about how you could incorporate k-selection in this model.

## NETLOGO FEATURES

This model uses the `runresult` primitive in order to convert your color selection (a `string`) into a NetLogo color (a number).

## 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 3 Genetic Drift and Natural Selection model. http://ccl.northwestern.edu/netlogo/models/GenEvo3GeneticDriftandNaturalSelection. 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.

![CC BY-NC-SA 3.0](http://ccl.northwestern.edu/images/creativecommons/byncsa.png)

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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Click to Run Model

breed [ ecolis ecoli ]

;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;;;;;;; SETUP PROCEDURES ;;;;;;;;;;
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

to setup   ; Sets up the population of bacteria (E. coli) randomly across the world.
  clear-all
  let color-list [ gray red brown yellow green cyan violet magenta ]

  create-ecolis number-of-traits [
    set shape "ecoli"
    setxy random-xcor random-ycor
    set color first color-list
    set color-list but-first color-list ; each type has a unique color so we remove this color form our list
  ]

  reset-ticks
end 

;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;
;;;;;;;; RUNTIME PROCEDURES ;;;;;;;;
;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;

to go
  ask ecolis [
    move
    reproduce
    check-if-dead
  ]
  tick
end 

to move  ; E. coli cells move randomly across the world.
  rt random-float 360
  fd 1
end 

to reproduce    ; E. coli cells reproduce based on % selective advantage when Natural-Selection? is ON.

  ifelse natural-selection? [

    ; we have to use `runresult` here in order to compare, for example, the string "magenta" to the primitive `magenta`
    ifelse color = runresult faster-reproducing-ecoli [

      ; When the natural selection is ON, Faster_reproducing E. coli cells
      ; have higher chance of reproduction based on % selective advantage.
      if random-float 100 > ( 99 - ( selective-advantage / 100 ) ) [
        hatch 1 [rt random-float 360 fd 1]
      ]
    ]
    [
      if random-float 100 > 99 [
        hatch 1 [rt random-float 360 fd 1]
      ]
    ]
  ]
  [
    ask ecolis [    ; When natural selection is OFF, all E. coli cells have same chance of reproducing.
      if random-float 100 > 99 [
        hatch 1 [rt random-float 360 fd 1]
      ]
    ]
  ]
end 

to check-if-dead       ;; random chance of death when the total population exceeds carrying capacity
  if random count ecolis > carrying-capacity [
    die
  ]
end 


; Copyright 2016 Uri Wilensky.
; See Info tab for full copyright and license.

There is only one version of this model, created about 2 years ago by Sugat Dabholkar.

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