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Evolution of legorgs
A physical simulation of adaptation by natural selection
By Jakob Christensen-Dalsgaard and Morten Kanneworff, Institute of Biology,
University of Southern Denmark.
This practical illustrates adaptation by natural selection for a trait, in this case motility of animals
with genetically specified morphology, assembled from six Lego® bricks. The animals are called
legorgs, (short for leg-organisms) since they only consist of a leg.
The individual legorgs are constructed by random draw from the gene pool of five 8x2 Lego®
bricks, each representing a body segment. Each of the bricks can have five colors (‘alleles’), and
each color specifies a morphogenetic rule. The morphogenetic rule specifies how to place the brick
on the previous brick (therefore, it is necessary to specify a foot segment, which we by convention
always select as black. The motility of the animal is the distance it can move under controlled
conditions (see below). We assume that fitness is proportional to the motility, and that individuals
transmit genes to the next generation proportional to their fitness. The experiment is to measure the
fitness on animals and their descendants through five generations. Our prediction is that in general,
fitness should increase with generation.
Scoring fitness.
Legorgs are built from five genes, specifying five segments placed on a foot. The animals are drawn
randomly from the gene pools, described below. Each allele (color) corresponds to a morphogenetic
rule, specifying how to place the brick on the previous (see morphogenetic rule table below), so the
genetic structure will build legorgs with different morphology. Fitness is scored by assembling the
legorgs (segment 1 is placed on the black foot-segment) and righting them on the foot. When
released, the animal may tip and fall, and when arighted again it will have moved a certain distance
on the surface. The distance moved of a corner of the foot is marked and measured. The average of
five measurements is the fitness of the legorg and is entered in the generation table (A). For best
results let the animals move on a hard, smooth surface such as a glass or whiteboard plate. Here, it
is convenient to mark the corner of the foot segment with a whiteboard marker.
First generation:
 5 opaque plastic bags are filled with 5 bricks (1 of each color in each bag). Each of these
bags simulate the gene pool for one of the five genes ( in the following generations it is
desirable to have 100 bricks in each bag, but it is not necessary in the first generation with
equal distribution of alleles).
 Shake bags to ensure randomized draw. Draw a brick from each bag (the sequence is
important). The color is noted at the entry of the corresponding gene in the generation table
(A). When bricks from the five bags are drawn, the animal is specified genetically. You do
not need to construct the animal, before you have drawn all, so put the bricks back (NB!)
and draw the next animals.
 Draw in total 10 or 20 legorgs and enter their genetic structure in the generation table (A).
 Build the legorgs from the morphogenetic rules, score their fitness and enter it in table A.
 Calculate and enter average fitness for the legorgs.
 After scoring fitness of all legorgs enter the fitness of each animal in the gene pool
table(table B, one table for each gene pool (bag), i.e. five tables/generation).
 The alleles of each animal is weighed by their fitness in table B. This is done by entering the
fitness in the table at the position of the allele this particular animal had for this gene.

In each B-table add fitness for each allele. Calculate fitness for each allele relative to the
total fitness in percent (rounded). The percentage of each allele is simply the number of
bricks of each color needed to fill the gene pool.
Second to fifth generation:
 Fill the bags according to the calculation from the last generation gene pool table (B).
 ( Mutations can be simulated by changing one brick in each of the bags with a brick of
another (randomly chosen) color. This corresponds to an ’unnaturally’ high mutation rate,
(0,01 against normally 10-4 og 10-7), but can probably show effects of mutations during the
few generations used here.
 Draw 10 or 20 legorgs, build and score fitness and register them in table A, as in first
generation. After scoring fitness in all animals transfer fitnesses to table B and calculate next
generation gene pools as in first generation, above.
The figure shows fifth- generation legorgs, with on average approx. 30 mm motility.
Diagram of the practical.
1: Calculating next generation gene pools. 2: Gene pool 1-5 filled with correct allele ratios, 3:
Drawing legorgs 4: Building legorgs according to morphogenetic rules 5: Scoring fitness
Table 1. Generation table.
Generation
No.
note allele (color) for each of the 5 genes in the legorg and measure fitness
Legorg no.
1
Gene 1
Gene 2
Gene 3
Gene 4
Gene 5
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Summed fitness :
Average fitness :
fitness
Table 2. Gene pool table (one table per gene per generation)
Generation
No.
note legorg’s fitness in column of the animal’s allele (color)
Gene No.
Legorg
No.
1
Alleles
fitness
Yellow
 fitness
 yellow weight
Red
Black
Blue
White
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Relative fitness
(rounded)
 red weight
 yellow weight /  red weight /
 fitness * 100 =  fitness * 100 =
 black weight
 blue weight
 white weight
 black weight /
 fitness * 100 =
 blue weight /
 fitness * 100 =
 white weight /
 fitness * 100 =
Tabel 3. Morphogenetical rules. Legorgs are assembled from segment 1, ’counter-clockwise’ i.e.
the previous segment (grey) is turned counter-clockwise to orient it up-down as in the figures.
Segment 1 is placed on the foot that is always black.
Allele/Color
Description
Red
Staggered, ahead
Blue
Just on top
White
Traverse, right
Traverse, left
Black
Yellow
Traverse, middle
Questions:
average fitness (mm)
1. Sketch the result of the practical in the diagram below:
50
40
30
20
10
0
0
1
2
3
4
5
generation
2. What do your results show?
3. Which type of selection is demonstrated by the practical?
4. Which elements of the simulation are realistic and which are unrealistic from a biological
perspective?
5. Describe some biological adaptations.
6. How does natural selection affect genetic variation in a population, and when is it beneficial
to have large genetic variation instead of ‘optimized’ adaptation?
7. How would average fitness change if the mutation rate was increased?
8. Why does natural selection not optimize organisms completely?
9. Which evident optimizations are improbable by the mechanism of natural selections (hint:
think of changes in bauplan, like extra sets of appendages)?
References:
Christensen-Dalsgaard J, Kanneworff M (2008) Evolution in lego. A physical simulation of
adaptation by natural selection. Evolution Education and Outreach 2: 518-526