EVOLUTION LAB 1
GENETIC DRIFT AND NATURAL SELECTION
Team name: Chiton Crew
Members: Megan Thees, Gretchen Janes, Jaena Bautista, Nhy Tran
Members: Megan Thees, Gretchen Janes, Jaena Bautista, Nhy Tran
Introduction
This lab was done to demonstrate that natural selection and genetic drift can result in evolution. Although both are fundamental processes in evolution, there are significant differences between the two. Natural selection is the process by which forms of life having those traits that better enable them to adapt to specific environmental pressures (predators, climate changes, competition for food or mates etc.) will tend to survive and reproduce in greater numbers over others of their kind, ensuring perpetuation of those favorable traits in future generations. Genetic drift is the variation in relative frequency of different genotypes in a small population due to the chance of disappearance of particular genes as individuals die or do not reproduce. Genetic drift can be random; the random change in allele frequencies. Natural selection is not random, but rather an adaptive process that alters only the frequency of alleles that favor a selective advantage to the organism.
In part A of this lab, we simulated the distribution of genes in a population, by creating a gene pool of 50 speckled beans and 50 white beans, with the different beans representing the alleles of a specific gene. Working in pairs, each partner drew a single bean and paired it with the partners bean, creating an allele pair representing the genotype of a diploid individual. This process was repeated to make 50 pairs.
Figure 1: Megan and Gretchen’s 50 pairs of simulated allele pairs
Figure 2: Jaena and Nhy’s 50 pairs of simulated allele pairs
In part B, we joined forces to create a gene pool of 25 red beans (round), 25 speckled beans (pinto), 25 black beans and 25 white beans. We emulated a “natural barrier” and divided the gene pool into two different populations. Megan and Gretchen worked with population A while Jaena and Nhy worked with population B. Each pair counted the number of each allele in each population and recorded the results in Generation. Once counted, Generation 1 was doubled to simulate new gene pool, and Generation two was created by randomly selecting 50 beans, and recording the respective alleles. Again the Generation was doubled to create the next generation until 10 generations were created.
Hypothesis: After 10 generations, there will be a change in allele frequency
Prediction: If genetic drift takes place, then the variation in allele frequency will be decreased.
Data Tables
Beans Population A
| ||||||||||
Generations
| ||||||||||
“Allele”
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
Round
|
19
|
13
|
10
|
7
|
3
|
2
|
1
|
1
|
0
|
0
|
Pinto
|
5
|
10
|
18
|
25
|
31
|
36
|
43
|
43
|
45
|
45
|
Black
|
9
|
10
|
7
|
7
|
7
|
6
|
5
|
5
|
5
|
5
|
White
|
17
|
17
|
15
|
11
|
9
|
6
|
1
|
1
|
0
|
0
|
Table 1: Recorded number of individuals (beans) in each generation according to allele type in Population A (group data)
Beans Population B
| ||||||||||
Generations
| ||||||||||
“Allele”
|
1
|
2
|
3
|
4
|
5
|
6
|
7
|
8
|
9
|
10
|
Round
|
6
|
3
|
4
|
2
|
2
|
2
|
1
|
1
|
0
|
0
|
Pinto
|
20
|
20
|
19
|
23
|
32
|
34
|
33
|
37
|
37
|
40
|
Black
|
16
|
18
|
19
|
20
|
14
|
11
|
14
|
12
|
13
|
10
|
White
|
8
|
9
|
8
|
5
|
2
|
3
|
2
|
0
|
0
|
0
|
Table 2: Recorded number of individuals (beans) in each generation according to allele type in Population B (group data)
Population of Other Groups
| ||||||||||
Generations
| ||||||||||
“Allele”
|
1 (Expected)
|
10 (Observed)
| ||||||||
Red
|
14
|
14
| ||||||||
White
|
12
|
6
| ||||||||
Navy
|
14
|
12
| ||||||||
Clear
|
10
|
18
| ||||||||
Table 3: Recorded number of individuals (beads) in each generation according to allele type (JonT&David’s population data)
Graphs
Figure 1. The number of beans (round, pinto, black, and white) over ten generations in population A. The allele distribution mostly declined throughout the generations, with the exception of the pinto “allele”
Figure 2. The number of beans (round, pinto, black, and white) over ten generations in population B. Population B relatively follows the trend of population A (the pinto “allele” goes up, and the rest decrease)
Chi-square Statistical Analysis
Null Hypothesis: There is no significant difference between the observed and expected outcomes over ten generations of beans.
Population A
|
Observed (O)
|
Expected (E)
|
(O-E)^2/E
|
Round
|
0
|
19
|
19
|
Pinto
|
45
|
5
|
320
|
Black
|
5
|
9
|
1.78
|
White
|
0
|
17
|
17
|
Chi-square = ∑ ((O-E)^2/E)
|
357.78
| ||
The degree of freedom = 4 - 1 = 3
The critical value of chi-square = 7.82
Since χ2 > critical value (357.78 > 7.82) => reject the null hypothesis
Population B
|
Observed (O)
|
Expected (E)
|
(O-E)^2/E
|
Round
|
0
|
6
|
6
|
Pinto
|
40
|
20
|
20
|
Black
|
10
|
16
|
6
|
White
|
0
|
8
|
8
|
Chi-square = ∑ ((O-E)^2/E
|
94
| ||
The degree of freedom = 4 - 1 = 3
The critical value of chi-square = 7.82
Since χ2 > critical value (94 > 7.82) => reject the null hypothesis
Population (Jon T. & David’s data)
|
Observed (O)
|
Expected (E)
|
(O-E)^2/E
|
Red
|
14
|
14
|
0
|
White
|
6
|
12
|
3
|
Navy
|
12
|
14
|
0.286
|
Clear
|
18
|
10
|
6.4
|
Chi-square = ∑ ((O-E)^2/E
|
9.686
| ||
The degree of freedom = 4 - 1 = 3
The critical value of chi-square = 7.82
Since χ2 > critical value (9.686 > 7.82) => reject the null hypothesis
Discussion/Conclusion
Our chi-squared calculations for the data of ten generations of beans was 357.78 for Population A and 94 for Population B, both greater than 7.82, which concludes we can reject our null hypothesis saying that there is no significant difference between the observed and expected outcomes over ten generations of beans. Between our observed and expected data there is a significant change in alleles in the bean populations. In both Populations A & B of our group we witnessed the total extinction of the “alleles” round and white and in the class data almost all the other groups experienced this too. In just Populations A & B of our group, we both started with a different number of each “allele” and even though generation one of Population A started with five pinto beans and Population B with twenty, they both ended generation ten with that being the most common “allele” (Table 1 and Table 2).
We compared our data of beans with a group that had data of beads. Our chi-squared for Population A (beans) was 357.78 and Jon and David’s chi-squared for Population A (beads) was 9.686. Both chi-squared values are greater than the critical value for 3 degrees of freedom, 7.82. This means that both groups can reject the null hypothesis of there not being a significant difference between the observed and the expected outcomes over 10 generations. The beads chi-squared was much less than the chi-squared of the beans. The beans chi-squared was large enough to reject the null hypothesis but there was not as much differentiation between generations compared to that of the beans. We conclude that this is because the size of the beads is consistent throughout each type of bead where as the beans are all different sizes. This makes the drawing of beads more random than that of the beans. At the beginning of this lab, our hypothesis and predictions stated the allele variations would be decreased, and we think that it is due to natural selection. Based on Figure 1 and Figure 2, the allele distribution mostly declined throughout ten generations, with the exception of the pinto “allele”. Since the pinto “allele” seemed to dominate the population, a theory for this could be that because they were larger and although we were choosing beans at random it was easier to pick up a larger bean than a smaller one like the round, white, or black beans.
Image 1. Population B: Generations 1, 6 and 10
Image 2. Population A: Generations 1, 5, 8 and 10
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