Effects of Mutation Rate on Population

Dheirya, Joseph, Noah, Moksh

QBio

Final Project

2025

Index

01

02

03

04

05

06

Introduction

Methodology

Results

Limitations

Next Steps

Conclusion

2

Organisms, creatures defined by their genes, survive in their environments based on the traits encoded by those genes. If the genes of an organism are mutated, their fitness in their environment might change. We simulated how varying mutation rates affect the fitness of a population in a controlled environment. We found that as mutation rate increases, the fitness of a population rises up to a certain point, where it will then decrease.

ABSTRACT

1

Introduction

• Natural selection, a cornerstone in evolution of populations, is the differential survival and reproduction of individuals in their environment due to differences in phenotype and genotype.
• The differences in phenotype determine the relative fitness of an individual based on the environment around them. The more fitness an individual has, the more likely they are to survive and reproduce in their environment, thereby passing on there genetic traits.
• Natural selection is essential for populations to survive and thrive in their environments because the genes of a population change over time to make them more fit for their environment as genetic mutations occur over generations.
• Genetic mutations are entirely random and occur at different rates. The rate of these mutations has an effect on the natural selection of a population, so this can be simulated to determine that effect in more detail.

4

Methodology

1. Created a 2D array with 100 rows
1. Each row represents an individual in a pop
2. Each individual has 10 numbers starting randomly between [-1, 1] representing whether a version of a gene helps/hurts them
3. Each gene is given a random weight signifying relative importance to fitness
2. Each trial, we randomly added/subtracted a number within mutation rate (MR)
3. Overall fitness is calculated and a sigmoid function is used to normalize between (0, 1)
4. From the index, a probabilistic decision tree is used to see if the individual either dies, asexually reproduces, or nothing happens
5. We repeat steps 1-4 over 128 trials and sum up the results for an entire experiment

​

For our experiment, we repeated these steps for 10 different mutation rates between 0.1 to 0.5

CODE

5

r → Random from [0,1]

r ≥ (1 - index)

r < (1 - index)

Dies

r < index

r > index

Pop < 10k

Reproduces

Nothing

Index Function

Probabilistic Decision Tree

CODE

6

Results: Total Fitness

DATA

7

Results: Total Population

MR=0.05

MR=0.15

MR=0.25

MR=0.35

MR=0.45

MR=0.5

DATA

8

Results: Individual Fitness

MR=0.5

MR=0.45

MR=0.35

MR=0.25

MR=0.15

MR=0.05

DATA

9

Results: Tabular Data

DATA

10

Analysis

• Higher mutation rate in general means a greater population fitness
• This is because there is a greater chance of developing towards beneficial traits with higher gene mutation rate
• However, at a certain point, we started to notice that some populations with a higher mutation rate began to decline in fitness
• At high mutation rates, harmful mutations accumulate faster than selection can remove them
• Our experiment shows a balance is critical

11

Challenges

Limitations

• No food supply, no environmental factors.
• Ultimately, the simplicity of our experiment is its greatest limitation.
• While we have “genes” and associated survival weightings, these genes are not specified to a specific purpose. They are simply numbers that alter survival and reproduction odds without actually simulating true biological factors.
• In addition, the nature of our model is that it is a closed observation. We don’t have variables for environmental factors such as weather, direct intra/inter-species competition, and food quantity, giving us a limited view in how mutation rates actually impact species’ populations.

12

Next steps

It would also be interesting to predict the kinds of mutations an organism may need in order to survive harsh environmental conditions and possible extinction. We can simulate what may have led to previous species going extinct as well as simulate different evolutionary ways a species could survive being endangered.

While our methods simulate a general population, it’s possible to simulate early conditions that led to life on Earth through this process. We can establish environmental factors and scale down to cells and just proteins to model the idea of the “selfish gene.”

This project can be taken a lot further with the introduction of more complicating variables that have specific purposes. Food usage efficiency, speed, vision, and intelligence are all viable ways to make the simulation more applicable to the real world

Idea 1

Idea 2

Idea 3

13

Conclusion

• We found that mutation rate has a positive correlation with population fitness and population growth up to a certain point.
• The specific point at which mutation rate starts having a negative correlation with fitness and population growth does not matter.
• Our experiment serves as a simulation to highlight and reinforce the broad trends in these relationships with quantitative data, not to provide any specific details about one kind of population.

Month 🞹 Year 🞹 14

14

Bibliography

From our literature searches

Lynch, M. (2008). The Cellular, Developmental and Population-Genetic Determinants of Mutation-Rate Evolution. Genetics, 180(2), 933–943. https://doi.org/10.1534/genetics.108.090456

Vahdati, A. R., Sprouffske, K., & Wagner, A. (2017). Effect of Population Size and Mutation Rate on the Evolution of RNA Sequences on an Adaptive Landscape Determined by RNA Folding. International Journal of Biological Sciences, 13(9), 1138–1151. https://doi.org/10.7150/ijbs.19436

15

Thank You!

-The Qbio Wizards

16