Natural Selection and Environmental Selection Pressures

In this virtual lab, you will explore the effect that environmental selection pressures have in the genetic makeup of a population. You will observe changes in the frequency of traits in a closed population and relate this to genetic fitness, or the chance that an organism with a particular trait will survive to reproduction.

Learning Objectives

When this virtual lab has been completed, you will have learned:

that phenotypic variation exists within populations, and that phenotypes survive better in particular environments compared to other phenotypes.

that phenotypes that are more likely to survive to reproduction are more likely to pass on their traits to the next generation, leading to changes in the genetic makeup of the next generation.

the concept of environmental selection pressures, and how this affects the prevalence of sickle cell anemia in malaria-endemic populations.

how to interpret diagrams and graphs representing different traits within a closed population.

See the appendix for more information on the suggested prerequisites for running this virtual lab, as well as supplementary reading material.

Background

The theory of natural selection was proposed by Charles Darwin in 1859 through his infamous book On the Origin of Species. While his theory was met with serious controversy at the time it was published, today it has become one of the most well-known concepts in biology!

Natural selection is fundamental in understanding how populations evolve over time. It helps us to understand why some traits die out while others flourish. It also helps us to understand how species adapt to changes in their environments. In order to understand how this process works, you need to understand three key concepts:

Phenotypic variation exists within populations. It is not hard to see that there are differences not only between organisms of different species, but also within species. Some of us have blue eyes, some of us have brown eyes. Some of us are tall, some of us are short. Although we are all human, there are differences in phenotypes among us, and the same can be said for all species that exist on Earth.

Phenotypic variation is heritable—genes play an important role in our phenotypes, and we inherit our genes from our parents. Thus, we can say that our phenotypes are heritable (i.e. that they are passed down from generation to generation). For example, if you have brown hair, it is likely that you inherited this trait from one of your parents.

Phenotypes differ in their ability to survive to reproduction. Some phenotypes are better at surviving than others. Thus, phenotypes that survive better in their environments are more likely to survive to reproduction. This is known as the genetic fitness, or reproductive success, of the organism, which is a measure of how likely the organism is to survive to reproduction.

Understanding these three concepts is fundamental to understanding how natural selection works. In the following exercises, you will put these concepts together and try to visualize the process of natural selection using diagrams and graphs.

System Description

The virtual lab consists of two different exercises—one using a simple scenario of natural selection, and one that is slightly more complex. In the first exercise, you will explore the changing frequencies of a trait A and a trait B within a closed population. In the second exercise, you will explore the example of sickle cell anemia and the effect that malaria has on the frequency of this trait.

Models of these scenarios have been created for you to interact with. To get started, first load the population models package:

ImportString[,"MO"];

Now you can load an image of the model used for the first scenario:

Show[SystemModel["NaturalSelection.NaturalSelectionSurvivability","Diagram"],ImageSize->800]

The scenarios you will explore in this virtual lab consist of different population groups with transitions, denoted by arrows, between them. A transition can be seen as an individual moving from one population group to the other—for example, transitioning from the proportion of the population able to reproduce (denoted by the letter “R”) into death. The rate of transition can be modified by the number of individuals in a population; for example, a high number of individuals from population A will promote new individuals being born into the population group. See the appendix for more details on the specific components from the diagram.

Exercise 1: “Survival of the Fittest!” How Does It Work?

Part 1: Starting Out

Background

You may have heard the phrase “survival of the fittest” before. This phrase originated from Darwin’s theory of natural selection—but what does it actually mean in natural selection?

Contrary to what you may think, it does not just mean that only the fit members of a species will survive, but rather, it refers to the ability of an organism to survive to reproduction. If an organism does not survive to reproduction, it cannot pass on its genes to the next generation. Thus, if a group of organisms with a particular trait have a decreased chance of surviving to reproduction, there is a decreased chance that the genes for this trait will be passed on to the next generation. This in turn may lead to the extinction of the trait.

Let us start with a population with 100 organisms, where 50 organisms have trait A and 50 organisms have trait B, and run this for 100 generations.

Instructions

The interface shown here uses the model described in the System Description section to calculate outcomes. At the moment, the initial percentage of the population with trait A is set to 75%, i.e. three-quarters of the organisms have trait A and one-quarter of the organisms have trait B.  Assume that both organisms with trait A and organisms with trait B have a 100% chance of surviving to reproduction. What happens when the initial proportion of organisms with trait A is changed?

Questions

Move the slider so that the proportion with trait A is around 40%. Now observe what happens. You should notice that the number of organisms with trait A remains constant around 40%, and the number of organisms with trait B remains around 60%.

Why does the population’s distribution remain constant under these conditions?

Answer:

Part 2: Survivability

Instructions

Let us set the first slider, “Initial percentage of population with trait A,” to 50% and decrease the “Percentage with trait A who survive to reproduction” slider to around 80%. This means that 80% of organisms with trait A will survive to reproduction, while all 100% of organisms with trait B will survive to reproduction. Change the different survivability values and observe what happens.

Questions

You should notice that the number of organisms with trait A decreases toward extinction, while the number of organisms with trait B increases toward 100%. Once trait A has become extinct, the entire population will have trait B. At this point, there will be no more organisms that have trait A. The only way that trait A can reenter the population is by immigration or mutation.

Reduce the “Percentage with trait B who survive to reproduction” slider to the same value as “Percentage with trait A who survive to reproduction,” i.e. so that both have the value 80%. What do you observe? Why do you think this occurs?

Answer:

Continue to experiment by changing the bottom two sliders, then check the correct responses in the following table:

Results:

({{ , Percent A that survive to rep.>
Percent B that survive to rep., Percent A that survive to rep. =
Percent B that survive to rep., Percent A that survive to rep.<
Percent B that survive to rep.}, {Percentage of organisms
with trait A and B
does not change,  ,  ,  }, {Trait  A 
predominates,  ,  ,  }, {Trait  B 
predominates,  ,  ,  }})

Now experiment by differing the initial percentage with trait A. Set the initial proportion with trait A to 70%. Set the survivability of trait A to 80% and the survivability of trait B at 100%. Observe what happens. Does changing the initial proportion with trait A affect which trait becomes extinct? Why do you think this occurs? What about when the proportion with trait A is set to 0%?

Results:

Part 3: Selection Pressure

Background

In this exercise, you will model the effect that different selection pressures have on the genetic makeup of the population.

A selection pressure is any factor that reduces the reproductive success of certain organisms within a population. If this factor comes from the environment, it is called an environmental selection pressure. For example, consider the introduction of a predator species, such as the red fox into a population of bilbies. Red foxes are known to prey upon bilbies, thus reducing the likelihood that a bilby will survive to reproduction. If bilbies had a gene that allowed them to run faster and escape attack by foxes, bilbies with this trait would be more likely to survive to reproduction than bilbies who did not have this trait.

The fox is an example of an environmental selection pressure, which will ultimately affect the genetic makeup of the population of bilbies. For any given environment, there are innumerable selection pressures like this that will influence whether a certain trait is advantageous or not. In this section, you will see this illustrated with an environment that can be warm and/or wet. Changing the type of environment will affect the survivability of the different populations.

Instructions

Here you have a different interface for the same model. Now, instead of being able to adjust the percentage of each trait that will survive to reproduction, you will look at the effect that different environments have on the number of organisms with each trait in the population. The type of environment will affect the survivability of the different traits. Observe what happens when the environment is changed.

Questions

In which environment(s) do organisms with trait A survive better than organisms with trait B (and vice versa)? In which environment(s) do the organisms have the same chance of survival?

Results:

Exercise 2: Heterozygote Advantage—Sickle Cell Anemia/Malaria Model

Part 1: Malaria Model

Background

This exercise and its accompanying model describe the relationship between two diseases, sickle cell anemia and malaria. Although this is more complex than the previous scenario, you do not need to be worried. You have already covered all the concepts needed to understand this exercise. Let us first cover some background material.

Sickle cell anemia is a genetic disorder that affects red blood cells in the human body. People with sickle cell anemia have dysfunctional blood cells that “sickle” (or form an odd shape), break apart and die. This means that people with sickle cell anemia do not have enough red blood cells to support them. Although there have been advances in medical treatment, people with sickle cell anemia still have a reduced lifespan compared to people without the disease. Thus they are less likely to reproduce and pass on their genes. In our model, you can assume that people with sickle cell anemia do not undergo reproduction, and thus do not pass on their genes.

1. Normal red blood cells; 2. "Sickled" red blood cells

Malaria is an infectious disease that is transmitted by mosquitoes. It is prevalent in Southeast Asia and African regions. After initially becoming infected with malaria (usually through a mosquito bite, from a mosquito infected with malaria), the parasite penetrates red blood cells, making the person sick and sometimes even causing death.

Although these two diseases appear to be unrelated (one is genetic and the other infectious), they can actually be linked by the theory of natural selection. But first, you need to understand how sickle cell anemia is inherited.

Sickle Cell Anemia Inheritance

Sickle cell anemia is an autosomal recessive trait, meaning that in order to show the full phenotype of the disease, a person needs to have two copies of the sickle cell anemia allele. If you define h to be the sickle cell allele and H to be the healthy allele, a person with sickle cell anemia would have the genotype hh.

According to your previous studies, you might assume that people with the genotypes HH and Hh have the healthy phenotypes. Indeed, people with the genotypes HH and Hh do appear healthy; however, there are phenotypic differences between people with the genotype HH and people with the genotype Hh.

In fact, people with the genotype Hh (known as the “carrier” population) have slightly different-shaped blood cells. The shape of the blood cells in the carrier population is not so extreme that it causes sick cell anemia, but it is different enough from the shape of normal blood cells that it prevents malaria from infecting the cell. Thus, this is an example of partial dominance.

It is not important that you know the details of how the carrier genotype protects against infection with malaria. In fact, the process by which this happens is still mostly unknown, and is an active area of research. What is important to know here is that the carrier genotype is protective against being infected with malaria.

Malaria as a Selection Pressure

In this example, you can consider malaria as a selection pressure. In environments where malaria is non-endemic, people with the HH and Hh genotypes have an equal chance of surviving to reproduction. However, in environments where malaria is endemic, the chance of survival is reduced in people with the HH genotype. Since the Hh genotype is protective against being infected with malaria, this genotype is favored in malaria-endemic environments, even though there is a possibility of producing offspring with the full sickle cell anemia disease.

Instructions

Now it is time to look at a more complex scenario. Bring up a diagram of the model used for this scenario by running the following code:

Show[SystemModel["NaturalSelection.HeterozygoteAdvantage","Diagram"],ImageSize->800]

Questions

This scenario looks similar to what you used in earlier exercises; however, instead of having two phenotypes (traits), there are now three—healthy, carrier and sickle cell. A few assumptions are made for this scenario—for example, no people with sickle cell anemia survive to reproduction. Thus, in the model you will be using, there is no reproductive stage for people with sickle cell anemia, and these people proceed directly to “Death.” See the appendix for more details on the model assumptions.

In order to understand how these genes are spread over generations, you first need to determine the probability that a healthy, carrier or sickle cell individual will be born. Use the Punnett square to predict the outcomes from different mating pairs.

Since it is assumed that people with sickle cell anemia do not survive to reproduction, only people with the healthy phenotype and people with the carrier phenotype undergo reproduction in the model. Thus there are three different mating pairs that could possibly occur: a healthy person mating with another h person, a healthy person mating with a carrier and a carrier mating with a carrier. Perform the monohybrid crosses for these three mating pairs and record the probability that a healthy child, a carrier child and a sickle cell child will be born for each mating pair.

Healthy*Healthy

({{ , H, H}, {H,  ,  }, {H,  ,  }})

Probability that healthy (HH) child will be born = 
Probability that carrier (Hh) child will be born = 
Probability that sickle cell (hh) child will be born = 

Healthy*Carrier

({{ , H, H}, {H,  ,  }, {h,  ,  }})

Probability that healthy (HH) child will be born = 
Probability that carrier (Hh) child will be born = 
Probability that sickle cell (hh) child will be born = 

Carrier*Carrier

({{ , H, h}, {H,  ,  }, {h,  ,  }})

Probability that healthy (HH) child will be born = 
Probability that carrier (Hh) child will be born = 
Probability that sickle cell (hh) child will be born =

Part 2: Malaria and Sickle Cell Interaction

Instructions

Now it is time to use your calculated probabilities in the model and observe what happens. The interface shown here will use the values that you entered into the question fields from Part 1. If these have not been answered, default values will be used. Experiment with different values on the slider. Under which conditions do the percentage of sickle cell carriers in the population increase?

Questions

Note that the population is closed, and the total population size is neither increasing nor decreasing. Uncheck the “Malaria is found within the area” checkbox for now. The first slider controls the initial percentage of sickle cell carriers in the population. It should be set at 10%. This means that the initial population is comprised of 10% carriers (Hh) and 90% healthy (HH) people. There are no people with the sickle cell disease in the initial population.

Experiment by changing the “Percentage of sickle cell carriers in the population” slider. What happens to the number of people with the sickle cell disease when you increase the slider? Why do you think this occurs?

Once you have finished, reset the slider to 10%.

Results:

The second slider controls the “Probability that a healthy person will survive to reproduction in a malaria-endemic environment” slider. Remember that when malaria is endemic within a population, the carrier phenotype is protective against being infected with malaria. Therefore, people with the healthy phenotype are more susceptible to contracting malaria and thus dying from malaria. This decreases the chance that a healthy person will survive to reproduction. At the moment, this slider is set to 50%, meaning that in a malaria-endemic environment, only 50% of healthy people will survive to reproduction (compared to 100% of people with the carrier phenotype). Keeping the malaria box unchecked, experiment by moving the slider up and down. What do you notice? Why?

Results:

Reset the “Probability that a healthy person will survive to reproduction in a malaria-endemic environment” slider back to 80%. Now check the malaria checkbox and observe what happens to the proportion of healthy, carrier and sickle cell disease individuals within the population. Report what happens in each of the subpopulations. Try to explain why this occurs in each case.

Summarize your results in these tables:

Non-Malaria-Endemic Area

({{Subpopulation, Observation, Explanation}, {Healthy,  ,  }, {Carrier,  ,  }, {Sickle cell,  ,  }})

Malaria-Endemic Area

({{Subpopulation, Observation, Explanation}, {Healthy,  ,  }, {Carrier,  ,  }, {Sickle cell,  ,  }})

Results and observations:

Keeping the malaria checkbox checked, experiment with what happens when you slide the “Probability that a healthy person will survive to reproduction in a malaria-endemic environment” slider up and down. What do you notice? What happens when the slider is set to 100%? This slider actually allows you to control how severe the malaria in the endemic area is. If the slider is set to 100%, you can observe results that are identical to a malaria-free case, as all healthy people survive to reproduction. Decreasing this value means that the proportion of healthy people who survive to reproduction decreases. This decrease could be attributed to a more severely affected endemic area.

Results:

Want More?

Open up the simulation in Wolfram SystemModeler and get one-click access to any plots that have been stored in the model, as well as every single model variable.

SystemModeler["NaturalSelection.HeterozygoteAdvantage","Simulation"]

Modify the model using the graphical modeling environment of SystemModeler. Quickly and intuitively build models using drag-and-drop using the built-in components.

SystemModeler["NaturalSelection.HeterozygoteAdvantage","Modeling"]

Find out more about how Wolfram SystemModeler will give you full advantage in education and model-based development here.

Appendix

Prerequisite

Before starting this course, it is recommended that students be familiar with the following topics:

Genome, genes and alleles

Genotypes and phenotypes

Patterns of inheritance

Basic theory of natural selection

Reading Material

The following reading material is recommended to be used together with this virtual lab:

J. Kinnear and M. Martin, Nature of Biology 2 5E Units 3 and 4, Australia: Jacaranda, 2012.

Khan Academy, “Natural Selection in Populations.” (Mar 14, 2018) www.khanacademy.org/science/biology/her/heredity-and-genetics/a/natural-selection-in-populations. [Free.]

System Descriptions

Part 1: Natural Selection Model

In this model, you will measure two different traits from the same species, trait A and trait B. An organism within this population will be born with either trait A or trait B. Note that you are using a closed population, meaning that there is no immigration or migration from the population. Also assume that the number of births and the number of deaths are equal in each generation, so the total population size remains constant.

See the following for a description of the different elements in the diagram.

Icons

This is where a person’s life begins. From here, the organisms are born into either population group A or population group B.

Population groups tally all the organisms that exhibit a certain combination of traits. In this model, there are four named population groups:

PopulationA represents the number of organisms within the population who have trait A.

PopulationB represents the number of organisms within the population who have trait B.

R_PopulationA represents the number of organisms within the population with trait A who are ready to reproduce.

R_PopulationB represents the number of organisms within the population with trait B who are ready to reproduce.

This is where a person’s life ends. From here, the organism is removed from its current population group, lowering the total amount of organisms in that group. Several factors can influence the death rate of organisms.

Arrows

The arrows represent transitions between each of the different stages in the life cycle:

Birth to Population: The first transition occurs when the organism is born. The organism will either move from “Birth” to “PopulationA” or from “Birth” to “PopulationB,” depending on which trait they inherit.

Population to R_Population: Once the organism is born and enters the population, there are two possible outcomes: either the organism progresses to the next stage in the life cycle where they can reproduce, or the organism dies. Organisms that live to reproduction move to “R_Population.” The remaining organisms move to “Death.”

R_Population to Death: Once the organism has undergone reproduction, the organism will also die.

Modifier Effect

There is one final element of the diagram, called the modifier effect. “Modifier effects” are represented by yellow circles in the diagram. What this aims to show is that the number of organisms born with trait A depends on the number of organisms with trait A who reproduced in the previous generation, and likewise for trait B.

Part 2: Sickle Cell Anemia/Malaria Model

A few assumptions are made in the model:

It is assumed that all people with sickle cell anemia do not survive to reproduction. Thus in our model there is no reproductive stage for people with sickle cell anemia, and these people proceed directly to “Death.”

It is assumed that all people with the carrier state survive to reproduction (no matter what environment they are in).

It is assumed that all people with the healthy genotype (HH) survive to reproduction when there is no malaria. When malaria is introduced, the proportion of people with the healthy phenotype who survive to reproduction is reduced, and a proportion of healthy people die without reproducing.

The proportion of people with the healthy phenotype and people with the carrier phenotype determine the number of people who are born with the healthy, carrier or sickle cell phenotype in the next generation.

Image Attributions

“evolution-charles-darwin-man,” by Clker Free Vector Images [CC0]. pixabay.com/en/evolution-charles-darwin-man-296584.

“Origin of Species illustration cropped,” by Charles Darwin [public domain]. commons.wikimedia.org/wiki/File:Origin_of _Species _illustration _cropped.png.

“Macrotis lagotis Gould,” byJohn Gould [public domain]. commons.wikimedia.org/wiki/File:Macrotis_lagotis _Gould.jpg.

“Sickle cell anemia,” by Pkleong at English Wikibooks [public domain]. commons.wikimedia.org/wiki/File:Sickle_cell _anemia.jpg.

“Autorecessive,” by Cburnett [GFDL or CC-BY-SA-3.0]. commons.wikimedia.org/wiki/File:Autorecessive.svg.