Student Learning Goal x Students will be able to explain that mutations occur at random, and not because they are directed to occur due to natural selection and the environment. Driving Questions xIs there a pattern to how mutations occur?
͒xCan we predict that an organism’s offspring will have mutations suitable to living and reproducing in its environment?
͒xWhat does it mean to say that mutations occur at random? ͒Mutation is essential for evolutionary processes because it is the ultimate source of genotypic variation –variation that can then be expressed phenotypically. Alterations to the instructions in an Avidian’s genome can affect its ability to perform certain functions and even its ability to reproduce. These abilities, or lack thereof, are the phenotypes of Avidians.
Note in biological systems, both genetic variation and environmental variation often act together (nature and nurture) to influence phenotypic variation; however,in Avida-ED, genotypic variation is solely responsible for phenotypic variation.
In this exercise we explore the consequences of random mutation generating the phenotypic variation that can be under selection in the environment by re-implementing a famous biology experiment1that tested whether mutations occur at random or directed in response to natural selection the environment. We will also consider a reason why time is fundamental to the process of evolution; if mutations do not generate a phenotype, then that trait cannot evolve in a population.
2Phenotypic Variation and Selection ͒Random mutations create genotypic diversity in a population. In Avida-ED, mutations can allow some Avidians to perform functions. For our purposes we will simply note that these are logic functions involving the comparison of numbers Avidians encounter in their digital environment. An Avidian with a sufficient sequence of instructions can perform a function, but is only rewardedif the corresponding resource is available in the environment. In Avida-ED there are nine functions –NOT, NAN, AND, ORN, ORO, ANT, NOR, XOR, EQU; and nine corresponding resources –notose, nanose, andose, ornose, orose, antose, norose, xorose, equose. For example, the “@ancestor” organism cannot perform anyfunctions, but random mutation over multiple generations might produce a descendant’s genome that codes for one or more functions (e.g., NOT). If the corresponding resource is in the environment (e.g., notose), then the Avidian will have an increased energy acquisition rate and be favored by selection. Natural selection acts upon phenotypic variation in a population of organisms. Individuals whose phenotypes are better suited to a particular environmenttend to have greater reproductive success. For understanding Avidian phenotypes in selective environments, it is illustrative to use an analogy to bacteria processing sugar resources as food. When an individual bacterium is able to process a sugar in its environment it receives energy to be used for growth and reproduction; bacteria that can process the sugar will be favored due to natural selection. Similarly, when an Avidian is able to perform a function corresponding to a resource in its environment it is rewarded with an increased energy acquisition rate, producing offspring quicker; Avidians that can perform a function associated with an available resource will be favored due to natural selection. Random versus Directed Mutation Before scientists understood the nature of genetic mutation in biology, scientists hypothesized that bacteria could develop mutations depending on the circumstances or environment in which the bacteria resided –mutations were thought to be nonrandom or directed. For example, bacteria exposed to a selective environment were thought to be able to generate the necessary mutations that would allow them to evolve accordingly. To test if mutations were random versus directed Salvador Luria and Max Delbrück devised an elegant experiment that allowed them to differentiate between these two hypotheses1. We can investigate this same question in Avida-ED. In this exercise,you will perform an experiment with two treatments to test the relationship between mutation and selection –the time of appearance of a phenotype in a population under the presence or absence of a selective advantage. First you will record how many updates (a measure of time) it takes for a mutation conferring the ability to perform NOT to occur in an environment with all resources absent; there will be no reward for performing NOT. You will do the same in the second treatment but with notose present; performing NOT will be rewarded with increased energy acquisition rate. The NOT phenotype is only selectively advantageous in the second treatment.
31The Nobel prize-winning Fluctuation Test experiment: Luria, SE and M Delbrück. 1943. “Mutations of Bacteria from Virus Sensitivity to Virus Resistance.” Genetics28:491-511. Before you begin collecting data:Do you predict an Avidian performing NOT will appear quicker in the first or second treatment? Why? Timing the occurrence of phenotype-conferring mutations Treatment 1–First occurrence of NOT when all resources absent.
1.In the Population viewer,flip to Setup. ͒2.Drag“@ancestor”from the Freezer to the Ancestral Organism(s)box. ͒3.Set the following parameters: Dish Size 30×30; 2% Per Site Mutation Rate; Place Offspring Near their parent; Uncheck all resources; Repeatability Mode Experimental; Pause Run Manually.4.Return to Map view and select Run.
5.Pause your experiment right after the first occurrence of an organism that can perform the NOT function. There are two ways you can watch for this: ͒a.Basic method: Closely watch the number next to the NOT function in the “Population Statistics” panel, and be very quick on the Pause button or else record an approximate update value.
b.Advanced method: Select the“NOT”button to the left of the number in method (a), turning it green. A green line near the x-axis will appear on the Population Graph. Wait until the green line increases, then hover your cursor over its initial rise and note the exact update highlighted along the x-axis. 6. Record the up date number of this occurrence in Table1. Treatment 2-First occurrence of NOT when notose present. 1.In the Control menu choose“Start New Experiment.”
2.In the Population viewer, flip to Set up. ͒3.KeepallparameterssetasinTreatment1exceptaddnotosetotheenvironmentby͒marking notose with a check. Leave all other resources absent (unchecked).
͒4.Return to Map view and select Run. ͒5.Pause your experiment at the first occurrence of an organism that can perform the ͒NOT function, following one of the methods described in Treatment 1, step 4. ͒6.RecordtheUpdatenumberofthisoccurrenceinTable1. ͒
5Table 1. Updates (time) until first occurrence of an Avidian performing NOT, with and without notose present (a selective advantage or reward) in the environment.Environmental Treatment Update of first occurrence All resources absent (No reward for NOT)Notose present (Reward for NOT) Recording your data.Since experiments in biology often involve investigating processes or phenomena with lots of variation, we will be examining the data generated by the entire class. Once you’ve finished your treatments, report your data to the instructor.The instructor will show the tabulated data for the entire class.Discussion Questions and Wrap-up. After examining the course data, work with your lab team to respond to the following questions. x How does this experimental set up test whether mutation is random versus directed by the selective environment? xFor your results as shown in Table 1, did the first occurrence of the NOT phenotype happen earlier or later in Treatment 1 compared to Treatment 2? ͒xWas this the same for each person in your group, and for each person in the course? ͒xWhat pattern would you have expected to observe in the course data if mutations occur in response to the presence of a selective environment? ͒
6x Given the data you have examined across all Avida-ED experiments you have performed, how would you describe what it means that mutations are random?
͒x Thought experiment –How would evolution be affected if mutations did not occur (that is, a zero percent mutation rate)?
͒x Why is mutation essential to the evolutionary process?
͒x We used Avida-ED and this experimental protocol to model what occurs when biological populations experience mutation. What are some limitations or constraints to our modeling in this exercise?͒
Reflection and Meta cognition Think-Pair-Share: Work with your lab team to answer the following questions. x What did you learn from this exercise?
͒xWhat are you still wondering about? ͒xWhat would you change in this exercise?
