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Overview
Overview
Although evolution has major impacts on species, populations, and communities, we often think about it happening over very long time scales. While this is true, evolution can also happen rapidly for various reasons. Today we'll begin an experiment to explore this fact using bean beetles. This lab will also offer a chance to discuss the scientific method and for each group to carry out their own experiment.
Background
Background
For help with terms, check chapters 18-20 of Biology and chapter 11 of Concepts of Biology from OpenStax.
Objectives
Objectives
Design and perform an experiment to determine whether evolution by genetic drift or directional selection can be induced in laboratory populations of bean beetles, Callosobruchus maculatus.
Evaluate control and experimental populations to measure evolutionary change.
Explain the concepts of natural selection and drift, including being able to predict changes in gene frequencies due to these processes
Introduction
Introduction
Why do organisms look different from each other? And why do offspring resemble their parents? Understanding genetics provides parts of the answers to these questions.
Every somatic (body) cell in an adult (or any post-fertilization) organism contains the information that acts a blueprint for that organism; how that information is expressed determines how each cell operates. This information is carried in genes. A gene is a section of DNA that provides instructions on how to make molecules, typically proteins. Genes, along with environment, determine the traits (or phenotypes) an organism displays. Morphological, development, and behavioral traits can all be influenced by genes. Genes are located at a specific spot (a locus) on a chromosome (a long structure composed of DNA). The number of chromosomes varies among organisms. Humans have 46 total, while fruit flies have 8.
Diploid organisms, or those that are formed by the meeting of sex cells (gametes), like sperm and eggs, contain two copies of each gene (one from each parent). These genes are located on matching chromosomes (e.g,, humans have 23 pairs of chromosomes). There are often multiple forms, or versions, of a gene with-in a population. We call these forms alleles. Different versions of a gene originally arise due to mutations, or accidental changes that occur in the DNA code when a cell is replicated. Unless mutations occur, genes do not change across an organism's lifespan. If an organism receives the same allele from both parents, we consider the organism to have a homozygous genotype (genetic constitution) at that locus. If they receive different alleles from each parent, the organism is heterozygous. Unless mutations occur, genes do not change across an organism's lifespan. This also means mutations can only be passed on if they impact sex cells.
In heterozygous individuals, interactions among alleles can impact what traits organisms display. If one allele is dominant and the other is recessive, the phenotype (trait we can observe in the organism) will be the same in organisms that are heterozygous and those that are homozygous for the dominant allele (have two copies of the dominant allele). This means that traits associate with recessive alleles are only observed in organisms that are homozygous recessive (or that have two copies of the recessive allele). While the simulation we will study today focuses on a gene that only has two alleles, one being dominant and the other recessive, it should be noted that in nature most genes have multiple alleles, interactions may be more complex than simple dominance/recessiveness, and that most traits are impacted by multiple genes. Interactions among alleles explain multiple things people have observed in natural populations. For example, allele interactions can help explain why some traits appear to "skip" generations, why children can have different traits than either parents, and why some rare diseases are more common to appear in matings between closely-related individuals or in small populations.
In addition to allele interactions determining the traits we observe in organisms, some genes are only found in the chromosomes contributed by one parent. In humans, for example, the 23rd chromosome pair consists of the sex chromosomes. These chromosomes partially determine the sex of offspring. In humans males possess an X and Y chromosome, and females possess two X chromosomes. The X chromosome contains some genes that are not found on the Y chromosome. These are known as sex-linked genes, and males (with their X and Y chromosome) only have one copy of each gene. This means the allele contributed by the mother (on the X chromosome) is the only one that impacts phenotypes for some traits. This explains why some traits such as color-blindness are more common in males.
Since alleles interact to determine organismal traits, evolution can be defined as the change in allele frequency over time. The relative abundance, or frequency, of these alleles may change over generations for a variety of reasons, but they all rely on the fact that parents pass on copies of their genetic material to their offspring and that multiple forms, or alleles, exist for most genes in a population. Since genes can determine the ability of organisms to survive and reproduce (the fitness of an organism) by impacting the phenotype of organisms, genes that lead to organisms being more fit can become more common in a population through a process called natural selection. For example, if adult body mass varied in a population and the risk of predation were greater among the smallest individuals in the population, then the larger individuals would have greater survival and consequently greater reproductive success than the smaller individuals. If body mass was determined by genetic factors, or was heritable, we might expect successive populations to show larger and larger average body masses. We would call this directional selection. Besides directional selection, natural selection can also select for less variation in a trait (stabilizing selection) and for trait extremes (divergent selection).
It should be noted that evolution is a stochastic (random) process. You can't guarantee which alleles from each parent will unite in their offspring, and random events may befall any individual. However, selection tends to "favor" a certain phenotype and thus has predictable results . For example, we can predict how evolution will lead to antibiotic resistance in bacteria exposed to "fatal" levels of antibiotics.
This experiment also demonstrates why bacteria are both an excellent and frightening group in which we can observe evolution. This also shows why we can define evolution as genetically-based phenotypic change that occurs over generational time spans. Both these definitions imply the importance of genetic change and that populations, not individuals, evolve.
Although natural selection is typically the most potent cause for evolution and is the principal cause for evolutionary change, other processes, such as mutation, gene flow, and genetic drift also can cause evolution (Freeman and Herron 2007). While natural selection has predictable impacts on a population, these other causes for evolution can lead to random phenotypic changes in a population. As mentioned above, mutation is the spontaneous change in the genotype of an individual that may cause a change in the phenotype of the offspring of that individual. Gene flow occurs when the frequency of an allele in a population is influenced by the movement of individuals into a population (immigration) or movement out of a population (emigration). An extreme example is when a new allele is introduced to a population. Both mutation and gene flow can introduce alleles to a population that can then be acted upon by natural selection.
The stochastic nature of evolution, however, can also lead to random changes in allele frequency over time. We call this random evolution genetic drift, and it differs from selection in that results are less predictable. These random changes tend to be larger in small populations for a number of reasons. For example, when a population contains few individuals, even random mating may result in the loss of alleles and an increased frequency of homozygous genotypes compared to populations with greater numbers (Futuyma 1986). Genetic drift is thus a form of reproductive sampling error. To the extent that random changes in genotype frequencies result in changes in phenotypes, phenotypic evolution may occur as a consequence of genetic drift. Drift can even lead to non-optimal genotypes becoming more common or even fixed in a population.
Today we'll explore these issues by attempting to observe selection and drift in bean beetle cultures. Insects offer some of the best chances to observe evolution due to their short life span and ability to be cultured in the lab. Bean beetles (Callosobruchus maculatus) are small beetles (adults are ~ 2 mm in length) that lay eggs on dry bean species. Once hatched, larvae consume the bean, form a pupae, and burrow out as adults to reproduce. Adults feed sparingly and only live for a weeks. This life history strategy has led to the beetles becoming a major agricultural pest in some areas of the world.
In this study, you will design and conduct experiments to induce evolutionary change in an insect species, bean beetles (cowpea seed beetles), Callosobruchus maculatus. Bean beetles are agricultural pest insects of Africa and Asia. Females lay their eggs on the surface of beans (Family Fabaceae). Eggs are deposited (=oviposition) singly and several days after oviposition, a beetle larva (maggot) burrows into the bean. At 30°C, pupation and emergence of an adult beetle occurs 25-30 days after an egg was deposited. Adults are mature 24 - 36 hours after emergence and they do not need to feed. Adults may live for 7-10 days during which time mating and oviposition occurs (Mitchell 1975). Adult body mass, linear body dimensions, and egg-to-adult development-time are variable traits in C. maculatus. Consequently, these easily measured traits are candidates for inducing evolutionary change in laboratory populations. Previous studies have found that variation in body mass is heritable in both sexes but failed to find heritable variation in egg-to-adult development-time (Fox et al. 2004).
Methods
Methods
You'll now apply these ideas about designing experiments and evolution by considering if you can act as a form of selection for size in bean beetle cultures.
For this experiment we will explore the effects of selection by inducing evolution and/or the impacts of genetic drift. Regardless of what your particular lab group focuses on, make sure you understand both concepts. You also need to understand how science works in order to carry out an experiment. Drawing from our class and lab discussions, you should be able to predict how the evolutionary impacts of selecting for a trait in a population (selection) and the chance selection of traits due to stochasticity (genetic drift) differ. You'll use that information to hypothesize how your next generation of beetles will compare to those that are originally found in your culture. You'll next design and carry out an experiment to test these specific hypotheses. After a few weeks (science takes time!) we'll collect and analyze data and use our new knowledge to consider if our hypotheses did a good job describing how the world really works. Hypotheses are never true or false! We just compare two (or more) and decide which one is currently the best at explaining what we observe. Finally, you'll share your insights via a presentation to the class. For both the drift and selection experiments, we will focus on changes in beetle biomass. This is the same trait we studied during the population statistics lab; review techniques as needed.
Selection
Selection
To consider selection, first obtain a beetle culture. Mark the culture with your groups name so you can identify it later if needed. Sample 50 beetles if possible and construct a histogram of adult mass for each sex (NOTE: This lab can be combined with the the Population Statistics Lab for this step and with the Mark-Recapture lab; see here for more details). See page 8 of the Bean Beetle Handbook for help in determining the sex of beetles. Note that under optimal conditions mass should be noted immediately upon emergence, as adults do not feed and may also lose weight due to reproductive activity.
Once a histogram is constructed, select individuals (~10 males and females, 20 total) that are in the top or bottom of each mass distribution. Place these beetles in a new culture dish (containing only mung beans). This population will serve as your "selected" treatment. Randomly select another new population (~10 males and females, 20 total) and place them in a different new culture dish. This population will serve as your "control" treatment and is essential to final analysis. Mark all cultures with your groups name so you can identify them later if needed.
Monitor the new cultures for signs of egg deposition and eventual adult emergence. After about 2 weeks all original adults should be dead; remove them from cultures to make spotting emerging adults easier and to avoid between-generation contamination. Collect new adults upon hatching (~50) and construct histograms for males and females in each population.
Analysis
Differences in the mean beetle mass (total or for each sex) between populations may also be tested using a t-test or ANOVA. Here we demonstrate methods in Google Sheets (where you may be constructing histograms) and using external Vassar stat site (like in the Comparing Differences Among Groups lab).
T-tests in Google Sheets
In Google Sheets, place your data from the parent and offspring (selected) population in 2 columns.
Once entered, you can use the t.test function to consider difference among the group. Arguments (input) required for the function are:
=t.test(first data range, second data range, 2,3)
Note the last 2 arguments values are specified for use in this class and denote a request for a two-tailed test assuming the data do not have equal variances; these assumptions are given as explaining them is beyond the scope of this course.
The formula returns a p value, which is the probability that differences between the two groups are due to chance alone. p values range from 0 to 1, and generally we take p values that are less than .05 to indicate the mean of the two groups are not the same.
An example of how to graphically summarize and analyze data from a selection experiment is shared in the spreadsheet below. You can also get more help at Data Summaries in Google Sheets .
ANOVA from Vassarstats.net
A t-test is just a special case of an ANOVA, so here we use the ANOVA function from http://vassarstats.net . This (and other) ANOVA will allow you to compare differences among more than 2 groups.
When you get to the main page, click on the tab in the menu box on the right labeled "ANOVA". Then choose the option for "One-Way ANOVA"
Enter the number of samples (groups) in your analysis. In most cases this will be 2 (data from control and selected cultures).
For our purposes, select "Independent Samples" and then enter your data in the highlighted boxes.
You can likely copy from your Google Sheet!
Select "Calculate"
Intepret the resulting p-value
If you compared more than 2 groups, you can also do a Tukey HSD test to consider which group(s) is(are) different from which others
More notes on analysis and interpretation
Besides comparing the parent and selected population, you may also wish to carry out a parent-control comparison and control-selected comparison. Why should you do this, and what does each indicate?
Note that conducting a selection experiment to induce evolution requires the assumption that the observed variation in the trait being selected is caused by genetic differences between individuals (variation must be heritable). For example, we assume that parents with greater than average body mass will produce offspring with greater than average body mass and the same for body length. Egg-to-adult development has very small or zero heritability so even very extreme selection is unlikely to yield evolutionary change.
Genetic Drift
Genetic Drift
This experiment is simpler than a selection experiment since the characteristics of the treatment populations need not be quantified at the start of the experiment. Upon obtaining a beetle culture, start one new culture by selecting ~10 randomly chosen males and females (20 total); this will be the "control" culture. See page 8 of the Bean Beetle Handbook for help in determining the sex of beetles. Start another new "bottleneck" cultures by selecting ~ 3 randomly chosen males and females (6 total). Mark all cultures with your groups name so you can identify them later if needed. As in the selection experiment, the control and bottleneck treatments must be run simultaneously to ensure that any changes observed in the bottleneck treatments are due to drift and not environmental effects.
Monitor the new cultures for signs of egg deposition and eventual adult emergence. After about 2 weeks all original adults should be dead; remove them from cultures to make spotting emerging adults easier and to avoid between-generation contamination. Collect new adults upon hatching (~50) and construct histograms for males and females in each population. Differences in the mean beetle mass (total or for each sex) between each set of populations may also be tested using the method noted above.
References
References
This lab contains information from
Blumer, L. S. and C. W. Beck. 2010. Inducing Evolution in Bean Beetles. Page(s) 25-35, in Tested Studies for Laboratory Teaching, Volume 31 (K.L. Clase, Editor). Proceedings of the 31st Workshop/Conference of the Association for Biology Laboratory Education (ABLE), 534 pages. Used with permission.
Other options
Other options
Presentation for stand-alone lab (when not connected to other simulations or experiments) is below
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