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In this lesson, you'll learn how the Hardy-Weinberg equation relates to different evolutionary agents and population changes. Discover how the equation may be used to discover populations that are not in equilibrium.
So, we've seen how the Hardy-Weinberg equilibrium equation can be used to test the evolutionary status of a population. An evolutionary agent is any force that alters the genetic structure of a population. If no evolutionary agents are affecting a population, the population is in equilibrium because allelic and genotypic frequency is not changing. By using the Hardy-Weinberg equilibrium equation to analyze the allelic and genotypic frequencies within a population of flying hamsters, we were able to determine that the coat color trait is in equilibrium.
However, the real power of the Hardy-Weinberg equation is identifying populations that are not in equilibrium. When a population fails to comply with the Hardy-Weinberg equilibrium predictions, we can try to infer what evolutionary agent (or agents) is affecting the population. By generating an educated guess, or hypothesis, we can provide the basis for further experimentation to explore the evolution of that population.
Well, let's go out into the wild and start examining flying hamster populations.
Let's start with the population where we found the different tail colors.
You know, I'm thinking it'd probably a good idea to check out our lab notebook to refresh our memory about this trait. All right, according to our notes, the tail color trait was an example of incomplete dominance, meaning the heterozygote exhibits a phenotype that is partway between the two homozygotes. We used B to represent the blue-tail allele and Y to represent the yellow-tail allele. Hamsters with a BB genotype have blue tails, those with a BY genotype have green ones, and those with a YY genotype have yellow ones.
We could make a hypothesis that the population is in Hardy-Weinberg equilibrium. That will allow us to use the Hardy-Weinberg equation to determine whether that is true. If the population satisfies all of the requirements that we've discussed previously, our observed data should match the numbers predicted by the Hardy-Weinberg equilibrium equation.
After walking around the area and counting hamsters, we determine that the population contains 526 blue-tailed, 42 green-tailed, and 432 yellow-tailed hamsters.
Since each blue-tailed hamster contributes two B alleles and each green-tailed hamster contributes one B allele, there are 1,094 B alleles out of a gene pool of 2,000 alleles. That means that p = 0.547.
Since we determined earlier that p + q = 1, we can, therefore, say that q = 0.453.
Let's insert these values into our handy dandy Hardy-Weinberg equilibrium equation. We want to know the frequency at which each phenotypic clash should occur in the population. Each value in this equation represents one of those classes; therefore, if we solve for p^2 + 2pq + q^2, we can determine those frequencies. And since we're dealing with a population of 1,000 hamsters, we can predict how many of each type to expect if the population is in equilibrium. The equation predicts we should see 299 blue-tailed, 496 green-tailed, and 205 yellow-tailed hamsters. Since the number of hamsters in each category that we observed is different than what we expected, an evolutionary agent may be affecting the population.
But some variation beyond the predicted values has to be expected. For instance, just because I don't get exactly a 50/50 split when flipping a coin doesn't mean that there isn't a one in two chance of getting heads or tails. The question is 'how can I tell the difference between random variation between data sets and data sets that are significantly different?' To answer this question, we need to use statistics.
The chi-square test is a statistical test commonly used to determine if observed values are significantly different from expected values. If we evaluate our data with this test, we find that the difference is significant. That means we can reject our hypothesis that the population is in Hardy-Weinberg equilibrium and predict that one or more evolutionary agents are altering the population.
By conducting further studies, we may be able to make a hypothesis to identify the major evolutionary agents affecting the population.
For instance, while we were doing our counts, I noticed that the blue-tailed hamsters seem to prefer to mate with other blue-tailed hamsters and yellow-tailed hamsters tend to mate with other yellow-tailed ones. This observation may be an indication that hamsters in the population do not mate randomly. Non-random mating alters genotypic frequency, which in turn alters the phenotypic composition of a population.
Okay, great. That could make for a really interesting research project. Although we can't exclude other possibilities simply based on this observation, we can perform some controlled experiments to provide more evidence to support our hypothesis. But let's do that later. For now, let's continue our field research.
Let's shift our studies to the fire-breathing trait. If we refer to our lab notebook again, we see that the fire-breathing trait is a recessive autosomal trait. We represented the non-fire-breathing allele with 'F' and the fire-breathing allele with 'f.'
So let's count the hamsters in the population; however, this time we'll need to perform a genotyping test to distinguish FF from Ff individuals. Those efforts yield the following results: 119 FF, 265 Ff, and 616 fire-breathing hamsters (ff).
As before, we can use this data to calculate the allelic frequency. 119 FF hamsters translate to 238 F alleles and 265 Ff hamsters contribute 265 F alleles to the gene pool. That means that out of a 2,000-allele gene pool, 503 are F. We can simplify this information as p = 0.252. And, plugging that p value into our allelic equation, p + q = 1, we find that q = 0.748.
Now, if we plug those values into the Hardy-Weinberg equilibrium equation, we predict we should see 63 FF, 377 Ff, and 560 fire-breathing hamsters.
A statistical analysis of the expected-versus-observed data tells us that we can reject the hypothesis that the population is in equilibrium with respect to the fire-breathing gene. I think our observations while counting and typing the hamsters in the population again provide a strong indication regarding at least one evolutionary agent that may be affecting the population. We saw more than one fire-breathing hamster use its breath to defend itself from predators while their poor, non-fire-breathing counterparts were eaten. What evolutionary agent do you think could be working here? Since it seems like one phenotype has a survival advantage over another, it seems like natural selection is providing fire-breathing hamsters in this population of beast with the opportunity to contribute more offspring to the next generation. Again, further studies could provide evidence for this hypothesis.
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Well, so far, I think we've collected a lot of interesting data, certainly enough for each of us to perform our own independent research.
Just as we're about to go back to the lab, though, we find an amazing discovery. There in front of us is a flying hamster that somehow appears to have wings that move more like a helicopter than the flying hamster wings we're used to seeing. However, just as we're about to capture it, we watch in horror as a giant boulder falls off a hill and crushes it.
Okay, no problem. We'll just find another. I mean it's not like we haven't been counting thousands of hamsters during our field study or anything.
As we count the hamsters in this population, we find that the population is actually really small and we can't find another helicopter hamster! Whereas we've been counting a thousand hamsters in the other populations, we can only find five others in this population. Because the population was so small, a random event that killed the helicopter hamster has drastically altered the genetic makeup of the population because it happened to be the only hamster with that phenotype. The random loss of individuals and the alleles they possess is called genetic drift.
Now you can see why Hardy-Weinberg equilibrium requires a large population. The larger the population, the easier it is for the population to absorb random loss of alleles without any significant affect on the gene pool. When population size decreases significantly, as seen in this example, the population is said to experience a population bottleneck.
We also learned about another form of genetic drift earlier, when we considered the example of stronger-winged hamsters escaping the devastation of a volcanic explosion on an island. Only a subset of the population was able to survive by moving to a new piece of land. The strong-winged hamster may have been the minority phenotype in the old population, but they are the majority now. This special form of a population bottleneck, in which a small group leaves the main population to form a new population, is called the founder effect.
The disproportionate representation of the alleles in the population causes a drastic change in the gene pool and disrupts equilibrium.
In summary, an evolutionary agent is any force that alters the genetic structure of a population.
The Hardy-Weinberg equation can be used to identify populations that are not in equilibrium.
A hypothesis is an educated guess proposed to explain a phenomenon.
Non-random mating is an evolutionary agent that alters genotypic frequency.
Natural selection is an evolutionary agent that allows certain individuals in a population to contribute more offspring to the next generation relative to the others.
Genetic drift is the random loss of individuals and the alleles they possess.
A population bottleneck occurs when a population decreases significantly in size.
The founder effect is a special form of population bottleneck in which a small group leaves the main population to form a new population.
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