CK-12 Biology I - Honors
Page 58
A change in allele frequencies within a population from one generation to the next – even if it involves only a single gene - is evolution. Biologists refer to this change in the gene pool as microevolution because it is evolution on the smallest scale. For our rabbit population from the previous lesson, a generation-to-generation increase in the frequency of the albino allele, b, from 0.3 to 0.4 (and the corresponding decrease in the frequency of allele B from 0.7 to 0.6) would be microevolution. The changes in Galapagos finch beak size, documented by Peter and Rosemary Grant, and the color changes of peppered moths will undoubtedly show corresponding changes in allele frequencies once we identify the responsible genes and alleles. Resistance to antibiotics in bacteria and the appearance of new strains of influenza viruses and HIV Figure below also involve changes in allele frequencies. Each of these is an example of microevolution.
Figure 13.9
This portion of the evolutionary tree for Human Immunodeficiency Virus (HIV) shows 8 or more strains of the HIV-1 M (Main) group, and a single strain of the HIV-1 N (Not Main/Not Outlier) group. The complete tree includes strains of SIV (Simian Immunodeficiency Virus). Each strain represents a change in allele frequencies.
What forces cause changes in allele frequencies? What mechanisms determine how microevolution happens? Before we tackle these questions, we will examine a population at equilibrium – a population which is not evolving.
Populations at Equilibrium: The Hardy-Weinberg Model
Like Darwin and Wallace, who independently developed similar ideas about evolution and natural selection, mathematician Godfrey Hardy and physician Wilhelm Weinberg independently developed a model of populations at equilibrium. The Hardy-Weinberg model (sometimes called a law) states that a population will remain at genetic equilibrium - with constant allele and genotype frequencies and no evolution - as long as five conditions are met:
No mutation
No migration
Very large population size
Random mating
No natural selection
We will consider the above in more detail in later sections of the lesson, because deviations from these conditions are the causes of evolutionary change. For now, let’s look more closely at the Hardy-Weinberg’s equilibrium model. We’ll use another hypothetical rabbit population to make the model concrete: 9 albino rabbits and 91 brown rabbits (49 homozygous and 42 heterozygous). The gene pool contains 140 B alleles and 60 b alleles – gene frequencies of 0.7 and 0.3, respectively. Figure below summarizes the data for this parent population.
Figure 13.10
The coat color gene pool for a hypothetical rabbit population includes two alleles. Genotype and allele frequencies are calculated, given the number of individuals having each of the three possible genotypes.
If we assume that alleles sort independently and segregate randomly as sperm and eggs form, and that mating and fertilization are also random, the probability that an offspring will receive a particular allele from the gene pool is identical to the frequency of that allele in the population. A Punnett Square (Figure below) using these frequencies predicts the probability of each genotype (and phenotype) in the next generation:
Figure 13.11
A Punnett Square predicts the probability of each genotype and phenotype for the offspring of the population described in . A summarizes the frequencies of each genotype among offspring, and B calculates allele frequencies for the next generation. Comparing these to the parent generation shows that the gene pool remains constant. The population is stable at a Hardy-Weinberg equilibrium.
If we calculate the frequency of genotypes among the offspring predicted by the Punnett square, they are identical to the genotype frequencies of the parents. Allele frequency remains constant as well. The population is stable – at a Hardy-Weinberg genetic equilibrium.
A useful equation generalizes the calculations we’ve just completed. Variables include p = the frequency of one allele (we’ll use allele B here) and q = the frequency of the second allele (b, in this example). We will use only two alleles, but similar, valid equations can be written for more alleles.
Recall that the allele frequency equals the probability of any particular gamete receiving that allele. Therefore, when egg and sperm combine, the probability of any genotype (as in the Punnett square above) is the product of the probabilities of the alleles in that genotype. So:
Probability of genotype BB = p X p = p2 and
Probability of genotype Bb= (p X q) + (q X p) = 2 pq and
Probability of genotype bb = q X q = q2
We have included all possible genotypes, so the probabilities must add to 1.0. Our equation becomes:
p2 + 2 pq + q2 = 1
frequency of genotype BB frequency of genotype Bb frequency of genotype bb
This is the Hardy-Weinberg equation, which describes the relationship between allele frequencies and genotype frequencies for a population at equilibrium.
The equation can be used to determine genotype frequencies if allele frequencies are known, or allele frequencies if genotype frequencies are known. Let’s use a common human genetic disease as an example. Cystic fibrosis (CF) is caused by a recessive allele (f) which makes a non-functional chloride ion channel, leading to excessive mucus in the lungs, inadequate enzyme secretion by the pancreas, and early death (Figure below).
Figure 13.12
Cystic fibrosis is an inherited disease of the lungs and pancreas. A recessive allele of a gene for a chloride ion channel located on chromosome 7 (the gene locus is colored red, right) causes the disease. Treatment includes ventilator and antibiotic therapy (above).
Knowing that 1 of every 3,900 children in the United States is born with CF, we can use the Hardy-Weinberg equation to ask what proportion of the population unknowingly carries the allele for cystic fibrosis. An individual who has CF must have the genotype ff, because the allele is recessive. Using the value for the frequency of the homozygous recessive genotype, we can calculate q, the frequency of the recessive allele,f:
1/3900 = 0.0002564 = frequency of ff genotypes = q2
To find q, the frequency of allele f, we must take the square root of the frequency of ff genotypes:
q = √0.0002564 = 0.016 = frequency of the f allele
Because p + q = 1 (the sum of the frequency of allele f and the frequency of allele F must equal 1.0),
p = 1 – q = 1.0 – 0.0160 = 0.9840 = frequency of the F allele
According to the Hardy-Weinberg equation, for a population at equilibrium the frequency of carrier genotypes, Ff, is 2pq = 2 X 0.016 X 0.984 = 0.0315.
In other words, if the population is indeed at equilibrium for this gene, just over 3% of the population carries the recessive allele for cystic fibrosis.
Of course, this calculation holds only true if the US population meets the five conditions we listed at the beginning of this section. In nature, populations seldom satisfy all five criteria. Let’s consider how well each condition describes the US population for the cystic fibrosis gene:
Very Large Population Size
Although the equation ideally describes an infinitely large population – never found in nature, of course – the US population is probably large enough that this condition alone does not significantly disrupt equilibrium.
No Mutation
Mutations happen constantly, if at a low rate, so “no mutation” is a second unrealistic condition. However, mutations affecting any one particular gene are rare, so their effect on an otherwise large, stable population is small.
No Migration
This condition assumes no net additions or losses of either allele to the gene pool through immigration or emigration. For the US population, immigration is probably more significant than emigration. Gene flow, in essence is the flow of alleles into or out of a population, may be the most significant problem for this particular gene, because the frequency of the allele for cystic fibrosis varies greatly according to ancestry. Although 1 in 25 Europeans carry the f al
lele, the frequency is just 1 in 46 among Hispanics, 1 in 60 among Africans, and 1 in 90 among Asians. Therefore, disproportionate immigration by certain groups changes allele frequencies, destabilizing the Hardy-Weinberg equilibrium.
Random Mating
Here is another assumption which is probably not realistic. Marriage between individuals of similar ancestry and culture is still more common than intermarriage, although both occur. If marriages are not random, Hardy-Weinberg equilibrium does not apply.
No Natural Selection
The final condition is that all genotypes must have an equal chance to survive and reproduce. Victims of cystic fibrosis (genotype ff) have shorter lifespans, which inevitably reduce reproduction compared to individuals without the disease (genotypes FF and Ff). Although medical care is improving, differential survival and reproduction among genotypes means the gene pool is not at equilibrium.
With respect to the cystic fibrosis gene, the U.S. population fails to meet at least three of the criteria for equilibrium. Therefore, the actual frequencies of alleles and genotypes probably deviate somewhat from those we calculated.
In nature, very few populations meet the Hardy-Weinberg requirements for equilibrium. If we look at this fact from a different angle, we see that any of these conditions can destabilize equilibrium, causing a change in allele frequencies. In other words, these five conditions are five major causes of microevolution. The remaining sections of this lesson will explore each cause in detail.
Causes of Microevolution: Mutation and Gene Flow
As discussed in the last lesson, mutation – a random, accidental change in the sequence of nucleotides in DNA – is the original source of genetic variation. Only mutation can create new alleles – new raw material for natural selection. UV or ionizing radiation, chemicals, and viruses constantly generate mutations in a gene pool, destabilizing genetic equilibrium and creating the potential for adaptation to changing environments. However, both rates of mutation and their effects on the fitness of the organism vary.
In multicellular organisms, most mutations occur in body cells and do not affect eggs and sperm; these are lost when the individual dies and usually do not affect evolution. Only mutations in gamete-producing cells can become part of the gene pool. The rate at which mutations enter the gene pool is low, due to DNA “proofreading” and repair enzymes - and the extensive amount of “junk” DNA which does not code for protein. Mutations which do change nucleotide sequences in functional genes may also have no effect, because the Genetic Code is redundant (multiple similar codons for a single amino acid), or very little effect, if the amino acid is not located in a critical part of the protein.
Occasionally, however, a single nucleotide substitution can have a major effect on a protein – as we saw with sickle-cell anemia in the last lesson. Usually, the effect of a mutation on a protein is harmful; rarely is it helpful. In sickle-cell anemia, it is both – in certain environments. Sickled cells carry oxygen much less efficiently, but prevent malaria infections. Overall, the chance that a single mutation will increase the fitness of a multicellular organism is extremely low. If the environment changes, however, the adaptive value of a new allele may change as well. Over time, mutations accumulate, providing the variation needed for natural selection.
For the small genomes of viruses and bacteria, mutations affect genes directly and generation times are short, so rates of mutation are much higher. For an HIV population in one AIDS patient, rates of viral mutation and replication are so high that in a single day, every site in the HIV genome may have experienced mutation (Figure below). This rapid generation of new alleles challenges our best efforts at drug treatment, and explains the evolution of drug antibiotic resistance. Because of the abundance of random, spontaneous mutations, HIV generates a large amount of raw material for natural selection, and readily evolves resistance to new “environments” created by single drugs (Figure below). Drug “cocktails,” which contain multiple anti-viral chemicals, are our effort to change the “environment” and keep up with mutation in the human-HIV evolutionary race. For microorganisms, mutation is a strong force for evolution.
Figure 13.13
HIV daughter particles are shed from an infected human T-cell host. HIV replication and mutation rates are so high that during a single day, the HIV population in one AIDS patient generates mutations at every site in the HIV genome. New alleles provide the potential for extremely rapid evolution, including the development of resistance to drugs.
Figure 13.14
Extremely high HIV mutation rates provide many new alleles raw material for natural selection in AIDS patients. This variation allows at least some mutant viruses to survive and reproduce in the changing environments of new drug therapies. The graph shows the effects of one type of drug: an initial decrease in the HIV population and a temporary rise in the number of human host (CD4) cells. Before long, however, mutants have alleles conferring drug resistance appear and begin to reproduce, and the population recovers. This change in allele frequencies is microevolution, caused by mutation and natural selection.
For all organisms, mutations are the ultimate source of genetic variation. For a population, however, the immigration or emigration of individuals or gametes may also add to or subtract from a gene pool – a process known as gene flow. For example, wind or animals can carry pollen or seeds from one plant population to another. In baboon troops or wolf packs (Figure below), juvenile males may leave the group to find mates and establish separate populations. Human history includes countless migrations; gene flow continues to mix gene pools and cause microevolutionary change.
Figure 13.15
Dominant alpha wolves lead their pack in Yellowstone National Park. The lowest ranking omega individual, in the rear, may eventually leave the pack to find a mate and establish his own territory and pack. He would carry some of the genes from his pack to the new one a form of gene flow which seems built in to wolves social organization.
Gene flow can bring into a population new alleles which occurred by chance and were successful in other populations. In this way, it can accelerate microevolution. However, if exchange between populations is frequent, it reduces differences between populations, in effect increasing population size. In this case, gene flow tends to maintain separate populations as one species, reducing speciation, if not microevolution.
Mutation, together with recombination of existing alleles by sexual reproduction (see lesson 13.1) provides the diversity which is the raw material for natural selection and evolution. Gene flow can accelerate the spread of alleles or reduce the differences between populations. Both can contribute significantly to microevolution. However, many biologists consider the major causes of microevolutionary change to be genetic drift and natural selection.
Causes of Microevolution: Population Size and Genetic Drift
Recall that the third requirement for Hardy-Weinberg equilibrium is a very large population size. This is because chance variations in allele frequencies are minimal in large populations. In small populations, random variations in allele frequencies can significantly influence the “survival” of any allele, regardless of its adaptive value. Random changes in allele frequencies in small populations are known as genetic drift. Many biologists think that genetic drift is a major cause of microevolution.
You see the effects of chance when you flip a coin. If you flipped a penny 4 times, you would not be too surprised if it came up heads 4 times and tails not at all. If you tossed it 100 times, you would be very surprised if the results were 100 heads and no tails. The larger the “population” of coin tosses, the lower the effects of chance, and the closer the results should match the expected 50-50 ratio. The same is true for populations. If we imagine a rabbit population with a very small gene pool of just 2 B alleles and 2 b alleles, it is not difficult to understand that occasionally, chance alone would result in no albino offspring (only genotypes BB or Bb) – or even no brown offspring (only genotype bb). However, a gene pool of 1
00 B alleles and 100 b alleles would be very unlikely to produce a generation of offspring entirely lacking one allele or the other, despite having identical initial allele frequencies of 0.5.
Because chance governs meiosis and fertilization, random variations can influence allele frequencies, especially for small populations. Note that these chance variations can increase the frequency of alleles which have no adaptive advantages or disadvantages – or decrease the frequency of alleles which do have adaptive value. Genetic drift can result in extinction of an allele or an entire population – or rapid evolution (Figure below). Two sets of circumstances can create small populations for which genetic drift can have major consequences: the bottleneck effect and the founder effect.
Figure 13.16
Computer models show that the effect of small population size on allele frequencies is a significant increase in variation due to chance. Each line depicts a different allele. In the small population (above), most of 20 alleles, beginning at frequencies of 0.5, become either fixed (frequency = 1.0) or extinct (frequency = 0) within 5 25 generations. In the larger population (below), only one pair of alleles shows fixation/extinction and that occurs only after 45 generations. Note that these variations are independent of natural selection; they do not necessary fit the organism to its environment.
The Bottleneck Effect
Natural catastrophes such as earthquakes, floods, fires, or droughts can drastically reduce population size – usually without respect to allele frequencies. As a result of the disaster, some alleles may be lost entirely, and others may be present in frequencies which differ from those of the original population. The smaller population is then subject to genetic drift, which may further reduce diversity within the population. The loss of diversity resulting from a drastic reduction in population size and subsequent genetic drift is the bottleneck effect (Figure below). Much of our concern for endangered species derives from our understanding of the way in which small population size can reduce diversity by increasing genetic drift. We will look at two examples of the bottleneck effect – one caused by humans, and the other probably experienced by our human ancestors.