Submitted the document for the case study in “Changing Allele Frequencies” and it contained the following:
Explained why the increased prevalence of sickle-cell disease among African Americans has more to do with the environmental factors than the skin color or other phenotypes used to define races. (10)
Described other examples of balanced polymorphism. (10)
Identified a population group (other than African Americans) with a high prevalence of sickle-cell disease. (10)
Listed six genetic diseases more common among Ashkenazi Jews than among other population groups. (10)
Week8 textbook info
14.1 Population Genetics Underlies Evolution
1. State the unit of information of genetics at the population level.
2. Define gene pool.
3. List the five processes that cause microevolutionary change.
4. State the consequence of macroevolutionary change.
14.2 Constant Allele Frequencies
5. State the genotypes represented in each part of the Hardy-Weinberg equation.
6. Explain the conditions necessary for Hardy-Weinberg equilibrium.
14.3 Applying Hardy-Weinberg Equilibrium
7. Explain how the Hardy-Weinberg equilibrium uses population incidence statistics to predict the probability of a particular phenotype.
14.4 DNA Profiling Uses Hardy-Weinberg Assumptions
8. Explain how parts of the genome that are in Hardy-Weinberg equilibrium can be used to identify individuals.
image The BIG Picture
Human genetics at the population level considers allele frequencies. Some parts of the genome that have changed over time enable us to trace our origins, migrations, and relationships. Allele frequencies that do not change in response to environmental factors provide a way to distinguish individuals.
Postconviction DNA Testing
Josiah Sutton had served 4 1/2 years of a 25-year sentence for rape when he was exonerated, thanks to the Innocence Project. The nonprofit legal clinic and public policy organization created in 1992 has used DNA retesting to free more than 312 wrongfully convicted prisoners, most of whom were “poor, forgotten, and have used up all legal avenues for relief,” according to the website (www.innocenceproject.com). Sutton became a suspect after a woman in Houston identified him and a friend 5 days after she had been raped, threatened with a gun, and left in a field. The two young men supplied saliva and blood samples, from which DNA profiles were done and compared to DNA profiles from semen found in the victim and in her car. At the trial, a crime lab employee testified that the probability that Sutton’s DNA matched that of the evidence by chance was 1 in 694,000, leading to a conviction. Jurors ignored the fact that Sutton’s physical description did not match the victim’s description of her assailant.
The DNA evidence came from more than one individual, yielded different results when the testing was repeated, and most importantly, looked at only seven of the parts of the genome that are typically compared in a DNA profile, or fingerprint. Doing the test correctly and considering more forensic “alleles” revised the statistics dramatically: Sutton’s pattern was shared not with 1 in 694,000 black men, as had originally been claimed, but with 1 in 16.
While in jail, Sutton read about DNA profiling and requested independent testing, but was refused. Then journalists investigating the Houston crime laboratory learned of his case and alerted the Page 264Innocence Project. Retesting the DNA evidence set Sutton free. DNA profiling is based on how common a suspect’s gene variants are in the appropriate population. The technology is a direct application of population genetics.
14.1 Population Genetics Underlies Evolution
The language of genetics at the family and individual levels is written in DNA sequences. At the population level, the language of genetics is allele (gene variant) frequencies. It is at the population level that genetics goes beyond science, embracing information from history, anthropology, human behavior, and sociology. Population genetics enables us to trace our beginnings, understand our diversity today, and imagine the future.
A biological population is any group of members of the same species in a given geographical area that can mate and produce fertile offspring (figure 14.1). A population in a sociological sense may be more restrictive, such as ethnic groups or economic strata. Population genetics is a branch of genetics that considers all the alleles of all the genes in a biological population, which constitute the gene pool. The “pool” refers to the collection of gametes in the population; an offspring represents two gametes from the pool. Alleles can move between populations when individuals migrate and mate. This movement, termed gene flow, underlies evolution, which is explored in the next two chapters.
Thinking about genes at the population level begins by considering frequencies—that is, how often a particular gene variant occurs in a particular population. Such frequencies can be calculated for alleles, genotypes, or phenotypes, and may include single base mutations or numbers of short, repeated DNA sequences. For example, an allele frequency for the cystic fibrosis gene (CFTR) might be the number of ΔF508 alleles among the residents of San Francisco. ΔF508 is the most common allele that, when homozygous, causes the disorder. The allele frequency derives from the two ΔF508 alleles in each person with CF, plus alleles carried in heterozygotes, considered as a proportion of all alleles for that gene in the gene pool of San Francisco. The genotype frequencies are the proportions of heterozygotes and the two types of homozygotes in the population. Finally, a phenotypic frequency is simply the percentage of people in the population who have CF (or who do not). With multiple alleles for a single gene, the situation becomes more complex because there are many more phenotypes and genotypes to consider.
Figure 14.1 A biological population is a group of interbreeding organisms living in the same place. Populations of sexually reproducing organisms include many genetic variants. This genetic diversity gives the group a flexibility that enhances species survival. To us, these hippos look alike, but they can undoubtedly recognize phenotypic differences in each other.
Phenotypic frequencies are determined empirically—that is, by observing how common a condition or trait is in a population. Genetic counselors use phenotype frequency to estimate the risk that a particular inherited disorder will occur in an individual when there is no family history of the illness. Table 14.1 shows disease incidence for phenylketonuria (PKU), an inborn error of metabolism that causes intellectual disability unless the person follows a special, low-protein diet from birth. Note how the frequency differs in different populations. A person from Turkey without a family history of PKU would have a higher risk of having an affected child than a person from Japan.
On a broader level, shifting allele frequencies in populations reflect small steps of genetic change, called microevolution. These small, step-by-step changes alter genotype frequencies and underlie evolution. Genotype frequencies rarely stay constant. They can change under any of the following conditions:
Individuals of one genotype are more likely to choose to reproduce with each other than with individuals of other genotypes (nonrandom mating).
Individuals move between populations (migration).
Random sampling of gametes alters allele frequencies (genetic drift).
Page 265New alleles arise (mutation).
People with a particular genotype are more likely to produce viable, fertile offspring under a specific environmental condition than individuals with other genotypes (natural selection).
In today’s world, all of these conditions, except mutation, are quite common. Therefore, genetic equilibrium—when allele frequencies are not changing—is rare. Put another way, given our tendency to pick our own partners and move about, microevolution is not only possible, but also nearly unavoidable. (Chapter 15 considers these factors in depth.)
When sufficient microevolutionary changes accumulate to keep two fertile organisms of opposite sex from producing fertile offspring together, a new species forms. Changes that are great enough to result in speciation are termed macroevolution. Speciation can occur through many small changes over time, and/or a few changes that greatly affect the phenotype.
Key Concepts Questions 14.1
What is a biological population?
What is a gene pool?
What are microevolution and macroevolution?
What are the five factors that can change genotype frequencies?
14.2 Constant Allele Frequencies
Before we consider the pervasive genetic evidence for evolution, this chapter discusses the interesting, but unusual, situation in which frequencies for certain alleles stay constant. This is a condition called Hardy-Weinberg equilibrium.
In 1908, Cambridge University mathematician Godfrey Harold Hardy (1877–1947) and Wilhelm Weinberg (1862–1937), a German physician interested in genetics, independently used algebra to explain how allele frequencies can be used to predict phenotypic and genotypic frequencies in populations of diploid, sexually reproducing organisms.
Hardy unintentionally cofounded the field of population genetics with a simple letter published in the journal Science. The letter began with a curious mix of modesty and condescension:
I am reluctant to intrude in a discussion concerning matters of which I have no expert knowledge, and I should have expected the very simple point which I wish to make to have been familiar to biologists.
Hardy continued to explain how mathematically inept biologists had incorrectly deduced from Mendel’s work that dominant traits would increase in populations while recessive traits would become rarer. At first glance, this seems logical. However, it is untrue because recessive alleles enter populations by mutation or migration and are maintained in heterozygotes. Recessive alleles also become more common when they confer a reproductive advantage, thanks to natural selection.
Hardy and Weinberg disproved the assumption that dominant traits increase while recessive traits decrease using the language of algebra. The expression of population genetics in algebraic terms begins with the simple equation
where p represents the frequency of all dominant alleles for a gene and q represents the frequency of all recessive alleles. The expression “p + q = 1.0” means that all the dominant alleles and all the recessive alleles comprise all the alleles for that gene in a population.
Next, Hardy and Weinberg described the possible genotypes for a gene with two alleles using the binomial expansion
In this equation, p2 represents the proportion of homozygous dominant individuals, q2 represents the proportion of homozygous recessive individuals, and 2pq represents the proportion of heterozygotes (figure 14.2). The letter p designates the frequency of a dominant allele, and q is the frequency of a recessive allele. Figure 14.3 shows how the binomial expansion is derived from allele frequencies. Note that the derivation is conceptually the same as tracing alleles in a monohybrid cross, in which the heterozygote forms in two ways: a from the mother and A from the father, or vice versa (see figure 4.4).
The binomial expansion used to describe genes in populations became known as the Hardy-Weinberg equation. It can reveal the changes in allele frequency that underlie evolution. If the proportion of genotypes remains the same from generation to generation, as the equation indicates, then that gene is not evolving (changing). This situation, Hardy-Weinberg equilibrium, is theoretical. It happens only if the population is large and undisturbed. That is, its members mate at random, do not migrate, and there is no genetic drift, mutation, or natural selection.
Figure 14.2 The Hardy-Weinberg equation in English.
Figure 14.3 Source of the Hardy-Weinberg equation. A variation on a Punnett square reveals how random mating in a population in which gene A has two alleles—A and a—generates genotypes aa, AA, and Aa, in the relationship p2 + 2pq + q2.
15.1 Nonrandom Mating
1. Explain how nonrandom mating changes allele frequencies in populations.
2. Explain how migration changes allele frequencies in populations.
15.3 Genetic Drift
3. Explain how the random fluctuations of genetic drift affect genetic diversity.
4. Discuss how founder effects and population bottlenecks amplify genetic drift.
5. Discuss how mutation affects population genetic structure.
15.5 Natural Selection
6. Provide examples of negative, positive, and artificial selection.
7. Explain how balanced polymorphism maintains diseases in populations.
8. Explain how eugenics attempts to alter allele frequencies.
image The BIG Picture
Several forces mold populations, which over time drive evolution. They are nonrandom mating, migration, genetic drift, mutation, and natural selection.
The Evolution of Lactose Tolerance
For millions of people who have lactose (milk sugar) intolerance, dairy food causes cramps, bloating, gas, and diarrhea. They no longer produce lactase, which is an enzyme made in early childhood that breaks down the milk sugar lactose into more easily digested sugars. But people who have lactose intolerance may represent the “normal,” or wild type condition. Only 35 percent of people in the world can digest lactose into adulthood. People who can digest dairy foods have lactase persistence (OMIM 223000). One gene controls the ability to digest milk sugar.
Clues in DNA suggest that agriculture drove the differences in our abilities to digest lactose. As dairy farming spread around the world, from 5,000 to 10,000 years ago, people who had gene variants enabling them to digest milk into adulthood had an advantage. They could eat a greater variety of the now more plentiful foods, were healthier, and had more children. Over time, populations that consumed dairy foods had more people with lactase persistence. In contrast, in populations with few or no dairy foods, lactose intolerance was not a problem, and so those gene variants persisted.
The link between lactose intolerance and agriculture is why today, the European American population only has 10 percent lactose intolerance. Among Asian Americans, who eat far less dairy, 90 percent have lactose intolerance. That is, the inability to digest lactose doesn’t bother them. Seventy-five percent of African Americans and Native Americans have lactose intolerance.
15.1 Nonrandom Mating
Many aspects of modern life alter allele frequencies, and so many genes are not in Hardy-Weinberg equilibrium, defined as unchanging allele frequencies from generation to generation. Religious restrictions and personal preferences guide our choices of mates. Wars and persecution kill certain populations. Economic and political systems enable some groups to have more children. We travel, shuttling genes in and out of populations. Natural disasters and new diseases reduce populations to a few individuals, who then rebuild their numbers, at the expense of genetic diversity. These factors, plus mutation and a reshuffling of genes at each generation, make a gene pool very fluid.
The ever-present and interacting forces of nonrandom mating, migration, genetic drift, mutation, and natural selection shape populations at the allele level. Changing allele frequencies can change genotype frequencies, which in turn can change phenotype frequencies. In a series of illustrations throughout this chapter, colored shapes represent alleles. Figure 15.16 combines the illustrations to summarize the chapter. We begin our look at the forces that change allele frequencies in populations with nonrandom mating (figure 15.1).
In the theoretical state of Hardy-Weinberg equilibrium, individuals of all genotypes are equally likely to successfully mate and to choose partners at random. In reality we choose partners for many reasons: physical appearance, ethnic background, intelligence, and shared interests, to name a few (figure 15.2). This nonrandom mating is a major factor in changing allele frequencies in human populations.
Figure 15.1 Nonrandom mating alters allele frequencies. More successful mating among individuals with the blue triangle allele will skew allele frequencies in the next generation.
Nonrandom mating occurs when certain individuals contribute more to the next generation than others. This is common in agriculture when semen from one prize bull is used to inseminate thousands of cows, and a similar situation has happened when many families used the same sperm donor to conceive children. One such man fathered 150 children. High prevalence of an otherwise rare inherited condition can be due to nonrandom mating. For example, a form of albinism is uncommon in the general U.S. population, but it affects 1 in 200 Hopi Indians who live in Arizona. The reason for the trait’s prevalence is cultural—men with albinism often stay back and help the women, rather than risk severe sunburn in the fields with the other men. They contribute more children to the population because they have more contact with the women.
The events of history can lead to nonrandom mating patterns. When a group of people is subservient to another, genes tend to “flow” from one group to the other as the males of the ruling class have children with females of the underclass—often forcibly. Historical records and DNA sequences show this directional gene flow phenomenon. For example, Y chromosome analysis suggests that Genghis Khan, a Mongolian warrior who lived from 1162 to 1227, had sex with so many women that today, 1 in every 200 males living between Afghanistan and northeast China shares his Y—that’s 16 million men. The number is so high because his many male descendants also passed on the distinctive Y.
Figure 15.2 Nonrandom mating. We marry people similar to ourselves about 80 percent of the time. In the 1990s, worldwide, about one-third of all marriages were between people who were born fewer than 10 miles apart. The Internet may change that statistic!
Page 281Traits may mix randomly in the next generation if we are unaware of them or do not consider them in choosing partners. In populations where AIDS is extremely rare or nonexistent, for example, the two mutations that render a person resistant to HIV infection are in Hardy-Weinberg equilibrium. This would change, over time, if HIV arrives, because the people with these mutations would become more likely to survive to produce offspring—and some of them would perpetuate the protective mutation. Natural selection would intervene, ultimately altering allele frequencies.
Many blood types are in Hardy-Weinberg equilibrium because we do not choose partners by blood type. Yet sometimes the opposite situation occurs. People with mutations in the same gene meet when their families participate in programs for people with the associated disorder. For example, more than two-thirds of relatives visiting a camp for children with cystic fibrosis are likely to be carriers, compared to the 1 in 23 or fewer in large population groups.
People can avoid genetic disease with controlled mate choice and reproduction. In a program that began in New York City called Dor Yeshorim, for example, young people take tests for more than a dozen genetic disorders that are much more common among Jewish people of Eastern European descent (Ashkenazim). Results are stored in a confidential database. Two people wishing to have children together can find out if they are carriers for the same disorder. If so, they may elect not to have children. Thousands of people have been tested, and the program is partly responsible for the near-disappearance of Tay-Sachs disease among Ashkenazi Jews. The very few cases each year are usually in non-Jews, because they have not been tested.
A population that practices consanguinity has very nonrandom mating. Recall from chapter 4 that in a consanguineous relationship, “blood” relatives have children together. On the family level, this practice increases the likelihood that harmful recessive alleles from shared ancestors will be combined and passed to offspring, causing disease. The birth defect rate in offspring is 2.5 times the normal rate of about 3 percent. On a population level, consanguinity decreases genetic diversity. The proportion of homozygotes rises as the proportion of heterozygotes falls.
Some populations encourage marriage between cousins, which increases the incidence of certain recessive disorders. In certain parts of the middle east, Africa, and India, 20 to 50 percent of marriages are between cousins, or uncles and nieces. The tools of molecular genetics can reveal these relationships. Researchers traced DNA sequences on the Y chromosome and in mitochondria among residents of an ancient, geographically isolated “micropopulation” on the island of Sardinia, near Italy. They consulted archival records dating from the village’s founding by 200 settlers around 1000 A.D. to determine familial relationships. Between 1640 and 1870, the population doubled, reaching 1,200 by 1990. Fifty percent of the present population descends from just two paternal and four maternal lines, and 86 percent of the people have the same X chromosome. Researchers are analyzing disorders that are especially prevalent in this population, which include hypertension and a kidney disorder.
Worldwide, about 960 million married couples are related, and know of their relationship. Also contributing to nonrandom mating is endogamy, which is marriage within a community. In an endogamous society, spouses may be distantly related and be unaware of the connection.
Key Concepts Questions 15.1
Why is human mating usually not random?
What would make a trait be in Hardy-Weinberg equilibrium?
What are the effects of consanguinity and endogamy on population genetic structure?
Large cities, with their pockets of ethnicity, defy Hardy-Weinberg equilibrium by their very existence. Waves of immigrants formed the population of New York City, for example. The original Dutch settlers of the 1600s had different alleles than those in today’s metropolis of English, Irish, Slavics, Africans, Hispanics, Italians, Asians, and many others. Figure 15.3 depicts the effect on allele and genotype frequencies when individuals join a migrating population. Clues to past migrations lie in historical documents as well as in differing allele frequencies in regions defined by geographical or language barriers.
The frequency of the allele that causes galactokinase deficiency (OMIM 230200) in several European populations reveals how people with this autosomal recessive disorder migrated (figure 15.4). Galactokinase deficiency causes cataracts (clouding of the lens) in infants. It is very common among a population of 800,000 gypsies, called the Vlax Roma, who live in Bulgaria. It affects 1 in 1,600 to 2,500 people among them, and 5 percent of the people are carriers. But among all gypsies in Bulgaria as a whole, the incidence drops to 1 in 52,000. As the map in figure 15.4 shows, the disease becomes rarer to the west. This pattern may have arisen when people with the allele settled in Bulgaria, with only a few individuals or families moving westward.
Figure 15.3 Migration alters allele frequencies. If the population travels and picks up new individuals, allele frequencies can change.
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