INTRODUCTION
Genetic Drift is a form of evolution that does not usually result in adaptation; it is usually said to be the evolution of neutrally adaptive traits. In other way, different alleles may increase or decrease with respect to each other but the change does not represent adaptation. Genetic Drift also a second mechanism for evolution proposed by largely by Sewall Wright in the 1930s. The mechanism of genetic drift is chance associated with recombination in small populations. When a small group separates from a larger population, or reproduces only among themselves, allele frequencies may change as a result of chance sampling from the whole. This change in allele frequency that occurs when a small group separates from the larger whole is termed genetic drift. It is like reaching into a bag of jellybeans and, by chance, grabbing only green and yellow ones. The allele frequency changes in genetic drift are random and unpredictable.
WHEN GENETIC DRIFT OCCURS:
Genetic drift occurs when the population size plummets, due either to migration, to a natural disaster or geographic barrier that isolates small pockets of people, or to the consequences of human behavior. Members of a small community might reproduce only among themselves, which keeps genetic variants within their ethnic groupGenetic drift is also seen within large cities. Pittsburgh, Pennsylvania and New York City are more mosaics of groups with distinct ethnic flavors than “melting pots” of mixed heritage. Some groups of people become isolated in several ways—geographically, linguistically, and by choice of partners. Such populations often have a high incidence of several otherwise rare inherited conditions. The native residents of the Basque country in the western part of the Pyrenees Mountains between France and Spain, for example, still speak remnants of Euskera, a language the first European settlers brought in more than 10,000 years ago. The Basques have unusual frequencies of certain ABO and Rh blood types, rare mtDNA sequences and cell surface antigen patterns, and a high incidence of a mild form of muscular dystrophy.
FACTORS FOR GENETIC DRIFT:
The following factors must function for genetic drift to work
- a. The alleles involved must not hold significant selective advantages over each other.
- b. The population involved must be quite small and sexually reproducing.
- c. There can be no significant immigration or emigration of one allele as compared to others.
For many populations and alleles, these factors hold true. For example, many alternative alleles of genes produce proteins that are essentially equivalent in function the differences in their amino acid structure result in no noticeable difference in function in the environment the organism is found in. In the recombination process, there are two events that can easily affect the frequency of alleles in small populations such as reductive division of meiosis and syngamy. As populations get smaller and smaller it becomes increasingly likely that alleles might change in their abundance in the offspring as compared to the parents. Genetic drift works the same way one allele or the other increases simply at chance in small populations.
CHARACTERISTICS OF GENETIC DRIFT
Phenomena Which Share Some Characteristics with Genetic Drift such as founder effect and migration are important in evolution.
FOUNDER EFFECT:
Founder effect is a related phenomenon of Ernst Mayr. Here the idea is that new populations that are founded by relatively few individuals will be biased by the small founding genotype. Differences between them and other populations may have little to do with adaptation and instead simply be the result of chance. The founder effect is an excellent example of the potential role that history can have in evolutionary change.
Biased Migrations where one genotype preferentially leaves a population might also in some cases by a factor. A common type of genetic drift in human populations is the founder effect,which occurs when small groups leave home to found new settlements. The new colony may have different allele frequencies than the original population. Founder populations can amplify certain alleles. This shows up in increased disease frequencies. Consider an isolated community of about 10,000 members of the Church of Jesus Christ of Latter Day Saints, who live on a plateau on the Utah-Arizona border. Half of all known cases of fumarate deficiency (MIM 606812), which causes mental retardation, seizures, and coma, occur in this area. Nearly 80 percent of the population descends from two original settlers.
Widespread cousin-cousin marriages as well as polygamy (men with multiple wives) and social isolation have joined the powerful founder effect to keep the disease in the population. In 2008, the U.S. government removed many children from this community on suspicion of abuse. Some of the children returned a year later— but some chose to remain in the outside world.
A powerful founder effect appears in the French Canadian population of Quebec. Their lack of diversity in disease causing mutations reflects a long history of isolation. Consider breast cancer caused by the BRCA1gene. More than 500 alleles are known worldwide, yet only four are seen among French Canadians. Several inborn errors of metabolism are also more common in this group. The French Canadians have ideal characteristics for gene discovery: many generations since founding, few founders (about 2,500), a high rate of population expansion percent increase per generation), a large present day population (about 6 million), and most marriages within the group.
The French Canadian population exemplifies genetic drift because the people have kept mostly to themselves within a larger population. The French founded Quebec City in 1608. Until 1660, the population grew as immigrants arrived from France, and then began to increase from births. More than 10,000 French had arrived by the time the British took over in 1759,but many of them had headed westward. In Quebec, religious, language, and other cultural differences separated the French and English gene pools. The French Canadian population of Quebec grew from the 2,500 or so founding genotypes to about 6 million individuals today. The cultural and physical isolation in Canada created an unusual situation—a founder effect within a founder effect. In the nineteenth century, when agricultural lands opened up about 150 miles north of Quebec, some families migrated north. Their descendants, who remained in the remote area, form an incredibly genetically homogeneous subpopulation of founders split off from the original set of founders.
Founder effects can be studied at the phenotypic and genotypic levels. Phenotypically, a founder effect is indicated when a community of people, known from local history to have descended from a few founders, have inherited traits and illnesses that are rare elsewhere. This is striking among the Old Order Amish and Mennonites of Lancaster County, Pennsylvania. Often, worried parents would bring their ill children to medical facilities in Philadelphia. Over the years, researchers realized that these
people are subject to an array of extremely rare conditions. For example, Victor McKusick, founder of Online Mendelian Inheritance in Man, discovered and described cartilage-hair hypoplasia after six Amish children died at a Philadelphia hospital from chickenpox in 1965. Part of their inherited syndrome was impaired immunity. Until McKusick made the connection, the other symptoms— including dwarfism, sparse hair, and anemia—were not recognized as part of a syndrome. Today, as
many geneticists study inherited diseases common among the Amish and Mennonites, treatments are becoming available, from special diets to counter inborn errors of metabolism to gene therapy. In addition to historical records, differences in allele frequencies in a smaller population compared to those in the general population suggest a founder effect. The incidence of certain diseases in Lancaster County, for example, is astounding. Maple syrup urine disease affects 1 in 225,000 newborns in the United States, but 1 in 400 newborns among the Lancaster families! A research fellow at Children’s Hospital in Philadelphia discovered that cerebral palsy in several young children from Lancaster County attributed to oxygen deprivation at birth was actually an inborn error of metabolism called glutaric aciduria type I. He went from farm to farm, tracking cases against genealogical records, and found that every family that could trace its roots back to the founders had members who had the disease! Today, 1 in 200 newborns in this population have the condition. A mutation that is the same in all affected individuals in a population is strong evidence of a founder effect due to descent from shared ancestors. The Bulgarian gypsies who have galactokinase deficiency, for example, all have a mutation that is extremely rare elsewhere. In contrast, a population with several mutations that cause the same disorder is more likely to have picked up those variants from people joining the group, rather than from descent from shared founders. Very often when a disease-associated allele is identical in DNA sequence among people in the same population, so is the DNA surrounding the gene. This pattern indicates that a portion of a chromosome, rather than just the disease-causing gene, has been passed among the members of the population from its founders. For this reason, many studies that trace founder effects examine haplotypes that include tightly linked genes. When historical or genealogical records are particularly well kept or recent, founder effects can sometimes be traced to the very beginning. This is the case for the Afrikaner population of South Africa. The 2.5 million Afrikaners descended from a small group of Dutch, French, and German immigrants who had huge families, often with as many as ten children. In the nineteenth century, some Afrikaners migrated northeast to the Transvaal Province, where they lived in isolation until the Boer War in 1902 introduced better transportation.
Today, 30,000 Afrikaners have porphyria variegata. All affected people descended from one couple who came from the Netherlands in 1688! Today’s allele frequency in South Africa is far higher than that in the Netherlands because the founding couple had many children—who, in turn, had large families, passing on and amplifying the dominant mutation. Founder effects are also evident in more common illnesses, where populations have different mutations in the same gene. BRCA1breast cancer, for example, is most prevalent among Ashkenazi Jewish people. Nearly all affected individuals have the same 3-base deletion. In contrast, BRCA1breast cancer is rare in blacks, but it affects families from the Ivory Coast in Africa, the Bahamas, and the southeastern United States. They share a 10-base deletion, probably inherited from West Africans ancestral to all three modern groups. Slaves brought the disease to the United States and the Bahamas between 1619 and 1808, but some of their relatives who stayed in Africa have perpetuated the mutant allele there.
POPULATION BOTTLENECKS
A population bottleneck occurs when many members of a group die, and only a few are left to replenish the numbers. The new population has only those alleles in the small group that survived the catastrophe. An allele in the remnant population might become more common in the replenished population than it was in the original larger group. Therefore, the new population has a much more restricted gene pool than the larger ancestral population, with some variants amplified, others diminished. Population bottlenecks can occur when people (or other animals) colonize islands. An extreme example is seen among the Pingelapese people of the eastern Caroline Islands in Micronesia.
Four to 10 percent are born with “Pingelapese blindness,” an autosomal recessive combination of colorblindness, nearsightedness, and cataracts also called achromatopsia (MIM 603096). Elsewhere, only 1 in 20,000 to 50,000 people inherits the condition. Nearly 30 percent of the Pingelapese are carriers. The prevalence of the blindness among the Pingelapese stems from a typhoon in 1780 that killed all but nine males and ten females who founded the present population. This severe population bottleneck, plus geographic and cultural isolation, increased the frequency of the blindness gene as the population resurged. A more widespread population bottleneck occurred as a consequence of the early human expansion from Africa, discussed in chapter 16. As numbers dwindled during the journeys and then were replenished as people settled down, mating among relatives led, over time, to an increase in homozygous recessive genotypes compared to ancestral populations that maintained their genetic diversity in Africa. These bottlenecks are reflected today in the persistence of genetic diversity among African populations. The lack of genetic diversity in some modern human populations is evident as “runs of homozygosity,” which are chromosome regions that vary little from person to person. Runs of homozygosity generally represent regions that are inherited from shared ancestors. They are common, for example, in highly purebred dogs.
Today’s cheetahs live in just two isolated populations of a few thousand animals in South and East Africa. Their numbers once exceeded 10,000. The South African cheetahs are so alike genetically that even unrelated animals can accept skin grafts from each other. Researchers attribute the cheetahs’ genetic uniformity to two bottlenecks—one that occurred at the end of the most recent ice age, when habitats changed, and another following mass slaughter by humans in the nineteenth century. However, the good health of the animals today indicates that the genes that have survived enable the cheetahs to thrive in their environment
CONSEQUENCES OF GENETIC DRIFT:
Genetic drift has several important effects on evolution. The forces of nonrandom mating, migration, genetic drift, mutation, and natural selection interact in complex ways. Drift reduces genetic variation in populations, potentially reducing a population’ s ability to evolve in response to new selective pressures. Genetic drift acts faster and has more drastic results in smaller populations. This effect is particularly important in rare and endangered species. Genetic drift can contribute to speciation. For example, a small isolated population may diverge from the larger population through genetic drift.
Loss of heterozygosity
LOH is caused by a variety of genetic mechanisms, including physical deletion of chromosome nondisjunction, mitotic nondisjunction followed by republication of the remaining chromosomes, mitotic recombination, and gene conversion. The mechanisms of LOH are remarkably chromosome specific. Some chromosomes display complete loss. However, more than half of the losses are associated with the loss of only a part of the chromosome rather than the whole chromosome. LOH is also a common form of allelic imbalance and the detection of LOH has been used to identify genomic regions that harbor tumor suppressor genes and to characterize different tumor types, pathological stages, and progression.
Loss of heterozygosity (LOH) is the loss of function of one allele of a gene in which the other allele was already inactivated. The LOH algorithm, as implemented by Partek® Genomics Suite™ (Partek GS), looks across many continuous markers (provided by array vendors) to detect regions heterozygous in ‘normal’ samples (e.g. 1×A, 1×B allele) that are homozygous (e.g. AA or BB) in
cancer (or study) samples. The workflow can be successfully applied for the three main applications:
- a. detection of copy-neutral LOH;
- b.confirmation of allele deletions detected by the copy number analysis;
- c.detection of homozygosity in germline environment.
The detection of copy-neutral LOH and the confirmation of allele deletions require integration with the copy number workflow and the discussion proceeds below. Detection of homozygosity in germline environment (also know as homozygosity mapping or uniparental disomy (UPD) mapping) may be used in conjunction with duo or trio workflows to detect identity by descent (IBD). An advantage of the LOH analysis is that it provides a solution to a problem associated with the copy number approach: the inability to detect genotypic changes which are copy neutral. The LOH may be caused by a hemizygous deletion in which the normal allele is lost and the mutated allele remains present (Figure 3, middle panel). That type of LOH can be recognized not only by SNP-genotyping, but by copy-number analysis as well.
However, an allele can get lost initially, but the subsequent amplification of the remaining copy creates a copy-neutral LOH (Figure 1, right panel), first described as UPD. Different mechanisms have been described to create copy-neutral LOH in myosis and mitosis, and the common feature is that copyneutral LOH can only be detected when copy number is studied in combination with SNP genotype. Please note that, irrespectively of the preservation of total number of copies, the biological effect is still important as the recessive mutations are no longer masked by their dominant normal counterparts.
The integration of copy number workflow with LOH workflow relies on the supplementation of the copy number data with the SNP genotyping data (currently available by Affymetrix and Illumina) to label the genomic regions in the following fashion:
amplification without LOH, amplification with LOH, deletion without LOH, deletion with LOH, and copy-neutral LOH (Figure 4). The last category, copy-neutral LOH is the added value of the workflow integration. Please note that the same five categories can be obtained by the allele-specific copy number (AsCN) workflow as well
Unfortunately, LOH has the limitations on its own: the correct interpretation of currently available algorithms for LOH has been proven complex and difficult, because cancer cells frequently deviate from diploid state and tumor specimens often contain significant proportion of normal cells. For instance, it has been shown that as the proportion of tumor cells in a sample decreases and approaches 50% or less, the capacity to detect the LOH diminishes (Yamamoto G et al. Am J Hum Gen 2007).
Moreover, genotyping algorithms fail to call a heterozygote SNP accordingly in a situation when only one of two alleles gets amplified (e.g. 3×A and 1×B): a false positive LOH result can be the consequence. AsCN analysis, on the other hand, is a method that enables a reliable detection of allele imbalance in tumor samples even in the presence of large proportions of tumor cells. Unlike LOH, it does not require a large set of normal reference samples. For a heterozygous SNP (only those are informative), a balance is expected between the two alleles (1×A and 1×B, or 1:1 ratio). AsCN algorithm provides an estimated number of copies of each allele and therefore enables the detection of allelic imbalance even in cases when alleles are mplified or deleted (e.g. 3×A and 1×B). Moreover, LOH can be considered a special case of allelic imbalance (e.g. 1×A, B allele deleted) .
Therefore, due to its better robustness, the AsCN can be suggested as a preferred application in tumor focused applications. To learn more about AsCN, please refer to the AsCN tutorial (Help > On-line Tutorials).
Variance among populations increases – Due to genetic drift variance among population increases and Proportion of shared alleles between populations decreases.Genetic drift and natural selection are the two most important causes of allele substitution that is, of evolutionary change in populations. Genetic drift occurs in all natural populations because, unlike ideal populations at Hardy-Weinberg equilibrium, natural populations are finite in size. Random fluctuations in allele frequencies can result in the replacement of old alleles by new ones, resulting in nonadaptive evolution. That is, while natural selection results in adaptation, genetic drift does not-so this process is not responsible for those anatomical, physiological, and behavioral features of organisms that equip them for reproduction and survival. Genetic drift nevertheless has many important consequences, especially at the molecular genetic level: it appears to account for much of the difference in DNA sequences among species. Because all populations are finite, alleles at all loci are potentially subject to random genetic drift but all are not necessarily subject to natural selection. For this reason, and because the expected effects of genetic drift can be mathematically described with some precision, some evolutionary geneticists hold the opinion that genetic drift should be the “null hypothesis” used to explain an evolutionary observation unless there is positive evidence of natural selection or some other factor. This perspective is analogous to the “null hypothesis” in statistics: the hypothesis that the data do not depart from those expected on the basis of chance alone.” According to this view, we should not assume that a characteristic, or a difference between populations or species, is adaptive or has evolved by natural selection unless there is evidence for this conclusion.
The theory of genetic drift, much of which was developed by the American geneticist Sewall Wright starting in the 1930s, and by the Japanese geneticist Motoo Kimura starting in the 1950s, includes some of the most highly refined mathematical models in biology.