# Population Genetics Question

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Can someone please help with this question? Here is my working (just in case it is not clear: 1/300*1/30*1/2) but is this actually correct or do I need to multiply by 0.5 once again? I appreciate any help!

Question is: If an Ashkenazi(1/30) and(multiply) French-Canadian(1/30)… Where 1/300 came from ?

I duno, I may missing something - but may it be like that

``Parrent1(=1/30 * 1/2)*Parrent2(=1/30 * 1/2) = P(child with both mutations)``

## Population Genetics

Individuals of a population often display different phenotypes, or express different alleles of a particular gene, referred to as polymorphisms. Populations with two or more variations of particular characteristics are called polymorphic. The distribution of phenotypes among individuals, known as the population variation , is influenced by a number of factors, including the population’s genetic structure and the environment ([link]). Understanding the sources of a phenotypic variation in a population is important for determining how a population will evolve in response to different evolutionary pressures.

## Population Genetics Question - Biology

Another way to answer this question involves looking at the population genetics of Monarchs. Population genetics, which combines theories from evolution and genetics, studies how genes are distributed in a population. By using the tools of population genetics, biologists can evaluate the distribution of genes in Monarch populations to get a better idea of how groups of Monarchs move around and mate. Some distributions would indicate that Monarchs stick together in groups and tend to mate within their own group, while other distributions would show that Monarch populations mix either in the summer, in the winter, or during both times.

Two experiments have investigated the population genetics of Monarch butterflies, and they found some interesting and surprising results. To help you better understand the ideas behind those studies, we encourage you to go review Theories in Evolution and Population Genetics before reading the summaries of these studies.

Genetic Structure of Summer and Migratory Monarchs

Eanes, W.F. and R.K. Koehn. 1978. An analysis of genetic structure in the Monarch butterfly, Danaus plexippus L. Evolution 32(4): 784-797.

Eanes and Koehn studied the genetics of different Monarch populations in the early 1970s. They collected 20 different sets of samples, both during the summer and during migration. Using electrophoresis to examine the same protein in different individuals, they found that Monarchs have allele frequencies that sort out into groups somewhat in the summer and become uniform again during migration. These results indicate that Monarchs divide into slightly isolated populations during the summer but mix together during migration (and, they assume, in the winter roosts although the roosts had not yet been discovered when they did this research). Migratory populations and roosts, therefore, include individuals from all over North America all the Monarchs from a particular summer region do not necessarily overwinter in the same place, and their descendants may not return to the same region the next year. The mixing that happens during spring mating in the roosts overwhelms any genetic differentiation that occurs during summer in isolated populations.

Eanes and Koehn found another interesting pattern in allele frequencies. For three of the eleven proteins they studied, there were more heterozygotes than expected. In at least once case, males and females also differed in which allele they were likely to have (that is, males more often had one version of the protein while females more often had the other version). When alleles have different average frequencies in males and females, mating will more often produce heterozygotes. For Monarchs, there are still many unanswered questions about whether mating behavior results in different allele frequencies between sexes and what causes increased heterozygosity in the population.

DNA Variation in Monarch Butterflies

Brower, A.V.Z. and T.M. Boyce. 1991. Mitochondrial DNA variation in Monarch butterflies. Evolution 45(5): 1281-1286.

Brower and Boyce studied the mitochondrial DNA (mtDNA) of Monarch butterflies from the United States, Mexico, and the West Indies to see how similar or different their genetic material was. They were especially curious about whether the eastern and western populations of Monarchs in North America were genetically different the eastern population overwinters in Mexico while the western one overwinters in California, and there is no evidence that these two populations ever interbreed. They looked at variation in mtDNA using restriction enzymes, a technique that identifies differences in DNA sequences. If one population, or individual, had a small change in its DNA, this technique can reveal that change. In some other insect species, studies have found that there are big differences in individuals' mtDNA between regional populations, and sometimes even within a region.

To their surprise, Brower and Boyce found almost no variation in any of the Monarch populations' mtDNA, including the ones from the West Indies. Using 13 restriction enzymes, they found only two individuals with a single difference in one site, and they attribute this difference to a single base substitution. This level of similarity in the DNA from geographically isolated populations is dramatically different from most other studied groups of animals. Vertebrates, for example, have differences at 10 times this level while other insects show differences in mtDNA even within a population.

The most plausible explanation Brower and Boyce have is that all of these Monarchs underwent a bottleneck in recent evolutionary time. Bottlenecks reduce the genetic diversity in a population (for another example, read about cheetahs) because only a small number of individuals and their DNA serve as the ancestors for the present populations. Since mtDNA is maternally inherited, it seems likely that sometime in the recent past there was a significant reduction in the number of females who reproduced. Since that bottleneck, enough time has not passed for major changes to have occurred.

##  Question 9

0 out of 1 points Which of the following is true of neutral alleles? Selected Answer:

They do not affect the expression of phenotypes Answers: A. They will eventually either go to fixation (100%) or go to extinction (0%) B. If they increase in frequency one generation, they are more likely to decrease in frequency in the next generation C. They can be subject to stabilizing, directional, or disruptive selection D. They do not affect the expression of phenotypes E. They do not get inherited

## Population Size and Evolution

When allele frequencies within a population change randomly with no advantage to the population over existing allele frequencies, the phenomenon is called genetic drift. The smaller a population, the more susceptible it is to mechanisms such as genetic drift as alleles are more likely to become fixed at 0 (absent) or 1 (universally present). Random events that alter allele frequencies will have a much larger effect when the gene pool is small. Genetic drift and natural selection usually occur simultaneously in populations, but the cause of the frequency change is often impossible to determine.

Natural selection also affects allele frequency. If an allele confers a phenotype that enables an individual to better survive or have more offspring, the frequency of that allele will increase. Because many of those offspring will also carry the beneficial allele and, therefore, the phenotype, they will have more offspring of their own that also carry the allele. Over time, the allele will spread throughout the population and may become fixed: every individual in the population carries the allele. If an allele is dominant but detrimental, it may be swiftly eliminated from the gene pool when the individual with the allele does not reproduce. However, a detrimental recessive allele can linger for generations in a population, hidden by the dominant allele in heterozygotes. In such cases, the only individuals to be eliminated from the population are those unlucky enough to inherit two copies of such an allele.

## Population Genetics

Population genetics is a sub-discipline of genetics that deals with genetic differences within and between populations. This field examines phenomena such as adaptation, speciation, and population structure. A major goal of this course is to make students familiar with basic models of population genetics and to acquaint students with empirical tests of these models. As much as any field of biology, population genetics has been divided into a theoretical and an empirical branch. However, these two bodies of knowledge are intimately related and this course will cover both in roughly equal amounts. We will discuss the primary forces and processes involved in shaping genetic variation in natural populations (mutation, drift, selection, migration, recombination, mating patterns, population size and population subdivision), methods of measuring genetic variation in nature, and experimental tests of important ideas in population genetics.

Perspective

Population genetics is a field of biology that studies the genetic composition of biological populations and the changes in genetic composition that result from the operation of various factors, including natural selection. Population geneticists pursue their goals by developing abstract mathematical models of gene frequency dynamics, trying to extract conclusions from those models about the likely patterns of genetic variation in actual populations, and testing the conclusions against empirical data.

Population genetics is intimately bound up with the study of evolution and natural selection, and is often regarded as the theoretical cornerstone of modern Darwinism. This is because natural selection is one of the most important factors that can affect a population’s genetic composition. Natural selection occurs when some variants in a population out-reproduce other variants as a result of being better adapted to the environment, or ‘fitter’. Presuming the fitness differences are at least partly due to genetic differences, this will cause the population’s genetic makeup to be altered over time. By studying formal models of gene frequency change, population geneticists therefore hope to shed light on the evolutionary process, and to permit the consequences of different evolutionary hypotheses to be explored in a quantitatively precise way.

The original, modern synthesis view of population genetics assumes that mutations provide ample raw material, and focuses only on the change in frequency of alleles within populations. The main processes influencing allele frequencies are natural selection, genetic drift, gene flow and recurrent mutation. Fisher and Wright had some fundamental disagreements about the relative roles of selection and drift. The availability of molecular data on all genetic differences led to the neutral theory of molecular evolution. In this view, many mutations are deleterious and so never observed, and most of the remainder are neutral, i.e. are not under selection. With the fate of each neutral mutation left to chance (genetic drift), the direction of evolutionary change is driven by which mutations occur, and so cannot be captured by models of change in the frequency of (existing) alleles alone. The origin-fixation view of population genetics generalizes this approach beyond strictly neutral mutations, and sees the rate at which a particular change happens as the product of the mutation rate and the fixation probability.

The field of population genetics came into being in the 1920s and 1930s, thanks to the work of R.A. Fisher, J.B.S. Haldane and Sewall Wright. Their achievement was to integrate the principles of Mendelian genetics, which had been rediscovered at the turn of century, with Darwinian natural selection. Though the compatibility of Darwinism with Mendelian genetics is today taken for granted, in the early years of the twentieth century it was not. Many of the early Mendelians did not accept Darwin’s ‘gradualist’ account of evolution, believing instead that novel adaptations must arise in a single mutational step conversely, many of the early Darwinians did not believe in Mendelian inheritance, often because of the erroneous belief that it was incompatible with the process of evolutionary modification as described by Darwin. By working out mathematically the consequences of selection acting on a population obeying the Mendelian rules of inheritance, Fisher, Haldane and Wright showed that Darwinism and Mendelism were not just compatible but excellent bed fellows this played a key part in the formation of the ‘neo-Darwinian synthesis’, and explains why population genetics came to occupy so pivotal a role in evolutionary theory.

Distant learning 2020

Discussion Sessions

“E-lectures for distant learning”

Transposable elements (TEs) have contributed substantially to the evolution of genomes’ structure. The following papers shed light on the role of TEs in causing genomic incompatibilities and speciation: Role of TEs in Speciation, Population Genomics of TEs, and TEs Drive Rapid Phenotypic Variation.

Reinforcement is a process by which natural selection increases the reproductive isolation between populations and acts as an initiator of speciation. The following papers are relevant to the topics of reinforcement and hybrid zones: Genomic Signatures of Reinforcement, Hybridization in Theory and Practice, and Reinforcement as an Initiator Speciation.

## Population Genetics Simulation

The population genetics simulation was the first one made for the site and is one of the most open-ended. Teachers can make a guided lab to test a variety of situations (like the "Heterozygote Advantage" lab, available on the resources page or on Google Drive), or it can be an opportunity for student inquiry (see the "Population Genetics" worksheet). Simulations can be a great option for letting students practice developing questions and designing experiments, so it was important to me that at least some of the simulations on Biology Simulations have an open structure.

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The simulation examines the frequencies of two alleles for one gene that codes for color in a fictional population. There are red (R) and blue (B) alleles, with red (RR), purple (RB), and blue (BB) phenotypes. Before jumping into any virtual labs using this simulation students should be familiar with heredity terms like gene, allele, genotype, and phenotype. Students should also understand frequencies. I do my evolution unit with the 9th grade before the heredity unit, so I review heredity terms which students worked with in middle school before starting any of the evolution simulations. There is an introduction worksheet available that I use to review terms and review/introduce frequencies. Students do not need to be familiar with Hardy-Weinberg formulas to use this simulation. However, teachers could incorporate H-W calculations and/or hypothesis testing for advanced classes.

In the simulation students can manipulate the starting frequency of the red allele, the number of generations, the population size, the survival chance of each phenotype, and mutation between the two alleles. The simulation can test genetic equilibrium, genetic drift, natural selection, and mutation (between existing alleles, not producing new alleles).

## Contents

Population genetics began as a reconciliation of Mendelian inheritance and biostatistics models. Natural selection will only cause evolution if there is enough genetic variation in a population. Before the discovery of Mendelian genetics, one common hypothesis was blending inheritance. But with blending inheritance, genetic variance would be rapidly lost, making evolution by natural or sexual selection implausible. The Hardy–Weinberg principle provides the solution to how variation is maintained in a population with Mendelian inheritance. According to this principle, the frequencies of alleles (variations in a gene) will remain constant in the absence of selection, mutation, migration and genetic drift. [3]

The next key step was the work of the British biologist and statistician Ronald Fisher. In a series of papers starting in 1918 and culminating in his 1930 book The Genetical Theory of Natural Selection, Fisher showed that the continuous variation measured by the biometricians could be produced by the combined action of many discrete genes, and that natural selection could change allele frequencies in a population, resulting in evolution. In a series of papers beginning in 1924, another British geneticist, J. B. S. Haldane, worked out the mathematics of allele frequency change at a single gene locus under a broad range of conditions. Haldane also applied statistical analysis to real-world examples of natural selection, such as peppered moth evolution and industrial melanism, and showed that selection coefficients could be larger than Fisher assumed, leading to more rapid adaptive evolution as a camouflage strategy following increased pollution. [4] [5]

The American biologist Sewall Wright, who had a background in animal breeding experiments, focused on combinations of interacting genes, and the effects of inbreeding on small, relatively isolated populations that exhibited genetic drift. In 1932 Wright introduced the concept of an adaptive landscape and argued that genetic drift and inbreeding could drive a small, isolated sub-population away from an adaptive peak, allowing natural selection to drive it towards different adaptive peaks. [ citation needed ]

The work of Fisher, Haldane and Wright founded the discipline of population genetics. This integrated natural selection with Mendelian genetics, which was the critical first step in developing a unified theory of how evolution worked. [4] [5] John Maynard Smith was Haldane's pupil, whilst W. D. Hamilton was influenced by the writings of Fisher. The American George R. Price worked with both Hamilton and Maynard Smith. American Richard Lewontin and Japanese Motoo Kimura were influenced by Wright and Haldane. [ citation needed ]

Gertrude Hauser and Heidi Danker–Hopfe have suggested that Hubert Walter also contributed to the creation of the subdiscipline population genetics. [6]

### Modern synthesis Edit

The mathematics of population genetics were originally developed as the beginning of the modern synthesis. Authors such as Beatty [7] have asserted that population genetics defines the core of the modern synthesis. For the first few decades of the 20th century, most field naturalists continued to believe that Lamarckism and orthogenesis provided the best explanation for the complexity they observed in the living world. [8] During the modern synthesis, these ideas were purged, and only evolutionary causes that could be expressed in the mathematical framework of population genetics were retained. [9] Consensus was reached as to which evolutionary factors might influence evolution, but not as to the relative importance of the various factors. [9]

Theodosius Dobzhansky, a postdoctoral worker in T. H. Morgan's lab, had been influenced by the work on genetic diversity by Russian geneticists such as Sergei Chetverikov. He helped to bridge the divide between the foundations of microevolution developed by the population geneticists and the patterns of macroevolution observed by field biologists, with his 1937 book Genetics and the Origin of Species. Dobzhansky examined the genetic diversity of wild populations and showed that, contrary to the assumptions of the population geneticists, these populations had large amounts of genetic diversity, with marked differences between sub-populations. The book also took the highly mathematical work of the population geneticists and put it into a more accessible form. Many more biologists were influenced by population genetics via Dobzhansky than were able to read the highly mathematical works in the original. [10]

In Great Britain E. B. Ford, the pioneer of ecological genetics, [11] continued throughout the 1930s and 1940s to empirically demonstrate the power of selection due to ecological factors including the ability to maintain genetic diversity through genetic polymorphisms such as human blood types. Ford's work, in collaboration with Fisher, contributed to a shift in emphasis during the modern synthesis towards natural selection as the dominant force. [4] [5] [12] [13]

### Neutral theory and origin-fixation dynamics Edit

The original, modern synthesis view of population genetics assumes that mutations provide ample raw material, and focuses only on the change in frequency of alleles within populations. [14] The main processes influencing allele frequencies are natural selection, genetic drift, gene flow and recurrent mutation. Fisher and Wright had some fundamental disagreements about the relative roles of selection and drift. [15] The availability of molecular data on all genetic differences led to the neutral theory of molecular evolution. In this view, many mutations are deleterious and so never observed, and most of the remainder are neutral, i.e. are not under selection. With the fate of each neutral mutation left to chance (genetic drift), the direction of evolutionary change is driven by which mutations occur, and so cannot be captured by models of change in the frequency of (existing) alleles alone. [14] [16]

The origin-fixation view of population genetics generalizes this approach beyond strictly neutral mutations, and sees the rate at which a particular change happens as the product of the mutation rate and the fixation probability. [14]

### Selection Edit

Natural selection, which includes sexual selection, is the fact that some traits make it more likely for an organism to survive and reproduce. Population genetics describes natural selection by defining fitness as a propensity or probability of survival and reproduction in a particular environment. The fitness is normally given by the symbol w=1-s where s is the selection coefficient. Natural selection acts on phenotypes, so population genetic models assume relatively simple relationships to predict the phenotype and hence fitness from the allele at one or a small number of loci. In this way, natural selection converts differences in the fitness of individuals with different phenotypes into changes in allele frequency in a population over successive generations. [ citation needed ]

Before the advent of population genetics, many biologists doubted that small differences in fitness were sufficient to make a large difference to evolution. [10] Population geneticists addressed this concern in part by comparing selection to genetic drift. Selection can overcome genetic drift when s is greater than 1 divided by the effective population size. When this criterion is met, the probability that a new advantageous mutant becomes fixed is approximately equal to 2s. [17] [18] The time until fixation of such an allele depends little on genetic drift, and is approximately proportional to log(sN)/s. [19]

#### Dominance Edit

Dominance means that the phenotypic and/or fitness effect of one allele at a locus depends on which allele is present in the second copy for that locus. Consider three genotypes at one locus, with the following fitness values [20]

 Genotype: A1A1 A1A2 A2A2 Relative fitness: 1 1-hs 1-s

s is the selection coefficient and h is the dominance coefficient. The value of h yields the following information:

 h=0 A1 dominant, A2 recessive h=1 A2 dominant, A1 recessive 01 Underdominance

#### Epistasis Edit

Epistasis means that the phenotypic and/or fitness effect of an allele at one locus depends on which alleles are present at other loci. Selection does not act on a single locus, but on a phenotype that arises through development from a complete genotype. [21] However, many population genetics models of sexual species are "single locus" models, where the fitness of an individual is calculated as the product of the contributions from each of its loci—effectively assuming no epistasis.

In fact, the genotype to fitness landscape is more complex. Population genetics must either model this complexity in detail, or capture it by some simpler average rule. Empirically, beneficial mutations tend to have a smaller fitness benefit when added to a genetic background that already has high fitness: this is known as diminishing returns epistasis. [22] When deleterious mutations also have a smaller fitness effect on high fitness backgrounds, this is known as "synergistic epistasis". However, the effect of deleterious mutations tends on average to be very close to multiplicative, or can even show the opposite pattern, known as "antagonistic epistasis". [23]

Synergistic epistasis is central to some theories of the purging of mutation load [24] and to the evolution of sexual reproduction.

### Mutation Edit

Mutation is the ultimate source of genetic variation in the form of new alleles. In addition, mutation may influence the direction of evolution when there is mutation bias, i.e. different probabilities for different mutations to occur. For example, recurrent mutation that tends to be in the opposite direction to selection can lead to mutation–selection balance. At the molecular level, if mutation from G to A happens more often than mutation from A to G, then genotypes with A will tend to evolve. [25] Different insertion vs. deletion mutation biases in different taxa can lead to the evolution of different genome sizes. [26] [27] Developmental or mutational biases have also been observed in morphological evolution. [28] [29] For example, according to the phenotype-first theory of evolution, mutations can eventually cause the genetic assimilation of traits that were previously induced by the environment. [30] [31]

Mutation bias effects are superimposed on other processes. If selection would favor either one out of two mutations, but there is no extra advantage to having both, then the mutation that occurs the most frequently is the one that is most likely to become fixed in a population. [32] [33]

Mutation can have no effect, alter the product of a gene, or prevent the gene from functioning. Studies in the fly Drosophila melanogaster suggest that if a mutation changes a protein produced by a gene, this will probably be harmful, with about 70 percent of these mutations having damaging effects, and the remainder being either neutral or weakly beneficial. [34] Most loss of function mutations are selected against. But when selection is weak, mutation bias towards loss of function can affect evolution. [35] For example, pigments are no longer useful when animals live in the darkness of caves, and tend to be lost. [36] This kind of loss of function can occur because of mutation bias, and/or because the function had a cost, and once the benefit of the function disappeared, natural selection leads to the loss. Loss of sporulation ability in a bacterium during laboratory evolution appears to have been caused by mutation bias, rather than natural selection against the cost of maintaining sporulation ability. [37] When there is no selection for loss of function, the speed at which loss evolves depends more on the mutation rate than it does on the effective population size, [38] indicating that it is driven more by mutation bias than by genetic drift.

Mutations can involve large sections of DNA becoming duplicated, usually through genetic recombination. [39] This leads to copy-number variation within a population. Duplications are a major source of raw material for evolving new genes. [40] Other types of mutation occasionally create new genes from previously noncoding DNA. [41] [42]

### Genetic drift Edit

Genetic drift is a change in allele frequencies caused by random sampling. [43] That is, the alleles in the offspring are a random sample of those in the parents. [44] Genetic drift may cause gene variants to disappear completely, and thereby reduce genetic variability. In contrast to natural selection, which makes gene variants more common or less common depending on their reproductive success, [45] the changes due to genetic drift are not driven by environmental or adaptive pressures, and are equally likely to make an allele more common as less common.

The effect of genetic drift is larger for alleles present in few copies than when an allele is present in many copies. The population genetics of genetic drift are described using either branching processes or a diffusion equation describing changes in allele frequency. [46] These approaches are usually applied to the Wright-Fisher and Moran models of population genetics. Assuming genetic drift is the only evolutionary force acting on an allele, after t generations in many replicated populations, starting with allele frequencies of p and q, the variance in allele frequency across those populations is

Ronald Fisher held the view that genetic drift plays at the most a minor role in evolution, and this remained the dominant view for several decades. No population genetics perspective have ever given genetic drift a central role by itself, but some have made genetic drift important in combination with another non-selective force. The shifting balance theory of Sewall Wright held that the combination of population structure and genetic drift was important. Motoo Kimura's neutral theory of molecular evolution claims that most genetic differences within and between populations are caused by the combination of neutral mutations and genetic drift. [48]

The role of genetic drift by means of sampling error in evolution has been criticized by John H Gillespie [49] and Will Provine, [50] who argue that selection on linked sites is a more important stochastic force, doing the work traditionally ascribed to genetic drift by means of sampling error. The mathematical properties of genetic draft are different from those of genetic drift. [51] The direction of the random change in allele frequency is autocorrelated across generations. [43]

### Gene flow Edit

Because of physical barriers to migration, along with the limited tendency for individuals to move or spread (vagility), and tendency to remain or come back to natal place (philopatry), natural populations rarely all interbreed as may be assumed in theoretical random models (panmixy). [52] There is usually a geographic range within which individuals are more closely related to one another than those randomly selected from the general population. This is described as the extent to which a population is genetically structured. [53]

Genetic structuring can be caused by migration due to historical climate change, species range expansion or current availability of habitat. Gene flow is hindered by mountain ranges, oceans and deserts or even man-made structures such as the Great Wall of China, which has hindered the flow of plant genes. [54]

Gene flow is the exchange of genes between populations or species, breaking down the structure. Examples of gene flow within a species include the migration and then breeding of organisms, or the exchange of pollen. Gene transfer between species includes the formation of hybrid organisms and horizontal gene transfer. Population genetic models can be used to identify which populations show significant genetic isolation from one another, and to reconstruct their history. [55]

Subjecting a population to isolation leads to inbreeding depression. Migration into a population can introduce new genetic variants, [56] potentially contributing to evolutionary rescue. If a significant proportion of individuals or gametes migrate, it can also change allele frequencies, e.g. giving rise to migration load. [57]

In the presence of gene flow, other barriers to hybridization between two diverging populations of an outcrossing species are required for the populations to become new species.

#### Horizontal gene transfer Edit

Horizontal gene transfer is the transfer of genetic material from one organism to another organism that is not its offspring this is most common among prokaryotes. [58] In medicine, this contributes to the spread of antibiotic resistance, as when one bacteria acquires resistance genes it can rapidly transfer them to other species. [59] Horizontal transfer of genes from bacteria to eukaryotes such as the yeast Saccharomyces cerevisiae and the adzuki bean beetle Callosobruchus chinensis may also have occurred. [60] [61] An example of larger-scale transfers are the eukaryotic bdelloid rotifers, which appear to have received a range of genes from bacteria, fungi, and plants. [62] Viruses can also carry DNA between organisms, allowing transfer of genes even across biological domains. [63] Large-scale gene transfer has also occurred between the ancestors of eukaryotic cells and prokaryotes, during the acquisition of chloroplasts and mitochondria. [64]

If all genes are in linkage equilibrium, the effect of an allele at one locus can be averaged across the gene pool at other loci. In reality, one allele is frequently found in linkage disequilibrium with genes at other loci, especially with genes located nearby on the same chromosome. Recombination breaks up this linkage disequilibrium too slowly to avoid genetic hitchhiking, where an allele at one locus rises to high frequency because it is linked to an allele under selection at a nearby locus. Linkage also slows down the rate of adaptation, even in sexual populations. [65] [66] [67] The effect of linkage disequilibrium in slowing down the rate of adaptive evolution arises from a combination of the Hill–Robertson effect (delays in bringing beneficial mutations together) and background selection (delays in separating beneficial mutations from deleterious hitchhikers).

Linkage is a problem for population genetic models that treat one gene locus at a time. It can, however, be exploited as a method for detecting the action of natural selection via selective sweeps.

In the extreme case of an asexual population, linkage is complete, and population genetic equations can be derived and solved in terms of a travelling wave of genotype frequencies along a simple fitness landscape. [68] Most microbes, such as bacteria, are asexual. The population genetics of their adaptation have two contrasting regimes. When the product of the beneficial mutation rate and population size is small, asexual populations follow a "successional regime" of origin-fixation dynamics, with adaptation rate strongly dependent on this product. When the product is much larger, asexual populations follow a "concurrent mutations" regime with adaptation rate less dependent on the product, characterized by clonal interference and the appearance of a new beneficial mutation before the last one has fixed.

### Explaining levels of genetic variation Edit

Neutral theory predicts that the level of nucleotide diversity in a population will be proportional to the product of the population size and the neutral mutation rate. The fact that levels of genetic diversity vary much less than population sizes do is known as the "paradox of variation". [69] While high levels of genetic diversity were one of the original arguments in favor of neutral theory, the paradox of variation has been one of the strongest arguments against neutral theory.

It is clear that levels of genetic diversity vary greatly within a species as a function of local recombination rate, due to both genetic hitchhiking and background selection. Most current solutions to the paradox of variation invoke some level of selection at linked sites. [70] For example, one analysis suggests that larger populations have more selective sweeps, which remove more neutral genetic diversity. [71] A negative correlation between mutation rate and population size may also contribute. [72]

Life history affects genetic diversity more than population history does, e.g. r-strategists have more genetic diversity. [70]

### Detecting selection Edit

Population genetics models are used to infer which genes are undergoing selection. One common approach is to look for regions of high linkage disequilibrium and low genetic variance along the chromosome, to detect recent selective sweeps.

A second common approach is the McDonald–Kreitman test. The McDonald–Kreitman test compares the amount of variation within a species (polymorphism) to the divergence between species (substitutions) at two types of sites, one assumed to be neutral. Typically, synonymous sites are assumed to be neutral. [73] Genes undergoing positive selection have an excess of divergent sites relative to polymorphic sites. The test can also be used to obtain a genome-wide estimate of the proportion of substitutions that are fixed by positive selection, α. [74] [75] According to the neutral theory of molecular evolution, this number should be near zero. High numbers have therefore been interpreted as a genome-wide falsification of neutral theory. [76]

### Demographic inference Edit

The simplest test for population structure in a sexually reproducing, diploid species, is to see whether genotype frequencies follow Hardy-Weinberg proportions as a function of allele frequencies. For example, in the simplest case of a single locus with two alleles denoted A and a at frequencies p and q, random mating predicts freq(AA) = p 2 for the AA homozygotes, freq(aa) = q 2 for the aa homozygotes, and freq(Aa) = 2pq for the heterozygotes. In the absence of population structure, Hardy-Weinberg proportions are reached within 1-2 generations of random mating. More typically, there is an excess of homozygotes, indicative of population structure. The extent of this excess can be quantified as the inbreeding coefficient, F.

Individuals can be clustered into K subpopulations. [77] [78] The degree of population structure can then be calculated using FST, which is a measure of the proportion of genetic variance that can be explained by population structure. Genetic population structure can then be related to geographic structure, and genetic admixture can be detected.

Coalescent theory relates genetic diversity in a sample to demographic history of the population from which it was taken. It normally assumes neutrality, and so sequences from more neutrally-evolving portions of genomes are therefore selected for such analyses. It can be used to infer the relationships between species (phylogenetics), as well as the population structure, demographic history (e.g. population bottlenecks, population growth), biological dispersal, source–sink dynamics [79] and introgression within a species.

Another approach to demographic inference relies on the allele frequency spectrum. [80]

### Evolution of genetic systems Edit

By assuming that there are loci that control the genetic system itself, population genetic models are created to describe the evolution of dominance and other forms of robustness, the evolution of sexual reproduction and recombination rates, the evolution of mutation rates, the evolution of evolutionary capacitors, the evolution of costly signalling traits, the evolution of ageing, and the evolution of co-operation. For example, most mutations are deleterious, so the optimal mutation rate for a species may be a trade-off between the damage from a high deleterious mutation rate and the metabolic costs of maintaining systems to reduce the mutation rate, such as DNA repair enzymes. [81]

## Population Genetics

Students learn about Hardy-Weinberg equilibrium by exploring a virtual population of koi fish. This virtual lab allows students to run experiments where they can change variables, like population size, migration rate, mutation rate, and fitness of two separate alleles.

The alleles being studied control the coloration of the fish. Fish can either be white, gold, or mottled. When all the conditions of Hardy Weinberg equilibrium are met, the p and q alleles exist at a .5 frequency each. Changing any of the five requirements, such as migrations and mutations will affect the allele frequencies.

Student complete a worksheet that first asks them to read the background information on population genetics. They summarize the five conditions needed for a population to be at equilibrium.

They then manipulate variables to explore how equilibrium is not achieved when factors such as selection strength are included. For example, if white coloration had a lower fitness, then over time, there would be fewer white alleles in the population.

Screenshot of Virtual Lab

The entire exercise was developed during the Covid-19 pandemic and was designed so that students could complete it independently from from. It is similar to the Hardy Weinberg Squirrel activity.

HS-LS4-3 – Apply concepts of statistics and probability to support explanations that organisms with an advantageous heritable trait tend to increase in proportion to organisms lacking this trait.

HS-LS4-4 – Construct an explanation based on evidence for how natural selection leads to adaptation of populations.

## Genetics Multiple Choice Questions and Answers

MCQ quiz on Genetics multiple choice questions and answers on Genetics MCQ questions quiz on Genetics objectives questions with answer test pdf for interview preparations, freshers jobs and competitive exams. Professionals, Teachers, Students and Kids Trivia Quizzes to test your knowledge on the subject.

## Genetics MCQ Questions and Answers Quiz

1. 22 autosomes and an X chromosome.
2. 22 autosomes and a Y chromosome.
3. 23 autosomes.
4. 46 chromosomes.

2. The cytoplasm of an animal cell is divided by means of:

1. A cleavage furrow.
2. A cell plate.
3. A cell membrane formed within the cytoplasm.
4. Mitosis.

3. Which of the following is correct?

1. A forms 2 hydrogen bonds with G T forms 3 hydrogen bonds with C
2. A forms 3 hydrogen bonds with T G forms 2 hydrogen bonds with C
3. A forms 2 covalent bonds with T G forms 3 covalent bonds with C
4. A forms 2 hydrogen bonds with T G forms 3 hydrogen bonds with C

4. Which of the following may contribute to causing cancer?

1. a mutation in a gene that slows the cell cycle
2. faulty DNA repair
3. loss of control over telomere length
4. all of the above

5. Which of the following is not true of DNA?

1. A pairs with T and G pairs with C
2. Nitrogen bases are 0.34 nm apart on a DNA strand
3. The double helix is 2.0 nm wide
4. The double helix is 3.4 nm wide

6. Those mutations that occur by environmental damage or mistakes during DNA replications are

7. Why is sickle cell disease so called?

1. because it makes people sick
2. its named after a special type of white blood cell
3. pH changes in the blood cells make them collapse into a sickle shape
4. because its caused by an infectious microorganism that has sickle shaped cells

8. Those cancers that derived from ectoderm or endoderm of epithelial cell are called

9. During cell division there are three types of check points one of them (M checkpoint) to ensure