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Mutations (practice) | Khan Academy[^1^]



In this collection of papers, various aspects are considered in detail, and in this introduction, we aim to provide an overview as a basis for the in-depth treatments that follow. We outline some of the theories that serve as the quantitative basis for more applied questions and have been developed with the main aims of: (i) measuring the rates at which different types of mutations occur in nature, (ii) predicting quantitatively their subsequent fate in populations, and (iii) assessing how they affect some properties of populations and therefore could be used for inference. The subsequent papers are broadly arranged in a continuum from specific questions of basic parameter estimation (strength of mutation, selection, recombination), via those that contribute a combination of biological theories and data on these parameters, to those which mostly address broader biological theories.


There is an enormous range of mutational effects on fitness, and wide differences exist in the strength of other evolutionary forces that operate on populations. This generates an array of complex phenomena that continues to challenge our capacity to mechanistically understand evolution. To make problems tractable, theoreticians have divided the parameter space into smaller regions such that specific simplifying assumptions can be made. These typically comprise assuming the absence of particular events (e.g. no recombination) or the presence of particular equilibria (e.g. mutation-selection balance). Subsequently, new theories are often developed in which these assumptions are relaxed so as to narrow the gap to reality, typically including more interactions between various evolutionary forces, albeit at the cost of becoming less tractable to analysis.




Mutation Worksheet Problems Biol



Of course not all mutations are harmful, and the occasional fitness increasing mutations drive adaptive evolution. In this issue Orr (2010) points out how some intriguing statements can be made about advantageous mutations beyond the fact that they are usually rare and difficult to observe. They include (i) back mutations that occur if a large enough number of slightly deleterious mutations was previously fixed, possibly at a time when the effective population size was smaller (Charlesworth & Eyre-Walker 2007), (ii) compensatory mutations that at least partially repair some harmful effects at the molecular level (e.g. Burch & Chao 1999; Innan & Stephan 2001; Kern & Kondrashov 2004), (iii) quantitative trait mutations that can either increase or decrease the value of a trait with an impact on fitness (e.g. Keightley & Halligan 2009), (iv) resistance mutations that are part of biological arms races between hosts and parasites (Hamilton et al. 1990), and (v) mutations that enable a species to start expanding into a new ecological niche (e.g. Elena & Lenski 2003; Bergthorsson et al. 2007). The frequencies and DMEs of these groups are probably very different and their prediction and estimation are likely to be fruitful fields for further research.


Evolutionary models are important for understanding a range of problems fundamental to biology and to other applications to health and welfare. For example, in this themed issue Hughes (2010) discusses the role of mutation in the evolution of ageing. This is a controversial subject on which Charlesworth (2000) has made significant contributions. Models of the evolution of pathogenic microbes (Sniegowski & Gerrish 2010) and their mutations (Trindade et al. 2010) are important for medical applications, such as optimizing the use of antibiotics to minimize resistance evolution and developing vaccines that might anticipate and neutralize simple evolutionary changes a pathogen is expected to produce. The wealth of data that can be obtained for these systems makes them attractive subjects for basic research on evolution. Some mutations that would be deleterious in natural populations provide the opportunity for improvement of crops and livestock in the farm environment. Understanding their pleiotropic effects, for example, is fundamental to long-term increase in food production.


Mechanisms that contribute to the development of cancer are numerous and complicated, though most can be traced to a set of mutations in cell cycle regulatory genes that throw the process of cell division off balance. Communication of these complex mechanisms in an engaging way often presents a challenge in a large introductory course with students from varied backgrounds and at distinct knowledge levels. We present a mixed active learning approach to facilitate student understanding of how mutation-mediated disruptions in cell cycle regulation can lead to the development of lung cancer. This lesson includes a case-based scenario, a card game about cell cycle checkpoints, mutations, and disrupted mechanisms in cancer, a problem-solving worksheet about mutations, and several electronic audience response questions interspersed throughout to monitor student progress. Through assessment of student content knowledge and perceptions, we have found this lesson to be an effective, engaging, and enjoyable way for students to learn about the molecular mechanisms underlying cancer development.


The lesson presented here is unique in that it combines multiple evidence-based approaches including a case-based scenario, a card game, a problem-based worksheet about mutations, and several real-time classroom-response questions interspersed throughout as a mechanism to gauge student progress. At the core of the lesson is a card game about cell cycle checkpoints, mutations, and mechanisms that are disrupted in cancer, which reinforces these concepts in an engaging way. This provides a holistic approach to student learning as they engage with peers in collaborative teams.


Mutations in repair genes have been known to cause cancer. Many mutated repair genes have been implicated in certain forms of pancreatic cancer, colon cancer, and colorectal cancer. Mutations can affect either somatic cells or germ cells. If many mutations accumulate in a somatic cell, they may lead to problems such as the uncontrolled cell division observed in cancer. If a mutation takes place in germ cells, the mutation will be passed on to the next generation, as in the case of hemophilia and xeroderma pigmentosa.


Mutation in general means a change or the process of changing, such as in nature, form, or quality. In biology, mutation refers to any change in the nucleotide sequence as a result of a failure of the system to revert the change. Thus, the altered sequence is permanent and heritable.


Mutations may arise from faulty deletions, insertions, or exchanges of nucleotides in the genetic material. These, in turn, may be caused by exposure to mutagens, such as ultraviolet or ionizing radiation, certain chemicals, and viruses. When a point mutation occurs in the DNA sequence, for instance, the error is corrected or repaired by direct reversal or by the replacement of damaged nitrogenous bases. When these mechanisms fail to restore the integrity of the sequence, the result is a mutation that is permanent and heritable. The error is propagated by DNA replication, i.e. a biological process of copying a strand of DNA.


1. 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What is a gene called that codes for a positive cell cycle regulator?\\n\",\"library\":\"H5P.MultiChoice 1.14\",\"metadata\":\"contentType\":\"Multiple Choice\",\"license\":\"U\",\"title\":\"Question 2 Multiple Choice\",\"subContentId\":\"5e986069-9c78-4b80-8616-bb04019ae20e\",\"useSeparator\":\"auto\",\"content\":\"params\":\"taskDescription\":\"3. 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This increases the chance that more mutations will be left *un-repaired* in the cell. Each subsequent generation of cells sustains more damage. The cell cycle can speed up as a result of loss of functional checkpoint *proteins*. The cells can lose the ability to self-destruct.\",\"library\":\"H5P.DragText 1.8\",\"metadata\":\"contentType\":\"Drag Text\",\"license\":\"U\",\"title\":\"Question 3 Drag Text\",\"subContentId\":\"6a4ca3f9-d7e0-4303-b3d9-674a70c60c96\",\"useSeparator\":\"auto\",\"content\":\"params\":\"taskDescription\":\"4. Drag the words into the correct boxes to complete the statements. \\n\",\"overallFeedback\":[\"from\":0,\"to\":100],\"checkAnswer\":\"Check\",\"tryAgain\":\"Retry\",\"showSolution\":\"Show solution\",\"dropZoneIndex\":\"Drop Zone @index.\",\"empty\":\"Drop Zone @index is empty.\",\"contains\":\"Drop Zone @index contains draggable @draggable.\",\"ariaDraggableIndex\":\"@index of @count draggables.\",\"tipLabel\":\"Show tip\",\"correctText\":\"Correct!\",\"incorrectText\":\"Incorrect!\",\"resetDropTitle\":\"Reset drop\",\"resetDropDescription\":\"Are you sure you want to reset this drop zone?\",\"grabbed\":\"Draggable is grabbed.\",\"cancelledDragging\":\"Cancelled dragging.\",\"correctAnswer\":\"Correct answer:\",\"feedbackHeader\":\"Feedback\",\"behaviour\":\"enableRetry\":true,\"enableSolutionsButton\":true,\"enableCheckButton\":true,\"instantFeedback\":false,\"scoreBarLabel\":\"You got :num out of :total points\",\"textField\":\"The difference between a proto-oncogene and a tumor suppressor gene is a proto-oncogene is the segment of DNA that codes for one of the *positive* cell-cycle regulators. 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