Genetic Engineering Compared to Natural Genetic Variations
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Models of the Gene Must Inform Data-Mining Strategies in Genomics
entropy Review Models of the Gene Must Inform Data-Mining Strategies in Genomics Łukasz Huminiecki Department of Molecular Biology, Institute of Genetics and Animal Biotechnology, Polish Academy of Sciences, 00-901 Warsaw, Poland; [email protected] Received: 13 July 2020; Accepted: 22 August 2020; Published: 27 August 2020 Abstract: The gene is a fundamental concept of genetics, which emerged with the Mendelian paradigm of heredity at the beginning of the 20th century. However, the concept has since diversified. Somewhat different narratives and models of the gene developed in several sub-disciplines of genetics, that is in classical genetics, population genetics, molecular genetics, genomics, and, recently, also, in systems genetics. Here, I ask how the diversity of the concept impacts data-integration and data-mining strategies for bioinformatics, genomics, statistical genetics, and data science. I also consider theoretical background of the concept of the gene in the ideas of empiricism and experimentalism, as well as reductionist and anti-reductionist narratives on the concept. Finally, a few strategies of analysis from published examples of data-mining projects are discussed. Moreover, the examples are re-interpreted in the light of the theoretical material. I argue that the choice of an optimal level of abstraction for the gene is vital for a successful genome analysis. Keywords: gene concept; scientific method; experimentalism; reductionism; anti-reductionism; data-mining 1. Introduction The gene is one of the most fundamental concepts in genetics (It is as important to biology, as the atom is to physics or the molecule to chemistry.). The concept was born with the Mendelian paradigm of heredity, and fundamentally influenced genetics over 150 years [1]. -
Chapter 14: Functional Genomics Learning Objectives
Chapter 14: Functional Genomics Learning objectives Upon reading this chapter, you should be able to: ■ define functional genomics; ■ describe the key features of eight model organisms; ■ explain techniques of forward and reverse genetics; ■ discuss the relation between the central dogma and functional genomics; and ■ describe proteomics-based approaches to functional genomics. Outline : Functional genomics Introduction Relation between genotype and phenotype Eight model organisms E. coli; yeast; Arabidopsis; C. elegans; Drosophila; zebrafish; mouse; human Functional genomics using reverse and forward genetics Reverse genetics: mouse knockouts; yeast; gene trapping; insertional mutatgenesis; gene silencing Forward genetics: chemical mutagenesis Functional genomics and the central dogma Approaches to function; Functional genomics and DNA; …and RNA; …and protein Proteomic approaches to functional genomics CASP; protein-protein interactions; protein networks Perspective Albert Blakeslee (1874–1954) studied the effect of altered chromosome numbers on the phenotype of the jimson-weed Datura stramonium, a flowering plant. Introduction: Functional genomics Functional genomics is the genome-wide study of the function of DNA (including both genes and non-genic regions), as well as RNA and proteins encoded by DNA. The term “functional genomics” may apply to • the genome, transcriptome, or proteome • the use of high-throughput screens • the perturbation of gene function • the complex relationship of genotype and phenotype Functional genomics approaches to high throughput analyses Relationship between genotype and phenotype The genotype of an individual consists of the DNA that comprises the organism. The phenotype is the outward manifestation in terms of properties such as size, shape, movement, and physiology. We can consider the phenotype of a cell (e.g., a precursor cell may develop into a brain cell or liver cell) or the phenotype of an organism (e.g., a person may have a disease phenotype such as sickle‐cell anemia). -
Gene Therapy and Genetic Engineering: Frankenstein Is Still a Myth, but It Should Be Reread Periodically
Indiana Law Journal Volume 48 Issue 4 Article 2 Summer 1973 Gene Therapy and Genetic Engineering: Frankenstein is Still a Myth, but it Should be Reread Periodically George A. Hudock Indiana University - Bloomington Follow this and additional works at: https://www.repository.law.indiana.edu/ilj Part of the Genetics and Genomics Commons Recommended Citation Hudock, George A. (1973) "Gene Therapy and Genetic Engineering: Frankenstein is Still a Myth, but it Should be Reread Periodically," Indiana Law Journal: Vol. 48 : Iss. 4 , Article 2. Available at: https://www.repository.law.indiana.edu/ilj/vol48/iss4/2 This Article is brought to you for free and open access by the Law School Journals at Digital Repository @ Maurer Law. It has been accepted for inclusion in Indiana Law Journal by an authorized editor of Digital Repository @ Maurer Law. For more information, please contact [email protected]. GENE THERAPY AND GENETIC ENGINEERING: FRANKENSTEIN IS STILL A MYTH, BUT IT SHOULD BE REREAD PERIODICALLY GEORGE A. HUDOCKt Biotechnology and the law are far removed from each other as disciplines of human intellect. Yet the law and my own discipline, genetics, have come together in many courtrooms concerning such matters as paternity, and they will continue to intersect with increasing frequency as the visions of 100 years ago become the reality of today. This article examines the implications of recent research for human genetic therapy and genetic engineering, and suggests some guidelines for legal regulation of genetic technology. The following discussion derives from three premises which I view as basic: (1) that which is currently possible in genetic engineering, and in fact has already been done, is generally underestimated; (2) what may be possible in the near future is quite commonly overesti- mated; (3) regulation of the application of genetic technology is possible and will not be overwhelmingly complicated. -
New Techniques of Genetic Engineering
March 2016 New techniques of genetic engineering Why EU GMO law must be fully applied to the so-called ‘New Plant Breeding Techniques’ The European Commission is considering whether genetically modified organisms (GMOs) that have been produced through a range of new techniques should be excluded from the European Union’s GMO regulations. Biotechnology companies want to apply these techniques to engineer plants and animals for use in industrial food, biomass and biofuel production. They argue that these new methods to directly modify the genetic make-up of living organisms fall outside the scope of EU GMO regulations. This would mean that there is no risk assessment, labelling and monitoring of GM organisms produced by the new techniques and their derived products. The Commission has announced that it will present a legal analysis on the matter by the end of March 2016. The new GMOs present a real risk to the environment and human health. Legal analysis shows that they are covered by EU GMO law. If they were to escape EU regulations, any potential negative effects on food, feed or environmental safety would go unchecked. European consumers, farmers and breeders would have no way to avoid GMOs. The Commission should leave no doubt that all products of genetic engineering are subject to EU GMO law which requires rigorous risk assessment, detectability and labelling. 1 Which techniques are we talking about? The biotechnology industry and the European Commission use the term ‘New Plant Breeding Techniques’ to refer to a diverse set of genetic -
Drawing the Line: Disability, Genetic Intervention and Bioethics
laws Article Drawing the Line: Disability, Genetic Intervention and Bioethics Adam Conti Graduate student, Melbourne Law School, University of Melbourne, 185 Pelham St., Carlton, VIC 3053, Australia; [email protected] Received: 2 June 2017; Accepted: 10 July 2017; Published: 17 July 2017 Abstract: Meteoric scientific advances in genetic technologies with the potential for human gene editing intervention pose tremendous legal, medical, social, ethical and moral issues for society as a whole. Persons with disabilities in particular have a significant stake in determining how these technologies are governed at the international, domestic and individual levels in the future. However, the law cannot easily keep up with the rate of scientific progression. This paper aims to posit a methodology of reform, based on a core value of human dignity, as the optimal course of action to ensure that the interests of persons with disabilities, other possibly marginalised groups, and the scientific community, are balanced fairly. The paper critically analyses the current law and varying bioethical perspectives to ultimately conclude that a clear principled approach toward open discussion and consensus is of paramount importance to have any chance of devising an effective regulatory regime over human gene editing technology. Keywords: disability; human rights; genetics; gene editing; bioethics; governance; human dignity; eugenics; germline; Convention on the Rights of Persons with Disabilities The true good is in the different, not the same (Menand 2004). 1. Introduction Popular, professional and scholarly interest in genetics and their influence on human variability, behaviour and development has grown exponentially in recent years. In no small part has this interest been bolstered by mainstream media coverage of large-scale collaborative scientific initiatives like the Human Genome Project, which endeavoured to identify and map the human genome and determine the sequence of nucleotide base pairs that make up our DNA. -
Epigenetics Is Normal Science, but Don't Call It Lamarckian
Extended Abstract Volume 6:3, 2020 DOI: 6.2472/imedipce.2020.6.002 Journal of Clinical Epigenetics ISSN: 2472-1158 Open Access Epigenetics is Normal Science, But Don’t Call It Lamarckian David Penny New Zealand Extended Abstract they are general (but not necessarily universal) because they are found in Excavates, which many people consider are ancestral to other eukaryotes [6, 7]. Similarly, an important point is that Epigenetic mechanisms are increasingly being accepted as an integral methylation, phosphorylation, etc. of the DNA and of the histones is a part of normal science. Earlier genetic studies appear to have part of normal evolution (at least in eukaryotes that have the assumed that the only changes were ‘mutations’ as a result of a nucleosome structure) [8]. One of the most interesting aspects is change in the DNA sequence. If any such changes altered the amino methylation (and hydroxymethylation) of cytosine, and this is found in acid sequences then it was effectively a mutation, and if it occurred in many deep branching eukaryotes [9]. Typically there is methylation of a germline cell (including in unicellular organisms) then it could be cytosine molecules, especially in CpG (cytosine followed by guanine) passed on to subsequent generations. However, it is increasingly regions. The role of small RNAs in helping regulate the levels of apparent that other changes are also important, for example, changes protein expression is discussed in [10]. The main point here is that to methylation patterns, and to the histone proteins. Epigenetics was protein expression levels are very variable in all cells – it is not just sometimes consider ‘additional’ to classical genetics, but it is still fully classical genetics that is important; there are many epigenetic dependent on DNA, RNA and protein sequences, and at least since [1] mechanisms affecting the differences in protein expression. -
Molecular Biology and Applied Genetics
MOLECULAR BIOLOGY AND APPLIED GENETICS FOR Medical Laboratory Technology Students Upgraded Lecture Note Series Mohammed Awole Adem Jimma University MOLECULAR BIOLOGY AND APPLIED GENETICS For Medical Laboratory Technician Students Lecture Note Series Mohammed Awole Adem Upgraded - 2006 In collaboration with The Carter Center (EPHTI) and The Federal Democratic Republic of Ethiopia Ministry of Education and Ministry of Health Jimma University PREFACE The problem faced today in the learning and teaching of Applied Genetics and Molecular Biology for laboratory technologists in universities, colleges andhealth institutions primarily from the unavailability of textbooks that focus on the needs of Ethiopian students. This lecture note has been prepared with the primary aim of alleviating the problems encountered in the teaching of Medical Applied Genetics and Molecular Biology course and in minimizing discrepancies prevailing among the different teaching and training health institutions. It can also be used in teaching any introductory course on medical Applied Genetics and Molecular Biology and as a reference material. This lecture note is specifically designed for medical laboratory technologists, and includes only those areas of molecular cell biology and Applied Genetics relevant to degree-level understanding of modern laboratory technology. Since genetics is prerequisite course to molecular biology, the lecture note starts with Genetics i followed by Molecular Biology. It provides students with molecular background to enable them to understand and critically analyze recent advances in laboratory sciences. Finally, it contains a glossary, which summarizes important terminologies used in the text. Each chapter begins by specific learning objectives and at the end of each chapter review questions are also included. -
Using Classical Genetics Simulator (CGS) to Teach Students the Basics of Genetic Research
Tested Studies for Laboratory Teaching Proceedings of the Association for Biology Laboratory Education Vol. 33, 85–94, 2012 Using Classical Genetics Simulator (CGS) to Teach Students the Basics of Genetic Research Jean Heitz1, Mark Wolansky2, and Ben Adamczyk3 1University of Wisconsin, Zoology Department, 250 N. Mills Street, Madison WI 53706 USA 2University of Alberta, Department of Biological Science, Edmonton AB, CAN T6G 2E9 3Genedata, MA, A-1 Cranberry HI, Lexington MA 02421 USA ([email protected];[email protected];[email protected]) Some experiments are not well suited to large introductory labs because of space, time and funding constraints. Among these are classical Mendelian genetics investigations. Cyber labs can overcome these constraints. Classi- cal Genetics Simulator (CGS) gives students the opportunity to perform controlled crosses with model organisms much like a geneticist would do. CGS provides populations of Drosophila, Arabidopsis or mice with unknown patterns of inheritance and gives students the tools to design and perform experiments to discover these patterns. Students require an understanding of the what, why and how of solving genetic problems to successfully complete our cyber genetics lab activities. Keywords: Mendelian genetics, simulator, classical genetics simulator (CGS), linkage, monohybrid, dihybrid Introduction In large introductory biology classes some labs are dif- How can students get practice doing what geneticists ficult to do because of space, time and funding constraints. actually do? Among these are classical Mendelian genetics investiga- An obvious way for students to get practice doing what tions. As a result, we have turned to cyber labs. Working geneticists do is to conduct actual crosses. -
Genetic Engineering & Genetically Modified Organisms
Genetic Engineering & Genetically Modified Organisms: Forming Informed Opinions By Smith, Lisa Scientific Theme(s): Science and Technology *Relationships among science, technology, and society Grade Level(s): 6-8 Lesson Duration: Designed for one 70 minute lesson Overview This lesson provides students an introduction to genetic engineering and genetically modified organisms, and raises student awareness of the potential Bias of availaBle information and the importance of forming informed, defendaBle opinions regarding controversial topics in science. The lesson was designed as an introduction for students to the genetic engineering and genetically modified organisms in preparation for a two-week research project exploring GMO topics, culminating with student presentations giving their opinions on the topics. Objectives Students will: 1. Define the term, ‘Biotechnology’. 2. Understand the difference Between selective Breeding and genetic engineering. 3. Identify different applications of genetic engineering, and recognize that all genetically engineered organisms are genetically modified organisms (GMOs). 4. Recognize Bias in print media, and to Be aware of the need to identify sources. 5. Understand the importance of forming informed, defendaBle opinions. Grade Level Expectations (GLEs) Addressed Science as Inquiry and Process [7] SA2.1 identifying and evaluating the sources used to support scientific statements Science and Technology [7] SE1.1 descriBing how puBlic policy affects the student’s life (e.g., puBlic waste disposal) [7] SE3.1 recognizing the effects of a past scientific discovery, invention, or scientific Breakthrough (e.g., DDT, internal comBustion engine) Required BacKground This lesson builds upon concepts covered in previous lessons on DNA, genes, and heredity. Students should have a solid understanding of the Basics of these concepts, including the idea that DNA is the “Blueprint” of life, that genes are coding regions of DNA, and that traits encoded By genes can Be inherited. -
Evolution Ofsenescence Under Positive Pleiotropy?
Why organisms age: Evolution ofsenescence under positive pleiotropy? Alexei A. Maklako, Locke Rowe and Urban Friberg Linköping University Post Print N.B.: When citing this work, cite the original article. Original Publication: Alexei A. Maklako, Locke Rowe and Urban Friberg, Why organisms age: Evolution ofsenescence under positive pleiotropy?, 2015, Bioessays, (37), 7, 802-807. http://dx.doi.org/10.1002/bies.201500025 Copyright: Wiley-VCH Verlag http://www.wiley-vch.de/publish/en/ Postprint available at: Linköping University Electronic Press http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-117545 1 Why organisms age: Evolution of senescence under positive pleiotropy? Alexei A. Maklakov1, Locke Rowe2 and Urban Friberg3,4 1Ageing Research Group, Department of Animal Ecology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden 2 Department of Ecology and Evolutionary Biology, University of Toronto, 25 Willcocks St., Toronto, ON, M5S 3G5, Canada 3Ageing Research Group, Department of Evolutionary Biology, Evolutionary Biology Centre, Uppsala University, Uppsala, Sweden 4IFM Biology, AVIAN Behavioural Genomics and Physiology Group, Linköping University, Linköping, Sweden Corresponding author: Maklakov, A.A. ([email protected]) Keywords: Aging, life-history evolution, mutation accumulation, positive pleiotropy senescence 2 Abstract Two classic theories maintain that aging evolves either because of alleles whose deleterious effects are confined to late life or because of alleles with broad pleiotropic effects that increase early-life fitness at the expense of late-life fitness. However, empirical studies often reveal positive pleiotropy for fitness across age classes, and recent evidence suggests that selection on early-life fitness can decelerate aging and increase lifespan, thereby casting doubt on the current consensus. -
3 Further Challenges
3 Further Challenges Hamilton’s claim of the inevitability of senescence can be disproved even within his own framework. Furthermore, his framework has sev- eral limitations. In this chapter theoretical and empirical issues that weaken his approach as the main explanation for the evolution of senes- cence will be discussed. Building on Medawar [126] and Williams [212], Hamilton wrote the pioneering first chapter on the moulding of senes- cence. I draw two main conclusions. • First, Hamilton’s basic notion – that the age-pattern of mortality is an inverse function of the age-pattern of his indicator – is wrong. For both his indicator and the other indicators in Table 2.1 the relationship between the indicator and mortality is so complicated that sophisticated modeling is required. • Second, several theoretical arguments as well as the bulk of em- pirical findings suggest that mutation accumulation is of secondary importance in molding the age-trajectories of mortality across the varied species of life. The primary force appears to be adaptation, i.e. the concept that patterns of aging are a byproduct of optimiza- tion of trade-offs. Hence, deep understanding of the evolution of aging requires optimization modeling. 3.1 General Problem with All Indicators Because his indicator declines with age, Hamilton deduced that mor- tality must increase with age. The relationship between his indicator of selection pressure and the age-pattern of mortality is not a simple one, however. During development his indicator is constant, while mortality, 36 3 Further Challenges for many and perhaps all species, is falling. At post-reproductive ages his indicator is zero, while mortality, at least in humans, rises and then slowly levels off. -
Evolutionary Genetics
Evolutionary Genetics Ruben C. Arslan & Lars Penke Institute of Psychology Georg August University Göttingen Forthcoming in D. M. Buss (Ed.), Handbook of Evolutionary Psychology (2nd ed.). New York: Wiley. September 17, 2014 Corresponding author: Ruben C. Arslan Georg August University Göttingen Biological Personality Psychology and Psychological Assessment Georg Elias Müller Institute of Psychology Goßlerstr. 14 37073 Göttingen, Germany Tel.: +49 551 3920704 Email: [email protected] 1 Introduction When Charles Darwin developed the theory of evolution, he knew nothing about genetics. Hence, one of its biggest weaknesses was that Darwin had to base it on crude ideas of inheritance. Around the same time, Gregor Mendel discovered the laws of inheritance, but the scientific community initially failed to appreciate his work’s importance. It was only in the 1930’s that Dobzhansky, Fisher, Haldane, Wright, Mayr and others unified genetics and the theory of evolution in the ‘modern synthesis’. Still, the modern synthesis was built on a basic understanding of genetics, with genes merely being particulate inherited information. The basics of molecular genetics, like the structure of DNA, were not discovered until the 1950’s. When modern evolutionary psychology emerged from ethology and sociobiology in the late 1980’s, it had a strong emphasis on human universals, borne from both the assumption that complex adaptations are monomorphic (or sexually dimorphic) and have to go back to at least the last common ancestor of all humans, and the methodological proximity to experimental cognitive psychology, which tends to treat individual differences as statistical noise. As a consequence, genetic differences between people were marginalized in evolutionary psychology (Tooby & Cosmides, 1990).