Glossary of Genetic Terms Used in This Review
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(APOCI, -C2, and -E and LDLR) and the Genes C3, PEPD, and GPI (Whole-Arm Translocation/Somatic Cell Hybrids/Genomic Clones/Gene Family/Atherosclerosis) A
Proc. Natl. Acad. Sci. USA Vol. 83, pp. 3929-3933, June 1986 Genetics Regional mapping of human chromosome 19: Organization of genes for plasma lipid transport (APOCI, -C2, and -E and LDLR) and the genes C3, PEPD, and GPI (whole-arm translocation/somatic cell hybrids/genomic clones/gene family/atherosclerosis) A. J. LUSIS*t, C. HEINZMANN*, R. S. SPARKES*, J. SCOTTt, T. J. KNOTTt, R. GELLER§, M. C. SPARKES*, AND T. MOHANDAS§ *Departments of Medicine and Microbiology, University of California School of Medicine, Center for the Health Sciences, Los Angeles, CA 90024; tMolecular Medicine, Medical Research Council Clinical Research Centre, Harrow, Middlesex HA1 3UJ, United Kingdom; and §Department of Pediatrics, Harbor Medical Center, Torrance, CA 90509 Communicated by Richard E. Dickerson, February 6, 1986 ABSTRACT We report the regional mapping of human from defects in the expression of the low density lipoprotein chromosome 19 genes for three apolipoproteins and a lipopro- (LDL) receptor and is strongly correlated with atheroscle- tein receptor as well as genes for three other markers. The rosis (15). Another relatively common dyslipoproteinemia, regional mapping was made possible by the use of a reciprocal type III hyperlipoproteinemia, is associated with a structural whole-arm translocation between the long arm of chromosome variation of apolipoprotein E (apoE) (16). Also, a variety of 19 and the short arm of chromosome 1. Examination of three rare apolipoprotein deficiencies result in gross perturbations separate somatic cell hybrids containing the long arm but not of plasma lipid transport; for example, apoCII deficiency the short arm of chromosome 19 indicated that the genes for results in high fasting levels oftriacylglycerol (17). -
A Chloroplast Gene Is Converted Into a Nucleargene
Proc. Nati. Acad. Sci. USA Vol. 85, pp. 391-395, January 1988 Biochemistry Relocating a gene for herbicide tolerance: A chloroplast gene is converted into a nuclear gene (QB protein/atrazine tolerance/transit peptide) ALICE Y. CHEUNG*, LAWRENCE BOGORAD*, MARC VAN MONTAGUt, AND JEFF SCHELLt: *Department of Cellular and Developmental Biology, 16 Divinity Avenue, The Biological Laboratories, Harvard University, Cambridge, MA 02138; tLaboratorium voor Genetica, Rijksuniversiteit Ghent, B-9000 Ghent, Belgium; and TMax-Planck-Institut fur Zuchtungsforschung, D-500 Cologne 30, Federal Republic of Germany Contributed by Lawrence Bogorad, September 30, 1987 ABSTRACT The chloroplast gene psbA codes for the the gene for ribulose bisphosphate carboxylase/oxygenase photosynthetic quinone-binding membrane protein Q which can transport the protein product into chloroplasts (5). We is the target of the herbicide atrazine. This gene has been have spliced the coding region of the psbA gene isolated converted into a nuclear gene. The psbA gene from an from the chloroplast DNA of the atrazine-resistant biotype atrazine-resistant biotype of Amaranthus hybridus has been of Amaranthus to the transcriptional-control and transit- modified by fusing its coding region to transcription- peptide-encoding regions of a nuclear gene, ss3.6, for the regulation and transit-peptide-encoding sequences of a bona SSU of ribulose bisphosphate carboxylase/oxygenase of pea fide nuclear gene. The constructs were introduced into the (6). The fusion-gene constructions (designated SSU-ATR) nuclear genome of tobacco by using the Agrobacteium tumor- were introduced into tobacco plants via the Agrobacterium inducing (Ti) plasmid system, and the protein product of tumor-inducing (Ti) plasmid transformation system using the nuclear psbA has been identified in the photosynthetic mem- disarmed Ti plasmid vector pGV3850 (7). -
Population Genetic Considerations for Using Biobanks As International
Carress et al. BMC Genomics (2021) 22:351 https://doi.org/10.1186/s12864-021-07618-x REVIEW Open Access Population genetic considerations for using biobanks as international resources in the pandemic era and beyond Hannah Carress1, Daniel John Lawson2 and Eran Elhaik1,3* Abstract The past years have seen the rise of genomic biobanks and mega-scale meta-analysis of genomic data, which promises to reveal the genetic underpinnings of health and disease. However, the over-representation of Europeans in genomic studies not only limits the global understanding of disease risk but also inhibits viable research into the genomic differences between carriers and patients. Whilst the community has agreed that more diverse samples are required, it is not enough to blindly increase diversity; the diversity must be quantified, compared and annotated to lead to insight. Genetic annotations from separate biobanks need to be comparable and computable and to operate without access to raw data due to privacy concerns. Comparability is key both for regular research and to allow international comparison in response to pandemics. Here, we evaluate the appropriateness of the most common genomic tools used to depict population structure in a standardized and comparable manner. The end goal is to reduce the effects of confounding and learn from genuine variation in genetic effects on phenotypes across populations, which will improve the value of biobanks (locally and internationally), increase the accuracy of association analyses and inform developmental efforts. Keywords: Bioinformatics, Population structure, Population stratification bias, Genomic medicine, Biobanks Background individuals, families, communities and populations, ne- Association studies aim to detect whether genetic vari- cessitated genomic biobanks. -
Genome-Wide Association Identifies Candidate Genes That Influence The
Genome-wide association identifies candidate genes that influence the human electroencephalogram Colin A. Hodgkinsona,1, Mary-Anne Enocha, Vibhuti Srivastavaa, Justine S. Cummins-Omana, Cherisse Ferriera, Polina Iarikovaa, Sriram Sankararamanb, Goli Yaminia, Qiaoping Yuana, Zhifeng Zhoua, Bernard Albaughc, Kenneth V. Whitea, Pei-Hong Shena, and David Goldmana aLaboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism, Rockville, MD 20852; bComputer Science Department, University of California, Berkeley, CA 94720; and cCenter for Human Behavior Studies, Weatherford, OK 73096 Edited* by Raymond L. White, University of California, Emeryville, CA, and approved March 31, 2010 (received for review July 23, 2009) Complex psychiatric disorders are resistant to whole-genome reflects rhythmic electrical activity of the brain. EEG patterns analysis due to genetic and etiological heterogeneity. Variation in dynamically and quantitatively index cortical activation, cognitive resting electroencephalogram (EEG) is associated with common, function, and state of consciousness. EEG traits were among the complex psychiatric diseases including alcoholism, schizophrenia, original intermediate phenotypes in neuropsychiatry, having been and anxiety disorders, although not diagnostic for any of them. EEG first recorded in humans in 1924 by Hans Berger, who documented traits for an individual are stable, variable between individuals, and the α rhythm, seen maximally during states of relaxation with eyes moderately to highly heritable. Such intermediate phenotypes closed, and supplanted by faster β waves during mental activity. appear to be closer to underlying molecular processes than are EEG can be used clinically for the evaluation and differential di- clinical symptoms, and represent an alternative approach for the agnosis of epilepsy and sleep disorders, differentiation of en- identification of genetic variation that underlies complex psychiat- cephalopathy from catatonia, assessment of depth of anesthesia, ric disorders. -
DNA Microarrays (Gene Chips) and Cancer
DNA Microarrays (Gene Chips) and Cancer Cancer Education Project University of Rochester DNA Microarrays (Gene Chips) and Cancer http://www.biosci.utexas.edu/graduate/plantbio/images/spot/microarray.jpg http://www.affymetrix.com Part 1 Gene Expression and Cancer Nucleus Proteins DNA RNA Cell membrane All your cells have the same DNA Sperm Embryo Egg Fertilized Egg - Zygote How do cells that have the same DNA (genes) end up having different structures and functions? DNA in the nucleus Genes Different genes are turned on in different cells. DIFFERENTIAL GENE EXPRESSION GENE EXPRESSION (Genes are “on”) Transcription Translation DNA mRNA protein cell structure (Gene) and function Converts the DNA (gene) code into cell structure and function Differential Gene Expression Different genes Different genes are turned on in different cells make different mRNA’s Differential Gene Expression Different genes are turned Different genes Different mRNA’s on in different cells make different mRNA’s make different Proteins An example of differential gene expression White blood cell Stem Cell Platelet Red blood cell Bone marrow stem cells differentiate into specialized blood cells because different genes are expressed during development. Normal Differential Gene Expression Genes mRNA mRNA Expression of different genes results in the cell developing into a red blood cell or a white blood cell Cancer and Differential Gene Expression mRNA Genes But some times….. Mutations can lead to CANCER CELL some genes being Abnormal gene expression more or less may result -
Genetic Code
AccessScience from McGraw-Hill Education Page 1 of 9 www.accessscience.com Genetic code Contributed by: P. Schimmel, K. Ewalt Publication year: 2014 The rules by which the base sequences of deoxyribonucleic acid (DNA) are translated into the amino acid sequences of proteins. Each sequence of DNA that codes for a protein is transcribed or copied ( Fig. 1 ) into messenger ribonucleic acid (mRNA). Following the rules of the code, discrete elements in the mRNA, known as codons, specify each of the 20 different amino acids that are the constituents of proteins. In a process called translation, the cell decodes the message in mRNA. During translation ( Fig. 2 ), another class of RNAs, called transfer RNAs (tRNAs), are coupled to amino acids, bind to the mRNA, and in a step-by-step fashion provide the amino acids that are linked together in the order called for by the mRNA sequence. The specific attachment of each amino acid to the appropriate tRNA, and the precise pairing of tRNAs via their anticodons to the correct codons in the mRNA, form the basis of the genetic code. See also: DEOXYRIBONUCLEIC ACID (DNA) ; PROTEIN ; RIBONUCLEIC ACID (RNA) . Universal genetic code The genetic information in DNA is found in the sequence or order of four bases that are linked together to form each strand of the two-stranded DNA molecule. The bases of DNA are adenine, guanine, thymine, and cytosine, which are abbreviated A, G, T, and C. Chemically, A and G are purines, and C and T are pyrimidines. The two strands of DNA are wound about each other in a double helix that looks like a twisted ladder (Fig. -
Gene Linkage and Genetic Mapping 4TH PAGES © Jones & Bartlett Learning, LLC
© Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR SALE OR DISTRIBUTION NOT FOR SALE OR DISTRIBUTION Gene Linkage and © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC 4NOTGenetic FOR SALE OR DISTRIBUTIONMapping NOT FOR SALE OR DISTRIBUTION CHAPTER ORGANIZATION © Jones & Bartlett Learning, LLC © Jones & Bartlett Learning, LLC NOT FOR4.1 SALELinked OR alleles DISTRIBUTION tend to stay 4.4NOT Polymorphic FOR SALE DNA ORsequences DISTRIBUTION are together in meiosis. 112 used in human genetic mapping. 128 The degree of linkage is measured by the Single-nucleotide polymorphisms (SNPs) frequency of recombination. 113 are abundant in the human genome. 129 The frequency of recombination is the same SNPs in restriction sites yield restriction for coupling and repulsion heterozygotes. 114 fragment length polymorphisms (RFLPs). 130 © Jones & Bartlett Learning,The frequency LLC of recombination differs © Jones & BartlettSimple-sequence Learning, repeats LLC (SSRs) often NOT FOR SALE OR DISTRIBUTIONfrom one gene pair to the next. NOT114 FOR SALEdiffer OR in copyDISTRIBUTION number. 131 Recombination does not occur in Gene dosage can differ owing to copy- Drosophila males. 115 number variation (CNV). 133 4.2 Recombination results from Copy-number variation has helped human populations adapt to a high-starch diet. 134 crossing-over between linked© Jones alleles. & Bartlett Learning,116 LLC 4.5 Tetrads contain© Jonesall & Bartlett Learning, LLC four products of meiosis. -
Dna the Code of Life Worksheet
Dna The Code Of Life Worksheet blinds.Forrest Jowled titter well Giffy as misrepresentsrecapitulatory Hughvery nomadically rubberized herwhile isodomum Leonerd exhumedremains leftist forbiddenly. and sketchable. Everett clem invincibly if arithmetical Dawson reinterrogated or Rewriting the Code of Life holding for Genetics and Society. C A process look a genetic code found in DNA is copied and converted into value chain of. They may negatively impact of dna worksheet answers when published by other. Cracking the Code of saw The Biotechnology Institute. DNA lesson plans mRNA tRNA labs mutation activities protein synthesis worksheets and biotechnology experiments for open school property school biology. DNA the code for life FutureLearn. Cracked the genetic code to DNA cloning twins and Dolly the sheep. Dna are being turned into consideration the code life? DNA The Master Molecule of Life CDN. This window or use when he has been copied to a substantial role in a qualified healthcare professional journals as dna the pace that the class before scientists have learned. Explore the Human Genome Project within us Learn about DNA and genomics role in medicine and excellent at the Smithsonian National Museum of Natural. DNA The Double Helix. Most enzymes create a dna the code of life worksheet is getting the. Worksheet that describes the structure of DNA students color the model according to instructions Includes a. Biology Materials Handout MA-H2 Microarray Virtual Lab Activity Worksheet. This user has, worksheet the dna code of life, which proteins are carried on. Notes that scientists have worked 10 years to disappoint the manner human genome explains that DNA is a chemical message that began more data four billion years ago. -
Expression Quantitative Trait Loci and the Phenogen
TECHNOLOGIES FROM THE FIELD EXPRESSION QUANTITATIVE TRAIT LOCI AND Like experimental technologies, techniques for analyz THE PHENOGEN DATABASE ing the data generated from the microarray technologies continue to evolve. Initially, researchers obtained data for several thousand genes but on a relatively small number of Laura Saba, Ph.D.; Paula L. Hoffman, Ph.D.; subjects. After applying the appropriate statistics and multi Cheryl Hornbaker; Sanjiv V. Bhave, Ph.D.; and ple comparison adjustment, the investigators would com Boris Tabakoff, Ph.D. pile from these a list of potential candidates that could contribute to the phenotype under investigation. In many KEY WORDS: Genetic theory of alcohol and other drug use; cases, this list would contain several hundred genes. For a microarray technologies; microarray analysis; phenotype; researcher who is looking to take a few candidate genes to candidate gene; qualitative trait locus (QTL); expression qualitative the next step of testing, such a long list was problematic. trait locus (eQTL); gene expression; gene transcription; genetics; With only limited resources and time available, the researcher genomics; transcriptomics; high-throughput analysis; messenger was forced to pick some “favorites” from the list for further RNA (mRNA); brain; laboratory mice; laboratory rats; PhenoGen testing. More recently, however, techniques have been Database developed to systematically narrow these lists. These approaches incorporate biological reasoning to avoid a subjective choice of candidate genes. The following section describes esearchers from a wide variety of backgrounds and one of these strategies. with a broad range of goals have utilized high- R throughput screening technologies (i.e., microarray technologies) to identify candidate genes that may be associ Behavioral and Expression Quantitative ated with an observable characteristic or behavior (i.e., phe Trait Loci for Selecting Candidate Genes notype) of interest. -
GENOME GENERATION Glossary
GENOME GENERATION Glossary Chromosome An organism’s DNA is packaged into chromosomes. Humans have 23 pairs of chromosomesincluding one pair of sex chromosomes. Women have two X chromosomes and men have one X and one Y chromosome. Dominant (see also recessive) Genes come in pairs. A dominant form of a gene is the “stronger” version that will be expressed. Therefore if someone has one dominant and one recessive form of a gene, only the characteristics of the dominant form will appear. DNA DNA is the long molecule that contains the genetic instructions for nearly all living things. Two strands of DNA are twisted together into a double helix. The DNA code is made up of four chemical letters (A, C, G and T) which are commonly referred to as bases or nucleotides. Gene A gene is a section of DNA that is the code for a specific biological component, usually a protein. Each gene may have several alternative forms. Each of us has two copies of most of our genes, one copy inherited from each parent. Most of our traits are the result of the combined effects of a number of different genes. Very few traits are the result of just one gene. Genetic sequence The precise order of letters (bases) in a section of DNA. Genome A genome is the complete DNA instructions for an organism. The human genome contains 3 billion DNA letters and approximately 23,000 genes. Genomics Genomics is the study of genomes. This includes not only the DNA sequence itself, but also an understanding of the function and regulation of genes both individually and in combination. -
DNA Sequencing and Sorting: Identifying Genetic Variations
BioMath DNA Sequencing and Sorting: Identifying Genetic Variations Student Edition Funded by the National Science Foundation, Proposal No. ESI-06-28091 This material was prepared with the support of the National Science Foundation. However, any opinions, findings, conclusions, and/or recommendations herein are those of the authors and do not necessarily reflect the views of the NSF. At the time of publishing, all included URLs were checked and active. We make every effort to make sure all links stay active, but we cannot make any guaranties that they will remain so. If you find a URL that is inactive, please inform us at [email protected]. DIMACS Published by COMAP, Inc. in conjunction with DIMACS, Rutgers University. ©2015 COMAP, Inc. Printed in the U.S.A. COMAP, Inc. 175 Middlesex Turnpike, Suite 3B Bedford, MA 01730 www.comap.com ISBN: 1 933223 71 5 Front Cover Photograph: EPA GULF BREEZE LABORATORY, PATHO-BIOLOGY LAB. LINDA SHARP ASSISTANT This work is in the public domain in the United States because it is a work prepared by an officer or employee of the United States Government as part of that person’s official duties. DNA Sequencing and Sorting: Identifying Genetic Variations Overview Each of the cells in your body contains a copy of your genetic inheritance, your DNA which has been passed down to you, one half from your biological mother and one half from your biological father. This DNA determines physical features, like eye color and hair color, and can determine susceptibility to medical conditions like hypertension, heart disease, diabetes, and cancer. -
An Introduction to Recurrent Nucleotide Interactions in RNA Blake A
Overview An introduction to recurrent nucleotide interactions in RNA Blake A. Sweeney,1 Poorna Roy2 and Neocles B. Leontis2∗ RNA secondary structure diagrams familiar to molecular biologists summarize at a glance the folding of RNA chains to form Watson–Crick paired double helices. However, they can be misleading: First of all, they imply that the nucleotides in loops and linker segments, which can amount to 35% to 50% of a structured RNA, do not significantly interact with other nucleotides. Secondly, they give the impression that RNA molecules are loosely organized in three-dimensional (3D) space. In fact, structured RNAs are compactly folded as a result of numerous long-range, sequence-specific interactions, many of which involve loop or linker nucleotides. Here, we provide an introduction for students and researchers of RNA on the types, prevalence, and sequence variations of inter-nucleotide interactions that structure and stabilize RNA 3D motifs and architectures, using Escherichia coli (E. coli) 16S ribosomal RNA as a concrete example. The picture that emerges is that almost all nucleotides in structured RNA molecules, including those in nominally single-stranded loop or linker regions, form specific interactions that stabilize functional structures or mediate interactions with other molecules. The small number of noninteracting, ‘looped-out’ nucleotides make it possible for the RNA chain to form sharp turns. Base-pairing is the most specific interaction in RNA as it involves edge-to-edge hydrogen bonding (H-bonding) of the bases. Non-Watson–Crick base pairs are a significant fraction (30% or more) of base pairs in structured RNAs. © 2014 John Wiley & Sons, Ltd.