Forensic DNA Phenotyping
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Estimation of DNA Contamination and Its Sources in Genotyped Samples
Gregory Zajac ORCID iD: 0000-0001-6411-9666 Estimation of DNA contamination and its sources in genotyped samples Gregory J. M. Zajac1; Lars G. Fritsche1; Joshua S. Weinstock1; Susan L. Dagenais2; Robert H. Lyons2; Chad M. Brummett3; Gonçalo. R. Abecasis1 1) Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, MI; MI; 2) Department of Biological Chemistry and DNA Sequencing Core, University of Michigan, Ann Arbor, MI; 3) Department of Anesthesiology, Division of Pain Medicine, University of Michigan Medical School, Ann Arbor, MI. Corresponding author: Gregory JM Zajac 734-763-5315 [email protected] University of Michigan School of Public Health - Department of Biostatistics 1415 Washington Heights Ann Arbor, MI 48109-2029 Grant Numbers: HG007022 Author Manuscript This is the author manuscript accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1002/gepi.22257. This article is protected by copyright. All rights reserved. Abstract Array genotyping is a cost-effective and widely used tool that enables assessment of up to millions of genetic markers in hundreds of thousands of individuals. Genotyping array data are typically highly accurate but sensitive to mixing of DNA samples from multiple individuals prior to or during genotyping. Contaminated samples can lead to genotyping errors and consequently cause false positive signals or reduce power of association analyses. Here, we propose a new method to identify contaminated samples and the sources of contamination within a genotyping batch. -
Ethical Dimensions of NGS Technologies to Criminal Investigations
ETHICAL DIMENSIONS OF THE APPLICATION OF NEXT GENERATION SEQUENCING TECHNOLOGIES TO CRIMINAL INVESTIGATIONS Author: National DNA Database Ethics Group Date: March 2017 1.0 Introduction 1.1 Next Generation Sequencing (NGS) is a term used to describe DNA sequencing technologies whereby multiple pieces of DNA are sequenced in parallel. This allows large sections of the human genome to be sequenced rapidly. The name is a catch- all-phrase that refers to high-throughput sequencing rather than the previous Sanger sequencing technology, which was much slower. NGS is also known as Massive Parallel Sequencing and the terms are often used interchangeably. Within this document the term NGS refers to technologies that provide more wide-ranging information than the standard DNA short tandem repeat (STR) profiling techniques that measure the number of repeats at a specific region of non-coding DNA within an autosomal chromosome. 1.2 NGS sequencing technologies have developed rapidly over the past decade while the costs associated with sequencing have declined. Whilst need and utility, and not merely the availability and affordability of NGS technologies, should be the driver for their introduction into criminal investigations, declining costs increase the feasibility of their introduction. It is therefore timely that the ethical issues associated with the application of NGS in criminal investigations are considered. In this document, the Ethics Group (EG) provides an outline of the NGS technologies that are likely to become available in the next 10 years and a map (albeit not yet an in-depth discussion) of the ethical challenges associated with the application of these technologies for forensic purposes. -
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. -
Fifty Years of Genetic Epidemiology, with Special Reference to Japan
J Hum Genet (2006) 51:269–277 DOI 10.1007/s10038-006-0366-9 MINIREVIEW Newton E. Morton Fifty years of genetic epidemiology, with special reference to Japan Received: 13 December 2005 / Accepted: 18 December 2005 / Published online: 15 February 2006 Ó The Japan Society of Human Genetics and Springer-Verlag 2006 Abstract Genetic epidemiology deals with etiology, dis- Introduction tribution, and control of disease in groups of relatives and with inherited causes of disease in populations. It The Japan Society of Human Genetics (JSHG) was took its first steps before its recognition as a discipline, established at a time when the science it represented was and did not reach its present scope until the Human growing so explosively that Carlson (2004) signalised the Genome Project succeeded. The intimate relationship death of classical genetics. Compared to their predeces- between genetics and epidemiology was discussed by sors, geneticists in 1956 were more distrustful of eugenics Neel and Schull (1954), just a year after Watson and and more committed to cytogenetics, biochemistry, and Crick reported the DNA double helix, and 2 years be- medical genetics, but not yet prepared for the genomic fore human cytogenetics and the Japan Society of Hu- revolution that the double helix would ultimately bring man Genetics were founded. It is convenient to divide (Yanase 1997). Population genetics was beginning to the next half-century into three phases. The first of these split into two major branches, one concerned with events (1956–1979) was before DNA polymorphisms were that took place in the past under poorly known forces of typed, and so the focus was on segregation and linkage systematic pressure and chance (evolutionary genetics), of major genes, cytogenetics, population studies, and the other dealing with etiology, distribution, and control biochemical genetics. -
Long-Term Missing Child Guide for Law Enforcement
Long-term missing child guide for law enforcement: Strategies for finding long-term missing children Long-term missing child guide for law enforcement: Strategies for finding long-term missing children 2016 Edited by Robert G. Lowery, Jr., and Robert Hoever National Center for Missing & Exploited Children® www.missingkids.org 1-800-THE-LOST® or 1-800-843-5678 ORI VA007019W Copyright © 2016 National Center for Missing & Exploited Children. All rights reserved. This project was supported by Grant No. 2015-MC-CX-K001 awarded by the Office of Juvenile Justice and Delinquency Prevention, Office of Justice Programs, U.S. Department of Justice. This document is provided for informational purposes only and does not constitute legal advice or professional opinion about specific facts. Information provided in this document may not remain current or accurate, so recipients should use this document only as a starting point for their own independent research and analysis. If legal advice or other expert assistance is required, the services of a competent professional should be sought. Points of view or opinions in this document are those of the author and do not necessarily represent the official position or policies of the U.S. Department of Justice. CyberTipline®, National Center for Missing & Exploited Children®, 1-800-THE-LOST® and Project ALERT® are registered trademarks of the National Center for Missing & Exploited Children. LONG-TERM MISSING CHILD GUIDE FOR LAW ENFORCEMENT - 2 Contents Acknowledgments.....10 Letter from John Walsh.....15 Foreword by Patty Wetterling.....16 Chapter 1: Introduction by Robert G. Lowery, Jr......18 Quick reference.....18 We are finding more long-term missing children now.....19 Are we doing enough?.....21 Chapter 2: Overview of missing children cases by Robert G. -
Manual for Conducting a Large-Scale GWAS and Whole Genome
(COVNET) NIH Lead Investigator: Stephen Chanock, M.D. ([email protected]) Director, Division of Cancer Epidemiology and Genetics, NCI NIH Investigators: Sharon Savage, M.D. ([email protected]) Lisa Mirabello, Ph.D. ([email protected]) Meredith Yeager, Ph.D. ([email protected]) Mitchell Machiela, Sc.D. ([email protected]) Joshua Sampson, Ph.D. ([email protected]) Amy Hutchinson, M.S. ([email protected]) Belynda Hicks, M.S. ([email protected]) Division of Cancer Epidemiology and Genetics, NCI Mary Carrington, Ph.D. ([email protected]) Center for Cancer Research, NCI Leslie Biesecker, M.D. ([email protected]) Teri Manolio, M.D., Ph.D. ([email protected]) National Human Genome Research Institute Steven Holland, M.D. ([email protected]) National Institute of Allergy and Infectious Diseases Project Manager Vibha Vij, M.S., MPH ([email protected]) Division of Cancer Epidemiology and Genetics, NCI Website: https://dceg.cancer.gov/research/how-we-study/genomic-studies/covnet Table of Contents Sections 1.0 Background and Rationale for a Large Crowdsourced GWAS of COVID19 Infection ...... 2 2.0 Biospecimens: genomic DNA, blood/blood products, buccal cells/saliva .......................... 6 3.0 Patient Phenotypes ............................................................................................................. 10 4.0 Genotyping and Imputation ............................................................................................... 10 5.0 Analysis Plan .................................................................................................................... -
Vendor List -2017
DEKALB COUNTY VENDOR LIST - 2017 Vendor Number Vendor Name Budget Unit Title Transaction Amount Billing City-State-Zip total ( Total Amount ) 60077 FIRST NATIONAL BANK OF OMAHA BUILD AMERICA BONDS 923597.50 1233705.50 RECOVERY ZONE BONDS 310108.00 1233705.50 77 BUILD AMERICA BONDS 800.00 1600.00 RECOVERY ZONE BONDS 800.00 1600.00 11668 1ST AYD CORPORATION FP GENERAL 711.64 ELGIN IL 60121-5298 2159.45 FP TORT & LIABILITY 1108.21 2159.45 HIGHWAY 339.60 2159.45 11926 2017 ALTERNATE REVENUE BOND FUND LANDFILL HOST BENEFIT FD 1807143.60 1807143.60 11224 4IMPRINT NURSING-SOCIAL SERVICES 1104.67 CHICAGO IL 60673-1253 1104.67 10551 A & I INNOVATIONS FP GENERAL 825.00 SYCAMORE IL 60178 2336.00 FP TORT & LIABILITY 1511.00 2336.00 2756 A-1 CORPORATE HARDWARE FACILITIES MANAGEMENT 339.30 SPRINGFIELD IL 62701 339.30 11847 A-TEC AMBULANCE INC. NURSING-NURSING 446.30 CAROL STREAM IL 60197-66 446.30 4863 A.R.C.-DEKALB LLC PUBLIC HEALTH 42.00 CAROL STREAM IL 60197-59 42.00 11586 AAE, LLC COMMUNITY ACTION 7000.00 ELK GROVE IL 60007 7000.00 3009 ABILITY NETWORK INC. NURSING-ADMINISTRATION 6310.00 MINNEAPOLIS MN 55485-60 6310.00 11685 ACCURATE CONSULTIVE SERVICES, INC. PUBLIC HEALTH 270.00 CRETE IL 60417 270.00 1971 ACCURATE DOCUMENT DESTRUCTION, INC. NURSING-MAINTENANCE 1795.91 ELK GROVE VILLAGE IL 600 2842.42 PUBLIC HEALTH 1046.51 2842.42 10123 ACP CORP. NURSING-NURSING 14012.93 CHICAGO IL 60693 14012.93 11863 ACTIVITY CONNECTION.COM LLC NURSING-ADMINISTRATION 143.40 PORTLAND OR 97204 143.40 1629 ADAMS, DONNY IMO 71.26 71.26 3685 ADAPCO, INC. -
Pharmacogenetic Testing: a Tool for Personalized Drug Therapy Optimization
pharmaceutics Review Pharmacogenetic Testing: A Tool for Personalized Drug Therapy Optimization Kristina A. Malsagova 1,* , Tatyana V. Butkova 1 , Arthur T. Kopylov 1 , Alexander A. Izotov 1, Natalia V. Potoldykova 2, Dmitry V. Enikeev 2, Vagarshak Grigoryan 2, Alexander Tarasov 3, Alexander A. Stepanov 1 and Anna L. Kaysheva 1 1 Biobanking Group, Branch of Institute of Biomedical Chemistry “Scientific and Education Center”, 109028 Moscow, Russia; [email protected] (T.V.B.); [email protected] (A.T.K.); [email protected] (A.A.I.); [email protected] (A.A.S.); [email protected] (A.L.K.) 2 Institute of Urology and Reproductive Health, Sechenov University, 119992 Moscow, Russia; [email protected] (N.V.P.); [email protected] (D.V.E.); [email protected] (V.G.) 3 Institute of Linguistics and Intercultural Communication, Sechenov University, 119992 Moscow, Russia; [email protected] * Correspondence: [email protected]; Tel.: +7-499-764-9878 Received: 2 November 2020; Accepted: 17 December 2020; Published: 19 December 2020 Abstract: Pharmacogenomics is a study of how the genome background is associated with drug resistance and how therapy strategy can be modified for a certain person to achieve benefit. The pharmacogenomics (PGx) testing becomes of great opportunity for physicians to make the proper decision regarding each non-trivial patient that does not respond to therapy. Although pharmacogenomics has become of growing interest to the healthcare market during the past five to ten years the exact mechanisms linking the genetic polymorphisms and observable responses to drug therapy are not always clear. Therefore, the success of PGx testing depends on the physician’s ability to understand the obtained results in a standardized way for each particular patient. -
M21-515 Fundamentals of Genetic Epidemiology Summer 2018
M21-515 Fundamentals of Genetic Epidemiology Summer 2018 Revised: 7/13/2018 Course Masters Treva Rice, Ph.D. ([email protected]) Yun Ju Sung, Ph.D. ([email protected]) Lab Instructor Oyomoare Osazuwa-Peters ([email protected]) Grading Computer Lab Assignments 30% Daily Quiz 30% Midterm Exam (covers lectures / homework 1-5) 20% Final Project 20% Final Grade (+/– letter grades) Software Software packages include: 1. R (http://www.r-project.org/) 2. PEDSTATS, Merlin, QTDT (http://www.sph.umich.edu/csg/abecasis) 3. PLINK (http://pngu.mgh.harvard.edu/~purcell/plink/) Textbook Austin, MA. Genetic Epidemiology: Methods & Applications 2013, CABI: Oxfordshire, UK. Format 2-week INTENSIVE course Morning lecture: 9:00 am – 12:00 noon Afternoon computer lab: 1:30 pm – 4:00 pm 10-minute break ~ every hour 1st Homework Due first day of class, Textbook (Chapters 1-2) Assignment On-line genetics tutorial, Chapters 3, 4, and 6 (http://anthro.palomar.edu/tutorials/biological.htm) Prerequisite 1) Knowledge of R programming, either having taken the MSIBS summer R-course or experience in R-programming; 2) experience in Linux/Unix operating system. The core competency for the Fundamentals of Genetic Epidemiology course (M21-515) is for students to understand basic concepts, methods and analytical approaches in genetic epidemiology. Learning objectives are to • Understand familial resemblance, heritability and family study designs • Appreciate maximum likelihood methods and hypothesis testing • Be aware of selected molecular and population genetics principles, including Hardy-Weinberg Equilibrium • Grasp the basic concepts and principles underlying genetic linkage and association • Be able to perform analysis in heritability, linkage and association using selected software and critically evaluate and interpret the corresponding results Page 1 of 10 Additional Information 1. -
Genetic Epidemiology of Health Disparities in Allergy and Clinical Immunology
Molecular mechanisms in allergy and clinical immunology (Supported by an unrestricted educational grant from Genentech, Inc. and Novartis Pharmaceuticals Corporation) Series editors: William T. Shearer, MD, PhD, Lanny J. Rosenwasser, MD, and Bruce S. Bochner, MD Reviews and feature articles Genetic epidemiology of health disparities in allergy and clinical immunology Kathleen C. Barnes, PhD Baltimore, Md This activity is available for CME credit. See page 45A for important information. The striking racial and ethnic disparities in disease prevalence for common disorders, such as allergic asthma, cannot be Abbreviations used explained entirely by environmental, social, cultural, or CF: Cystic fibrosis economic factors, and genetic factors should not be ignored. CFTR: Cystic fibrosis transmembrane conductance Unfortunately, genetic studies in underserved minorities are regulator hampered by disagreements over the biologic construct of race CTLA4: Cytotoxic T lymphocyte–associated 4 and logistic issues, including admixture of different races and LD: Linkage disequilibrium ethnicities. Current observations suggest that the frequency NOS: Nitric oxide synthase of high-risk variants in candidate genes can differ between SNP: Single nucleotide polymorphism African Americans, Puerto Ricans, and Mexican Americans, and this might contribute to the differences in disease prevalence. Maintenance of certain allelic variants in the population over time might reflect selective pressures in influences (ie, gene-environment interactions). Con- previous generations. -
HIV Genotyping and Phenotyping AHS – M2093
Corporate Medical Policy HIV Genotyping and Phenotyping AHS – M2093 File Name: HIV_genotyping_and_phenotyping Origination: 1/2019 Last CAP Review: 2/2021 Next CAP Review: 2/2022 Last Review: 2/2021 Description of Procedure or Service Description Human immunodeficiency virus (HIV) is an RNA retrovirus that infects human immune cells (specifically CD4 cells) causing progressive deterioration of the immune system ultimately leading to acquired immune deficiency syndrome (AIDS) characterized by susceptibility to opportunistic infections and HIV-related cancers (CDC, 2014). Related Policies Plasma HIV-1 and HIV-2 RNA Quantification for HIV Infection Scientific Background Human immunodeficiency virus (HIV) targets the immune system, eventually hindering the body’s ability to fight infections and diseases. If not treated, an HIV infection may lead to acquired immunodeficiency syndrome (AIDS) which is a condition caused by the virus. There are two main types of HIV: HIV-1 and HIV-2; both are genetically different. HIV-1 is more common and widespread than HIV-2. HIV replicates rapidly; a replication cycle rate of approximately one to two days ensures that after a single year, the virus in an infected individual may be 200 to 300 generations removed from the initial infection-causing virus (Coffin & Swanstrom, 2013). This leads to great genetic diversity of each HIV infection in a single individual. As an RNA retrovirus, HIV requires the use of a reverse transcriptase for replication purposes. A reverse transcriptase is an enzyme which generates complimentary DNA from an RNA template. This enzyme is error-prone with the overall single-step point mutation rate reaching ∼3.4 × 10−5 mutations per base per replication cycle (Mansky & Temin, 1995), leading to approximately one genome in three containing a mutation after each round of replication (some of which confer drug resistance). -
Review of the Current State of Genetic Testing - a Living Resource
Review of the Current State of Genetic Testing - A Living Resource Prepared by Liza Gershony, DVM, PhD and Anita Oberbauer, PhD of the University of California, Davis Editorial input by Leigh Anne Clark, PhD of Clemson University July, 2020 Contents Introduction .................................................................................................................................................. 1 I. The Basics ......................................................................................................................................... 2 II. Modes of Inheritance ....................................................................................................................... 7 a. Mendelian Inheritance and Punnett Squares ................................................................................. 7 b. Non-Mendelian Inheritance ........................................................................................................... 10 III. Genetic Selection and Populations ................................................................................................ 13 IV. Dog Breeds as Populations ............................................................................................................. 15 V. Canine Genetic Tests ...................................................................................................................... 16 a. Direct and Indirect Tests ................................................................................................................ 17 b. Single