Meeting Report: “Metagenomics, Metadata and Meta-Analysis” (M3) Workshop at the Pacific Symposium on Biocomputing 2010
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Attitudes Towards Personal Genomics Among Older Swiss Adults: an Exploratory Study
Research Collection Journal Article Attitudes towards personal genomics among older Swiss adults: An exploratory study Author(s): Mählmann, Laura; Röcke, Christina; Brand, Angela; Hafen, Ernst; Vayena, Effy Publication Date: 2016 Permanent Link: https://doi.org/10.3929/ethz-b-000114241 Originally published in: Applied and Translational Genomics 8, http://doi.org/10.1016/j.atg.2016.01.009 Rights / License: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International This page was generated automatically upon download from the ETH Zurich Research Collection. For more information please consult the Terms of use. ETH Library Applied & Translational Genomics 8 (2016) 9–15 Contents lists available at ScienceDirect Applied & Translational Genomics journal homepage: www.elsevier.com/locate/atg Attitudes towards personal genomics among older Swiss adults: An exploratory study Laura Mählmann a,b, Christina Röcke c, Angela Brand b, Ernst Hafen a,EffyVayenad,⁎ a Institute of Molecular Systems Biology, ETH Zurich, Auguste-Piccard-Hof 1, 8093 Zürich, Switzerland b Institute for Public Health Genomics, Faculty of Health, Medicine and Life Sciences, Maastricht University, PO Box 616, 6200 MD Maastricht, The Netherlands c University Research Priority Program “Dynamics of Healthy Aging”, University of Zurich, Andreasstrasse 15/Box 2, 8050 Zurich, Switzerland d Health Ethics and Policy Lab, Institute of Epidemiology, Biostatistics and Prevention, University of Zurich, Hirschengraben 84, 8001 Zurich, Switzerland article info abstract Objectives: To explore attitudes of Swiss older adults towards personal genomics (PG). Keywords: Personal genomics Methods: Using an anonymized voluntary paper-and-pencil survey, data were collected from 151 men and Attitudes of older adults women aged 60–89 years attending the Seniorenuniversität Zurich, Switzerland (Seniors' University). -
In Human-Computer Interaction Published, Sold and Distributed By: Now Publishers Inc
Full text available at: http://dx.doi.org/10.1561/1100000067 Communicating Personal Genomic Information to Non-experts: A New Frontier for Human-Computer Interaction Orit Shaer Wellesley College, Wellesley, MA, USA [email protected] Oded Nov New York University, USA [email protected] Lauren Westendorf Wellesley College, Wellesley, MA, USA [email protected] Madeleine Ball Open Humans Foundation, Boston, MA, USA [email protected] Boston — Delft Full text available at: http://dx.doi.org/10.1561/1100000067 Foundations and Trends R in Human-Computer Interaction Published, sold and distributed by: now Publishers Inc. PO Box 1024 Hanover, MA 02339 United States Tel. +1-781-985-4510 www.nowpublishers.com [email protected] Outside North America: now Publishers Inc. PO Box 179 2600 AD Delft The Netherlands Tel. +31-6-51115274 The preferred citation for this publication is O. Shaer, O. Nov, L. Wstendorf, and M. Ball. Communicating Personal Genomic Information to Non-experts: A New Frontier for Human-Computer Interaction. Foundations and Trends R in Human-Computer Interaction, vol. 11, no. 1, pp. 1–62, 2017. R This Foundations and Trends issue was typeset in LATEX using a class file designed by Neal Parikh. Printed on acid-free paper. ISBN: 978-1-68083-254-9 c 2017 O. Shaer, O. Nov, L. Wstendorf, and M. Ball All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, mechanical, photocopying, recording or otherwise, without prior written permission of the publishers. Photocopying. In the USA: This journal is registered at the Copyright Clearance Cen- ter, Inc., 222 Rosewood Drive, Danvers, MA 01923. -
Multigenic Condition Risk Assessment in Direct-To-Consumer Genomic Services Melanie Swan, MBA
ARTICLE Multigenic condition risk assessment in direct-to-consumer genomic services Melanie Swan, MBA Purpose: Gene carrier status and pharmacogenomic data may be de- November 2009, cover 127, 46, and 28 conditions for $429, $985, tectable from single nucleotide polymorphisms (SNPs), but SNP-based and $999, respectively. These 3 services allow consumers to down- research concerning multigenic common disease such as diabetes, can- load their raw genotyping data, which can then be reviewed in 1 cers, and cardiovascular disease is an emerging field. The many SNPs other genome browsers such as the wiki-based SNPedia, where and loci that may relate to common disease have not yet been compre- there are 35 publicly available whole and partial human genomes hensively identified and understood scientifically. In the interim, direct- as of November 2009. Pathway Genomics and Gene Essence have to-consumer (DTC) genomic companies have forged ahead in develop- launched more recently, in mid-2009, and cover 71 and 84 condi- ing composite risk interpretations for multigenic conditions. It is useful tions for $299 and $1,195 respectively. SeqWright also provides a to understand how variance in risk interpretation may arise. Methods: basic service, genotyping 1 million SNPs for $998. 23andMe, A comprehensive study was conducted to analyze the 213 conditions deCODEme, and Pathway Genomics provide 2 services, health covered by the 5 identifiable genome-wide DTC genomic companies, and ancestry testing. Not a lot is known about the overall DTC and the total SNPs (401) and loci (224) assessed in the 20 common genomic testing market size; however, 23andMe reported having 2 disease conditions with the greatest overlapping coverage. -
Insights Into the Dynamics Between Viruses and Their Hosts in a Hot Spring Microbial Mat
The ISME Journal (2020) 14:2527–2541 https://doi.org/10.1038/s41396-020-0705-4 ARTICLE Insights into the dynamics between viruses and their hosts in a hot spring microbial mat 1,2,11 1,2 1,2 1,2 1,2 Jessica K. Jarett ● Mária Džunková ● Frederik Schulz ● Simon Roux ● David Paez-Espino ● 1,2 1,2 1,2 3 4 Emiley Eloe-Fadrosh ● Sean P. Jungbluth ● Natalia Ivanova ● John R. Spear ● Stephanie A. Carr ● 5 6 7 8,9 1,2 Christopher B. Trivedi ● Frank A. Corsetti ● Hope A. Johnson ● Eric Becraft ● Nikos Kyrpides ● 9 1,2,10 Ramunas Stepanauskas ● Tanja Woyke Received: 13 January 2020 / Revised: 3 June 2020 / Accepted: 11 June 2020 / Published online: 13 July 2020 © The Author(s) 2020. This article is published with open access Abstract Our current knowledge of host–virus interactions in biofilms is limited to computational predictions based on laboratory experiments with a small number of cultured bacteria. However, natural biofilms are diverse and chiefly composed of uncultured bacteria and archaea with no viral infection patterns and lifestyle predictions described to date. Herein, we predict the first DNA sequence-based host–virus interactions in a natural biofilm. Using single-cell genomics and metagenomics – 1234567890();,: 1234567890();,: applied to a hot spring mat of the Cone Pool in Mono County, California, we provide insights into virus host range, lifestyle and distribution across different mat layers. Thirty-four out of 130 single cells contained at least one viral contig (26%), which, together with the metagenome-assembled genomes, resulted in detection of 59 viruses linked to 34 host species. -
Personal Genomics for Bioinformaticians
Personal Genomics for Bioinformaticians Instructor: Melissa Gymrek Audience: UCSD grad students (Ph.D. and M.Sc. students) Objective: Given someone’s genome, what could you learn? (Students are encouraged to analyze their own 23&Me data). Student backgrounds: • Computer Science and Engineering • Electrical Engineering • Bioinformatics • Biomedical Sciences Modules: • Introduction to personal genomics • Ancestry • Complex traits • NGS • Mutation hunting Course Resources Course website: https://gymreklab.github.io/teaching/personal_genomics/personal_genomics_2017.html Syllabus: https://s3-us-west-2.amazonaws.com/cse291personalgenomics/genome_course_syllabus_winter17.pdf Materials for generating problem sets: https://github.com/gymreklab/personal-genomics-course-2017 Contact: [email protected] Bioinforma)cs/Genomics Courses @UCLA ¤ h"p://www.bioinformacs.ucla.edu/graduate-courses/ ¤ h"p://www.bioinformacs.ucla.edu/undergraduate-courses/ ¤ All courses require 1 year of programming, a probability course ¤ 3 courses are combined Graduate and Undergraduate Courses ¤ Undergraduate Courses enrollment are primarily students from Computer Science and Undergradaute Bioinformacs Minor (Mostly Life Science Students) ¤ Graduate Enrollment is mostly from Bioinformacs Ph.D. program, Gene0cs and Genomics Ph.D. program, CS Ph.D. Program. ¤ 3 courses are only Graduate Courses ¤ Enrollment is mostly Bioinformacs Ph.D. program and CS Ph.D. Program ¤ Courses are taught by faculty in Computer Science or Stas0cs (or have joint appointments there) Bioinforma)cs/Genomics Courses @UCLA ¤ CM221. Introduc0on to Bioinformacs ¤ Taught by Christopher Lee ¤ Focuses on Classical Bioinformacs Problems and Stas0cal Inference ¤ CM222. Algorithms in Bioinformacs ¤ Taught by Eleazar Eskin ¤ Focuses on Algorithms in Sequencing ¤ CM224. Computaonal Gene0cs ¤ Taught by Eran Halperin ¤ Focuses on Stas0cal Gene0cs and Machine Learning Methods ¤ CM225. Computaonal Methods in Genomics ¤ Taught by Jason Ernst and Bogdan Pasaniuc ¤ Has component of reading recent papers ¤ CM226. -
Personal Genomic Information Management and Personalized Medicine: Challenges, Current Solutions, and Roles of HIM Professionals
Personal Genomic Information Management and Personalized Medicine: Challenges, Current Solutions, and Roles of HIM Professionals Personal Genomic Information Management and Personalized Medicine: Challenges, Current Solutions, and Roles of HIM Professionals by Amal Alzu’bi, MS; Leming Zhou, PhD; and Valerie Watzlaf, PhD, RHIA, FAHIMA Abstract In recent years, the term personalized medicine has received more and more attention in the field of healthcare. The increasing use of this term is closely related to the astonishing advancement in DNA sequencing technologies and other high-throughput biotechnologies. A large amount of personal genomic data can be generated by these technologies in a short time. Consequently, the needs for managing, analyzing, and interpreting these personal genomic data to facilitate personalized care are escalated. In this article, we discuss the challenges for implementing genomics-based personalized medicine in healthcare, current solutions to these challenges, and the roles of health information management (HIM) professionals in genomics-based personalized medicine. Introduction Personalized medicine utilizes personal medical information to tailor strategies and medications for diagnosing and treating diseases in order to maintain people’s health.1 In this medical practice, physicians combine results from all available patient data (such as symptoms, traditional medical test results, medical history and family history, and certain personal genomic information) so that they can make accurate diagnoses and determine -
Genomics Education in the Era of Personal Genomics: Academic, Professional, and Public Considerations
International Journal of Molecular Sciences Review Genomics Education in the Era of Personal Genomics: Academic, Professional, and Public Considerations Kiara V. Whitley , Josie A. Tueller and K. Scott Weber * Department of Microbiology and Molecular Biology, 4007 Life Sciences Building, 701 East University Parkway, Brigham Young University, Provo, UT 84602, USA; [email protected] (K.V.W.); [email protected] (J.A.T.) * Correspondence: [email protected]; Tel.: +1-801-422-6259 Received: 31 December 2019; Accepted: 22 January 2020; Published: 24 January 2020 Abstract: Since the completion of the Human Genome Project in 2003, genomic sequencing has become a prominent tool used by diverse disciplines in modern science. In the past 20 years, the cost of genomic sequencing has decreased exponentially,making it affordable and accessible. Bioinformatic and biological studies have produced significant scientific breakthroughs using the wealth of genomic information now available. Alongside the scientific benefit of genomics, companies offer direct-to-consumer genetic testing which provide health, trait, and ancestry information to the public. A key area that must be addressed is education about what conclusions can be made from this genomic information and integrating genomic education with foundational genetic principles already taught in academic settings. The promise of personal genomics providing disease treatment is exciting, but many challenges remain to validate genomic predictions and diagnostic correlations. Ethical and societal concerns must also be addressed regarding how personal genomic information is used. This genomics revolution provides a powerful opportunity to educate students, clinicians, and the public on scientific and ethical issues in a personal way to increase learning. -
GSC Workshop 10 Grant Finances Monthly Teleconference Calls
Standards in Genomic Sciences (2010) 3:225-231 DOI:10.4056/sigs.1423520 Meeting Report from the Genomic Standards Consortium (GSC) Workshop 10 Elizabeth Glass1, Folker Meyer1,2, Jack A Gilbert1,3, Dawn Field4, Sarah Hunter5, Renzo Kottmann6, Nikos Kyrpides7, Susanna Sansone8, Lynn Schriml9, Peter Sterk10, Owen White9 and John Wooley11 1 Argonne National Laboratory, Argonne, IL USA 2 Computation Institute, University of Chicago, Chicago, IL USA 3 Department of Ecology and Evolution, University of Chicago, Chicago, IL USA, 4 Centre for Ecology & Hydrology, Oxfordshire, UK 5 European Molecular Biology Laboratory (EMBL) Outstation, European Bioinformatics Insti- tute (EBI), Hinxton, Cambridge UK 6 Microbial Genomics Group, Max Planck Institute for Marine Microbiology and Jacobs University Bremen, Bremen, Germany 7 DOE Joint Genome Institute, Walnut Creek, CA, USA 8 University of Oxford, Oxford e-Research Centre, Oxford, UK 9 Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, MD USA 10 Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge UK 11 University of California San Diego, La Jolla, CA USA *Corresponding Author: Dawn Field This report summarizes the proceedings of the 10th workshop of the Genomic Standards Consortium (GSC), held at Argonne National Laboratory, IL, USA. It was the second GSC workshop to have open registration and attracted over 60 participants who worked together to progress the full range of projects ongoing within the GSC. Overall, the primary focus of the workshop was on advancing the M5 platform for next-generation collaborative computa- tional infrastructures. Other key outcomes included the formation of a GSC working group focused on MIGS/MIMS/MIENS compliance using the ISA software suite and the formal launch of the GSC Developer Working Group. -
The Minimum Information About a Genome Sequence (MIGS) Specification
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln US Department of Energy Publications U.S. Department of Energy 2008 The minimum information about a genome sequence (MIGS) specification Dawn Field Natural Environmental Research Council Centre for Ecology and Hydrology, [email protected] George Garrity Michigan State University Tanya Gray Natural Environmental Research Council Centre for Ecology and Hydrology Norman Morrison FUnivollowersity this of and Manchester additional works at: https://digitalcommons.unl.edu/usdoepub Jer emyPart ofSelengut the Bior esource and Agricultural Engineering Commons J. Craig Venter Institute SeeField, next Dawn; page Garrity for additional, George; Grauthorsay, Tany a; Morrison, Norman; Selengut, Jeremy; Sterk, Peter; Tatusova, Tatiana; Thomson, Nicholas; Allen, Michael J.; Angiuoli, Samuel V.; Ashburner, Michael; Axelrod, Nelson; Baldauf, Sandra; Ballard, Stuart; Boore, Jeffrey; Cochrane, Guy; Cole, James; Dawyndt, Peter; De Vos, Paul; dePamphilis, Claude; Edwards, Robert; Faruque, Nadeem; Feldman, Robert; Gilbert, Jack; Gilna, Paul; Glöckner, Frank Oliver; Goldstein, Philip; Guralnick, Robert; Haft, Dan; Hancock, David; Hermjakob, Henning; Hertz-Fowler, Christiane; Hugenholtz, Phil; Joint, Ian; Kagan, Leonid; Kane, Matthew; Kennedy, Jessie; Kowalchuk, George; Kottmann, Renzo; Kolker, Eugene; Kravitz, Saul; Kyrpides, Nikos; Leebens-Mack, Jim; Lewis, Suzanna E.; Li, Kelvin; Lister, Allyson L.; Lord, Phillip; Maltsev, Natalia; Markowitz, Victor; Martiny, Jennifer; Methe, Barbara; Mizrachi, Ilene; Moxon, Richard; Nelson, Karen; Parkhill, Julian; Proctor, Lita; White, Owen; Sansone, Susanna-Assunta; Spiers, Andrew; Stevens, Robert; Swift, Paul; Taylor, Chris; Tateno, Yoshio; Tett, Adrian; Turner, Sarah; Ussery, David; Vaughan, Bob; Ward, Naomi; Whetzel, Trish; San Gil, Ingio; Wilson, Gareth; and Wipat, Anil, "The minimum information about a genome sequence (MIGS) specification" (2008). US Department of Energy Publications. -
Personal Genomics Wynn K Meyer, Phd Bioscience in the 21St Century Lehigh University November 18, 2019 Draw Your Genome
Personal Genomics Wynn K Meyer, PhD Bioscience in the 21st Century Lehigh University November 18, 2019 Draw your genome. On your drawing, please label: • The region(s) that can help you figure out where your ancestors lived. • The region(s) that determine whether you will fall asleep in this class. • The region(s) that determine your eye color. • The region(s) that determine your skin color. • The region(s) that contribute to your risk of cancer. Guessing is fine! What does your drawing look like? Public domain photo / NASA] Courtesy: National Human Genome Research Institute [Public domain] If things were simple: Heart disease Eye color Skin color Cancer Stroke Diabetes Arthritis Courtesy: National Human Genome Research Institute [Public domain] Why not? How do we link phenotypes with the genetic variants that underlie them? Arthritis Heart disease Cancer Skin color Diabetes Stroke Eye color What are genetic variants? The term “allele” can refer either Zoom WAY in… to the nucleotide at the SNP Allele 1 (A/G or T/A) … …TTGACCCGTTATTG… or to the combination across both SNPs (AT/GA). …TTGGCCCGTTATAG… Allele 2 Either way, it represents one “version” of the sequence. Single Nucleotide Polymorphisms The combination of alleles that a (SNPs) person has at a SNP is called a genotype. What process generates SNPs? E.g., for SNP1: AA, AG, and GG. What do genetic variants do? Mostly nothing! From the 1000 Genomes Project Consortium (Nature 2015): • We find that a typical genome differs from Why? the reference human genome at 4.1 million to 5.0 million sites (out of 3.2 billion). -
Personal Genomes and Ethical Issues
Personal Genomes and Ethical Issues 02-223 How to Analyze Your Own Genome Declining Cost of Genome Sequencing • The genome sequencing is expected to happen rouAnely in the near future Schadt, MSB, 2012 The era of big data: the genome data are already being collected in a large scale and being mined for scienAfic discovery to drive more accurate descripAve and predicAve models that inform decision making for the best diagnosis and treatment choice for a given paent. Would you post your genome on the web? Genomes and Privacy • DNA sequence data contain informaon that can be used to uniquely idenAfy an individual (i.e., genome sequences are like fingerprints) • Balancing the need for scienAfic study and privacy Genomes and Privacy • Privacy concerns – Genome sequence data and other related types of data (gene expressions, clinical records, epigeneAc data, etc.) are collected for a large number of paents for medical research – Most types of data are freely available through internet except for genotype data • NCBI GEO database for gene expression data • The cancer genome atlas data portals – Genotype data are available to scienAsts through restricted access – ProtecAng parAcipants’ privacy through informed consent hWps://tcga-data.nci.nih.gov/tcga/tcgaHome2.jsp The Cancer Genome Atlas (TCGA) Data The Cancer Genome Atlas (TCGA) Data hWps://tcga-data.nci.nih.gov/tcga/tcgaCancerDetails.jsp? diseaseType=LAML&diseaseName=Acute%20Myeloid%20Leukemia Access Control for TCGA Data • Open access data Aer – De-idenAfied clinical and demographic data – Gene -
The ELSI Advisory Board GP-Write/ the Center of Excellence For
! The ELSI Advisory Board GP-write/ The Center of Excellence for Engineering Biology Background Information on GP-write, with ELSI dimensions The Genome Project-write (GP-write) is an open, international research project led by a multi- disciplinary group of scientific leaders who will oversee a reduction in the costs of engineering and testing large genomes, including a human genome, in cell lines by over 1,000-fold within ten years. The overarching goal of such an effort is to further our understanding of the blueprint for life provided by the Human Genome Project (HGP-read) by developing new technologies and an ethical framework for genome-scale engineering, as well as transformative medical applications. GP-write will include whole genome engineering of human cell lines and other organisms of significance to research and development, agriculture, and public health, as well as organoids derived from human cells. A coordinated scientific effort to understand, discuss, and apply large genome editing technologies is timely, and public discourse regarding such an endeavor is both expected and encouraged as GP-write gets underway. However, responsible innovation requires having more than ELSI discussions; it also involves identifying common goals important to scientists and the public through timely and detailed consultation among diverse stakeholders. The GP-write effort is aimed at technology development and knowledge creation, with the ultimate goal of improving life on Earth. Potential innovations relate to biomedical therapies, food supply management, biofuels, and public health. However, as with many other technology development initiatives, there is potential for misuse, and some risks may be unforeseen.