Genomics and Bioinformatics As Pillars of Precision Medicine in Oncology
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Integrative Analysis of Exogenous, Endogenous, Tumour and Immune
Gut Online First, published on February 6, 2018 as 10.1136/gutjnl-2017-315537 Recent advances in basic science Integrative analysis of exogenous, endogenous, Gut: first published as 10.1136/gutjnl-2017-315537 on 6 February 2018. Downloaded from tumour and immune factors for precision medicine Shuji Ogino,1,2,3,4 Jonathan A Nowak,1 Tsuyoshi Hamada,2 Amanda I Phipps,5,6 Ulrike Peters,5,6 Danny A Milner Jr,7 Edward L Giovannucci,3,8,9 Reiko Nishihara,1,3,4,8,10 Marios Giannakis,4,11,12 Wendy S Garrett,4,11,13 Mingyang Song8,14,15 For numbered affiliations see ABSTRACT including inflammatory and immune cells. A fraction end of article. Immunotherapy strategies targeting immune checkpoints of somatic mutations may result in the generation of such as the CTLA4 and CD274 (programmed cell death new antigens (neoantigens) that can be recognised as Correspondence to 1 ligand 1, PD-L1)/PDCD1 (programmed cell death 1, non-self by the immune system. During an individu- Dr Shuji Ogino, Program in MPE Molecular Pathological PD-1) T-cell coreceptor pathways are revolutionising al's life-course, cells may acquire somatic molecular Epidemiology, Brigham and oncology. The approval of pembrolizumab use for alterations, and some of these cells undergo clonal Women’s Hospital, Boston, MA solid tumours with high-level microsatellite instability expansion, displaying hallmarks of early neoplasia. 02215, USA; shuji_ ogino@ dfci. or mismatch repair deficiency by the US Food and Many of these cells are likely kept in check or killed harvard. edu Drug Administration highlights promise of precision by the host immune system before they can develop Received 24 October 2017 immuno-oncology. -
13 Genomics and Bioinformatics
Enderle / Introduction to Biomedical Engineering 2nd ed. Final Proof 5.2.2005 11:58am page 799 13 GENOMICS AND BIOINFORMATICS Spencer Muse, PhD Chapter Contents 13.1 Introduction 13.1.1 The Central Dogma: DNA to RNA to Protein 13.2 Core Laboratory Technologies 13.2.1 Gene Sequencing 13.2.2 Whole Genome Sequencing 13.2.3 Gene Expression 13.2.4 Polymorphisms 13.3 Core Bioinformatics Technologies 13.3.1 Genomics Databases 13.3.2 Sequence Alignment 13.3.3 Database Searching 13.3.4 Hidden Markov Models 13.3.5 Gene Prediction 13.3.6 Functional Annotation 13.3.7 Identifying Differentially Expressed Genes 13.3.8 Clustering Genes with Shared Expression Patterns 13.4 Conclusion Exercises Suggested Reading At the conclusion of this chapter, the reader will be able to: & Discuss the basic principles of molecular biology regarding genome science. & Describe the major types of data involved in genome projects, including technologies for collecting them. 799 Enderle / Introduction to Biomedical Engineering 2nd ed. Final Proof 5.2.2005 11:58am page 800 800 CHAPTER 13 GENOMICS AND BIOINFORMATICS & Describe practical applications and uses of genomic data. & Understand the major topics in the field of bioinformatics and DNA sequence analysis. & Use key bioinformatics databases and web resources. 13.1 INTRODUCTION In April 2003, sequencing of all three billion nucleotides in the human genome was declared complete. This landmark of modern science brought with it high hopes for the understanding and treatment of human genetic disorders. There is plenty of evidence to suggest that the hopes will become reality—1631 human genetic diseases are now associated with known DNA sequences, compared to the less than 100 that were known at the initiation of the Human Genome Project (HGP) in 1990. -
Genomics and Its Impact on Science and Society: the Human Genome Project and Beyond
DOE/SC-0083 Genomics and Its Impact on Science and Society The Human Genome Project and Beyond U.S. Department of Energy Genome Research Programs: genomics.energy.gov A Primer ells are the fundamental working units of every living system. All the instructions Cneeded to direct their activities are contained within the chemical DNA (deoxyribonucleic acid). DNA from all organisms is made up of the same chemical and physical components. The DNA sequence is the particular side-by-side arrangement of bases along the DNA strand (e.g., ATTCCGGA). This order spells out the exact instruc- tions required to create a particular organism with protein complex its own unique traits. The genome is an organism’s complete set of DNA. Genomes vary widely in size: The smallest known genome for a free-living organism (a bac- terium) contains about 600,000 DNA base pairs, while human and mouse genomes have some From Genes to Proteins 3 billion (see p. 3). Except for mature red blood cells, all human cells contain a complete genome. Although genes get a lot of attention, the proteins DNA in each human cell is packaged into 46 chro- perform most life functions and even comprise the mosomes arranged into 23 pairs. Each chromosome is majority of cellular structures. Proteins are large, complex a physically separate molecule of DNA that ranges in molecules made up of chains of small chemical com- length from about 50 million to 250 million base pairs. pounds called amino acids. Chemical properties that A few types of major chromosomal abnormalities, distinguish the 20 different amino acids cause the including missing or extra copies or gross breaks and protein chains to fold up into specific three-dimensional rejoinings (translocations), can be detected by micro- structures that define their particular functions in the cell. -
Genetic Effects on Microsatellite Diversity in Wild Emmer Wheat (Triticum Dicoccoides) at the Yehudiyya Microsite, Israel
Heredity (2003) 90, 150–156 & 2003 Nature Publishing Group All rights reserved 0018-067X/03 $25.00 www.nature.com/hdy Genetic effects on microsatellite diversity in wild emmer wheat (Triticum dicoccoides) at the Yehudiyya microsite, Israel Y-C Li1,3, T Fahima1,MSRo¨der2, VM Kirzhner1, A Beiles1, AB Korol1 and E Nevo1 1Institute of Evolution, University of Haifa, Mount Carmel, Haifa 31905, Israel; 2Institute for Plant Genetics and Crop Plant Research, Corrensstrasse 3, 06466 Gatersleben, Germany This study investigated allele size constraints and clustering, diversity. Genome B appeared to have a larger average and genetic effects on microsatellite (simple sequence repeat number (ARN), but lower variance in repeat number 2 repeat, SSR) diversity at 28 loci comprising seven types of (sARN), and smaller number of alleles per locus than genome tandem repeated dinucleotide motifs in a natural population A. SSRs with compound motifs showed larger ARN than of wild emmer wheat, Triticum dicoccoides, from a shade vs those with perfect motifs. The effects of replication slippage sun microsite in Yehudiyya, northeast of the Sea of Galilee, and recombinational effects (eg, unequal crossing over) on Israel. It was found that allele distribution at SSR loci is SSR diversity varied with SSR motifs. Ecological stresses clustered and constrained with lower or higher boundary. (sun vs shade) may affect mutational mechanisms, influen- This may imply that SSR have functional significance and cing the level of SSR diversity by both processes. natural constraints. -
Gene Prediction and Genome Annotation
A Crash Course in Gene and Genome Annotation Lieven Sterck, Bioinformatics & Systems Biology VIB-UGent [email protected] ProCoGen Dissemination Workshop, Riga, 5 nov 2013 “Conifer sequencing: basic concepts in conifer genomics” “This Project is financially supported by the European Commission under the 7th Framework Programme” Genome annotation: finding the biological relevant features on a raw genomic sequence (in a high throughput manner) ProCoGen Dissemination Workshop, Riga, 5 nov 2013 Thx to: BSB - annotation team • Lieven Sterck (Ectocarpus, higher plants, conifers, … ) • Yao-cheng Lin (Fungi, conifers, …) • Stephane Rombauts (green alga, mites, …) • Bram Verhelst (green algae) • Pierre Rouzé • Yves Van de Peer ProCoGen Dissemination Workshop, Riga, 5 nov 2013 Annotation experience • Plant genomes : A.thaliana & relatives (e.g. A.lyrata), Poplar, Physcomitrella patens, Medicago, Tomato, Vitis, Apple, Eucalyptus, Zostera, Spruce, Oak, Orchids … • Fungal genomes: Laccaria bicolor, Melampsora laricis- populina, Heterobasidion, other basidiomycetes, Glomus intraradices, Pichia pastoris, Geotrichum Candidum, Candida ... • Algal genomes: Ostreococcus spp, Micromonas, Bathycoccus, Phaeodactylum (and other diatoms), E.hux, Ectocarpus, Amoebophrya … • Animal genomes: Tetranychus urticae, Brevipalpus spp (mites), ... ProCoGen Dissemination Workshop, Riga, 5 nov 2013 Why genome annotation? • Raw sequence data is not useful for most biologists • To be meaningful to them it has to be converted into biological significant knowledge -
A Call for Public Archives for Biological Image Data Public Data Archives Are the Backbone of Modern Biological Research
comment A call for public archives for biological image data Public data archives are the backbone of modern biological research. Biomolecular archives are well established, but bioimaging resources lag behind them. The technology required for imaging archives is now available, thus enabling the creation of the frst public bioimage datasets. We present the rationale for the construction of bioimage archives and their associated databases to underpin the next revolution in bioinformatics discovery. Jan Ellenberg, Jason R. Swedlow, Mary Barlow, Charles E. Cook, Ugis Sarkans, Ardan Patwardhan, Alvis Brazma and Ewan Birney ince the mid-1970s it has been possible image data to encourage both reuse and in automation and throughput allow this to analyze the molecular composition extraction of knowledge. to be done in a systematic manner. We Sof living organisms, from the individual Despite the long history of biological expect that, for example, super-resolution units (nucleotides, amino acids, and imaging, the tools and resources for imaging will be applied across biological metabolites) to the macromolecules they collecting, managing, and sharing image and biomedical imaging; examples in are part of (DNA, RNA, and proteins), data are immature compared with those multidimensional imaging8 and high- as well as the interactions among available for sequence and 3D structure content screening9 have recently been these components1–3. The cost of such data. In the following sections we reported. It is very likely that imaging data measurements has decreased remarkably outline the current barriers to progress, volume and complexity will continue to over time, and technological development the technological developments that grow. Second, the emergence of powerful has widened their scope from investigations could provide solutions, and how those computer-based approaches for image of gene and transcript sequences (genomics/ infrastructure solutions can meet the interpretation, quantification, and modeling transcriptomics) to proteins (proteomics) outlined need. -
Small Variants Frequently Asked Questions (FAQ) Updated September 2011
Small Variants Frequently Asked Questions (FAQ) Updated September 2011 Summary Information for each Genome .......................................................................................................... 3 How does Complete Genomics map reads and call variations? ........................................................................... 3 How do I assess the quality of a genome produced by Complete Genomics?................................................ 4 What is the difference between “Gross mapping yield” and “Both arms mapped yield” in the summary file? ............................................................................................................................................................................. 5 What are the definitions for Fully Called, Partially Called, Half-Called and No-Called?............................ 5 In the summary-[ASM-ID].tsv file, how is the number of homozygous SNPs calculated? ......................... 5 In the summary-[ASM-ID].tsv file, how is the number of heterozygous SNPs calculated? ....................... 5 In the summary-[ASM-ID].tsv file, how is the total number of SNPs calculated? .......................................... 5 In the summary-[ASM-ID].tsv file, what regions of the genome are included in the “exome”? .............. 6 In the summary-[ASM-ID].tsv file, how is the number of SNPs in the exome calculated? ......................... 6 In the summary-[ASM-ID].tsv file, how are variations in potentially redundant regions of the genome counted? ..................................................................................................................................................................... -
3 on the Nature of Biological Data
ON THE NATURE OF BIOLOGICAL DATA 35 3 On the Nature of Biological Data Twenty-first century biology will be a data-intensive enterprise. Laboratory data will continue to underpin biology’s tradition of being empirical and descriptive. In addition, they will provide confirming or disconfirming evidence for the various theories and models of biological phenomena that researchers build. Also, because 21st century biology will be a collective effort, it is critical that data be widely shareable and interoperable among diverse laboratories and computer systems. This chapter describes the nature of biological data and the requirements that scientists place on data so that they are useful. 3.1 DATA HETEROGENEITY An immense challenge—one of the most central facing 21st century biology—is that of managing the variety and complexity of data types, the hierarchy of biology, and the inevitable need to acquire data by a wide variety of modalities. Biological data come in many types. For instance, biological data may consist of the following:1 • Sequences. Sequence data, such as those associated with the DNA of various species, have grown enormously with the development of automated sequencing technology. In addition to the human genome, a variety of other genomes have been collected, covering organisms including bacteria, yeast, chicken, fruit flies, and mice.2 Other projects seek to characterize the genomes of all of the organisms living in a given ecosystem even without knowing all of them beforehand.3 Sequence data generally 1This discussion of data types draws heavily on H.V. Jagadish and F. Olken, eds., Data Management for the Biosciences, Report of the NSF/NLM Workshop of Data Management for Molecular and Cell Biology, February 2-3, 2003, Available at http:// www.eecs.umich.edu/~jag/wdmbio/wdmb_rpt.pdf. -
The Future of Precision Medicine : Potential Impacts for Health Technology Assessment
This is a repository copy of The Future of Precision Medicine : Potential Impacts for Health Technology Assessment. White Rose Research Online URL for this paper: https://eprints.whiterose.ac.uk/133069/ Version: Accepted Version Article: Love-Koh, James orcid.org/0000-0001-9009-5346, Peel, Alison, Rejon-Parilla, Juan Carlos et al. (6 more authors) (2018) The Future of Precision Medicine : Potential Impacts for Health Technology Assessment. Pharmacoeconomics. pp. 1439-1451. ISSN 1179-2027 https://doi.org/10.1007/s40273-018-0686-6 Reuse This article is distributed under the terms of the Creative Commons Attribution-NonCommercial (CC BY-NC) licence. This licence allows you to remix, tweak, and build upon this work non-commercially, and any new works must also acknowledge the authors and be non-commercial. You don’t have to license any derivative works on the same terms. More information and the full terms of the licence here: https://creativecommons.org/licenses/ Takedown If you consider content in White Rose Research Online to be in breach of UK law, please notify us by emailing [email protected] including the URL of the record and the reason for the withdrawal request. [email protected] https://eprints.whiterose.ac.uk/ The Future of Precision Medicine: Potential Impacts for Health Technology Assessment Title: The Future of Precision Medicine: Potential Impacts for Health Technology Assessment Authors: James Love-Koh1,2, Alison Peel1, Juan Carlos Rejon-Parilla3, Kate Ennis1,4, Rosemary Lovett3, Andrea Manca2,5, Anastasia Chalkidou6, Hannah Wood1, Matthew Taylor1 1 YorK Health Economics Consortium 2 Centre for Health Economics, University of YorK 3 National Institute for Health and Care Excellence 4 Institute of Infection and Global Health, University of Liverpool 5 Luxembourg Institute of Health 6 Kings Technology Evaluation Centre Corresponding Author Details: Name: James Love-Koh Address: Centre for Health Economics, Alcuin A Block, University of York, Heslington, York, YO10 5DD, UK. -
Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine
biomolecules Review Epigenetics Analysis and Integrated Analysis of Multiomics Data, Including Epigenetic Data, Using Artificial Intelligence in the Era of Precision Medicine Ryuji Hamamoto 1,2,*, Masaaki Komatsu 1,2, Ken Takasawa 1,2 , Ken Asada 1,2 and Syuzo Kaneko 1 1 Division of Molecular Modification and Cancer Biology, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuo-ku, Tokyo 104-0045, Japan; [email protected] (M.K.); [email protected] (K.T.); [email protected] (K.A.); [email protected] (S.K.) 2 Cancer Translational Research Team, RIKEN Center for Advanced Intelligence Project, 1-4-1 Nihonbashi, Chuo-ku, Tokyo 103-0027, Japan * Correspondence: [email protected]; Tel.: +81-3-3547-5271 Received: 1 December 2019; Accepted: 27 December 2019; Published: 30 December 2019 Abstract: To clarify the mechanisms of diseases, such as cancer, studies analyzing genetic mutations have been actively conducted for a long time, and a large number of achievements have already been reported. Indeed, genomic medicine is considered the core discipline of precision medicine, and currently, the clinical application of cutting-edge genomic medicine aimed at improving the prevention, diagnosis and treatment of a wide range of diseases is promoted. However, although the Human Genome Project was completed in 2003 and large-scale genetic analyses have since been accomplished worldwide with the development of next-generation sequencing (NGS), explaining the mechanism of disease onset only using genetic variation has been recognized as difficult. Meanwhile, the importance of epigenetics, which describes inheritance by mechanisms other than the genomic DNA sequence, has recently attracted attention, and, in particular, many studies have reported the involvement of epigenetic deregulation in human cancer. -
Visualization of Biomedical Data
Visualization of Biomedical Data Corresponding author: Seán I. O’Donoghue; email: [email protected] • Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Eveleigh NSW 2015, Australia • Genomics and Epigenetics Division, Garvan Institute of Medical Research, Sydney NSW 2010, Australia • School of Biotechnology and Biomolecular Sciences, UNSW, Kensington NSW 2033, Australia Benedetta Frida Baldi; email: [email protected] • Genomics and Epigenetics Division, Garvan Institute of Medical Research, Sydney NSW 2010, Australia Susan J Clark; email: [email protected] • Genomics and Epigenetics Division, Garvan Institute of Medical Research, Sydney NSW 2010, Australia Aaron E. Darling; email: [email protected] • The ithree institute, University of Technology Sydney, Ultimo NSW 2007, Australia James M. Hogan; email: [email protected] • School of Electrical Engineering and Computer Science, Queensland University of Technology, Brisbane QLD, 4000, Australia Sandeep Kaur; email: [email protected] • School of Computer Science and Engineering, UNSW, Kensington NSW 2033, Australia Lena Maier-Hein; email: [email protected] • Div. Computer Assisted Medical Interventions (CAMI), German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany Davis J. McCarthy; email: [email protected] • European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, CB10 1SD, Hinxton, Cambridge, UK • St. Vincent’s Institute of Medical Research, Fitzroy VIC 3065, Australia William -
The Economic Impact and Functional Applications of Human Genetics and Genomics
The Economic Impact and Functional Applications of Human Genetics and Genomics Commissioned by the American Society of Human Genetics Produced by TEConomy Partners, LLC. Report Authors: Simon Tripp and Martin Grueber May 2021 TEConomy Partners, LLC (TEConomy) endeavors at all times to produce work of the highest quality, consistent with our contract commitments. However, because of the research and/or experimental nature of this work, the client undertakes the sole responsibility for the consequence of any use or misuse of, or inability to use, any information or result obtained from TEConomy, and TEConomy, its partners, or employees have no legal liability for the accuracy, adequacy, or efficacy thereof. Acknowledgements ASHG and the project authors wish to thank the following organizations for their generous support of this study. Invitae Corporation, San Francisco, CA Regeneron Pharmaceuticals, Inc., Tarrytown, NY The project authors express their sincere appreciation to the following indi- viduals who provided their advice and input to this project. ASHG Government and Public Advocacy Committee Lynn B. Jorde, PhD ASHG Government and Public Advocacy Committee (GPAC) Chair, President (2011) Professor and Chair of Human Genetics George and Dolores Eccles Institute of Human Genetics University of Utah School of Medicine Katrina Goddard, PhD ASHG GPAC Incoming Chair, Board of Directors (2018-2020) Distinguished Investigator, Associate Director, Science Programs Kaiser Permanente Northwest Melinda Aldrich, PhD, MPH Associate Professor, Department of Medicine, Division of Genetic Medicine Vanderbilt University Medical Center Wendy Chung, MD, PhD Professor of Pediatrics in Medicine and Director, Clinical Cancer Genetics Columbia University Mira Irons, MD Chief Health and Science Officer American Medical Association Peng Jin, PhD Professor and Chair, Department of Human Genetics Emory University Allison McCague, PhD Science Policy Analyst, Policy and Program Analysis Branch National Human Genome Research Institute Rebecca Meyer-Schuman, MS Human Genetics Ph.D.