Next Generation Sequencing for SARS-Cov-2
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DNA Sequencing
1 DNA Sequencing Description of Module Subject Name Paper Name Module Name/Title DNA Sequencing Dr. Vijaya Khader Dr. MC Varadaraj 2 DNA Sequencing 1. Objectives 1. DNA sequencing Introduction 2. Types of methods available 3. Next generation sequencing 2. Lay Out 3 DNA Sequencing Sequencing Maxam Gilbert Sanger's Next generation 3 Introduction 4 DNA Sequencing In the mid 1970s when molecular cloning techniques in general were rapidly improving, simple methods were also developed to determine the nucleotide sequence of DNA. These advances laid the foundation for the detailed analysis of the structure and function of the large number of genes. Other fields which utilize DNA sequencing include diagnostic and forensic biology. With the invention of DNA sequencing, research and discovery of new genes is increased many folds. Using this technique whole genomes of many animal (human), plant, and microbial genomes have been sequenced. The first attempts to sequence DNA mirrored techniques developed in 1960s to sequence RNA. These involved : a) Specific cleavage to the DNA in to smaller fragments by enzymatic digestion or chemical digestion b) Nearest neighbour analysis c) Wandering spot method. Indeed in some studies the DNA was transcribed in to RNA with E.coli RNA polymerase and then sequenced as RNA So there were several questions unanswered; How many base pairs (bp) are there in a human genome?( ~3 billion (haploid)) How much did it cost to sequence the first human genome? ~$2.7 billion How long did it take to sequence the first human genome?( ~13 years) When was the first human genome sequence complete? (2000-2003) Goal figuring the order of nucleotides across a genome Problem Current DNA sequencing methods can handle only short stretches of DNA at once (<1-2Kbp) Solution 5 DNA Sequencing Sequence and then use computers to assemble the small pieces 3.1 Maxam-Gilbert sequencing Also known as chemical sequencing, here there is use radioactive labeling at one 5' end of the DNA fragment which is to be sequenced. -
BGI at a Glance EN20190626
AT A GLANCE BACKGROUND The Human Genome Project (HGP) is considered one of the greatest scientific achievements of the last century. BGI was founded in 1999 in order to participate in this significant research project. Since then, BGI has become a world-leading life science organization. SERVICES BGI leads innovative development in genom- ics and life sciences through its integrated model incorporating industry development, ed- ucation and research in compliance with inter- national bioethical protocols, and applies fron- tier multi-omics research findings to areas in- cluding medicine, healthcare, resource con- servation, forensics and more; and provides cutting-edge proprietary life science instruments and devices, technical support and solutions to accelerate industry transfer of genomic technologies and revolu- tionize current healthcare system towards precision medicine and precision healthcare, using "omics" to benefit the mankind. CORE CAPABILITIES Research BGI·Research 24 2200+ 1200+ Innovation Centers SCI Publications Patent Applications (including 1 national and 7 provincial) Sequencing Services BGI·Genomics Reproductive Health Cancer Prevention Infectious Diseases and Treatment Advanced Tools in Life Sciences MGI Fully automated scale data production Oct. 2018: launched the ultra-high-throughput sequencer MGISEQ-T7 and the high-throughput automated sample preparation system MGISP-960 Oct. 2017: launched high-throughput genetic sequencers MGISEQ-2000 and MGISEQ-200, MGIFLP modular NGS workstation,and MGI- US-R3 robotic ultrasound system Nov. 2016: launched the BGISEQ-50 desktop sequencing system Oct. 2015: launched the BGISEQ-500 high-throughput desktop sequencing system Jun. 2015: launched the RevolocityTM sequencing system Jul. 2014: launched the BGISEQ-1000 sequencing system Mar. 2013: successful acquisition of a U.S. -
DNA Sequencing - I
SUBJECT FORENSIC SCIENCE Paper No. and Title PAPER No.13: DNA Forensics Module No. and Title MODULE No.21: DNA Sequencing - I Module Tag FSC_P13_M21 FORENSIC SCIENCE PAPER No.13: DNA Forensics MODULE No.21: DNA Sequencing - I TABLE OF CONTENTS 1. Learning Outcomes 2. Introduction 3. First Generation Sequencing Methods 4. Second Generation Sequencing Techniques 5. Third Generation Sequencing – emerging technologies 6. DNA Sequence analysis 7. Summary FORENSIC SCIENCE PAPER No.13: DNA Forensics MODULE No.21: DNA Sequencing - I 1. Learning Outcomes After studying this module, reader shall be able to understand - DNA Sequencing Methods of DNA Sequencing DNA sequence analysis 2. Introduction In 1953, James Watson and Francis Crick discovered double-helix model of DNA, based on crystallized X-ray structures studied by Rosalind Franklin. As per this model, DNA comprises of two strands of nucleotides coiled around each other, allied by hydrogen bonds and moving in opposite directions. Each strand is composed of four complementary nucleotides – adenine (A), cytosine (C), guanine (G) and thymine (T) – with A always paired with T and C always paired with G with 2 & 3 hydrogen bonds respectively. The sequence of the bases (A,T,G,C) along DNA contains the complete set of instructions that make up the genetic inheritance. Defining the arrangement of these nucleotide bases in DNA strand is a primary step in assessing regulatory sequences, coding and non-coding regions. The term DNA sequencing denotes to methods for identifying the sequence of these nucleotides bases in a molecule of DNA. The basis for sequencing proteins was initially placed by the effort of Fred Sanger who by 1955 had accomplished the arrangement of all the amino acids in insulin, a small protein produced by the pancreas. -
Computational and Experimental Approaches for Evaluating the Genetic Basis of Mitochondrial Disorders
Computational and Experimental Approaches For Evaluating the Genetic Basis of Mitochondrial Disorders The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters Citation Lieber, Daniel Solomon. 2013. Computational and Experimental Approaches For Evaluating the Genetic Basis of Mitochondrial Disorders. Doctoral dissertation, Harvard University. Citable link http://nrs.harvard.edu/urn-3:HUL.InstRepos:11158264 Terms of Use This article was downloaded from Harvard University’s DASH repository, and is made available under the terms and conditions applicable to Other Posted Material, as set forth at http:// nrs.harvard.edu/urn-3:HUL.InstRepos:dash.current.terms-of- use#LAA Computational and Experimental Approaches For Evaluating the Genetic Basis of Mitochondrial Disorders A dissertation presented by Daniel Solomon Lieber to The Committee on Higher Degrees in Systems Biology in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the subject of Systems Biology Harvard University Cambridge, Massachusetts April 2013 © 2013 - Daniel Solomon Lieber All rights reserved. Dissertation Adviser: Professor Vamsi K. Mootha Daniel Solomon Lieber Computational and Experimental Approaches For Evaluating the Genetic Basis of Mitochondrial Disorders Abstract Mitochondria are responsible for some of the cell’s most fundamental biological pathways and metabolic processes, including aerobic ATP production by the mitochondrial respiratory chain. In humans, mitochondrial dysfunction can lead to severe disorders of energy metabolism, which are collectively referred to as mitochondrial disorders and affect approximately 1:5,000 individuals. These disorders are clinically heterogeneous and can affect multiple organ systems, often within a single individual. Symptoms can include myopathy, exercise intolerance, hearing loss, blindness, stroke, seizures, diabetes, and GI dysmotility. -
Plos Biology
PLOS BIOLOGY RESEARCH ARTICLE A network medicine approach to investigation and population-based validation of disease manifestations and drug repurposing for COVID-19 Yadi Zhou1☯, Yuan Hou1☯, Jiayu Shen1, Reena Mehra2,3, Asha Kallianpur1,2, Daniel A. Culver4,5, Michaela U. Gack6, Samar Farha4,5, Joe Zein2,4, Suzy Comhair2,4, 2,4 2,4 2,4 1,2,4,7,8 Claudio Fiocchi , Thaddeus StappenbeckID , Timothy Chan , Charis EngID , Jae 2,4 2,3 2,4 1,2,8 a1111111111 U. Jung , Lara JehiID , Serpil Erzurum , Feixiong ChengID * a1111111111 a1111111111 1 Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, United States of America, 2 Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western a1111111111 Reserve University, Cleveland, Ohio, United States of America, 3 Neurological Institute, Cleveland Clinic, a1111111111 Cleveland, Ohio, United States of America, 4 Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, United States of America, 5 Department of Pulmonary Medicine, Respiratory Institute, Cleveland Clinic, Cleveland, Ohio, United States of America, 6 Florida Research and Innovation Center, Cleveland Clinic, Port Saint Lucie, Florida, United States of America, 7 Department of Genetics and Genome Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America, 8 Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, OPEN ACCESS United States of America Citation: Zhou Y, Hou Y, Shen J, Mehra R, Kallianpur A, Culver DA, et al. (2020) A network ☯ These authors contributed equally to this work. * [email protected] medicine approach to investigation and population- based validation of disease manifestations and drug repurposing for COVID-19. -
Details Subject to Change. MGI Workshop Part 1
MGI Workshop Part 1: Dr. Kwong Wai Choy (Richard) Associate Professor, Dept of Obstetrics & Gynaecology, Deputy Director, Prenatal Genetic Diagnosis Centre, The Chinese University of Hong Kong Bio: Dr. Choy obtained his BSc degree in Biomedical Sciences from the University of Bradford and M(Med)Sc in Immunology at University of Birmingham, UK. He received postgraduate training in genetics and was awarded Doctor of Philosophy by The Chinese University of Hong Kong in 1999. Dr. Choy’s main research interests include the development of novel molecular diagnostic strategies and innovative applications of molecular analysis tools in prenatal diagnosis. His current research focuses on (1) structural genomic variation (including copy number variants); (2) development and application of the microarray-based Comparative Genomic Hybridization (array CGH) and massively parallel sequencing technology for prenatal diagnosis. In 2007 he founded the Agilent microarray core facilities in CUHK, which is the first centre of its kind in Asia dedicated to prenatal diagnosis with a focus on molecular basis of normal and abnormal fetal development. Dr. Choy is an Honorary Scientific Officer (medical) at the New Territories East Cluster of Hospitals, Hong Kong, where he is involved in the delivery of the laboratory diagnostic service. He is also the board member of the Hong Kong Society of Medical Genetics since 2009. Title: Low-Pass Genome Sequencing versus Chromosomal Microarray Analysis: Implementation in Prenatal Diagnosis Abstract: Emerging studies suggest that low-pass genome sequencing (GS) provides additional diagnostic yield of clinically significant copy-number variants (CNVs) compared with chromosomal microarray analysis (CMA). However, a prospective back-to-back comparison evaluating accuracy, efficacy, and incremental yield of low-pass GS compared with CMA is warranted. -
PROGRAM and ABSTRACTS for 2020 ANNUAL MEETING of the SOCIETY for GLYCOBIOLOGY November 9–12, 2020 Phoenix, AZ, USA 1017 2020 Sfg Virtual Meeting Preliminary Schedule
Downloaded from https://academic.oup.com/glycob/article/30/12/1016/5948902 by guest on 25 January 2021 PROGRAM AND ABSTRACTS FOR 2020 ANNUAL MEETING OF THE SOCIETY FOR GLYCOBIOLOGY November 9–12, 2020 Phoenix, AZ, USA 1017 2020 SfG Virtual Meeting Preliminary Schedule Mon. Nov 9 (Day 1) TOKYO ROME PACIFIC EASTERN EASTERN SESSION TIME TIME TIME START END TIME TIME 23:30 15:30 6:30 9:30 9:50 Welcome and Introduction - Michael Tiemeyer, CCRC UGA Downloaded from https://academic.oup.com/glycob/article/30/12/1016/5948902 by guest on 25 January 2021 23:30 15:30 6:30 9:50 – 12:36 Session 1: Glycobiology of Normal and Disordered Development | Chair: Kelly Ten-Hagen, NIH/NIDCR 23:50 15:50 6:50 9:50 10:10 KEYNOTE: “POGLUT1 mutations cause myopathy with reduced Notch signaling and α-dystroglycan hypoglycosylation” - Carmen Paradas Lopez, Biomedical Institute Sevilla 0:12 16:12 7:12 10:12 10:24 Poster Talk: “Regulation of Notch signaling by O-glycans in the intestine” – Mohd Nauman, Albert Einstein 0:26 16:26 7:26 10:26 10:38 Poster Talk: “Generation of an unbiased interactome for the tetratricopeptide repeat domain of the O-GlcNAc transferase indicates a role for the enzyme in intellectual disability” – Hannah Stephen, University of Georgia 0:40 16:30 7:30 10:40 10:50 Q&A 10:52 11:12 7:52 10:52 11:12 KEYNOTE: “Aberrations in N-cadherin Processing Drive PMM2-CDG Pathogenesis” - Heather Flanagan-Steet, Greenwood Genetics Center 1:14 11:26 8:14 11:14 11:26 Poster Talk: “Functional analyses of TMTC-type protein O-mannosyltransferases in Drosophila model -
DNA Sequencing Genetically Inherited Diseases
DNA, MUTATION DETECTION TYPES OF DNA There are two major types of DNA: Genomic DNA and Mitochondrial DNA Genomic DNA / Nuclear DNA: Comprises the genome of an organism and lead to an expression of genetic traits. Controls expression of the various traits in an organism. Sequenced as part of the Human Genome Project to study the various functions of the different regions of the genome Usually, during DNA replication there is a recombination of genes bringing about a change in sequence leading to individual specific characteristics. This way the difference in sequence could be studied from individual to individual. MITOCHONDRIAL DNA(MT DNA) mtDNA is a double stranded circular molecule. mtDNA is always Maternally inherited. Each Mitochodrion contains about 2-10 mtDNA molecules. mtDNA does not change from parent to offspring (Without recombination) Containing little repetitive DNA, and codes for 37 genes, which include two types of ribosomal RNA, 22 transfer RNAs and 13 protein subunits for some enzymes HUMAN STRUCTURAL GENE 1. Helix–turn–helix 2. Zinc finger 3. Leucine zipper 4. Helix–loop–helix GENE TO PROTEIN Facilitate transport of the mRNA to the cytoplasm and attachment to the ribosome Protect the mRNA from from 5' exonuclease Acts as a buffer to the 3' exonuclease in order to increase the half life of mRNA. TRANSLATION TYPES OF DNA SEQUENCE VARIATION VNTR: Variable Number of Tandem Repeats or minisatellite (Telomeric DNA, Hypervariable minisatellite DNA) ~6-100 bp core unit SSR : Simple Sequence Repeat or STR (short -
The Transcriptional Landscape and Hub Genes Associated with Physiological Responses to Drought Stress in Pinus Tabuliformis
International Journal of Molecular Sciences Article The Transcriptional Landscape and Hub Genes Associated with Physiological Responses to Drought Stress in Pinus tabuliformis Tariq Pervaiz 1,† , Shuang-Wei Liu 1,†, Saleem Uddin 1 , Muhammad Waqas Amjid 2 , Shi-Hui Niu 1,* and Harry X. Wu 1,3,4,* 1 Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, National Engineering Laboratory for Tree Breeding, College of Biological Sciences and Technology, Beijing Forestry University, Beijing 100083, China; [email protected] (T.P.); [email protected] (S.-W.L.); [email protected] (S.U.) 2 State Key Laboratory of Crop Genetics and Germplasm Enhancement, Cotton Germplasm Enhancement and Application Engineering Research Center (Ministry of Education), Nanjing Agricultural University, Nanjing 210095, China; [email protected] 3 Umea Plant Science Centre, Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences, Linnaeus vag 6, SE-901 83 Umea, Sweden 4 CSIRO National Research Collection Australia, Black Mountain Laboratory, Canberra, ACT 2601, Australia * Correspondence: [email protected] (S.-H.N.); [email protected] (H.X.W.) † These authors contributed equally. Abstract: Drought stress has an extensive impact on regulating various physiological, metabolic, and molecular responses. In the present study, the Pinus tabuliformis transcriptome was studied to Citation: Pervaiz, T.; Liu, S.-W.; evaluate the drought-responsive genes using RNA- Sequencing approache. The results depicted Uddin, S.; Amjid, M.W.; Niu, S.-H.; that photosynthetic rate and H2O conductance started to decline under drought but recovered 24 h Wu, H.X. The Transcriptional after re-watering; however, the intercellular CO2 concentration (Ci) increased with the onset of Landscape and Hub Genes drought. -
Supplementary Methods
Supplementary methods Somatic mutation and gene expression data This section describes the somatic mutation and gene expression data used in our pathway and network analysis. Gene-level mutation data Pathway and network databases record interactions at the gene or protein level. Therefore, we combine somatic mutation data for coding and non-coding elements into gene-level scores using the following procedure. P-values from the PCAWG-2-5-9-14 analysis summarize the statistical significance of somatic mutations on these regions. For each gene, we use Fisher’s method to combine P-values for multiple regions that are associated to the gene to create three gene scores: (1) a coding gene score (GS-C); (2) a non-coding (promoter, 5’ UTR, 3’ UTR, and enhancer) gene score (GS-N); and (3) a combined coding-and-non-coding (coding, promoter, 5’ UTR, 3’ UTR, and enhancer) gene score (GS-CN). Mutation data We obtained and processed two sources of somatic mutation data on various coding and non- coding regions associated with one or more genes: (1) binary mutation data that describe the presence or absence of mutations in a region for each sample in a tumor cohort and (2) integrated driver score P-values that describe the statistical significance of mutations in a region across samples in a cohort. 1. For binary mutation data we used the following procedure: a. We obtained somatic mutations from the PCAWG MAF (syn7364923). b. We retained mutations in a pan-cancer tumor cohort that excludes samples from the lymphoma and melanoma tumor cohorts, i.e., the Lymph-BNHL, Lymph-CLL, Lymph-NOS, and Skin-Melanoma cohorts, as well as 69 hypermutated samples with over 30 mutations/MB, which are listed by donor (syn7894281) or aliquot ID (syn7814911). -
The Draft Genomes of Softshell Turtle and Green Sea Turtle Yield Insights
LETTERS OPEN The draft genomes of soft-shell turtle and green sea turtle yield insights into the development and evolution of the turtle-specific body plan Zhuo Wang1,12, Juan Pascual-Anaya2,12, Amonida Zadissa3,12, Wenqi Li4,12, Yoshihito Niimura5, Zhiyong Huang1, Chunyi Li4, Simon White3, Zhiqiang Xiong1, Dongming Fang1, Bo Wang1, Yao Ming1, Yan Chen1, Yuan Zheng1, Shigehiro Kuraku2, Miguel Pignatelli6, Javier Herrero6, Kathryn Beal6, Masafumi Nozawa7, Qiye Li1, Juan Wang1, Hongyan Zhang4, Lili Yu1, Shuji Shigenobu7, Junyi Wang1, Jiannan Liu4, Paul Flicek6, Steve Searle3, Jun Wang1,8,9, Shigeru Kuratani2, Ye Yin4, Bronwen Aken3, Guojie Zhang1,10,11 & Naoki Irie2 The unique anatomical features of turtles have raised Three major hypotheses have been proposed for the evolutionary unanswered questions about the origin of their unique body origin of turtles, including that they (i) constitute early-diverged rep- plan. We generated and analyzed draft genomes of the soft- tiles, called anapsids3, (ii) are a sister group of the lizard-snake-tuatara shell turtle (Pelodiscus sinensis) and the green sea turtle (Lepidosauria) clade4 or (iii) are closely related to a lineage that (Chelonia mydas); our results indicated the close relationship includes crocodilians and birds (Archosauria)5–8. Even using molecular of the turtles to the bird-crocodilian lineage, from which they approaches, inconsistency still remains6–9. To clarify the evolution of split ~267.9–248.3 million years ago (Upper Permian to Triassic). the turtle-specific body plan, we first addressed the question of evolu- We also found extensive expansion of olfactory receptor genes tionary origin of the turtle by performing the first genome-wide phylo- in these turtles. -
High-Throughput Low-Cost DNA Sequencing Using Surface-Coating Technology
High-throughput low-cost DNA sequencing using surface-coating technology Yanzhe Qin ( [email protected] ) BGI-shenzhen Stephan Koehler Harvard University Shengming Zhao BGI-shenzhen Ruibin Mai MGI Tech Co., Ltd. Zhuo Liu MGI Tech Co., Ltd. Hao Lu MGI Tech Co., Ltd. Chengmei Xing BGI-shenzhen Biological Sciences - Article Keywords: next-generation sequencers, surface coating technology, reagent layers Posted Date: June 28th, 2021 DOI: https://doi.org/10.21203/rs.3.rs-130381/v1 License: This work is licensed under a Creative Commons Attribution 4.0 International License. Read Full License Page 1/11 Abstract The speed, expense and throughput of genomic sequencing impose limitations on its use for time-sensitive acute applications, such as rare or antibiotic resistant infections, and large-scale testing that is necessary for population- wide source-tracing, as in the COVID-19 pandemic. A major bottleneck for increasing throughput and decreasing operating costs of next-generation sequencers (NGS) is the ow cell that supplies reagents for the biochemical processes; this subsystem has not signicantly improved since 2005. Here we report a new method for sourcing reagents based on surface coating technology (SCT): the DNA adhered onto a biochip that is directly contacted by a reagent-coated polymeric strip. Compared with ow cells, reagent layers are an order of magnitude thinner while both the reagent exchange rate and biochip area are orders of magnitude greater. For whole genome sequencing (WGS), these improvements reduce turn-around time from days to twelve hours, reduce cost from about $1000 to $15, and increase data throughput by orders of magnitude.