12 results on '"Owen Lancaster"'
Search Results
2. F. W. Lancaster: A Family Tribute.
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Cesaria Lancaster, Miriam Meyer, Owen Lancaster, Jude Lancaster, Aaron Lancaster, Lakshmi Hanumanthappa, and Raji Hanumanthappa
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- 2008
- Full Text
- View/download PDF
3. Array-based Dynamic Allele Specific Hybridization (Array-DASH): optimization-free microarray processing for multiple simultaneous genomic assays
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Nathalie Zahra, Colin Veal, Caroline Howard, Maria Casadellà Fontdevila, Roger Paredes, Anthony J. Brookes, Spencer J. Gibson, Peter Freeman, Owen Lancaster, Marc Noguera-Julian, and Adrian Slater
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Genotyping ,HIV-1/genetics ,Microarray ,Coronavirus disease 2019 (COVID-19) ,Genotyping Techniques ,Computer science ,Biophysics ,Human immunodeficiency virus (HIV) ,Hybridization Array ,Computational biology ,Genome, Viral ,medicine.disease_cause ,01 natural sciences ,Biochemistry ,Genome ,Semi-quantitative ,03 medical and health sciences ,Hypericum/genetics ,medicine ,Humans ,Molecular Biology ,Allele specific ,030304 developmental biology ,COVID-19/epidemiology ,Oligonucleotide Array Sequence Analysis ,0303 health sciences ,010401 analytical chemistry ,COVID-19 ,HIV ,Cell Biology ,0104 chemical sciences ,HIV-1 ,Re-sequencing ,Hypericum ,Genome, Plant ,Software - Abstract
We report proof-of-principle experiments regarding a dynamic microarray protocol enabling accurate and semi-quantitative DNA analysis for re-sequencing, fingerprinting and genotyping. Single-stranded target molecules hybridise to surface-bound probes during initial gradual cooling with high-fidelity. Real-time tracking of target denaturation (via fluorescence) during a 'dynamic' gradual heating phase permits 'melt-curve' analysis. The probe most closely matching the target sequence is identified based on the highest melting temperature. We demonstrated a >99% re-sequencing accuracy and a potential detection rate of 1% for SNPs. Experiments employing Hypericum ribosomal ITS regions and HIV genomes illustrated a reliable detection level of 5% plus simultaneous re-sequencing and genotyping. Such performance suggests a range of potential real-world applications involving rapid sequence interrogation, for example, in the Covid-19 pandemic. Guidance is offered towards the development of a commercial platform and dedicated software required to bring this technique into mainstream science.
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- 2021
4. Prevalence of carbapenem resistance and carbapenemase production among Enterobacteriaceae isolated from urine in the UK: results of the UK infection-Carbapenem Resistance Evaluation Surveillance Trial (iCREST-UK)
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David W. Wareham, Neil Woodford, Holly Ciesielczuk, Gregory G. Stone, Li Xu-McCrae, Simon Bracher, Owen Lancaster, Houdini Ho Tin Wu, Frances Davies, Matthew J. Ellington, Hugo Donaldson, G Gopal Rao, Paurus M Irani, Peter M Hawkey, Anita Verma, and Shazad Mushtaq
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Adult ,Male ,0301 basic medicine ,Microbiology (medical) ,medicine.medical_specialty ,Carbapenem ,Adolescent ,medicine.drug_class ,Cost effectiveness ,Avibactam ,030106 microbiology ,Antibiotics ,Ceftazidime ,Microbial Sensitivity Tests ,Carbapenem-resistant enterobacteriaceae ,Polymerase Chain Reaction ,Meropenem ,beta-Lactamases ,Young Adult ,03 medical and health sciences ,chemistry.chemical_compound ,Bacterial Proteins ,Internal medicine ,Prevalence ,polycyclic compounds ,medicine ,Humans ,Pharmacology (medical) ,Etest ,Aged ,Pharmacology ,business.industry ,Enterobacteriaceae Infections ,Middle Aged ,biochemical phenomena, metabolism, and nutrition ,United Kingdom ,Anti-Bacterial Agents ,Carbapenem-Resistant Enterobacteriaceae ,Infectious Diseases ,Carbapenems ,chemistry ,Female ,business ,Sentinel Surveillance ,medicine.drug - Abstract
Objectives Although carbapenem susceptibility testing has been recommended for all Enterobacteriaceae from clinical specimens, for practical reasons a carbapenem is not included in many primary antibiotic panels for urine specimens. The 'iCREST' study sought carbapenemase-producing Enterobacteriaceae (CPE) in routine urine specimens yielding Gram-negative growth in five diagnostic laboratories in the UK. We sought also to compare locally and centrally determined MICs of meropenem and ceftazidime/avibactam. Methods Positive growth from up to 2000 urine specimens per laboratory was plated onto chromID® CARBA SMART agar. Suspected CPE colonies were tested locally by Etest for susceptibility to meropenem and ceftazidime/avibactam, and referred to central laboratories for PCR confirmation of CPE status and microbroth MIC determination. Results Twenty-two suspected CPE were identified from 7504 urine specimens. Ten were confirmed by PCR to have NDM (5), IMP (2), KPC (2) or OXA-48-like (1) carbapenemases. Locally determined ceftazidime/avibactam MICs showed complete categorical agreement with those determined centrally by microbroth methodology. The seven ceftazidime/avibactam-resistant isolates (MICs ≥256 mg/L) had NDM or IMP metallo-carbapenemases. Conclusions The frequency of confirmed CPE among Gram-negative urinary isolates was low, at 0.13% (10/7504), but CPE were found in urines at all five participating sites and the diversity of carbapenemase genes detected reflected the complex epidemiology of CPE in the UK. These data can inform local policies about the cost-effectiveness and clinical value of testing Gram-negative bacteria from urine specimens routinely against a carbapenem as part of patient management and/or infection prevention and control strategies.
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- 2017
5. VarioML framework for comprehensive variation data representation and exchange.
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Myles Byrne, Ivo F. A. C. Fokkema, Owen Lancaster, Tomasz Adamusiak, Anni Ahonen-Bishopp, David Atlan, Christophe Béroud, Michael Cornell, Raymond Dalgleish, Andrew Devereau, George P. Patrinos, Morris A. Swertz, Peter E. M. Taschner, Gudmundur A. Thorisson, Mauno Vihinen, Anthony J. Brookes, and Juha Muilu
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- 2012
- Full Text
- View/download PDF
6. New Technologies for DNA analysis-A review of the READNA Project
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Björn Stade, Lotte Moens, Joachim Fritzsche, Sascha Sauer, Tom Brown, Xia Teng, David Stoddart, Anders Kristensen, Kalim U. Mir, Afaf H. El-Sagheer, Andre Franke, Nadine Schracke, Jonas O. Tegenfeldt, Mats Nilsson, Elin Falk-Sörqvist, Andrew John Heron, Jane Kaye, Giovanni Maglia, Nathalie Zahra, Abdou ElSharawy, Colin Veal, Rodolphe Marie, Fredrik Persson, Jonathan Mangion, Marco Mignardi, Joop M.L.M. van Helvoort, Jörg Tost, Dvir Rotem, Ivo Gut, Hagan Bayley, Achillefs N. Kapanidis, Vincent Picaud, Spencer J. Gibson, Liqin Dong, Thomas Brefort, Henrik Flyvbjerg, Markus Beier, Emile Schyns, Johannes Hohlbein, Pieter Jan Van Der Zaag, Florence Mauger, Jelle Oostmeijer, Peter Freeman, Simon Heath, Geraint Evans, Owen Lancaster, Hans Lehrach, Simone Guenther, Michael Forster, David L.V. Bauer, Rongqin Ke, Jennifer Sengenes, Steven McGinn, Jonas Nyvold Pedersen, Marta Gut, Isabelle Heath-Brun, Ludovic Le Reste, Camilla Freitag, Anthony J. Brookes, Björn Ekström, Simon Fredriksson, Mats Gullberg, Florian Mertes, James P Willcocks, Peer F. Stähler, Ruud Out, Cees Dekker, Chemical Biology 1, Centre National de Génotypage (CNG), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford, Guided Development Heidelberg GmbH [Heidelberg, Germany], Damietta University, Suez University, Christian-Albrechts-Universität zu Kiel (CAU), University of Oxford, Clarendon Laboratory, Parks Road, University of Gothenburg (GU), Olink AB, Dag Hammarskjölds väg 52A, 752 37 Uppsala, Sweden (Olink AB), University of Leicester, Department of Physics [Gothenburg], Chalmers University of Technology [Göteborg], Centro Nacional de Analisis Genomico [Barcelona] (CNAG), Clarendon Laboratory [Oxford], Science for Life Laboratory [Solna], Royal Institute of Technology [Stockholm] (KTH ), Department of Chemistry [Oxford], DTU Nanotech, Danmarks Tekniske Universitet = Technical University of Denmark (DTU), Max Planck Institute for Molecular Genetics (MPIMG), Max-Planck-Gesellschaft, FlexGen BV, Galileiweg 8, 2333 BD Leiden, The Netherlands (FlexGen BV), Laboratoire Sciences des Données et de la Décision (LS2D), Département Métrologie Instrumentation & Information (DM2I), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Department of Chemistry, University of Oxford, Technologiepark Heidelberg GmbH, School of Chemistry [Southampton, UK], University of Southampton, Kavli Institute of Nanosciences [Delft] (KI-NANO), Delft University of Technology (TU Delft), Thermo Fisher Scientific Inc., Centre for Health, Law and Emerging Technologies (HeLEX), Photonis France (PHOTONIS FRANCE), Photonis Group, Philips Research Laboratories [Eindhoven], Oxford Nanopore Technologies, Department of Immunology, Genetics and Pathology [Uppsala, Sueden] (IGP), Uppsala University, and European Project: 201418,EC:FP7:HEALTH,FP7-HEALTH-2007-A,READNA(2008)
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0301 basic medicine ,Nucleic acid quantitation ,Emerging technologies ,Biophysics ,Bioengineering ,Biology ,Protein detection ,Mass Spectrometry ,03 medical and health sciences ,Dna genetics ,[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing ,Animals ,Humans ,Life Science ,European commission ,Mutation detection ,Exome ,signal processing, bioinformatics, statistical analysis, Nucleic Acid analysis, classification ,Molecular Biology ,Biological sciences ,VLAG ,business.industry ,General Medicine ,DNA ,Sequence Analysis, DNA ,[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM] ,Biotechnology ,Engineering management ,030104 developmental biology ,Biofysica ,Click Chemistry ,EPS ,business - Abstract
International audience; The REvolutionary Approaches and Devices for Nucleic Acid analysis (READNA) project received 12 million s funding under the European Union Framework Programme 7 from 1st June 2008 to 30th November 2012. The 19 project partners from both academia and industry from in total 7 countries had a project budget of 16 Ms with which they have discovered, created and developed a huge body of insights into nucleic acid analysis. Results have been presented widely in publications and in innumerous public presentations. Results have been moved to spin-offs such as the Olink enrichment kits (now sold by Agilent as Haloplex) and are findingtheir way to the market, such as the Oxford Nanopore MinIon sequencer that was first released to early-access user sites in 2014.
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- 2016
7. Cafe Variome
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Tim Beck, Anthony J. Brookes, Raymond Dalgleish, Colin Veal, Morris A. Swertz, Dhiwagaran Thangavelu, David Atlan, Owen Lancaster, and Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI)
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Genotype ,Interface (computing) ,Data field ,rare disease ,Biology ,Web Browser ,computer.software_genre ,World Wide Web ,User-Computer Interface ,Rare Diseases ,Genetics ,Humans ,Genetic Predisposition to Disease ,Cafe Variome ,Genetics (clinical) ,Simple (philosophy) ,Information Dissemination ,software ,Data discovery ,Databases, Bibliographic ,genotype-phenotype ,Data sharing ,Variome ,Phenotype ,Search box ,Matchmaker Exchange ,data discovery ,Web service ,computer - Abstract
Biomedical data sharing is desirable, but problematic. Data "discovery" approaches-which establish the existence rather than the substance of data-precisely connect data owners with data seekers, and thereby promote data sharing. Cafe Variome (http://www.cafevariome.org) was therefore designed to provide a general-purpose, Web-based, data discovery tool that can be quickly installed by any genotype-phenotype data owner, or network of data owners, to make safe or sensitive content appropriately discoverable. Data fields or content of any type can be accommodated, from simple ID and label fields through to extensive genotype and phenotype details based on ontologies. The system provides a "shop window" in front of data, with main interfaces being a simple search box and a powerful "query-builder" that enable very elaborate queries to be formulated. After a successful search, counts of records are reported grouped by "openAccess" (data may be directly accessed), "linked-Access" (a source link is provided), and "restrictedAccess" (facilitated data requests and subsequent provision of approved records). An administrator interface provides a wide range of options for system configuration, enabling highly customized single-site or federated networks to be established. Current uses include rare disease data discovery, patient matchmaking, and a Beacon Web service. (C) 2015 Wiley Periodicals, Inc.
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- 2015
8. HGVbaseG2P: a central genetic association database
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Debasis Dash, Anthony J. Brookes, Pallavi Sarmah, Robert K. Hastings, Robert C. Free, Gudmundur A. Thorisson, Samir K. Brahmachari, and Owen Lancaster
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Genotype ,Association (object-oriented programming) ,Genome-wide association study ,Biology ,computer.software_genre ,Genome ,03 medical and health sciences ,0302 clinical medicine ,Databases, Genetic ,Computer Graphics ,Genetics ,False positive paradox ,Humans ,030304 developmental biology ,Genetic association ,0303 health sciences ,Database ,Genome, Human ,Genetic Variation ,Articles ,Replicate ,Phenotype ,030220 oncology & carcinogenesis ,Human genome ,computer ,Software ,Genome-Wide Association Study ,Type I and type II errors - Abstract
The Human Genome Variation database of Genotype to Phenotype information (HGVbaseG2P) is a new central database for summary-level findings produced by human genetic association studies, both large and small. Such a database is needed so that researchers have an easy way to access all the available association study data relevant to their genes, genome regions or diseases of interest. Such a depository will allow true positive signals to be more readily distinguished from false positives (type I error) that fail to consistently replicate. In this paper we describe how HGVbaseG2P has been constructed, and how its data are gathered and organized. We present a range of user-friendly but powerful website tools for searching, browsing and visualizing G2P study findings. HGVbaseG2P is available at http://www.hgvbaseg2p.org.
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- 2009
- Full Text
- View/download PDF
9. F. W. Lancaster: A Family Tribute
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Aaron Lancaster, Raji Hanumanthappa, Cesaria Lancaster, Lakshmi Hanumanthappa, Owen Lancaster, Jude Lancaster, and Miriam Meyer
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Philosophy ,Tribute ,Environmental ethics ,General Medicine ,Theology - Abstract
This article in the Festschrift for F. W. Lancaster contains reflections by Lancaster’s family about him as a husband and father.
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- 2008
10. MegaPlex PCR: a strategy for multiplex amplification
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Guido Kopal, J Paul Pasche, Anthony J. Brookes, Owen Lancaster, and Linda Strömqvist Meuzelaar
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Cell Biology ,Computational biology ,Biology ,Bioinformatics ,Polymerase Chain Reaction ,Biochemistry ,DNA sequencing ,Humans ,Multiplex ,Primer (molecular biology) ,Molecular Biology ,Genotyping ,DNA Primers ,Biotechnology - Abstract
'MegaPlex PCR' is a robust technology for highly multiplexed amplification of specific DNA sequences. It uses target-specific pairs of PCR primers that are physically separated by surface immobilization. Initial surface-based amplification cycles are then coupled to efficient solution-phase PCR using one common primer pair. We demonstrate this method by co-amplifying and genotyping 75 unselected human single-nucleotide polymorphism (SNP) loci.
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- 2007
11. VarioML framework for comprehensive variation data representation and exchange
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Raymond Dalgleish, Anni Ahonen-Bishopp, Gudmundur A. Thorisson, David Atlan, Ivo F.A.C. Fokkema, Peter E.M. Taschner, Owen Lancaster, Juha Muilu, Morris A. Swertz, George P. Patrinos, Mauno Vihinen, Michael Cornell, Christophe Béroud, Andrew Devereau, Tomasz Adamusiak, Anthony J. Brookes, Myles Byrne, Institute for Molecular Medicine Finland (FIMM), Department of Human Genetics, Leiden University Medical Center (LUMC), Universiteit Leiden-Universiteit Leiden, Department of Genetics [Leicester], University of Leicester, Medical College of Wisconsin, Biocomputing Platforms, Ltd, Phenosystems Inc, Génétique Médicale et Génomique Fonctionnelle (GMGF), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), National Genetics Reference Laboratory, Department of Pharmacy, University of Patras, Department of Genetics, University of Groningen [Groningen], Department of Experimental Medical Science, Lund University [Lund], Institute of Biomedical Technology, University of Tampere [Finland], Tampere University Hospital, European Project: 200754,EC:FP7:HEALTH,FP7-HEALTH-2007-A,GEN2PHEN(2008), University of Patras [Greece], Biolääketieteellisen teknologian yksikkö - Institute of Biomedical Technology, University of Tampere, Science in Healthy Ageing & healthcaRE (SHARE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), BMC, Ed., and Genotype-To-Phenotype Databases: A Holistic Solution - GEN2PHEN - - EC:FP7:HEALTH2008-01-01 - 2013-06-30 - 200754 - VALID
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INFORMATION ,Computer science ,computer.internet_protocol ,Data publishing ,DATABASES ,Distribution ,PHENOTYPE ,Biochemistry ,0302 clinical medicine ,Structural Biology ,Lääketieteen bioteknologia - Medical biotechnology ,Databases, Genetic ,Disease ,lcsh:QH301-705.5 ,computer.programming_language ,[INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM] ,0303 health sciences ,[SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM] ,Applied Mathematics ,Methodology Article ,JSON ,[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM] ,Computer Science Applications ,GENOTYPE ,Data model ,030220 oncology & carcinogenesis ,Data collection ,[SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,lcsh:R858-859.7 ,User interface ,LSDB ,PROJECT ,LSDBS ,FORMAT ,External Data Representation ,lcsh:Computer applications to medicine. Medical informatics ,03 medical and health sciences ,Computer Systems ,[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,Web application ,Humans ,Molecular Biology ,030304 developmental biology ,Information retrieval ,Bioinformatics and Systems Biology ,business.industry ,Information Dissemination ,TAB ,Genetic Variation ,Variation database curation ,Data science ,ONTOLOGY ,MODEL ,Workflow ,Variome ,lcsh:Biology (General) ,[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM] ,Leiden Open Variation Database ,business ,computer ,XML - Abstract
Background Sharing of data about variation and the associated phenotypes is a critical need, yet variant information can be arbitrarily complex, making a single standard vocabulary elusive and re-formatting difficult. Complex standards have proven too time-consuming to implement. Results The GEN2PHEN project addressed these difficulties by developing a comprehensive data model for capturing biomedical observations, Observ-OM, and building the VarioML format around it. VarioML pairs a simplified open specification for describing variants, with a toolkit for adapting the specification into one's own research workflow. Straightforward variant data can be captured, federated, and exchanged with no overhead; more complex data can be described, without loss of compatibility. The open specification enables push-button submission to gene variant databases (LSDBs) e.g., the Leiden Open Variation Database, using the Cafe Variome data publishing service, while VarioML bidirectionally transforms data between XML and web-application code formats, opening up new possibilities for open source web applications building on shared data. A Java implementation toolkit makes VarioML easily integrated into biomedical applications. VarioML is designed primarily for LSDB data submission and transfer scenarios, but can also be used as a standard variation data format for JSON and XML document databases and user interface components. Conclusions VarioML is a set of tools and practices improving the availability, quality, and comprehensibility of human variation information. It enables researchers, diagnostic laboratories, and clinics to share that information with ease, clarity, and without ambiguity.
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- 2012
12. A mechanistic basis for amplification differences between samples and between genome regions
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Peter Freeman, Colin Veal, Stephen J. Chanock, Marion Leboyer, Reshma R Vaghela, Owen Lancaster, Stéphane Jamain, Anthony J. Brookes, Demetrius Albanes, Kevin B. Jacobs, Ivo Gut, BMC, Ed., REvolutionary Approaches and Devices for Nucleic Acid Analysis - READNA - - EC:FP7:HEALTH2008-06-01 - 2012-11-30 - 201418 - VALID, Department of Genetics [Leicester], University of Leicester, Division of Cancer Epidemiology and Genetics, National Cancer Institute [Bethesda] (NCI-NIH), National Institutes of Health [Bethesda] (NIH)-National Institutes of Health [Bethesda] (NIH), Core Genotyping Facility, Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Service de psychiatrie, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Hôpital Albert Chenevier, Centre Nacional d'Analisi Genomica, This research was supported by Action Medical Research (grants SP4139 and SP4483) and by the European Union's Seventh Framework Programme (FP7/ 2007-2013) project READNA (grant agreement HEALTH-F4-2008-201418)., and European Project: 201418,EC:FP7:HEALTH,FP7-HEALTH-2007-A,READNA(2008)
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Illumina infinium ,lcsh:QH426-470 ,lcsh:Biotechnology ,C + G ,Genomics ,Biology ,Proteomics ,Genome ,Base Composition/genetics ,03 medical and health sciences ,chemistry.chemical_compound ,0302 clinical medicine ,DNA amplification ,lcsh:TP248.13-248.65 ,[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,Genetics ,Humans ,DNA denaturation ,Nucleic Acid Amplification Techniques/methods ,030304 developmental biology ,Comparative genomics ,Base Composition ,0303 health sciences ,Genome, Human ,Nucleic acid amplification technique ,lcsh:Genetics ,chemistry ,Evolutionary biology ,030220 oncology & carcinogenesis ,Genome, Human/genetics ,[SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN] ,Human genome ,DNA microarray ,Nucleic Acid Amplification Techniques ,DNA ,Research Article ,Biotechnology - Abstract
Background For many analytical methods the efficiency of DNA amplification varies across the genome and between samples. The most affected genome regions tend to correlate with high C + G content, however this relationship is complex and does not explain why the direction and magnitude of effects varies considerably between samples. Results Here, we provide evidence that sequence elements that are particularly high in C + G content can remain annealed even when aggressive melting conditions are applied. In turn, this behavior creates broader ‘Thermodynamically Ultra-Fastened’ (TUF) regions characterized by incomplete denaturation of the two DNA strands, so reducing amplification efficiency throughout these domains. Conclusions This model provides a mechanistic explanation for why some genome regions are particularly difficult to amplify and assay in many procedures, and importantly it also explains inter-sample variability of this behavior. That is, DNA samples of varying quality will carry more or fewer nicks and breaks, and hence their intact TUF regions will have different lengths and so be differentially affected by this amplification suppression mechanism – with ‘higher’ quality DNAs being the most vulnerable. A major practical consequence of this is that inter-region and inter-sample variability can be largely overcome by employing routine fragmentation methods (e.g. sonication or restriction enzyme digestion) prior to sample amplification.
- Published
- 2012
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