Best Practice Guidelines for Molecular Analysis of Friedreich Ataxia
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Genome Analysis and Knowledge
Dahary et al. BMC Medical Genomics (2019) 12:200 https://doi.org/10.1186/s12920-019-0647-8 SOFTWARE Open Access Genome analysis and knowledge-driven variant interpretation with TGex Dvir Dahary1*, Yaron Golan1, Yaron Mazor1, Ofer Zelig1, Ruth Barshir2, Michal Twik2, Tsippi Iny Stein2, Guy Rosner3,4, Revital Kariv3,4, Fei Chen5, Qiang Zhang5, Yiping Shen5,6,7, Marilyn Safran2, Doron Lancet2* and Simon Fishilevich2* Abstract Background: The clinical genetics revolution ushers in great opportunities, accompanied by significant challenges. The fundamental mission in clinical genetics is to analyze genomes, and to identify the most relevant genetic variations underlying a patient’s phenotypes and symptoms. The adoption of Whole Genome Sequencing requires novel capacities for interpretation of non-coding variants. Results: We present TGex, the Translational Genomics expert, a novel genome variation analysis and interpretation platform, with remarkable exome analysis capacities and a pioneering approach of non-coding variants interpretation. TGex’s main strength is combining state-of-the-art variant filtering with knowledge-driven analysis made possible by VarElect, our highly effective gene-phenotype interpretation tool. VarElect leverages the widely used GeneCards knowledgebase, which integrates information from > 150 automatically-mined data sources. Access to such a comprehensive data compendium also facilitates TGex’s broad variant annotation, supporting evidence exploration, and decision making. TGex has an interactive, user-friendly, and easy adaptive interface, ACMG compliance, and an automated reporting system. Beyond comprehensive whole exome sequence capabilities, TGex encompasses innovative non-coding variants interpretation, towards the goal of maximal exploitation of whole genome sequence analyses in the clinical genetics practice. This is enabled by GeneCards’ recently developed GeneHancer, a novel integrative and fully annotated database of human enhancers and promoters. -
The Bio Revolution: Innovations Transforming and Our Societies, Economies, Lives
The Bio Revolution: Innovations transforming economies, societies, and our lives economies, societies, our and transforming Innovations Revolution: Bio The The Bio Revolution Innovations transforming economies, societies, and our lives May 2020 McKinsey Global Institute Since its founding in 1990, the McKinsey Global Institute (MGI) has sought to develop a deeper understanding of the evolving global economy. As the business and economics research arm of McKinsey & Company, MGI aims to help leaders in the commercial, public, and social sectors understand trends and forces shaping the global economy. MGI research combines the disciplines of economics and management, employing the analytical tools of economics with the insights of business leaders. Our “micro-to-macro” methodology examines microeconomic industry trends to better understand the broad macroeconomic forces affecting business strategy and public policy. MGI’s in-depth reports have covered more than 20 countries and 30 industries. Current research focuses on six themes: productivity and growth, natural resources, labor markets, the evolution of global financial markets, the economic impact of technology and innovation, and urbanization. Recent reports have assessed the digital economy, the impact of AI and automation on employment, physical climate risk, income inequal ity, the productivity puzzle, the economic benefits of tackling gender inequality, a new era of global competition, Chinese innovation, and digital and financial globalization. MGI is led by three McKinsey & Company senior partners: co-chairs James Manyika and Sven Smit, and director Jonathan Woetzel. Michael Chui, Susan Lund, Anu Madgavkar, Jan Mischke, Sree Ramaswamy, Jaana Remes, Jeongmin Seong, and Tilman Tacke are MGI partners, and Mekala Krishnan is an MGI senior fellow. -
Clinical Genome Analysis Evidence Review
Clinical genome analysis evidence review Update 2020 Authors: Laura Blackburn, Chantal Babb de Villiers, Joanna Janus, Emma Johnson, Mark Kroese Acknowledgements: The authors would like to thank Karina O’Rourke and Sian Morgan, authors of sections 2.1 and 2.3 respectively. The PHG Foundation is grateful for the insight provided by the individuals consulted during the course of this evidence synthesis. Full acknowledgements are listed in Appendix 1. This review was commissioned and funded by the National Specialist and Screening Services Directorate, NHS Services Scotland NB: URLs in this report were correct as of June 2020 Published by PHG Foundation 2 Worts Causeway Cambridge CB1 8RN UK Tel: +44 (0)1223 761 900 Report produced by PHG Foundation on behalf of NHS Scotland. Copyright NHS Scotland, under licence from PHG Foundation. How to reference this report: Clinical genome analysis evidence review: update 2020 PHG Foundation (2020) This report is the result of PHG Foundation’s independent research and analysis and is not linked to a third party in any way. PHG Foundation has provided occasional analytical services to Oxford Nanopore Technologies (ONT) as part of a consultancy agreement. The PHG Foundation is a health policy think-tank and linked exempt charity of the University of Cambridge. We work to achieve better health through the responsible and evidence based application of biomedical science. We are a registered company, no. 5823194 Contents Executive summary 6 Context 6 The UK genomics policy landscape 6 Summary of findings -
Identification of the Gene for Nance-Horan Syndrome (NHS) S P Brooks, N D Ebenezer, S Poopalasundaram, O J Lehmann, a T Moore, a J Hardcastle
768 SHORT REPORT J Med Genet: first published as 10.1136/jmg.2004.022517 on 1 October 2004. Downloaded from Identification of the gene for Nance-Horan syndrome (NHS) S P Brooks, N D Ebenezer, S Poopalasundaram, O J Lehmann, A T Moore, A J Hardcastle ............................................................................................................................... J Med Genet 2004;41:768–771. doi: 10.1136/jmg.2004.022517 Background: The disease intervals for Nance-Horan syndrome (NHS [MIM 302350]) and X linked congenital cataract (CXN) overlap on Xp22. See end of article for Objective: To identify the gene or genes responsible for these diseases. authors’ affiliations ....................... Methods: Families with NHS were ascertained. The refined locus for CXN was used to focus the search for candidate genes, which were screened by polymerase chain reaction and direct sequencing of potential Correspondence to: exons and intron-exon splice sites. Genomic structures and homologies were determined using Alison J Hardcastle, Division of Molecular bioinformatics. Expression studies were undertaken using specific exonic primers to amplify human fetal Genetics, Institute of cDNA and mouse RNA. Ophthalmology, 11–43 Results: A novel gene NHS, with no known function, was identified as causative for NHS. Protein Bath Street, London, EC1V 9EL, UK; a.hardcastle@ truncating mutations were detected in all three NHS pedigrees, but no mutation was identified in a CXN ucl.ac.uk family, raising the possibility that NHS and CXN may not be allelic. The NHS gene forms a new gene family with a closely related novel gene NHS-Like1 (NHSL1). NHS and NHSL1 lie in paralogous Revised version received duplicated chromosomal intervals on Xp22 and 6q24, and NHSL1 is more broadly expressed than NHS in 4 June 2004 Accepted for publication human fetal tissues. -
Trans-Ancestral Fine-Mapping and Epigenetic [0.95]Annotation
International Journal of Molecular Sciences Article Trans-Ancestral Fine-Mapping and Epigenetic Annotation as Tools to Delineate Functionally Relevant Risk Alleles at IKZF1 and IKZF3 in Systemic Lupus Erythematosus Timothy J. Vyse and Deborah S. Cunninghame Graham * Department of Medical and Molecular Genetics, King’s College London, London SE1 9RT, UK; [email protected] * Correspondence: [email protected] Received: 28 August 2020; Accepted: 13 October 2020; Published: 9 November 2020 Abstract: Background: Prioritizing tag-SNPs carried on extended risk haplotypes at susceptibility loci for common disease is a challenge. Methods: We utilized trans-ancestral exclusion mapping to reduce risk haplotypes at IKZF1 and IKZF3 identified in multiple ancestries from SLE GWAS and ImmunoChip datasets. We characterized functional annotation data across each risk haplotype from publicly available datasets including ENCODE, RoadMap Consortium, PC Hi-C data from 3D genome browser, NESDR NTR conditional eQTL database, GeneCards Genehancers and TF (transcription factor) binding sites from Haploregv4. Results: We refined the 60 kb associated haplotype upstream of IKZF1 to just 12 tag-SNPs tagging a 47.7 kb core risk haplotype. There was preferential enrichment of DNAse I hypersensitivity and H3K27ac modification across the 30 end of the risk haplotype, with four tag-SNPs sharing allele-specific TF binding sites with promoter variants, which are eQTLs for IKZF1 in whole blood. At IKZF3, we refined a core risk haplotype of 101 kb (27 tag-SNPs) from an initial extended haplotype of 194 kb (282 tag-SNPs), which had widespread DNAse I hypersensitivity, H3K27ac modification and multiple allele-specific TF binding sites. -
ROCK: a Breast Cancer Functional Genomics Resource David Sims, Borisas Bursteinas, Qiong Gao, Ekta Jain, Alan Mackay, Costas Mitsopoulos, Marketa Zvelebil
ROCK: a breast cancer functional genomics resource David Sims, Borisas Bursteinas, Qiong Gao, Ekta Jain, Alan Mackay, Costas Mitsopoulos, Marketa Zvelebil To cite this version: David Sims, Borisas Bursteinas, Qiong Gao, Ekta Jain, Alan Mackay, et al.. ROCK: a breast cancer functional genomics resource. Breast Cancer Research and Treatment, Springer Verlag, 2010, 124 (2), pp.567-572. 10.1007/s10549-010-0945-5. hal-00548215 HAL Id: hal-00548215 https://hal.archives-ouvertes.fr/hal-00548215 Submitted on 20 Dec 2010 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. ROCK: a Breast Cancer Functional Genomics Resource David Sims, Borisas Bursteinas, Qiong Gao, Ekta Jain, Alan MacKay, Costas Mitsopoulos and Marketa Zvelebil* * To whom correspondence should be addressed. Tel: +44 207 153 5350; Fax: +44 207 153 5016; Email: [email protected] Breakthrough Breast Cancer Research Centre, Institute of Cancer Research, Chester Beatty Laboratories, 237 Fulham Road, London, SW3 6JB. 1 Abstract The clinical and pathological heterogeneity of breast cancer has instigated efforts to stratify breast cancer sub-types according to molecular profiles. These profiling efforts are now being augmented by large-scale functional screening of breast tumour cell lines, using approaches such as RNA interference. -
Next Steps in the Sequence
Next steps in the sequence The implications of whole genome sequencing for health in the UK PHG Foundation project team and authors Dr Caroline Wright* Programme Associate Dr Hilary Burton Director Ms Alison Hall Project Manager (Law) Dr Sowmiya Moorthie Project Coordinator Dr Anna Pokorska-Bocci‡ Project Coordinator Dr Gurdeep Sagoo Epidemiologist Dr Simon Sanderson Associate Dr Rosalind Skinner Senior Fellow ‡ Corresponding author: [email protected] * Lead author Disclaimer This report is accurate as of September 2011, but readers should be aware that genome sequencing technology and applications will continue to develop rapidly from this point. This report is available from www.phgfoundation.org Published by PHG Foundation 2 Worts Causeway Cambridge CB1 8RN UK Tel: +44 (0)1223 740200 Fax: +44 (0)1223 740892 October 2011 © 2011 PHG Foundation ISBN 978-1-907198-08-3 Cover photo: http://www.sxc.hu/photo/914335 The PHG Foundation is the working name of the Foundation for Genomics and Population Health, a charitable organisation (registered in England and Wales, charity no. 1118664; company no. 5823194) which works with partners to achieve better health through the responsible and evidence-based application of biomedical science. Acknowledgements Dr Tom Dent contributed the section on risk prediction in the Other Applications chapter. Dr Richard Fordham contributed to the Health Economics chapter. Professor Anneke Lucassen, Dr Kathleen Liddell and Professor Jenny Hewison contributed to the Ethical, Legal and Social Implications chapter. Dr Ron Zimmern contributed to the Policy Analysis and Recommendations chapters. The PHG Foundation is grateful for the expert guidance and advice provided by the external Steering Group, in particular to Dr Jo Whittaker, Mr Chris Mattocks and Dr Paul Flicek for their extensive comments on the manuscript. -
Autosomal Recessive Coding Variants Explain Only a Small Proportion of Undiagnosed Developmental Disorders in the British Isles
bioRxiv preprint doi: https://doi.org/10.1101/201533; this version posted October 13, 2017. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-ND 4.0 International license. Autosomal recessive coding variants explain only a small proportion of undiagnosed developmental disorders in the British Isles Hilary C. Martin1,*, Wendy D. Jones1,2, James Stephenson1,3, Juliet Handsaker1, Giuseppe Gallone1, Jeremy F. McRae1, Elena Prigmore1, Patrick Short1, Mari Niemi1, Joanna Kaplanis1, Elizabeth Radford1,4, Nadia Akawi5, Meena Balasubramanian6, John Dean7, Rachel Horton8, Alice Hulbert9, Diana S. Johnson6, Katie Johnson10, Dhavendra Kumar11, Sally Ann Lynch12, Sarju G. Mehta13, Jenny Morton14, Michael J. Parker15, Miranda Splitt16, Peter D Turnpenny17, Pradeep C. Vasudevan18, Michael Wright16, Caroline F. Wright19, David R. FitzPatrick20, Helen V. Firth1,13, Matthew E. Hurles1, Jeffrey C. Barrett1,* on behalf of the DDD Study 1. Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, U.K. 2. Great Ormond Street Hospital for Children, NHS Foundation Trust, Great Ormond Street Hospital, Great Ormond Street, London WC1N 3JH, UK. 3. European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, U.K. 4. Department of Paediatrics, Cambridge University Hospitals NHS Foundation Trust, Cambridge, U.K. 5. Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, U.K. 6. Sheffield Clinical Genetics Service, Sheffield Children's NHS Foundation Trust, OPD2, Northern General Hospital, Herries Rd, Sheffield, S5 7AU, U.K. 7. Department of Genetics, Aberdeen Royal Infirmary, Aberdeen, U.K. -
CTCF Variants in 39 Individuals with a Variable Neurodevelopmental Disorder Broaden the Mutational and Clinical Spectrum
ARTICLE CTCF variants in 39 individuals with a variable neurodevelopmental disorder broaden the mutational and clinical spectrum A full list of authors and affiliations appears at the end of the paper. Purpose: Pathogenic variants in the chromatin organizer CTCF defects were observed. RNA-sequencing in five individuals were previously reported in seven individuals with a neurodevelop- identified 3828 deregulated genes enriched for known NDD genes mental disorder (NDD). and biological processes such as transcriptional regulation. Ctcf Methods: Through international collaboration we collected data dosage alteration in Drosophila resulted in impaired gross from 39 subjects with variants in CTCF. We performed tran- neurological functioning and learning and memory deficits. scriptome analysis on RNA from blood samples and utilized Conclusion: We significantly broaden the mutational and clinical Drosophila melanogaster to investigate the impact of Ctcf dosage spectrum of CTCF-associated NDDs. Our data shed light onto the alteration on nervous system development and function. functional role of CTCF by identifying deregulated genes and show Results: The individuals in our cohort carried 2 deletions, 8 likely that Ctcf alterations result in nervous system defects in Drosophila. gene-disruptive, 2 splice-site, and 20 different missense variants, most of them de novo. Two cases were familial. The associated Genetics in Medicine (2019) 21:2723–2733; https://doi.org/10.1038/s41436- phenotype was of variable severity extending from mild develop- 019-0585-z -
Genetic Variants in Epigenetic Pathways and Risks of Multiple Cancers in the GAME-ON Consortium
Published OnlineFirst January 23, 2017; DOI: 10.1158/1055-9965.EPI-16-0728 Research Article Cancer Epidemiology, Biomarkers Genetic Variants in Epigenetic Pathways and & Prevention Risks of Multiple Cancers in the GAME-ON Consortium Reka Toth1,2, Dominique Scherer1,3, Linda E. Kelemen4, Angela Risch2,5,6,7, Aditi Hazra8,9,Yesilda Balavarca1, Jean-Pierre J. Issa10,Victor Moreno11, Rosalind A. Eeles12, Shuji Ogino13,14,15, Xifeng Wu16, Yuanqing Ye16, Rayjean J. Hung17,18, Ellen L. Goode19, and à Ãà Cornelia M. Ulrich1,20,21, on behalf of the OCAC, CORECT , TRICL, ELLIPSE , DRIVE, and GAME-ON consortiaa Abstract Background: Epigenetic disturbances are crucial in cancer ated with ER-negative breast, endometrioid ovarian, and overall initiation, potentially with pleiotropic effects, and may be influ- and aggressive prostate cancer risk (OR ¼ 0.93; 95% CI ¼ 0.91– enced by the genetic background. 0.96; q ¼ 0.005). Variants in L3MBTL3 were associated with Methods: In a subsets (ASSET) meta-analytic approach, we colorectal, overall breast, ER-negative breast, clear cell ovarian, investigated associations of genetic variants related to epigenetic and overall and aggressive prostate cancer risk (e.g., rs9388766: mechanisms with risks of breast, lung, colorectal, ovarian and OR ¼ 1.06; 95% CI ¼ 1.03–1.08; q ¼ 0.02). Variants in TET2 were prostate carcinomas using 51,724 cases and 52,001 controls. False significantly associated with overall breast, overall prostate, over- discovery rate–corrected P values (q values < 0.05) were consid- all ovarian, and endometrioid ovarian cancer risk, with ered statistically significant. rs62331150 showing bidirectional effects. Analyses of subpath- Results: Among 162,887 imputed or genotyped variants in 555 ways did not reveal gene subsets that contributed disproportion- candidate genes, SNPs in eight genes were associated with risk of ately to susceptibility.