Sebastian Köhler1,2, Uwe Schoeneberg3, Johanna Christina Czeschik4, Sandra C Doelken1, Jayne Y Hehir-Kwa5, Jonas Ibn-Salem1, Christopher J Mungall6, Damian Smedley7, Melissa A Haendel8, Peter N Robinson1,2,9,10. 1. Institute for Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin,Berlin, Germany. 2. Berlin-Brandenburg Center for Regenerative Therapies (BCRT), Berlin, Germany. 3. Foundation Institute Molecular Biology and Bioinformatics, Freie Universitaet Berlin, Berlin, Germany. 4. Institut für Humangenetik, Universitätsklinikum Essen, Universität Duisburg-Essen, Essen, Germany. 5. Department of Human Genetics, Radboud University Medical Centre, Nijmegen, The Netherlands. 6. Lawrence Berkeley National Laboratory, Berkeley, California, USA. 7. The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, UK. 8. Department of Medical Informatics and Epidemiology and OHSU Library, Oregon Health & Science University, Portland, USA. 9. Max Planck Institute for Molecular Genetics, Berlin, Germany. 10. Department of Mathematics and Computer Science, Institute for Bioinformatics, Freie Universitaet Berlin, Berlin, Germany.
Abstract
BACKGROUND: Clinical evaluation of CNVs identified via techniques such as array comparative genome hybridisation (aCGH) involves the inspection of lists of known and unknown duplications and deletions with the goal of distinguishing pathogenic from benign CNVs. A key step in this process is the comparison of the individual's phenotypic abnormalities with those associated with Mendelian disorders of the genes affected by the CNV. However, because often there is not much known about these human genes, an additional source of data that could be used is model organism phenotype data. Currently, almost 6000 genes in mouse and zebrafish are, when knocked out, associated with a phenotype in the model organism, but no disease is known to be caused by mutations in the human ortholog. Yet, searching model organism databases and comparing model organism phenotypes with patient phenotypes for identifying novel disease genes and medical evaluation of CNVs is hindered by the difficulty in integrating phenotype information across species and the lack of appropriate software tools. METHODS: Here, we present an integrated ranking scheme based on phenotypic matching, degree of overlap with known benign or pathogenic CNVs and the haploinsufficiency score for the prioritisation of CNVs responsible for a patient's clinical findings. RESULTS: We show that this scheme leads to significant improvements compared with rankings that do not exploit phenotypic information. We provide a software tool called PhenogramViz, which supports phenotype-driven interpretation of aCGH findings based on multiple data sources, including the integrated cross-species phenotype ontology Uberpheno, in order to visualise gene-to-phenotype relations. CONCLUSIONS: Integrating and visualising cross-species phenotype information on the affected genes may help in routine diagnostics of CNVs. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
BACKGROUND: Clinical evaluation of CNVs identified via techniques such as array comparative genome hybridisation (aCGH) involves the inspection of lists of known and unknown duplications and deletions with the goal of distinguishing pathogenic from benign CNVs. A key step in this process is the comparison of the individual's phenotypic abnormalities with those associated with Mendelian disorders of the genes affected by the CNV. However, because often there is not much known about these human genes, an additional source of data that could be used is model organism phenotype data. Currently, almost 6000 genes in mouse and zebrafish are, when knocked out, associated with a phenotype in the model organism, but no disease is known to be caused by mutations in the human ortholog. Yet, searching model organism databases and comparing model organism phenotypes with patient phenotypes for identifying novel disease genes and medical evaluation of CNVs is hindered by the difficulty in integrating phenotype information across species and the lack of appropriate software tools. METHODS: Here, we present an integrated ranking scheme based on phenotypic matching, degree of overlap with known benign or pathogenic CNVs and the haploinsufficiency score for the prioritisation of CNVs responsible for a patient's clinical findings. RESULTS: We show that this scheme leads to significant improvements compared with rankings that do not exploit phenotypic information. We provide a software tool called PhenogramViz, which supports phenotype-driven interpretation of aCGH findings based on multiple data sources, including the integrated cross-species phenotype ontology Uberpheno, in order to visualise gene-to-phenotype relations. CONCLUSIONS: Integrating and visualising cross-species phenotype information on the affected genes may help in routine diagnostics of CNVs. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Entities:
Keywords:
Copy number variation; data integration; human phenotype ontology; model organism phenotype; phenogram
Authors: Erin Rooney Riggs; Karen E Wain; Darlene Riethmaier; Melissa Savage; Bethanny Smith-Packard; Erin B Kaminsky; Heidi L Rehm; Christa Lese Martin; David H Ledbetter; W Andrew Faucett Journal: Hum Mutat Date: 2013-04-02 Impact factor: 4.878
Authors: David T Miller; Margaret P Adam; Swaroop Aradhya; Leslie G Biesecker; Arthur R Brothman; Nigel P Carter; Deanna M Church; John A Crolla; Evan E Eichler; Charles J Epstein; W Andrew Faucett; Lars Feuk; Jan M Friedman; Ada Hamosh; Laird Jackson; Erin B Kaminsky; Klaas Kok; Ian D Krantz; Robert M Kuhn; Charles Lee; James M Ostell; Carla Rosenberg; Stephen W Scherer; Nancy B Spinner; Dimitri J Stavropoulos; James H Tepperberg; Erik C Thorland; Joris R Vermeesch; Darrel J Waggoner; Michael S Watson; Christa Lese Martin; David H Ledbetter Journal: Am J Hum Genet Date: 2010-05-14 Impact factor: 11.025
Authors: Nicole de Leeuw; Trijnie Dijkhuizen; Jayne Y Hehir-Kwa; Nigel P Carter; Lars Feuk; Helen V Firth; Robert M Kuhn; David H Ledbetter; Christa Lese Martin; Conny M A van Ravenswaaij-Arts; Steven W Scherer; Soheil Shams; Steven Van Vooren; Rolf Sijmons; Morris Swertz; Ros Hastings Journal: Hum Mutat Date: 2012-06 Impact factor: 4.878
Authors: Jayne Y Hehir-Kwa; Nienke Wieskamp; Caleb Webber; Rolph Pfundt; Han G Brunner; Christian Gilissen; Bert B A de Vries; Chris P Ponting; Joris A Veltman Journal: PLoS Comput Biol Date: 2010-04-22 Impact factor: 4.475
Authors: Jannine D Cody; Courtney Sebold; Amtul Malik; Patricia Heard; Erika Carter; Analisa Crandall; Bridgette Soileau; Margaret Semrud-Clikeman; Catherine M Cody; L Jean Hardies; Jinqi Li; Jack Lancaster; Peter T Fox; Robert F Stratton; Brian Perry; Daniel E Hale Journal: Am J Med Genet A Date: 2007-06-01 Impact factor: 2.802
Authors: Sebastian Köhler; Sandra C Doelken; Barbara J Ruef; Sebastian Bauer; Nicole Washington; Monte Westerfield; George Gkoutos; Paul Schofield; Damian Smedley; Suzanna E Lewis; Peter N Robinson; Christopher J Mungall Journal: F1000Res Date: 2013-02-01
Authors: Christina A Castellani; Melkaye G Melka; Andrea E Wishart; M Elizabeth O Locke; Zain Awamleh; Richard L O'Reilly; Shiva M Singh Journal: BMC Bioinformatics Date: 2014-04-21 Impact factor: 3.169
Authors: Judith A Blake; Carol J Bult; Janan T Eppig; James A Kadin; Joel E Richardson Journal: Nucleic Acids Res Date: 2013-11-26 Impact factor: 16.971
Authors: Gautier Koscielny; Gagarine Yaikhom; Vivek Iyer; Terrence F Meehan; Hugh Morgan; Julian Atienza-Herrero; Andrew Blake; Chao-Kung Chen; Richard Easty; Armida Di Fenza; Tanja Fiegel; Mark Grifiths; Alan Horne; Natasha A Karp; Natalja Kurbatova; Jeremy C Mason; Peter Matthews; Darren J Oakley; Asfand Qazi; Jack Regnart; Ahmad Retha; Luis A Santos; Duncan J Sneddon; Jonathan Warren; Henrik Westerberg; Robert J Wilson; David G Melvin; Damian Smedley; Steve D M Brown; Paul Flicek; William C Skarnes; Ann-Marie Mallon; Helen Parkinson Journal: Nucleic Acids Res Date: 2013-11-04 Impact factor: 16.971
Authors: Douglas G Howe; Judith A Blake; Yvonne M Bradford; Carol J Bult; Brian R Calvi; Stacia R Engel; James A Kadin; Thomas C Kaufman; Ranjana Kishore; Stanley J F Laulederkind; Suzanna E Lewis; Sierra A T Moxon; Joel E Richardson; Cynthia Smith Journal: Lab Anim (NY) Date: 2018-09-17 Impact factor: 12.625
Authors: Barbara Poszewiecka; Victor Murcia Pienkowski; Karol Nowosad; Jérôme D Robin; Krzysztof Gogolewski; Anna Gambin Journal: Nucleic Acids Res Date: 2022-05-07 Impact factor: 19.160
Authors: Damian Smedley; Max Schubach; Julius O B Jacobsen; Sebastian Köhler; Tomasz Zemojtel; Malte Spielmann; Marten Jäger; Harry Hochheiser; Nicole L Washington; Julie A McMurry; Melissa A Haendel; Christopher J Mungall; Suzanna E Lewis; Tudor Groza; Giorgio Valentini; Peter N Robinson Journal: Am J Hum Genet Date: 2016-08-25 Impact factor: 11.025
Authors: Melissa A Haendel; Nicole Vasilevsky; Matthew Brush; Harry S Hochheiser; Julius Jacobsen; Anika Oellrich; Christopher J Mungall; Nicole Washington; Sebastian Köhler; Suzanna E Lewis; Peter N Robinson; Damian Smedley Journal: Mamm Genome Date: 2015-06-20 Impact factor: 2.957
Authors: Robert J Sicko; Marilyn L Browne; Shannon L Rigler; Charlotte M Druschel; Gang Liu; Ruzong Fan; Paul A Romitti; Michele Caggana; Denise M Kay; Lawrence C Brody; James L Mills Journal: PLoS One Date: 2016-10-27 Impact factor: 3.240
Authors: Han Fang; Yiyang Wu; Hui Yang; Margaret Yoon; Laura T Jiménez-Barrón; David Mittelman; Reid Robison; Kai Wang; Gholson J Lyon Journal: BMC Med Genomics Date: 2017-02-23 Impact factor: 3.063
Authors: Sebastian Köhler; Nicole A Vasilevsky; Mark Engelstad; Erin Foster; Julie McMurry; Ségolène Aymé; Gareth Baynam; Susan M Bello; Cornelius F Boerkoel; Kym M Boycott; Michael Brudno; Orion J Buske; Patrick F Chinnery; Valentina Cipriani; Laureen E Connell; Hugh J S Dawkins; Laura E DeMare; Andrew D Devereau; Bert B A de Vries; Helen V Firth; Kathleen Freson; Daniel Greene; Ada Hamosh; Ingo Helbig; Courtney Hum; Johanna A Jähn; Roger James; Roland Krause; Stanley J F Laulederkind; Hanns Lochmüller; Gholson J Lyon; Soichi Ogishima; Annie Olry; Willem H Ouwehand; Nikolas Pontikos; Ana Rath; Franz Schaefer; Richard H Scott; Michael Segal; Panagiotis I Sergouniotis; Richard Sever; Cynthia L Smith; Volker Straub; Rachel Thompson; Catherine Turner; Ernest Turro; Marijcke W M Veltman; Tom Vulliamy; Jing Yu; Julie von Ziegenweidt; Andreas Zankl; Stephan Züchner; Tomasz Zemojtel; Julius O B Jacobsen; Tudor Groza; Damian Smedley; Christopher J Mungall; Melissa Haendel; Peter N Robinson Journal: Nucleic Acids Res Date: 2016-11-28 Impact factor: 16.971