A catalogue of 863 Rett-syndrome-causing MECP2 mutations and lessons learned from data integration
Rett syndrome (RTT) is a rare neurological disorder mostly caused by a genetic variation in MECP2. Making new MECP2 variants and the related phenotypes available provides data for better understanding of disease mechanisms and faster identification of variants for diagnosis. This is, however, curren...
| Autores: | , , , , , , , , , , , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2021 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/338157 |
| Acceso en línea: | https://hdl.handle.net/2117/338157 https://dx.doi.org/10.1038/s41597-020-00794-7 |
| Access Level: | acceso abierto |
| Palabra clave: | Rett syndrome Methyl-CpG-binding protein 2 Data sets Nervous system--Diseases Data integration Disease genetics Genetics research Neurological disorders Genètica Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica |
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A catalogue of 863 Rett-syndrome-causing MECP2 mutations and lessons learned from data integrationEhrhart, FriederikeJacobsen, AnnikaRigau, Maria|||0000-0002-6501-7212Bosio, MattiaKaliyaperumal, RajaramLaros, Jeroen F. J.Willighagen, Egon L.Valencia, Alfonso|||0000-0002-8937-6789Roos, MarcoCapella Gutiérrez, Salvador|||0000-0002-0309-604XCurfs, Leopold M. G.Evelo, Chris T.Rett syndromeMethyl-CpG-binding protein 2Data setsNervous system--DiseasesData integrationDisease geneticsGenetics researchNeurological disordersGenèticaÀrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::BioinformàticaRett syndrome (RTT) is a rare neurological disorder mostly caused by a genetic variation in MECP2. Making new MECP2 variants and the related phenotypes available provides data for better understanding of disease mechanisms and faster identification of variants for diagnosis. This is, however, currently hampered by the lack of interoperability between genotype-phenotype databases. Here, we demonstrate on the example of MECP2 in RTT that by making the genotype-phenotype data more Findable, Accessible, Interoperable, and Reusable (FAIR), we can facilitate prioritization and analysis of variants. In total, 10,968 MECP2 variants were successfully integrated. Among these variants 863 unique confirmed RTT causing and 209 unique confirmed benign variants were found. This dataset was used for comparison of pathogenicity predicting tools, protein consequences, and identification of ambiguous variants. Prediction tools generally recognised the RTT causing and benign variants, however, there was a broad range of overlap Nineteen variants were identified that were annotated as both disease-causing and benign, suggesting that there are additional factors in these cases contributing to disease development.The authors would like to thank the Mutalyzer team for support and feedback, Henk van Kranen for support in liftover of ancient genetic variant descriptions, and Eric Smeets for collection of the Maastricht Rett dataset.This work was funded by ELIXIR (funded by the European Commission within the Research Infrastructures programme of Horizon 2020), the research infrastructure for life-science data (MolData2). FE and LC were also funded by The Dutch Rett Syndrome Foundation (Stichting Terre). CE, AJ, RK, AV, SCG, MB, MRi and MR also received funding from EXCELERATE (H2020, Grant No. 676559). AJ, RK, MR, MB, and SCG also received funding from RD-Connect, European Union Seventh Framework Programme (FP7/2007–2013, Grant No. 305444). FE, CE, AJ, RK, MR, MB, and SCG received funding from the European Union’s Horizon 2020 Research and Innovation Program under grant agreement EJP RD N°825575. RK was also funded by NWO in project VWData (grant no. 400.17.605) and BBMRI-NL (NWO, National Roadmap for Large-Scale Research Facilities, grant no. 184.033.111). AV and SCG also received funding from INB Grant (Grant No. PT17/0009/0001 - ISCIII-SGEFI / ERDF).Peer ReviewedSpringer Nature20212021-01-0120212021-02-09journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/338157https://dx.doi.org/10.1038/s41597-020-00794-7reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengEuropean Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 676559 ELIXIR-EXCELERATE: Fast-track ELIXIR implementation and drive early user exploitation across the life-sciences.open accesshttp://purl.org/coar/access_right/c_abf2Attribution 3.0 Spainhttp://creativecommons.org/licenses/by/3.0/es/Attribution 3.0 Spainhttps://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3381572026-05-27T15:37:01Z |
| dc.title.none.fl_str_mv |
A catalogue of 863 Rett-syndrome-causing MECP2 mutations and lessons learned from data integration |
| title |
A catalogue of 863 Rett-syndrome-causing MECP2 mutations and lessons learned from data integration |
| spellingShingle |
A catalogue of 863 Rett-syndrome-causing MECP2 mutations and lessons learned from data integration Ehrhart, Friederike Rett syndrome Methyl-CpG-binding protein 2 Data sets Nervous system--Diseases Data integration Disease genetics Genetics research Neurological disorders Genètica Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica |
| title_short |
A catalogue of 863 Rett-syndrome-causing MECP2 mutations and lessons learned from data integration |
| title_full |
A catalogue of 863 Rett-syndrome-causing MECP2 mutations and lessons learned from data integration |
| title_fullStr |
A catalogue of 863 Rett-syndrome-causing MECP2 mutations and lessons learned from data integration |
| title_full_unstemmed |
A catalogue of 863 Rett-syndrome-causing MECP2 mutations and lessons learned from data integration |
| title_sort |
A catalogue of 863 Rett-syndrome-causing MECP2 mutations and lessons learned from data integration |
| dc.creator.none.fl_str_mv |
Ehrhart, Friederike Jacobsen, Annika Rigau, Maria|||0000-0002-6501-7212 Bosio, Mattia Kaliyaperumal, Rajaram Laros, Jeroen F. J. Willighagen, Egon L. Valencia, Alfonso|||0000-0002-8937-6789 Roos, Marco Capella Gutiérrez, Salvador|||0000-0002-0309-604X Curfs, Leopold M. G. Evelo, Chris T. |
| author |
Ehrhart, Friederike |
| author_facet |
Ehrhart, Friederike Jacobsen, Annika Rigau, Maria|||0000-0002-6501-7212 Bosio, Mattia Kaliyaperumal, Rajaram Laros, Jeroen F. J. Willighagen, Egon L. Valencia, Alfonso|||0000-0002-8937-6789 Roos, Marco Capella Gutiérrez, Salvador|||0000-0002-0309-604X Curfs, Leopold M. G. Evelo, Chris T. |
| author_role |
author |
| author2 |
Jacobsen, Annika Rigau, Maria|||0000-0002-6501-7212 Bosio, Mattia Kaliyaperumal, Rajaram Laros, Jeroen F. J. Willighagen, Egon L. Valencia, Alfonso|||0000-0002-8937-6789 Roos, Marco Capella Gutiérrez, Salvador|||0000-0002-0309-604X Curfs, Leopold M. G. Evelo, Chris T. |
| author2_role |
author author author author author author author author author author author |
| dc.subject.none.fl_str_mv |
Rett syndrome Methyl-CpG-binding protein 2 Data sets Nervous system--Diseases Data integration Disease genetics Genetics research Neurological disorders Genètica Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica |
| topic |
Rett syndrome Methyl-CpG-binding protein 2 Data sets Nervous system--Diseases Data integration Disease genetics Genetics research Neurological disorders Genètica Àrees temàtiques de la UPC::Informàtica::Aplicacions de la informàtica::Bioinformàtica |
| description |
Rett syndrome (RTT) is a rare neurological disorder mostly caused by a genetic variation in MECP2. Making new MECP2 variants and the related phenotypes available provides data for better understanding of disease mechanisms and faster identification of variants for diagnosis. This is, however, currently hampered by the lack of interoperability between genotype-phenotype databases. Here, we demonstrate on the example of MECP2 in RTT that by making the genotype-phenotype data more Findable, Accessible, Interoperable, and Reusable (FAIR), we can facilitate prioritization and analysis of variants. In total, 10,968 MECP2 variants were successfully integrated. Among these variants 863 unique confirmed RTT causing and 209 unique confirmed benign variants were found. This dataset was used for comparison of pathogenicity predicting tools, protein consequences, and identification of ambiguous variants. Prediction tools generally recognised the RTT causing and benign variants, however, there was a broad range of overlap Nineteen variants were identified that were annotated as both disease-causing and benign, suggesting that there are additional factors in these cases contributing to disease development. |
| publishDate |
2021 |
| dc.date.none.fl_str_mv |
2021 2021-01-01 2021 2021-02-09 |
| dc.type.none.fl_str_mv |
journal article http://purl.org/coar/resource_type/c_6501 VoR http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| dc.type.openaire.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| dc.identifier.none.fl_str_mv |
https://hdl.handle.net/2117/338157 https://dx.doi.org/10.1038/s41597-020-00794-7 |
| url |
https://hdl.handle.net/2117/338157 https://dx.doi.org/10.1038/s41597-020-00794-7 |
| dc.language.none.fl_str_mv |
Inglés eng |
| language_invalid_str_mv |
Inglés |
| language |
eng |
| dc.relation.none.fl_str_mv |
European Commission http://doi.org/10.13039/100010661 Horizon 2020 Framework Programme 676559 ELIXIR-EXCELERATE: Fast-track ELIXIR implementation and drive early user exploitation across the life-sciences. |
| dc.rights.none.fl_str_mv |
open access http://purl.org/coar/access_right/c_abf2 Attribution 3.0 Spain http://creativecommons.org/licenses/by/3.0/es/ Attribution 3.0 Spain https://creativecommons.org/licenses/by/4.0/ |
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info:eu-repo/semantics/openAccess |
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open access http://purl.org/coar/access_right/c_abf2 Attribution 3.0 Spain http://creativecommons.org/licenses/by/3.0/es/ https://creativecommons.org/licenses/by/4.0/ |
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openAccess |
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application/pdf |
| dc.publisher.none.fl_str_mv |
Springer Nature |
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Springer Nature |
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reponame:UPCommons. Portal del coneixement obert de la UPC instname:Universitat Politècnica de Catalunya (UPC) |
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