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UniProt Genomic Mapping for Deciphering Functional Effects of Missense Variants

View ORCID ProfilePeter B. McGarvey, View ORCID ProfileAndrew Nightingale, View ORCID ProfileJie Luo, Hongzhan Huang, View ORCID ProfileMaria J. Martin, Cathy Wu, the UniProt Consortium
doi: https://doi.org/10.1101/192914
Peter B. McGarvey
1Innovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC, USA
4SIB Swiss Institute of Bioinformatics (SIB), Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland; Protein Information Resource (PIR), Washington, DC and Newark, DE, USA; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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Andrew Nightingale
3European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
4SIB Swiss Institute of Bioinformatics (SIB), Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland; Protein Information Resource (PIR), Washington, DC and Newark, DE, USA; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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Jie Luo
3European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
4SIB Swiss Institute of Bioinformatics (SIB), Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland; Protein Information Resource (PIR), Washington, DC and Newark, DE, USA; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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Hongzhan Huang
2Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE, USA
4SIB Swiss Institute of Bioinformatics (SIB), Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland; Protein Information Resource (PIR), Washington, DC and Newark, DE, USA; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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Maria J. Martin
3European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
4SIB Swiss Institute of Bioinformatics (SIB), Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland; Protein Information Resource (PIR), Washington, DC and Newark, DE, USA; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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Cathy Wu
2Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE, USA
4SIB Swiss Institute of Bioinformatics (SIB), Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland; Protein Information Resource (PIR), Washington, DC and Newark, DE, USA; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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4SIB Swiss Institute of Bioinformatics (SIB), Centre Medical Universitaire, 1 rue Michel Servet, 1211 Geneva 4, Switzerland; Protein Information Resource (PIR), Washington, DC and Newark, DE, USA; European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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Abstract

Understanding the association of genetic variation with its functional consequences in proteins is essential for the interpretation of genomic data and identifying causal variants in diseases. Integration of protein function knowledge with genome annotation can assist in rapidly comprehending genetic variation within complex biological processes. Here, we describe mapping UniProtKB human sequences and positional annotations such as active sites, binding sites, and variants to the human genome (GRCh38) and the release of a public genome track hub for genome browsers. To demonstrate the power of combining protein annotations with genome annotations for functional interpretation of variants, we present specific biological examples in disease-related genes and proteins. Computational comparisons of UniProtKB annotations and protein variants with ClinVar clinically annotated SNP data show that 32% of UniProtKB variants co-locate with 8% of ClinVar SNPs. The majority of co-located UniProtKB disease-associated variants (86%) map to ‘pathogenic’ ClinVar SNPs. UniProt and ClinVar are collaborating to provide a unified clinical variant annotation for genomic, protein and clinical researchers. The genome track hubs, and related UniProtKB files, are downloadable from the UniProt FTP site and discoverable as public track hubs at the UCSC and Ensembl genome browsers.

Footnotes

  • Email addresses: PBM§: pbm9{at}georgetown.edu AN: anight{at}ebi.ac.uk, J.L: jluo{at}ebi.ac.uk, MJM: martin{at}ebi.ac.uk, H.H: huang{at}dbi.udel.edu, CW: wuc{at}dbi.udel.edu

  • Grant Sponsor: NIH/NIGRI grants U41HG007822, U41HG007822-02S1 for UniProt and U01HG007437 for ClinGen.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted March 04, 2019.
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UniProt Genomic Mapping for Deciphering Functional Effects of Missense Variants
Peter B. McGarvey, Andrew Nightingale, Jie Luo, Hongzhan Huang, Maria J. Martin, Cathy Wu, the UniProt Consortium
bioRxiv 192914; doi: https://doi.org/10.1101/192914
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UniProt Genomic Mapping for Deciphering Functional Effects of Missense Variants
Peter B. McGarvey, Andrew Nightingale, Jie Luo, Hongzhan Huang, Maria J. Martin, Cathy Wu, the UniProt Consortium
bioRxiv 192914; doi: https://doi.org/10.1101/192914

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