Evidence map›Paper›PMID 30840782›Full record

ArticleHuman mutation2019

UniProt genomic mapping for deciphering functional effects of missense variants.

Peter B McGarvey, Andrew Nightingale, Jie Luo, Hongzhan Huang, Maria J Martin, Cathy Wu, UniProt Consortium

Abstract read
In one paragraph

Article in Human mutation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed.

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  16. Anxiolytic-Pharmaceuticals (Basel, Switzerland) · 2023
    Article
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  18. Microbiology spectrum · 2023
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Peter B McGarveyInnovation Center for Biomedical Informatics, Georgetown University Medical Center, Washington, DC.ORCID 0000-0002-8312-6017
Andrew NightingaleEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom.
Jie LuoEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom.
Hongzhan HuangCenter for Bioinformatics and Computational Biology, University of Delaware, Newark, Delaware.
Maria J MartinEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, United Kingdom.
Cathy WuCenter for Bioinformatics and Computational Biology, University of Delaware, Newark, Delaware.
UniProt ConsortiumProtein Information Resource, Georgetown Medical Center, Washington, DC.

Funding

UniProt - Text Mining and Large Language models to Enhance Functional Annotation in UniProt of Protein Variants Associated with Alzheimer's DiseaseU24HG007822 · NHGRI · GEORGETOWN UNIVERSITY · PI Alex Bateman, Alan James Bridge · 2018 to 2026
$53.0M
UniProt: A centralized protein sequence and function resourceU41HG007822 · NHGRI · EUROPEAN MOLECULAR BIOLOGY LABORATORY · PI BATEMAN, ALEX · 2014 to 2017
$21.9M
A Knowledge Base for Clinically Relevant Genes and VariantsU01HG007437 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI BERG, JONATHAN S, EVANS, JAMES PHILIP · 2013 to 2016
$9.0M
NHGRI NIH HHS U01 HG007437NHGRI NIH HHS U01HG007437NHGRI NIH HHS U24 HG007822NHGRI NIH HHS U41 HG007822NHGRI NIH HHS U41HG007822NHGRI NIH HHS U41HG007822-02S1
6 · The paper itself

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 single nucleotide polymorphism (SNP) data show that 32% of UniProtKB variants colocate with 8% of ClinVar SNPs. The majority of colocated 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.

Indexed as

Databases, GeneticMutation, MissenseBinding SitesChromosome MappingDatabases, ProteinGenetic Predisposition to DiseaseHumansMolecular Sequence AnnotationPolymorphism, Single NucleotideProtein BindingProteinsSoftwareWeb BrowserProteinsgenome mappingmissense variantsUniProt database

Identifiers

PMID30840782
PMCPMC6563471

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.