Analysis of stop-gain and frameshift variants in human innate immunity genes.

Détails

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Etat: Public
Version: de l'auteur
ID Serval
serval:BIB_238AF5BFDF14
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Analysis of stop-gain and frameshift variants in human innate immunity genes.
Périodique
Plos Computational Biology
Auteur(s)
Rausell A., Mohammadi P., McLaren P.J., Bartha I., Xenarios I., Fellay J., Telenti A.
ISSN
1553-7358 (Electronic)
ISSN-L
1553-734X
Statut éditorial
Publié
Date de publication
2014
Peer-reviewed
Oui
Volume
10
Numéro
7
Pages
e1003757
Langue
anglais
Notes
Publication types: Publication Status: epublish
Résumé
Loss-of-function variants in innate immunity genes are associated with Mendelian disorders in the form of primary immunodeficiencies. Recent resequencing projects report that stop-gains and frameshifts are collectively prevalent in humans and could be responsible for some of the inter-individual variability in innate immune response. Current computational approaches evaluating loss-of-function in genes carrying these variants rely on gene-level characteristics such as evolutionary conservation and functional redundancy across the genome. However, innate immunity genes represent a particular case because they are more likely to be under positive selection and duplicated. To create a ranking of severity that would be applicable to innate immunity genes we evaluated 17,764 stop-gain and 13,915 frameshift variants from the NHLBI Exome Sequencing Project and 1,000 Genomes Project. Sequence-based features such as loss of functional domains, isoform-specific truncation and nonsense-mediated decay were found to correlate with variant allele frequency and validated with gene expression data. We integrated these features in a Bayesian classification scheme and benchmarked its use in predicting pathogenic variants against Online Mendelian Inheritance in Man (OMIM) disease stop-gains and frameshifts. The classification scheme was applied in the assessment of 335 stop-gains and 236 frameshifts affecting 227 interferon-stimulated genes. The sequence-based score ranks variants in innate immunity genes according to their potential to cause disease, and complements existing gene-based pathogenicity scores. Specifically, the sequence-based score improves measurement of functional gene impairment, discriminates across different variants in a given gene and appears particularly useful for analysis of less conserved genes.
Pubmed
Web of science
Open Access
Oui
Création de la notice
17/12/2014 9:58
Dernière modification de la notice
20/08/2019 13:01
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