Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases
Abstract
Here, whole-exome sequencing (WES) has opened up previously unheard of possibilities for identifying novel disease genes in Mendelian disorders, only about half of which have been elucidated to date. However, interpretation of WES data remains challenging. As a result, we analyze protein–protein association (PPA) networks to identify candidate genes in the vicinity of genes previously implicated in a disease. The analysis, using a random-walk with restart (RWR) method, is adapted to the setting of WES by developing a composite variant-gene relevance score based on the rarity, location and predicted pathogenicity of variants and the RWR evaluation of genes harboring the variants. Benchmarking using known disease variants from 88 disease-gene families reveals that the correct gene is ranked among the top 10 candidates in ≥50% of cases, a figure which we confirmed using a prospective study of disease genes identified in 2012 and PPA data produced before that date. In conclusion, we implement our method in a freely available Web server, ExomeWalker, that displays a ranked list of candidates together with information on PPAs, frequency and predicted pathogenicity of the variants to allow quick and effective searches for candidates that are likely to reward closer investigation.
- Authors:
-
- The Wellcome Trust Sanger Institute, Cambridgeshire (United Kingdom)
- Charite-Univ. Berlin, Berlin (Germany)
- Univ. of Duisburg-Essen, Essen (Germany)
- Johns Hopkins Univ. School of Medicine, Baltimore, MD (United States)
- Charite-Univ. Berlin, Berlin (Germany); Freie Univ. Berlin, Berlin (Germany)
- Charite-Univ. Berlin, Berlin (Germany); Polish Academy of Sciences, Poznan (Poland)
- Charite-Univ. Berlin, Berlin (Germany); Freie Univ. Berlin, Berlin (Germany); Max Planck Institute for Molecular Genetics, Berlin (Germany)
- Publication Date:
- Research Org.:
- Johns Hopkins Univ., Baltimore, MD (United States). School of Medicine
- Sponsoring Org.:
- USDOE Office of Science (SC), Basic Energy Sciences (BES)
- OSTI Identifier:
- 1342955
- Grant/Contract Number:
- AC02-05CH11231
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Bioinformatics
- Additional Journal Information:
- Journal Volume: 30; Journal Issue: 22; Journal ID: ISSN 1367-4803
- Publisher:
- Oxford University Press
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 60 APPLIED LIFE SCIENCES
Citation Formats
Smedley, Damian, Kohler, Sebastian, Czeschik, Johanna Christina, Amberger, Joanna, Bocchini, Carol, Hamosh, Ada, Veldboer, Julian, Zemojtel, Tomasz, and Robinson, Peter N. Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases. United States: N. p., 2014.
Web. doi:10.1093/bioinformatics/btu508.
Smedley, Damian, Kohler, Sebastian, Czeschik, Johanna Christina, Amberger, Joanna, Bocchini, Carol, Hamosh, Ada, Veldboer, Julian, Zemojtel, Tomasz, & Robinson, Peter N. Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases. United States. https://doi.org/10.1093/bioinformatics/btu508
Smedley, Damian, Kohler, Sebastian, Czeschik, Johanna Christina, Amberger, Joanna, Bocchini, Carol, Hamosh, Ada, Veldboer, Julian, Zemojtel, Tomasz, and Robinson, Peter N. Wed .
"Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases". United States. https://doi.org/10.1093/bioinformatics/btu508. https://www.osti.gov/servlets/purl/1342955.
@article{osti_1342955,
title = {Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases},
author = {Smedley, Damian and Kohler, Sebastian and Czeschik, Johanna Christina and Amberger, Joanna and Bocchini, Carol and Hamosh, Ada and Veldboer, Julian and Zemojtel, Tomasz and Robinson, Peter N.},
abstractNote = {Here, whole-exome sequencing (WES) has opened up previously unheard of possibilities for identifying novel disease genes in Mendelian disorders, only about half of which have been elucidated to date. However, interpretation of WES data remains challenging. As a result, we analyze protein–protein association (PPA) networks to identify candidate genes in the vicinity of genes previously implicated in a disease. The analysis, using a random-walk with restart (RWR) method, is adapted to the setting of WES by developing a composite variant-gene relevance score based on the rarity, location and predicted pathogenicity of variants and the RWR evaluation of genes harboring the variants. Benchmarking using known disease variants from 88 disease-gene families reveals that the correct gene is ranked among the top 10 candidates in ≥50% of cases, a figure which we confirmed using a prospective study of disease genes identified in 2012 and PPA data produced before that date. In conclusion, we implement our method in a freely available Web server, ExomeWalker, that displays a ranked list of candidates together with information on PPAs, frequency and predicted pathogenicity of the variants to allow quick and effective searches for candidates that are likely to reward closer investigation.},
doi = {10.1093/bioinformatics/btu508},
journal = {Bioinformatics},
number = 22,
volume = 30,
place = {United States},
year = {Wed Jul 30 00:00:00 EDT 2014},
month = {Wed Jul 30 00:00:00 EDT 2014}
}
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Integrative Annotation of Variants from 1092 Humans: Application to Cancer Genomics
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DDOST Mutations Identified by Whole-Exome Sequencing Are Implicated in Congenital Disorders of Glycosylation
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A new face and new challenges for Online Mendelian Inheritance in Man (OMIM®)
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Hereditary sensory autonomic neuropathy caused by a mutation in dystonin
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Mutation in PNPT1 , which Encodes a Polyribonucleotide Nucleotidyltransferase, Impairs RNA Import into Mitochondria and Causes Respiratory-Chain Deficiency
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A founder mutation in Vps37A causes autosomal recessive complex hereditary spastic paraparesis
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