Improved exome prioritization of disease genes through cross-species phenotype comparison
Open accessAbstract
Numerous new disease-gene associations have been identified by whole-exome sequencing studies in the last few years. However, many cases remain unsolved due to the sheer number of candidate variants remaining after common filtering strategies such as removing low quality and common variants and those deemed unlikely to be pathogenic. The observation that each of our genomes contains about 100 genuine loss-of-function variants makes identification of the causative mutation problematic when using these strategies alone. We propose using the wealth of genotype to phenotype data that already exists from model organism studies to assess the potential impact of these exome variants. Here, we introduce PH enotypic I nterpretation of V ariants in E xomes (PHIVE), an algorithm that integrates the calculation of phenotype similarity between human diseases and genetically modified mouse models with evaluation of the variants according to allele frequency, pathogenicity, and mode of inheritance approaches in our Exomiser tool. Large-scale validation of PHIVE analysis using 100,000 exomes containing known mutations demonstrated a substantial improvement (up to 54.1-fold) over purely variant-based (frequency and pathogenicity) methods with the correct gene recalled as the top hit in up to 83% of samples, corresponding to an area under the ROC curve of >95%. We conclude that incorporation of phenotype data can play a vital role in translational bioinformatics and propose that exome sequencing projects should systematically capture clinical phenotypes to take advantage of the strategy presented here.
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- Authors
- Robinson, P. N., Köhler, S., Oellrich, A., Sanger Mouse Genetics Project, Wang, K., Mungall, C. J., Lewis, S. E., Washington, N., Bauer, S., Seelow, D., Krawitz, P., Gilissen, C., Haendel, M., & Smedley, D.
- Affiliations
- Max Planck Institute for Molecular Genetics (DE)
- Charité – Universitätsmedizin Berlin (DE)
- Wellcome Sanger Institute (GB)
- University of Southern California (US)
- Lawrence Berkeley National Laboratory (US)
- Radboud University Nijmegen (NL)
- Oregon Health & Science University (US)
- Corresponding author
- Robinson, Peter N.
- Smedley, Damian
- ORCID
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2013-10-25
- Volume
- 24
- Issue
- 2
- Pages
- 340-348
- ISSN
- 1088-9051 (ISSN-L)
- PMC
- PMC3912424
- OpenAlex
- W2127006085
- Cited by
- 375
- References
- 51
- Citations by year
- 2026: 13 · 2025: 20 · 2024: 27 · 2023: 19 · 2022: 46 · 2021: 33 · 2020: 22 · 2019: 26 · 2018: 33 · 2017: 36 · 2016: 39 · 2015: 34 · 2014: 25 · 2013: 1
- Type
- posted content
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Genome Research (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Portal (King's College London) (publishedVersion, cc-by)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- HighWire Press Open Archive (submittedVersion)
- Funders
- U.S. Department of Energy (-AC02-05CH11231, 05CH11231, DE AC02 05CH11231, DE-AC02-)
- Wellcome Trust
- Deutsche Forschungsgemeinschaft (DE-AC02-05CH11231)
- Bundesministerium für Bildung und Forschung (0313911)
- National Institutes of Health (R24OD011883, DE-AC02–05CH11231)
- Office of Science (DEAC02–05CH11231, AC02-05CH11231, DE-AC02)
- Basic Energy Sciences (DE-AC02, DE-AC02-05CH11231., AC02–05CH11231)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- disease gene prioritization, Exomiser, loss-of-function mutations, genotype-phenotype data, mouse model, allele frequency, pathogenicity, mode of inheritance
- MeSH terms
- Algorithms, Animals, Humans, Phenotype, Software, Sequence Analysis, DNA, Computational Biology, Genetic Predisposition to Disease, Polymorphism, Single Nucleotide, Databases, Genetic, Mice, Genetic Association Studies, Exome
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