EvoTol: a protein-sequence based evolutionary intolerance framework for disease-gene prioritization
Author(s) -
Owen J. L. Rackham,
Hashem A. Shihab,
Michael R. Johnson,
Enrico Petretto
Publication year - 2014
Publication title -
nucleic acids research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.008
H-Index - 537
eISSN - 1362-4954
pISSN - 0305-1048
DOI - 10.1093/nar/gku1322
Subject(s) - biology , gene , interactome , exome , genetics , computational biology , exome sequencing , sequence (biology) , genome , human genome , protein sequencing , disease , conserved sequence , mutation , peptide sequence , medicine , pathology
Methods to interpret personal genome sequences are increasingly required. Here, we report a novel framework (EvoTol) to identify disease-causing genes using patient sequence data from within protein coding-regions. EvoTol quantifies a gene's intolerance to mutation using evolutionary conservation of protein sequences and can incorporate tissue-specific gene expression data. We apply this framework to the analysis of whole-exome sequence data in epilepsy and congenital heart disease, and demonstrate EvoTol's ability to identify known disease-causing genes is unmatched by competing methods. Application of EvoTol to the human interactome revealed networks enriched for genes intolerant to protein sequence variation, informing novel polygenic contributions to human disease.
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