Concordance of gene expression in human protein complexes reveals tissue specificity and pathology.
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Abstract | Disease-causing variants in human genes usually lead to phenotypes specific to only a few tissues. Here, we present a method for predicting tissue specificity based on quantitative deregulation of protein complexes. The underlying assumption is that the degree of coordinated expression among proteins in a complex within a given tissue may pinpoint tissues that will be affected by a mutation in the complex and coordinated expression may reveal the complex to be active in the tissue. We identified known disease genes and their protein complex partners in a high-quality human interactome. Each susceptibility gene's tissue involvement was ranked based on coordinated expression with its interaction partners in a non-disease global map of human tissue-specific expression. The approach demonstrated high overall area under the curve (0.78) and was very successfully benchmarked against a random model and an approach not using protein complexes. This was illustrated by correct tissue predictions for three case studies on leptin, insulin-like-growth-factor 2 and the inhibitor of NF-κB kinase subunit gamma that show high concordant expression in biologically relevant tissues. Our method identifies novel gene-phenotype associations in human diseases and predicts the tissues where associated phenotypic effects may arise. |
Year of Publication | 2013
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Journal | Nucleic Acids Res
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Volume | 41
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Issue | 18
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Pages | e171
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Date Published | 2013 Oct
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ISSN | 1362-4962
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URL | |
DOI | 10.1093/nar/gkt661
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PubMed ID | 23921638
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PubMed Central ID | PMC3794609
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