title: Comparative analysis of human tissue interactomes reveals factors leading to tissue-specific manifestation of hereditary diseases.
abstract: An open question in human genetics is what underlies the tissue-specific manifestation of hereditary diseases, which are caused by genomic aberrations that are present in cells across the human body. Here we analyzed this phenomenon for over 300 hereditary diseases by using comparative network analysis. We created an extensive resource of protein expression and interactions in 16 main human tissues, by integrating recent data of gene and protein expression across tissues with data of protein-protein interactions (PPIs). The resulting tissue interaction networks (interactomes) shared a large fraction of their proteins and PPIs, and only a small fraction of them were tissue-specific. Applying this resource to hereditary diseases, we first show that most of the disease-causing genes are widely expressed across tissues, yet, enigmatically, cause disease phenotypes in few tissues only. Upon testing for factors that could lead to tissue-specific vulnerability, we find that disease-causing genes tend to have elevated transcript levels and increased number of tissue-specific PPIs in their disease tissues compared to unaffected tissues. We demonstrate through several examples that these tissue-specific PPIs can highlight disease mechanisms, and thus, owing to their small number, provide a powerful filter for interrogating disease etiologies. As two thirds of the hereditary diseases are associated with these factors, comparative tissue analysis offers a meaningful and efficient framework for enhancing the understanding of the molecular basis of hereditary diseases.
authors.affiliation: Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
authors.forename: Ruth
authors.initials: R
authors.lastname: Barshir
authors.affiliation: Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
authors.forename: Omer
authors.initials: O
authors.lastname: Shwartz
authors.affiliation: Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
authors.forename: Ilan Y
authors.initials: IY
authors.lastname: Smoly
authors.affiliation: Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Beer-Sheva, Israel; National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel.
authors.forename: Esti
authors.initials: E
authors.lastname: Yeger-Lotem
mesh_terms: D019295:Computational Biology; D030541:Databases, Genetic; D020869:Gene Expression Profiling; D030342:Genetic Diseases, Inborn / Q000235:genetics* / Q000378:metabolism*; D020022:Genetic Predisposition to Disease; D023281:Genomics; D006801:Humans; D025941:Protein Interaction Mapping / Q000379:methods* / Q000706:statistics & numerical data; D060066:Protein Interaction Maps; D040901:Proteomics; D014018:Tissue Distribution