Systematic analysis of gene properties influencing organ system phenotypes in mammalian perturbations.

Bioinformatics

German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum Muenchen, 85764 Neuherberg, Germany and Technical University Munich WZW Chair of Bioinformatics, 80333 Munich, Germany German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764 Neuherberg, Germany, Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum Muenchen, 85764 Neuherberg, Germany and Technical University Munich WZW Chair of Bioinformatics, 80333 Munich, Germany.

Published: November 2014

Motivation: Diseases and adverse drug reactions are frequently caused by disruptions in gene functionality. Gaining insight into the global system properties governing the relationships between genotype and phenotype is thus crucial to understand and interfere with perturbations in complex organisms such as diseases states.

Results: We present a systematic analysis of phenotypic information of 5047 perturbations of single genes in mice, 4766 human diseases and 1666 drugs that examines the relationships between different gene properties and the phenotypic impact at the organ system level in mammalian organisms. We observe that while single gene perturbations and alterations of nonessential, tissue-specific genes or those with low betweenness centrality in protein-protein interaction networks often show organ-specific effects, multiple gene alterations resulting e.g. from complex disorders and drug treatments have a more widespread impact. Interestingly, certain cellular localizations are distinctly associated to systemic effects in monogenic disease genes and mouse gene perturbations, such as the lumen of intracellular organelles and transcription factor complexes, respectively. In summary, we show that the broadness of the phenotypic effect is clearly related to certain gene properties and is an indicator of the severity of perturbations. This work contributes to the understanding of gene properties influencing the systemic effects of diseases and drugs.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4609011PMC
http://dx.doi.org/10.1093/bioinformatics/btu487DOI Listing

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