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. 2017 Jul 3;45(W1):W138-W145.
doi: 10.1093/nar/gkx302.

Gene ORGANizer: linking genes to the organs they affect

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Gene ORGANizer: linking genes to the organs they affect

David Gokhman et al. Nucleic Acids Res. .

Abstract

One of the biggest challenges in studying how genes work is understanding their effect on the physiology and anatomy of the body. Existing tools try to address this using indirect features, such as expression levels and biochemical pathways. Here, we present Gene ORGANizer (geneorganizer.huji.ac.il), a phenotype-based tool that directly links human genes to the body parts they affect. It is built upon an exhaustive curated database that links >7000 genes to ∼150 anatomical parts using >150 000 gene-organ associations. The tool offers user-friendly platforms to analyze the anatomical effects of individual genes, and identify trends within groups of genes. We demonstrate how Gene ORGANizer can be used to make new discoveries, showing that chromosome X is enriched with genes affecting facial features, that positive selection targets genes with more constrained phenotypic effects, and more. We expect Gene ORGANizer to be useful in a variety of evolutionary, medical and molecular studies aimed at understanding the phenotypic effects of genes.

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Figures

Figure 1.
Figure 1.
Sources of the Gene ORGANizer database. Sources of associations that comprise the Gene ORGANizer DB. Associations in Gene ORGANizer are divided into four levels of hierarchy: organ (e.g. stomach), system (e.g. digestive), region (e.g. abdomen) and germ layer (e.g. endoderm).
Figure 2.
Figure 2.
Gene ORGANizer detects enrichment of immune-related organs within immune-related genes. A body and head map of enrichment and depletion of organs across immune-related genes. As a positive control, we extracted from the Kyoto Encyclopedia of Genes and Genomes (KEGG) (11) genes that are associated with specific systems. Genes that are involved in immune response were run in ORGANize and the most enriched body parts were those that are associated with immune response.
Figure 3.
Figure 3.
Genes affecting the face, the brain, and the urogenital and skeletal systems are over-represented on chromosome X. (A) A heat map of enriched and depleted organs within X-linked genes. Gene ORGANizer detects significant enrichment of the brain and testes within these genes, confirming previous claims. A more pronounced trend is the over-representation of different facial features, including all parts of the face except the eyes. Many parts of the urogenital and skeletal systems are enriched as well. (B) A heat map of enriched and depleted systems within X-linked genes. The reproductive and the skeletal systems are significantly enriched (×1.38 and ×1.12, FDR = 3 × 10−5 and 0.022, respectively). The immune and the cardiovascular systems are significantly depleted (×0.74 and ×0.87, FDR = 0.002 and 0.032, respectively). (C) A heat map of enriched and depleted body regions within X-linked genes. The regions of the pelvis and limbs are significantly over-represented (×1.22 and ×1.16, FDR = 5 × 10−4 and 0.003, respectively). The abdominal region is significantly depleted (×0.84, FDR = 0.008).

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References

    1. Brookes A.J., Robinson P.N.. Human genotype-phenotype databases: aims, challenges and opportunities. Nat. Rev. Genet. 2015; 16:702–715. - PubMed
    1. Huang D.W., Sherman B.T., Lempicki R.A.. Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists. Nucleic Acids Res. 2009; 37:1–13. - PMC - PubMed
    1. Papatheodorou I., Oellrich A., Smedley D.. Linking gene expression to phenotypes via pathway information. J. Biomed. Semantics. 2015; 6:17. - PMC - PubMed
    1. Huang D.W., Lempicki R.A, Sherman B.T.. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat. Protoc. 2009; 4:44–57. - PubMed
    1. Köhler S., Doelken S.C., Mungall C.J., Bauer S., Firth H.V., Bailleul-Forestier I., Black G.C.M., Brown D.L., Brudno M., Campbell J. et al. . The Human Phenotype Ontology project: linking molecular biology and disease through phenotype data. Nucleic Acids Res. 2014; 42:D966–D974. - PMC - PubMed

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