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Systematic discovery of nonobvious human disease models through orthologous phenotypes
Author(s) -
Kriston L. McGary,
Tae Joo Park,
John O. Woods,
Hye Young Ji,
John B. Wallingford,
Edward M. Marcotte
Publication year - 2010
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.0910200107
Subject(s) - biology , phenotype , gene , model organism , genetics , computational biology , orthologous gene , genome
Biologists have long used model organisms to study human diseases, particularly when the model bears a close resemblance to the disease. We present a method that quantitatively and systematically identifies nonobvious equivalences between mutant phenotypes in different species, based on overlapping sets of orthologous genes from human, mouse, yeast, worm, and plant (212,542 gene-phenotype associations). These orthologous phenotypes, or phenologs, predict unique genes associated with diseases. Our method suggests a yeast model for angiogenesis defects, a worm model for breast cancer, mouse models of autism, and a plant model for the neural crest defects associated with Waardenburg syndrome, among others. Using these models, we show that SOX13 regulates angiogenesis, and that SEC23IP is a likely Waardenburg gene. Phenologs reveal functionally coherent, evolutionarily conserved gene networks-many predating the plant-animal divergence-capable of identifying candidate disease genes.

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