Prediction of Gene-Phenotype Associations in Humans, Mice, and Plants Using Phenologs

dc.contributor.utaustinauthorWoods, John O.en_US
dc.contributor.utaustinauthorSingh-Blom, Ulf Martinen_US
dc.contributor.utaustinauthorLaurent, Jon M.en_US
dc.contributor.utaustinauthorMcGary, Kriston L.en_US
dc.contributor.utaustinauthorMarcotte, Edward M.en_US
dc.creatorWoods, John O.en_US
dc.creatorSingh-Blom, Ulf Martinen_US
dc.creatorLaurent, Jon M.en_US
dc.creatorMcGary, Kriston L.en_US
dc.creatorMarcotte, Edward M.en_US
dc.date.accessioned2016-10-28T19:50:16Z
dc.date.available2016-10-28T19:50:16Z
dc.date.issued2013-06en_US
dc.description.abstractPhenotypes and diseases may be related to seemingly dissimilar phenotypes in other species by means of the orthology of underlying genes. Such "orthologous phenotypes," or "phenologs," are examples of deep homology, and may be used to predict additional candidate disease genes. Results: In this work, we develop an unsupervised algorithm for ranking phenolog-based candidate disease genes through the integration of predictions from the k nearest neighbor phenologs, comparing classifiers and weighting functions by cross-validation. We also improve upon the original method by extending the theory to paralogous phenotypes. Our algorithm makes use of additional phenotype data-from chicken, zebrafish, and E. coli, as well as new datasets for C. elegans-establishing that several types of annotations may be treated as phenotypes. We demonstrate the use of our algorithm to predict novel candidate genes for human atrial fibrillation (such as HRH2, ATP4A, ATP4B, and HOPX) and epilepsy (e. g., PAX6 and NKX2-1). We suggest gene candidates for pharmacologically-induced seizures in mouse, solely based on orthologous phenotypes from E. coli. We also explore the prediction of plant gene-phenotype associations, as for the Arabidopsis response to vernalization phenotype. Conclusions: We are able to rank gene predictions for a significant portion of the diseases in the Online Mendelian Inheritance in Man database. Additionally, our method suggests candidate genes for mammalian seizures based only on bacterial phenotypes and gene orthology. We demonstrate that phenotype information may come from diverse sources, including drug sensitivities, gene ontology biological processes, and in situ hybridization annotations. Finally, we offer testable candidates for a variety of human diseases, plant traits, and other classes of phenotypes across a wide array of species.en_US
dc.description.departmentCenter for Systems and Synthetic Biologyen_US
dc.description.sponsorshipTexas Advanced Research Programen_US
dc.description.sponsorshipNational Science Foundationen_US
dc.description.sponsorshipNational Institutes of Healthen_US
dc.description.sponsorshipU.S. Army Research 58343-MAen_US
dc.description.sponsorshipWelch Foundation F-1515en_US
dc.description.sponsorshipPackard Fellowshipen_US
dc.description.sponsorshipNational Science Foundation Graduate Research Fellowshipen_US
dc.identifierdoi:10.15781/T2QR4NT1S
dc.identifier.citationWoods, John O., Ulf Martin Singh-Blom, Jon M. Laurent, Kriston L. McGary, and Edward M. Marcotte. "Prediction of gene–phenotype associations in humans, mice, and plants using phenologs." BMC bioinformatics, Vol. 14, No. 1 (Jun., 2013): 1.en_US
dc.identifier.doi10.1186/1471-2105-14-203en_US
dc.identifier.issn1471-2105en_US
dc.identifier.urihttp://hdl.handle.net/2152/43186
dc.language.isoEnglishen_US
dc.relation.ispartofen_US
dc.relation.ispartofserialBMC Bioinformaticsen_US
dc.rightsAdministrative deposit of works to Texas ScholarWorks: This works author(s) is or was a University faculty member, student or staff member; this article is already available through open access or the publisher allows a PDF version of the article to be freely posted online. The library makes the deposit as a matter of fair use (for scholarly, educational, and research purposes), and to preserve the work and further secure public access to the works of the University.en_US
dc.rights.restrictionOpenen_US
dc.subjectlange-nielsen-syndromeen_US
dc.subjectatrial-fibrillationen_US
dc.subjectarabidopsis-thalianaen_US
dc.subjectelectrocardiographic abnormalitiesen_US
dc.subjectcongenital deafnessen_US
dc.subjectescherichia-colien_US
dc.subjectmolecular-basisen_US
dc.subjectjervellen_US
dc.subjectexpressionen_US
dc.subjecthistamineen_US
dc.subjectbiochemical research methodsen_US
dc.subjectbiotechnology & applied microbiologyen_US
dc.subjectmathematical & computational biologyen_US
dc.titlePrediction of Gene-Phenotype Associations in Humans, Mice, and Plants Using Phenologsen_US
dc.typeArticleen_US
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