Predicting functional upstream open reading frames in Saccharomyces cerevisiaeReportar como inadecuado

Predicting functional upstream open reading frames in Saccharomyces cerevisiae - Descarga este documento en PDF. Documentación en PDF para descargar gratis. Disponible también para leer online.

BMC Bioinformatics

, 10:451

First Online: 30 December 2009Received: 04 November 2008Accepted: 30 December 2009


BackgroundSome upstream open reading frames uORFs regulate gene expression i.e., they are functional and can play key roles in keeping organisms healthy. However, how uORFs are involved in gene regulation is not yet fully understood. In order to get a complete view of how uORFs are involved in gene regulation, it is expected that a large number of experimentally verified functional uORFs are needed. Unfortunately, wet-experiments to verify that uORFs are functional are expensive.

ResultsIn this paper, a new computational approach to predicting functional uORFs in the yeast Saccharomyces cerevisiae is presented. Our approach is based on inductive logic programming and makes use of a novel combination of knowledge about biological conservation, Gene Ontology annotations and genes- responses to different conditions. Our method results in a set of simple and informative hypotheses with an estimated sensitivity of 76%. The hypotheses predict 301 further genes to have 398 novel functional uORFs. Three RPC11, TPK1, and FOL1 of these 301 genes have been hypothesised, following wet-experiments, by a related study to have functional uORFs. A comparison with another related study suggests that eleven of the predicted functional uORFs from genes LDB17, HEM3, CIN8, BCK2, PMC1, FAS1, APP1, ACC1, CKA2, SUR1, and ATH1 are strong candidates for wet-lab experimental studies.

ConclusionsLearning based prediction of functional uORFs can be done with a high sensitivity. The predictions made in this study can serve as a list of candidates for subsequent wet-lab verification and might help to elucidate the regulatory roles of uORFs.

Electronic supplementary materialThe online version of this article doi:10.1186-1471-2105-10-451 contains supplementary material, which is available to authorized users.

Download fulltext PDF

Autor: Selpi - Christopher H Bryant - Graham JL Kemp - Janeli Sarv - Erik Kristiansson - Per Sunnerhagen


Documentos relacionados