Genome-wide identification of osmotic stress response gene in Arabidopsis thaliana
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AbstractIn this paper, we present a cis-regulatory element based computational approach to genome-wide identification of genes putatively responding to various osmotic stresses in Arabidopsis thaliana. The rationale of our method is that gene expression is largely controlled at the transcriptional level through the interactions between transcription factors and cis-regulatory elements. Using cis-regulatory motifs known to regulate osmotic stress response, we therefore built an artificial neural network model to identify other functionally relevant genes involved in the same process. We performed Gene Ontology enrichment analysis on the 500 top-scoring predictions and found that, except for un-annotated ORFs (similar to 40%), 91.3% of the enriched GO classification was related to stress response and ABA response. Publicly available gene expression profiling data of Arabidopsis under various stresses were used for cross validation. We also conducted RT-PCR analysis to experimentally verify selected predictions. According to our results, transcript levels of 27 out of 41 top-ranked genes (65.8%) altered under various osmotic stress treatments. We believe that a similar approach could be extensively adopted elsewhere to infer gene function in various cellular processes from different species. (C) 2008 Elsevier Inc. All rights reserved.
All Author(s) ListLi Y, Zhu YM, Liu Y, Shu YJ, Meng FJ, Lu YM, Bai X, Liu B, Guo DJ
Journal nameGenomics
Year2008
Month12
Day1
Volume Number92
Issue Number6
PublisherElsevier
Pages488 - 493
ISSN0888-7543
eISSN1089-8646
LanguagesEnglish-United Kingdom
KeywordsArabidopsis thaliana; Artificial neural network; Cis-regulatory element; Gene finding; Osmotic stress
Web of Science Subject CategoriesBiotechnology & Applied Microbiology; BIOTECHNOLOGY & APPLIED MICROBIOLOGY; Genetics & Heredity; GENETICS & HEREDITY

Last updated on 2020-21-09 at 01:15