Bioinformatics Advance Access originally published online on May 12, 2005
Bioinformatics 2005 21(14):3074-3081; doi:10.1093/bioinformatics/bti490
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Cis-regulatory element based targeted gene finding: genome-wide identification of abscisic acid- and abiotic stress-responsive genes in Arabidopsis thaliana
1Department of Computer Science and Engineering, Washington University in Saint Louis Saint Louis, MO 63130, USA
2Department of Genetics, Washington University in Saint Louis Saint Louis, MO 63130, USA
3Department of Biology, Washington University in Saint Louis Saint Louis, MO 63130, USA
*To whom correspondence should be addressed.
Motivation: A fundamental problem of computational genomics is identifying the genes that respond to certain endogenous cues and environmental stimuli. This problem can be referred to as targeted gene finding. Since gene regulation is mainly determined by the binding of transcription factors and cis-regulatory DNA sequences, most existing gene annotation methods, which exploit the conservation of open reading frames, are not effective in finding targetgenes.
Results: A viable approach to targeted gene finding is to exploit the cis-regulatory elements that are known to be responsible for the transcription of target genes. Given such cis-elements, putative target genes whose promoters contain the elements can be identified. As a case study, we apply the above approach to predict the genes in model plant Arabidopsis thaliana which are inducible by a phytohormone, abscisic acid (ABA), and abiotic stress, such as drought, cold and salinity. We first construct and analyze two ABA specific cis-elements, ABA-responsive element (ABRE) and its coupling element (CE), in A.thaliana, based on their conservation in rice and other cereal plants. We then use the ABRE–CE module to identify putative ABA-responsive genes in A.thaliana. Based on RT–PCR verification and the results from literature, this method has an accuracy rate of 67.5% for the top 40 predictions. The cis-element based targeted gene finding approach is expected to be widely applicable since a large number of cis-elements in many species are available.
Contact: zhang{at}cse.wustl.edu
Supplementary information: Supplementary data for this paper are available at Bioinformatics online.
Received on January 20, 2005; revised on May 5, 2005; accepted on May 6, 2005
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