Cis-regulatory element based gene finding: an application in Arabidopsis thaliana.
Using cis-regulatory motifs known to regulate plant osmotic stress response, an artificial neural network model was built to identify other functionally releted genes involved in the same process. The rationale behind our approach is that gene expression is largely controlled at the transcriptional level through the interactions between transcription factors and cis-regulatory elements. Gene Ontology enrichment analysis on the 500 top-scoring predictions showed that, 60% of the enriched GO classification was related to stress response. RT-PCR analysis showed that nearly 70% of the top-scoring predictions exhibited altered expression under various stress treatments. We expect that similar approach is widely applicable to infer gene function in various cellular processes in different species.
Li
Yong
Y
Plant Bioengineering Laboratory, Northeast Agricultural University, Harbin, China. yong@neau.edu.cn
Zhu
Yanming
Y
Liu
Yang
Y
Shu
Yongjun
Y
Meng
Fanjiang
F
Lu
Yanmin
Y
Liu
Bei
B
Bai
Xi
X
Guo
Dianjing
D
D000040:Abscisic Acid / Q000378:metabolism; D000465:Algorithms; D000818:Animals; D017360:Arabidopsis / Q000235:genetics*; D029681:Arabidopsis Proteins / Q000235:genetics; D017173:Caenorhabditis elegans / Q000235:genetics; D002980:Climate; D004331:Drosophila melanogaster / Q000235:genetics; D004777:Environment; D018506:Gene Expression Regulation, Plant; D017343:Genes, Plant / Q000235:genetics*; D018745:Genome, Plant; D008957:Models, Genetic; D011401:Promoter Regions, Genetic; D012045:Regulatory Sequences, Nucleic Acid; D015203:Reproducibility of Results; D014157:Transcription Factors / Q000235:genetics
D029681:Arabidopsis Proteins; D014157:Transcription Factors; D000040:Abscisic Acid