Cis-Regulatory Element Based Gene Finding: An Application in Arabidopsis thaliana

Yong Li[1] (yong@neau.edu.cn)
Yanming Zhu[1] (ymzhu2001@neau.edu.cn)
Yang Liu[2] (liuyang@cuhk.edu.hk)
Yongjun Shu[1] (syjun@neau.edu.cn)
Fanjiang Meng[3] (fjmeng@neau.edu.cn)
Yanmin Lu[3] (luyanmin@neau.edu.cn)
Bei Liu[3] (liubei@neau.edu.cn)
Xi Bai[1] (maixi@neau.edu.cn)
Diangjin Guo[2] (djguo@cuhk.edu.hk)

[1] Plant Bioengineering Laboratory, Northeast Agricultural University, Harbin, China
[2] State Key Lab for Agrobiotechnology and Department of Biology, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong
[3] Department of Computer Science, Northeast Agricultural University, Harbin, China


Abstract

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.

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Japanese Society for Bioinformatics