Research article

A combinatorial approach to determine the context-dependent role in transcriptional and posttranscriptional regulation in Arabidopsis thaliana

Le Lu^1,2 and Jinming Li¹

¹Division of Structural and Computational Biology, School of Biological Sciences, Nanyang Technological University, 60 Nanyang Drive, Singapore 637551, Singapore

²Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University, Beijing 100084, PR China

author email corresponding author email

BMC Systems Biology 2009, 3:43doi:10.1186/1752-0509-3-43

Published:	28 April 2009

Abstract

Background

While progresses have been made in mapping transcriptional regulatory networks, posttranscriptional regulatory roles just begin to be uncovered, which has arrested much attention due to the discovery of miRNAs. Here we demonstrated a combinatorial approach to incorporate transcriptional and posttranscriptional regulatory sequences with gene expression profiles to determine their probabilistic dependencies.

Results

We applied the proposed method to microarray time course gene expression profiles and could correctly predict expression patterns for more than 50% of 1,132 genes, based on the sequence motifs adopted in the network models, which was statistically significant. Our study suggested that the contribution of miRNA regulation towards gene expression in plants may be more restricted than that of transcription factors; however, miRNAs might confer additional layers of robustness on gene regulation networks. The programs written in C++ and PERL implementing methods in this work are available for download from our supplemental data web page.

Conclusion

In this study we demonstrated a combinatorial approach to incorporate miRNA target motifs (miRNA-mediated posttranscriptional regulatory sites) and TFBSs (transcription factor binding sites) with gene expression profiles to reconstruct the regulatory networks. The proposed approach may facilitate the incorporation of diverse sources with limited prior knowledge.