Identification of Feed Forward Loops Composed of MicroRNAs and Transcription Factors in Arabidopsis


Authors: Nicholas Wu, Xiaozeng Yang and Lei Li
Page Range: 79-85
Published in: Journal of Biochemistry and Molecular Biology in the Post Genomic Era, 1#1 (2011)
ISSN: 2156-5732

Table of Contents


In eukaryotes, differential gene expression is regulated at many levels and by various trans-acting factors in the context of gene networks. Transcription factors (TFs) and microRNAs (miRNAs) are two classes of primary regulators for differential gene expression during organism development and function. Transcriptional gene networks mediated by TFs have been intensively mapped in several model organisms. However, relatively little has been done to examine regulatory network involving both miRNAs and TFs. This paper attempts to discover computationally the composite feed forward loops (FFLs) involving both miRNAs and TFs in the model plant Arabidopsis thaliana at the genome scale. 99 positional weight matrixes (PWM) that represent different DNA protein-binding motifs and 176 miRNAs were used to infer regulatory interactions at both the transcriptional and post-transcriptional levels. VisANT was then used to integrate the data and perform network motif searching. This approach generated many potential FFLs that are preferentially associated with conserved miRNAs. Further validation and study of these FFLs should provide much needed insights into the function and evolution of miRNA-mediated gene circuits in plants.

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