MTide: an integrated tool for the identification of miRNA-target interaction in plants.

MOTIVATION: Small RNA sequencing and degradome sequencing (also known as parallel analysis of RNA ends) have provided rich information on the microRNA (miRNA) and its cleaved mRNA targets on a genome-wide scale in plants, but no computational tools have been developed to effectively and conveniently deconvolute the miRNA-target interaction (MTI). RESULTS: A freely available package, MTide, was developed by combining modified miRDeep2 and CleaveLand4 with some other useful scripts to explore MTI in a comprehensive way. By searching for targets of a complete miRNAs, we can facilitate large-scale identification of miRNA targets, allowing us to discover regulatory interaction networks. AVAILABILITY AND IMPLEMENTATION: http://bis.zju.edu.cn/MTide.

Construction and analysis of microRNA-transcription factor regulation network in Arabidopsis.

Transcription factors (TFs) and microRNAs (miRNAs) are two major types of regulators of gene expression, at transcriptional and post-transcriptional levels, respectively. By gathering their gene regulatory relationships, gene regulatory networks (GRNs) could be formed. A network motif is a type of connection pattern among a set of nodes which appears significantly more frequently than in random networks. Investigations of the network motifs often yield biological insights into the nature of the network. The previous study on miRNA-TF regulation networks concentrated on animals, and relied heavily on computational predictions. The authors collected data concerning miRNA regulation and transcriptional regulation relationships in Arabidopsis from publicly available databases, and further incorporated them with the protein-protein interaction data. All the data in the author's collection are supported by experiments. They screened the network motifs, whose size ranges between 1 and 4. The biological implications of the motifs were further analysed, and a flower development related network was constructed as an example. In this example, they illustrated the relevance of the network with the given process, and proposed the association of several genes with flowers by a network cluster identification. In this study, they analysed the properties of the GRN in Arabidopsis, and discussed their biological implications, as well as their potential applications.