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Computational identification of novel microRNAs and targets in Brassica napus
Authors:Xie Fu Liang  Huang Si Qi  Guo Kai  Xiang An Ling  Zhu Yi Yong  Nie Li  Yang Zhi Min
Institution:Department of Biochemistry and Molecular Biology, College of Life Sciences, Nanjing Agricultural University, Nanjing 210095, China.
Abstract:MicroRNAs (miRNAs) are a newly discovered class of non-protein-coding small RNAs with roughly 22 nucleotide-long. Increasing evidence has shown that miRNAs play multiple roles in biological processes, including development, cell proliferation and apoptosis and stress responses. In this research, several approaches were combined to make computational prediction of potential miRNAs and their targets in Brassica napus. We used previously known miRNAs from Arabidopsis, rice and other plant species against both expressed sequence tags (EST) and genomic survey sequence (GSS) databases to search for potential miRNAs in B. napus. A total of 21 potential miRNAs were detected following a range of strict filtering criteria. Using these potential miRNA sequences, we could further blast the mRNA database and found 67 potential targets in this species. According to the mRNA target information provided by NCBI (http://www.ncbi.nlm.nih.gov/), most of the target mRNAs appeared to be involved in plant growth, development and stress responses. To validate the prediction of miRNAs in B. napus, we performed a RT-PCR based assay of mature miRNA expression. Five miRNAs were identified in response to auxin, cadmium stress and phosphate starvation. So far, little is known about experimental or computational identification of miRNA in B. napus species. To improve efficiency for blast search, we developed an implementation (miRNAassist) that can identify homologs of miRNAs and their targets, with high sensitivity and specificity. The program is allowed to be run on Windows Operation System platform. miRNAassist is freely available if required.
Keywords:MicroRNA  Prediction  Targets  Brassica napus
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