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Updated: May 20, 2026

A Bioinformatics Pipeline to Accurately and Efficiently Analyze the MicroRNA Transcriptomes in Plants
Published on: January 21, 2020
Identification of soybean microRNAs involved in soybean cyst nematode infection by deep sequencing
Xiaoyan Li1, Xue Wang, Shaopeng Zhang
1Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China.
Abstract:
Soybean cyst nematode (SCN), Heterodera glycines, is the most devastating pathogen of soybean worldwide. MicroRNAs (miRNAs) are a class of small, non-coding RNAs that are known to play important role in plant stress response. However, there are few reports profiling the miRNA expression patterns during pathogen stress. We sequenced four small RNA libraries from two soybean cultivar (Hairbin xiaoheidou, SCN race 3 resistant, Liaodou 10, SCN race 3 susceptible) that grown under un-inoculated and SCN-inoculated soil. Small RNAs were mapped to soybean genome sequence, 364 known soybean miRNA genes were identified in total. In addition, 21 potential miRNA candidates were identified. Comparative analysis of miRNA profiling indicated 101 miRNAs belong to 40 families were SCN-responsive. We also found 20 miRNAs with different express pattern even between two cultivars of the same species. These findings suggest that miRNA paly important role in soybean response to SCN and have important implications for further identification of miRNAs under pathogen stress.

