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Updated: Sep 19, 2025

mirMachine: A One-Stop Shop for Plant miRNA Annotation
Published on: May 1, 2021
Specific distinguishing between miRNA and pre-miRNA by blocker displacement SMOS-qPCR
Guodong Zhao1, Yanmiao Dai2, Chenjing Xia2
1Zhejiang University of Technology, Zhejiang, Hangzhou, 310014, China; ZJUT Yinhu Research Institute of Innovation and Entrepreneurship, Zhejiang, Hangzhou, 311400, China; Suzhou Key Laboratory of Integrated Traditional Chinese and Western Medicine for Digestive Diseases, Department of Spleen and Stomach Diseases, Kunshan Hospital of Traditional Chinese Medicine, Affiliated Hospital of Yangzhou University, Kunshan, Jiangsu, 215300, China; State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, Nanjing, 211189, China.
None:
MicroRNAs (miRNAs) play crucial roles in various biological processes, and their dysregulation is associated with numerous diseases. Accurate quantification of mature miRNAs is essential for their use as biomarkers. However, distinguishing between mature miRNAs and pre-miRNAs remains challenging. This study introduces a novel method called Blocker Displacement SMOS-qPCR (BL-SMOS-qPCR) to enhance the differentiation between miRNAs and pre-miRNAs. The method employs a blocker sequence complementary to the 3' end of pre-miRNA cDNA, effectively competing with the Linker sequence and reducing non-specific amplification. We optimized various parameters, including blocker modification, length, concentration, and reaction temperature. Results showed that MGB-modified blockers at optimal concentrations significantly improved discrimination between miRNAs and pre-miRNAs, reducing pre-miRNA signals by approximately 3.2-fold. The BL-SMOS-qPCR maintained similar dynamic ranges (6˟108 to 6˟101 copies per reaction) and R2 values compared to the original SMOS-qPCR method across multiple miRNA targets. Furthermore, the new method successfully distinguished between normal controls and esophageal cancer patients in serum samples, demonstrating its effectiveness in clinical applications. This study provides a novel approach for precise miRNA quantification, addressing the challenges of differentiating between mature miRNAs and their precursors in complex biological samples.

