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Related Concept Videos

MicroRNAs01:22

MicroRNAs

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MicroRNA (miRNA) are short, regulatory RNA transcribed from introns (non-coding regions of a gene) or intergenic regions (stretches of DNA present between genes). Several processing steps are required to form biologically active, mature miRNA. The initial transcript, called primary miRNA (pri-mRNA), base-pairs with itself, forming a stem-loop structure. Within the nucleus, an endonuclease enzyme, called Drosha, shortens the stem-loop structure into hairpin-shaped pre-miRNA. After the pre-miRNA...
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Mining plant endogenous target mimics from miRNA-lncRNA interactions based on dual-path parallel ensemble pruning

Qiang Kang1, Jun Meng1, Chenglin Su2

  • 1School of Computer Science and Technology, Dalian University of Technology, Dalian, Liaoning 116024, China.

Briefings in Bioinformatics
|October 18, 2021
PubMed
Summary

This study introduces a new method to predict plant microRNA-long non-coding RNA interactions, identifying potential endogenous target mimics (eTMs) and their functions. The approach enhances understanding of plant regulatory networks and RNA interactions.

Keywords:
dual-pathendogenous target mimicensemble pruningnon-coding RNAprediction

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Area of Science:

  • Plant molecular biology
  • Bioinformatics
  • Genomics

Background:

  • MicroRNA (miRNA) and long non-coding RNA (lncRNA) interactions are crucial in biological processes.
  • lncRNAs function as endogenous target mimics (eTMs), regulating messenger RNA (mRNA) expression by binding miRNAs.
  • Research on plant eTMs is limited, with many functions remaining unknown.

Purpose of the Study:

  • To develop a novel ensemble pruning protocol for predicting plant miRNA-lncRNA interactions.
  • To identify potential eTMs in plants and elucidate their regulatory functions.
  • To construct plant RNA regulatory networks and infer eTM functions.

Main Methods:

  • A dual-path parallel ensemble method with adaptive pruning for cross-species prediction.
  • Mining potential eTMs from predicted miRNA-lncRNA interactions.
  • Biological experiments to determine RNA expression levels and construct regulatory networks.
  • Gene Ontology enrichment analysis for inferring eTM functions.

Main Results:

  • The proposed protocol demonstrated superior performance over existing methods on various plant species.
  • 17 potential eTMs were experimentally verified, involved in 22 regulatory interactions.
  • 14 potential eTMs were associated with 63 functions through Gene Ontology analysis.

Conclusions:

  • The novel ensemble pruning protocol effectively predicts plant miRNA-lncRNA interactions and identifies functional eTMs.
  • This study significantly advances the understanding of plant RNA-mediated regulation.
  • The findings provide a foundation for further research into plant gene regulation and functional genomics.