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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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mirMachine: A One-Stop Shop for Plant miRNA Annotation
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scanMiR: a biochemically based toolkit for versatile and efficient microRNA target prediction.

Michael Soutschek1,2, Fridolin Gross1, Gerhard Schratt1,2

  • 1Lab of Systems Neuroscience, D-HEST Institute for Neuroscience, ETH Zürich, Zürich, Switzerland.

Bioinformatics (Oxford, England)
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Summary

Identifying microRNA targets is challenging. The scanMiR tool offers a user-friendly solution for predicting microRNA binding sites and their regulatory effects on gene expression.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Molecular Biology

Background:

  • MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression.
  • Identifying functional miRNA targets remains a significant challenge in molecular biology.
  • Previous prediction methods, while improved, lacked practical applicability.

Purpose of the Study:

  • To develop a user-friendly R package and web interface, scanMiR, for predicting miRNA-mediated gene repression.
  • To enable the identification of both conventional and unconventional miRNA binding sites.
  • To provide a tool for efficient scanning, affinity estimation, and prediction of transcript repression.

Main Methods:

  • Development of the scanMiR R package and a companion Shiny web application.
  • Utilizing lightweight linear models for efficient binding site scanning and affinity estimation.
  • Incorporating flexible 3'-supplementary alignment to predict unconventional interactions like target-directed miRNA degradation or slicing.

Main Results:

  • scanMiR provides a flexible and user-friendly platform for miRNA target prediction.
  • The tool efficiently scans for binding sites, estimates their affinity, and predicts aggregated transcript repression.
  • Demonstrated application of scanMiR in identifying unconventional binding sites on neuronal transcripts, including lncRNAs and circRNAs.

Conclusions:

  • scanMiR enhances the ability to identify functional miRNA targets and understand their regulatory roles.
  • The package and web interface offer accessible tools for researchers in bioinformatics and molecular biology.
  • Facilitates the study of miRNA interactions, including novel mechanisms like target-directed miRNA degradation.