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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 ends...

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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Related Experiment Video

Updated: Jun 15, 2026

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

Published on: June 15, 2016

Identifying co-regulating microRNA groups.

Jiyuan An¹, Kwok Pui Choi, Christine A Wells

¹The National Centre for Adult Stem Cell Research, The Eskitis Institute for Cell and Molecular Therapies, Griffith University, Nathan, QLD 4111, Australia. j.an@griffith.edu.au

Journal of Bioinformatics and Computational Biology

|February 26, 2010

Summary

This summary is machine-generated.

This study introduces a novel statistical procedure to accurately identify co-regulating microRNA (miRNA) groups and their target genes, overcoming limitations of current prediction tools. The findings help biologists pinpoint specific miRNA sets for gene of interest research.

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Last Updated: Jun 15, 2026

Describing a Transcription Factor Dependent Regulation of the MicroRNA Transcriptome

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Published on: June 15, 2016

Identifying Targets of Human microRNAs with the LightSwitch Luciferase Assay System using 3'UTR-reporter Constructs and a microRNA Mimic in Adherent Cells

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Current microRNA (miRNA) target prediction tools suffer from high false positive rates, hindering reliable identification of co-regulating miRNA and target gene groups.
This unreliability complicates the study of complex gene regulatory networks.

Purpose of the Study:

To develop a robust procedure for identifying highly probable co-regulating miRNA groups and their corresponding co-regulated gene sets.
To improve the accuracy of miRNA target prediction and functional group identification.

Main Methods:

A multi-step statistical testing procedure was employed.
Genes were screened for high-probability miRNA targets.
The minimum number of co-regulating miRNAs for each gene was determined.
Combinations of miRNAs and co-regulated gene groups were identified using p-values and Gene Ontology (GO) term annotations.

Main Results:

The method successfully identified 2, 3, and 4-term miRNA co-regulatory groups for gene groups of at least size 3 in humans.
Results suggest functional roles for miRNAs through "guilt by association"; for example, miR-130, miR-19, and miR-101 were identified as a co-regulating group, with miR-144 suggested as potentially related to neurodegenerative diseases.

Conclusions:

The developed procedure refines miRNA predictions using signal-to-noise ratios for accuracy and GO terms for functional relevance.
Findings are partially supported by biological experiments and provide a more focused approach for biologists seeking specific miRNA sets for gene targets.