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MicroRNAs

MicroRNAs

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...

MicroRNAs

MicroRNAs

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 ends...

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...

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Related Experiment Video

Updated: Jul 4, 2026

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools

Published on: August 21, 2019

Comparison of normalization methods with microRNA microarray.

You-Jia Hua¹, Kang Tu, Zhong-Yi Tang

¹Bioinformatics Center, The Center of Functional Genomics, Key Lab of System Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, People's Republic of China.

|June 3, 2008

Summary

This summary is machine-generated.

This study compared 15 normalization methods for microRNA (miRNA) microarray data. Print-tip loess normalization proved most accurate, aligning with real-time PCR results across various rat tissues.

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Area of Science:

Molecular Biology
Genomics
Bioinformatics

Background:

MicroRNAs (miRNAs) regulate gene expression and protein translation.
Oligonucleotide microarrays are used for miRNA expression detection.
Previous microarray platforms had limited probes, complicating data normalization.

Purpose of the Study:

To compare 15 different normalization methods for miRNA microarray data.
To identify the most accurate normalization method for miRNA expression analysis.
To validate the chosen normalization method across diverse rat tissues.

Main Methods:

Microarray data for eight miRNAs from inflamed rat dorsal root ganglion (DRG) tissue were analyzed.
Fifteen distinct data normalization techniques were applied.
Normalized data were compared against results from real-time polymerase chain reaction (PCR).

Main Results:

The print-tip loess normalization method demonstrated the highest consistency with real-time PCR results.
This normalization pattern was replicated across 14 different types of rat tissue.
Print-tip loess normalization effectively addressed normalization challenges in miRNA microarray data.

Conclusions:

Print-tip loess is a highly reliable method for normalizing miRNA microarray data.
This finding is crucial for accurate miRNA expression profiling in various biological contexts.
The study provides valuable guidance for preprocessing miRNA microarray datasets.