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Related Concept Videos

MicroRNAs01:22

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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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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...
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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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Impact of normalization on miRNA microarray expression profiling.

Sylvain Pradervand1, Johann Weber, Jérôme Thomas

  • 1Lausanne DNA Array Facility, Center for Integrative Genomics, University of Lausanne, CH-1015 Lausanne, Switzerland. Sylvain.Pradervand@unil.ch

RNA (New York, N.Y.)
|January 30, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces a robust method for normalizing microRNA (miRNA) array data using invariant miRNAs. This approach improves data reliability across various experimental conditions and platforms.

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Area of Science:

  • Biotechnology
  • Genomics
  • Molecular Biology

Background:

  • MicroRNA (miRNA) profiling using microarrays is a common technique.
  • Established normalization methods for mRNA arrays lack detailed investigation for miRNA arrays.
  • Standardized normalization is crucial for accurate miRNA expression analysis.

Purpose of the Study:

  • To investigate the impact of normalization on Agilent miRNA array data.
  • To develop and validate a novel normalization method using invariant miRNAs.
  • To compare the performance of the proposed method against existing normalization techniques.

Main Methods:

  • Developed a method to select non-changing miRNAs (invariants).
  • Used invariants to compute normalization coefficients for linear regression and variance stabilizing normalization (VSN).
  • Compared invariant-based normalization with scaling, quantile, default VSN, and no normalization using diverse sample sets.

Main Results:

  • All tested normalization methods outperformed no normalization.
  • Invariant-based normalization and quantile normalization demonstrated the most robust performance across experimental conditions.
  • The proposed invariant selection and normalization method proved effective for Agilent miRNA arrays.

Conclusions:

  • Normalization is essential for reliable miRNA microarray data analysis.
  • Invariant-based normalization offers a robust and widely applicable solution for miRNA expression profiling.
  • The developed method is adaptable to various microarray platforms and quantitative PCR data.