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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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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...
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A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools
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Data Normalization Strategies for MicroRNA Quantification.

Heidi Schwarzenbach1, Andreia Machado da Silva2, George Calin3

  • 1Department of Tumour Biology, Center of Experimental Medicine, University Cancer Center Hamburg, University Medical Center Hamburg-Eppendorf, Hamburg, Germany;

Clinical Chemistry
|September 27, 2015
PubMed
Summary
This summary is machine-generated.

Normalizing microRNA (miRNA) expression data is crucial for accurate biological interpretation. This review examines small RNAs as normalizers and proposes a standardized workflow to improve data comparability across studies.

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Area of Science:

  • Molecular Biology
  • Genomics
  • Biotechnology

Background:

  • Quantitative real-time PCR and microarrays are used to measure microRNA (miRNA) expression.
  • Data normalization using reference genes is essential for accurate miRNA quantification.
  • Current normalization strategies lack consensus, impacting data interpretation.

Purpose of the Study:

  • To review the reliability of small RNAs as miRNA expression normalizers.
  • To compare different data normalization strategies for miRNA expression.
  • To propose a standardized workflow for miRNA data normalization.

Main Methods:

  • Literature review of miRNA expression quantification technologies.
  • Comparative analysis of various miRNA normalization strategies.
  • Discussion of reference gene selection challenges.

Main Results:

  • Small RNAs are commonly used as miRNA expression normalizers.
  • No universal consensus exists on the optimal normalization strategy.
  • The choice of reference gene significantly affects miRNA transcript levels and biological interpretation.

Conclusions:

  • A proposed workflow strategy aims to standardize miRNA expression data normalization.
  • Establishing a global standard procedure will enhance cross-study comparability.
  • Standardization is critical for reliable biological interpretation of miRNA data.