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Nat Methods. 2014 Aug;11(8):809-15. doi: 10.1038/nmeth.3014. Epub 2014 Jun 29.

Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study.

Author information

1
Center for Medical Genetics, Ghent University, Ghent, Belgium.
2
Novartis Institutes of Biomedical Research, Basel, Switzerland.
3
Exiqon, Vedbaek, Denmark.
4
Life Technologies, South San Francisco, California, USA.
5
Quanta Biosciences, Inc., Gaithersburg, Maryland, USA.
6
Agilent Technologies, Inc., Santa Clara, California, USA.
7
Affymetrix, Santa Clara, California, USA.
8
NanoString Technologies, Seattle, Washington, USA.
9
WaferGen, San Francisco, California, USA.
10
Miltenyi Biotec, Bergisch Gladbach, Germany.
11
Qiagen, Fredrick, Maryland, USA.
12
Illumina, Hayward, California, USA.
13
Strand Life Sciences, Bangalore, India.
14
Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, USA.

Erratum in

  • Nat Methods. 2014 Sep;11(9):971.

Abstract

MicroRNAs are important negative regulators of protein-coding gene expression and have been studied intensively over the past years. Several measurement platforms have been developed to determine relative miRNA abundance in biological samples using different technologies such as small RNA sequencing, reverse transcription-quantitative PCR (RT-qPCR) and (microarray) hybridization. In this study, we systematically compared 12 commercially available platforms for analysis of microRNA expression. We measured an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples and synthetic spikes from microRNA family members with varying homology. We developed robust quality metrics to objectively assess platform performance in terms of reproducibility, sensitivity, accuracy, specificity and concordance of differential expression. The results indicate that each method has its strengths and weaknesses, which help to guide informed selection of a quantitative microRNA gene expression platform for particular study goals.

PMID:
24973947
DOI:
10.1038/nmeth.3014
[Indexed for MEDLINE]

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