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

Autor: Elliot J Shelton, Sabine Peiffer, Lucas Dennis, Kathy Y. Lee, Peter Mouritzen, Nicole Hartmann, Vamsi Veeramachaneni, Stefaan Derveaux, David Cheo, Ditte Andreasen, Silvia Rüberg, Chris Grimley, Mike DeMayo, Gary P. Schroth, Scott Silveria, Jo Vandesompele, Frank Staedtler, Dave Schuster, Umberto Ulmanella, Shujun Luo, Stephanie Fulmer-Smentek, Pieter Mestdagh, Yun Feng, Caifu Chen, Jonathan M Shaffer, Bernhard Gerstmayer, Julia S. Gouffon, Nathalie Bernard, Sunali Patel, Aishwarya Narayanan, Linda Wong, Lukas Baeriswyl, Thomas Peters, Eric Lader, Toumy Guettouche, Petula D'Andrade
Rok vydání: 2014
Předmět:
Zdroj: Nature Methods. 11:809-815
ISSN: 1548-7105
1548-7091
Popis: 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.
Databáze: OpenAIRE