A novel and universal method for microRNA RT-qPCR data normalization

By Pieter Mestdagh, P. Van Vlierberghe, A. De Weer, D. Muth, Frank Westermann, Frank Speleman, Jo Vandesompele. Genome Biology, 2009

1,047 citations recorded by the source corpus.

Gene expression analysis of microRNA molecules is becoming increasingly important. In this study we assess the use of the mean expression value of all expressed microRNAs in a given sample as a normalization factor for microRNA real-time quantitative PCR data and compare its performance to the currently adopted approach. We demonstrate that the mean expression value outperforms the current normalization strategy in terms of better reduction of technical variation and more accurate appreciation of biological changes.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/1f5394bdada06c7ba10ae12047dbf5a5d8117c79

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Citations in the corpus

Microvesicles released from human renal cancer stem cells stimulate angiogenesis and formation of lung premetastatic niche. (2011, background): “miRNAs with raw Ct values greater than 35 in both preparations were not included in the analysis, as they were considered nonspecific (18, 19).”
miR-9, a MYC/MYCN-activated microRNA, regulates E-cadherin and cancer metastasis (2010, neutral): “MiRNA expression was profiled as described previousl”
Cell-free nucleic acids as biomarkers in cancer patients (2011, background): “, but others have argued that all tested miRNAs should have established mean expression levels to reduce the technical variation in the miRNA isolation and to more accurately assess the biological change”
MicroRNAs in human cancer. (2013, methodology): “Mean expression normalization has been suggested as an alternative RT-PCR normalization method for reduction of technical variation to allow appreciation of biological changes [28].”
The multiMiR R package and database: integration of microRNA–target interactions along with their disease and drug associations (2014, methodology): “…used to give relative expression of a miRNA normalized to three additional miRNAs profiled and selected for normalization based on the approach in (33). cDNA was generated using the miScript Reverse Transcriptase kit (Qiagen) followed by qRT-PCR using miScript SYBR green (Qiagen) with the…”
BM mesenchymal stromal cell-derived exosomes facilitate multiple myeloma progression. (2013, neutral): “Mean miR expression was used for miR qRT-PCR data normalization, as previously described (49).”
Obstacles and opportunities in the functional analysis of extracellular vesicle RNA – an ISEV position paper (2017, background): “miRNA analysed in the study (geomean) has been suggested to serve as an accurate normalisation factor.[88,91] Other authors recommend a combination of various algo-”
MicroRNA signatures in tissues and plasma predict development and prognosis of computed tomography detected lung cancer (2011, background): “When usingmicrofluidic cards, there is general agreement on thenormalization of singlemiRNAexpressionusing themean values of expression of all miRNAs of each card (13).”
Benchmarking of RNA-sequencing analysis workflows using whole-transcriptome RT-qPCR expression data (2017, methodology): “Cq-values were normalized using the global mean normalization strategy 19 .”
Microvesicles Derived from Adult Human Bone Marrow and Tissue Specific Mesenchymal Stem Cells Shuttle Selected Pattern of miRNAs (2010, methodology): “To reduce sample variations among different arrays, miRNAs were compared between MSC and HLSC samples, based on their cycle threshold (Ct) values normalized to the mean expression value, calculated on the overall miRNA expression in each array according to Mestdagh [23].”