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. 2016 Jan 22:9:38.
doi: 10.1186/s13104-016-1848-2.

Identification of valid reference genes for microRNA expression studies in a hepatitis B virus replicating liver cell line

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Identification of valid reference genes for microRNA expression studies in a hepatitis B virus replicating liver cell line

Kari Stougaard Jacobsen et al. BMC Res Notes. .

Abstract

Background: MicroRNAs are regulatory molecules and suggested as non-invasive biomarkers for molecular diagnostics and prognostics. Altered expression levels of specific microRNAs are associated with hepatitis B virus infection and hepatocellular carcinoma. We previously identified differentially expressed microRNAs with liver-specific target genes in plasma from children with chronic hepatitis B. To further understand the biological role of these microRNAs in the pathogenesis of chronic hepatitis B, we have used the human liver cell line HepG2, with and without HBV replication, after transfection of hepatitis B virus expression vectors. RT-qPCR is the preferred method for microRNA studies, and a careful normalisation strategy, verifying the optimal set of reference genes, is decisive for correctly evaluating microRNA expression levels. The aim of this study was to provide valid reference genes for the human HCC-derived cell line HepG2.

Results: A panel of 739 microRNAs was screened to identify the most stably expressed microRNAs, followed by a PubMed search identifying microRNAs previously used as reference genes. Sixteen candidate reference genes were validated by RT-qPCR. Reference gene stabilities were calculated first by standard deviations of ΔCt values and then by geNorm and NormFinder analyses, taking into account the amplification efficiency of each microRNA primer set. The optimal set of reference genes was verified by a target analysis using RT-qPCR on miR-215-5p.

Conclusion: We identified miR-24-3p, miR-151a-5p, and miR-425-5p as the most valid combination of reference genes for microRNA RT-qPCR studies in our hepatitis B virus replicating HepG2 cell model.

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Figures

Fig. 1
Fig. 1
geNorm analysis of candidate reference genes. a Ranking of reference genes according to the average expression stability M. A stepwise exclusion strategy identified miR-93-5p and miR-151a-5p as the most stable reference gene pair. b Determination of the optimal number of reference genes for normalisation, concluding that top three most stable reference genes would suffice for correct normalisation
Fig. 2
Fig. 2
Venn diagram showing the top five candidates from the three different approaches (∆Ct, geNorm and NormFinder) and their overlap

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