Influence of Reference Gene Selection on miRNA Quantification by RT-qPCR in Human Placental Samples

The gold standard for assessing expression of miRNAs, small molecules involved in numerous biological processes, is reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The reliability of RT-qPCR analysis results largely depends on accurate data normalization and the selection of an appropriate reference gene. This study evaluated the stability of five candidate reference genes-miR-525, miR-520c, SNORD48, miR-135b, and miR-143-in human placental samples. GeNorm, NormFinder, BestKeeper, and the delta Ct-method were used to evaluate gene expression stability. The effect of reference gene selection for normalization of target miRNAs (miR-1537, miR-190b, miR-16, miR-21, and miR-146a) expression in term placental samples from smokers and non-smokers was also investigated. All statistical tools identified miR-525, miR-520c, and SNORD48 as the three most stable reference genes, except for GeNorm, which recommends the combination of the first two genes. Normalization using SNORD48 and miR-525 produced comparable results for miR-21 expression in the placental samples, both in smokers and non-smokers, whereas normalization with miR-143 yielded markedly different outcomes compared to SNORD48 and miR-525. These findings highlight the considerable impact of reference gene selection on RT-qPCR results, emphasizing the importance of careful validation to avoid misinterpretation of gene expression data.

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Publication Details

Journal
British Journal of Biomedical Science
Published
2025-12-04
DOI
https://doi.org/10.3389/bjbs.2025.15354
Primary Topic
Molecular Biology Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Influence of Reference Gene Selection on miRNA Quantification by RT-qPCR in Human Placental Samples

Tatjana Orct, Martina Piasek, Daria Pašalić, Zorana Kljaković‐Gašpić et al.
British Journal of Biomedical Science
Molecular Biology Techniques and Applications
article

Influence of Reference Gene Selection on miRNA Quantification by RT-qPCR in Human Placental Samples

Tatjana Orct, Martina Piasek, Daria Pašalić, Zorana Kljaković‐Gašpić, Adrijana Dorotić, Jasna Jurasović, Ankica Sekovanić, Tatjana Mioč, Sandra Stasenko
article en

Abstract

The gold standard for assessing expression of miRNAs, small molecules involved in numerous biological processes, is reverse transcription-quantitative polymerase chain reaction (RT-qPCR). The reliability of RT-qPCR analysis results largely depends on accurate data normalization and the selection of an appropriate reference gene. This study evaluated the stability of five candidate reference genes-miR-525, miR-520c, SNORD48, miR-135b, and miR-143-in human placental samples. GeNorm, NormFinder, BestKeeper, and the delta Ct-method were used to evaluate gene expression stability. The effect of reference gene selection for normalization of target miRNAs (miR-1537, miR-190b, miR-16, miR-21, and miR-146a) expression in term placental samples from smokers and non-smokers was also investigated. All statistical tools identified miR-525, miR-520c, and SNORD48 as the three most stable reference genes, except for GeNorm, which recommends the combination of the first two genes. Normalization using SNORD48 and miR-525 produced comparable results for miR-21 expression in the placental samples, both in smokers and non-smokers, whereas normalization with miR-143 yielded markedly different outcomes compared to SNORD48 and miR-525. These findings highlight the considerable impact of reference gene selection on RT-qPCR results, emphasizing the importance of careful validation to avoid misinterpretation of gene expression data.

British Journal of Biomedical ScienceVol. 82
University of Zagreb (HR), Klinička bolnica "Sveti Duh" (HR), Klinička bolnica Merkur (HR), Centro poliklinika (LT), Institute for Medical Research and Occupational Health (HR)
Hrvatska Zaklada za Znanost, European Regional Development Fund
Openalex Percentile: Top 65%
Molecular Biology Techniques and Applications
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