ヒト胎盤サンプルにおけるRT-qPCRによるmiRNA定量における参照遺伝子選択の影響
Ankica Sekovanić1, Tatjana Orct1, Adrijana Dorotić2
1Institute for Medical Research and Occupational Health, Zagreb, Croatia.
British journal of biomedical science
|December 22, 2025
まとめ
逆転写定量PCR(RT-qPCR)を用いたマイクロRNA(miRNA)発現解析において、安定した参照遺伝子を選択することは非常に重要です。この研究では、ヒト胎盤サンプルにおいて、miR-525、miR-520c、およびSNORD48が信頼性の高い参照遺伝子として同定されました。
科学分野:
- Molecular Biology
- Genetics
- Biochemistry
背景:
- MicroRNAs (miRNAs) are key regulators of biological processes.
- Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) is the standard for miRNA expression analysis.
- Accurate data normalization, dependent on stable reference genes, is critical for reliable RT-qPCR results.
研究 の 目的:
- To evaluate the expression stability of five candidate reference genes in human placental samples.
- To assess the impact of reference gene selection on the normalization of target miRNA expression in smokers and non-smokers.
- To provide recommendations for selecting appropriate reference genes for miRNA studies in placental tissues.
主な方法:
- Candidate reference genes (miR-525, miR-520c, SNORD48, miR-135b, miR-143) were selected.
- Gene expression stability was assessed using GeNorm, NormFinder, BestKeeper, and the delta Ct-method.
- The effect of different reference genes on normalizing target miRNAs (miR-1537, miR-190b, miR-16, miR-21, miR-146a) was investigated in term placental samples from smokers and non-smokers.
主要な成果:
- miR-525, miR-520c, and SNORD48 were consistently identified as the most stable reference genes across multiple statistical tools.
- GeNorm recommended a combination of miR-525 and miR-520c.
- Normalization with miR-143 produced significantly different results compared to SNORD48 and miR-525, highlighting the impact of reference gene choice.
結論:
- The selection of reference genes significantly influences RT-qPCR results for miRNA expression analysis.
- miR-525, miR-520c, and SNORD48 are recommended as stable reference genes for human placental samples.
- Careful validation of reference genes is essential to avoid misinterpretation of gene expression data in research.


