Reference Genes for qPCR-Based miRNA Expression Profiling in 14 Human Tissues

Abstract

MicroRNAs (miRNAs) are promising biomarkers for the diagnosis and prognosis of various diseases. Quantitative PCR is the most frequently used method of measuring miRNA expression levels. However, the lack of validated reference genes represents the main source of potential bias in results. It is normal practice to use small nuclear RNAs as reference genes; however, they often have variable expression. Researchers tend to prefer the most stable reference genes in each experiment. The review includes reference genes for the following tissue types: gliomas, lung cancer, melanoma, gastric cancer, liver cancer, prostate cancer, breast cancer, thyroid cancer, ovarian cancer, cervical cancer, endometrial cancer, rectal cancer, blood tumors and placental tissues.

Biomarker potential of vitreous microRNA in retinal disease: a meta-analysis

“…The housekeeping gene used by all 7 studies was the small nuclear-RNA U6, a widely used reference gene. A review of miRNA-analysis using qPCR in cancer studies showed that 84% of studies used U6 as the reference gene (100). However, the expression of U6 was shown to vary with experimental conditions and disease, suggesting potential limitations in its use as a universal housekeeping gene (101, 102).…”

“…However, the expression of U6 was shown to vary with experimental conditions and disease, suggesting potential limitations in its use as a universal housekeeping gene (101,102). Other studies have shown that the ideal housekeeping gene varies based on disease state and the biological fluid being studied, and mathematical models such as geNorm, NormFinder, and BestKeeper should be used to identify a housekeeping gene that is optimal for vitreous humor (100,103). This holds particular significance as a gold standard 31 housekeeping gene would alleviate the challenge of small sample sizes in these studies, facilitating more straightforward pooling of data.…”

gQuant: A Robust and Generalizable Algorithm for Identifying Normalizer Genes in qRT-PCR Data: A Case Study on Urinary Exosomal miRNAs

“…The linchpin of comparative gene expression studies utilizing qRT-PCR is the judicious selection of normalizer genes for accurate data normalization (Smith et al, 2020). Although internal reference genes, such as ACTB, GAPDH, and 18s Ribosomal RNA (Suzuki et al, 2000), have been successfully employed at the tissue level for mRNA quantification, Researchers also opt to choose specific normalizers for individual experiments particularly where a universally accepted set of normalizers remains elusive such as in miRNA-based assays (Shen et al, 2011, Danese et al, 2017, Veryaskina et al, 2022). Although many miRNA-based studies used U6 as the most commonly used reference gene, it has variable expression and does not represent the optimal reference gene for miRNA analysis (Jacobsen et al, 2016).…”

“…However, the absence of a robust and standardized normalizer led to the use of varied strategies for miRNA normalization, ranging from the use of spike-in controls (Sewer et al, 2014) like cel-miR-39 (Smith et al, 2020) to the employment of multiple endogenous miRNAs and their arithmetic means (Pagacz et al, 2020), as well as the pair ratio method (Lekchnov et al, 2018) or study specific normalizers (Jain et al, 2023, Veryaskina et al, 2022), raising questions about the comparability and reliability of results across studies.…”