RNA-Seq is not required to determine stable reference genes for qPCR normalization

Assessment of differential gene expression by qPCR is heavily influenced by the choice of reference genes. Although numerous statistical approaches have been proposed to determine the best reference genes, they can give rise to conflicting results depending on experimental conditions. Hence, recent studies propose the use of RNA-Seq to identify stable genes followed by the application of different statistical approaches to determine the best set of reference genes for qPCR data normalization. In this study, we demonstrate that the statistical approach to determine the best reference genes from randomly selected candidates is more important than the preselection of ‘stable’ candidates from RNA-Seq data. Using a qPCR data normalization workflow that we have previously established; we show that qPCR data normalization using randomly chosen conventional reference genes renders the same results as stable reference genes selected from RNA-Seq data. We validated these observations in two distinct cross-sectional experimental conditions involving human iPSC derived microglial cells and mouse sciatic nerves. These results taken together show that given a robust statistical approach for reference gene selection, stable genes selected from RNA-Seq data do not offer any significant advantage over commonly used reference genes for normalizing qPCR assays.

Appropriate Reference Genes for RT-qPCR Normalization in Various Organs of Anemone Flaccida Fr. Schmidt at Different Growing Stages

Anemone flaccida Fr. Schmidt is a traditional medicinal herb in southwestern China and has multiple pharmacological effects on bruise injuries and rheumatoid arthritis (RA). A new drug with a good curative effect on RA has recently been developed from the extract of A. flaccida rhizomes, of which the main medicinal ingredients are triterpenoid saponins. Due to excessive exploitation, the wild population has been scarce and endangered in a few of its natural habitats and research on the cultivation of the plant commenced. Studies on the gene expressions related to the biosynthesis of triterpenoid saponins are not only helpful for understanding the effects of environmental factors on the medicinal ingredient accumulations but also necessary for monitoring the herb quality of the cultivated plants. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) as a sensitive and powerful technique has been widely used to detect gene expression across tissues in plants at different stages; however, its accuracy and reliability depend largely on the reference gene selection. In this study, the expressions of 10 candidate reference genes were evaluated in various organs of the wild and cultivated plants at different stages, using the algorithms of geNorm, NormFinder and BestKeeper, respectively. The purpose of this study was to identify the suitable reference genes for RT-qPCR detection in A. flaccida. The results showed that two reference genes were sufficient for RT-qPCR data normalization in A. flaccida. PUBQ and ETIF1a can be used as suitable reference genes in most organs at various stages because of their expression stabilitywhereas the PUBQ and EF1Α genes were desirable in the rhizomes of the plant at the vegetative stage.

Identification and Validation of Reference Genes in Clostridium beijerinckii NRRL B-598 for RT-qPCR Using RNA-Seq Data

Gene expression analysis through reverse transcription-quantitative real-time polymerase chain reaction (RT-qPCR) depends on correct data normalization by reference genes with stable expression. Although Clostridium beijerinckii NRRL B-598 is a promising Gram-positive bacterium for the industrial production of biobutanol, validated reference genes have not yet been reported. In this study, we selected 160 genes with stable expression based on an RNA sequencing (RNA-Seq) data analysis, and among them, seven genes (zmp, rpoB1, rsmB, greA, rpoB2, topB2, and rimO) were selected for experimental validation by RT-qPCR and gene ontology (GO) enrichment analysis. According to statistical analyses, zmp and greA were the most stable and suitable reference genes for RT-qPCR normalization. Furthermore, our methodology can be useful for selection of the reference genes in other strains of C. beijerinckii and it also suggests that the RNA-Seq data can be used for the initial selection of novel reference genes, however, their validation is required.

Selecting suitable reference genes for qPCR normalization: a comprehensive analysis in MCF-7 breast cancer cell line

Background MCF-7 breast cancer cell line is undoubtedly amongst the most extensively studied patient-derived research models, providing pivotal results that have over the decades translated to constantly improving patient care. Many research groups, have previously identified suitable reference genes for qPCR normalization in MCF-7 cell line. However, over the course of identification of suitable reference genes, a comparative analysis comprising these genes together in a single study has not been reported. Furthermore, the expression dynamics of these reference genes within sub-clones cultured over multiple passages (p) has attracted limited attention from research groups. Therefore, we investigated the expression dynamics of 12 previously suggested reference genes within two sub-clones (culture A1 and A2) cultured identically over multiple passages. Additionally, the effect of nutrient stress on reference gene expression was examined to postulate an evidence-based recommendation of the least variable reference genes that could be employed in future gene expression studies. Results The analysis revealed the presence of differential reference gene expression within the sub-clones of MCF-7. In culture A1, GAPDH-CCSER2 were identified as the least variable reference genes while for culture A2, GAPDH-RNA28S were identified. However, upon validation using genes of interest, both these pairs were found to be unsuitable control pairs. Normalization of AURKA and KRT19 with triplet pair GAPDH-CCSER2-PCBP1 yielded successful results. The triplet also proved its capability to handle variations arising from nutrient stress. Conclusions The variance in expression behavior amongst sub-clones highlights the potential need for exercising caution while selecting reference genes for MCF-7. GAPDH-CCSER2-PCBP1 triplet offers a reliable alternative to otherwise traditionally used internal controls for optimizing intra- and inter-assay gene expression differences. Furthermore, we suggest avoiding the use of ACTB, GAPDH and PGK1 as single internal controls.

Selecting Suitable Reference Genes for qPCR Normalization: A Comprehensive Analysis in MCF-7 Breast Cancer Cell Line

BackgroundMCF-7 breast cancer cell line is undoubtedly amongst the most extensively studied patient-derived research models, providing pivotal results that have over the decades translated to constantly improving patient care. Many research groups, have previously identified suitable reference genes for qPCR normalization in MCF-7 cell line. However, over the course of identification of suitable reference genes, a comparative analysis comprising these genes together in a single study have not been reported. Furthermore, the expression dynamics of these reference genes within sub-clones cultured over multiple passages (p) has attracted limited attention from research groups. Therefore, we investigated the expression dynamics of 12 previously suggested reference genes within two sub-clones (culture A1 and A2) cultured identically over multiple passages. Additionally, the effect of nutrient stress on reference gene expression was examined to devise an evidence-based recommendation of the least variable reference genes that could be employed in future gene expression studies.ResultsThe analysis revealed the presence of differential reference gene expression within the sub-clones of MCF-7. In culture A1, GAPDH-CCSER2 were identified as the least variable reference gene pair while for culture A2, GAPDH-RNA28S was identified. However, upon validation using genes of interest, both these pairs were found to be unsuitable control pairs. Normalization of AURKA and KRT19 with triplet pair GAPDH-PCBP1-CCSER2 yielded successful results. The triplet also proved its capability to handle variations arising from nutrient stress.ConclusionsThe variance in expression behavior amongst sub-clones highlights the potential need for exercising caution while selecting reference genes for MCF-7. GAPDH-PCBP1-CCSER2 triplet offers a reliable alternative to otherwise traditionally used internal controls for optimizing intra- and inter-assay gene expression differences. Furthermore, we suggest avoiding the use of ACTB, GAPDH and PGK1 as single internal controls.