ERgene: Python library for screening endogenous reference genes

In gene expression analysis, sample differences and experimental operation differences are common, but sometimes, these differences will cause serious errors to the results or even make the results meaningless. Finding suitable internal reference genes efficiently to eliminate errors is a challenge. Aside from the need for high efficiency, there is no package for screening endogenous genes available in Python. Here, we introduce ERgene, a Python library for screening endogenous reference genes. It has extremely high computational efficiency and simple operation steps. The principle is based on the inverse process of the internal reference method, and the robust matrix block operation makes the selection of internal reference genes faster than any other method.

Human Circulating miRNAs Real-time qRT-PCR-based Analysis: An Overview of Endogenous Reference Genes Used for Data Normalization

miRNAs are small non-coding RNAs of about 18–25 nucleotides that negatively regulate gene expression at the post-transcriptional level. It was reported that a deregulation of their expression patterns correlates to the onset and progression of various diseases. Recently, these molecules have been identified in a great plethora of biological fluids, and have also been proposed as potential diagnostic and prognostic biomarkers. Actually, real time quantitative polymerase chain reaction is the most widely used approach for circulating miRNAs (c-miRNAs) expression profiling. Nevertheless, the debate on the choice of the most suitable endogenous reference genes for c-miRNAs expression levels normalization is still open. In this regard, numerous research groups are focusing their efforts upon identifying specific, highly stable, endogenous c-mRNAs. The aim of this review is to provide an overview on the reference genes currently used in the study of various pathologies, offering to researchers the opportunity to select the appropriate molecules for c-miRNA levels normalization, when their choosing is based upon literature data.

Validation of endogenous reference genes in rat cerebral cortex for RT-qPCR analyses in developmental toxicity studies

Relative gene expression data obtained from quantitative RT-PCR (RT-qPCR) experiments are dependent on appropriate normalization to represent true values. It is common to use constitutively expressed endogenous reference genes (RGs) for normalization, but for this strategy to be valid the RGs must be stably expressed across all the tested samples. Here, we have tested 10 common RGs for their expression stability in cerebral cortex from young rats after in utero exposure to thyroid hormone (TH) disrupting compounds. We found that all 10 RGs were stable according to the three algorithms geNorm, NormFinder and BestKeeper. The downstream target gene Pvalb was significantly downregulated in brains from young rats after in utero exposure to propylthiouracil (PTU), a medicinal drug inhibiting TH synthesis. Similar results were obtained regardless of which of the 10 RGs was used for normalization. Another potential gene affected by developmental TH disruption, Dio2, was either not affected, or significantly upregulated about 1.4-fold, depending on which RG was used for normalization. This highlights the importance of carefully selecting correct RGs for normalization and to take into account the sensitivity of the RT-qPCR method when reporting on changes to gene expression that are less than 1.5-fold. For future studies examining relative gene expression in rat cerebral cortex under toxicological conditions, we recommend using a combination of either Rps18/Rpl13a or Rps18/Ubc for normalization, but also continuously monitor any potential regulation of the RGs themselves following alterations to study protocols.