A comparative assessment of reference genes in mouse brown adipocyte differentiation and thermogenesis in vitro.

Adipogenic differentiation and thermogenesis in brown adipose tissue (BAT) undergo dynamic processes, altering phenotypes and gene expressions. Proper reference genes in gene expression analysis are crucial to mitigate experimental variances and ensure PCR efficacy. Unreliable reference genes can lead to erroneous gene expression quantification, resulting in data misinterpretation. This study focused on identifying suitable reference genes for mouse brown adipocyte research, utilizing brown adipocytes from the Ucp1-luciferase ThermoMouse model. Comparative analysis of gene expression data under adipogenesis and thermogenesis conditions was conducted, validating 13 housekeeping genes through various algorithms, including DeltaCq, BestKeeper, geNorm, Normfinder, and RefFinder. Tbp and Rer1 emerged as optimal references for Ucp1 and Pparg expression in brown adipogenesis, while Tbp and Ubc were ideal for the expression analysis of these target genes in thermogenesis. Conversely, certain conventional references, including Actb, Tubb5, and Gapdh, proved unstable as reference genes under both conditions. These findings stress the critical consideration of reference gene selection in gene expression analysis within specific biological systems to ensure accurate conclusions.

pcr: an R package for quality assessment, analysis and testing of qPCR data.

BACKGROUND: Real-time quantitative PCR (qPCR) is a broadly used technique in the biomedical research. Currently, few different analysis models are used to determine the quality of data and to quantify the mRNA level across the experimental conditions. METHODS: We developed an R package to implement methods for quality assessment, analysis and testing qPCR data for statistical significance. Double Delta CT and standard curve models were implemented to quantify the relative expression of target genes from CT in standard qPCR control-group experiments. In addition, calculation of amplification efficiency and curves from serial dilution qPCR experiments are used to assess the quality of the data. Finally, two-group testing and linear models were used to test for significance of the difference in expression control groups and conditions of interest. RESULTS: Using two datasets from qPCR experiments, we applied different quality assessment, analysis and statistical testing in the pcr package and compared the results to the original published articles. The final relative expression values from the different models, as well as the intermediary outputs, were checked against the expected results in the original papers and were found to be accurate and reliable. CONCLUSION: The pcr package provides an intuitive and unified interface for its main functions to allow biologist to perform all necessary steps of qPCR analysis and produce graphs in a uniform way.