Usual normalization strategies for gene expression studies impair the detection and analysis of circadian patterns

Recent studies have shown that transcriptomes from different tissues present circadian oscillations. Therefore, the endogenous variation of total RNA should be considered as a potential bias in circadian studies of gene expression. However, normalization strategies generally include the equalization of total RNA concentration between samples prior to cDNA synthesis. Moreover, endogenous housekeeping genes (HKGs) frequently used for data normalization may exhibit circadian variation and distort experimental results if not detected or considered. In this study, we controlled experimental conditions from the amount of initial brain tissue samples through extraction steps, cDNA synthesis, and quantitative real time PCR (qPCR) to demonstrate a circadian oscillation of total RNA concentration. We also identified that the normalization of the RNA’s yield affected the rhythmic profiles of different genes, including Per1-2 and Bmal1. Five widely used HKGs (Actb, Eif2a, Gapdh, Hprt1, and B2m) also presented rhythmic variations not detected by geNorm algorithm. In addition, the analysis of exogenous microRNAs (Cel-miR-54 and Cel-miR-39) spiked during RNA extraction suggests that the yield was affected by total RNA concentration, which may impact circadian studies of small RNAs. The results indicate that the approach of tissue normalization without total RNA equalization prior to cDNA synthesis can avoid bias from endogenous broad variations in transcript levels. Also, the circadian analysis of 2^{−Cycle threshold (Ct)} data, without HKGs, may be an alternative for chronobiological studies under controlled experimental conditions.