Normalizing RT-qPCR Data: Are We Getting the Right Answers? An Appraisal of Normalization Approaches and Internal Reference Genes from a Case Study in the Finfish Lates calcarifer

摘要

Commonly used normalization approaches for quantitative reverse transcription polymerase chain reaction analyses include (a) input nucleic acids standardization (Delta C (q) method), (b) normalizing target gene transcript abundance against a single internal reference gene (Delta Delta C (q) method), and (c) geometric averaging of multiple reference gene abundance using the geNorm software. We compared these three approaches to examine expression of a negative muscle growth regulator gene, myostatin-I (mstn-I), in the finfish Lates calcarifer, following 4 weeks of nutritional fasting. Interestingly, these three different approaches led to widely divergent data interpretations. When Delta C (q) and subsequently Delta Delta C (q) with alpha-tub as the reference gene were applied to mstn-I expression data, an similar to threefold upregulation of this gene was observed in fasted compared to fed fish. In contrast, mstn-I appeared unchanged when data was normalized against the geometric average of the two apparently most "stable" reference genes (elongation factor-1 alpha (ef1-alpha) and rpl8) selected from a panel comprising seven commonly utilized candidate reference genes (18S, cat-D, ef1-alpha, rpl8, gapdh, ubq, and alpha-tub). The geNorm software erroneously suggested that ef1-alpha, rpl8, and ubq were the most "stable" reference genes, whereas Delta C (q) analysis revealed these genes simply to exhibit similar patterns of regulation in response to fasting. The Delta C (q) approach showed that alpha-tub was the least variable in its expression level between fasted and fed fish after 4 weeks. The present study also highlights the importance of validating internal references for each time point under investigation when applying Delta Delta C (q) and suggests that the more cost-effective Delta C (q) normalization approach, if carefully applied, may in fact produce the most biologically valid results.