Quantitative PCR is used in transcriptome analysis. Hence, PCR services offering bioanalytical testing, such as ADA assays, are focused on qPCR and ddPCR assays. ddPCR analysis is an advanced version of qPCR assays where each reaction volume is divided into thousands of droplets, each having a target sequence. However, qPCR CROs are often dependent on reference genes for qPCR analysis. 

The accuracy of qPCR expression analysis largely depends on reliable transcript normalization through stably expressed genes called references. Researchers have developed statistical algorithms for validating reference genes. However, these approaches are underutilized. Instead, housekeeping genes are used increasingly as references without adequate validation. Hence, normalization is critical for accurate and reliable qPCR expression analysis. The current article discusses crucial considerations for normalization in qPCR expression analysis. 

Normalization in qPCR expression analysis 

The amount of a specific compound in a study sample largely depends on the sample size. Hence, before comparing samples, researchers should normalize the quantified study compounds for every sample to consider variations in the compound quantity. Usually, normalization consists of dividing the measured amount by the quantity of material in the study sample. However, this process is different in gene expression analysis. 

Gene expression analysis includes quantifying specific mRNA molecules with similar chemical constituents to other mRNA molecules, which differ only in RNA sequences. Besides, the transcriptional activity among tissues is highly variable, and hence, basing normalization simply on the starting material amount is not possible. Instead, mRNA species are normalized based on the total mRNA quantity present in the sample. As all mRNA have the same variations in the starting material and quantification efficiency, the target gene quantification can be normalized efficiently through the ratio of target mRNA and total mRNA. In conclusion, reliable normalization of such mRNA analysis depends on accurate and reliable evaluation of total mRNA quantity in the study sample. 

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The normalization approach for qPCR analysis differs from Northern blotting and microarray assays. The primary reason for this difference is that enzymatic reaction efficiency impacts the detected signals and hence, needs to be evaluated in qPCR normalization. In qPCR analysis, the target gene expression level is normalized to the reference gene expression levels. This reference gene is representative of the cyclic DNA in each sample, and it is subjected to similar issues faced during cyclic DNA preparation and the target gene. 

qPCR analysis has several applications because it can detect the target transcript in low abundance with very high sensitivity and specificity. qPCR has higher specificity than Northern blotting analysis because of the high temperatures applied during the annealing process in the PCR reaction. On the other hand, high sensitivity is due to the exponential nature of PCR experiments that enables the detection of specific sequences in study samples even when a few copies are present in the sample. However, using highly robust and reliable reference genes is crucial for normalizing the results of qPCR analysis. 

In Conclusion

QPCR expression analysis has increasingly been applied to detect and quantify mRNA expression levels. However, effective normalization is the key to robust qPCR expression analysis.